Antibiotic Resistance- An ongoing crisis

Antibiotic resistance is an ancient and mounting problem. Common causes are overpopulation, increased use of antibiotics, and even due to enhanced global migration.  For a long time, antibiotic treatment has been the main approach of treatment in modern medicine to combat infections. The golden era of antibiotics was between the 1930s to 1960s, giving rise to many antibiotics. Antibiotic resistance poses a very serious global threat due to the growing concern of human and animal health. This is due to multidrug-resistant bacteria or popularly known as “superbugs”.

The plausible causes of global microbial resistance include overuse of antibiotics in animals consumed as food by humans. Other superficial causes include, increase in international travel and poor hygiene. These factors mainly play a role in the genetic selection in a community of resisting antibiotics. 

History and Benefits of Antibiotics:

The first documented use of antibiotics was with the discovery of penicillin by Alexander Fleming during the world war. Penciliine was successful in controlling the bacteria and was said to have saved millions of lives. Shortly after the boom in usage, the penicillin resistance was a major problem, threatening many of the advances in the medical field at that time. What was thought as just penicillin resistance later proved to be a multidrug resistance. Microorganisms under Darwinian natural selection to develop the resistance. Naturally, most antibiotics are produced using bacteria or environmental fungi, and few are completely synthetic using sulphonamides and fluoroquinolones. 

Not only saving lives, but antibiotics have also played a vital role in advancing major breakthroughs in the field of surgery and medicine. They have successfully prevented and treated infections that commonly occur in patients undergoing chemotherapy, who are also suffering from chronic diabetes or rheumatoid arthritis. 


Even as early as 1945, Alexander Fleming with the discovery of penicillin, also warned the public that the era of antibiotics will also lead to the era of misuse and resistance. Epidemiological studies depict a direct relationship between the consumption of antibiotics and the rise in bacterial resistant diseases. These bacteria can be transmitted or inherited between relatives and friends. Resistance can also occur due to spontaneous mutation. Antibiotics remove the sensitive competitors and leave the resistance bacteria by natural selection to reproduce and multiply more. Despite these warnings, antibiotics are overprescribed throughout the world. 

Agricultural use:

In both developing and developed worlds, antibiotics are seen to be used very frequently as growth supplements in livestock. According to a census, almost 80% of the antibiotics sold throughout the world are used in animals to prevent infection and promote growth. Treating livestock with antimicrobials can improve overall health, produce larger yields, and an overall high-quality product.  

The antibiotics used in treating livestock is in turn consumed by the top of the food chain- humans. This transfer of resistant bacteria to humans was first noticed 35 years ago when the antibiotic rates were found high in the intestines of both farm animals and farmers. Recently molecular detection methods prove that resistant bacteria from farm animals reach humans through consumption. 

It should also be noted that the agricultural use of antibiotics also thrive in urine and stool. These are widely dispersed through fertilizers affecting the groundwater and surface. While this may account for a small fraction of overall antibiotic use, the end geographical spread can be a considerable size. This practice also affects the micro

The emergence of resistance:

Organisms develop resistance by several techniques including altering the target site of binding, inhibiting the drug entry, and enzyme production that leads to the degradation of antimicrobials.Various antimicrobial drugs like antibiotics produced by saprophytic bacteria tend to develop mutual benefits with the other organisms surrounding it and sometimes even inhibit growth. Available data suggest that the sublethal concentration is the antibiotics have a significant impact on the microbial flora, and may even be effective in signalling molecules which may induce a microbial and host gene expression. 

Another important finding reveals that few saprophytic bacteria is capable of producing a broad-spectrum antibiotic known as carbapenems. Various genes involved in constructing this antibiotic may also play an important role in biofilm formation. These findings reveal more unexpected impacts of the antibiotics.

More knowledge is needed to the extent of the broad-spectrum antimicrobial resistance. Current panic is due to the inadequate information. The future cannot be predicted with surety at the stage with regards to the resistance with the unavailability of novel antibiotics. Multiple well thought strategies need to be in place to confront this particular issue. Regulations should be implemented by every country to monitor prescriptions and the use of antibiotics. Environmental and ecological issues should not be ignored and all elements should be part of the control policy. Alternatives to antibiotics such as lytic bacteriophages vectors and probiotics can potentially help to decrease the use of antibiotics. 


COVID-19: Ridgeback working on anti-viral tests for patients in the hospital and at home

With efforts underway to find treatments for COVID-19 patients at the hospital, Ridgeback therapeutics are doing things differently.

By the looks of it, COVID-19 does not seem to slow down anytime soon. Thousands of fresh cases are being reported every day, and hospitals are flooded around the world. Most of the pharmaceutical companies are right now focused on finding a treatment for hospitalized patients, in a way that makes sense. After all, they are the most severely affected patients. But Miami based Ridgeback biotherapeutics are currently working differently. 

Currently, the company is kicking off its phase 2 trial for an antiviral that can serve as a treatment for both hospitalized patients and freshly diagnosed patients who are staying at home. The underway antiviral- EIDD-2801 is first being tested on hospitalized COVID-19 patients and the second with cases at home. 

What is EIDD-2801?

Although doctors and scientists around the world are testing out a variety of existing drugs to fight COVID-19, EIDD-2801, an oral antiviral drug stands apart. 

The drug can be used as both prophylactic and a therapeutic against the COVID-19 virus. It is a nucleoside analog that shows broad spectrum activity against RNA viruses, which includes the current coronavirus, COVID-19 and previous virus MERS and SARS. 

EIDD-2801 attacks RNA dependent RNA polymerase the same way as Gilead Sciences’ Remdesivir, a previously FDA-appointed drug for emergency use. But unlike remdesivir which is administered intravenously, EIDD-2801 can be taken orally. 

Why EIDD-2801?

Since the convenience of taking EIDD-2801 orally, patients could take it at home rather than  risking themselves and others by coming to the hospital. By this, the drug is taken at the earlier stages of the infection, potentially killing the virus before it causes havoc on the body. 

EIDD-2801 is completely safe and effective and has a rather intriguing feature of being highly resistant. Usually drugs alert the viruses to quickly mutate that aren’t affected by the drug, making it incompetent. But EID-2801 when tested hasn’t prompted any such resistance.

“We always worry about resistance,” says Andy Mehle, a virologist at the University of Wisconsin–Madison. Though drug resistance is inevitable, sometimes the viruses work on changing so much to overcome a drug’s effects that they cripple. Alternatively, resistance may seem as a simple change, the changes occur with a difficulty of the virus’s ability to multiply. Experts speculate this might be the case with EIDD-2801.

What’s next for Ridgeback?

Though the first set of clinical studies are just beginning, Ridgeback is confident about the drug and is currently gearing up to manufacture hundreds of thousands of doses of the drug. In the near future the company is planning to ramp up the production to millions. 

“While we still need to wait and see the intended efficacy of the drug as ridgeback believes it to be, it is imperative to have a backup of immediate and ample supply to the world, once the clinical trials are successful” stated Wendy Holman, CEO and co-founder of Ridgeback.

Good news as researchers find a key to cystic fibrosis detection and treatment

Good news as researchers find a key to cystic fibrosis detection and treatment

Groundbreaking research by Monash University paves the way to a possibility of better monitoring and treatment of the cystic fibrosis lung disease

For years, cystic fibrosis (CF) has known to be a serious hereditary condition that causes severe damage to the respiratory and digestive systems. The damage starts with a build-up of thick mucosal kind of fluid in the organs especially lungs. 

In particular cystic fibrosis affects the cells that produce digestive enzymes, sweat, and mucus. Usually, these secretions are thin and watery, which function as lubrication for various organs and tissues. However, when affected with CF, due to faulty genes the person experiences thick fluid build-up, clogging up the passages and ducts.  

Early diagnosis and treatment are important for improving the quality and the length of the affected life. Currently available lung assessment tools have many drawbacks, especially the inability to accurately identify the origin of the changes seen in lung health. 

Monash University research team announced the results of the World’s first research promising a possibility of better diagnosis and treatment of cystic fibrosis using X-ray velocimetry. 

What is X-ray velocimetry?

A phase-contrast X-ray imaging makes use of the refractive properties of materials to produce high definition soft tissue images. Recently X-ray velocimetry (XV) has caught the eye of researchers. In particular, XV is used to study the airflow through the lungs and the technique is based on particle image velocimetry. Particle image velocimetry (PIV) is a well-established technique known for years. 

XV is known to provide high quality, non-invasive, real-time images of the airflow through the lungs. The X-ray was first designed and developed by 4DMedical, in hope for clinical use. The technology has also recently been approved by the FDA for its all respiratory indications in adults. 

All about the study:

An effective assessment of the lung cystic fibrosis should be capable of capturing its patchy nature and fluid buildup. This is in particular important for detecting the disease at early stages. 

With the help of XV, a multidisciplinary collaboration of engineers, physicists, and clinicians were able to measure real-time airflow through the lungs. 

The research was led by one of the University’s leading scientists Dr. Freda Werdiger. The study revealed that by using XV, it was possible to pinpoint the precise locations where there was an obstruction of airflow in the lung of a cystic fibrosis patient.  

“In this study, we present two developments in XV analysis. Firstly, we show the ability of laboratory-based XV to detect the patchy nature of CF-like disease in affected mice. Secondly, we present a technique for numerical quantification of that disease, which can delineate between two major modes of disease symptoms,” Dr. Werdiger said.

This particular model provides a very simple, easy top interpret approach, which in the future can be readily applied to large quantities of data generated in XV imaging. 

What does the future hold?

The success of XV lies in its capability of drawing reliable and quantitative measures, and the above study shows how that can be accomplished. 

The researchers of the study recommend that this promising technique should be applied to the numerical characterization of CF lung disease. The analysis can be applied in a straight forward fashion with minimal manual labour required. 

Use of Computational Methods in Stem Cell Biology

Use of Computational Methods in Stem Cell Biology

For a few decades now, the field of developmental biology has utilized computational technologies to explore the mechanisms of the developmental process. It was first in the 1950’s Alan Turing wrote a computer program that was able to model how morphogen concentrations can affect the growth of an in vitro embryo. Since then several techniques have been developed that can generate comprehensive data of a molecular type also known as OMICs. 

Though the use of computational methods was largely limited to the theoretical mechanisms, the birth of large genome sequencing, paved the way to process large molecular data. Computational models complement the statistical data by providing mechanistic insights into the biological processes and by the ability to predict future outcomes in terms of biological processes that can guide experimental research. 

Difference between Mechanistic models and Machine Learning Models:

For several years, Machine Learning (ML) approaches have been used for pattern recognition, prediction, and classification of biological systems, especially system cell research. Some of the important examples include the construction of 3D stem cell images from fluorescent microscopic results. Ml can also predict the experimental conditions and determine future outcomes.

Although ML has a decent accurate predictive power, they require large amounts of data especially imaging and omics datasets for interpreting statistical relationships between the input and predicted output data. ML usually specializes in predicting the outcome but not revealing the underlying complex processes, preventing them from providing any mechanistic insights on the biological processes. ML can be classified as supervised and unsupervised learning. The supervised learning can predict outcomes of foreseen data by studying the labeled training data, whereas unsupervised tries to make sense of any unlabelled data by extracting in-depth features and patterns of its own. 

By contrast, mechanistic models generally rely on the mechanistic hypothesis implied from the experimental data to predict novel outcomes and describe the behaviors of the whole system. These models are often assembled based on the simplified mathematical and conceptual formulations of the observed experiment. Moreover, a single based cell experiment of this model has been developed to elucidate cell fate dysregulation linked with congenital diseases. 

Applications of Computational Methods in Regenerative Medicine

It is well known that cell transplantation especially using induced pluripotent stem cells (iPSCs) is one of the main strategies in regenerative medicine to reinstate damaged or ill-functioning cells. Though various clinical applications using iPSCs are underway there are still few challenges that need to be overcome before it reaches its full potential. One of the main ways to overcome this problem is by figuring out the in-vitro manufacturing of the donor cells to gain appropriate knowledge of the cell expression- the identity of host tissue cells. 

Current techniques have a low conversion efficiency, forcing the researchers to spend a large number of their resources in order to get an accurate result. Moreover, cell conversion often results in creating unnecessary immature cells or non-variants of the cells, ultimately failing to reciprocate the desired functionalities and phenotypes. On the other hand, computational methods can help in achieving the desired results. The latest advancements in scRNA sequencing technologies can help the researchers to accurately characterize functionally gene expression and cell subtypes. 

By combining the computational methods with existing novel experimental techniques, it is possible for researchers to now open up to new avenues in designing protocols and treatments for congenital disorders and for enhancing regeneration of cells. 

Stem cell rejuvenation is another strategy promising to prevent the damaged stem cell function and to help optimize tissue repair processes in age-related or degenerative disorders. The main reason behind impaired stem cell function is the disruption of pathways of the endogenous stem cells due to certain mutations or aged niche. The computational models can help in determining this particular impaired niches and signaling pathways and further help in proving insights with the mechanisms of the cell dysregulation in aging. Researches can use these predicted signaling molecules to counteract a niche effect for rejuvenating stem cells.  

Future Perspectives:

As discussed a number of challenges in the research can be resolved with the development of multiscale computational methods. With the increasing work in single-cell expansion and scRNA data, it is now possible to develop complex computational methods, including cell-cell communication and intracellular network-based models. 

Although ML has been employed successfully in pattern recognition and classification, they are not capable of providing information on biological processes. The implementation of mechanistic models with ML can help in a better understanding of mechanisms and predictions based on simple assumptions. In the future, stem cell researchers could coordinate with computational models, before performing an experiment to address certain biological questions and assess the required data for the model.

Serum- and glucocorticoid- inducible kinase 2, SGK2, is a novel autophagy regulator and modulates platinum drugs response in cancer cells

Serum- and glucocorticoid- inducible kinase 2, SGK2, is a novel autophagy regulator and modulates platinum drugs response in cancer cells

Many cases of ovarian cancers arise from the epithelial cells of the ovary and fallopian tube. The epithelial ovarian cancer is not a single entity disease but rather are several subtypes, each with its distinct genetic and biological backgrounds. This diversity determines the clinical outcome of the disease, where the patients respond differently to the same treatment and sometimes even different prognosis. 

For the past three decades, the standard treatment for advanced epithelial ovarian cancer is chemotherapy, commonly used platinum-based drugs (PT). Though the majority of the patients achieve complete remission, there are cases who might experience recurrence due to acquired resistance to platinum-based drugs. Cellular diversity in tumors and the microenvironment can lead to chemoresistance. Overcoming PT resistance is one of the major challenges faced in ovarian cancer research. 

Over the years, many experiments have been conducted to identify the particular genes responsible for the mechanism directly associated with the PT resistance. PT resistance is linked to several alterations such as drug inactivation, transport, DNA repair, and apoptosis. Among the general pathways, researchers have also observed autophagy has shown to confer with the metabolic plasticity which is necessary to grow and survive in therapy-induced stress. 

Autophagy is a dynamic catabolic process that aids in the formation of double-membrane vesicles also known as autophagosomes. They help in engulfing cellular proteins and organelles and deliver them to the lysosome. When  autophagosomes merge with lysosomes, the contents are degraded and help in fueling the metabolic pathways. 

In this study, the authors began a mission to find the genes responsible for the PT- chemoresistance. A loss of function screening was performed and unveiled that serum- glucocorticoid- kinase 2 (SGK2) as a novel modulator of platinum-based drug sensitivity. SGK family constitutes three isoforms: SGK1, SGK2, and SGK3. Most of the studies revolving around the SGK family, mention its role in the development of human diseases in cancer and in cellular physiology. SGKs were initially identified as regulators, and pumps in the context of epithelial cells ion transport. The study further demonstrates the previously unrecognized role of SGK2 in platinum based drug sensitivity exerted by the autophagic reflux. 

Starting from identifying SGK2 as a druggable modulator, the study characterized the role of autophagy as an escaping strategy activated by the cancer cells to resist PT treatment. The study later demonstrated that pharmacological or genetic inhibition of the isotype SGK2 could potentially block the autophagic process stimulated by the PT treatment. This evidence throws light on the possibility of developing new anticancer strategies on drug repositioning. Overall the study proves that SGK2 kinase controls the PT induced cell death in epithelial ovarian cancer by inhibiting autophagy.

Isolation of potent SARS-CoV-2 neutralizing antibodies and protection from disease in a small animal model

Isolation of potent SARS-CoV-2 neutralizing antibodies and protection from disease in a small animal model

For the past few months, there has been a global spread and toll of COVID-19. So far, humanity has been able to eradicate only one other human infectious disease- smallpox. The novel infectious disease- COVID-19 has had its devastating share of lives globally and currently there is no cure or licensed vaccine. 

Many studies lately have been discussing in-depth about neutralizing antibodies. They represent therapeutic and prophylactic options that could help guide potential vaccine designs. Neutralizing antibodies (nAbs) in terms of another respiratory virus- respiratory syncytial virus (RSV) is widely used clinically, usually to protect vulnerable infants prophylactically. Generally, nAbs with good potency also known as super antibodies can supersize antiviral therapeutic efficiency. Along with the help of bioengineering, the nAbs half-life can be prolonged bringing down the cost considerably. 

In this study, the authors try to present potent nAbs to the COVID-19 virus and further demonstrate their efficacy in-vivo using small animal models. The researchers of this paper, isolated and characterized the required monoclonal antibodies from recovering convalescent donors and developed neutralizing assays to investigate the antibody responses. In parallel, the researchers also developed both live attenuated and pseudovirus neutralization assays using HeLa- ACE2 (Angiotensin-converting enzyme) cell line. The collected convalescent plasma was evaluated against COVID-19 by using 8 donors. The antigen-specific B cells were sorted and corresponding genes were identified and cloned to enable antibody expression and characterization. The promising monoclonal antibodies were progressed for further testing in-vivo using a small animal model. 

The study further isolated the potent neutralizing antibodies to two epitopes- the receptor-binding domain (RBD) and the non RBD- Spike (S) protein. The data showed that the passive transfer of neutralizing antibodies provides distinct protection against the novel- COVID-19 virus as seen in Syrian hamsters. The animal model throughout the infection maintained the same weight and showed low lung abnormalities. Nevertheless, as for any animal model, there were a few limitations, including the difference in receptor cells between the hamster and humans.

The results from the study suggest a focus on the RBD and a string neutralizing antibody responses were seen by immunizing mice with a multivalent RBD. The few weak preponderances of neutralizing antibody to S protein may be due to the result of the study using recombinant S protein. In conclusion, the data from the study potentially open up to the idea of the very rapid generation of neutralizing antibodies to a newly emerged novel virus. The antibodies can open up to the possibilities of finding a clinical application and will aid in vaccine manufacturing or design.

Research Paper Vs Thesis- Understanding the Difference

Research Paper Vs Thesis- Understanding the Difference

At some point in time, being a researcher, one must wonder the difference between a research paper and thesis, since both seem similar and it’s difficult to identify the difference. Although both are academic documents, the reason, the purpose, and the structure behind them are different. With a quick introduction, it can be explained that the research paper is an outcome of the research work conducted by the publisher in his/her area of interest, whereas a thesis is an argument or a write-up that backs up an already existing result. 

What is a thesis?

A thesis of an academic document is commonly written for an academic degree or higher education, before issuing a degree. A thesis is generally written under a supervisor who helps in guiding and commenting on a draft created by the author. They also advise them on how to better it further. 

The main purpose of a thesis is to collect specific data, analyze, and present it to their instructors or a committee of people formed by the degree offering institute. A thesis is broad and refers to the general subjects. The students usually choose a specific topic that is relevant to their specific area of interest. It usually takes several months to write a thesis as it is a long and demanding task to collect all the data and analyze it. Proper set procedures must be followed in order to successfully complete a thesis on time. The thesis is also called a dissertation in several countries- which a person obtaining a postgraduate degree needs to complete before obtaining their degree. 

What is a Research Paper?

A research paper is an individually written academic document, a publication of the researchers’ findings after analyzing the gathered data. Research papers are mostly short in length compared to a thesis, since it only specifies the relevant data, while a thesis focuses on a much broader subject.

A research paper has its own structure or format and focuses on the gathered data. There is usually a structured methodology that must be followed by the research paper before being published in any academic magazine or journal. Each research paper has its own journal which publishes papers that fall in one area of research, like the journal of the cell, will only accept research papers related to cell biology. Research papers are essentially the way for researchers to contribute to their area of specialty. 

Now that the concepts of both thesis and research papers are relatively clear, let’s distinguish between them.

Structural and technical difference:

A thesis concerned more with the central question, while a research paper is about proving a central argument. A thesis contains minimal or no methodology whereas a research paper explicates method thoroughly whether quantitative or qualitative. It revolves more around possibilities and even the end of possibilities through antithesis. A research paper proves the central thesis and gathers the concerning evidence to explore possibilities to nullify any speculation or future alternatives to the thesis. To be precise, a research paper is all about explaining and pricing a thesis. 

The thesis is usually constructed through extensive originality that puts forth a novel statement or proposal, but a research paper requires a more cohesive approach by the researcher to justify the question at hand. 

All this is performed to prove a thesis, to which a research paper can also be called as an extension to the central thesis. 


As mentioned above, a sameness lies between both the thesis and research paper, what a thesis that potentially holds is unveiled and explained in a research paper. Usually, a research paper consists of the thesis, but this is not always the case. The research paper might be a part of the thesis question which on its own can have validity. 

Although a number of anti- foundational theories are floating against the classical model, the lines of work such an anti-thesis should be considered a deterministic end. Each model, a thesis or a research paper should be respected enough as a great potential of new knowledge which is completely based on new paradigms. Each model should be nurtured and boundless knowledge should be encouraged.

To be conclusive there are differences and similarities between a thesis and research paper. There are even alternatives that go into the creation of new knowledge which is quite different from the dominant research paradigm.