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Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) has emerged as the causative agent behind the global pandemic of Coronavirus Disease 2019 (COVID-19). As the scientific community strives to comprehend the intricate workings of this virus, a fundamental aspect lies in deciphering the myriad proteins it expresses. This knowledge is pivotal in unraveling the complexities of the viral machinery and devising targeted therapeutic interventions. The proteomic landscape of SARS-CoV2 encompasses structural, non-structural, and open-reading frame proteins, each playing crucial roles in viral replication, host interactions, and the pathogenesis of COVID-19. This comprehensive review aims to provide an updated and detailed examination of the structural and functional attributes of SARS-CoV2 proteins. By exploring the intricate molecular architecture, we have highlighted the significance of these proteins in viral biology. Insights into their roles and interplay contribute to a deeper understanding of the virus's mechanisms, thereby paving the way for the development of effective therapeutic strategies. As the global scientific community strives to combat the ongoing pandemic, this synthesis of knowledge on SARS-CoV2 proteins serves as a valuable resource, fostering informed approaches toward mitigating the impact of COVID-19 and advancing the frontier of antiviral research., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Purpose: The early phase of the COVID-19 pandemic affected cancer care globally. Evaluating the impact of the pandemic on the quality of cancer care delivery is crucial for understanding how changes in care delivery may influence outcomes. Our study compared care delivered during the early phase of the pandemic with the same period in the previous year at two institutions across continents (Princess Margaret Cancer Center [PM] in Canada and A.C. Camargo Cancer Center [AC] in Brazil)., Methods: Patients newly diagnosed with colorectal or anal cancer between February and December 2019 and the same period in 2020 were analyzed. Sociodemographic and clinical characteristics and performance of individual indicators within and between centers and between the peri-COVID-19 and control cohorts were tested using Cohen's h test to assess the standardized differences between the two groups., Results: Among 925 patients, distinct effects of the early COVID-19 pandemic on oncology services were observed. AC experienced a 50% reduction in patient consultations (98 v 197) versus a 12.5% reduction at PM (294 v 336). Similarly, AC experienced a higher proportion of stage IV disease presentations (42.9% v 29.9%; P = .015) and an increase in treatment delay (61.9% v 9.7%; P < .001) compared with prepandemic. At PM, a 10% increase in treatment interruption (32.4% v 22.3%; P < .001) and a higher rate of discontinuation of radiotherapy (9.4% v 1.1%; P < .001) were observed during the pandemic. Postsurgical readmission rates increased in both AC (20.9% v 2.6%; P < .001) and PM (10.5% v 3.6%; P < .01)., Conclusion: The early phase of the COVID-19 pandemic affected the quality of care delivery for colorectal and anal cancers at both centers. However, the magnitude of this impact was greater in Brazil.

Coronavirus disease 2019 (COVID-19) and influenza are respiratory illnesses caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza viruses, respectively. Both diseases share symptoms and clinical risk factors 1 , but the extent to which these conditions have a common genetic etiology is unknown. This is partly because host genetic risk factors are well characterized for COVID-19 but not for influenza, with the largest published genome-wide association studies for these conditions including >2 million individuals 2 and about 1,000 individuals 3-6 , respectively. Shared genetic risk factors could point to targets to prevent or treat both infections. Through a genetic study of 18,334 cases with a positive test for influenza and 276,295 controls, we show that published COVID-19 risk variants are not associated with influenza. Furthermore, we discovered and replicated an association between influenza infection and noncoding variants in B3GALT5 and ST6GAL1, neither of which was associated with COVID-19. In vitro small interfering RNA knockdown of ST6GAL1-an enzyme that adds sialic acid to the cell surface, which is used for viral entry-reduced influenza infectivity by 57%. These results mirror the observation that variants that downregulate ACE2, the SARS-CoV-2 receptor, protect against COVID-19 (ref. 7 ). Collectively, these findings highlight downregulation of key cell surface receptors used for viral entry as treatment opportunities to prevent COVID-19 and influenza., (© 2024. The Author(s).)

Background: This update outlines amendments to the CHAMPION2/STRIPES2 cluster randomised trial protocol primarily made due to the COVID-19 pandemic and nationwide lockdown in India in 2020. These amendments were in line with national guidelines for health research during the COVID-19 pandemic., Methods: We did not change the original trial design, eligibility, and outcomes. Amendments were introduced to minimise the risk of COVID-19 transmission and ensure safety and wellbeing of trial staff, participants, and other villagers. CHAMPION2 intervention: participatory learning and action (PLA) and fixed day service (FDS) meeting were revised to incorporate social distancing and hygiene precautions. During the COVID-19 pandemic, PLA participation was limited to pregnant women and birthing partners. STRIPES2 intervention: before/after-school classes were halted for a period and then modified temporarily (reducing class sizes, and/or changing meeting places) with hygiene and safe distancing practices introduced., Data Collection: The research team gathered as much information as possible from participants by telephone. If the participant had no telephone or could not be contacted by telephone, data were collected in person. COVID-19 precautions: trial teams were trained on COVID-19 precautions and used personal protective equipment whilst in the villages for trial-related activities. After restarting the trial between June and September 2020 in a phased manner, some trial activities were suspended again in all the trial villages from April to June 2021 due to the second wave of COVID-19 cases and lockdown imposed in Satna, Madhya Pradesh. Trial timelines were also revised, with outcomes measured later than originally planned., Trial Registration: Clinical Trial Registry of India CTRI/2019/05/019296. Registered 23 May 2019. https://ctri.nic.in/Clinicaltrials/pmaindet2.php?EncHid=MzExOTg=&Enc=&userName=champion2 ., (© 2024. The Author(s).)

Introduction: The coronavirus disease 2019 pandemic has led to concerns over transmission risk from head and neck operations including facial cosmetic surgeries. Objectives: To quantify droplet and aerosol generation from rhinoplasty techniques in a human anatomic specimen model using fluorescein staining and an optical particle sizer. Methods: Noses of human anatomic specimens were infiltrated using 0.1% fluorescein. Droplets and aerosols were measured during rhinoplasty techniques including opening the skin-soft tissue envelope, monopolar electrocautery, endonasal rasping, endonasal osteotomy, and percutaneous osteotomy. Results: No visible droplet contamination was observed for any rhinoplasty techniques investigated. Compared with the negative control of anterior rhinoscopy, total 0.300-10.000 μm aerosols were increased after monopolar electrocautery ( p  < 0.001) and endonasal rasp ( p  = 0.003). Opening the skin-soft tissue envelope, endonasal osteotomies, and percutaneous osteotomies did not generate a detectable increase in aerosols ( p  > 0.15). Discussion and Conclusions: In this investigation, droplets were not observed under ultraviolet light, and aerosol generation was noted only with cautery and endonasal rasping.

COVID-19 has resulted in millions of deaths and severe impact on economies worldwide. Moreover, the emergence of SARS-CoV-2 variants presented significant challenges in controlling the pandemic, particularly their potential to avoid the immune system and evade vaccine immunity. This has led to a growing need for research to predict how mutations in SARS-CoV-2 reduces the ability of antibodies to neutralize the virus. In this study, we assembled a set of 1813 mutations from the interface of SARS-CoV-2 spike protein's receptor binding domain (RBD) and neutralizing antibody complexes and developed a machine learning model to classify high or low escape mutations using interaction energy, inter-residue contacts and predicted binding free energy change. Our approach achieved an Area under the Receiver Operating Characteristics (ROC) Curve (AUC) of 0.91 using the Random Forest classifier on the test dataset with 217 mutations. The model was further utilized to predict the escape mutations on a dataset of 29,165 mutations located at the interface of 83 RBD-neutralizing antibody complexes. A small subset of this dataset was also validated based on available experimental data. We found that top 10 % high escape mutations were dominated by charged to nonpolar mutations whereas low escape mutations were dominated by polar to nonpolar mutations. We believe that the present method will allow prioritization of high/low escape mutations in the context of neutralizing antibodies targeting SARS-CoV-2 RBD region and assist antibody design for current and emerging variants., Competing Interests: Declaration of competing interest We state that there is no conflict of interest., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Boceprevir drug is a ketoamide serine protease inhibitor with a linear peptidomimetic structure that exhibits inhibition activity against 2019-nCoV main protease. This paper reports electronic properties of boceprevir and its molecular docking as well as molecular dynamics simulation analysis with protein receptor. For this, the equilibrium structure of boceprevir has been obtained by DFT at B3LYP and ωB97XD levels with 6-311+G(d,p) basis set in gas and water mediums. HOMO-LUMO and absorption spectrum analysis have been used to evaluate the boceprevir's toxicity and photosensitivity, respectively. Molecular docking simulation has been performed to test the binding affinity of boceprevir with 2019-nCoV M PRO ; which rendered a variety of desirable binding locations between the ligand and target protein's residue positions. The optimum binding location has been considered for molecular dynamics simulation. The findings have been addressed to clarify the boceprevir drug efficacy against the 2019-nCoV M PRO ., (© 2023 Walter de Gruyter GmbH, Berlin/Boston.)

For close to 2 years, we have witnessed the impacts of the SARS-CoV-2 pandemic on research at several different levels. Among the list, limited access to laboratory-based training for undergraduate students prevented this cohort from gaining exposure to the realities of a research laboratory at a critical time in training when they may have found motivation in this area as a career. COVID exposed a weakness in our training pipeline; an extreme dependency on face-to-face training that threatened to create a void in the research talent needed to replenish the scientific community every year. In the classroom, we witnessed a revolution of e-learning based approaches that could be rapidly implemented based on existing footprints. Out of necessity, our laboratory developed and implemented an e-learning model of an undergraduate peer mentor network that provides a knowledge and experience exchange platform between students with different levels of research experience. Implementation of the platform was to aid students with gaining knowledge in multiple aspects of scientific research and hands-on work in a research laboratory. The collaboration between the students of the network was aimed at not only advancing the theoretical and practical research experience, but also at developing feedback implementation and practicing "soft skills" critical for teamwork and leadership. Herein, we present an overview of the model along with survey responses of the students participating in the peer mentor network. We have found that peer delivery of practical benchwork both via scientific presentations and visualized experiments, reduced the time of training and the amount of staff assistance needed when students returned to the bench. Furthermore, this model accelerated student independence in laboratory work and increased research interest overall. In summary, the model of a peer mentor network has the potential to serve as a training platform and as a customized tool, supplementing research laboratory training at the undergraduate level beyond the pandemic., (© 2023 The Authors. Biochemistry and Molecular Biology Education published by Wiley Periodicals LLC on behalf of International Union of Biochemistry and Molecular Biology.)

Social media is a powerful communication tool and a reflection of our digital environment. Social media acted as an augmenter and influencer during and after COVID-19. Many of the people sharing social media posts were not actually aware of their mental health status. This situation warrants to automate the detection of mental disorders. This paper presents a methodology for the detection of mental disorders using micro facial expressions. Micro-expressions are momentary, involuntary facial expressions that can be indicative of deeper feelings and mental states. Nevertheless, manually detecting and interpreting micro-expressions can be rather challenging. A deep learning HybridMicroNet model, based on convolution neural networks, is proposed for emotion recognition from micro-expressions. Further, a case study for the detection of mental health has been undertaken. The findings demonstrated that the proposed model achieved a high accuracy when attempting to diagnose mental health disorders based on micro-expressions. The attained accuracy on the CASME dataset was 99.08%, whereas the accuracy that was achieved on SAMM dataset was 97.62%. Based on these findings, deep learning may prove to be an effective method for diagnosing mental health conditions by analyzing micro-expressions., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2023 Sharma, Singh, Shah, Ali, AlZubi and AlZubi.)

Human race is preparing for the upsurge and aftermath of COVID-19 pandemic complicated by novel variants, new waves, variable mortality rate, and post-COVID complications. Despite use of repurposed drugs, symptomatic treatments and licensing of multiple vaccines, the daily number of cases and rate of transmission are significant. Culinary spices and herbs have been historically used in pandemic and non-pandemic times to reduce respiratory viral burden. Specific food items and culinary spices can boost the levels of protective immunity and also offer therapeutic benefits against impervious bugs via well-known as well as less-known but scientifically testable mechanisms. Here, we analyzed the phytochemicals profile of Ayurvedic herbs and inferred from the clinical trials/observational studies to provide a focused and succinct perspective on the relevance of "food-based" traditional decoction to moderate COVID-19 disease and long-COVID via modulation of immunity and reinstatement of homeostasis. We also underscore the druggable targets in pathogenesis of COVID-19 which are relevant to the ongoing clinical trials using spices and herbs. This information will provide a strong scientific rationale for standardization of the traditional herbs-based therapies and adopting the use of herbs, spices, and their formulations for reducing SARS-CoV-2 transmission, long-COVID symptoms, and COVID-19 disease progression., (© 2023 John Wiley & Sons Ltd.)

Background: Sudden upsurge in cases of COVID-19 Associated Mucormycosis (CAM) following the second wave of the COVID-19 pandemic was recorded in India. This study describes the clinical characteristics, management and outcomes of CAM cases, and factors associated with mortality., Methods: Microbiologically confirmed CAM cases were enrolled from April 2021 to September 2021 from ten diverse geographical locations in India. Data were collected using a structured questionnaire and entered into a web portal designed specifically for this investigation. Bivariate analyses and logistic regression were conducted using R version 4.0.2., Results: A total of 336 CAM patients were enrolled; the majority were male (n = 232, 69.1%), literate (n = 261, 77.7%), and employed (n = 224, 66.7%). The commonest presenting symptoms in our cohort of patients were oro-facial and ophthalmological in nature. The median (Interquartile Range; IQR) interval between COVID diagnosis and admission due to mucormycosis was 31 (18, 47) days, whereas the median duration of symptoms of CAM before hospitalization was 10 (5, 20) days. All CAM cases received antifungal treatment, and debridement (either surgical or endoscopic or both) was carried out in the majority of them (326, 97.02%). Twenty-three (6.9%) of the enrolled CAM cases expired. The odds of death in CAM patients increased with an increase in HbA1c level (aOR: 1.34, 95%CI: 1.05, 1.72) following adjustment for age, gender, education and employment status., Conclusion: A longer vigil of around 4-6 weeks post-COVID-19 diagnosis is suggested for earlier diagnosis of CAM. Better glycemic control may avert mortality in admitted CAM cases., (© 2023. The Author(s), under exclusive licence to Springer Nature B.V.)

COVID-19 is caused by severe acute respiratory syndrome coronavirus-2, SARS-CoV-2. COVID-19 has changed the world scenario and caused mortality around the globe. Patients who recovered from COVID-19 have shown neurological, psychological, renal, cardiovascular, pulmonary, and hematological complications. In some patients, complications lasted more than 6 months. However, significantly less attention has been given to post-COVID complications. Currently available drugs are used to tackle the complications, but new interventions must address the problem. Phytochemicals from natural sources have been evaluated in recent times to cure or alleviate COVID-19 symptoms. An edible plant, Solanum nigrum, could be therapeutic in treating COVID-19 as the AYUSH ministry of India prescribes it during the pandemic. S. nigrum demonstrates anti-inflammatory, immunomodulatory, and antiviral action to treat the SARS-CoV-2 infection and its post-complications. Different parts of the plant represent a reduction in proinflammatory cytokines and prevent multi-organ failure by protecting various organs (liver, kidney, heart, neuro, and lung). The review proposes the possible role of the plant S. nigrum in managing the symptoms of COVID-19 and its post-COVID complications based on in silico docking and pharmacological studies. Further systematic and experimental studies are required to validate our hypothesis., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

To mitigate COVID-19-related shortage of treatment capacity, the hepatopancreatobiliary (HPB) unit of the Royal Free Hospital London (RFHL) transferred its practice to independent hospitals in Central London through the North Central London Cancer Alliance. The aim of this study was to critically assess this strategy and evaluate perioperative outcomes. Prospectively collected data were reviewed on all patients who were treated under the RFHL HPB unit in six hospitals between November 2020 and October 2021. A total of 1541 patients were included, as follows: 1246 (81%) at the RFHL, 41 (3%) at the Chase Farm Hospital, 23 (2%) at the Whittington Hospital, 207 (13%) at the Princess Grace Hospital, 12 (1%) at the Wellington Hospital and 12 (1%) at the Lister Hospital, Chelsea. Across all institutions, overall complication rate were 40%, major complication (Clavien-Dindo grade ≥ 3a) rate were 11% and mortality rates were 1.4%, respectively. In COVID-19-positive patients (n = 28), compared with negative patients, complication rate and mortality rates were increased tenfold. Outsourcing HPB patients, including their specialist care, to surrounding institutions was safe and ensured ongoing treatment with comparable outcomes among the institutions during the COVID-19 pandemic. Due to the lack of direct comparison with a non-pandemic cohort, these results can strictly only be applied within a pandemic setting., (© 2023. Springer Nature Limited.)

Objective: To find out differences in the presentation, management and outcomes of COVID-19 infected STEMI patients compared to age and sex-matched non-infected STEMI patients treated during the same period., Methods: This was a retrospective multicentre observational registry in which we collected data of COVID-19 positive STEMI patients from selected tertiary care hospitals across India. For every COVID-19 positive STEMI patient, two age and sex-matched COVID-19 negative STEMI patients were enrolled as control. The primary endpoint was a composite of in-hospital mortality, re-infarction, heart failure, and stroke., Results: 410 COVID-19 positive STEMI cases were compared with 799 COVID-19 negative STEMI cases. The composite of death/reinfarction/stroke/heart failure was significantly higher among the COVID-19 positive STEMI patients compared with COVID-19 negative STEMI cases (27.1% vs 20.7% p value = 0.01); though mortality rate did not differ significantly (8.0% vs 5.8% p value = 0.13). Significantly lower proportion of COVID-19 positive STEMI patients received reperfusion treatment and primary PCI (60.7% vs 71.1% p value=< 0.001 and 15.4% vs 23.4% p value = 0.001 respectively). Rate of systematic early PCI (pharmaco-invasive treatment) was significantly lower in the COVID-19 positive group compared with COVID-19 negative group. There was no difference in the prevalence of high thrombus burden (14.5% and 12.0% p value = 0.55 among COVID-19 positive and negative patients respectively) CONCLUSIONS: In this large registry of STEMI patients, we did not find significant excess in in-hospital mortality among COVID-19 co-infected patients compared with non-infected patients despite lower rate of primary PCI and reperfusion treatment, though composite of in-hospital mortality, re-infarction, stroke and heart failure was higher., (Copyright © 2023 Cardiological Society of India. Published by Elsevier, a division of RELX India, Pvt. Ltd. All rights reserved.)

The utility of telemedicine in healthcare has been brought to the forefront by the COVID-19 pandemic. 'SwasthGarbh' (Healthy Pregnancy) is a multi-functional, interactive smartphone application for providing antenatal care and real-time medical support to all pregnant women (especially those in rural areas and/or do not have easy access to doctors). A randomized controlled trial (n = 150) demonstrates its utility in improving the quality of antenatal care, reducing obstetric/medical complications and achieving a positive pregnancy experience. The test group (patients registered on the App) showed a significantly higher number of mean (± SD) antenatal visits (7.0 ± 1.5 vs. 5.7 ± 1.8; P < 0.001) as well as better compliance with the WHO visit protocol (87.2% vs. 69.8%, P < 0.001) and antenatal investigations (73.2% vs. 41.7%, P<0.001) in comparison to the control group (followed-up conventionally), respectively. Furthermore, substantial reduction in medical (38.0% vs. 55.5%, P = 0.04) and obstetric (52.1% vs. 59.7%, P = 0.36) complications during pregnancy as well as significant improvement in mean (± SD) maternal systolic BP (118.9 ± 11.8 vs. 123.4 ± 14.2 mmHg; P = 0.046), diastolic BP (76.0 ± 8.4 vs. 80.0 ± 10.9 mmHg; P = 0.02) and hemoglobin (11.5 ± 1.4 vs. 10.9 ± 1.4 g/dL; P = 0.03) parameters at delivery was observed in the test group compared to the controls, respectively. All the above mentioned positive clinical outcomes were the result of the provision of high quality antenatal care, timely detection of complications, prompt medical assistance and improved medication adherence. This is first pregnancy App that provides instantaneous access to doctor's advice and is clinically endorsed as well as credible.

Background: Influenza poses a major public health challenge in South-East Asia Region (SEAR). To address the challenge, there is a need to generate contextual evidence that could inform policy makers and program managers for response preparedness and impact mitigation. The World Health Organization has identified priority areas across five streams for research evidence generation at a global level (WHO Public Health Research Agenda). Stream 1 focuses on research for reducing the risk of emergence, Stream 2 on limiting the spread, Stream 3 on minimizing the impact, Stream 4 on optimizing the treatment and Stream 5 on promoting public health tools and technologies for Influenza. However, evidence generation from SEAR has been arguably low and needs a relook for alignment with priorities. This study aimed to undertake a bibliometric analysis of medical literature on Influenza over the past 21 years to identify gaps in research evidence and for identifying major areas for focusing with a view to provide recommendations to member states and SEAR office for prioritizing avenues for future research., Methods: We searched Scopus, PubMed, Embase, and Cochrane databases in August 2021. We identified studies on influenza published from the 11 countries in WHO SEAR in the date range of 1 January 2000-31 December 2021. Data was retrieved, tagged and analyzed based on the WHO priority streams for Influenza, member states, study design and type of research. Bibliometric analysis was done on Vosviewer., Findings: We included a total of 1,641 articles (Stream 1: n  = 307; Stream 2: n  = 516; Stream 3: n  = 470; Stream 4: n  = 309; Stream 5: n  = 227). Maximum number of publications were seen in Stream 2, i.e., limiting the spread of pandemic, zoonotic, and seasonal epidemic influenza which majorly included transmission, spread of virus at global and local levels and public health measures to limit the transmission. The highest number of publications was from India ( n  = 524) followed by Thailand ( n  = 407), Indonesia ( n  = 214) and Bangladesh ( n  = 158). Bhutan ( n  = 10), Maldives ( n  = 1), Democratic People's Republic of Korea ( n  = 1), and Timor-Leste ( n  = 3) had the least contribution in Influenza research. The top-most journal was PloS One which had the maximum number of influenza articles ( n  = 94) published from SEAR countries. Research that generated actionable evidence, i.e., implementation and intervention related topics were less common. Similarly, research on pharmaceutical interventions and on innovations was low. SEAR member states had inconsistent output across the five priority research streams, and there was a much higher scope and need for collaborative research. Basic science research showed declining trends and needed reprioritization., Interpretation: While a priority research agenda has been set for influenza at the global level through the WHO Global Influenza Program since 2009, and subsequently revisited in 2011 and again in 2016-2017, a structured contextualized approach to guide actionable evidence generation activities in SEAR has been lacking. In the backset of the Global Influenza Strategy 2019-2030 and the COVID-19 pandemic, attuning research endeavors in SEAR could help in improved pandemic influenza preparedness planning. There is a need to prioritize contextually relevant research themes within priority streams. Member states must inculcate a culture of within and inter-country collaboration to produce evidence that has regional as well as global value., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Ranjan Wijesinghe, Sharma, Vaishnav, Mukherjee, Pawar, Mohapatra, Buddha, Ceniza Salvador and Kakkar.)

Context: A healthy lifestyle has been the need of the hour during the COVID 19 pandemic. Analyzing the current lifestyle patterns of many individuals can be the basis for finding solutions toward building a healthy future for India., Objectives: The study intended to evaluate the current lifestyles of adults in an urban setting in the midst of a pandemic and to examine the diseases that people could face with respect to their current lifestyles., Design: The research team performed a cross-sectional study., Setting: The survey was conducted in an urban setting in the Pimpri Chinchwad area of Pune, India., Participants: Participants were 500 men and women between the ages of 18 and 25., Outcome Measures: The research team created a survey with 13 multiple-choice questions., Results: The pandemic has taken a toll on people's mental and physical health. Social distancing and staying indoors for long periods are factors that have affected people's mental health., Conclusions: Efforts need to be made by individuals to focus not only on their physical health but also on their mental health.

Coronavirus disease (COVID-19) is a class of SARS-CoV-2 virus which is initially identified in the later half of the year 2019 and then evolved as a pandemic. If it is not identified in the early stage then the infection and mortality rates increase with time. A timely and reliable approach for COVID-19 identification has become important in order to prevent the disease from spreading rapidly. In recent times, many methods have been suggested for the detection of COVID-19 disease have various flaws, to increase diagnosis performance, fresh investigations are required. In this article, automatically diagnosing COVID-19 using ECG images and deep learning approaches like as Visual Geometry Group (VGG) and AlexNet architectures have been proposed. The proposed method is able to classify between COVID-19, myocardial infarction, normal sinus rhythm, and other abnormal heart beats using Lead-II ECG image only. The efficacy of the technique proposed is validated by using a publicly available ECG image database. We have achieved an accuracy of 77.42% using Alexnet model and 75% accuracy with the help of VGG19 model., (© 2023 IOP Publishing Ltd.)

Aim: This study was aimed to determine antimicrobial and antiviral activity of a novel lanthipeptide from a Brevibacillus sp. for disinfectant application., Methods and Results: The antimicrobial peptide (AMP) was produced by a bacterial strain AF8 identified as a member of the genus Brevibacillus representing a novel species. Whole genome sequence analysis using BAGEL identified a putative complete biosynthetic gene cluster involved in lanthipeptide synthesis. The deduced amino acid sequence of lanthipeptide named as brevicillin, showed >30% similarity with epidermin. Mass determined by MALDI-MS and Q-TOF suggested posttranslational modifications like dehydration of all Ser and Thr amino acids to yield Dha and Dhb, respectively. Amino acid composition determined upon acid hydrolysis is in agreement with core peptide sequence deduced from the putative biosynthetic gene bvrAF8. Biochemical evidence along with stability features ascertained posttranslational modifications during formation of the core peptide. The peptide showed strong activity with 99% killing of pathogens at 12 μg ml-1 within 1 minute. Interestingly, it also showed potent anti-SARS-CoV-2 activity by inhibiting ∼99% virus growth at 10 μg ml-1 in cell culture-based assay. Brevicillin did not show dermal allergic reactions in BALB/c mice., Conclusion: This study provides detailed description of a novel lanthipeptide and demonstrates its effective antibacterial, antifungal and anti-SARS-CoV-2 activity., (© The Author(s) 2023. Published by Oxford University Press on behalf of Applied Microbiology International.)

BACKGROUND: Optimal thromboprophylaxis for hospitalized patients with coronavirus disease 2019 (Covid-19) is uncertain. METHODS: In an open-label, adaptive platform trial, we randomly assigned hospitalized adults with Covid-19 to low-dose low-molecular-weight heparin thromboprophylaxis or intermediate-dose or low-dose plus aspirin. In response to external evidence, the aspirin intervention was discontinued and a therapeutic-dose arm added. The primary end point was death or the requirement for new organ support by day 28, analyzed with a Bayesian logistic model. Enrolment was closed as a result of operational constraints. RESULTS: Between February 2021 and March 2022, 1574 patients were randomly assigned. Among 1526 participants included in the analysis (India, n=1273; Australia and New Zealand, n=138; and Nepal, n=115), the primary outcome occurred in 35 (5.9%) of 596 in low-dose, 25 (4.2%) of 601 in intermediate-dose, 20 (7.2%) of 279 in low-dose plus aspirin, and 7 (14%) of 50 in therapeutic-dose anticoagulation. Compared with low-dose thromboprophylaxis, the median adjusted odds ratio for the primary outcome for intermediate-dose was 0.74 (95% credible interval [CrI], 0.43 to 1.27; posterior probability of effectiveness [adjusted odds ratio<1; Pr], 86%), for low-dose plus aspirin 0.88 (95% CrI, 0.47 to 1.64; Pr, 65%), and for therapeutic-dose anticoagulation 2.22 (95% CrI, 0.77 to 6.20; Pr, 7%). Overall thrombotic and bleeding rates were 0.8% and 0.4%, respectively. There were 10 serious adverse reactions related to anticoagulation strategy, of which nine were grade 1 or 2 across study interventions and one grade 4 episode of retroperitoneal hematoma in a patient receiving intermediate-dose anticoagulation. CONCLUSIONS: In hospitalized non–critically ill adults with Covid-19, compared with low-dose, there was an 86% posterior probability that intermediate-dose, 65% posterior probability that low-dose plus aspirin, and a 7% posterior probability that therapeutic-dose anticoagulation reduced the odds of death or requirement for organ support. No treatment strategy met prespecified stopping criteria before trial closure, precluding definitive conclusions. (Funded by Australian National Health and Medical Research Council or Medical Research Future Fund Investigator and Practitioner Grants and others; ClinicalTrials.gov number, NCT04483960.)

Reprogrammed cell metabolism has been observed in a wide range of virally infected cells. Viruses do not have their metabolism; they rely on the cellular metabolism of the host to ensure the energy and macromolecules requirement for replication. Like other viruses, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) does not own its metabolism, but virus infected cells adopt aberrant cell metabolism. Infected viral use the energy and macromolecules to make their own copies; to do so, they need to increase the rate of metabolism to ensure the requirement of macromolecules. In contrast, the cellular metabolism of noninfected cells is more plastic than infected cells. Therefore, it is essential to examine the virus infection in the context of metabolic alterations of host cells. A novel therapeutic approach is urgently required to treat highly infectious COVID-19 disease and its pathogenesis. Interference of glucose metabolism might be a promising strategy to determine COVID-19 treatment options. Based on the recent research, this mini-review aims to understand the impact of reprogrammed cell metabolism in COVID-19 pathogenesis and explores the potential of targeting metabolic pathways with small molecules as a new strategy for the development of a novel drug to treat COVID-19 disease. This type of research line provides new hope in the development of antiviral drugs by targeting hijacked cell metabolism in case of viral diseases and also in COVID-19., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

The emergence of new variants seems to perpetually prolong the COVID-19 pandemic. On top of that, the waning of vaccine protection is further thwarting our efforts to end it. Our article discusses the incessant question raging in everybody's mind: Are we ever going to win?, (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

As T cells transit between blood, lymphoid organs, and peripheral tissues, they experience varied levels of oxygen/hypoxia in inflamed tissues, skin, intestinal lining, and secondary lymphoid organs. Critical illness among COVID-19 patients is also associated with transient hypoxia and attenuation of T cell responses. Hypoxia is the fulcrum of altered metabolism, impaired functions, and cessation of growth of a subset of T cells. However, the restoration of normal T cell functions following transient hypoxia and kinetics of their phenotype-redistribution is not completely understood. Here, we sought to understand kinetics and reversibility of dichotomous T cell responses under sustained and transient hypoxia. We found that a subset of activated T cells accumulated as lymphoblasts under hypoxia. Further, T cells showed the normal expression of activation markers CD25 and CD69 and inflammatory cytokine secretion but a subset exhibited delayed cell proliferation under hypoxia. Increased levels of reactive oxygen species (ROS) in cytosol and mitochondria were seen during dichotomous and reversible attenuation of T cell response under hypoxia. Cell cycle analysis revealed maximum levels of cytosolic and mitochondrial ROS in dividing T cells (in S, G2, or M phase). Hypoxic T cells also showed specific attenuation of activation induced memory phenotype conversion without affecting naïve and activated T cells. Hypoxia-related attenuation of T cell proliferation was also found to be reversible in an allogeneic leukocyte specific mixed lymphocyte reaction assay. In summary, our results show that hypoxia induces a reversible delay in proliferation of a subset of T cells which is associated with obliteration of memory phenotype and specific increase in cytosolic/mitochondrial ROS levels in actively dividing subpopulation. Thus, the transient reoxygenation of hypoxic patients may restore normal T cell responses.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant of concern (VoC) Omicron (B.1.1.529) has rapidly spread around the world, presenting a new threat to global public human health. Due to the large number of mutations accumulated by SARS-CoV-2 Omicron, concerns have emerged over potentially reduced diagnostic accuracy of reverse-transcription polymerase chain reaction (RT-qPCR), the gold standard diagnostic test for diagnosing coronavirus disease 2019 (COVID-19). Thus, we aimed to assess the impact of the currently endemic Omicron sublineages BA.4 and BA.5 on the integrity and sensitivity of RT-qPCR assays used for coronavirus disease 2019 (COVID-19) diagnosis via in silico analysis. We employed whole genome sequencing data and evaluated the potential for false negatives or test failure due to mismatches between primers/probes and the Omicron VoC viral genome., Methods: In silico sensitivity of 12 RT-qPCR tests (containing 30 primers and probe sets) developed for detection of SARS-CoV-2 reported by the World Health Organization (WHO) or available in the literature, was assessed for specifically detecting SARS-CoV-2 Omicron BA.4 and BA.5 sublineages, obtained after removing redundancy from publicly available genomes from National Center for Biotechnology Information (NCBI) and Global Initiative on Sharing Avian Influenza Data (GISAID) databases. Mismatches between amplicon regions of SARS-CoV-2 Omicron VoC and primers and probe sets were evaluated, and clustering analysis of corresponding amplicon sequences was carried out., Results: From the 1164 representative SARS-CoV-2 Omicron VoC BA.4 sublineage genomes analyzed, a substitution in the first five nucleotides (C to T) of the amplicon's 3'-end was observed in all samples resulting in 0% sensitivity for assays HKUnivRdRp/Hel (mismatch in reverse primer) and CoremCharite N (mismatch in both forward and reverse primers). Due to a mismatch in the forward primer's 5'-end (3-nucleotide substitution, GGG to AAC), the sensitivity of the ChinaCDC N assay was at 0.69%. The 10 nucleotide mismatches in the reverse primer resulted in 0.09% sensitivity for Omicron sublineage BA.4 for Thai N assay. Of the 1926 BA.5 sublineage genomes, HKUnivRdRp/Hel assay also had 0% sensitivity. A sensitivity of 3.06% was observed for the ChinaCDC N assay because of a mismatch in the forward primer's 5'-end (3-nucleotide substitution, GGG to AAC). Similarly, due to the 10 nucleotide mismatches in the reverse primer, the Thai N assay's sensitivity was low at 0.21% for sublineage BA.5. Further, eight assays for BA.4 sublineage retained high sensitivity (more than 97%) and 9 assays for BA.5 sublineage retained more than 99% sensitivity., Conclusion: We observed four assays (HKUnivRdRp/Hel, ChinaCDC N, Thai N, CoremCharite N) that could potentially result in false negative results for SARS-CoV-2 Omicron VoCs BA.4 and BA.5 sublineages. Interestingly, CoremCharite N had 0% sensitivity for Omicron Voc BA.4 but 99.53% sensitivity for BA.5. In addition, 66.67% of the assays for BA.4 sublineage and 75% of the assays for BA.5 sublineage retained high sensitivity. Further, amplicon clustering and additional substitution analysis along with sensitivity analysis could be used for the modification and development of RT-qPCR assays for detecting SARS-CoV-2 Omicron VoC sublineages., (© 2022 Wiley Periodicals LLC.)

Viruses are widely recognized as the primary cause of infectious diseases around the world. The ongoing global pandemic due to the emergence of SARS-CoV-2 further added fuel to the fire. The development of therapeutics becomes very difficult as viruses can mutate their genome to become more complex and resistant. Medicinal plants and phytocompounds could be alternative options. Isoquinoline and their related alkaloids are naturally occurring compounds that interfere with multiple pathways including nuclear factor-κB, mitogen-activated protein kinase/extracellular-signal-regulated kinase, and inhibition of Ca 2+ -mediated fusion. These pathways play a crucial role in viral replication. Thus, the major goal of this study is to comprehend the function of various isoquinoline and related alkaloids in viral infections by examining their potential mechanisms of action, structure-activity relationships (SAR), in silico (particularly for SARS-CoV-2), in vitro and in vivo studies. The current advancements in isoquinoline and related alkaloids as discussed in the present review could facilitate an in-depth understanding of their role in the drug discovery process.

It would be apt to say that one of the greatest accomplishments in modern medicine has been the development of vaccines against COVID-19, which had paralyzed the entire world for more than a year. Pfizer and BioNTech codeveloped the first COVID-19 vaccine that was granted emergency-use authorization or conditional approval in several regions globally. This article is an attempt to go 'behind-the-scenes' of this development process and highlight key factors that allowed us to move with this unprecedented speed, while adhering to normal vaccine-development requirements to generate the information the regulatory authorities needed to assess the safety and effectiveness of a vaccine to prevent an infectious disease, including quality and manufacturing standards. This is also a story of how Pfizer and BioNTech leveraged our combined skill sets and experience to respond to the global health crisis to progress this program swiftly while ensuring the compliance with our high-quality standards and keeping patient safety at the forefront. We will also highlight multiple other factors that were instrumental in our success., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Aim: Achieve an international consensus on how to recover lost training opportunities. The results of this study will help inform future EAES guidelines about the recovery of surgical training before and after the pandemic., Background: A global survey conducted by our team demonstrated significant disruption in surgical training during the COVID-19 pandemic. This was wide-spread and affected all healthcare systems (whether insurance based or funded by public funds) in all participating countries. Thematic analysis revealed the factors perceived by trainees as barriers to training and gave birth to four-point framework of recovery. These are recommendations that can be easily achieved in any country, with minimal resources. Their implementation, however, relies heavily on the active participation and leadership by trainers. Based on the results of the global trainee survey, the authors would like to conduct a Delphi-style survey, addressed to trainers on this occasion, to establish a pragmatic step-by-step approach to improve training during and after the pandemic., Methods: This will be a mixed qualitative and quantitative study. Semi-structured interviews will be performed with laparoscopic trainers. These will be transcribed and thematic analysis will be applied. A questionnaire will then be proposed; this will be based on both the results of the semi structured interviews and of the global trainee survey. The questionnaire will then be validated by the steering committee of this group (achieve consensus of >80%). After validation, the questionnaire will be disseminated to trainers across the globe. Participants will be asked to consent to participate in further cycles of the Delphi process until more than 80% agreement is achieved., Results: This study will result in a pragmatic framework for continuation of surgical training during and after the pandemic (with special focus on minimally invasive surgery training)., Competing Interests: The authors have declared that no competing interests exist.

At the end of 2019 and 2020s, a wave of coronavirus disease 19 (COVID-19) epidemics worldwide has catalyzed a new era of 'communicable infectious diseases'. However, the world is not currently prepared to deal with the growing burden of COVID-19, with the unexpected arrival of Hantavirus infection heading to the next several healthcare emergencies in public. Hantavirus is a significant class of zoonotic pathogens of negative-sense single-stranded ribonucleic acid (RNA). Hemorrhagic renal syndrome (HFRS) and hantavirus cardiopulmonary syndrome (HCPS) are the two major clinical manifestations. Till date, there is no effective treatments or vaccines available, public awareness and precautionary measures can help to reduce the spread of hantavirus disease. In this study, we outline the epidemiology, virology, clinical aspects, and existing HFRS and HCPS management approaches. This review will give an understanding of virus-host interactions and will help for the early preparation and effective handling of further outbreaks in an ever-changing environment.

The prolonged transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus in the human population has led to demographic divergence and the emergence of several location-specific clusters of viral strains. Although the effect of mutation(s) on severity and survival of the virus is still unclear, it is evident that certain sites in the viral proteome are more/less prone to mutations. In fact, millions of SARS-CoV-2 sequences collected all over the world have provided us a unique opportunity to understand viral protein mutations and develop novel computational approaches to predict mutational patterns. In this study, we have classified the mutation sites into low and high mutability classes based on viral isolates count containing mutations. The physicochemical features and structural analysis of the SARS-CoV-2 proteins showed that features including residue type, surface accessibility, residue bulkiness, stability and sequence conservation at the mutation site were able to classify the low and high mutability sites. We further developed machine learning models using above-mentioned features, to predict low and high mutability sites at different selection thresholds (ranging 5-30% of topmost and bottommost mutated sites) and observed the improvement in performance as the selection threshold is reduced (prediction accuracy ranging from 65 to 77%). The analysis will be useful for early detection of variants of concern for the SARS-CoV-2, which can also be applied to other existing and emerging viruses for another pandemic prevention., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Heparin-induced thrombocytopenia (HIT) occurs with the development of IgG antibodies that bind complexes of heparin and platelet factor 4 (PF4), which activate platelets and result in a profoundly prothrombotic condition. In rare instances, this syndrome develops in the absence of proximate heparin administration, referred to as spontaneous HIT, for which less than three dozen cases have been reported. Spontaneous HIT is considered a subtype of "autoimmune HIT" (aHIT), characterized by platelet activation in the serotonin release assay (SRA) without the addition of exogenous heparin. Here, we report spontaneous HIT as the presenting feature in a patient with 2019 coronavirus disease infection (COVID-19).A 66-year-old male presented with progressive leg pain and was found to have a platelet count of 39 × 10 9 /L and multiple lower extremity arterial thromboses requiring fasciotomy and thrombectomy. He had no recent hospitalization, heparin exposure, vaccinations, or known thrombophilia. He had a strongly positive IgG-specific enzyme-linked immunosorbent assay for heparin-PF4 antibodies, and the SRA was strongly positive both with and without the addition of heparin. He was treated successfully with bivalirudin, intravenous immunoglobulin, and apixaban., (© 2022. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Data science has been an invaluable part of the COVID-19 pandemic response with multiple applications, ranging from tracking viral evolution to understanding the vaccine effectiveness. Asymptomatic breakthrough infections have been a major problem in assessing vaccine effectiveness in populations globally. Serological discrimination of vaccine response from infection has so far been limited to Spike protein vaccines since whole virion vaccines generate antibodies against all the viral proteins. Here, we show how a statistical and machine learning (ML) based approach can be used to discriminate between SARS-CoV-2 infection and immune response to an inactivated whole virion vaccine (BBV152, Covaxin). For this, we assessed serial data on antibodies against Spike and Nucleocapsid antigens, along with age, sex, number of doses taken, and days since last dose, for 1823 Covaxin recipients. An ensemble ML model, incorporating a consensus clustering approach alongside the support vector machine model, was built on 1063 samples where reliable qualifying data existed, and then applied to the entire dataset. Of 1448 self-reported negative subjects, our ensemble ML model classified 724 to be infected. For method validation, we determined the relative ability of a random subset of samples to neutralize Delta versus wild-type strain using a surrogate neutralization assay. We worked on the premise that antibodies generated by a whole virion vaccine would neutralize wild type more efficiently than delta strain. In 100 of 156 samples, where ML prediction differed from self-reported uninfected status, neutralization against Delta strain was more effective, indicating infection. We found 71.8% subjects predicted to be infected during the surge, which is concordant with the percentage of sequences classified as Delta (75.6%-80.2%) over the same period. Our approach will help in real-world vaccine effectiveness assessments where whole virion vaccines are commonly used., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Responding to the fast transmission rates and increasing fatality rates, countries across the world expedited the development and deployment of the vaccine for coronavirus disease 2019 (COVID-19). Evaluation of individuals' willingness to pay (WTP) would provide pertinent information regarding future demand and financing preferences, which shall help to devise the effective payment strategy for COVID-19 vaccination., Methods: A nationwide, cross-sectional, and self-administered online survey using a structured questionnaire was conducted to identify the sociodemographic determinants of willingness and extent to pay for COVID-19 vaccine in India. A non-probability convenience sampling followed by snowball sampling was employed to recruit participants ( n = 3,341). The likelihood of sociodemographic determinants to predict willingness and extent to pay was modeled using the multivariate binary logistic regression analysis., Results: Out of 3,341 participants, 68% ( n = 2,271) were willingness to pay for COVID-19 vaccine. Results showed significantly higher odds for willingness to pay among participants who were single [adjusted odds ratio (aOR) = 1.394, p < 0.01] and having a family size of 4 members (aOR = 1.346, p < 0.01). The adjusted odds ratio sizably increased from 1.396 for participants whose monthly income was between INR 10,000 and 20,000/month to 2.240 for participants whose monthly income was above INR 50,000/month. Further, out of 2,271 of those participants who were willingness to pay for COVID-19 vaccine, majority ( n = 1,246, 54.9%) of participants were willingness to pay below 50% of COVID-19 vaccine cost. This study found that those who are single (aOR = 0.688, p < 0.01), having an income between INR 20,000 and 50,000/month (aOR = 0.686, p < 0.05), and those who belonged to socially disadvantaged category (aOR = 0.450, p < 0.01) were estimated to have significantly lower odds of willingness to pay more than 50% of COVID-19 vaccine cost., Conclusion: This study observed that majority of those participants who willingness to pay for COVID-19 vaccine were willingness to pay only up to 50% of COVID-19 vaccine and income was observed as a precursor predictor of the willingness and extent to pay for COVID-19 vaccine. The understanding on the willingness and extent to pay for COVID-19 vaccine and its sociodemographic determinants will be helpful for making the strategic decisions related to the financing of COVID vaccine in India., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Kiran, Junaid, Sharma, Jain, Vij, Satapathy, Chakrapani, Patro, Kar, Singh, Pala, Bali, Rustagi, Goel, Sankhe, Modi, Gupta, Aggarwal, Rajagopal and Padhi.)

Objective: The coronavirus disease (COVID-19) pandemic was initiated in Wuhan Province of mainland China in December 2019 and has spread over the world. This study analyzes the effects of COVID-19 based on likely positive cases and fatality in India during and after the lockdown period from March 24, 2020, to May 24, 2020., Methods: Python has been used as the main programming language for data analysis and forecasting using the Prophet model, a time series analysis model. The data set has been preprocessed by grouping together the days for total numbers of cases and deaths on few selected dates and removing missing values present in some states., Results: The Prophet model performs better in terms of precision on the real data. Prediction depicts that, during the lockdown, the total cases were rising but in a controlled manner with an accuracy of 87%. After the relaxation of lockdown rules, the predictions have shown an obstreperous situation with an accuracy of 60%., Conclusion: The resilience could have been better if the lockdown with strict norms was continued without much relaxation. The situation after lockdown has been found to be uncertain as observed by the experimental study conducted in this work.

Since the emergence of novel Coronavirus (SARS-CoV-2) infection in Wuhan, China in December 2019, it has now spread to over 205 countries. The ever-growing list of globally spread corona virus-19 disease (COVID-19) patients has demonstrated the high transmission rate among the human population. Currently, there are no FDA approved drugs or vaccines to prevent and treat the infection of the SARS-CoV-2. Considering the current state of affairs, there is an urgent unmet medical need to identify novel and effective approaches for the prevention and treatment of COVID-19 by re-evaluating the knowledge of traditional medicines and repurposing of drugs. Here, we used molecular docking and molecular dynamics simulation approach to explore the beneficial roles of phytochemicals and active pharmacological agents present in the Indian herbs which are widely used in the preparation of Ayurvedic medicines in the form of Kadha to control various respiratory disorders such as cough, cold and flu. Our study has identified an array of phytochemicals present in these herbs which have significant docking scores and potential to inhibit different stages of SARS-CoV-2 infection as well as other Coronavirus target proteins. The phytochemicals present in these herbs possess significant anti-inflammatory property. Apart from this, based on their pharmaceutical characteristics, we have also performed in-silico drug-likeness and predicted pharmacokinetics of the selected phytochemicals found in the Kadha. Overall our study provides scientific justification in terms of binding of active ingredients present in different plants used in Kadha preparation with viral proteins and target proteins for prevention and treatment of the COVID-19.Communicated by Ramaswamy H. Sarma.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enters human host cells via angiotensin-converting enzyme 2 (ACE2) and causes coronavirus disease 2019 (COVID-19). Here, through a genome-wide association study, we identify a variant (rs190509934, minor allele frequency 0.2-2%) that downregulates ACE2 expression by 37% (P = 2.7 × 10 - 8 ), providing human genetic evidence that ACE2 expression levels influence COVID-19 risk. We also replicate the associations of six previously reported risk variants, of which four were further associated with worse outcomes in individuals infected with the virus (in/near LZTFL1, MHC, DPP9 and IFNAR2). Lastly, we show that common variants define a risk score that is strongly associated with severe disease among cases and modestly improves the prediction of disease severity relative to demographic and clinical factors alone.- 13 ), providing human genetic evidence that ACE2 expression levels influence COVID-19 risk. We also replicate the associations of six previously reported risk variants, of which four were further associated with worse outcomes in individuals infected with the virus (in/near LZTFL1, MHC, DPP9 and IFNAR2). Lastly, we show that common variants define a risk score that is strongly associated with severe disease among cases and modestly improves the prediction of disease severity relative to demographic and clinical factors alone., (© 2022. The Author(s).)

Corona virus disease 2019 started in December 2019 as an outbreak of unexplained pneumonias in Wuhan, a city in Hubei province of China. This illness emerged as an epidemic in China and later spread to almost all countries over the globe except Antarctica. This is caused by a beta Corona virus, which is genetically similar to SARS virus. The predominant mode of transmission is via droplet spread, when the infected person coughs, sneezes or talks the virus is released in the respiratory secretions. As there are only a few cases of COVID 19 in neonates, there is no convincing evidence to support the possibility of vertical transmission. Clinical presentation in neonates is nonspecific, commonly observed are temperature instability, respiratory distress, poor feeding, lethargy, vomiting and diarrhea. Laboratory examinations may be nonspecific. Definitive test for 2019-nCoV is the detection of viral nucleic acid by real-time fluorescence polymerase chain reaction (RT-PCR). Suspected and confirmed COVID positive mothers should be delivered in separate delivery rooms and operation theaters. Since there is no approved treatment or drug for this disease, prevention of infection and breaking the chain of transmission plays a crucial role.

The coronavirus disease 2019 (COVID-19) has affected the lives of millions of people around the world. In an effort to develop therapeutic interventions and control the pandemic, scientists have isolated several neutralizing antibodies against SARS-CoV-2 from the vaccinated and convalescent individuals. These antibodies can be explored further to understand SARS-CoV-2 specific antigen-antibody interactions and biophysical parameters related to binding affinity, which can be utilized to engineer more potent antibodies for current and emerging SARS-CoV-2 variants. In the present study, we have analyzed the interface between spike protein of SARS-CoV-2 and neutralizing antibodies in terms of amino acid residue propensity, pair preference, and atomic interaction energy. We observed that Tyr residues containing contacts are highly preferred and energetically favorable at the interface of spike protein-antibody complexes. We have also developed a regression model to relate the experimental binding affinity for antibodies using structural features, which showed a correlation of 0.93. Moreover, several mutations at the spike protein-antibody interface were identified, which may lead to immune escape (epitope residues) and improved affinity (paratope residues) in current/emerging variants. Overall, the work provides insights into spike protein-antibody interactions, structural parameters related to binding affinity and mutational effects on binding affinity change, which can be helpful to develop better therapeutics against COVID-19., (© 2021 Wiley Periodicals LLC.)

In the milieu of coronavirus disease 2019 (COVID-19), there are increasing reports of paediatric hyperinflammatory conditions (PHICs), including multisystem inflammatory syndrome in children (MIS-C), paediatric multisystem inflammatory syndrome temporally associated with SARS-CoV-2 (PIMS-TS) and Kawasaki disease (KD). Few analyses of PHIC prevalence in paediatric and adolescent hospitalized COVID-19 patients exist. The purpose of this study was to perform a meta-analysis to determine a pooled prevalence estimate of PHICs in paediatric and adolescent hospitalized patients admitted for treatment due to COVID-19. Individual studies were retrieved from PubMed/Medline, EMBASE and Cochrane databases. Relevant prevalence, baseline, treatment and outcome data were extracted using a standardized datasheet. The systematic review and meta-analysis were conducted as per the PRISMA and MOOSE guidelines. Overall, 14 studies with 2202 patients admitted for treatment due to COVID-19, among whom 780 were diagnosed with PHICs, were included. The crude estimate of prevalence was 35.42%, and the pooled estimate of prevalence was 29% (random pooled ES = 0.29; 95% CIs = 0.18-0.42; p < 0.0001; z = 7.45). A sizeable proportion of paediatric and adolescent hospitalized patients admitted for treatment due to COVID-19 are diagnosed with a PHIC warranting a high index of clinical suspicion for PHICs. Further studies are required to validate these findings., (© 2021 Scandinavian Societies for Medical Microbiology and Pathology.)

Background: The adoption of nonpharmaceutical interventions and their surveillance are critical for detecting and stopping possible transmission routes of COVID-19. A study of the effects of these interventions can help shape public health decisions. The efficacy of nonpharmaceutical interventions can be affected by public behaviors in events, such as protests. We examined mask use and mask fit in the United States, from social media images, especially during the Black Lives Matter (BLM) protests, representing the first large-scale public gatherings in the pandemic., Objective: This study assessed the use and fit of face masks and social distancing in the United States and events of large physical gatherings through public social media images from 6 cities and BLM protests., Methods: We collected and analyzed 2.04 million public social media images from New York City, Dallas, Seattle, New Orleans, Boston, and Minneapolis between February 1, 2020, and May 31, 2020. We evaluated correlations between online mask usage trends and COVID-19 cases. We looked for significant changes in mask use patterns and group posting around important policy decisions. For BLM protests, we analyzed 195,452 posts from New York and Minneapolis from May 25, 2020, to July 15, 2020. We looked at differences in adopting the preventive measures in the BLM protests through the mask fit score., Results: The average percentage of group pictures dropped from 8.05% to 4.65% after the lockdown week. New York City, Dallas, Seattle, New Orleans, Boston, and Minneapolis observed increases of 5.0%, 7.4%, 7.4%, 6.5%, 5.6%, and 7.1%, respectively, in mask use between February 2020 and May 2020. Boston and Minneapolis observed significant increases of 3.0% and 7.4%, respectively, in mask use after the mask mandates. Differences of 6.2% and 8.3% were found in group pictures between BLM posts and non-BLM posts for New York City and Minneapolis, respectively. In contrast, the differences in the percentage of masked faces in group pictures between BLM and non-BLM posts were 29.0% and 20.1% for New York City and Minneapolis, respectively. Across protests, 35% of individuals wore a mask with a fit score greater than 80%., Conclusions: The study found a significant drop in group posting when the stay-at-home laws were applied and a significant increase in mask use for 2 of 3 cities where masks were mandated. Although a positive trend toward mask use and social distancing was observed, a high percentage of posts showed disregard for the guidelines. BLM-related posts captured the lack of seriousness to safety measures, with a high percentage of group pictures and low mask fit scores. Thus, the methodology provides a directional indication of how government policies can be indirectly monitored through social media., (©Asmit Kumar Singh, Paras Mehan, Divyanshu Sharma, Rohan Pandey, Tavpritesh Sethi, Ponnurangam Kumaraguru. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 18.01.2022.)

Objective: To identify clinical and biochemical characteristics associated with 7- & 30-day mortality and intensive care admission amongst diabetes patients admitted with COVID-19., Research Design and Methods: We conducted a cohort study collecting data from medical notes of hospitalised people with diabetes and COVID-19 in 7 hospitals within the Mersey-Cheshire region from 1 January to 30 June 2020. We also explored the impact on inpatient diabetes team resources. Univariate and multivariate logistic regression analyses were performed and optimised by splitting the dataset into a training, test, and validation sets, developing a robust predictive model for the primary outcome., Results: We analyzed data from 1004 diabetes patients (mean age 74.1 (± 12.6) years, predominantly men 60.7%). 45% belonged to the most deprived population quintile in the UK. Median BMI was 27.6 (IQR 23.9-32.4) kg/m 2 . The primary outcome (7-day mortality) occurred in 24%, increasing to 33% by day 30. Approximately one in ten patients required insulin infusion (9.8%). In univariate analyses, patients with type 2 diabetes had a higher risk of 7-day mortality [p < 0.05, OR 2.52 (1.06, 5.98)]. Patients requiring insulin infusion had a lower risk of death [p = 0.02, OR 0.5 (0.28, 0.9)]. CKD in younger patients (<70 years) had a greater risk of death [OR 2.74 (1.31-5.76)]. BMI, microvascular and macrovascular complications, HbA1c, and random non-fasting blood glucose on admission were not associated with mortality. On multivariate analysis, CRP and age remained associated with the primary outcome [OR 3.44 (2.17, 5.44)] allowing for a validated predictive model for death by day 7., Conclusions: Higher CRP and advanced age were associated with and predictive of death by day 7. However, BMI, presence of diabetes complications, and glycaemic control were not. A high proportion of these patients required insulin infusion warranting increased input from the inpatient diabetes teams., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Llanera, Wilmington, Shoo, Lisboa, Jarman, Wong, Nizza, Sharma, Kalathil, Rajeev, Williams, Yadav, Qureshi, Narayanan, Furlong, Westall and Nair.)

A well-validated in-silico approach can provide promising drug candidates for the treatment of the ongoing CoVID19 pandemic. In this study, we have screened 32 phytochemical constituents (PCCs) with Mpro binding site (PDB:6W63) based on which we identified three possible candidates that are likely to be effective against CoVID19-viz., licoleafol (binding energy: -8.1 kcal/mol), epicatechin gallate (-8.5 kcal/mol) and silibinin (-8.4 kcal/mol) that result in higher binding affinity than the known inhibitor, X77 (-7.7 kcal/mol). Molecular dynamics (MD) simulations of PCCs-Mpro complex confirmed molecular docking results with high structural and dynamical stability. The selected compounds were found to exhibit low mean squared displacements (licoleafol: 2.25 ± 0.43 Å, epicatechin gallate: 1.93 ± 0.35 Å, and silibinin: 1.39 ± 0.19 Å) and overall low fluctuations of the binding complexes (root mean squared fluctuations below 2 Å). Visualization of the MD trajectories and structural analyses revealed that they remain confined to the initial binding region, with mean fluctuations lower than 3 Å. To access the collective motion of the atoms, we performed principal component analysis demonstrating that the first 10 principal components are the major contributors (approximate contribution of 80%) and are responsible for the overall PCCs motion. Considering that the three selected PCCs share the same flavan backbone and exhibit antiviral activity against hepatitis C, we opine that licoleafol, epi-catechin gallate, and silibinin can be promising anti-CoVID19 drug candidates. Communicated by Ramaswamy H. Sarma.

As most of the countries have already passed the peaks of the second or third wave of infections, COVID-19 is (finally) on the wane and will soon touch the baseline persistence with a reduced death rate. The Case Fatality Ratio (CFR) or lethality is presently only ~2.0%, which is relatively low in comparison to the high of 14% in April 2020. More importantly, the lethality in healthy people is 20 times lower. In addition, successful vaccination programs are currently underway in several countries. Thus, although new pathogenic variants as well as a few isolated cases of resurgence, will continue to emerge, the worst seems to be over and we will surely win this battle soon., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

We describe a low-cost simulation model for teaching core needle biopsy to surgical trainees in Low- and Middle-income countries (LMICs). Pre-session and post-session surveys showed that correct core sampling (ability to hit the beetroot) after training was 91.4% compared to 75.7% before demonstration and improved adequacy (68.5% before v. 85.7% after). This low-cost model using locally available products is designed to simulate a palpable breast lump and can easily be incorporated into surgical training in LMICs, where a palpable breast lump is the commonest presentation of breast cancer.

Mitigating the devastating effect of COVID-19 is necessary to control the infectivity and mortality rates. Hence, several strategies such as quarantine of exposed and infected individuals and restricting movement through lockdown of geographical regions have been implemented in most countries. On the other hand, standard SEIR based mathematical models have been developed to understand the disease dynamics of COVID-19, and the proper inclusion of these restrictions is the rate-limiting step for the success of these models. In this work, we have developed a hybrid Susceptible-Exposed-Infected-Quarantined-Removed (SEIQR) model to explore the influence of quarantine and lockdown on disease propagation dynamics. The model is multi-compartmental, and it considers everyday variations in lockdown regulations, testing rate and quarantine individuals. Our model predicts a considerable difference in reported and actual recovered and deceased cases in qualitative agreement with recent reports., (© 2021. The Author(s).)

Food, energy, and water (collectively referred to as 'FEW') security forms the key to human survival as well as socioeconomic development. However, the security of these basic resources is increasingly threatened due to growing demand. Beyond the widespread implications on public health, Coronavirus disease (COVID-19) has further raised additional challenges for FEW security, particularly for urban populations, as they mainly outsource their FEW demands from rural areas outside their physical boundaries. In light of that, this study reviews existing literature on FEW security to highlight the growing relevance of urban-rural linkages for realizing FEW security, especially against the backdrop of the COVID-19 pandemic. To achieve this, relevant research documents have been identified through Elsevier's Scopus database and other sources (by applying search equations). The authors have accordingly underlined the necessity of shifting the conventional urban-centric approach to city region-centric development planning for the post-COVID-19 era. To this end, a framework has been suggested for translating physical urban-rural linkages to a partnership enhancing a collective response. The major elements of this framework are the conceptualization of national-level policies to support urban-rural linkages. The framework can play the role of a science-policy-action interface to redesign the FEW system in city regions.