Elucidation of novel compounds and epitope-based peptide vaccine design against C30 endopeptidase regions of SARS-CoV-2 using immunoinformatics approaches.

There has been progressive improvement in immunoinformatics approaches for epitope-based peptide design. Computational-based immune-informatics approaches were applied to identify the epitopes of SARS-CoV-2 to develop vaccines. The accessibility of the SARS-CoV-2 protein surface was analyzed, and hexa-peptide sequences (KTPKYK) were observed having a maximum score of 8.254, located between amino acids 97 and 102, whereas the FSVLAC at amino acids 112 to 117 showed the lowest score of 0.114. The surface flexibility of the target protein ranged from 0.864 to 1.099 having amino acid ranges of 159 to 165 and 118 to 124, respectively, harboring the FCYMHHM and YNGSPSG hepta-peptide sequences. The surface flexibility was predicted, and a 0.864 score was observed from amino acids 159 to 165 with the hepta-peptide (FCYMHHM) sequence. Moreover, the highest score of 1.099 was observed between amino acids 118 and 124 against YNGSPSG. B-cell epitopes and cytotoxic T-lymphocyte (CTL) epitopes were also identified against SARS-CoV-2. In molecular docking analyses, -0.54 to -26.21 kcal/mol global energy was observed against the selected CTL epitopes, exhibiting binding solid energies of -3.33 to -26.36 kcal/mol. Based on optimization, eight epitopes (SEDMLNPNY, GSVGFNIDY, LLEDEFTPF, DYDCVSFCY, GTDLEGNFY, QTFSVLACY, TVNVLAWLY, and TANPKTPKY) showed reliable findings. The study calculated the associated HLA alleles with MHC-I and MHC-II and found that MHC-I epitopes had higher population coverage (0.9019% and 0.5639%) than MHC-II epitopes, which ranged from 58.49% to 34.71% in Italy and China, respectively. The CTL epitopes were docked with antigenic sites and analyzed with MHC-I HLA protein. In addition, virtual screening was conducted using the ZINC database library, which contained 3,447 compounds. The 10 top-ranked scrutinized molecules (ZINC222731806, ZINC077293241, ZINC014880001, ZINC003830427, ZINC030731133, ZINC003932831, ZINC003816514, ZINC004245650, ZINC000057255, and ZINC011592639) exhibited the least binding energy (-8.8 to -7.5 kcal/mol). The molecular dynamics (MD) and immune simulation data suggest that these epitopes could be used to design an effective SARS-CoV-2 vaccine in the form of a peptide-based vaccine. Our identified CTL epitopes have the potential to inhibit SARS-CoV-2 replication.

Smartphone-based diagnostics for biosensing infectious human pathogens.

The widespread usage of smartphones has made accessing vast troves of data easier for everyone. Smartphones are powerful, handy, and easy to operate, making them a valuable tool for improving public health through diagnostics. When combined with other devices and sensors, smartphones have shown potential for detecting, visualizing, collecting, and transferring data, enabling rapid disease diagnosis. In resource-limited settings, the user-friendly operating system of smartphones allows them to function as a point-of-care platform for healthcare and disease diagnosis. Herein, we critically reviewed the smartphone-based biosensors for the diagnosis and detection of diseases caused by infectious human pathogens, such as deadly viruses, bacteria, and fungi. These biosensors use several analytical sensing methods, including microscopic imaging, instrumental interface, colorimetric, fluorescence, and electrochemical biosensors. We have discussed the diverse diagnosis strategies and analytical performances of smartphone-based detection systems in identifying infectious human pathogens, along with future perspectives.

NVAS: A non-interactive verifiable federated learning aggregation scheme for COVID-19 based on game theory.

The continued spread of COVID-19 seriously endangers the physical and mental health of people in all countries. It is an important method to establish inter agency COVID-19 detection and prevention system based on game theory through wireless communication and artificial intelligence. Federated learning (FL) as a privacy preserving machine learning framework has received extensive attention. From the perspective of game theory, FL can be regarded as a process in which multiple participants play games against each other to maximize their own interests. This requires that the user's data is not leaked during the training process. However, existing studies have proved that the privacy protection capability of FL is insufficient. In addition, the existing way of realizing privacy protection through multiple rounds of communication between participants increases the burden of wireless communication. To this end, this paper considers the security model of FL based on game theory, and proposes our scheme, NVAS, a non-interactive verifiable privacy-preserving FL aggregation scheme in wireless communication environments. The NVAS can protect user privacy during FL training without unnecessary interaction between participants, which can better motivate more participants to join and provide high-quality training data. Furthermore, we designed a concise and efficient verification algorithm to ensure the correctness of model aggregation. Finally, the security and feasibility of the scheme are analyzed.

NVAS: A non-interactive verifiable federated learning aggregation scheme for COVID-19 based on game theory☆

The continued spread of COVID-19 seriously endangers the physical and mental health of people in all countries. It is an important method to establish inter agency COVID-19 detection and prevention system based on game theory through wireless communication and artificial intelligence. Federated learning (FL) as a privacy preserving machine learning framework has received extensive attention. From the perspective of game theory, FL can be regarded as a process in which multiple participants play games against each other to maximize their own interests. This requires that the user's data is not leaked during the training process. However, existing studies have proved that the privacy protection capability of FL is insufficient. In addition, the existing way of realizing privacy protection through multiple rounds of communication between participants increases the burden of wireless communication. To this end, this paper considers the security model of FL based on game theory, and proposes our scheme, NVAS, a non-interactive verifiable privacy-preserving FL aggregation scheme in wireless communication environments. The NVAS can protect user privacy during FL training without unnecessary interaction between participants, which can better motivate more participants to join and provide high-quality training data. Furthermore, we designed a concise and efficient verification algorithm to ensure the correctness of model aggregation. Finally, the security and feasibility of the scheme are analyzed.

Anti-viral drug discovery against monkeypox and smallpox infection by natural curcumin derivatives: A Computational drug design approach.

Background: In the last couple of years, viral infections have been leading the globe, considered one of the most widespread and extremely damaging health problems and one of the leading causes of mortality in the modern period. Although several viral infections are discovered, such as SARS CoV-2, Langya Henipavirus, there have only been a limited number of discoveries of possible antiviral drug, and vaccine that have even received authorization for the protection of human health. Recently, another virial infection is infecting worldwide (Monkeypox, and Smallpox), which concerns pharmacists, biochemists, doctors, and healthcare providers about another epidemic. Also, currently no specific treatment is available against Monkeypox. This research gap encouraged us to develop a new molecule to fight against monkeypox and smallpox disease. So, firstly, fifty different curcumin derivatives were collected from natural sources, which are available in the PubChem database, to determine antiviral capabilities against Monkeypox and Smallpox. Material and method: Preliminarily, the molecular docking experiment of fifty different curcumin derivatives were conducted, and the majority of the substances produced the expected binding affinities. Then, twelve curcumin derivatives were picked up for further analysis based on the maximum docking score. After that, the density functional theory (DFT) was used to determine chemical characterizations such as the highest occupied molecular orbital (HOMO), lowest unoccupied molecular orbital (LUMO), softness, and hardness, etc. Results: The mentioned derivatives demonstrated docking scores greater than 6.80 kcal/mol, and the most significant binding affinity was at -8.90 kcal/mol, even though 12 molecules had higher binding scores (-8.00 kcal/mol to -8.9 kcal/mol), and better than the standard medications. The molecular dynamic simulation is described by root mean square deviation (RMSD) and root-mean-square fluctuation (RMSF), demonstrating that all the compounds might be stable in the physiological system. Conclusion: In conclusion, each derivative of curcumin has outstanding absorption, distribution, metabolism, excretion, and toxicity (ADMET) characteristics. Hence, we recommended the aforementioned curcumin derivatives as potential antiviral agents for the treatment of Monkeypox and Smallpox virus, and more in vivo investigations are warranted to substantiate our findings.

Post-COVID-19-associated multiorgan complications or "long COVID" with literature review and management strategy discussion: A meta-analysis.

Objective: To investigate the post-COVID-19 long-term complications or long COVID of various organ systems in patients after 3 months of the infection, specifically before the Omicron variant, with comparative literature analysis. Methods: A systemic literature search and meta-analysis were conducted using multiple electronic databases (PubMed, Scopus, Cochrane library) with predefined search terms to identify eligible articles. Eligible studies reported long-term complications of COVID-19 infection before the Omicron variant infection. Case reports, case series, observational studies with cross-sectional or prospective research design, case-control studies, and experimental studies that reported post-COVID-19 complications were included. The complications reported after 3 months after the recovery from COVID-19 infection were included in the study. Results: The total number of studies available for analysis was 34. The effect size (ES) for neurological complications was 29% with 95% confidence interval (CI): 19%-39%. ES for psychiatric complications was 24% with 95% CI: 7%-41%. ES was 9% for cardiac outcomes, with a 95% CI of 1%-18%. ES was 22%, 95% CI: 5%-39% for the gastrointestinal outcome. ES for musculoskeletal symptoms was 18% with 95% CI: 9%-28%. ES for pulmonary complications was 28% with 95% CI: 18%-37%. ES for dermatological complications was 25%, with a 95% CI of 23%-26%. ES for endocrine outcomes was 8%, with a 95% CI of 8%-9%. ES size for renal outcomes was 3% with a 95% CI of 1%-7%. At the same time, other miscellaneous uncategorized outcomes had ES of 39% with 95% CI of 21%-57%. Apart from analyzing COVID-19 systemic complications outcomes, the ES for hospitalization and intensive care unit admissions were found to be 4%, 95% CI: 0%-7%, and 11% with 95% CI: 8%-14%. Conclusion: By acquiring the data and statistically analyzing the post-COVID-19 complications during the prevalence of most virulent strains, this study has generated a different way of understanding COVID-19 and its complications for better community health.

A Video is Worth a Thousand Words: The Use of Home Videos in Pediatric Neurology.

The use of home video recordings (HVRs) may aid in the diagnosis of neurological disorders. However, this practice remains underutilized. Through an anonymous survey, we sought to understand the perspectives of healthcare providers regarding the sharing of HVRs alongside referrals for responsive and economical pediatric neurology care. This was timely given COVID-19 has worsened wait times for diagnosis and consequently treatment. Most providers agree that sharing of HVRs improves patient care (93.1%: 67/73) and prevents both additional investigations (67%: 49/73) and hospital admissions (68.5%: 50/73). However, a minority of providers (21.9 %: 16/73) currently share HVRs alongside their referrals.

Virtual Mentoring: A Novel Approach to Facilitate Medical Student Applications to General Surgery Residency.

OBJECTIVE: The COVID-19 pandemic rapidly altered the landscape of medical education, particularly disrupting the residency application process and highlighting the need for structured mentorship programs. This prompted our institution to develop a virtual mentoring program to provide tailored, one-on-one mentoring to medical students applying to general surgery residency. The aim of this study was to examine general surgery applicant perception of a pilot virtual mentoring curriculum. DESIGN: The mentorship program included student-tailored mentoring and advising in 5 domains: resume editing, personal statement composition, requesting letters of recommendation, interview skills, and residency program ranking. Electronic surveys were administered following ERAS application submission to participating applicants. The surveys were distributed and collected via a REDCap database. RESULTS: Eighteen out of 19 participants completed the survey. Confidence in a competitive resume (p = 0.006), interview skills (p < 0.001), obtaining letters of recommendation (p = 0.002), personal statement drafting (p < 0.001), and ranking residency programs (p < 0.001) were all significantly improved following completion of the program. Overall utility of the curriculum and likelihood to participate again and recommend the program to others was rated a median 5/5 on the Likert scale (5 [IQR 4-5]). Confidence in the matching carried a premedian 66.5 (50-65) and a postmedian 84 (75-91) (p = 0.004). CONCLUSION: Following the completion of the virtual mentoring program, participants were found to be more confident in all 5 targeted domains. In addition, they were more confident in their overall ability to match. General Surgery applicants find tailored virtual mentoring programs to be a useful tool allowing for continued program development and expansion.

An Insight into COVID-19 and Traditional Herbs: Bangladesh Perspective.

SARS-CoV-2 was first discovered in Wuhan in late 2019 and has since spread over the world, resulting in the present epidemic. Because targeted therapeutics are unavailable, scientists have the opportunity to discover new drugs or vaccines to counter COVID-19, and a number of synthetic bioactive compounds are now being tested in clinical studies. Due to its broad therapeutic spectrum and low adverse effects, medicinal herbs have been used as traditional healing medication in that countries for ages. Due to a lack of synthetic bioactive antiviral medications, pharmaceutical and alternative therapies have been developed using a variety of herbal compositions. Due of the widespread availability of herbal and dietary products worldwide, people frequently use them. Notably, the majority of the Bangladeshi people continue to use a variety of natural plants and herbs to treat various types of disease. This review discusses about how previous research has shown that some herbs in Bangladesh have immunomodulatory and antiviral effects, and how their active ingredients have been gathered. Even though FDA-approved medications and vaccines are available for the treatment of Covid-19, the purpose is to encourage the use of herbal medicine as immuno-modulators and vaccine adjuvants for the treatments of COVID-19 prevention.

Metformin: Activation of 5' AMP-activated protein kinase and its emerging potential beyond anti-hyperglycemic action.

Metformin is a plant-based drug belonging to the class of biguanides and is known to treat type-2 diabetes mellitus (T2DM). The drug, combined with controlling blood glucose levels, improves the body's response to insulin. In addition, trials have identified the cardioprotective potential of metformin in the diabetic population receiving the drug. Activation of 5' AMP-activated protein kinase (AMPK) is the major pathway for these potential beneficial effects of metformin. Historically, much emphasis has been placed on the potential indications of metformin beyond its anti-diabetic use. This review aims to appraise other potential uses of metformin primarily mediated by the activation of AMPK. We also discuss various mechanisms, other than AMPK activation, by which metformin could produce beneficial effects for different conditions. Databases including PubMed/MEDLINE and Embase were searched for literature relevant to the review's objective. Reports from both research and review articles were considered. We found that metformin has diverse effects on the human body systems. It has been shown to exert anti-inflammatory, antioxidant, cardioprotective, metabolic, neuroprotective, anti-cancer, and antimicrobial effects and has now even been identified as effective against SARS-CoV-2. Above all, the AMPK pathway has been recognized as responsible for metformin's efficiency and effectiveness. Owing to its extensive potential, it has the capability to become a part of treatment regimens for diseases apart from T2DM.

A comprehensive review on variants of SARS-CoVs-2: Challenges, solutions and open issues.

SARS-CoV-2 is an infected disease caused by one of the variants of Coronavirus which emerged in December 2019. It is declared a pandemic by WHO in March 2020. COVID-19 outbreak has put the world on a halt and is a major threat to the public health system. It has shattered the world with its effects on different areas as the pandemic hit the world in a number of waves with different variants and mutations. Each variant and mutation have different transmission and infection rates in the human population. More than 609 million people have tested positive and more than 6.5 million people have died due to this disease as per 14th September 2022. Despite of numerous efforts, precautions and vaccination the infection has grown rapidly in the world. In this paper, we aim to give a holistic overview of COVID-19 its variants, game theory perspective, effects on the different social and economic areas, diagnostic advancements, treatment methods. A taxonomy is made for the proper insight of the work demonstrated in the paper. Finally, we discuss the open issues associated with COVID-19 in different fields and futuristic research trends in the area. The main aim of the paper is to provide comprehensive literature that covers all the areas and provide an expert understanding of the COVID-19 techniques and potentially be further utilized to combat the outbreak of COVID-19.

Nanoparticles in clinical trials of COVID-19: An update.

Once the World Health Organization (WHO) declared the COVID-19 (Coronavirus Infectious Disease-19) outbreak to be pandemic, massive efforts have been launched by researchers around the globe to combat this emerging infectious disease. Strategies that must be investigated such as expanding testing capabilities, developing effective medicines, as well as developing safe and effective vaccines for COVID-19 disease that produce long-lasting immunity to human system. Now-a-days, bio-sensing, medication delivery, imaging, and antimicrobial treatment are just a few of the medical applications for nanoparticles (NPs). Since the early 1990s, nanoparticle drug delivery methods have been employed in clinical trials. Since then, the discipline of nanomedicine has evolved in tandem with expanding technological demands to better medicinal delivery. Newer generations of NPs have emerged in recent decades that are capable of performing additional delivery tasks, allowing for therapy via novel therapeutic modalities. Many of these next generation NPs and associated products have entered clinical trials and have been approved for diverse indications in the present clinical environment. For systemic applications, NPs or nanomedicine-based drug delivery systems have substantial benefits over their non-formulated and free drug counterparts. Nanoparticle systems, for example, are capable of delivering medicines and treating parts of the body that are inaccessible to existing delivery systems. As a result, NPs medication delivery is one of the most studied preclinical and clinical systems. NPs-based vaccines delivering SARS-CoV-2 antigens will play an increasingly important role in prolonging or improving COVID-19 vaccination outcomes. This review provides insights about employing NPs-based drug delivery systems for the treatment of COVID-19 to increase the bioavailability of current drugs, reducing their toxicity, and to increase their efficiency. This article also exhibits their capability and efficacy, and highlighting the future aspects and challenges on nanoparticle products in clinical trials of COVID-19.

Mucormycosis in the COVID-19 Environment: A Multifaceted Complication.

The second wave of coronavirus disease 2019 (COVID-19) caused severe infections with high mortality. An increase in the cases of COVID-19-associated mucormycosis (CAM) was reported predominantly in India. Commonly present in immunocompromised individuals, mucormycosis is often a life-threatening condition. Confounding factors and molecular mechanisms associated with CAM are still not well understood, and there is a need for careful research in this direction. In this review, a brief account of the diagnosis, management, and advancement in drug discovery for mucormycosis has been provided. Here, we summarize major factors that dictate the occurrence of mucormycosis in COVID-19 patients through the analysis of published literature and case reports. Major predisposing factors to mucormycosis appear to be uncontrolled diabetes, steroid therapy, and certain cancers. At the molecular level, increased levels of iron in COVID-19 might contribute to mucormycosis. We have also discussed the potential role and regulation of iron metabolism in COVID-19 patients in establishing fungal growth. Other factors including diabetes prevalence and fungal spore burden in India as contributing factors have also been discussed.

Effect of vaccination on the HRCT profile of COVID-19 patients – A single-center experience

Introduction: Vaccination against the global pandemic coronavirus disease 2019 (COVID-19) is a promising way out of the havoc caused by the disease. The clinico-radiological profile of COVID-19 patients in relation to the vaccination status is depicted in the present study. Materials and Methods: This is a retrospective observational imaging and hospital data-based study performed on 214 confirmed and clinically suspicious patients of COVID-19 who underwent high-resolution computed tomography (HRCT) scan of the thorax at the Department of Radio-Diagnosis of a tertiary medical center in the Himalayan foothills. The present study aims to evaluate the effect of vaccination on HRCT findings of COVID-19 populations. Results: Forty-three percent of the non-vaccinated population presented with severe HRCT scores (19–25) in comparison to only 11.5% of the study population who had taken both doses of vaccine (P = 0.018). Two doses of vaccination had a negative Pearson correlation coefficient with severe HRCT scores (–0.146). Co-morbidities had a significant correlation with HRCT severity score, with 61.5% diabetics and 63.33% of hypertensive patients showing scores >19 on HRCT. Conclusion: Vaccination proves to be a game changer in the pandemic with two doses of vaccination having a significant negative correlation with COVID-19-induced severe pneumonitis on HRCT of the thorax.

In silico investigation and potential therapeutic approaches of natural products for COVID-19: Computer-aided drug design perspective.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a substantial number of deaths around the world, making it a serious and pressing public health hazard. Phytochemicals could thus provide a rich source of potent and safer anti-SARS-CoV-2 drugs. The absence of approved treatments or vaccinations continues to be an issue, forcing the creation of new medicines. Computer-aided drug design has helped to speed up the drug research and development process by decreasing costs and time. Natural compounds like terpenoids, alkaloids, polyphenols, and flavonoid derivatives have a perfect impact against viral replication and facilitate future studies in novel drug discovery. This would be more effective if collaboration took place between governments, researchers, clinicians, and traditional medicine practitioners' safe and effective therapeutic research. Through a computational approach, this study aims to contribute to the development of effective treatment methods by examining the mechanisms relating to the binding and subsequent inhibition of SARS-CoV-2 ribonucleic acid (RNA)-dependent RNA polymerase (RdRp). The in silico method has also been employed to determine the most effective drug among the mentioned compound and their aquatic, nonaquatic, and pharmacokinetics' data have been analyzed. The highest binding energy has been reported -11.4 kcal/mol against SARS-CoV-2 main protease (7MBG) in L05. Besides, all the ligands are non-carcinogenic, excluding L04, and have good water solubility and no AMES toxicity. The discovery of preclinical drug candidate molecules and the structural elucidation of pharmacological therapeutic targets have expedited both structure-based and ligand-based drug design. This review article will assist physicians and researchers in realizing the enormous potential of computer-aided drug design in the design and discovery of therapeutic molecules, and hence in the treatment of deadly diseases.