EMBSDiaries

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Stem Cell-Based Therapy for COVID-19

The Novel Corona virus has become a global pandemic since patients were first detected in Wuhan, China in December 2019.As of September 7, 2020, the Novel Corona virus has infected 2.73 Crore people in the world. It causes mild respiratory tract infection, cough and fever in most of the patients. However, the majority of patients are accompanied by pneumonia. As of now, we don’t have any vaccine to deal with this global pandemic. Current studies suggest that there exists cytokine storm in COVID-19-infected patients, due to which some of the patients will develop acute respiratory distress syndrome and multiple organ failure, sometimes even death. 

Lung injury caused by COVID-19 poses a major clinical management challenge because there is no specific treatment/drug that has been approved. Various researchers offered an alternative promising therapy for COVID-19, that is, Mesenchymal Stem Cell transplantation.

Mesenchymal Stem Cells (MSCs) are a well‐characterized type of adult stem cells with ideal differentiation, proliferative and immunomodulatory properties. MSCs regenerate and repair damaged tissues by secretion of various bioactive molecules to stimulate resident cells. MSCs are well known for its promising anti‐inflammatory properties. Various studies have shown that the immunomodulatory properties of MSCs help in modulation of activation, proliferation and function of various immune cells and thus are able to alter the innate and adaptive immune responses. MSCs were first used in China and were proved effective against COVID-19. Adult stem cells can be isolated from neonatal sources such as cord tissue, cord blood, placenta and menstrual blood as well as adult tissues such as adipose tissue, bone marrow and peripheral blood. MSCs do not have any ethical issues and are available for autologous or allogeneic use. Autologous stem cells are usually preferred for stem cell‐based therapies for COVID-19. There are three types of COVID-19 patients- Critically ill young patients, Critically ill older patients and those patients who are at high risk of infection due to comorbidities. Stem Cell therapy should be used accordingly on these patients. The selection of a suitable stem cell source and type is important for the treatment of COVID‐19 patients. MSCs are multipotent and could be cryopreserved for multiple uses and thus are readily available any time. 

References:

https://www.liebertpub.com/doi/10.1089/SCD.2020.0071#:~:text=In%20this%20commentary%2C%20we%20offer,%2C%20China%2C%20in%20December%202019.

https://stemcellres.biomedcentral.com/articles/10.1186/s13287-020-01699-3

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Unlocking the Anti-Aging potential of Sirtuins

The science of aging has made an enormous progress in the last few years, with human trials about to begin in the near future. Scientists are trying to shift the attention of the medical community from optimising lifespan to optimising health span. According to the biological clock, every individual is aging; a teenage person is aging, young infants are aging, even in the womb we are aging. The study of sirtuin proteins made a real breakthrough in the field of anti-aging by resetting the aging clock of the body.

Sirtuins have risen to scientific prominence in aging and age-related diseases such as diabetes, cancer, neurodegenerative diseases and cardiovascular diseases. Studies revealed that the broken chromosomes disrupt the structure of the DNA and the cells start to lose their function as well as identity. And ultimately, the outcome of losing cellular identity is aging. Sirtuins play a vital role in sustaining genome integrity. They take part in maintaining normal chromatin condensation state, DNA damage response and repair, modulating oxidative stress and energy metabolism. Sirtuins can only function in the presence of (NAD+) nicotinamide adenine dinucleotide, a coenzyme found in all living cells. In mammals, there are seven sirtuins (SIRT1–7) that occupies different cellular compartments.

Several lines of evidence suggest that benefits of calorie restriction are mediated through sirtuins. Trials in non-human primates and humans have indicated that sirtuin-activating compounds (STACs) and NAD+ precursors that improved organ function, physical endurance, disease resistance and longevity may be safe and effective in treating inflammatory and metabolic disorders. Sirtuin also play a role in memory formation by modulating synaptic plasticity. Hypothalamic functions that affect endocrine function and circadian rhythmicity are regulated by SIRT1. Sirtuins (SIRT1) have a dual role in cancer, functioning as tumour suppressors or as an oncogenic factor, depending on the type and stage of cancer. Since the NAD+ levels decline with age, hypothesis suggests that deficiency of NAD+ may be the primary factor related to the SARS-Cov-2 disease spectrum and the risk for mortality. SIRT1 inhibitors can be an effective solution to treat Novel Coronavirus, based on the research on reduction of many virus growth and replication. These inhibitors are associated to the halt of cells apoptotic response. In addition, SIRT1 reduce ACE2 activity, the receptor which Coronavirus uses to enter in the host cells. 

Future studies should indicate whether modulation of sirtuins could have implications for cancer treatment. However, the mechanism of sirtuin proteins are very complex and not entirely understood yet. These advances have demonstrated that it is possible to rationally design molecules that can possibly extend the health span in humans. The ongoing quest to discover and develop safe and potential sirtuin-activating compounds to alleviate multiple aging-related diseases and the use of such compounds in clinical trials is discussed in the context of the challenges that lies ahead to reach their full potential in medicine. As the sirtuins field continues to expand, this leaves scope for incredible research opportunities into how activating sirtuins with NAD+ precursors can lead to more exciting discoveries.

Citations:

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5514220/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3174263/

https://www.youtube.com/watch?v=9nXop2lLDa4 

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Nanotechnology for COVID19

We are all aware of the pandemic situation going on right now. Ever since this has started there has been many researches going on about how to prevent or cure this disease. And one such research is if we can use nanotechnology to help us fight against this dreadful covid-19. The perspectives of implementation of antiviral nano systems by experts to fight Covid-19 are still being envisioned. 

In the structure of this coronavirus, there are 4 proteins – Spike, envelope, membrane and a nucleocapsid. The spike protein is responsible for attaching itself to the host cell. It consists of a receptor binding domain which recognizes the ACE2 receptor present in the lungs, heart, kidney etc. It has a 20% more binding capability to SARS which can be why it spreads easily among us. Many nanomaterials have been developed, let it be polymers to nanoparticles, oligomers and liposomes. But the clinical transition is inhibited by the fact that when diluted, these compounds lose efficiency as the virus-compound complex dissociates leaving the viruses to resume their replication cycle. Recently, there has been a research where this problem was overcome by synthesizing nano particles that after binding are able to inhibit viral infectivity by damaging the virion by refueling it with broad spectrum antiviral drugs. This would help in blocking the spike protein interaction with the ACE2 receptor. But this is hesitant to be done as receiving these drugs for a prolonged period can be dangerous and the infected person will be more weakened. Scientists are trying to fix this problem in a way that won’t hurt the patients. 

Currently, for diagnosis, the technique used to detect covid-19 is using real-time reverse transcription-polymerase chain reaction (rRT-PCR), which detects RNA from SARS-CoV-2 and provides accurate results. However, the disadvantage to this sophisticated equipment is the need of a laboratory with biosafety of level 2 or above. Other than this it also takes upto 3 days to acquire the results. This is a time-consuming method and extremely a disadvantage to public health emergencies. Various other testing kits have also been developed but they were found to be inaccurate. This is where nanotechnology can help us to provide solutions. For example, nano diagnostics depend on binding between nanoparticles and the interested target molecules to produce a signal which allow the detection of biomarkers or pathogens. This allows the use of smaller devices and a platform to make use of nanoscale properties available from interactions between the surface and biomolecules. The main advantage of using nano diagnosis is that the device used would be small (hand held), stable and highly accurate which would be easy for rapid testing. 

We can say that nanotechnology has much to offer in the fight against covid-19 and has been very successful in treating various other diseases in the past by its advanced combating tool in drug designing as well as in drug targeting and better virus inhibition. Even if we do not feel like it now, we can say there will be a better tomorrow.

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The promise of regenerative medicine

We all know that Lizards can regrow a lost tail. Starfish are famous for their ability to regenerate limbs. Salamanders and Newts can completely regenerate heart tissue and entire limbs following tissue injury at any stage of their life. But what about Humans? So far, the Liver is the only organ in the body known to regenerate. It can replace damaged tissues with new cells. What happens if any other organ or body part is permanently damaged? Can we turn back the clock and replace worn out or damaged body parts with completely new ones? This where Regenerative Medicine comes into play. 

Regenerative Medicine aims to repair, replace or regenerate human cells or tissues that have been damaged due to disease, trauma or congenital defects. It is a multidisciplinary field that involves Tissue Engineering, Cell and Immunomodulation Therapy and Production of Artificial limbs and organs. A combination of scaffolds, stem cells and growth factors must either replace the damaged tissue and function as the original tissue, or stimulate the regrowth of the original tissue. The cells used can be Autologous (from the same patient) or Allogenic (from a donor). Carticel, is the first FDA approved biogenic product that treats focal articular cartilage defects using autologous chondrocytes. The chondrocytes are harvested from the articular cartilage, expanded ex vivo and is implanted at the site of injury. GINTUIT is a allogenic product used to treat mucogingivial conditions in adults. 3D Bioprinting is a technique where Bioinks, generally a combination of cells and growth factors, are printed layer by layer to create tissue-like structures that can mimic natural tissues. In 2019, Israeli researchers constructed a rabbit sized, bioprinted heart out of human cells.

Umbilical cord blood was previously considered as a waste material after childbirth. Recent studies show that Umbilical Cord Blood-derived Hematopoietic Stem Cells(UCB-HSCs) can generate RBCs, WBCs and platelets and the Umbilical Cord Blood-derived Mesenchymal Stem Cells (UCB-MSCs) are capable of giving rise to mesenchymal lineages such as bone, cartilage and fat. Thus the UCB shows great potential for the treatment of cancer, Type 1 diabetes, blood and neurological disorders and immune deficiencies. The Coronavirus has adverse effects on both the respiratory and immune system. The immunomodulatory effects of MSCs, which may assist in inhibiting cytokine storm and lung inflammation, are of particular interest for COVID-19 therapy. In the hopes of finding a cure for ALS, researchers are also doing studies on the ability of the MSCs to protect our neurons. Current stem cell therapies for ALS focus on keeping the neurons alive for as long as possible, but imagine if we could generate new neurons to replace the old ones and make new connections in our brain.

Imagine a future where no one waits on an organ transplant list!

Imagine a future where if you are disfigured in an unfortunate accident, a pill could change the electrical charge at the site of the injury causing your toes to regenerate!

Imagine a future where, if you suffer from heart failure, a new organ could be grown on a cadaver heart Scaffold using your own stem cells. And with this new heart, you could get back to running!

It may sound like science fiction but it could soon become a science fact!

This is the promise and future of Regenerative Medicine.

Citations:

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7305935/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4664309/

https://www.youtube.com/watch?v=e0vKOYQUmgg

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Tiny particles might end the quest to solve big problems!

Nanomedicines is a very young branch of science. It has come into the picture only since the 1990s. Wonder what made researchers go down the nanoscale when we already had various drug development systems? The basic flaws in the conventional drug delivery system provided the spark for the emergence of a nano-drug delivery system.

 When we swallow a pill, its contents are constantly lost or tampered. This may be because of the acidic environment of the stomach, detoxification properties of the liver, or due to the presence of proteins and enzymes in the bloodstream which may bind to the drug and change its physiological properties. As the loss at these barriers is very high, a massive dose is required to compensate for this loss. According to David Anderson, a neurobiologist, current medication is like pouring a can of oil all over your car engine. Some of it will dribble into the right spot, but most of it is wasted, and some even does harm. This is the reason why chemotherapy patients lose hair. The drugs are so toxic that they not only affect but also kill normal healthy cells.

These problems can be dealt with if the delivery system of these drugs is altered. This is where nanoscience emerges as a potential solution. Nanomedicines are manufactured on a scale of 10^-9 m and can be even smaller than a virus! Due to its peculiar size, it can exude properties of both quantum and Newtonian mechanics thereby adding to the number of benefits we can avail. Moreover, its surface to mass ratio is exceedingly large, hence, it has the ability to bind, absorb, and carry various compounds. Coating them may also be necessary to prevent agglomeration. This can be done with various substances, such as natural, synthetic, inorganic, etc. To reach only the target site certain compounds are added which function as "Molecular keys". This technology is being harnessed mostly for the treatment of brain cancer as it is one of the most difficult malignancies due to the presence of blood brain barrier which tightly regulates the movement of molecules and ions between blood and brain. Nano-medicines recognize specific markers on cancer cells and their size opens the potential for crossing various biological barriers thereby increasing their efficacy. Anti-cancer drugs such as loperamide and doxorubicin bound to nanomaterials have been shown to cross the intact blood-brain barrier and released at therapeutic concentrations in the brain. In most cases, resistance develops when cancer cells begin expressing a protein, known as p-glycoprotein that is capable of pumping anticancer drugs out of a cell as quickly as they cross through the cell's outer membrane. New research shows that nanoparticles may be able to get anticancer drugs into cells without triggering the p-glycoprotein pump. The researchers studied in vivo efficacy of paclitaxel loaded nanoparticles in paclitaxel-resistant human colorectal tumors. Paclitaxel entrapped in emulsifying wax nanoparticles was shown to overcome drug resistance in a human colon adenocarcinoma cell line (HCT-15).

Many questions are still raised on the safety and cost of the nano-drug delivery system. Therefore, it remains irrefutable that the development of more sophisticated designs and further understanding of the properties at the nanoscale are required to yield such advanced therapies.

Citations:

·       https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2222591/

·       https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2527668/

·       https://www.youtube.com/watch?v=0wFwXUhHu5c

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AI POWERED DATA ANALYSIS FOR CORONA VIRUS EPIDEMIC MONITERING AND CONTROL.

As the first few cases emerged in Wuhan, around the 31st of December information had reached the WHO. Early stages showed pneumonia like syndrome and had heavy similarities with the SARs virus. Whenever such a situation arises, we have very less or no clue at all that this might turn into a global disaster. By the time the severity and destructive strength of the virus was detected it had already flown to various countries and had started the pandemic. As an early protective measure government across the world had stopped the air transport facilities to a certain extend and had advised citizens to stay quarantined. But the big picture here is that these implemented procedures are no fool proof solutions to tackle the situation.

 Now to tackle such extensively spreading diseases or situations it would require heavy data rendering and processing artificial intelligence system working at various levels, that are able to predict and foresee the damage the disease can cause and design solutions to deal with it. If the AI system were to predict the intensity of the spread rate at a very early stage and proposed the right lockdown period, the pandemic control would have been a success. But while the design of such an artificial intelligence system that promises on predicting a global disaster, it would have to be very accurate as it is responsible for many lives. But building a 100% accurate artificial intelligence model is rarely possible, but AI models with slightly reduced accuracy rates have been announced in the recent times. Alibaba was supposed to release an AI model with about 96% accuracy which would categorise CT scans of pneumonia patients as infected and non-infected. Similarly, US military had announced an AI algorithm that could predict infection in non-symptomatic patients before the signs are visible with an accuracy of about 85%. Canadian company blue dot said to have observed signals of a potential pandemic long before the actual surge and had warned the officials well before hand. These signals where picked up by sophisticated AI models. AI has the capacity to work with enormous amounts of continuously updating data, and to render it and to produce meaningful conclusions. 

The interesting thing to note here is the possibility of detecting a potential pandemic from the macro data collected from the society from invariably everywhere. And this would not produce a security threat as these macro data collected from the user serves the purpose of understanding the mood and flavour of the society. Micro and microdata would include social media posts, amount of people visiting the doctor, symptom details, cash flow details and its rate, amount and places of ATM swipes, flight and transport details. These data could be integrated and fed into an AI model which according to the given data could analyse the mood of a certain society and predict the possibility of an upcoming pandemic. Sudden changes in patterns of domestic and international flights, direction and intensity of traffic flow, increase in procurement of medical supplies, retail patterns and increasing sentiments of a certain disease on social media suggests a peculiar event occurring in the community. Now there will be multiple layered AI model that would be used to first predict the possibility of a potential disease then further layered AI would be used to predict the damages it could cause and further layered AI would be used to provide a suitable defence mechanism to the problem.

In multi-layered complex AI algorithm once the chance of a potential pandemic is observed it starts working on the fate of covid 19 patients. The model would be fed with medical data containing all the symptoms that are shown. Now the algorithm would decide the fate of the patient with the symptoms mentioned. The patient could show various symptoms but may not necessarily be in fatal condition, but a patient showing only a few symptoms could turn serious. Now the AI model did not find most symptoms leading to a confirmed fatality, but it was able to narrow down 3 symptoms that ensured serious infection with heavy accuracy. Increase in haemoglobin levels, muscle aching(myglia) and the subtle fluctuation of presence of enzyme called alanine aminotransferase in the liver ensured the patient to be seriously infected. The prediction model also involved data feeding from a swarm of people and later analysing using probabilities, there is random forest model where all patient details are fed and different optional trees are created and finally the most accurate tree is selected that could perform the most accurate prediction of the fate of the covid infected patient.

Now considering the seriousness of the role performed by the AI system it is important to consider that the most accurate model must be used. A separate committee was designated in order to find the most preferable and reliable artificial intelligence model. Now there where 5 different groups of approaches that an AI model could use to produce predictions. Now these groups were evaluated according to their level of complexity, time taken to produce a certain conclusion, accuracy of the prediction is monitored. Clinical surveillance and the predictive surveillance of the patient data is matched and scored for accuracy. There could be basically 3 sets of models, it could be multi input models, parametric models or non-parametric models. Now a set of predefined small data is passed within these algorithms and the accuracy % is matched, now finally in panel selection the winner is selected and invariably the winner produces the most accurate prediction. This method is also known as the GROOMS methodology of selection of suitable AI model from all 5 different groups with predefined sets of characteristics.

Now one of the most important prediction that the AI model will have to make is the spread rate and possible infection probability strength of the virus. These predictions are made using the SIR and SEIR AI model. These are heavily mathematically modelled data which would finally produce a destined result that would predict the possible rate of spread of the virus in a particular community. Now this prediction necessarily would have very little accuracy as this prediction solely relies on the historical spread rate data that is fed into the model. But in reality, the spread of the virus would not follow a specific trend, we are just able to replicate the previous data and also considering the demographics, living conditions of people, the possible rates or its increase could to a certain extend be predicted. The SIR model relies on patient population data and its changes with time. It takes into account three parameters, the people with possibility of infection(S), infected people from the pool of people who had probability of being infected(I), infected and later on recovered people(R). now using these three data a probability calculation is estimated that could show the probability of infection in that particular area and similar demographics. These data when correlated with the surge rate we are able to produce a satisfactory curve on the increase of patients in the upcoming months, hence the rate of spread of the disease can be easily predicted. Similarly, mathematical modelling using various other data could produce further accurate predictions and its combination would make the predictions even more reliable. SIR and SEIR AI models help in drawing various analytical graphs and study on the spread in various places and the similarities shown, we could predict the overall infectious nature of the virus across the globe and find reasons that deteriorate its spread which would facilitate in easier solution development.

As we have now seen the process of fighting this covid 19 pandemic, we could anticipate that the modelling of virus pandemic behaviours would be aided by artificial intelligence in the future. It could provide mathematically regulated estimate for the ideal lockdown period that is not too short to facilitate the pandemic to resurface nor too long to harm the economy and be driven into extensive rates of unemployment rates and recession. It could be ensured that the death toll, infected rate, the economic damage, the lockdown period and necessary resources be minimised. And the availability of relief facilities at the exact required places be maximised as we will be able to predict the places with possible extensive increase. The treatment costs would be reduced and would help us choose intelligently the right mixture of preventive strategies for its control.

Overall, the artificial intelligence system rather than just providing a mathematically driven statistical analysis, it simulates the entire pandemic conditions using the bulk of data using super computers to predict with more accuracy. With the bulk of intelligently derived fight back strategies AI could also be deployed in medicine R&D which would ensure faster medical support and hence a faster break from the pandemic. So, these AI models would ensure a completely systematic and strategized fight against any devasting life threatening situation that may arise in the near future and would ensure our readiness against facing the global misery.

Reference:

https://link.springer.com/chapter/10.1007/978-981-15-5936-5_3

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Has Russia found a cure for COVID19?!

The current worldwide upsurge of COVID-19 is becoming a matter of tremendous concern. The spread of novel coronavirus has brought daily life activities to a standstill. And till date, the best way we have to keep ourselves safe consist only of preventive measures. Therefore, many organizations are working towards formulation of a vaccine and we are also getting positive results. Of the 19 vaccines currently in human trial, only two are in final phase-III; one by China’s Sinopharm and other by AstraZeneca and University of Oxford (announced to be most advanced by WHO). Currently, the researchers from Sechenov University, Russia claim to have developed a clinically safe vaccine against coronavirus. However, WHO still lists Russian COVAX in Phase-I of clinical trial.  

Study:

The genomic sequences of coronavirus shows that the S-protein present on the viral surface is the ideal target for vaccine. The concerns for development of an effective vaccine are the prospects of the virus mutating and waning of the antibody response. The infection with human coronavirus does not always produce long-lived antibody responses and thus chances of re-infection are likely. Apart from this vaccines will also have to undergo clinical and safety trial before being approved. 

Theory:

As per the results of preliminary tests, the Russian Vaccine results in an increase in non-specific immunity. The vaccine is administered in two doses and consist of two serotypes (serologically distinguishable strain of microbe) of the human adenovirus, each carrying an S-antigen of the new coronavirus, which enter human cells and produce an immune response. The vaccine showed good results on primates.

Clinical trial:

The COVAX trial began in mid-June. Two volunteer groups between the ages of 18 to 65 were tested. Minor side-effects like fever and headache were observed but these symptoms subsided in 24 hours.

Russian scientists are hopeful to launch world’s first coronavirus vaccine by mid-August.

References: WHO, Times of India, Channel News Asia, The Hindu, Financial Express

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Estimation of Tool-Tissue Forces in Robot-Assisted Minimally Invasive Surgery 

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Estimation of Tool-Tissue Forces in Robot-Assisted Minimally Invasive Surgery

The advent of robots in surgery started in 1994 when the first AESOP (voice-controlled camera holder) prototype robot was used clinically in 1993. AESOP was then marketed as the first surgical robot ever in 1994 by the US FDA. Since then Robot-assisted minimally invasive surgery (RAMIS) has gained immense popularity over the last two decades. Statistics show that more than 50% of errors performed by surgical trainees are due to excessive force. This may often lead to irreparable damage. RAMIS reduces the error percentage of tool-tissue interaction forces significantly, it is much more accurate than an open surgery or laparoscopic minimally invasive surgery. Although it may seem like this approach saves the patient from excessive trauma this method is limiting. This is because the surgeon is not directly controlling the machine. Which means the tool might lose direct contact with the surface of surgery, i.e. loss of tactile information for the surgeon. This entire process of relaying tool-tissue force information to the surgeon is the haptic feedback or force feedback. The tool-tissue interaction forces affect the efficacy of the surgery to a great extent, so it is imperative for RAMIS to overcome this obstacle to reach its full potential. 

This disparity in information is the main reason RAMIS has not reached its apogee. The lack of haptic feedback, tactile sensing, and tool tissue force-sensing contributes to this method’s dubiousness. Several attempts have been made over the years for the sensorization of surgical instruments but even the most of developed sensory systems required to alter the standard shape of the surgical tool (as it may affect the handling of the surgical tool and possibly the amount of tool-tissue interaction forces), are not suitable in terms of size or the installation place, require the filtration of noise signals, or have an unsuitable range of measurement. In addition to that they make the instruments bulky and complicate the process of sterilization. The size of force sensors, and incision ports, the sterilization of tools at high temperature and the disposable nature of surgical tools have so far prevented the integration of end-effector/tissue force sensing in RAMIS. 

Scientists soon understood that sensors are definitely not the way to go.

There have been multitudes of research solutions for this problem. None of the methods seemed to provide a complete remedy. However, a recent research brings forth an answer to this long-lasting issue by proposing a new algorithm to estimate the tool-tissue force interaction in robot-assisted minimally invasive surgery in a way that it does not require the use of external force sensing (sensor-less). This incredible feat was achieved by applying a neural network method to estimate the tool-tissue force interaction during a grasp manoeuvre in RAMIS for future application in providing haptic feedback to surgeons. Its distinctive features reside in the fact that it considers a black box approach regarding the whole mechanism, thus rendering the analysis of the grippers mechanism unnecessary. The proposed method is based on utilization of the current of the gripper-actuating motors as well as a detailed examination of the various stages of a grasping motion. In contrast to existing algorithms in literature, this model does not require external sensors or equipment such as vision systems, predicting sufficiently both small and large forces.

This model was tested online and offline to check its feasibility and feedback system. The results showed that the developed algorithm can estimate the tool-tissue interaction force during the grasp online and could thus allow haptic feedback in robotic surgery to be provided. This model can predict both large and relatively small forces which was an issue in the algorithm developed by Zhao and Nelson (2015). The model developed by Zhao and Nelson used motor current and was the first model to tackle the existing problems of RAMIS without the use of sensors. Their model utilized the Gaussian Process Regression, which unfortunately failed when the target went out of range. This research tactfully handles the problem of GPR not being able to predict the outcomes when the target goes out of the range of the dataset. This problem was combated with the help of neural networks. This approach was inspired by Yu et al. (2018) who proposed a cable tension based method to estimate external forces and utilized a back propagation (BP) network to estimate resistance parameters such as friction to aid in the force estimation. Along with Yu, Aviles et al. (2015, 2015) also inspired this algorithm with his seminal paper on combined vision based methods with recurrent neural networks to estimate tool-tissue interaction.

Source:

https://www.frontiersin.org/articles/10.3389/frobt.2019.00056/full

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2699074/

https://asmedigitalcollection.asme.org/medicaldevices/article-abstract/9/4/041012/376819/Sensorless-Force-Sensing-for-Minimally-Invasive?redirectedFrom=fulltext

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FabiFlu

Over nine million people have tested positive for COVID-19 so far, out of which, 4,25,000 are Indians. With the advent of such a disastrous pandemic, the need for it’s treatment becomes all the more important.

Glenmark Pharmaceuticals is a research-led pharmaceutical company in India which has received approval for officially manufacturing and marketing Favipiravir, an antiviral drug to be used for treatment of mild to moderate COVID-19 patients. After this approval, Favipiravir has become the first approved oral medication for the treatment of COVID-19 in India. This drug shall be available by the name Fabiflu and is priced at Rs, 103 per tablet. Glenmark has also become the first Indian pharma company to have received the approval for conducting phase 3 clinical trials on COVID-19 patients with mild to moderate symptoms.

Considering a minimum of two strips per patient, Glenmark said it will be able to provide Fabiflu to about 82,500 patients in the first month itself. They will then scale up and meet the healthcare needs of the country.

It is an oral product which means it does not require hospitalization. This will reduce the burden on the hospitals and it’s staff to some extent. The medicine is said to result in the rapid reduction in viral load within four day and provide faster symptomatic and radiological improvement.

Following are certain drugs which are being used to treat COVID-19 in different countries-

1. Favipiravir: the Japanese Flu drug

Favipiravir is an antiviral drug which was developed by a Japanese pharma company, Fujifilm Toyama Chemical, to treat influenza and thus, it is also known as the Japanese Flu drug. Favipiravir was approved as an experimental treatment for COVID-19 infections in China in February 2020. According to scientists, the drug shows antiviral activity against all the subtypes of influenza virus strains including influenza A, B, and even avian influenza.

2. Remdesivir: the Ebola drug

Remdesivir was first developed by Gilead Sciences, a US-based pharma company, during the outbreak of ebola. Since the drug did not work well on ebola patients, it was tested against coronavirus strains, SARS and MERS, in the year 2017. The research showed that Remdesivir had the ability to stop the enzyme RNA polymerase which was necessary for virus multiplication. This ensured that the virus could not spread in the body. Since then, it has been tested in various countries for its effectiveness against COVID-19 infection.

3. Hydroxychloroquine: the Anti-malarial drug

Hydroxychloroquine (HCQ) was first developed in India for the treatment of malaria, however, the drug is also a disease-modifying anti-rheumatic drug (DMARD) which helps in reducing swelling and pain in arthritis patients. Some laboratory and in-vivo studies have suggested that HCQ has the ability to prevent COVID-19 infection. Since then, many nations including India, have been using hydroxychloroquine as a prophylactic drug. 

4. Tocilizumab: the Rheumatoid arthritis drug

Tocilizumab is an anti-rheumatoid arthritis drug which is being tested against SARS-CoV-2 virus by the National Cancer Institute in Naples and the trial is called TOCIVID-19. Tocilizumab is actually a humanized IgG1 monoclonal antibody which has the ability to mimic the natural antibodies produced by the immune system of the body in response to the bad microorganisms that enter the body. The trial is ongoing and the drug is being used to treat pneumonia caused by the COVID-19 infection.

5. Ivermectin: the Anti-parasitic drug

Ivermectin is a drug which is used for the treatment of head lice and intestinal worms. On testing the drug against the novel coronavirus, scientists found that ivermectin could restrict the growth of SARS-CoV-2 virus present in a cell within 48 hours and kills it eventually. Ivermectin has also been effective against other viruses such as dengue, influenza and even HIV. The medication is still under trial.

REFERENCES:

https://www.indiatvnews.com/health/glenmark-fabiflu-covid-medicine-to-treat-mild-to-moderate-coronavirus-cases-price-availability-in-stores-627881

https://www.firstpost.com/health/covid-19-treatment-fabiflu-by-glenmark-hcq-remdesivir-and-other-drugs-that-are-being-used-to-treat-coronavirus-patients-8515091.html

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Dexamethasone

Dexamethasone is a generic steroid widely used in other diseases or disorders to reduce inflammation. This drug helps stop some of the damage that can happen when the body’s immune system goes overdrive as it tries to fight off coronavirus.

A statement  by the researchers associated with an Oxford University-led clinical trial - Randomised Evaluation of COVid-19 thERapY (RECOVERY) Trial suggests that dexamethasone may reduce by upto one-third in hospitalized patients with severe respiratory complications due to COVID-19.

This is the same study that earlier this month showed that the malaria drug, hydroxychloroquine was not working against coronavirus.

In the trial, 2104 patients were given dexamethasone and were compared to 4321 patients who did not receive the drug. The drug is shown to cut the risk of death by one third of patients by ventilators and those for oxygen, it cuts death by one fifth.

This steroid medicine has been available as a generic for decades. It is used to treat a wide range of diseases like arthritis, allergy, rheumatism and even help cancer patients to better handle the nausea triggered by chemotherapy.

TEST RESULTS:

The data showed, for patients on ventilators, it cuts the risk of death from 40 percent to 28 percent. For patients needing oxygen, it cuts the risk of death from 25 percent to 20 percent.

Researchers further estimated that the drug will prevent one death for every eight patients treated while on breathing machines and one for every 25 patients on extra oxygen alone.

However, dexamethasone does not help people with milder symptoms for coronavirus i.e those who don’t need help with breathing.

While research is still going on to find out more about the “life saving” drug, we remain hopeful that it wouldn’t be a disappointment this time.