Evaluating the Association between Routine Pneumococcal Vaccination and COVID-19 Severity among Older Adults in the United States (preprint)

BackgroundThe relationship between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and Streptococcus pneumoniae remains uncertain. This study investigates the association between routine pneumococcal vaccination and the progression to severe COVID-19 outcomes in a cohort of older adults in the United States. MethodsOur cohort study includes adults aged 65 and older from a subset of adults covered by Medicare in the United States with a documented COVID-19 diagnosis. Logistic regression models were employed to assess the association between pneumococcal vaccination (13-valent conjugate vaccine [PCV13] and 23-valent pneumococcal polysaccharide vaccine [PPSV23]) and COVID-19 severity. ResultsAmong 90,070 Medicare enrollees with a COVID-19 diagnosis, 28,124 individuals exhibited severe respiratory symptoms or were admitted to the intensive care unit (ICU). The odds ratio (OR) for progression from non-severe symptoms to respiratory symptoms with or without ICU admission with prior PCV13 receipt was 0.91 (95% confidence interval [CI], 0.88, 0.93), the OR for progression from severe respiratory symptoms to ICU critical care with prior PCV13 receipt was 0.92 (95% CI, 0.88, 0.97), and the OR for progression from non-severe symptoms to ICU critical care with prior PCV13 receipt was 0.85 (95% CI, 0.81, 0.90). There was no association between PPSV23 received more than five years before the COVID-19 diagnosis and the COVID-19 outcomes. ConclusionsOverall, our findings indicate moderate to no association between PCV vaccination and COVID-19 severity.

Revealing and evaluation of antivirals targeting multiple druggable sites of RdRp complex in SARS-CoV-2 (preprint)

SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) complex consisting of nsp12, nsp7, and nsp8 as the key enzyme for viral genome replication and is a proven antiviral drug target. In this study, molecular interactions of nsp7 and nsp8 with nsp12 and the active site of nsp12 were coterminously targeted using in-silico screening of small molecule libraries to identify potential antivirals. Surface plasmon resonance (SPR) based assay using purified nsp7 and nsp8 proteins was developed, and the binding of identified molecules to targets was validated. The antiviral efficacy of identified small molecules was evaluated using cell-based assays, and potent antiviral effect with EC50 values of 0.56 uM, 0.73 uM, and 2.8 uM was demonstrated by fangchinoline, cepharanthine, and sennoside B, respectively. Further in vivo, investigation using hACE2 mice is being conducted. This is the first study that targets multiple sites in the RdRp complex of SARS-CoV-2 using a structure-based molecular repurposing approach and suggests potential therapeutic options for emerging variants of SARS-CoV-2.

Unraveling antiviral efficacy of multifunctional immunomodulatory triterpenoids against SARS-COV-2 targeting virus-specific enzymes (preprint)

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus (SARS-CoV-2) may be over, but its variants continue to emerge, and patients with mild symptoms having long COVID is still under investigation. SARS-CoV-2 infection leading to elevated cytokine levels and suppressed immune responses set off cytokine storm, fatal systemic inflammation, tissue damage, and multi-organ failure. Thus, drug molecules against virus-specific proteins that play a role in viral inflammation and simultaneous act on the host pathways participating in viral inflammation, will provide an effective antiviral therapy against emerging variants of concern. Evolutionarily conserved papain-like protease (PLpro) and main protease (Mpro) play an indispensable role in the virus life cycle and immune evasion. Direct-acting antivirals targeting both these viral proteases represent an attractive antiviral strategy that is also expected to reduce viral inflammation. The present study has evaluated the antiviral and anti-inflammatory potential of natural triterpenoids: azadirachtin, withanolide_A, and isoginkgetin. These molecules inhibit the Mpro and PLpro proteolytic activities with half-maximal inhibitory concentrations (IC50) values ranging from 1.42 to 32.7 M. Isothermal titration calorimetry (ITC) analysis validated the binding of these compounds to Mpro and PLpro. As expected, the two compounds, withanolide_A and azadirachtin exhibit potent antiviral activity with half-maximum effective concentration (EC50) values of 21.73 M and 31.19 M, respectively. The anti-inflammatory role of azadirachtin and withanolide_A when assessed using HEK293T cells were found to significantly reduce the levels of CXCL10, TNF, IL6, and IL8 cytokines, which are elevated in severe cases of COVID-19. Interestingly, azadirachtin and withanolide_A were also found to rescue the decreased type-I interferon response (IFN-1). The results of this study clearly highlight the role of triterpenoids as effective antiviral molecules that target SARS-CoV-2 specific enzymes and also host immune pathways involved in virus mediated inflammation.

Where is science heading? The main challenges before today's scientists?

Anecdotal and historical accounts of science suggest that in earlier times, researchers pursued science more as a hobby at their own pace with support and encouragement from patrons and communities. This leads to inequality in scientific research, where some fields and researchers may have an easier time obtaining funding and resources, while other fields and researchers may lack this support, making it difficult to conduct meaningful research. Progress of science needs efforts from the researchers with a poly-disciplinary mindset as well as mono-disciplinary strengths.[[5]] The role of science is evident to everyone from the recent example, i.e., protecting eight billion people from the devastating effects of COVID-19 pandemic. Millions of researchers are now pursuing science as opposed to thousands and hundreds of researchers in the earlier periods of science. [Extracted from the article] Copyright of Drying Technology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Mania: An Atypical Presentation of probable Streptococcus Agalactiae Meningoencephalitis

Streptococcus agalactiae, also known as Group B Streptococcus (GBS), is a common pathogen in the neonatal period, causing meningitis and sepsis. In non-pregnant adults it is an unusual cause of meningitis. We report about an elderly female with several risk factors for invasive GBS infection who developed GBS meningoencephalitis one month after treatment for COVID-19 upper respiratory tract infection. The patient presented with mania, and the classic triad of headache, neck stiffness, and fever was absent which contributed to the delay in diagnosis. Following initiation of treatment with intravenous ceftriaxone she attained full recovery, and her behavior returned to baseline. This case illustrates an unusual presentation of an emerging infection and should alert clinicians about this presentation. By reporting this case we want to raise awareness about mania as a presenting feature of meningoencephalitis. This should lead to more timely diagnosis and better outcomes for future patients.

LTSI Consensus Guidelines: Preoperative Pulmonary Evaluation in Adult Liver Transplant Recipients.

The relationship between chronic liver disease and respiratory symptoms and hypoxia is well recognized. Over the last century, three pulmonary complications specific to chronic liver disease (CLD) have been characterized: hepatopulmonary syndrome, portopulmonary hypertension, and hepatic hydrothorax. Apart from that coexisting pulmonary disease like chronic obstructive lung disease and interstitial lung disease also complicate the outcomes after liver transplantation (LT). Assessment for evaluation of underlying pulmonary disorders is essential to improve outcomes in patients with CLD, posted for LT. This consensus guideline of the Liver Transplant Society of India (LTSI) provides a comprehensive review of pulmonary issues in CLD, related and unrelated to underlying liver disease and gives recommendations for pulmonary screening in specific clinical scenarios in adults with chronic liver disease planned for LT. This document also aims to standardize the strategies for preoperative evaluation of these pulmonary issues in this subset of patients. Proposed recommendations were based on selected single case reports, small series, registries, databases, and expert opinion. The paucity of randomized, controlled trials in either of these disorders was noted. Additionally, this review will highlight the lacunae in our current evaluation strategy, challenges faced, and will provide direction to potentially useful futuristic preoperative evaluation strategies.

"Effect of COVID-19 Vaccination on Menstrual Cycle Patterns of Reproductive-Age Women: A Multi-centric Observational Study."

AIM: The study was conducted to know the impact of COVID-19 vaccination on menstrual cycle patterns and pre- and post-menstrual symptoms in women aged 18-45 years. BACKGROUND: COVID-19 vaccination was introduced to combat the dreadful impacts of human coronavirus infection. The two indigenously developed COVID-19 vaccines approved for use in India are COVISHILED and COVAXIN. OBJECTIVES: To investigate the effects of COVID-19 vaccination on the menstrual cycle, pre- and post-menstrual symptoms and to establish the correlation with the type of vaccine received. METHODS: Multi-centric observational study conducted in six institutes of national importance in different states of India over one year. A total of 5709 female participants fulfilling inclusion criteria were enrolled. Data about the impact of vaccines (COVISHIELD and COVAXIN) and prior COVID-19 infection on the menstrual cycle and its associated symptoms were obtained using all participants' online and offline interviews. RESULTS: Of 5709 participants, 78.2% received COVISHIELD and 21.8% COVAXIN. Of the total 5709 participants, 333(5.8%) developed post-vaccination menstrual disturbances, with 32.7% having frequent cycles, 63.7% prolonged cycles, and 3.6% inter-menstrual bleeding. A total of 301 participants noticed changes in the amount of bleeding, with 50.2% excessive, 48.8% scanty, and 0.99% amenorrhea followed by heavy bleeding. Furthermore, the irregularities of the menstrual cycle (p=0.011) and length (0.001) were significantly higher in the COVAXIN group (7.2%) as compared to the COVISHIELD (5.3%) group. A total of 721 participants complained of newly developed/worsening pre- and post-menstrual symptoms. These symptoms were significantly higher in the COVISHIELD group (p=0.031), with generalized weakness and body pains as the main complaints (p=0.001). No significant difference was observed in the incidence of COVID-19 infection with these vaccines. No significant associations were observed when comparing menstrual abnormalities among those with COVID-19 infection (p>0.05). CONCLUSIONS: COVISHILED and COVAXIN vaccines were associated with menstrual cycle disturbances and pre-and post-menstrual symptoms in a small proportion of participants, with 94.7% having no change in the amount of bleeding during menstruation post-vaccination. The menstrual irregularities observed were significantly higher with the COVAXIN vaccine. Others: Further, long-term studies are required to confirm that the impact of COVID-19 vaccination on the menstrual cycle may be short-lasting, with no severe effects on women's menstrual health.

Quality assessment of global health care system in the shadow of COVID-19: - a systematic review.

INTRODUCTION: The healthcare system is critical to the country's overall growth, which involves the healthy development of individuals, families, and society everywhere. This systematic review focuses on providing an overall assessment of the quality of healthcare delivery during COVID-19. METHODOLOGY: The literature search was conducted from March 2020 till April 2023 utilising the databases "PubMed," "Google Scholar," and "Embase." A total of nine articles were included. Descriptive statistics was performed using Microsoft Excel. PROSPERO registration ID- CRD42022356285. RESULTS: According to the geographic location of the studies included, four studies were conducted in Asia [Malaysia(n = 1); India (Madhya Pradesh) (n = 1); Saudi Arabia(n = 1); Indonesia (Surabaya) (n = 1)], three in Europe [U.K. (n = 1); Poland (n = 1); Albania (n = 1)] and two in Africa [Ethiopia(n = 1); Tunisia (n = 1)]. Overall patient satisfaction was found highest among studies conducted in Saudi Arabia (98.1%) followed by India (Madhya Pradesh) (90.6%) and the U.K. (90%). CONCLUSION: This review concluded five different aspects of patients satisfaction level i.e. reliability, responsiveness, assurance, empathy, and tangibility. It was found that the empathy aspect had the greatest value of the five factors, i.e., 3.52 followed by Assurance with a value of 3.51.

An amalgamation of vision transformer with convolutional neural network for automatic lung tumor segmentation.

Lung cancer has the highest mortality rate. Its diagnosis and treatment analysis depends upon the accurate segmentation of the tumor. It becomes tedious if done manually as radiologists are overburdened with numerous medical imaging tests due to the increase in cancer patients and the COVID pandemic. Automatic segmentation techniques play an essential role in assisting medical experts. The segmentation approaches based on convolutional neural networks have provided state-of-the-art performances. However, they cannot capture long-range relations due to the region-based convolutional operator. Vision Transformers can resolve this issue by capturing global multi-contextual features. To explore this advantageous feature of the vision transformer, we propose an approach for lung tumor segmentation using an amalgamation of the vision transformer and convolutional neural network. We design the network as an encoder-decoder structure with convolution blocks deployed in the initial layers of the encoder to capture the features carrying essential information and the corresponding blocks in the final layers of the decoder. The deeper layers utilize the transformer blocks with a self-attention mechanism to capture more detailed global feature maps. We use a recently proposed unified loss function that combines cross-entropy and dice-based losses for network optimization. We trained our network on a publicly available NSCLC-Radiomics dataset and tested its generalizability on our dataset collected from a local hospital. We could achieve average dice coefficients of 0.7468 and 0.6847 and Hausdorff distances of 15.336 and 17.435 on public and local test data, respectively.

Machine Learning-Guided Antibody Engineering That Leverages Domain Knowledge To Overcome The Small Data Problem (preprint)

The application of Machine Learning (ML) tools to engineer novel antibodies having predictable functional properties is gaining prominence. Herein, we present a platform that employs an ML-guided optimization of the complementarity-determining region (CDR) together with a CDR framework (FR) shuffling method to engineer affinity-enhanced and clinically developable monoclonal antibodies (mAbs) from a limited experimental screen space (order of 10^2 designs) using only two experimental iterations. Although high-complexity deep learning models like graph neural networks (GNNs) and large language models (LLMs) have shown success in protein folding with large dataset sizes, the small and biased nature of the publicly available antibody-antigen interaction datasets is not sufficient to capture the diversity of mutations virtually screened using these models in an affinity enhancement campaign. To address this key gap, we introduced inductive biases learned from extensive domain knowledge of protein-protein interactions through feature engineering and selected model hyperparameters to reduce the overfitting of the limited interaction datasets. Notably, we show that this platform performs better than GNNs and LLMs on an in-house validation dataset that is enriched in diverse CDR mutations that go beyond alanine-scanning. To illustrate the broad applicability of this platform, we successfully solved a challenging problem of redesigning two different anti-SARS-COV-2 mAbs to enhance affinity (up to 2 orders of magnitude) and neutralizing potency against the dynamically evolving SARS-COV-2 Omicron variants.

Formulation, process optimization, and quality evaluation of barnyard millet (Echinochloa frumentacea)‐based ready‐to‐eat (RTE) extruded snack

COVID‐19 pandemic has increased the demand for antioxidant and micronutrient‐rich foods that are easy to prepare, consume, and require less handling. In this research, we worked on the development of nutritious extruded snack made from barnyard millet, defatted soy flour, Indian gooseberry powder, and rice flour. Box–Behnken Design of Response Surface Methodology was utilized to determine the influence of process variables viz;blend ratio of barnyard millet and defatted soy flour, extruder barrel temperature, and Indian gooseberry powder on nutritional and organoleptic properties of snack. Optimized extruded snack were attained at blend ratio (6:1), barrel temperature (115°C), and Indian gooseberry (12.25 g/100 g of total flour). Extruded snack presented good overall acceptability along with high fiber (16.84 g/100 g), protein (18.91 g/100 g), total phenol (67.51 mg GAE/100 g), and total flavonoid (153.61 mg RE/100 g) content. Microbial analysis indicates that extruded snack can be stored for up to 60 days without microbial contamination. NOVELTY IMPACT STATEMENT: The pandemic has made people refocus on the foods that are nutritious, yet take less time to prepare and handle. In the present research, we explored the use of locally available and low‐cost barnyard millet and defatted soy flour coupled with Indian gooseberry powder—a rich source of antioxidants and rice flour for the preparation of nutritious snack. Extrudates developed with a higher blend ratio at higher barrel temperature and enriched with Indian gooseberry content displayed excellent nutritional, bioactive, and dimensional characteristics. The study will help formulate extruded snack with high protein, antioxidants, as well as fiber content.

Computational Intelligence and Soft Computing Paradigm for Cheating Detection in Online Examinations

Covid-19 has been a life-changer in the sphere of online education. With complete lockdown in various countries, there has been a tumultuous increase in the need for providing online education, and hence, it has become mandatory for examiners to ensure that a fair methodology is followed for evaluation, and academic integrity is met. A plethora of literature is available related to methods to mitigate cheating during online examinations. A systematic literature review (SLR) has been followed in our article which aims at introducing the research gap in terms of the usage of soft computing techniques to combat cheating during online examinations. We have also presented state-of-the-art methods followed, which are capable of mitigating online cheating, namely, face recognition, face expression recognition, head posture analysis, eye gaze tracking, network data traffic analysis, and detection of IP spoofing. A discussion on improvement of existing online cheating detection systems has also been presented.

Immunohematological challenges in COVID infected patients.

BACKGROUND: Several autoimmune disorders have been reported to be related with COVID infection. In continuation to these autoimmune phenomenon, autoimmune hemolytic anaemia (AIHA) also has been noted in COVID infected patients. The aim of the study was to find out the prevalence of red cell alloimmunization, ABO discrepancy and positive direct antiglobulin test (DAT) results in COVID infected patients hospitalised in a tertiary care centre in North India. METHODOLOGY: This was a retrospective observational study done from July 2020 to June 2021. All symptomatic patients admitted to ICU tested positive for SARS CoV-2 whose blood samples were received in the immunohematology laboratory of department of Transfusion Medicine for determination of blood group and issue of packed red cells, and found to have positive antibody screen, blood group discrepancy and positive DAT results, were included in the study. RESULTS: A total of 10,568 tests were run, out of which 4437 were for determination of blood group, 5842 were for antibody screen and 289 were for direct antiglobulin test. Included in this study were 146 patients who either had blood group discrepancy, or had a positive antibody screen or had a positive DAT. Out of 115 positive antibody screen, 66 patients had only alloantibodies, 44 patients had only autoantibodies while only 5 patients had both auto as well as alloantibodies. Total number of positive DAT cases was 50 (50/289 = 17.3 %). There were 26 ABO discrepancies (26/4437 =0.58 %) found. CONCLUSION: Our results also indicate that there is rise in rate of alloimmunization and DAT positivity among COVID patients.

Forging Ahead the Repositioning of Multitargeted Drug Ivermectin.

With the advent of ivermectin, tremendous improvement in public health has been observed, especially in the treatment of onchocerciasis and lymphatic filariasis that created chaos mostly in rural, sub-Saharan Africa and Latin American countries. The discovery of ivermectin became a boon to millions of people that had suffered in the pandemic and still hold its pharmacological potential against these. Ivermectin continued to surprise scientists because of its notable role in the treatment of various other tropical diseases (Chagas, leishmaniasis, worm infections, etc.) and is viewed as the safest drug with the least toxic effects. The current review highlights its role in unexplored avenues towards forging ahead of the repositioning of this multitargeted drug in cancer, viral (the evaluation of the efficacy of ivermectin against SARS-Cov-2 is under investigation) and bacterial infection and malaria. This article also provides a glimpse of regulatory considerations of drug repurposing and current formulation strategies. Due to its broad-spectrum activity, multitargeted nature and promising efforts are put towards the repurposing of this drug throughout the field of medicine. This single drug originated from a microbe, changed the face of global health by proving its unmatched success and progressive efforts continue in maintaining its bequestnin the management of global health by decreasing the burden of various diseases worldwide.

Impact of comorbidity on patients with COVID-19 in India: A nationwide analysis.

Background: The emergence of coronavirus disease (COVID-19) as a global pandemic has resulted in the loss of many lives and a significant decline in global economic losses. Thus, for a large country like India, there is a need to comprehend the dynamics of COVID-19 in a clustered way. Objective: To evaluate the clinical characteristics of patients with COVID-19 according to age, gender, and preexisting comorbidity. Patients with COVID-19 were categorized according to comorbidity, and the data over a 2-year period (1 January 2020 to 31 January 2022) were considered to analyze the impact of comorbidity on severe COVID-19 outcomes. Methods: For different age/gender groups, the distribution of COVID-19 positive, hospitalized, and mortality cases was estimated. The impact of comorbidity was assessed by computing incidence rate (IR), odds ratio (OR), and proportion analysis. Results: The results indicated that COVID-19 caused an exponential growth in mortality. In patients over the age of 50, the mortality rate was found to be very high, ~80%. Moreover, based on the estimation of OR, it can be inferred that age and various preexisting comorbidities were found to be predictors of severe COVID-19 outcomes. The strongest risk factors for COVID-19 mortality were preexisting comorbidities like diabetes (OR: 2.39; 95% confidence interval (CI): 2.31-2.47; p < 0.0001), hypertension (OR: 2.31; 95% CI: 2.23-2.39; p < 0.0001), and heart disease (OR: 2.19; 95% CI: 2.08-2.30; p < 0.0001). The proportion of fatal cases among patients positive for COVID-19 increased with the number of comorbidities. Conclusion: This study concluded that elderly patients with preexisting comorbidities were at an increased risk of COVID-19 mortality. Patients in the elderly age group with underlying medical conditions are recommended for preventive medical care or medical resources and vaccination against COVID-19.