Introduction 

The field of science uses observations from the natural world to comprehend the explanations and procedures behind every event. This perspective implies the interconnectedness between psychology and neuroscience. While psychology focuses on numerous unique mental processes and human behaviors from various subfields, such as cognition and development, neuroscience aims to record the complex communication and activity occurring throughout the brain and nervous system that is vital to produce certain behavioral phenomena. The action or behavior in particular that I will further investigate with reference to the described domains is reinforcement learning. One way to think about reinforcement learning is that it helps to understand that we continue to implement the same choice or shift towards another based on varied outcomes or rewards. In other words, the consequences of each trial could alter our predictions and decision-making. Computational models of reinforcement learning are developed, simulated, and fitted into real-world data to test hypotheses of cognition. A multitude of activity occurs in many corners of the nervous system that needs to be deciphered to describe the findings about each area of the brain and how they are interdependent with reinforcement learning. Two essential foundations that can help us further perceive reinforcement learning is classical and operant/instrumental conditioning.

Psychology of Reinforcement Learning 

Classical Conditioning 

A neutral stimulus is an event that does not reveal a specific response, while an unconditioned stimulus (US) results in an automatic reply known as the unconditioned response (UR). Suppose the transition from the neutral to the unconditioned occurs multiple times, and the two stimuli are associated or easily predicted in the agent’s mind. In that case, it will produce the same response as the unconditioned called the conditioned response (CR) for the neutral stimulus. Therefore, the neutral stimulus is now referred to as a conditioned stimulus (CS) (Rehman, Mahabadi, Sanvictores, & Rehman, 2022). Key terminologies are integral to further recognizing the behaviors involved in classical conditioning. Giving the same CR to things the subject perceives as similar to the CS is known as stimulus generalization. In contrast, stimulus discrimination is when the participant is aware of the differences between the conditioned and other stimuli and responds to each separately. If the US less frequently appears after the conditioned, the CR is slowly removed within our system; this is defined as extinction . However, if the US is suddenly presented after CS, that specific classical conditioning scenario is reactivated; this describes spontaneous recovery (Rehman, Mahabadi, Sanvictores, & Rehman, 2022). Studies that have contributed to understanding this form of learning are Pavlov’s work and the Little Albert Experiment. Classical conditioning directs our awareness of the role of predictions in reinforcement learning. 

Operant Conditioning 

The effects of certain activities can improve or build new behaviors by guiding agents towards redoing an action or slowly avoiding it. There are a couple of paths to dive into, so one can further grasp the details of this kind of learning. The most common form of operant conditioning is positive reinforcement. This involves receiving a reward or positive reinforcer that increases the behavior recently implemented. On the other hand, negative reinforcement explains that relieving oneself from something undesired also strengthens the willingness to continue that behavior. However, positive and negative punishment describes a different process. Positive punishment is when the subject receives an additional burden, while negative punishment removes something pleasant, most likely directing them to decrease that action gradually (McLeod, 2018). It is also necessary to inform that not earning a reward after a given task has been achieved can also lead to weaker performance of that activity in the future. B.F. Skinner was a renowned psychologist during his time and even today. His theories and experiments using the operant chamber/Skinner box contributed significantly towards understanding a key component of human behavior. The study of operant conditioning relating to reinforcement learning has shown that our aim toward earning more rewards follows the development of strategies. 

Reward Prediction Error and Rescorla Wagner 

An integral point of reinforcement learning is that continuous implementation of a task and realizing where one can go wrong in the procedure can slowly guide us towards making decisions to get the best possible reward. Classical conditioning can help us relate to the components of reinforcement learning, from prediction errors to values. What learning in the form of behaviors and ideas arises from classical conditioning? As mentioned earlier, agents could predict that an unconditioned stimulus will come after the conditioned; therefore, they were prepared beforehand by presenting a conditioned response. Similarly, in reinforcement learning, the amount of reward anticipation can support decision-making. This ability comes through experience by observing different trials and their results (Daw & Tobler, 2014). Initially, we develop an expected value, the reward anticipated if one selected a particular option. However, it could also be zero because the subject might be doing the activity or game for the first time without experience or expectations. This leads the participant to plan and carry out decisions, and an outcome is reached, leading to the prediction error. The prediction error computes the gap between the expected value and the actual amount of reward. This is similar to Ivan Pavlov’s observations, where a dog has a high expectation of receiving a treat after the bell (the conditioned stimulus) and either receives or doesn’t, except it doesn’t make a choice unlike reinforcement learning. Prediction Error is divided into two parts: positive and negative prediction error. Prediction Error is summarized with a mathematical formula where r is the reward after choice k at trial t between 0 and 1.(Wilson & Collins, 2019)

The learning rate determines the weight or how seriously the participant takes the prediction error. It is represented through the alpha parameter, α, where a quantity of 0 simplifies that regardless of how far or close the prediction error might seem, the value of a choice would be constant. However, if the learning rate is initially set to 1, the value is fully updated based on the previous outcome. Given the input of the expected value, prediction, error, and learning rate, a result is the updated value. This type of reinforcement learning is called Rescorla Wagner. Its mathematical explanation is given below, where V at t (the previous trial) is the expected value and V at t+1(the next trial) is the updated value. (Wilson & Collins, 2019)

Finally, Rescorla Wagner is another kind of learning through reward by changing the values of certain options based on the result. This can guide us towards making better choices that could reach optimization. 

Temporal Difference Learning 

Sutton and Barto were two renowned scientists of the 20th century that developed Temporal Difference (TD) learning in response to different observations about the Rescorla Wagner Model. For example, the theory perceived that time goes through single and set periods called trials where the expected value of options is updated. It also concluded that signals could anticipate that different events could arrive. Finally, the model could also continue to compute the weight of past events or choices. However, some limitations of the Rescorla Wagner theory are essential to be aware of. It did not capture the major goal of learning processes Sutton and Barto formulated. They expressed that learning directs the value of events or selections in the future but not in the past, even though past occurrences can lead to these future values. Emphasizing future values, we should change how we approach reward prediction error. To reiterate, prediction error calculates the difference between the expected value or the average of the values of each trial from the past up to some point and the resulting reward. However, to rephrase it for this context, we should describe it as the gap between future expectations of rewards based on logic and reasoning and the predictive stimuli and reward (Glimcher, 2011). This shows that prediction error and learning can occur not only after the trial but also at the point when the predictive stimuli were present or the time before the final reward. Rescorla Wagner was also not able to explain that even though there is a strong association between a stimulus and a resulting reward, that stimulus that reappears in the future can’t help when it comes to learning new things. Another point to remember is that time is constantly moving in reality compared to trials, indicating that there could be complexity in the environment, and many different things can occur. Therefore, Sutton and Barto developed a reinforcement learning theory where there are moments that are the building blocks of one trial. Additionally, they stated that learning happens not only after the trial but also at these moments. In fact, there are expectations of reward for each moment that can be represented as values and give us a total. Predicted rewards for every moment are derived by the sum of the value of the reward of a moment and the discounted reward for each of the following moments. The discounted reward is further broken down into the product of the value of the reward of one of the next moments and the discount parameter that decreases that value and measures the satisfaction of faster than slower rewards (Glimcher, 2011). This detail is simplified into a mathematical equation below where we assume that there are 50 moments. 

γ -> discount parameter 

V -> expectation of reward for 1st moment 

r -> reward

A stimulus repetitively predicts a reward, but one is not perplexed about the reward because of the previous appearance of the stimulus. The reward relates not only with the value of the reward moment but also the value of the recent moments till the stimulus. In other words, the change of value due to the reward can be traced back to the moments of the stimulus. The many details above explain the overview of temporal difference learning. 

Neuroscience of Reinforcement Learning 

The Role of Dopamine 

Psychologists Olds and Milner started an experiment to understand reward and the behaviors connected by setting electrodes into different areas of a rat’s brain. They directed the rat towards turning a lever, which led to a transfer of electricity and the action potential of many neurons. Action potential involves electrical charges passing through an axon surrounded by a neuron’s membrane. This helped the rat learn the lever procedure to reinforce it with the same or a higher reward(Schultz, 2016). The experiment gave the idea that events in the brain or nervous system play a vital role in the emphasis of reward, stimuli, and the behaviors that are influenced through it. Some parts of the brain where the electrodes were placed had dopamine neurons, which reveals the strong relationship between these cells and rewards.

Dopamine is a neurotransmitter that functions at its best when we accomplish a goal or are highly motivated. Dopamine or dopaminergic neurons have these chemicals found in the midbrain, whose axons connect parts of the brain, such as the amygdala and prefrontal cortex. The action potentials of these neurons are initiated when one receives a reward; as the reward becomes greater, the dopamine response strengthens. The dopamine response also activates when one observes stimuli that anticipate future rewards. These neurons store information about past and future rewards, guiding us when planning and making choices. It is important to note that the activity of dopamine responses during conditioned stimuli is not as much as the actual reward. Dopamine neurons can comprehend past actions through conditioned stimuli and clarify a long chain of events. 

Although positive and negative reward prediction errors weren’t mentioned above, they will be defined here because of their strong relationship with dopamine responses. A positive reward prediction error is when our expectations are exceeded because of a higher reward. Dopamine responses are strengthened, which is known as positive dopamine response or activation, during this experience. On the other hand, a negative reward prediction error occurs when the resulting reward does not meet our expectations; therefore, the dopamine response is depressed or decreases. Finally, an outcome that comes as expected tells that there is no prediction error and dopamine response. One helpful idea to remember is that of Temporal Discounting, which describes that the further the time between the conditioned stimuli and reward, the weight of the reward decreases, as well as the dopamine response. Prediction errors compared with full awareness help us to understand the environment around us efficiently and save processing (Schultz, 2016). 

Suppose a group of people gain a reward higher than predicted and the dopamine response is highly active, their anticipation could increase based on the resulting reward, and they would be accustomed to it. If they receive the same reward in the future, there would be no prediction error and dopamine response because of that previous update. However, if a positive prediction error (increasing rewards) dopamine response continues to occur, our desire for escalating reward improves regardless of what we have. This illustrates that dopamine activity increases when someone comes across a reward, which would bring forth new learning and behavior.

We take a look at the environment around us, including rewards, undesired results, and neutral stimuli. We try to find something that stands out, and our neurons are aware of it quickly. Once we have noticed that an object has the property of salience, this procedure known as initial nonselective response leaves very soon. The subsequent process, known as the second selective response, involves processing reward detail even before we realize it is a reward. This gives us time to approach the reward when we know about it(Schultz, 2016). The overall procedure explained in detail above is known as careful analysis. These are essential parts of a dopamine response whenever a reward, stimuli, or reward prediction error is present. 

Synopsis 

Using psychological terms and detail, we were able to explore reinforcement learning behavior and the important role of predictions and rewards through the perspectives of conditioning such as classical and instrumental and value learning such as rescorla-wagner and temporal difference. Mathematical equations were also included to illustrate and summarize the detailed learning processes; therefore, the field of mathematics is also another interdisciplinary pathway to understand different behavioral and cognitive processes. We also reviewed experiments that created the foundation and realization that biological and neurological processes place an important role in scientifically observable behaviors, especially of that related to reward. The action potential of dopamine neurons and dopamine response surges when one comes across anticipations and reward is another component that we looked into detail about. This relates to the summer project I did that dealt with building computational models and analyzing the parameters that best fit the data, which helps formulate and test cognitive and reinforcement learning processes. The combination of findings based on the research paper and computational modeling exercises establishes the intricate and profound connectivity between psychology and neuroscience when it comes to understanding reinforcement learning. 

References

Rehman, I., & Mahabadi, N., & Sanvictores, T., & Rehman, C.  (2022). Classical Conditioning. Retrieved from National Center for Biotechnology Information. 

McLeod, S.  (2018). Skinner – Operant Conditioning. Retrieved from Simply Psychology. 

Daw, N., & Tobler, P.  (2014). Chapter 15 – Value Learning through Reinforcement: The Basics of Dopamine and Reinforcement Learning. Retrieved from ScienceDirect. 

Wilson, R., & Collins, A.  (2019). Ten simple rules for the computational modeling of behavioral data. Retrieved from eLife. 

Glimcher, P.  (2011). Understanding dopamine and reinforcement learning: The dopamine reward prediction error hypothesis. Retrieved from Proceedings of the National Academy of Sciences. 

Schultz, W.  (2016). Dopamine reward prediction error coding. Retrieved from PubMed Central.

About the author

Srikrishna Ammu

Srikrishna Ammu is currently a first-year student at Boston University majoring in Neuroscience. He is interested in studying the field to discover the biological processes behind human behavioral phenomena and to create strong connections with related fields such as Chemistry and Artificial Intelligence. Krishna also reads different scientific articles to learn about the latest advancements in Neuroscience and Medicine. He worked on a research project that involved utilizing Matlab software to investigate reinforcement learning further. His hobbies include playing tennis, chess, and the piano, and he volunteers at a hospital during his free time to explore the medical field.

The post Reinforcement Learning and its Connections with Psychology and Neuroscience appeared first on Exploratio Journal.

Abstract

Many treatments and therapies have been developed for treating cancer; however, these treatments suffer from serious side effects. Cancer vaccines are an innovation which manipulates the patient’s own immune system to specifically target their own cancer.  The development of such therapies is critical in curing and preventing cancer. Tremendous research on cancer vaccines have been conducted over years, and several cancer specific vaccines have been approved by FDA since 1990. Even though an effective and universal cancer vaccine for all cancers does not currently exist, the recent progress on driver antigen cancer vaccines and targeted immunotherapy including CAR T-cell therapy and checkpoint inhibitor therapy show great promise. This review analyzes the feasibility of cancer vaccines and reviews some of the most recent advancements in this field.

Introduction

Cancer is a detrimental disease that has been recorded in humans as early as 1500 BCE. While there are plenty of treatment options for cancer patients, to this day no universal cure has been discovered. In 2021, more than 10 million people succumbed to cancer, with estimates of even more deaths in 2022. [28] Without any significant cure for this disease, millions of more lives will be taken each year. Cancer research is important as it helps doctors identify, cure, and prevent cancer, allowing people around the globe to have safer, longer, and higher quality lives. By understanding the biological processes of cancer, researchers can identify patterns which assist in developing ways to protect people from developing cancer and treating cancer patients. This will ultimately result in decreased occurrences of cancer and mortality. With the help of the research funding (USD 6.4 billion in 2020 alone), there have been many breakthroughs in cancer treatment. [2] One of these breakthroughs is called targeted immunotherapy, which is also known as the cancer vaccine. [3] This therapy uses the patient’s own immune system to destroy cancer. Although no complete cure has been fully developed, these cancer vaccines have been heavily researched and are used in patients. With cancer vaccines being one of the most prominent and potential cures to cancer in the future, this review briefly discusses the effects, processes, and results of cancer vaccines.

What is Cancer?

Cancer is a disease caused by an uncontrolled division of abnormal cells in parts of the body. There are many types of cancers such as breast, lung, colon, skin cancer, etc. As of 2022, breast cancer is the most common cancer in the US [12] whereas lung cancer is the most common cancer in China. [13] Statistics show that about 60% of people who are diagnosed with metastatic breast cancer also develop lesions in the lungs. [26] Metastatic cancers are when cancerous cells spread to another part of the body, which is commonly found in breast, colon, kidney, lung, among other cancers. An example of the metastasis can be seen in kidney cancer, where the cancer spreads to adrenal gland, bone, brain, liver, and lung. 

Although cancer can develop and spread to different organs within the body, they share some similar symptoms such as fatigue, weight loss or gain, swelling, unusual bleeding or bruising, headaches, among many other symptoms. [34] The most severe symptoms usually are experienced by bone and pancreatic cancer patients. [33]

In figure one, it shows that patients that are diagnosed with brain cancer usually have the lowest 5-year survival rates (12.8%) whereas testis cancer has the higher survival rate (97%) in England. [9] Interestingly, some cancer patients can live with their cancer as long as they continue treatment such as melanoma, breast, prostate, testicular, cervical, and thyroid cancer patients as the 5-year survival rates are highest.

It is scientifically accepted that the universal cause of cancer is damage to genetic material i.e. DNA. Chemical disruption of the nucleotides that hold the DNA chains together results in genetic mutations once the DNA replicates itself. Loss or rearrangement of these nucleotides alters the genetic information contained in the DNA i.e. mutations. As can be seen in figure two, double strand breaks can also cause rearrangement of the chromosome structure, which could disrupt a gene and ultimately lead to mutation(s). However, these mutations can be avoided if the DNA repair system recognizes the DNA damage as abnormal structures and repairs it before the round of replication. [15] Alterations in DNA sequence result with improper cell cycle maintenance and functions. The sequence of DNA is important for expressing critical proteins in and on the cells of the body. When the sequence changes, that directly impacts the function of these proteins. Depending on where this damage occurs and which protein is affected, the function of the cell changes and can lead to developing cancerous cells. 

There are a few exogenous factors that may cause DNA damage, and eventually cancer. These include lifestyle habits, such as, but not limited to, smoking, unhealthy diet, or exposure to toxic chemicals. DNA damage resulting from continuous smoking increases the chances for developing lung cancer, which can then spread to other parts of the body. [23] An unhealthy diet could lead a patient into obesity, which is a risk factor for various cancers such as colon, breast, kidney, etc. Maintaining a healthy body weight and also reducing alcohol intake can lower the risk of developing these cancers. [7] Exposure to heavy metals such as cadmium, arsenic, and nickel [18] (from factories or industrial productions), asbestos (aging and unmaintained buildings), and ultraviolet light (from the sun) can also cause damage to DNA in cells, leading to various cancers. There are many dangerous carcinogens such as PAH, N-nitrosamines, aromatic amines, 1,3-butadiene, benzene, aldehydes, and ethylene oxide which can cause damage to DNA.  These carcinogens can be found in natural resources such as UV Light or viruses, or man-made waste like automobile fumes and cigarette smoke, and can cause mutations to the DNA, increasing the likelihood of cancer diseases. Some cancers can also be hereditary where one or both parents carry altered genes and carry that on to their offspring(s). Most common hereditary cancers are breast and colon. [37]

The main effect cancer has on the body is weakening of the immune system. For example, leukemia, lymphomas, and multiple myelomas spread into the bone marrow, outcompeting with the bone marrow cells for space and nutrients. [42] When this happens, the bone marrow won’t be able to generate white blood cells to fight infections in the body. Without a strong immune system, there is no protection against illnesses, leaving patients very vulnerable to other diseases. Not only do blood cancers affect the immune system, but also solid tumors. A tumor is a solid mass of tissue consisting of abnormal cell groups. Solid tumors grow on bones (sarcoma), skin (melanoma), lung (carcinoma), and other organs and glands. Malignant cells from the tumors avoid immune elimination through loss of antigenicity (ability to interact with immune cells and antibodies) and/or loss of immunogenicity (ability to provoke immune response). [24] The degree to which the tumor overrides the immune system on tumor type and lesion. 

Many treatments have been developed to help cure or slow the progression of cancer. The most common treatments include surgery, chemotherapy, and radiation. [27] Surgery is the physical removal of a solid tumor/mass from the patient. Side effects of surgery include blood clots, bleeding, infections, damage of other organs, and reaction to drugs. [32] Chemotherapy is the use of drugs to kill cancer cells. Chemotherapy has negative side effects in which the immune system becomes weak, and infections are more probable. This is because chemotherapy is meant to kill fast growing cells, but they could also accidently affect healthy cells that are also fast growing. Radiation therapy uses x-rays, particles, or radioactive seeds to destroy the cancer. Radiation slows down the abnormal growth rate of the cancer cells. Side effects of radiation include fatigue, hair loss, memory or concentration problems, nausea, skin changes, and blurry vision. Most recently, targeted immunotherapy has been developed and considered to be the “cancer vaccine” for patients. This therapy focuses on using a person’s own immune system to fight cancer. The most prominent immunotherapies use CAR T-cell therapy and checkpoint inhibitors to fuel the production of cancer fighting cells to attack cancer cells. [41]

What Are Vaccines?

A vaccine is a substance used to stimulate the production of antibodies to provide long term immunity against a disease. The most common types of vaccines are live-attenuated vaccines, inactivated vaccines, and toxoid vaccines. Live-attenuated vaccines are created by using a weakened form of germ that causes the disease. These vaccines are similar to the natural infection, so it provides a strong and long lasting immune response. A limitation to this type of vaccine is people with weak immune systems, chronic health problems, and organ transplant recipients may not be eligible to receive such vaccines. Live-attenuated vaccines are used for various diseases including measles, rotavirus, smallpox, chickenpox, and yellow fever. 

Inactivated vaccines use the deactivated version of the germ that causes the disease. The inactivated vaccines are not as strong or long lasting as the live-attenuated vaccines. This type of vaccine is a safer alternative for those with weak immune systems and chronic health problems since they are weaker than the live-attenuated vaccines. Booster shots are required for inactivated vaccines to ensure that the patient gets longer immunity against diseases. Inactivated vaccines are used for hepatitis A, flu, polio, and rabies. Toxoid vaccines use a toxin made by the germ that causes the disease. It creates immunity against the germs that cause the disease, but not the disease itself. Similar to the inactivated vaccine, it also requires booster shots for an ongoing immunity against diseases. Toxoid vaccines are used to protect against diphtheria and tetanus. [40]

With the outbreak of the COVID-19 pandemic, a new type of vaccine has been developed and globally used to prevent the spread of this deadly virus and maintain the lives of billions. These vaccines are mRNA based, which means inactivated regions of proteins from the virus are genetically encoded to be expressed on the surface of healthy cells. Once these proteins are detected by the immune cells, an immune response is generated. The main difference compared to the vaccine types above is that these proteins remain on the surface of the cells as long as the cells are in the body. [29] This method has been researched for more than a decade but has only been used in humans since the pandemic outbreak. Given that this technology is still in its infancy, there are many areas of development to increase the efficiency and longevity of mRNA vaccines.

Innovating Vaccines against Cancer

Cancer has always seemed to be the greatest enigmas of the modern day as no universal cure has been developed. The idea of a cancer vaccine – not a direct cure, but a prevention against cancer – is an absolute breakthrough as it has the potential to drastically decrease the mortality and infection of cancer throughout the globe. Unlike the types of vaccine mentioned in the last section, cancer vaccines take advantage of proteins found in or on cancer cells. [41]

The progress to the current cancer vaccines in early trials has come a long way. Immunotherapy was first developed in 1891 by William Coley, also known as the “father of immunotherapy.” Coley attempted to leverage the immune system through injecting patients with bacteria or bacterial products. His belief was that forcefully activating the immune system will generate a response against inoperable cancers. While his approach was not entirely understood or accepted by professionals and healthcare providers at the time, he was able to treat about 1000 cases of bone and soft-tissue sarcoma where patients’ tumors decreased in size after being injected with these inactivated bacteria. These short lived, “immunotherapy” injections were referred to as Coley Toxins. [39]

About a century later, the first FDA approved cancer vaccine (1990) was BCG (Bacillus Calmette-Guérin) which uses a weakened strain of TB (tuberculosis) bacteria, and it triggers the immune system to protect against the infection that results in early-stage bladder cancer.  [6, 10] A second FDA approved cancer vaccine (2010) is the Sipuleucel-T, which is an autologous cellular immunotherapy used for patients with metastatic castration-resistant prostate cancer (mCRPC). The vaccine activates the multiplication of immune cells and attacks prostate cancer cells using an antigen (one or more proteins on the surface of cancer cells that induce an immune response), that is highly specific to prostate cancer. [16, 8] A third FDA (2015) approved cancer vaccine is called T-VEC (Talimogene laherparepvec). T-VEC is an immunotherapy for treatment of melanoma skin cancer. T-VEC is made with a weakened version of herpesvirus in which it can break down cancer cells without affecting normal cells. Unlike other cancer vaccines, T-VEC is injected directly into the tumor. [38]

While two of the three cancer vaccines mentioned primarily function on established tumors/cancers, the more traditional way of thinking about vaccines is to prevent the disease from occuring. Since cancer is a genetic-based disease for the most part, this has been the greatest challenge in developing immune-shields against cancer. However, there are some “traditional” vaccines that immunize against viruses known to be linked to development of cancer. Epstein-Barr virus (EBV) is linked to nasopharyngeal cancer, stomach cancer, and Bukitt/Hodgkin lymphoma. The EBV vaccine targets EBV glycoprotein gp350, which is found in the virus and on virus infected cells. Gp350 is the main target for neutralizing antibodies in the body and causes cells to target a specific antigen. [31] Human papillomavirus (HPV) causes most cervical cancers including vulva, vagina, penis, anus, and oropharynx cancer. [5] The HPV vaccine is a non-infectious recombinant vaccine that stimulates the body to produce antibodies. These antibodies bind to specific parts of the HPV and signal to the immune cells to destroy these virus particles, preventing viral infection. Hepatitis B virus (HBV) causes chronic hepatitis, liver cirrhosis, and hepatocellular carcinoma. [21] The HBV vaccine is also a recombinant vaccine and it work by causing the body to produce its own antibodies against the disease. [20,19] Human herpes virus (HSV) has been linked to cause cervical cancer. [22] While there aren’t any approved vaccines against HSV, there is a potential mRNA-based vaccine that is being studied to prevent HSV. The concept of this vaccine is to provide a strong antibody response and drive immune cells to kill HSV particles. [30, 14]

Many years of commitment have been put into developing immune cell-based therapies. Although there were many obstacles in developing and implementing this therapy, immune cells that were engineered to treat cancer called CAR T cells (approved by the FDA in 2017 and created by Novartis) were discovered. CAR T cells, also known as chimeric antigen receptor T cells, have been implemented in cancer treatment including lymphomas, leukemia, and myelomas. CAR T-cells are referred to as a living drug as they orchestrate the immune system and directly kill pathogenic cells. Immune T cells are harvested from patients and are customized for each patient. This results with highly engineered CAR T cells that can recognize and bind to specific proteins or antigens on the patient’s own cancer cells prompting their elimination. These T cells are customized because normal T cells are incapable of binding to these antigens. Once these cells are injected, they are directed towards cancer cells that express the antigen the CAR is designed to target. One major drawback is that since cancer cells are abnormal human cells, these antigens are sometimes expressed on healthy cells leading to off-target toxic effects. Not only are CAR T cells referred to as a cancer therapy, but they can also be considered a vaccine because the cells remain in circulation and proliferate inside the patient, potentially protecting against any recurrence of the cancer. [11]

In 2022, researchers believe they have found another viable cancer vaccine based on positive clinical trial results. Olivera Finn, a professor of immunology at the University of Pittsburgh was able to identify a colon tumor-specific antigen known as MUC1. Finn’s team was able to create a MUC1-based vaccine to help patients with premalignant colon polyps. This vaccine works by triggering an immune system response to attack the colon polyps. The vaccine reduced recurrence rates by 38% in the clinical trial, proving its effectiveness. Another example of the use of an antigen is the HER2, which is a protein found in about 25% of breast cancers. Knutson and Amy Degnim, who are breast surgeons at Mayo Clinic in Minnesota designed a HER2 vaccine used in a trial of 22 patients with invasive breast cancer. This vaccine is like the MUC1 vaccine where it targets the antigen, provokes the immune system, and kills cancer cells. The results were very promising, with only two recurrences after two years. [11] Although the timetable for a truly universal cancer vaccine is unclear, these examples of clinical trials show the potential of these vaccines to cure cancer, and how researchers are setting the stage to make cancer history. [1]

Conclusion

The most prominent method that researchers have been developing these cancer vaccines is using “driver” antigens, which acts as a target for the immune system. Although these cancer vaccines seem promising, a limitation is that tumors express an array of antigens that are also common in healthy cells, making it difficult for researchers to identify tumor-specific antigens. Cancer vaccines are not like live-attenuated or inactive vaccines where the germ is already placed in the body. Rather, they use these antigens to make the immune system purposely attack the tumors to prevent recurrence. Cellular immunotherapies introduce the least risk of toxic side effects since the cells are from the patient and they are engineered to target the cancer specifically. Similar to CAR-T therapy, researchers have developed CAR-macrophages (CAR-M) where these immune cells are also engineered in a similar manner to CAR-T cells. [17] However, a unique method to activate macrophage immune cells is to use antibodies, proteins and peptides to block interactions responsible for survival of the cancer cells and then only have activating signals against the cancer. [4] This is also known as checkpoint inhibitor therapy. Many breakthroughs along the studies of a cure for cancer have arisen recently, and it may just be a matter of a few years before the deadliest disease is eradicated. 

References

[1] (2022, June 14). Retrieved from https://www.washingtonpost.com/health/2022/06/14/cancer-vaccine-future/

[2] 2021 NCI budget fact book – Research funding. (n.d.). Retrieved from https://www.cancer.gov/about-nci/budget/fact-book/data/research-funding

[3] 5 Oncology Breakthroughs to be Excited About in 2022. (2022, May 11). Retrieved from https://www.cityofhope.org/breakthroughs/5-oncology-breakthroughs-to-be-excited-about-in-2022

[4] Activated macrophages in the tumour microenvironment – dancing to the tune of TLR and NF-κb. (n.d.). Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2935674/

[5] Basic information about HPV and cancer. (2021, December 14). Retrieved from https://www.cdc.gov/cancer/hpv/basic_info/

[6] BCG vaccine for tuberculosis (TB) overview. (2019, 31). Retrieved from https://www.nhs.uk/conditions/vaccinations/bcg-tuberculosis-tb-vaccine/

[7] Cancer and food. (n.d.). Retrieved from https://www.betterhealth.vic.gov.au/health/conditionsandtreatments/cancer-and-food

[8] Cancer, C. C. (n.d.). Sipuleucel-T – Chemotherapy drugs – Chemocare. Retrieved from https://chemocare.com/chemotherapy/drug-info/SipuleucelT.aspx

[9] Cancer survival rates. (2022, June 29). Retrieved from https://www.nuffieldtrust.org.uk/resource/cancer-survival-rates

[10] Cancer vaccines: Preventive, therapeutic, personalized. (n.d.). Retrieved from https://www.cancerresearch.org/en-us/immunotherapy/treatment-types/cancer-vaccines

[11] CAR T cells: Engineering immune cells to treat cancer. (2022, March 10). Retrieved from https://www.cancer.gov/about-cancer/treatment/research/car-t-cells

[12] Common cancer types. (2022, May 10). Retrieved from https://www.cancer.gov/types/common-cancers

[13] Comparison of cancer incidence between China and the USA. (n.d.). Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3643656/

[14] Developments in vaccination for herpes simplex virus. (n.d.). Retrieved from https://www.frontiersin.org/articles/10.3389/fmicb.2021.798927/full

[15] DNA damage, DNA repair and cancer. (n.d.). Retrieved from https://www.intechopen.com/chapters/43929

[16] Factors associated with use of Sipuleucel-T to treat patients with advanced prostate cancer. (n.d.). Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6481456/

[17] First-in-Human trial with CAR macrophages shows the cell therapy may be safe, feasible for solid tumors – Penn medicine. (n.d.). Retrieved from https://www.pennmedicine.org/news/news-releases/2022/january/first-in-human-trial-with-car-macrophages-shows-the-cell-therapy-safe-feasible-for-solid-tumors

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About the author

Jonathan Lu

Jonathan Lu is a senior at the Concordia International School in Shanghai, China. Jonathan has a passion for Physics, Materials Science, Chemistry, Engineering, Biology, and all things basketball. In the paper, Jonathan analyzes the development of cancer vaccines and immunotherapy.

The post Cancer Vaccines: The Advancement of Immunotherapy appeared first on Exploratio Journal.

Introduction

Patellofemoral injuries occur when the structures that join the kneecap with the femur are injured, stressed, or torn. Many times, these injuries stem from underlying patellar instability which then contributes to symptoms including but not restricted to anterior knee pain and patellar subluxation/dislocation. It is important to understand that this type of injury is seen with specific mechanisms of injury, many of which involve a jumping motion and the subsequent landing or repeated stress, such as running. This review will not only delve into the anatomy and etiology of patellofemoral pain syndrome (PFPS), but also discuss the treatment and rehabilitation associated with it as well.

Pathology/Anatomy:

Overall, patellofemoral pain syndrome is an overarching term regarding pain in any of the structures that compose the joint and the surrounding tissues and ligaments (Physiopedia 1). This joint consists of the bony structures of the patella and the femur, along with, mainly, the lateral and medial collateral ligaments (LCL/MCL) and the lesser known epi condylopatellar, menisco patellar, medial patellofemoral, and lateral patellofemoral ligaments.

Additionally, there are also many bursae that are within this region in order to cushion the impact the knee experiences (Physiopedia 1). The patella is the largest sesamoid bone in the human body, and is roughly shaped like an upside down triangle. It has 2 main facets in the back and a vertical ridge in between that divides the two. These two facets line up with the condyles of the femur, and the lateral condyle is deeper than the medial in order to compensate for the more severe stress and pull on this side than the other (Physiopedia 2). Along with the bony structures, the ligaments are the other part of the static system in this joint. The MCL and LCL are important stabilizers of this joint and both originate from the femur. However, the MCL inserts at the tibial head, whereas the LCL inserts at the fibular head. These ligaments counteract lateral stresses on the knee, but are also subject to rupture if they are subject to excessive valgus or varus force. In addition to these structures, The Medial Patellofemoral Ligament (MPFL) and the Lateral Patellofemoral Ligament (LPFL) also contribute to the stability of the patellar bone itself. Each originate at their respective femoral condyles and insert at the medial and lateral sides of the patella. The MPFL provides a medial force to keep the patella tracking the correct direction, and the LPFL does the same on its side (Physiopedia 2). If these ligaments are torn, lateral or medial subluxation or dislocation may be experienced. Lastly, the largest and strongest muscle of the joint is the quadriceps. This muscle extends the joint and is made of the rectus femoris and the vastus group. The vastus group is made of the vastus lateralis and the vastus oblique. The vastus lateralis helps with patellar tracking and the vastus oblique stabilizes the patella against lateral force.

Etiology/Mechanism

With Patellofemoral Injury being a blanket term, there are numerous causes and injuries that may stem from this. One cause of patellofemoral pain is the orientation of the bone itself that induces improper tracking which then leads to instability (Physiopedia 1). Moreover, if there is an imbalance in muscular strength, this can also contribute to the pain as one side is being pulled more than the other. Another cause of the syndrome is flat feet which can cause the knee to fall inwards. The lack of foot arch leads to the foot falling flat which then causes the knee to also follow suit and become valgus rather than its normal line up (Han,Y. et.al. 2017). Some common stresses that also contribute to this variety of injury are running, jumping, and other repeated impact-type stresses (Shubin Stein et.al. 2016, Oct.). Additionally, patellofemoral pain syndrome is more seen in women rather than men. This is due to women standing and squatting in more valgus positions than men and this contributes to uneven stress distribution (Shubin Stein et.al. 2016, Oct.).

Signs and Symptoms

Many times, the signs and symptoms are the cause of the problem itself; for example, a symptom such as flat feet could be a sign of patellofemoral pain, but it is also a cause of it. Some symptoms that follow a similar pattern are weak quadriceps (or portion of the quads), tight iliotibial band, tight hamstrings, weak or tight hip muscles, and tight calf muscles (Physiopedia 1). All of these cause an imbalance in how the knee is pulled, which then contributes to the pain that follows. Moreover, certain activities may aggravate the pain, such as running, jumping, and squatting. The patient may also present with pain when going up and down stairs, bending their knees, and lunging; popping or crackling noises may be heard when standing up from a sitting position or when ascending stairs (Mulcahey et.al. 2020).

Treatment

NON-SURGICAL:

Simple changes, such as activity substitution could help with relieving the pain, and avoiding activities that are known to aggravate the injury can also work, depending on the severity of the pain. Low impact activities, such as riding a bike or swimming could substitute high impact ones. The RICE method (rest, ice, elevation, compression) can also assist in relieving pain as it will bring down inflammation to the joint. Anti-inflammatory medications, such as NSAIDs can also be taken to remediate symptoms (Mulcahey et.al. 2020). Additionally, physical therapy can be done to strengthen the surrounding structures of the knee, improve range of motion, and build endurance. Lastly, orthotics can be worn in shoes to help with flat feet and provide an arch to the foot so that the knee does not fall into valgus. These can be purchased at a store or online, or they can be custom made to fit what the patient specifically needs (Mulcahey et.al. 2020).

SURGICAL:

Surgical treatments are used conservatively, and only in instances when it is absolutely needed. Most of the surgical options are performed arthroscopically, where small incisions are made as needed and small tools, along with the assistance of a camera, are used rather than opening up the whole knee. This results in less scarring in the future after healing. Some instances where surgical intervention is needed is for cartilage debridement or if the patient has experienced multiple subluxations or dislocation of the patella, in which case a MPFL reconstruction may be needed (Shubin Stein et.al. 2016, June).

Rehabilitation

Rehab for this injury mostly consists of quadriceps strengthening and stretching, along with surrounding muscles. Some stretches that are commonly implemented include calf wall stretch, standing quad stretch, and lying hamstring wall stretch (Healthwise Staff). Some strengthening exercises done include, but are not limited to quad sets, where the affected knee is placed on a rolled towel and quads are tightened by pushing the knee into the towel, lying straight leg raises to the front and back, and wall assisted squats (Healthwise Staff). Rehab for these injuries can take anywhere from 4-7 months if it is surgical, but much of the time, these rehab exercises need to be completed consistently over an indefinite period of time, especially if the injury is non-surgical. Ultimately, the exercises will help remediate the imbalance and can help with pain.

Prevention

The prevention of patellofemoral pain syndrome is essentially the goal of the rehab program for it. Strengthening the quadriceps and making sure that any imbalances are taken care of is extremely important in this case. Wearing the right shoes, doing low impact exercises, cross training to take the load off the knee, and being aware of what causes symptoms and what does not is also extremely important. Studies have also shown that certain taping techniques, when used in conjunction with strengthening exercises, can assist in pain relief and recovery from PFPS (Logan et.a. 2017).

Conclusion

Over the course of this review, patellofemoral pain syndrome was discussed in great detail. Throughout this joint, there are many structures that comprise it, mainly the patellar bone, the femur, and various ligaments and muscle groups. PFPS can be the result of any one of these structures being injured, but the method of injury is quite common between them. Oftentimes, it is high impact activities that instigate the pain, and this syndrome is seen more in women than men. There are many ways of treatment, rehabilitation, and prevention of injury, all ranging from basic strength work to surgery. Overall, to maintain a healthy patellofemoral joint, it is important to gauge activity, be aware of what causes pain, and be proactive in how that pain is managed or treated.

References

Kujala, U M et al. “Scoring of patellofemoral disorders.” Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association vol. 9,2 (1993): 159-63. doi:10.1016/s0749-8063(05)80366-4

(1) Patellofemoral Pain Syndrome. (2022, February 28). Physiopedia, . Retrieved 13:48, May 13, 2022 from https://www.physio-pedia.com/index.php?title=Patellofemoral_Pain_Syndrome&oldid=295866.

Loudon J. K. (2016). BIOMECHANICS AND PATHOMECHANICS OF THE PATELLOFEMORAL JOINT. International journal of sports physical therapy, 11(6), 820–830.

(2) Patellofemoral Joint. (2022, February 28). Physiopedia, . Retrieved 16:46, May 14, 2022 from https://www.physio-pedia.com/index.php?title=Patellofemoral_Joint&oldid=295861.

Shubin Stein, B. E., & Strickland, S. M. (2016, October 26). Patellofemoral Disorders: An Overview. Hospital for Special Surgery. Retrieved May 14, 2022, from https://www.hss.edu/conditions_patellofemoral-disorders-overview.asp

Han, Y., Duan, D., Zhao, K., Wang, X., Ouyang, L., & Liu, G. (2017). Investigation of the Relationship Between Flatfoot and Patellar Subluxation in Adolescents. The Journal of foot and ankle surgery : official publication of the American College of Foot and Ankle Surgeons, 56(1), 15–18.

Mulcahey, M. M., Hettrich, C. M., & Liechti, D. (2020, October). Patellofemoral Pain Syndrome.OrthoInfo. Retrieved May 14, 2022, from https://orthoinfo.aaos.org/en/diseases–conditions/patellofemoral-pain-syndrome/

Shubin Stein, B. E., & Strickland, S. M. (2016, June 27). Medial Patellofemoral Ligament (MPFL) Reconstruction. Hospital for Special Surgery. Retrieved May 14, 2022, from https://www.hss.edu/conditions_medial-patellofemoral-ligament-reconstruction-mpfl.asp

Healthwise Staff. (2021, July 1). Patellofemoral Pain Syndrome (Runner’s Knee): Exercises. Alberta Healthcare. Retrieved May 14, 2022, from https://myhealth.alberta.ca/Health/aftercareinformation/pages/conditions.aspx?hwid=bo1601

Logan, C. A., Bhashyam, A. R., Tisosky, A. J., Haber, D. B., Jorgensen, A., Roy, A., & Provencher, M. T. (2017). Systematic Review of the Effect of Taping Techniques on Patellofemoral Pain Syndrome. Sports health, 9(5), 456–461. https://doi.org/10.1177/1941738117710938

Diagram of the patellofemroal structures of the knee joint, including the patella (kneecap). [Image]. (n.d.). Hospital for Special Surgery. https://www.hss.edu/ condition-list_patellofemoral-disorders.asp

About the author

Rishya Gutti

Rishya is currently a junior at Neuqua Valley High School. She interested in the biological sciences and is an aspiring medical student. Research programs like RISE (Research, Inquiry Skills & Experimentation) have equipped Rishya with the necessary skills to conduct independent research. She is a third degree black belt in Taekwondo and has won several national titles in her age group. Rishya enjoys volunteering her time to teach mathematics to younger students and to promote mental health awareness through a non-profit organization. In her free time, you will find her reading, working out or watching her favorite tv shows.

The post A Review on Patellofemoral Pain Syndrome (PFPS) appeared first on Exploratio Journal.

Abstract

Every person has two kidney organs responsible for filtering and cleaning fluid waste from the blood. Kidney disease occurs when one or both kidneys lose their ability to function properly. Patients are either placed on dialysis or receive kidney organ transplants in order to maintain their lives. We discuss in this brief review what some of the causes of kidney failure are and how to potentially prevent kidney failure. The process of receiving a kidney is also discussed along with the risks involved with such a procedure. While there are many precautionary measures taken before a patient receives a kidney, there have been significant improvements in the lives of patients once they receive a kidney. Survival rates have significantly increased with the advancement of medical procedures and treatments. Nevertheless, there are areas that can be further developed to increase the number of patients eligible for kidney transplants and to prevent deleterious side effects of drugs.

Introduction

A kidney transplant is a surgical procedure in which a diseased kidney is replaced with a healthy kidney from a donor. The kidneys are a pair of organs located on each side of the lower abdomen that function to remove waste and excess fluid from the body by producing urine. Although humans have two kidneys, they can survive with only one functioning kidney. As shown in Figure 1, kidney failure (end stage kidney renal disease) can result if a kidney loses its filtration ability and allows certain wastes and fluids to gather in the body. People that are diagnosed with end stage renal disease must have a kidney transplant or undergo dialysis, where a machine mechanically removes fluid wastes from the body, replacing the function of the diseased kidney(s), in order to survive (Mayo, 2022). Examples of kidney diseases include lupus nephritis and kidney cancer, all requiring a kidney transplant to prolong the survival of the patient for as long as possible (Rodgers, 2022). Patients who are eligible for a kidney transplant surgery have a higher chance of a longer life expectancy and overall better quality of life. A donated kidney can be transplanted from a relative, an unrelated donor, or a deceased donor. Based on the statistics of current surgeries, patients who receive a kidney from a live donor have experienced more benefits than patients who have received a kidney from a deceased donor who has passed (Thongprayoon et al., 2020).

The history of kidney transplants comes with many unsuccessful attempts of experimentation, but has ultimately persevered past these setbacks. The first ever human kidney transplant was performed in 1936 as an allograft (human-to-human). The transplanted kidney left an area of the ureter unattached and because organ rejection was not yet understood, the transplant ultimately failed (Turner, 2018). After improving on the methods of transplantation, the first successful human-to-human kidney transplant took place in 1954 between identical twins (Williams, 2008). Based on prior failed kidney transplant surgeries, the medical team speculated the fact that a kidney transplant with identical twins may be successful. Amazingly, the kidney was able to adjust to the body of the recipient because the organ did not appear “foreign” when transplanted into the body due to the fact that the identical twins shared many similar traits. Both patients survived for nine years without immunosuppressive therapy (to be discussed later) after undergoing this surgery (Dziewanowski et al., 2011). Shortly after, the first successful kidney transplant between unrelated individuals took place in 1962. These monumental results would soon become a breakthrough in medicine offering people a solution to such a chronic disease.

Kidney transplantation has now become an option to increase the rate of survival and life expectancy for kidney disease patients. Although there are advantages to having the procedure performed on patients, there are prerequisites, limitations and risks involved in undergoing such a procedure. Patients are first put on a waiting list as a candidate to receive a kidney from donors, but a shortage of organs available for donation makes it difficult for this process to occur quickly. During this waiting period, patients must be placed on dialysis until they are eligible to receive a kidney organ. Nonetheless, this operation is not fit for everyone. For example, people of older age with a history of cardiovascular conditions do not have the option to have a kidney transplant. Patients may also not be eligible for a kidney transplant if they have a history with drug or alcohol usage, an inability to take post-surgery medications, or no health insurance (Rodgers, 2018). Although there are many advantages to kidney transplantations such as fewer food restrictions and higher energy levels for work or travel, there are some considerations to having the operation done. The risks of a kidney transplant include possible infection, damage, or bleeding in the surrounding organs in the lower abdomen. After the surgery, the patient will be required to take strong medications for the rest of their lifetime to prevent organ rejection by lowering their immune system (Hendry & Robb, 2020). These medications come with many side effects such as a higher risk of infections and diseases like cancer. An example of a significant risk factor is the development of diabetes mellitus, which has been shown to be acquired by almost 70% of patients with a kidney transplant post transplantation (Peev et al., 2014). It is crucial for the patient to consider all of these factors before deciding whether the surgical procedure is the best option.

II. The Importance of Kidney Transplants

Kidney transplant surgeries are becoming more common as the number of kidney failures have dramatically increased over the years (Figure 2). This can be a result of common diseases such as diabetes, high blood pressure, and cardiovascular disease which all increase the likelihood of developing chronic kidney failure. Each single kidney is made up of over one million small filtering units known as nephrons. Any condition, such as those previously listed, that may damage or cause potential harm to the nephrons can result in kidney disease (Digital, 2020). There are approximately 1 in every 3 adults in the world that are diagnosed with a type of diabetes with 1 in every 3 diabetic also developing chronic kidney disease (Walensky, 2021). High levels of blood glucose that are a result of the diagnosis of diabetes damages blood vessels in the kidneys which clusters and limits the kidneys’ abilities to filter waste. Furthermore, hypertension and obesity rates are increasing and have also been causes of kidney failures. Roughly 23% of patients who are diagnosed with kidney disease are also obese, demonstrating the close gap between the two conditions (Tran et al., 2016). Being overweight forces the kidneys to perform extra work to maintain balance by filtering waste and removing excess fluids that may come in addition to the supplemental body fat (Kovesdy et al., 2017).

Although kidney transplantation is the most prominent option for prolonging the lifespan of a patient with a diseased kidney, the procedure is not as simple as it may seem. In the United States, there are over 3,000 new patients added to the kidney organ transplant list each month, making it extremely difficult to find and receive a kidney in a short period of time. There are at least thirteen people who die each day waiting for a kidney, and others are put on dialysis to rely on the machine until they find a matching donor (UNOS, 2016). There were more than 20,000 donor organs available for transplant in the United States in 2016, but more than 100,000 patients were on the waiting list to receive a transplant. Given the stringent requirements to qualify a patient to receive a kidney, not all donor kidneys can be transplanted thus increasing the number of donor organs at about 8% per year (USRD, 2020). As shown in Figure 2, the annual need for kidney transplants is significantly greater than any other organ transplant. Recent statistics show that there has been a record in both the number of total kidney transplant surgeries and also the number of lives saved in 2021. The number of living donors had substantially decreased in 2020 due to the outbreak of the COVID pandemic and although the number of living donors was slightly higher in 2021, the number was still significantly less as compared to previous years. There were more than 6,000 organ transplants performed in 2021, which was approximately 14% higher than in 2020. Note that from 2010 to 2020 the total number of transplants performed was about 7,000 (Figure 2). Because of the result of the recent pandemic, more kidneys have been donated from deceased donors in order to maintain the consistency of survival rates (UNOS, 2022).

Kidney transplants have significantly shown beneficial outcomes and significant improvements in the lives of patients. Because of how common kidney disease has become, the need for transplants only continues to grow. A living donor kidney survives on average anywhere from 12-20 years, whereas a diseased kidney organ survives around 8-12 years (BIDIC, 2022). Short term rejections (within 3 months of surgery) occured in about 17.3% of patients 10 years ago, but have significantly decreased to around 4% as of current statistics (Lee et al., 2021). Survival expectancy rates of kidney transplants ranged around 75% around 10 years ago (Walensky, 2021), but has risen up to around 94-97% as of 2022 (BIDIC, 2022). This is mainly due to the increasing number of successful surgeries every year. The improvement of national transplant statistics comes from the benefit of developing medicine and research.

The most common age group to develop both kidney diseases and receive transplants is between 50-64. Although more than 45,000 individuals in this age group were on waiting lists for a kidney in 2021, current improvements in medicine and transplant surgery have nevertheless given these people the potential to live longer with less complications (Elflein, 2021). Unfortunately, there are many food restrictions and physical limitations that all kidney disease patients endure while living on dialysis. Having a kidney transplant relieves these individuals from the restrictions put on their daily life, which thus allows them to live healthier and more comfortably (Lee et al., 2021). Kidney transplants help to save the lives of over 20,000 individuals (i.e. actual living recipients of kidneys and patients who match for a transplant) every year (UNOS, 2022).

II. The Types of Kidney Transplant Rejections

The immune system protects the body by identifying cell markers and recognizing the cells as being healthy or foreign. Lacking these markers sometimes prompts immune cells to attack the cells to destroy them. Individuals have a unique and different collection of cells in their immune system. Foreign cells are removed from the body in order to provide protection from possible infections, illnesses, or diseases (Waltzer, 2019). The most common examples of foreign invaders include bacteria, viruses, parasites, and fungi that the immune system works to remove from the body. Foreign cells can also be healthy cells but from different individuals. Receiving a kidney transplant is seen as foreign by the immune system because the entrance of new antigens (cell markers on donor cells) prompt an immune response in the recipient. The immune system then works to reject the kidney by removing cells and antibodies that may cause potential harm. Transplant recipients therefore take immunosuppressive (anti-rejection) drugs to prevent damage to the kidney. It is extremely crucial to take these medications at around the same time every day in order to avoid kidney rejection (Hendry & Robb, 2020).

One of the three main types of kidney rejection is hyperacute rejection, which occurs within the first couple minutes of the surgery. This occurrence is irreversible and immediately results in the loss of the transplanted kidney and must be removed from the body promptly. Hyperacute rejection is diagnosed when the patient experiences immediate symptoms after surgery. Diagnosing this type of rejection is not too difficult, and even a simple urine test can diagnose or predict a rejection. Hyperacute rejection is caused by already existing antibodies that recognize the foreign kidney and cells from the donor and act immediately to reject this outlier. Fortunately, hyperacute rejection has now become extremely rare due to a special test called a crossmatch, which is completed before the transplant takes place. Instead of having the patient undergo the entire procedure leading to the surgery just to find out there is no match present, there are now prerequisites that are done which can determine superficially that there will be no severe reaction with the kidney. The tissue cross match is used to check how the immune system of the recipient may act to the placement of the new donated kidney (KHSCN, 2019). A positive result of this crossmatch indicates that the antibodies of the recipient will attack those of the donor, thus making the kidney unsuitable for the transplant process. A negative result of a crossmatch implies that there is no reaction between the antibodies of the recipient and the donor, thus making the kidney suitable for the transplant (Smoot, 2021).

Acute rejection is the second and most common type of rejection that is prone to happen anytime, but most frequently occurs around the first three months post transplant surgery. About 15-25% of recipients who experience this type of rejection within their first three months of surgery (Czech, 2022). This is usually a significant cause of allograft dysfunction, which causes an increase in serum creatinine level and correlates to a decrease in glomerular filtration rates (Goldenberg et al., 2016). Symptoms that prompt the doctor to perform tests to further observe this condition include an elevated temperature, tenderness or pain over the kidney transplant, a rapid increase in blood pressure or body weight, or a sudden decrease in urine output (Czech, 2022). Although this rejection is possible to be reversed in most cases when treated early, it may also result in a negative impact on the long-term graft survival overall. There are many instances where failed kidneys are not able to regain their functions even with the use of maximal antirejection therapy (Goldenberg et al., 2016).

Lastly, chronic rejections occur when any of the alternate rejection processes never completely reconcile and they continue to occur over long periods of time. This type of rejection can also be a result of when immunosuppressants stop regulation in the immune system due to their side effects. Chronic rejections typically occur in the first six months after surgery. Transplanted kidneys that have chronic rejection are found to have developed scarring of the tissue and damage to the blood vessels (Punch, 2022). Chronic rejection most commonly occurs among patients that have not received a sufficient amount of immunosuppression or medication following the transplant surgery (Henry & Robb, 2020). Symptoms that most likely indicate the presence of a chronic rejection in a kidney transplant are similar to those for the acute rejection, but come at later stages because of the different time periods the varying types of rejections occur at. Because there are no early symptoms for chronic rejections, this type of rejection is also commonly diagnosed by changes in laboratory tests or possible kidney biopsies. Although there is no medication to reverse chronic rejection, the kidney is generally able to last for months after the diagnosis is made by the doctor (Waltzer, 2019).

IV. How to Have a Successful Kidney Transplant Surgery

As previously mentioned, there are many different symptoms that may indicate possible kidney failure and prompt a doctor to run a diagnostic test on the patient. However in order to prevent the occurrence of these symptoms of failure as best as possible, it is crucial that the kidney from the donor and the patient are the right match. The three main blood tests that are used to check this are blood typing, tissue typing, and cross matching (Center, 2022). Blood typing is the first test done to determine if the kidney donor and the recipient have compatible blood types, indicating whether or not the kidney can be potentially transplanted. The next test after passing the initial blood typing exam is the tissue typing test, which is accomplished through routine testing and short turn around testing (STAT). Blood is drawn from the inside of the cheeks to determine if the potential donor and the recipient have a compatible HLA or tissue type (Center, 2022). As briefly mentioned above, cross matching is the ultimate step before the kidney officially becomes approved to be a donor for the recipient. Samples of blood are taken from both the donor and the recipient, then the blood cells of the donor are mixed with the serum of the recipient. A negative crossmatch result indicates that there is no presence of antibodies attacking the donor while a positive result shows that the kidney is not suitable for donation (Smoot, 2021).

However in order to prevent rejection of the kidney after the transplant surgery is completed, doctors prescribe immunosuppressants to help the newly transferred kidney survive in the new recipient’s body. The immunosuppressants must be taken every day for the rest of the recipients’ lives to prevent harmful interactions between foreign antibodies that may cause serious damage. The dosage of the medication is adjusted because of the many side effects that also commonly occur among patients as a result of the immunosuppressants. The most common side effects are constant migraines, hair loss, high blood pressure, or nausea, which can all become a consequence of taking the medication every day (Kalluri, 2012). Prednisone, tacrolimus, cyclosporine, mycophenolate mofetil, imuran, rapamune are among the most commonly prescribed immunosuppressants. Because there is such a wide variety, most patients take a combination of around three of these listed drugs (Trotta, 2021). About 6 months to a year after the kidney transplant surgery is administered, the dosage of the immunosuppressants are usually lowered in order to prevent the presence of the common side effects.

Conclusion

Despite all the information that has been gathered on this topic of kidney transplants, there are still a few questions that have been left unclarified. For example, why do women have a slower overall progression to end stage renal kidney disease than men? There are always biological and systematic factors to consider, but it is unclear whether the rates of progression are due to different accesses to care or possibly the true differences in the severity of their diseases. Furthermore, why are there always more women donating their kidneys than men? This question also lacks a clear answer and there are so many unique possibilities ranging from risks of kidney disease, personal requests, cultural factors, and much more. There is always a vast difference between genders regarding their access to care for their conditions, but there is not necessarily enough data obtained to recognize the range of these differences.

Chronic kidney disease and end stage renal disease are both extremely common, but medicine has shown progress in decreasing the side effects as a result of these procedures. However, there is still plenty of work to be researched and done. Improvement on the medical and treatment front such as ongoing clinical trials for different cell therapies to minimize the side effects would be an example of a beneficial approach to take the next step in the research. Due to the deleterious side effects of immunosuppressant drugs, more focus has been drawn to immunotherapeutics and cellular therapies to use the body’s own immune system to suppress activated immune cells that target the transplanted organ. There are ongoing clinical trials as well as numerous research projects all aiming to develop breakthrough cellular therapies that are more natural to the body and potentially safer options than drugs.

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About the author

Emily Kim

Emily is currently a junior in the Academy for Medical Science and Technology at the Bergen County Academies High School. She is also a competitive nationally ranked swimmer and is looking to pursue medicine in the future.

The post Kidney Diseases and Transplants: Diagnosis, Procedure, and Prolongation appeared first on Exploratio Journal.

Abstract

From past times to recent times antibiotic resistance has emerged as a global threat. Antibiotic resistance has mainly affected the progress in health care, food industries and ultimately life expectancy. Almost all regions of the world are suffering from these antibiotic resistant diseases. This is mainly due to the movement of people, animals and goods across borders and countries. The emergence of different species of bacterium like Staphylococcus aureus, Enterococcus faecium, Streptococcus pyogenes, Staphylococcus pneumonia and more by adapting various defense mechanisms, has lead to the development of resistance towards antibiotics like Penicillin and Methicillin. This resistance is mainly caused by the presence of two important genes called mec-A that codes the PBP2a protein. mec-A and PBP2a are known to confer resistance, but the mechanism of resistance remains unclear. Further study of the mechanism has the potential to develop a new generation of antibiotics. Here, we have investigated the structural biology basis of PBP2a antibiotic resistance and the contribution of the genetic background of resistant S. aureus strains. It has been found that PBP2a confers resistance through its Ser403 residue in its active site, but that PBP2a is not sufficient to drive resistance. Genetic studies have identified an additional gene responsible for conferring PBP2a-based resistance, that is the bla gene that codes a beta lactamase. The presence of bla genes along with mec-A is important for effective activity of the PBP2a protein, as the presence of mec-A alone showed insufficient activity of the PBP2a protein. Western blot analysis of PBP2a expression in different S. aureus strains determined, that the concentration of PBP2a protein was high in cells containing plasmids that carried both mec-A and bla genes and low concentration of PBP2a was found in cells containing plasmids carrying only the mec-A gene.

Introduction

Antibiotic resistance is a property where a bacteria becomes resistant to antibiotics that are designed to kill them. Bacteria can escape inhibitory effects of drugs by acquiring certain mechanisms of resistance. There are several problems that are caused due to the persistent increase in the antibacterial resistance in bacteria. Antibiotic resistance occurs naturally by random mutations (Julin Davis and Dorothy Davis, 2010) through the process of natural selection and also can occur by selective pressure on the bacterial population (Alfredo Tello, et al. 2012). If a resistant gene is generated, it can be transferred from one strain to another by exchange of plasmids through horizontal gene transfer (HGT). During this process of acquiring resistance the antibiotics act as environmental pressure, due to which bacteria undergo certain mutations for its survival. When such strains proliferate, they produce progeny that are resistant towards various antibiotics by evolving certain resistance mechanisms.

Over usage of antibiotics, usage of broad spectrum antibiotics, incorrect diagnostics, unwanted prescription, wrong usage of antibiotics by patients and use of antibiotics in cattle feed for enhancing early growth, are mainly responsible for antibiotic resistance. It was discovered that the lexA gene is mostly responsible for these mutations (Charlie Ye Mo, 2016). A bacteria called Staphylococcus aureus is one of the major resistant pathogens, which is responsible for causing various diseases. Later on it became known as MRSA that was first detected in Britain in 1961, which is resistant to the methicillin antibiotic. Later in 1991, 4% of fatal cases of infections were recorded and rose to 37% by 1999 in the UK. In the USA 50% of the Staphylococcus aureus were resistant to tetracycline, penicillin, methicillin and erythromycin. Vancomycin used to be an effective drug at that period for Staphylococcus aureus but in the late 1990’s intermediate strains were detected with moderate resistance to Vancomycin at 4 μg/ml, which was named Vancomycin intermediate Staphylococcus aureus. In Japan in 1996 the first case was identified with a strain which is resistant to Vamcomycin at >16 μg/ml and the second case was found in the USA in 2002 (Susana Gardete and Alexander Tomasz, 2014 july).

In the late 1990’s new antibiotics like oxazolidinone and linezolid were found to be effective against MRSA. In 2003 Staphylococcus aureus resistance to linezolid was observed. CA-MRSA, community acquired MRSA, is the most common antimicrobial drug resistant pathogen found in US hospitals and became part of Endemic infections at that time. Along with MRSA there are other bacterial strains that are found to have resistance including Enterococcus faecium (penicillin resistant), in 1983, (vancomycin resistant) Enterococcus in 1987 and linezolid resistant Enterococcus in the late 1990’s. However group A Streptococcus pyogenes remained sensitive to penicillin. Later penicillin resistant Staphylococcus pneumonia emerged worldwide. The main gene responsible for beta lactamase and penicillin resistance is mec-A which encodes PBP2a proteins.

There are several problems caused by increasing antibiotic resistance that have become a major threat in various sectors including health, food, security, clinical sectors, agricultural sectors, It is most commonly prevalent among frontline workers like military officers, hospital staff and patients. It can affect anyone of any age, gender and any country. It occurs naturally, but misuse of antibiotics in humans and animals accelerate this process. Due to antibiotic resistance, the effectiveness of antibiotics is decreasing. As a result, it is becoming difficult to treat various diseases including pneumonia, tuberculosis, gonorrhea and salmonellosis.It leads to higher medical costs, longer hospital stays and increased mortality. Plasmids are one of the major important vectors which are responsible for spreading resistance among the strains in soil in agroecosystems. PBR3222 is one such resistant plasmid which carries genes for tetracycline and ampicillin resistance. HGT is one of the most common mechanisms by which bacteria either acquire or exchange resistance from other bacteria. Mobile genetic elements (MGE) like integrons (which are gene cassettes) usually carry antibiotic resistant genes to bacterial plasmids and transposons. Most of this resistance is due to the presence of certain proteins and genes, mainly the mecA gene which was originated from coagulase negative Staphylococci and is associated with a mobile genetic element called Staphylococcal chromosomal cassette mec (secmec) and integrates in the Staphylococcal chromosome. mecA encodes for the PBP2a protein, which is a transpeptidase and has a low affinity for beta lactam antibiotics like methicillin and tetracycline. PBP2a being a transpeptidase is involved in the continuous synthesis of the cell wall during antibiotic attack. PBP2d protein along with beta lactamases are mainly responsible for the broad spectrum resistance in MRSA.

Discussion

The genes mec-A for the PBP2a protein and bla gene for beta lactamases are mainly responsible for resistance in bacteria like MRSA. To know the mechanism behind the resistance and to study the location and properties of the active site, the study of crystalline structures of PBP2a is very important (Lim and colleagues, 2002). For the crystallization process, cells were grown on m9 medium to which 50 g of protein solution containing thr, leu, met, selenomethionine were added per liter of culture. After 15 minutes, protein expression was induced and the colonies were subjected to further purification by hydrophobic affinity chromatography and gel filtration exchange chromatography by adding 0.1% thiodiglycol. Cells were lysed and native Staphylococcus aureus (Sau) PBP2a was extracted as a soluble protein by a purification process using a hydroxyapatite column.

Further purification was done by gel filtration chromatography on a sepharyle 1000 column apparatus, which is equilibrated with 5 mM NaHCO3. Extraction of PBP2a was carried out using a hanging drop vapour diffusion method. Then, exposure of PBP2a with chemical compounds like NaCl, PEG and HEPES at pH 7 led to the formation of crystals and the crystals were extracted by a cryopreservation technique in which the N terminal anchor of PBP2a was replaced with a methionine and was observed under electrospray mass spectrometry. When beta lactams are introduced, they inhibit beta lactam sensitive PBP’s. Strains containing PBP2a have low affinity for beta lactams, conferring antibiotic resistance by the continuous synthesis of the cell wall, which prevents the cell from lysis. Beta lactam antibiotics like penicillin and methicillin are substrate analogs of PBPs and catalyze the process of cell wall lysis and eventually lead to death. However,acquisition of mec-A genes by MRSA confers resistance. The mec-A gene is highly conserved among MRSA isolates with > 90% sequence identity and encodes the PBP2a protein. This PBP2a is resistant to beta lactam and does not have any sensitive analogs or homologs. It has a large molecular mass of 78 kD and belongs to class B PBPs which usually have broad spectrum for methicillin and other beta lactam antibiotics. This study on the crystal structure of PBP2a reveals the structural features responsible for its beta lactam resistance and provides important insights for the design of novel antibiotics against MRSA. Sau PBP2a has a transmembrane anchor which can be removed for the studying of beta lactam binding kinetics without affecting the beta lactam activity. The soluble derivative residues of PBP2a were determined by MAD method (Mean Absolute Deviation) using selenomethionine substituted protein. The extraction of this molecule has revealed structural conformations of the PBP2a protein and the location of active sites present within the non penicillin binding domain in the PBP2a. The active site along with the serine 403 at the N terminal helix of the alpha2 fold of Sau PBP2a along with a conserved oxidation hole containing serine 403 and Thr 600 as a nitrogenous backbone.During the acylation of beta lactam, the serine active site is mostly responsible for the process of inducing resistance towards the antibiotic. However, continuous acylation of serine molecules leads to dehydration. And may result in decreasing the activity of the active site, resulting in cell lysis and death. In order to make this process continuous, the serine 403 associated with the N terminal end of lys 406, present in beta lactam carboxylate enzyme. This forms hydrogen bonds, thus helping the serine present in the active site undergo deacylation, to further continue the process of cell wall protection by nucleophilic attack during the resistance mechanism.

This serine-lysine bond promotes the PBP2a conformational change, thus providing unfavourable conditions for the antibiotic to attack the complex. The low affinity binding towards the beta lactam induces slow acylation, leading to a rate limiting step responsible for the beta lactam resistance in MRSA. In normal methicillin sensitive PBPs, higher acylation rates are one of the major reasons for the antibiotic sensitivity and lead to cell death.

Location and function of the mec-A gene

The mec-A gene is located on a mobile chromosomal cassette called secmec. In this paper (Katayama, et al. 2003), use of naive cells (strains without mec-A genes) and experienced hosts (methicillin susceptible strains in which mec-A was excised) was mainly done to demonstrate the expression of mec-A genes and PBP2a protein activity towards the beta lactam resistance. A plasmid called pYK-20 was used as a carrier for the mec-A gene and was introduced into experienced and naive strains. The excision of this mec-A gene from the methicillin resistant strain was done by CC5-1, CC5-2 restriction enzymes and were introduced into the different vector plasmids like pYK-644, pYK-20, Hind 3, Coln plasmid, pNR-5542 and pCN-2278 and some of the plasmids were introduced with both mec-A and bla genes. These plasmids were amplified using PCR and these plasmids were introduced into naive hosts and experienced hosts through the process of micropropagation and growth curves were measured to screen for the transformants containing the plasmid vectors. These cells were grown on nafcillin containing media to test for antibiotic resistance. Naive cells containing the plasmids that carried only mec genes showed weak growth of 2.5% and the naive cells containing plasmids which are introduced with both mec-A and bla genes showed resistance to nafcillin. Transformed experienced strains showed normal resistance as that of parents containing mec-A genes. Taken together, these experiments suggest resistance is driven by transformants containing the plasmids with both mec-A genes and bla genes, indicating that combined activity of mec-A and bla are required for resistance. As, the experienced strains showed resistance and the naive cells did not express due to the host barrier. Tranformants were then tested to analyse the expression of the PBP2a protein by western blot. After the electrophoresis separation the separated proteins are loaded onto the nitrocellulose membrane containing monoclonal anti PBP2a antibodies. The desired PBP2a proteins bind with the antibodies. After the washing the unwanted proteins are removed. The secondary labelled antibodies are introduced and bind to the desired protein-antibody complex and develop colour and the PBP2a are visualised as thick bands depending upon the concentration under autoradiography. It was observed that Colnex with pYK 20 showed the maximum PBP2a production indicating high resistance, containing a plasmid carrying both mec and bla genes.

Conclusion

Both PBP2a and beta Lactamases are important for antibiotic resistance, and the structural confirmation of Ser403 present in the active site of the PBP2a protein is most important to confer proper and effective resistance towards the antibiotics. As in the studies we observed that the cells with plasmids carrying both mec and bla genes showed more resistance than cells with plasmids containing a single gene. What this suggests is although PBP2a is required for antibiotic resistance, it is not sufficient to induce resistance. In fact, additional genes such as bla are also required to induce resistance. More studies and research on new antibiotics targeting Ser403 and the active site of PBP2a, possibly designing new antibiotics towards PBP2a and designing antibiotics that target bla gene products would be effective. Combinatorial antibiotic treatment targeting both PBP2a and bla may help in effective treatment towards these antibiotic resistant diseases.

References

Julin Davis and Dorothy Davis, September 2010. Origins and Evolution of Antibiotic Resistance.Microbiol Mol Biol Rev. V 74(3): 417–433.

Alfredo Tello, Brain Austin and Trevor C Telfer, Aug 2012. Selective pressure of antibiotic pollution on bacteria of importance to public health. PubMed.

Charlie Ye Mo, January 2016. Make Antibiotics Great Again: Combating Drug Resistance By Targeting Lexa, A Regulator Of Bacterial Evolution. Researchgate.

Susana Gardete and Alexander Tomasz, Jul 1 2014. Mechanisms of vancomycin resistance in Staphylococcus aureus. The journal of clinical investigation, V 124(7): 2836–2840.

Daniel Lim and Natalie C. J. Strynadka, 21 October 2002. Structural basis for the -lactam resistance of PBP2a from methicillin-resistant Staphylococcus aureus. Nature structural biology, Volume 9: 870-876.

Yuki Katayama, Hong-Zhong Zhang, Dong Hong, and Henry F. Chambers, 23 June 2003. Jumping the Barrier to -Lactam Resistance in Staphylococcus aureus. JOURNAL OF BACTERIOLOGY, p. 5465–5472.

About the author

Harshini Balaga

The post Antibiotic resistance in Staphylococcus aureus and its adverse effects on global health appeared first on Exploratio Journal.

Abstract

Heart attacks, or Myocardial Infarctions (MI), lead to death of tissue due to lack of blood supply to the portion of the organ. Resulting scar tissue does not contract or function as well as healthy muscle tissue. On the other hand, stem cells have shown propensity to be guided into becoming specific cells that can be used to regenerate and repair diseased or damaged tissues in people. This paper will explore the latest research that supports using induced pluripotent stem cells for tissue reparation in cardiovascular disease.

Introduction

Over the past few decades, stem cell therapies have evolved considerably and one of their many potential applications could be to repair the scarring caused by myocardial infarctions. Myocardial Infarction (MI), which is a reduction or blockage of blood flow in the coronary arteries, commonly referred to as heart attack, is one of the leading causes of death in the United States with 805,000 people experiencing one every year (CDC). Unfortunately, out of those 805,000, 12% will die (CDC). Following MI, the inadequate blood flow to the infarcted tissue causes a severe reduction of oxygen and nutrients, leading to cardiomyocyte necrosis (reduced contractility), and therefore compromised heart function. MI does not traditionally have any treatment since once the tissue has necrotized, it can not regain its function. MI’s can only be managed with preventative measures taken to inhibit another incident. Medicines like aspirin and other anti-clotting drugs are used to keep clots from forming and causing another MI (CDC). ACE inhibitors reduce the strain on the heart by lowering blood pressure and this helps to not weaken the damaged tissues any further (NIH). Similarly, Betablockers also reduce the strain on the organ by blocking the release of stress hormones like noradrenaline and adrenaline to keep heart rate constant (NIH). All of these, however, only reduce the risk of a recurrence and do not regenerate the dead tissue, whereas a different form of therapy for the damaged tissue could bring about a brighter prospect. Stem cells can regenerate tissues suitable to one’s own body without having to use a transplant. This makes it less risky when it comes to a patient’s body rejecting the cells. Some varieties are also easily accessible, usable, and effective in their respective needs.

Out of the many varieties of stem cells, induced pluripotent stem cells, are some of the most promising to study. Induced pluripotent stem cells (iPS cells) are derived from somatic cells that are reprogrammed into iPS cells. These cells can then be made to differentiate into whatever tissue cell is needed (Shi et al, 2016). They are also important to observe because of their accessibility and high turnover rate (Krzysztof et al, 2018). In this review, we will focus on two types of stem cells: induced pluripotent stem cells, and their abilities in tissue regeneration in regards to therapies to treat the infarcted myocardium (Yoshida et al, 2017).

Induced Pluripotent Stem cells

Induced Pluripotent Stem Cells (iPSCs) are adult somatic cells that are reprogrammed into a pluripotent state. These cells are adults and unipotent, meaning they are capable of regenerating only their own specific tissue type (Tweedell, 2017). For example, an adult somatic cell in the skin could only generate skin cells. When these cells are reprogrammed into iPSCs, they become pluripotent, and are able to differentiate into any type of tissue with appropriate differentiation factors (Tweedell, 2017).

The use of iPSCs for regenerative medicine bears significant advantages. In fact, the somatic cells generally used for reprogramming are highly accessible and they are already part of the body of the person who needs them. Therefore, there is no risk of rejection when they are implanted for regenerating damaged tissues or organs (Arjmand et al, 2017). One further advantage is that they are not controversial like embryonic stem cells that are isolated from embryos while having similar properties. Generating the iPSCs is completed by taking any healthy adult somatic cells from the body and reverse engineering them into a pluripotent state where they can then differentiate into whatever cell type is needed. How this occurs is that first, the cells organize spatially and then divide into three areas. The middle section, differentiates into the middle portion of the three’s lineage and this activates certain genes.

Cardiovascular Regeneration

As mentioned above, one of the capabilities of iPSCs is tissue regeneration, which is paramount for cardiovascular tissue regeneration. The basic process for cardiovascular tissue engineering consists in isolating somatic cells of the patient or from healthy donors, which are then reprogrammed to iPSCs. Next, the obtained iPSCs are differentiated into the specific cell type that is needed (such as cardiomyocytes, cardiac fibroblasts, or endothelial cells). The differentiated cells must be cultured in the lab to grow, and during this process they can be stimulated with chemical or physical cues to mimic the mechanical properties of the beating heart. The last step is to inject or implant the cells into the patient.

Cardiovascular tissue engineering has shown promising results in vitro and in preclinical in vivo studies. Several groups have used small animal models, including mice and rats model of myocardial infarction to assess the ability of repairing the damaged heart tissue with iPSCs-derived cardiomyocytes. An example of implantation of cardiac engineered tissues in a small animal model is provided by (Tompkins et. al. 2018), that used 3D bioprinted iPSC-derived cardiomyocytes, fibroblasts and endothelial cells to produce 3D patches that were implanted in n=6 infarcted rats.

Additionally, vivo models further demonstrate that this path of study is incredibly promising. The work of Tompkins et. al. describes small animal models where iPSCs are implanted. This article demonstrates how this work is viable in live models as they tested various species of small animals to prove efficacy. Moreover, the same study considered large animal studies and deduced that they too have promising results. More specifically, in swine models, which are known to have extremely similar cardiac structure to that of humans, these studies further the thought that using iPSCs to repair tissues is a viable solution. Kawamura et al. placed a sheet of dermal fibroblast-derived hiPSC-CMs over the infarcted area in an ischemic swine model, which produced improved cardiac performance, angiogenesis (increased number of blood vessels in the infarct), and an attenuated LV remodeling 8-weeks post implantation.

While in the lab, stimuli of stretching and current are used to help the cells mature faster and grow more resilient. This is one place of research that is continuing to challenge researchers, since they do not have years to culture mature cells and there is risk with implanting immature cells regarding their ability to adapt to the heart’s environment. However, it can and has been done, as explained above, which has drawn tremendous attention to this field of pursuit. Moreover, cardiovascular regeneration is one of the newest technologies in repairing damaged tissues in the heart. This breakthrough has made it possible to just regrow healthy and functional tissue instead of needing a transplant since it is already known that once tissue is dead from a myocardial infarction, there is no way to salvage it. As the MI damages the tissue, it makes it impossible for the original tissue to be functional, so inputting fresh, cultivated tissues open up new possibilities in life for the patient after their MI episode.

Drug Screening

During the process of drug screening, various drugs are tested on the cardiac engineered tissues to gauge safety and efficacy of the tested molecules and drugs. One of the commonly tested side effects of newly developed drugs are for drug induced arrhythmias. By testing in-vitro with iPSCs outside of a patient’s body, it is not only more convenient to do so but also safer so as to not involve a live subject (Smith et. al. 2017). Various types of cell models are used, ranging from flat, 2D monolayers to more complex 3D tissues, organ-on-a-chip models show a wide range of functionality. Each of these model types show a range from the least to most complex levels of organization in order to understand how drugs can affect the cardiomyocytes on a basic to fully vascularized level (Smith et. al. 2017 Fig. 1). This is one place of development in the field of iPSCs that would be of great benefit to the scientific community and to the general population as well. If drugs can be screened and tested within a lab without having to use in vivo models until much later in the process, it can be much more ethical and more varieties of medicines that may or may not be viewed as viable could potentially be trialed in this way due to the reduced ethics concerns.

One example of a clinical trial is in the research of Blinova et. al. which shows a personalized drug screen model that highlights how iPSCs derived from 22 healthy subjects can be grown and tested within a dish. Safety and efficacy of two drugs, dofetilide and moxifloxacin (hERG‐blocking and QT prolonging), were tested on iPSCs isolated from the peripheral blood mononuclear cells and differentiated in cardiomyocytes. There were no drug induced arrhythmia-like events observed at the studied drug concentration rate. In vivo model of testing that highlights how tissue can be grown and tested within a dish. In this trial, the researchers tested and analyzed for arrhythmias in the iPSCs. This demonstrates how various environments of the heart can be simulated in the lab and that it is necessary to do so (Blinova et. al. 2019)

Various different types of trials can be used to screen for arrhythmias in a drug screening. One method researchers historically and commonly use is the analysis of hERG channel response which is the standard procedure for in vitro preclinical trials of drug screening. While this is a method commonly used, it is not as accurate as could be desired since false positive results are frequent occurrences (Smith et. al. 2017). This is why iPSC-CMs are making headway in the field of drug screening since they offer a more accurate option. There are various tests researchers can run with in vitro models of iPSCs to represent the function of the heart more fully and effectively. Out of the multitude of options researchers now have with iPSC-CMs as an option, an example presented in the above research is that researchers measure cell contraction to observe the cardiomyocytes’ contractile function (Smith et. al. 2017).

Conclusion

After an episode of myocardial infarction, heart tissue is damaged irreversibly and the prognosis only entails either drug therapeutics or organ transplant. Cardiovascular regeneration is one of the newest technologies in regards to repairing damaged tissues in the heart. With reprogrammed iPSCs , the patient is able to have their healthy cells cultured in a lab and remediate the scarred tissue resulting from an MI episode. Furthermore, progress has also been made in labs to accommodate the new research and to screen drugs to ensure their safety with the cultured tissues when implanted in a person. All together, these breakthroughs have made it possible to regrow healthy and functioning tissue and using iPSCs could make this possibility a reality.

References

Arjmand B, Goodarzi P, Mohamadi-Jahani F, Falahzadeh K, Larijani B. Personalized Regenerative Medicine. Acta Med Iran. 2017 Mar;55(3):144-149.

Blinova K, Schocken D, Patel D, Daluwatte C, Vicente J, Wu JC, Strauss DG. Clinical Trial in a Dish: Personalized Stem Cell-Derived Cardiomyocyte Assay Compared With Clinical Trial Results for Two QT-Prolonging Drugs. Clin Transl Sci. 2019 Nov;12(6):687-697.

CDC, Heart Disease in the United States, 2020 Sept.

Csöbönyeiová M, Polák Š, Danišovič L. Perspectives of induced pluripotent stem cells for cardiovascular system regeneration. Exp Biol Med (Maywood). 2015 May;240(5):549-56.

Hoang P, Wang J, Conklin BR, Healy KE, Ma Z. Generation of spatial-patterned early-developing cardiac organoids using human pluripotent stem cells. Nat Protoc. 2018 Apr;13(4):723-737.

Justin Liu, Kathleen Miller, Xuanyi Ma, Sukriti Dewan, Natalie Lawrence, Grace Whang, Peter Chung, Andrew D. McCulloch, Shaochen Chen,Direct 3D bioprinting of cardiac micro-tissues mimicking native Biomaterials, Volume 256, 2020, 120204, ISSN 0142-9612myocardium,

Kawamura M, Miyagawa S, Miki K, Saito A, Fukushima S, Higuchi T, Kawamura T, Kuratani T, Daimon T, Shimizu T, Okano T, Sawa Y. Feasibility, safety, and therapeutic efficacy of human induced pluripotent stem cell-derived cardiomyocyte sheets in a porcine ischemic cardiomyopathy model. Circulation. 2012 Sep 11;126(11 Suppl 1):S29-37.

Madigan M, Atoui R. Therapeutic Use of Stem Cells for Myocardial Infarction. Bioengineering (Basel). 2018 Apr 6;5(2):28

Müller P, Lemcke H, David R. Stem Cell Therapy in Heart Diseases – Cell Types, Mechanisms andImprovement Strategies. Cell Physiol Biochem. 2018;48(6):2607-2655.

NIH, What is a Heart Attack?, 2018 June.

Polonchuk L, Chabria M, Badi L, Hoflack JC, Figtree G, Davies MJ, Gentile C. Cardiac spheroids as promising in vitro models to study the human heart microenvironment. Sci Rep. 2017 Aug 1;7(1):7005.

Rikhtegar R, Pezeshkian M, Dolati S, Safaie N, Afrasiabi Rad A, Mahdipour M, Nouri M, Jodati AR, Yousefi M. Stem cells as therapy for heart disease: iPSCs, ESCs, CSCs, and skeletal myoblasts. Biomed Pharmacother. 2019 Jan;109:304-313.

Shi Y, Inoue H, Wu JC, Yamanaka S. Induced pluripotent stem cell technology: a decade of progress. Nat Rev Drug Discov. 2017 Feb;16(2):115-130.

Smith AS, Macadangdang J, Leung W, Laflamme MA, Kim DH. Human iPSC-derived cardiomyocytes and tissue engineering strategies for disease modeling and drug screening. Biotechnol Adv. 2017 Jan-Feb;35(1):77-94.

Tompkins BA, Balkan W, Winkler J, Gyöngyösi M, Goliasch G, Fernández-Avilés F, Hare JM. Preclinical Studies of Stem Cell Therapy for Heart Disease. Circ Res. 2018 Mar 30;122(7):1006-1020.

Tweedell KS. The Adaptability of Somatic Stem Cells: A Review. J Stem Cells Regen Med. 2017 May 30;13(1):3-13

Ye L, Swingen C, Zhang J. Induced pluripotent stem cells and their potential for basic and clinical sciences. Curr Cardiol Rev. 2013 Feb 1;9(1):63-72.

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Zhao Y, Rafatian N, Wang EY, Wu Q, Lai BFL, Lu RX, Savoji H, Radisic M. Towards chamber specific heart-on-a-chip for drug testing applications. Adv Drug Deliv Rev. 2020;165-166:60-76.

About the author

Rishya Gutti

Rishya is a junior at Neuqua Valley High School. She is interested in biological sciences and is an aspiring medical student. Research programs like RISE (Research, Inquiry Skills & Experimentation) have equipped Rishya with necessary skills to conduct independent research. She is a third degree black belt in Taekwondo and has won several national titles in her age group. Rishya enjoys volunteering her time to teach mathematics to younger students and to promote mental health awareness through a non-profit organization. In her free time, you will find her reading, working out, or watching her favorite tv shows.

The post Using induced pluripotent stem cells for tissue regeneration in cardiovascular diseases appeared first on Exploratio Journal.

Background

Dengue is a vector-borne, viral infection commonly found in tropical and sub-tropical areas of Central America, South America, Africa, Asia and Oceania [1]. It is caused by 4 types of viruses (DENV-1, DENV-2, DENV-3 and DENV-4), and is spread by the Aedes albopictus and Aedes aegypti species of mosquito, both of which thrive in areas containing standing water like puddles, pails, water tanks and tires [2]. The first dengue case was picked up at Pulau Pinang in 1901, and since then dengue has been a major problem affecting the Malaysian healthcare system and population as a whole for more than a century. By the 1960s, dengue had become endemic and in 1962 the first confirmed case of dengue-haemorrhagic fever was discovered in Pulau Pinang, eventually leading to the first epidemic outbreak in 1973 [3]. 

The current COVID-19 pandemic and the interventions put forth by the government in response have had their effects on recent dengue incidence rates, particularly in the year 2021. From the epidemiologic weeks 1 to 32 of 2021, a total of 16,565 dengue cases were reported, a drastic decrease of 47,423 (74.1%) from the same period in 2020 [4]. 

There have been a few different Movement Control Orders (MCO) implemented throughout the period of this study. The first MCO which spanned from 18^th March 2020 to 3^rd May 2020 [5] contained sanctions for all Malaysians traveling abroad, 14-day quarantines for those returning from overseas [6], general prohibition of mass movements and gatherings including religious, sports, social and cultural activities [6] and the entry of foreign persons into the country [6]. Some specific locations like Simpang Renggam in Johor were subjected to the Enhanced Movement Control Order (EMCO) for 14 days at a time during the period of the first MCO if a large cluster was detected within the area [7]. All residents living in such areas were forbidden from exiting their homes, outsiders were not allowed into the area and all roads into the area were blocked [7]. The Conditional Movement Control Order (CMCO) was implemented from 4^th May 2020 to 9^th June 2020, and had more relaxed regulations to stimulate the national economy [8]. Most activities and businesses were allowed to operate as long as social distancing was obeyed and interstate travel was not allowed except for work purposes [9]. The Recovery Movement Control Order (RMCO) was implemented from 10^th June 2020 to 31^st August 2020, and allowed interstate travel outside of areas under EMCO and certain religious activities at mosques [10]. Tourism businesses were allowed to open from 1^st July provided that the number of people in crowds was kept to 200-250 people and social distancing measures were obeyed [11]. Private pre-schools, kindergartens and day-care centres were also allowed to operate and many activities such as weddings, seminars, cinemas etc were allowed [12].

This paper examined and analysed the Dengue and COVID-19 incidents more extensively to investigate the reason and the details of this figure, as well as discusses the possible causes of such a drastic decrease.

Objectives

1. To show that the dengue incident rates in Malaysia had behaved unusually and dropped significantly in 2021.

2. To explore the potential contributing factors to the declined dengue incidence rates.

Methodology

This study was conducted during week 44 of 2021, so only data up to that point was used.

In order to illustrate that the dengue incidence rate of 2021 was significant, comparisons with the weekly trend of the Dengue incidence of the previous years was made. The number of reported dengue cases each week starting from week 1 of 2015 to week 44 of 2021 was recorded from public press releases posted on iDengue [13]. Any missing pieces of data were filled by dividing the cumulative number of cases over the number of weeks in the gaps. The epidemiologic weeks were plotted against the dengue incidence rates of each year. 

Correlations between COVID-19 incidence rates and dengue incidence rates were explored. Data on COVID-19 incidences per week from 2020 to week 44 of 2021 was retrieved from the Johns Hopkins University COVID-19 data repository. The maximum value from the COVID-19 case data set was divided by the maximum value from the dengue case data set to end up with a value of 44. All COVID-19 incidences per week were then divided by 44 to normalise the data for graph-plotting. The new COVID-19 data was plotted with the dengue incidence rate from 2020 to week 44 of 2021. The periods of the different Movement Control Orders (MCO) were labelled.

Dengue incidence rates during 2021 may have been low due to underreporting: fear of exposure to the COVID-19 virus and the overwhelmed healthcare system are possible reasons. To investigate this, the ratio of positive dengue tests to total number of dengue tests was analysed. This part of the study only covers the city of Ipoh. Dengue NS1 test data was retrieved from Pantai Hospital Ipoh. The data included the total number of negative and positive tests for dengue from 2015 to 2021 in the population of Ipoh. The total number of positive tests from each year was divided by the total number of tests carried out in the respective years to find the positivity rate. The percentage of positive tests for all years were then analysed.

The method of judgement was as follows: 

• If the percentage of positive tests was significantly lower than previous years, it was a sign of over testing
• If the percentage of positive tests was significantly higher than previous years, it was a sign of undertesting.

Next, the mortality rates of dengue throughout the years from 2018 to 2021 were analysed. The total number of deaths by dengue each studied year in Malaysia was recorded. The data was taken from the World Health Organizations Dengue Situation Update Number 634 [14]. The results between the years were then compared.

The idea of a correlation between vaccination and dengue incidence rates was also explored inside this study. The cumulative number of full vaccinations (2 doses) for each week from week 9 to week 44 of 2021 in Malaysia was recorded. The data was taken from the University of Oxford’s “Our World in Data” website [15]. Each successive value had been deducted by the previous value in order to find the number of complete vaccinations each week. To normalise the data for graph-plotting purposes, the greatest value of complete vaccinations in a week was divided by the greatest number of dengue cases in a week. The value that came out was 666. All values of complete vaccinations each week were then divided by 666 and plotted with the dengue incidence rate of the corresponding weeks.

Results

Graph 1 shows clearly that the dengue incidence rates of 2021 stray far from the trends of the previous years, behaving entirely differently. The most obvious observation is that the number of cases in 2021 appears to be significantly lower than the previous years, with very little deviance from an approximate range of 300-500 cases. Dengue cases usually rise in the months of June to August (week 23 to week 32), and November to February (week 43 to week 60), during the monsoon seasons, as it leaves many areas with standing water which mosquitoes can thrive in [16]. However, dengue incidences in 2021 do not seem to follow this trend which has been consistent for all past years, pointing towards 2021 being highly unusual.  

Graph 2 shows that dengue incidence rates had begun to decrease continuously around the same time as the beginning of the increase in COVID-19 cases. This could indicate a possible correlation between the two, but more investigation and study is required in order to make any conclusions. During March to June, there is a drop in dengue cases compared to earlier years that is not far from the previous years, but the MCOs contribute to the progressive drop of dengue incidence. Besides that, there does not appear to be much correlation between dengue incidence rates and COVID-19. 

There was a general decrease in percentage of positive tests from 2015 to 2018. The rates then increased in the years of 2019 and 2020 then decreased to 1.16% in 2021. It should be noted that the total number of tests done in 2021 was only 614, which is a 79.9% decrease from the average of the past years (2999.5). The low percentage of positive tests shows that undertesting was unlikely. This suggests that the low incidence of Dengue during 2021 is unlikely to cause by under detection.

From Table 2, it can be seen that the total number of cases recorded as well as the total number of recorded deaths were significantly lower than previous years. The total deaths in 2021 were 116 lower than 2020, a decrease of 87.2%. The mortality rate in deaths per 1000 people for 2021 was 0.0751%, drastic decrease from the yearly average of the previous years which was 0.158%. 

Mortality rates are a reliable way to visualise real dengue incidence rates, as deaths will always be reported. This method of analysis and the results decrease the possibility of underreporting being the cause of such low recorded incidence rates. This data points convincingly towards dengue cases dropping in 2021.

Graph 3 reflects no correlation between complete vaccinations and dengue, implying that the COVID-19 vaccinations have no effect on immunity against dengue. Although, majority of COVID-19 vaccinations were only completed near the end of the dengue data recorded, so claiming that there is completely no correlation would not be a reliable conclusion. They may have been a further decrease in dengue cases after week 44. Further study must be done.

Discussion

The data shows unequivocally that there is a significant drop in dengue incidence in the year 2021 compared to previous years, although this decrease seemed to begin around week 30 of 2020. A few speculations were made at an attempt to explain such a decrease. Firstly, one of the possible contributing factors to the decrease was that the cases may have been underreported as the healthcare system may have been overwhelmed, and people who potentially had dengue may have been afraid to seek treatment due to fear of contracting COVID-19 from healthcare facilities. Furthermore, the low dengue mortality rates during 2021 reflects the reduction of dengue incidence, as deaths are less likely to be unreported. The low positive rate of dengue tests and low dengue mortality rate convinced us that the drop of dengue cases in 2021 is unlikely to be caused by under reporting or under detection.

The next hypothesis is that under the movement control orders, people had more time to clean their homes and get rid of potential breeding grounds for vectors. Studies have shown that more frequent cleaning does lead to lower dengue incidence rates [17] [18]. This can only be ascertained with data from a vector (Aedes aegypti and Aedes albopictus) surveillance study.

The restriction on travel might also have affected dengue incidence rates heavily. Previous studies have shown that lesser travel is correlated with lower dengue incidence rates [19]. There have been many travel bans throughout the COVID-19 periods in Malaysia. Further study and analysis of the dengue incidence rates in these time periods is required to draw any conclusions. Unfortunately, month by month data of specific regions was not accessible.

Another potential contributing factor is the closing down of schools and workplaces because of the MCOs and transition to online schooling/working. In 2020, there were 5 million students among the population of 32.37 million in Malaysia [20]. The students were also equally distributed across every household across the nation, making the abstention from schools all the more significant. If this speculation is true, it would prove fruitful to look further into school and working environments as potential reservoirs of Aedes mosquitoes. 

The dengue test data collected had two limitations: patient specific data could not be collected and the data only represented the population of Perak. Different trends and conclusions could be made if all test types and a bigger part of the population was included.

The significant drop of dengue cases during the COVID-19 pandemic has generated a plethora of hypotheses that could be made for further investigation. This pandemic and the MCOs implemented in response have led to a natural experiment in which there was a nationwide change of lifestyle in Malaysia. Hence, a lot of opportunities for further research into the control of dengue and other infectious diseases have opened up. 

Bibliography 

[1] World Health Organization, “Dengue and Severe Dengue,” 10 January 2022. [Online]. Available: https://www.who.int/news-room/fact-sheets/detail/dengue-and-severe-dengue.

[2] Centers for Disease Control and Prevention, “How to Prevent the Spread of the Mosquito that Causes Dengue,” 25 January 2012. [Online]. Available: https://www.cdc.gov/dengue/resources/vectorcontrolsheetdengue.pdf. [Accessed 17 January 2022].

[3] A. Rudnick, “Dengue fever epidemiology in Malaysia, 1901-1980,” ResearchGate, vol. 1, pp. 1269-1272, 1986. 

[4] The Star, “Health Minister: Drastic drop in dengue cases in Malaysia this year,” The Star, 7 August 2021. [Online]. Available: https://www.thestar.com.my/news/nation/2021/08/07/health-minister-drastic-drop-in-dengue-cases-in-malaysia-this-year. [Accessed 17 January 2022].

[5] Bernama, “MCO extended another two weeks to May 12 – Muhyiddin,” Bernama, 23 April 2020. [Online]. Available: https://www.bernama.com/en/general/news.php?id=1835248. [Accessed 17 January 2022].

[6] New Straits Times, “Covid-19: Movement Control Order imposed with only essential sectors operating,” New Straits Times, 16 March 2020. [Online]. Available: https://www.nst.com.my/news/nation/2020/03/575177/covid-19-movement-control-order-imposed-only-essential-sectors-operating. [Accessed 17 January 2022].

[7] N. S. Sham, “COVID-19: PKPD dikuat kuasa di dua kawasan di Simpang Renggam,” Astro Awani, 26 March 2020. [Online]. Available: https://www.astroawani.com/berita-malaysia/covid19-pkpd-dikuat-kuasa-di-dua-kawasan-di-simpang-renggam-235454. [Accessed 17 January 2022].

[8] Bernama, “Perintah Kawalan Pergerakan bersyarat akan dilaksana – Muhyiddin,” Bernama, 1 May 2020. [Online]. Available: https://www.bernama.com/bm/news.php?id=1837419. [Accessed 29 January 2022].

[9] Bernama, “Essence of conditional Movement Control Order,” Bernama, 1 May 2020. [Online]. Available: https://web.archive.org/web/20200502065534/https://www.bernama.com/en/general/news.php?id=1837487. [Accessed 29 January 2022].

[10] The Sun, “Interstate travel among activities allowed from Wednesday – Muhyiddin,” The Sun , 7 June 2020. [Online]. Available: https://web.archive.org/web/20200608041411/https://www.thesundaily.my/home/interstate-travel-among-activities-allowed-from-wednesday-muhyiddin-HN2539119. [Accessed 29 January 2022].

[11] C. Loo, “More sectors to be reopened under RMCO from July 1,” The Sun, 26 June 2020. [Online]. Available: https://web.archive.org/web/20200626081436/https://www.thesundaily.my/covid-19/more-sectors-to-be-reopened-under-rmco-from-july-1-YD2630375. [Accessed 29 January 2022].

[12] The Sun, “Pre-schools, kindergartens to open on Wednesday, preparations underway for the little ones,” The Sun, 29 June 2020. [Online]. Available: https://web.archive.org/web/20200629010541/https://www.thesundaily.my/home/pre-schools-kindergartens-to-open-on-wednesday-preparations-underway-for-the-little-ones-AB2636604. [Accessed 29 January 2022].

[13] Menteri Kesihatan Malaysia, “Demam Denggi Dan Chikungkunya,” 2015-2021. [Online]. Available: https://www.moh.gov.my/index.php/database_stores/store_view/17?items=25&page=6. [Accessed 17 January 2022].

[14] World Health Organization, “Update on the Dengue situation in the Western Pacific Region,” World Health Organization, 2 December 2021. [Online]. Available: https://www.who.int/docs/default-source/wpro—documents/emergency/surveillance/dengue/dengue-20211202.pdf?sfvrsn=fc80101d_106. [Accessed 17 January 2022].

[15] E. M. L. R.-G. C. A. C. G. E. O.-O. J. H. B. M. D. B. a. M. R. Hannah Ritchie, “Our World in Data,” University of Oxford, 2021. [Online]. Available: https://ourworldindata.org/covid-vaccinations?country=MYS. [Accessed 17 January 2022].

[16] H.-Y. Y. et.al, “The effects of seasonal climate variability on dengue annual incidence in Hong Kong: A modelling study,” Scientific Reports, vol. 10, 2020. 

[17] P. R. B. S. Krishna Prasad Bhandari, “Application of GIS Modelling for Dengue Fever Prone Area Based on Socio-Cultural and Environmental Factors,” The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 37, no. 8, 2008. 

[18] T. Chareonviriyaphap, “Larval habitats and distribution patterns of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse), in Thailand,” Southeast Asian J Trop Med Public Health, vol. 34, no. 3, pp. 529-535, 2003. 

[19] H. H. e. al, “Dengue viruses circulating in Indonesia: A systematic review and phylogenetic analysis of data from five decades,” Reviews in Medical Virology, vol. 29, no. 4, 2019. 

[20] The Straits Times, “All 5m students in Malaysia back to school for first time since Covid-19 outbreak,” The Straits Times, 5 April 2021. [Online]. Available: https://www.straitstimes.com/asia/se-asia/all-students-in-malaysia-back-to-school-for-first-time-since-covid-19-outbreak. [Accessed 30 January 2022].

About the author

Ze Shan Chan

The post The drastic drop in dengue cases in Malaysia during the COVID-19 pandemic appeared first on Exploratio Journal.

Introduction

“If agriculture is to continue to feed the world, it needs to become more like manufacturing”, says Geoffrey Carrand fortunately, that is already beginning to happen.¹Advances in technology are key to the future of agriculture as farmers strive to feed the world with limited natural resources.² In Tamil Nadu state, located in South India, Agriculture is the greatest overriding sector of the state’s economy and nearly 70% of states population is based on agriculture. The agriculture in Tamil Nadu has executed a good performance over the years with the help of efficient farmers who are both receptive and responsive to the technological development announced in the agricultural sector of the state.³ Innovations for small agricultural operations can significantly increase profit margins by minimizing the need for manual labour with automation, expediting machinery commands with remote and real-time monitoring, and allowing farmers to utilize resources more efficiently with preventative maintenance and environmental prediction. Mass embracement of these technology advancements in agriculture will allow small land holding farmers to achieve higher potential for profit, and higher yields on the upfront investments.⁴I live in Tamil Nadu and our family own an agricultural field and that interests me to investigate this study, for which I researched and collected primary and secondary data regarding the topic.  The technologies that are currently reshaping the agriculture of Tamil Nadu state are detailed below.

PRECISION FARMING

Precision Farming helps farmers to generate data with the help of sensors and analyse that information to take intelligent and quick decisions.⁵ It is the application of modern information technologies to provide, process and analyse multisource data of high spatial and temporal resolution for decision making and operations in the management of crop production⁶  and helps in changing the socio-economic status of farmers.⁷ 

CASE STUDY   

Mr.Rajamani, a farmer in Coimbatore district, Tamil Nadu, follows the precision farming in his field, where he broadcasted the coriander seeds in between the turmeric crop, small onion and chilly as intercrops, red gram as border crop and irrigated the field through drip system. He harvested the coriander in 30 – 35 days, onion in 70 days, chillies on 90th day, red gram on 250th day and turmeric fingers on 275 days after sowing. He acquired yield of 7 tonnes of turmeric fingers and 13 tonnes of onion, 2 tonnes of green and dry chilies and 50 kg red gram in one hectare of land. He sold turmeric fingers at the rate of Rs. 135 / kg, onion at Rs. 20/ kg, chillies at Rs. 12/ kg, red gram at Rs. 100/ kg, tender coriander leaves Rs.4/kg and coriander seed at Rs. 15/ kg. He invested Rs. 3,35,400 for cultivation practices and attained a high profit of Rs. 9,66,000 per hectare and this was possible since he shifted from conventional farming to precision farming.⁸

ORGANIC FARMING

This process involves the use of biological materials, avoiding synthetic substances to maintain soil fertility and ecological balance thereby minimizing pollution and wastage. It relies on ecological processes, biodiversity and cycles adapted to local conditions, rather than the use of inputs with adverse effects and care for the larger environment and conservation of natural habitats and wildlife.⁹

CASE STUDY

Organic farming is the in-thing now in Thanjavur district, the rice bowl of Tamil Nadu, where one hundred farmers are successful in practising organic farming, for crops like- banana, maize and paddy. Mr.Kulandaisamy, a progressive farmer has raised Rasthali and Robust variety of bananas adopting organic farming methods. With respect to Rasthali, a bunch has five to six hands (hands means “seeppu” in Tamil language), instead of three to four hands, which are normally seen in ordinary cultivation and a single bunch weighs 20 kgs and fetches Rs.200. And the Robust variety of banana has 12 to 15 hands in a bunch and the bunch weighs 30 to 35 kgs, which are popularly sold in Tiruchirappalli city (my native), market. Fertiliser used by the farmer was composed using organic matters, neem, and pancha kavya prepared using cow’s urine and cow dung. The farmer has cultivated maize, paddy and Vanila (a profit-oriented venture), using organic farming.¹⁰

DRONES 

 Drones help farmers optimize the use of inputs such as seeds, fertilizers, water, and pesticides more efficiently. This allows timely protection of crops from pests, saves time for crop scouting, reduces overall cost in farm production, and secures high yield, increasing the farm profitability. ¹¹Initially used for chemical spraying, today drones are a great tool used to assess different aspects of plant health, weeds, and assets.

CASE STUDY

Tamil Nadu Agricultural University has developed drones, that could carry 15kg agricultural input, that helps to spray pesticides, insecticides and herbicides to protect crops, with a capability of covering one hectare in five minutes and a maximum of three hectares in 15 minutes in a single flight. It could cover large areas in a short time, so that pests could be destroyed across massive tracts of land before they could spread. However, drifting due to varying wind speed is a risk. During windy days it may not be a good choice, says the officials. ¹² And in future, usage of a drone would eliminate dependence on the already scarce farm labour. 

IOT BASED SMART FARMING

In IoT-based smart farming, a system is built for monitoring the crop field with the help of sensors and automating the irrigation system. The farmers can monitor the field conditions from anywhere.In terms of environmental issues, IoT-based smart farming can provide great benefits including more efficient water usage, or optimization of inputs and treatments. ¹³

CASE STUDY

A team of college students from Salem city, Tamil Nadu, have come into the spotlight recently for their Internet-of-Things (IoT) based software solution that seeks to give a push to smart farming, and this crop guidance software is a set of three applications that enable remote monitoring of pest control, automated watering and growth. The objective is to bring in smart farming solutions that allow farmers to produce maximum yields with minimum resources such as water, fertiliser and seeds, and reduce wastage or losses. One of the applications of their IoT-based comprehensive solution is the Plant Growth Monitoring System, which uses colour sensors to check the growth of the plants and sprays fertiliser as and when needed. Another application with an additional WiFi module identifies pest attacks and sprays pesticide precisely on the affected parts of the agricultural land. Another application, the Automatic Plant Watering System, uses a moisture sensor and utilises water resource judiciously as it triggers watering based on the moisture level of the soil. The systems work automatically- for example- in the watering system when the sufficient water level is reached, it will switch off on its own. This makes it easier for farmers and makes the process seamless. As the applications are IoT-based, they also have a feature that provides weather conditions for proper crop growth to the farmers. ¹⁴

MOBILE APPS 

There are mobile applications that provide latest agricultural information about trends, equipment, technologies and methods being used, help identify pests and diseases, provide real-time data about weather, early warnings about storms, local markets offering best prices, seeds, fertilizers etc. In addition, farmers can also interact and get guidance from agriculture experts across the country via the apps. These apps help in providing market information, facilitating market links, providing access to extension services, farm related information etc.¹⁵

CASE STUDY

About 4,91,811 users of Uzhavan App, launched by Tamil Nadu Agricultural Ministry, educate farmers about soil quality, seeds and fertilizers. FarmMOJO app provides real time solutions for aquaculture, including shrimp and fish farming and this app records data like pH balance, ammonia and nitrate levels and water quality. Tumaini app allows farmers, cultivating banana, to scan plants and detects symptoms on any part of the crop with an accuracy rate of 98%.¹⁶

HYDROPONICS

Hydroponics is a way to skip the soil and grow crops directly in nutrient-rich water, that gives higher yield with fewer resources. ¹⁷

CASE STUDY

According to Mr.Srinivasan, a resident of Chennai city, perform commercial hydroponics by growing crops like spinach, kale, and lettuce. With nearly 250 plants across 50 square feet, Rahul Dhoka runs Acqua Farms in Chennai city. The rate of crop growth is around 30 to 40 per cent faster and have a 30 to 40 per cent higher yield, than soil-based agriculture, with a less cost of production ie-lettuce costs Rs 15 to 17 per kg, and basil costs Rs 20 to 25 per kg. ¹⁸

SOIL MOISTURE INDICATOR

Soil moisture indicator has sensors to detect the soil moisture content for proper development of plants and notify the user when the soil gets too dry or too wet.¹⁹ This device works based on the principle that electrical conductivity of the soil is directly proportional to soil moisture or soil electrical resistance is indirectly proportional to soil moisture content.^20.  It is suitable for different types of soils and can be used in nurseries, farms, potted plants, etc.²¹

CASE STUDY

The Soil Moisture Indicator, a handy and user-friendly electronic moisture–indicating device, was first launched at Sugarcane Breeding Institute at Coimbatore city, Tamil Nadu, which is used for the efficient irrigation management practices such as irrigation-scheduling, particularly in sugarcane fields, that helps the farmers in deciding when to irrigate their fields and as a result there would be considerable saving of irrigation water. The sensor rods of the device need to be inserted into the soil to a required depth to assess the soil moisture, which is indicated by glowing LEDs and the device is suitable for use in agricultural farms as well as in potted plants.²²

RFID TECHNOLOGY

Radio Frequency Identification Technology offers monitoring systems, which protects the crops from pests and wireless sensors can be used to monitor cattle. It uses dedicated software and hardware to monitor livestock management.²³  It supports Animal population trackingand Animal data base monitoring.²⁴

CASE STUDY

“Mr. Vijaykumar, Perambalur district, Tamil Nadu, relies on computerisation to monitor the dairy along with the 60 staff who stay on the farm. Each animal has a blue-collar tag with a unique microchip number. “Of the 368 cows here, 160 are used for milking and the microchip helps us not just to track each cow’s health and daily milk output, but also to decide if it can be selected for breeding in future.²⁵

CONCLUSION:

The agriculture technologies have changed almost all the domains of farming from sowing to harvesting. These technologies are continued to evolve and invent new innovations that act as catalyst to ameliorate farmers’ life by increasing incoming and providing the access to research stations and agro-scientists.  The use of technology can make farmers feel more empowered and enable them to adopt required measures in needful time. It has potential capabilities to transform agriculture into a better prospect to get aware of climatic change and appropriate use of limited natural resources in agricultural land.²⁶ However technologies like hydroponics; drone farming; use of mobile applications and IOT based devices had get tremendous success in Tamil Nadu. Many government organizations and private bodies are working on to give a clear view about new technologies to the farmers of Tamil Nadu, like robotic farming, chromosomal technique and application of remote sensing etc… which are practiced globally.

REFERENCES

1. https://www.economist.com/technology-quarterly/2016-06-09/factory-fresh
2. https://www.raconteur.net/sustainability/top-5-tech-innovations-in-agriculture/
3. https://www.agrifarming.in/agriculture-farming-in-tamil-nadu-cultivation-practices
4. https://www.aeris.com/news/post/five-iot-applications-that-are-reshaping-agriculture-technology/
5. https://www.biz4intellia.com/blog/5-applications-of-iot-in-agriculture/
6. https://www.sciencedirect.com/topics/earth-and-planetary-sciences/precision-agriculture
7. https://www.downtoearth.org.in/blog/agriculture/why-farmers-today-need-to-take-up-precision-farming-64659
8. https://icar.org.in/node/8077
9. https://www.conserve-energy-future.com/organic-farming-benefits.php
10. https://agritech.tnau.ac.in/org_farm/orgfarm_success%20stories.html
11. https://blog.agrivi.com/post/powerful-role-of-drones-in-agriculture_april2018
12. https://timesofindia.indiatimes.com/city/coimbatore/reaping-rich-dividends-with-drones/articleshow/71382745.cms
13. https://www.iotforall.com/iot-applications-in-agriculture
14. https://www.edexlive.com/campus/2020/sep/29/tn-students-develop-smart-farming-solutions-for-automatedpest-control-and-plant-watering-14868.html
15. https://www.manage.gov.in/publications/edigest/dec2017.pdf
16. https://m.timesofindia.com/city/chennai/click-cure-tech-helps-farmers-reap-a-bounty/amp_articleshow/71284085.cms
17. https://www.verticalroots.com/the-what-and-why-of-hydroponic-farming/
18. https://www.dtnext.in/News/City/2019/12/10052809/1202790/Hydroponic-farming-helps-Chennaiites-grow-greens-at-.vpf
19. https://link.springer.com/chapter/10.1007/978-981-15-5113-0_55
20. https://sugarcane.icar.gov.in/index.php/en/home/1157-soil-moisture-indicator
21. http://www.techsourcesolutions.in/manufacturing/soil-moisture-indicator/
22. http://sugarcane100.blogspot.com/2016/01/soil-moisture-indicator-launched.html?m=1
23. https://agritechsupport.com/agriculture-technology/radio-frequency-identification-technology-in-agriculture/
24. https://academic.oup.com/jas/article-abstract/97/Supplement_2/1/5541113
25. https://www.thehindu.com/sci-tech/agriculture/data-analytics-helps-an-integrated-farm-in-arumbavur-village-perambalur-district-to-produce-additive-free-cows-milk/article26888613.ece
26. https://www.ijcmas.com/10-2-2021/Pradeep%20Kumar%20Singh,%20et%20al.pdf

About the author

Harnishya Palanichamy

Harnishya is currently in Grade 10 at the Hebron School, Ootacamund, Tamil Nadu, India. She’s passionate about the field of computer science, particularly the coding languages, Java and JavaScript. She enjoys coding and researching about AI. She started her coding journey by coding games in JavaScript, and she also has experience with robotics; being in the school robotics club. In the future, she wants to develop her coding knowledge by creating more complex apps.

The post Technologies Reshaping Agriculture in Tamil Nadu, India appeared first on Exploratio Journal.

Abstract 

Sleep has been the center of discussion for scientists over nearly the past century, with compelling evidence that show sleep influences memory consolidation. Nervous systems have specific structures related to distinctive functions, which serves to transform short-term memories into long-term memories, with synapses playing a crucial role. Tests on electrophysiology markers of synaptic efficacy adds proof to the synaptic homeostasis (SHY) hypothesis. During sleep, spontaneous activity renormalizes net synaptic strength and restores cellular homeostasis. Sleep stages and rhythms correspond to 5 types of brain waves respectively, and there are interplays between sleep rhythms and memory consolidation. Explicit memories (associated with neocortex and amygdala), reported by traditional studies, are strengthened during SWS sleep, whereas implicit memory (associated with basal ganglia and cerebellum) mechanisms have been also demonstrated in recent research to be recruited during NREM sleep periods. Experiments have provided evidence that show how individuals reproduce knowledge they learned after retention of several hours after intervals of sleep or wakefulness respectively. Data analysis show that sleep promotes memory consolidation consistently; effects are extremely significant in the situation with declarative memories (syllables).  Further research done recently have also come up with the result of brain reactivation during sleep.

1. Introduction

The basics of memory formation involve three stages: encoding, storage, and retrieval. Encoding represents the transformation of sensory inputs into short-term and long-term memories, storage is defined as to maintaining the encoded sensory information over time, whereas retrieval refers to how people get access to the actual memories stored in their brain. Different mechanisms, as well as different brain areas, are triggered when humans are forming and storing memories. For example, short-term memory involves mainly the prefrontal cortex, while long term memory involves the hippocampus, neocortex and amygdala (explicit memory) or the basal ganglia and cerebellum (implicit memory). Explicit memories, which are episodic events and semantic information, together with implicit memories, which involve motor memories, make up long-term memories. 

Memory consolidation is the rehearsal of earlier memories resulting in the increasing number of synapses, swelling amount of neurotransmitter released, and enlarging number of receptors on postsynaptic membrane. By consolidation, short-term memories can develop into long-term memories. Memory consolidation is rather significant. It is reported that students on average are able to grasp only 25% of the lecture they are listening to even carefully. The left 75% requires the mechanism of memory consolidation to be in the storehouse where it should be. Hence, teachers are supposed to assign homework and give feedbacks. This can be named as early consolidation practice which is later strengthened by quizzes and examinations.

Over the last decades, scientists have gained compelling evidence that sleep enhances the formation of long-term memories. Traditional theories proposed a passive role for sleep supporting memories by sheltering them from external stimuli, however recent research have uncovered an active role for sleep during memory consolidation. Traditional studies emphasized the role of rapid-eye-movement (REM) sleep, present papers have revealed that slow-wave-sleep (SWS) is also significant (Rasch B, Born J. 2013). Initially, scientists emphasize that sleeping provides shelter for the brain’s memory storage from external stimuli or interferences; yet later researchers put forward that sleep actively involves in system consolidation of memories. In this review, we will summarize about the correlations of sleep and memory consolidation. 

1. Neuron physiology
2. Neuronal structures and functions 

Neurons (also called nerve cells or neurones) are the fundamental units of the brain and nervous system. They are responsible for receiving input from external world, sending commands to the muscles, and relaying or integrating electrical signals. Most of a neuron’s organelles are in the cell body, with the largest karyoplasmic ratio of approximately 1:1 among all the other cell types.

 A useful model is to consider the structure of a neuron as a tree, consisting of three major parts: an axon (tree root), dendrites (tree branches), and a cell body (tree trunk). Long and slender, axons are projections of nerve cells that conducts action potential away from the cell body. The primary function of axons is to transmit signals to target cells. Axons fall into two categories: myelinated and unmyelinated. Myelinated axons are surrounded by segments of a fatty layer of insulating glial cells, namely Schwann cells (in the CNS) and oligodendrocytes (in the PNS). Vacant space in myelin sheath is known as nodes of Ranvier, where action potentials jump along. Due to their lengths, axons can be divided into branches of telodendrions, whose ends are called axon terminals. Axon terminals, as pre-synaptic axons, contain vesicles of neurotransmitters for the relay of electrical signals in the synapses. The post-synaptic dendrites can be easily distinguished by its similar appearances to lushy but short branches. Dendrites receives signals from axons and carries the action potential towards the soma. Dendrite spines are small protrusions that increase the receptive properties of dendrites to isolate signal specificity. Implication of dendrite spines can be seen in long-term potentiation. In other words, the ability of dendritic development plays a crucial role in memory formation. The cell body, the soma, holds nucleus responsible for production of proteins.  

The site in the nervous system where signals are relayed is called synapses. As signals can be described as chemical and electrical, so as synapses. In chemical synapses, the electrical signals must first trigger the release of neurotransmitters and next the second messenger or be again converted into electrical signals. While in electrical synapses, currents past through gap junctions directly by inducing voltage changes in the postsynaptic cells. Without the multiple steps used in chemical synapses, electrical ones are special for their rapidity (Cirelli C. 2013).

When not functioning, a neuron has a rest potential of 60-70 mV across its membrane, with the interior more negatively-charged. Opening or closing ion channels in the membrane lead to changes in the potentials. Hyperpolarization is when the membrane potential becomes more negative, with depolarization the opposite. Opening of channels that let potassium cations out or chlorine anions in may results in hyperpolarization. On the other hand, opening of channels that let sodium cations in will cause depolarization. When multiple depolarizing inputs happen at the same time, a large enough depolarization may ultimately lead to an action potential. An action potential is an all-or-none event, which means the stimulus must thrust the threshold of negative 55 mV. At this threshold, sodium cations influxes to increase the potential up to 40mV. Next, influxes stop and potassium cations rush out, causing a rapid fall towards normal resting state. Yet the potassium cations keep flowing out, resulting in a period of undershoot, where even larger potentials are needed to induce another action potential. Eventually, potassium outfluxes stop and the potential returns to -60 to -70 mV, ready for the next cycle. (Reece, J. B., et al, 2011)

1.12 Electrophysiology of synapses during wakefulness and sleep

Electrophysiological markers of synaptic efficacy have been tested in recent decades. The slope of the early response evoked by electrical stimulation delivered within a cell is a classical electrophysiological measure of synaptic strength, with a steeper slope indicating higher synaptic efficiency. A recent study utilized transcranial magnetic stimulation to evoke a response in humans’ frontal cortex. Results have shown that the slope of early responses increased gradually over the period of 18 hours of consisting awareness, and then recover to basic levels after one night of sleep (Cirelli, Chiara,2013). The explanation for such phenomenon has been proposed. The synaptic homeostasis hypothesis (SHY) proposes that sleep is the price the brain pays for plasticity. During a waking episode, learning statistical regularities about the current environment requires strengthening connections throughout the brain. This increases cellular needs for energy and supplies, decreases signal-to-noise ratios, and saturates learning. During sleep, spontaneous activity renormalizes net synaptic strength and restores cellular homeostasis. Activity-dependent down-selection of synapses can also explain the benefits of sleep on memory acquisition, consolidation, and integration (Tononi, G, et al, 2014).

1. Correlations between sleep and memory consolidation
2. Sleep stages and brain waves

As measured by eletroencephalography (EEG), the brain’s electrical activity is determined by the presence of brain waves, which fall into 5 categories: Gamma, Beta, Alpha, Theta and Delta waves. Gamma waves, are small-amplitude high-frequency (25-140 Hz) ones related to hyper brain activity, such as problem solving and high-concentration tasks. Beta waves (14-25 HZ) possess both lower amplitude and frequency traits and are generated when the brain is busily engaged in activities and conversation. Alpha waves (7.5-13 Hz); Theta waves (3.5-7.5 Hz) and Delta waves (3Hz or below) are all associated with rest, sleep and dreaming activities. 

During the approximately 90-minute-long sleep cycle, non-REM sleep first appears and rapid-eye-movement sleep (REM) follows. The sleep cycle has four stages, that are characterized by the presence of different brain waves. Stage 1 represents the transition step between wakefulness and sleep, in which the brain generates Alpha waves.  The following stage 2 is where Theta waves, K-Complex and sleep spindle waves alternate as responses and inhibition towards outside stimuli. While progressing to stage 3 and 4 sleep, people are drifting down into deeper sleep, and the brain emits Delta waves. Finally, people fall into stage 5 sleep, or REM sleep, presenting bran waves similar to those of an awake person. In this phase, dreaming occurs and the skeletal muscles experience atonia, and are unable to move. Cycles of slow wave and REM sleep alternate at night, with the slow wave sleep becoming less deep and the REM periods more prolonged until awakening.

2. Consolidation during SWS and REM 

Memory consolidation happens during slow wave sleep and REM phase. Slow wave sleep (SWS) periods appear to strengthen explicit memories evidenced by the observations on increased SWS after intensive episodic learning (Acosta MT, 2019). Recent studies on implicit memories during sleep have also demonstrated the recruitment of implicit learning mechanisms during NREM sleep, suggesting that memory consolidation may be optimized when taking into account sleep stages and sleep rhythms (Born J, et al, 2012). 

During slow wave sleep, the experienced episodes are stored temporarily in the hippocampus and are then redistributed in a long-term store in the neocortex. The waves generated in this process are hippocampal ripples, thalamocortical spindles and slow waves (delta waves). Originating in the medial temporal lobe, hippocampal ripples have a frequency of 100-300 Hz. Thalamocortical spindles are typical waves for stage 2 and SWS sleep, with a frequency of 10-15 Hz (Gage et al, 2018).  Spindles reaching the neocortex likely act to prime respective neuronal networks, e.g., by stimulating Ca²⁺ influx for subsequent synaptic plastic processes. Thus, memory information carried in single troughs of spindle oscillations maybe particularly effective in changing synaptic connections underlying the long-term storage of the information in the respective neocortical networks (Born et al, 2012). The third key SWS oscillation are the slow waves (0.5 – 4Hz). Slow waves are considered to reflect the brain’s up-and-down states, which is critical for memory redistribution, i.e., the encoding of information. The more information is encoded during wakefulness the higher amplitude of the slow oscillations is generated over respective cortical areas during succeeding SWS（Schonauer, et al. 2014).  A major function of the slow oscillations is that they temporally group neuronal activity into hyperpolarizing down-states during which neurons are globally silent and succeeding depolarizing up-states during which neuronal firing is increased to wake-like levels (Steriade et al. 2006). As previously described, the hippocampus, thalamus, and the cortex combine to form the complex neural symphony that corresponds to a key aspect of human SWS: memory stabilization and consolidation.

3. Effects of sleep on memory consolidation

3.1 Performance of individual subjects on the LGT-3 total score

Primary research has found that sleep consistently promotes overall declarative memory consolidation. Forty healthy adults aged 18–30 y, and 17 healthy adults aged 24–55 y with extensive meditation experience participated in the 3 experiments (Schonauer et al, 2014). In Experiment 1, subjects learned Turkish in the afternoon followed by a 2-h sleep, and after a 3-h retention they were tested. Results shown people performing far better after sleep than after wakefulness. There was only one exception that shown better results after an interval of wakefulness. In Experiment 2, volunteers acquired knowledge in the morning, after which they took a 2-h sleep and were tested after 8-h retention. Statistical analysis comported with results from experiment 1, with exception of 2 of 18 subjects (Schonauer et al, 2014).  In Experiment 3, procedures were same with Experiment 1 expect for the three states (sleep/active awake/meditation) subjects were kept respectively to compare. Subjects performed better on the test when there were only 3 h between learning and testing than when encoding and testing were spaced 8 h apart. There was still one exception out of 18 subjects. Conclusions were drawn: sleep does improve the consolidation of declarative memories while such effect is reserved only to sleep, and does not happen in the case of wakefulness. 

3.2 Significant improvements on syllable memories 

Two OS, L. R. Hodell and J. S. McGraw served as subjects and were required to learn meaningless syllables in series of ten by reading aloud, with exposure at the rate of 0.7 sec (Jenkins et al. 2021). The series were repeated by the subjects until they completely remembered the syllables. The experiment was carried out at night, when subjects go to bed after learning. They were separately waked by Ebbinghaus, the scientist, to give reproduction of the syllables. Analysis of data shown superiority of the reproductions after intervals of sleep. This superiority became more and more prominent as the length of the intervals elongated (Jenkins et al. 2021).

3.3 Improve memory by protection or reactivation of the brain during sleep

Sleep after learning leads to superior recall of syllables after the 1-, 2-, 4-, and 8-h retention interval, compared with wake intervals of the same length. Two subjects (H. and Mc.) participated in this classic study by Jenkins and Dallenbach. For each data point, each participant completed 6–8 trials, with the different retention intervals performed in random order (Rash et al. 2013). A time dependency of the effects of sleep on memory formation is indicated by studies showing stronger effects for sleep occurring shortly after learning than for sleep at a later time. For example, sleep occurring within 3-h after learning vocabulary was more beneficial than sleep delayed by more than 10 h. Furthermore, recall of word pairs after 24-h was better when sleep occurred immediately after learning than after a day of wakefulness.Whereas initially it was commonly assumed that sleep improves memory in a passive manner, by protecting it from being overwritten by interfering external stimulus inputs, the current theorizing assumes an active consolidation of memories that is specifically established during sleep, and basically originates from the reactivation of newly encoded memory representations (Rash et al. 2013). Maquet and colleagues (Maquet et al. 2000) led first experiments to mark out the activation of brain in learning using PET. Although there have been plenty of current studies on the evidence of reactivation of the brain using PET, fMRI, and EEG, higher resolution images will be needed to determine when and where reactivations occur. 

Conclusions

There’s no deny that sleep is fundamental for memory formation, as proved by studies down recently, which showcased significant enhancements in implicit memories and episodic learning in SWS and REM respectively, syllable learnings being the most evident.  However, there’s still great needs for higher resolution images to further decipher the exact mechanisms of latest discovered reactivations during sleeping.  

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About the author

Ashley Qian

Ashley is currently a Junior at the Wuxi Big Bridge Academy.

The post Brief Review of Sleeping to Enhance Memory Consolidation appeared first on Exploratio Journal.

Abstract

As an innovative way to target B cell malignancies, the chimeric antigen receptors (CARs) therapy uses patient’s cells and reengineers them with a T cell receptor, enabling them to identify CD-19 antigens and eliminate tumors. However, the problem of cytotoxicity and tumor relapse exists within the CARs therapies. To address these limitations, a new generation of CARs, T cell receptor fusion constructs (TRuCs), to treat cancer diseases have been developed. Unlike CAR-T cells, which do not integrate anti-CD19 as part of T cell receptor (TCR), TRuC-T cells incorporates fusion constructs into functional T cell receptors. Using quantitative techniques such as Fluorescence-activated cell sorting (FACS) and Blue native PAGE, researchers have reported that TRuC-T cells exhibit higher levels of activated signaling proteins compared with CAR-T cells. In both vitro and in vivo models, TRuC-T cells showed a higher efficacy than CAR-T cells in killing lymphoma and leukemia tumors. They also showed a significantly lower level of cytokine release and lower risk of tumor relapse after the treatment than CARs. As a new generation of cancer treatments, TRuC-T cells carry the prospect of treating diseases in an efficacious way with fewer side effects.

Keywords: cancer cells, tumor cells, the chimeric antigen receptors (CARs), T cell receptor fusion constructs (TRuCs), 

Introduction

Cancer, a disease that involves abnormal cell growth through uncontrolled mitosis and with the potential to invade to other parts of the body, is one of the most deleterious and dangerous threats to people’s physical health. Propagating in all parts of the human body such as the lymph system as regular cells need to divide through mitosis, cancer cells cause detrimental effects by keeping old cells from dying and interfering with daughter cell functioning. In 2018, there was an estimated 18.1 million new cancer cases diagnosed and 9.5 million cancer deaths around the globe (National Cancer Institute, 2020). Indeed, the number of cases and deaths are expected to rise to 29.5 million and 16.4 million by 2040, which call for a strong need for immunologists and biochemists to work out a better therapeutic solution. In August 2017, CAR (chimeric antigen receptor) therapy, which reprograms the immune system by engineering the T-cell receptor and targeting CD19 on the surface of cancer cells, first demonstrated impressive response to aggressive lymphomas. However, it has been accompanied by seriously harmful side effects such as cytokine release syndrome (CRS) and neurotoxicity. A considerable proportion of patients treated with CARs also relapsed.

Here, I discuss the development of the TRuC-T cells (TCR Fusion Construct T cells), their unique design and their high efficacy in the treatment of B cell malignancies. TRuC-T cells entered the clinic in 2018, killing tumor cells more efficaciously than CAR-T cells but with a significantly lower level of cytokine production. In addition, they exhibit potent anti-tumor activity in both liquid and solid cancer models, while the response seen in solid tumors from CAR-T cell therapy are less robust. This paper will discuss the effect of TRuC-T cells on cancer therapy in the following parts: TCR design, TCR composition, TCR efficacy in vitro, TCR activation, and TCR efficacy in vivo. The research on TRuC-T cells has a prominent significance in exploring current ways to cure cancer diseases and contributing to the improvement of people’s health all over the world.

Design of TRuC

T cell receptor fusion constructs effectively attach anti-CD19 to TCR complexes enabling them to recognize tumor surface antigens (Baeuerle, 2019). As shown in figure 1, there are four essential parts in TRuCs: EF1α, anti-CD19, TCR subunits, and GFP, between which linker and signal peptides connect individual domains. EF1α acts as a transcriptional promotor to enhance TRuC protein production. Anti-CD19 comprises two low and high domains which target antigen CD19 and induce immune response in the body. They are interconnected with G4S (G-quadruplex secondary structures) that allows fusion protein flexibility and also allows domains to come together. In TCR subunits, ECD, TM, and ICD respectively represent extracellular domain, transmembrane domain, and intracellular domain, all of which contributes to the activation of T cells in response to CD19. T2A is the cleavage site where GFP is cleaved and detected as a sign of successful TRuC activation. 

To test TRuC assembly on individual TCR subunits, anti-CD19 was attached to each TCR subunit. There are five different kinds of TRuC: TCRα, TCRβ, CD3γ, CD3δ, and CD3ε. “All subunits are type I membrane proteins but CD3ζ have extracellular immunoglobulin (Ig) domains” (Baeuerle, 2019). Changes in the arrangement of anti-CD19 can regulate the activity of TCR not only in surface expression but also in function. Of note, two scFv (single-chain variable fragment) are fused to CD3ε while only one scFv is fused to other units in TCR, which affect the efficacy of TRuCs and will be discussed in the following sections. 

The researchers use the technology FACS (Fluorescence-activated cell sorting) to show the expression of all five TRuC variants, and of 28ζ CAR, BBζ CAR, and linked GFP. It measures the shape and size of the cell and quantifies surface molecules and fluorescence. The y-axis represents anti-F(ab’)2 antibody recognizing the murine scFv framework. The x-axis represents GFP, which makes sure that the engineered genes work and indicates whether the TRuC protein is at the cell surface. Higher GFP amounts indicates that the engineered TRuC DNA constructs are being expressed in destination cells. As shown in figure 1c, the ε-TRuC exhibits the highest proportion 83% of T cells with anti-F(ab’)2 and GFP among five TRuCs. The other four vary greatly between 9% and 57%, which reflects the differences in efficiency of different scFv fused onto the TCR. As the second generation of CAR-T cells, BBζ CAR express a higher proportion on the T cell surface than any individual TRuC. Yet 28ζ CAR exhibit a lower expression than most TRuCs. 

Consistent with FACS analysis, ε-TRuC and BBζ CAR have the highest F(ab’)2 mean fluorescent intensity compared with other signaling units. However, a big difference in MFI occurs in two individual donors despite the fact that both of them are inserted into the same T cell receptor. This means that there are discrepancies between individuals, so TRuCs and CARs will have different expression levels in different individuals. Another point worth noting is the vector control in this graph: without the scFv units fused to the TRuC or CAR, the F(ab’)2 MFI are still in a high amount, which reveals that the signaling units TCRα, TCRβ, CD3γ, CD3δ may not be helpful to enhance the mean fluorescent intensity. Additionally, the scale of the data is a bit unclear because there are far more numbers between 1000 and 10000 than that between 10 and 100. It is inappropriate to put them together as causing confusion.

TCR composition

After the incorporation of TRuCs, cells were lysed and TCR complexes were separated by Blue native PAGE. They were stained using an anti-CD3ζ antibody. “0” denotes the natural TCR complex, “1” and “2” denote TCR complexes with one or two TRuCs, respectively (Baeuerle, 2019). Blue native PAGE is a technique used for isolation of protein complexes and measurement of native protein masses without protein complex denaturation. In Figure 2a, the y-axis represents the measure of molecular weight or mass in kDa (kilodalton). Some are natural T cell receptor, while others are engineered TRuC receptor. The minimum mass of protein of natural TCR complex is 440 kDa. There is a direct correlation between the quantity of protein and how dark it is. According to the extent of stain darkness, the TCR complex with two α-TRuCs has the highest molecular mass with protein complexes measuring 660 kDa. Following close are TCR complexes with ε-TRuCs and β-TRuCs. Interestingly, natural vector control has a higher amount of protein than the cell with δ-TRuCs. 

Researchers then used immunoprecipitation to show the amount of individual TRuC proteins in TCRs. “They were immunopurified using the anti-F(ab’)2 antibody, and then separated by reducing SDS-PAGE. (Co)-purified proteins were detected using the described antibodies by western blot” (Baeuerle, 2019). Different from figure 2a, TRuC variants here have similar amounts of protein and use different specific antibodies. For α-TRuC, they use corresponding anti-TCRα to show its molecular size 95 kDa. For β-TRuC, they use anti-TCRβ and identify its size as 80 kDa. For 28ζ and BBζ CAR-T cells, they both use anti-CD3ζ to show it size at 72 kDa. The overall result is that each TRuC and CAR shows its expected molecular size.  

What researchers do next is to test the function of the T-cell receptor, which determines their sensitivity to different amounts of peptides. The higher mean fluorescent intensity it has, the more sensitive the T cell is. If TRuC or CAR T cells are too sensitive, they will be activated without any stimulation and be always on, which will finally lead to the self-destruction of the T cell. As shown in figure 2c, the MFI increases as the H-A peptide amount increases, indicating that they are becoming more active. It is worth noting that both of the CARs are easily activated, probably due to its strong tonic signaling. Also, the ε-TRuC exhibits equal mean fluorescent intensity with the vector control, meaning that TRuCs do not interfere with normal TCR function, while CARs impair a lot through increasing sensitivity.

TCR efficacy in vitro  

To test the TRuC and CAR efficacy, researchers use two approaches: one was by percent lysis of luciferase-expressing Nalm6 cells after 24 h; the other was by means of an impedance-based assay using CD19-expressing HeLa cells to study the kinetics of cell lysis (Baeuerle, 2019). Luciferase is a bioluminescent enzyme, which in this case serves as reporter of successful lysis. Fig. 3a represents the tumor cell lysis of luciferase-expressing Nalm6 cells. The three blue dots are the biological replicates and means of the lysis percent. Error bars are also included in the graph. It is easy to see that there are stark differences in the lysis percent between vector control and two TCRs. The vector control only lyses about ten percent of tumor cells, while the most effective TCR, BBζ CAR-T cells, exhibits 65% tumor cell lysis. Among the TRuCs, the ε-TRuC demonstrates the highest tumor cell lysis, with 60% cell lysis. α-TRuC’s efficacy in tumor cell lysis is less robust than the other TRuC subunits, with 25% lysis.

As mentioned in the previous paragraph, this is the other approach that uses CD19-expressing HeLa cells to study cell lysis. HeLa cells are tumor cells, which are represented on the y-axis as normalized cells. After T cells were added, the tumor cell index decreased quickly and finally declined to zero after 120 hours. The fact that normalized cell index increased for vector control and cells without T cells insertion demonstrates the effectiveness of TRuC and CAR to lyse tumor cells. Among all TCRs, the most efficacious was BBζ CAR-T cells, in accordance with the result in tumor cell lysis using luciferase. The one with slowest rate of decreasing normalized cell index was β-TRuC.

Researchers selected three TCRs, ε-TRuC, 28ζ CAR, BBζ CAR, to examine the donor variability in tumor cell killing. It is clearly shown in fig.3c that donor variability only slightly affected the efficacy of TCRs in decreasing normalized cell index. All three patients’ normalized cell index successfully declined to zero after 120 hours. The cytokine release after the T cell adding and treatment is discussed in the next part. 

Accompanied with T-cell treatment are cytokine production and secretion. One of the most harmful side effects of CAR-T cells is the cytokine release syndrome (CRS), which is further illustrated in these graphs. Compared with TRuCs, CARs release far more IL-2, IFNγ, IL-4, IL-13, and TNFα cytokines. Specifically for IL-2, when no TCRs are added, no cytokine release was observed. After the incorporation of γ-TRuC and ε-TRuC, there are approximately 4000 to 5000 pg IL-2 release, while after 28ζ CAR was inserted into the cell, the cytokine release was about 22000 pg. Thus, smaller amount of cytokine release is one of the advantages TRuC receptors have over CAR-T cell receptors, which prevents patients from suffering from neurotoxicity and other diseases.

TCR activation and signaling

The researchers then investigated on the activation of T-cell receptors by quantifying the amounts of CD69⁺ and CD25⁺ using FACS. The distribution of these two positive cell surface molecules, shown in fig. 4a, corresponds to the percentages of T-cell activation. ε-TRuC had the most significant amount of signaling among all TRuCs, displaying similar activation levels to BBζ CAR. Both ε-TRuC and BBζ CAR had 65% of CD69⁺ and CD25⁺ signaling, while that of α, β, δ-TRuC were much lower, exhibiting activation between 20 to 30%. Overall, both TRuCs and CARs showed less expression of CD69⁺ upon activation, but comparatively higher expression of CD25⁺, possibly due to their different TCR units. 

Researchers then looked for the phosphorylation of intracellular signaling proteins and found that both CAR-T and TRuC-T cells induce intracellular signaling protein phosphorylation, but to different extents. They co-cultured T cells with CD19+ Raji cells at a 10:1 effector-to-target ratio for 30 min (Baeuerle, 2019). The phosphorylation of intracellular signaling proteins upon activation induced a change in charge, in turn causing a conformational change. The y-axis represents mean fluorescent intensity, which was used for detecting the amount of signaling per cell. For phosphorylation of CD3ε, the TRuCs displayed more than double the phosphorylation than the CARs. While for phosphorylation of LAT (Linker for activation of T cells) was an order of magnitude lesser, the signaling of TRuCs and CARs was measured and indicated that intercellular signaling is activated in both TRuCs and CARs upon stimulation.

Using FACS again, the graph shows T cells in GFP and phosphor-CD3ζ after 5 days expansion in the presence of IL-2 and anti-CD3/anti-CD28-coupled Dynabeads (Baeuerle, 2019). ε-TRuC had low levels of activated phosphor-CD3ζ, while the two CARs had slightly higher activation, while all their GFP amounts displayed 46.7%. In summary, TRuC-T cells and CAR-T cells had differing intracellular activation and signaling events. 

TCR efficacy in vivo

To test the anti-tumor activity of TCRs in liquid tumor model, researchers subcutaneously inoculated lymphoma and leukemia cells into mice. After the tumor cells began to grow in mice, they injected them with TRuC-T cells and CAR-T cells to treat them and test the efficacy of killing tumor cells. There was also a group of non-transduced mice used as a negative control. In NT group, the tumor volume increased in an exponential way: it nearly quadrupled after 20 days and kept increasing as the study progressed. However, the situation turned way much better when T cells were present. For ε-TRuC, when 1×10⁸ T cells were injected, the tumor volume kept close to zero and no tumor could be detected at the end of the study. While when 1×10⁸ CAR-T cells were injected into the mice, the tumor volume increased slowly. Thus, TRuC-T cells are more effective than CAR-T cells at killing tumor cells in vivo. Another advantage TRuC-T cells displayed was that the survival rates of mice after injecting them were almost 100%, while 20 to 30% of mice injected with CARs die after 20-30 days, highlighting the cytotoxic effects of CAR-T cell therapies. Also, as the number of injected T cells was decreased, the effectiveness of tumor cell elimination decreased as well: when 5×10⁴ T cells were injected, neither TRuC nor CAR could reduce the tumor volume over 40 days. 

Immunocompromised NSG mice were injected with 5 × 10⁵ Raji-LUC cells into the tail vein of mice 5 days prior to treatment with 1 × 10⁷ non-transduced or engineered T cells (Baeuerle, 2019). For ε-TRuC, the luminescence rose, then decreased, and finally stayed constant, corresponding with its tumor volume in fig. 5a. The two CAR-T cells’ luminescence increases more than with TRuC: although it decreased at first, it then relapsed quickly, meaning that the tumor grew post treatment in CAR-treated mice. 

In the end, researchers wanted to investigate the effectiveness of TRuC-T cells against solid tumor models. They focused on specific domain for BCMA (B cell maturation antigen) and IL13Rα2 (interleukin-13 receptor α2). As shown in fig. 6a, almost 100% of tumor cells are lysed and the tumor growth is inhibited no matter what kind of TRuC was fused with BCMA. For HeLa-CD19, the TRuCs had a low effect in tumor cell lysis, having small difference with the vector control.

RMPI 8226 is another multiple myeloma cell line, which is used here to test its anti-tumor activity. ε-TRuC, γ-TRuC, and β-TRuC successfully reduced tumor volume to zero after 40 days. However, the experiment cannot assure that the tumor may relapse after these 40 days.

Researchers lysed U251 glioblastoma cells using IL-13Rα2-specific ε-TRuC-T cells at various effector-to-target ratios. When the effector-to-target ratio was larger, the percentage of tumor lysis tended to increase. In fig.6a, the effector-to-target ratio was 1:1 and had near 100% tumor cell lysis. By contrast, when the ratio was 1:1 in IL-13Rα2, the tumor cell lysis was only 35%. This shows that IL-13Rα2-specific TRuC cells are less efficient than BCMA TRuC cells in inducing tumor cell lysis, despite having similar effects on tumor growth.

As TRuC-T cells were shown to have efficacious tumor cell lysis effects and anti-tumor activity, they also released cytokines IL-2 and IFN- γ. Comparatively, the cytokine IFN- γ was released at higher levels than that of IL-2, about 20 times, but the unit is pg/mL, so the amount was actually lower than that released by CAR-T cells. The question of relapse is answered in the graph on the right: after 40 days, the tumor volume kept constant at zero and the trend suggested that their effects would be continual rather than only for a period of days,

Conclusion

TRuC-T cells are a generation of more effective CAR-T cell therapies that use fusion constructs to incorporate anti-CD19 into functional T cell receptors, as opposed to using chimeric T cell receptors. They are effective in vitro, as well as in vivo towards both liquid and solid tumors. TRuCs induce roughly half the amount of cytokine release compared to CAR-T cells and present a new generation of engineered T-cell receptor anti-cancer therapies, with promising efficacy and a lower risk of cytokine release syndrome (CRS). The research on TRuC-T cells plays a significant role in exploring current ways to combat cancer diseases improving people’s health all over the globe.

Bibliography

“Cancer Statistics.” National Cancer Institute, www.cancer.gov/about-cancer/understanding/statistics.

Baeuerle, Patrick A., et al. “Synthetic TRuC receptors engaging the complete T cell receptor for potent anti-tumor response.” Nature communications 10.1 (2019): 1-12.

About the author

Yicheng (Ethan) Ding

Yicheng is strongly interested in biology, especially molecular biology related to human bodies, such as proteins, DNA, and tumors. This inspiration is obtained partly due to the COVID-19 pandemic, which raises our concern and his want to improve human disease treatments. In his spare time, Ethan usually plays table tennis and plays basketball with friends, as well as watching TV programs such as the Big Bang theory.

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