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The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic has adversely affected humankind and caused millions of deaths globally since January 2020. Robust and quick serological tests such as antibody detection assays for SARS-CoV-2 provide relevant information and aid in the process of vaccine development and diagnostics, as well as in sero-epidemiological monitoring of antibody response to the virus. The receptor-binding domain (RBD) of spike and nucleocapsid protein are specific targets for detecting SARS-CoV-2 antibodies. Here, we present the development of a stable spike (S) and nucleocapsid (N) protein-based ELISA antibody detection test "CoroSuchak," with 99% sensitivity, 98% specificity, cost-effective, and detection in a minimum time for serodiagnosis and mass screening of the population for antibodies against SARS-CoV-2. Blood samples were analyzed from 374 SARS-CoV-2 reverse transcription-polymerase chain reaction (RT-PCR) positive, 772 negative and asymptomatic, and 874 random groups of subjects. We found that the antibody titer was significantly higher (p < 0.0001) in infected and vaccinated group compared to the only vaccinated and only infected group. Using enzyme-linked immunosorbent assay (ELISA), we detected SARS-CoV-2 immunoglobulin G (IgG) antibodies in 118/123 (96%) infected individuals, 570/653 (87%) non-infected but vaccinated individuals, 231/237 (97%) individuals who were both infected and vaccinated, and 499/874 (57%) from randomly selected individuals from the first and second waves of the pandemic. Similarly in the third wave, 14/14 (100%) infected and 16/20 (80%) RT-PCR-negative but symptomatic subjects were detected. Thus, the highly sensitive and specific in-house developed ELISA antibody detection kit "CoroSuchak" is extremely useful to determine the seroprevalence of SARS-CoV-2 antibodies in the coronavirus-exposed population. KEY POINTS: •Indigenous kit using a combination of spike and nucleocapsid proteins and peptide sequences. •High sensitivity and specificity to detect variants. •Highly sensitive for mass screening.

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Around 140 million people live in high-altitude (HA) conditions! and even a larger number visit such places for tourism, adventure-seeking or sports training. Rapid ascent to HA can cause severe damage to the body organs and may lead to many fatal disorders. During induction to HA, human body undergoes various physiological, biochemical, hematological and molecular changes to adapt to the extreme environmental conditions. Several literature references hint that gene-expression-regulation and regulatory molecules like miRNAs and transcription factors (TFs) control adaptive responses during HA stress. These biomolecules are known to interact in a complex combinatorial manner to fine-tune the gene expression and help in controlling the molecular responses during this stress and ultimately help in acclimatization. High-Altitude Human miRNA Database (HAHmiR.DB) is a unique, comprehensive and curated collection of miRNAs that have been experimentally validated to be associated with HA stress, their level of expression in different altitudes, fold change, experiment duration, biomarker association, disease and drug association, tissue-specific expression level, Gene Ontology (GO) and Kyoto Encyclopaedia of Gene and Genomes (KEGG) pathway associations. As a server platform, it also uniquely constructs and analyses interactive miRNA-TF-gene coregulatory networks and extracts regulatory circuits/feed-forward loops (FFLs). These regulatory circuits help to offer mechanistic insights into complex regulatory mechanisms during HA stress. The server can also build these regulatory networks between two and more miRNAs of the database and also identify the regulatory circuits from this network. Hence, HAHmiR.DB is the first-of-its-kind database in HA research, which is a reliable platform to explore, compare, analyse and retrieve miRNAs associated with HA stress, their coregulatory networks and FFL regulatory-circuits. HAHmiR.DB is freely accessible at http://www.hahmirdb.in.

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BACKGROUND: Our earlier Google Trend (GT) Analytics study reported that the worldwide human population severely subject to four seasonal (sensitive) comorbid lifestyle diseases (SCLD) such as asthma, obesity, hypertension and fibrosis. The human population subject to seasonal variability in these four diseases activity referred as "severe seasonal sensitive population". In India, the estimated burden of these four seasonal diseases is more than 350 million as on the year 2018. It is a growing crisis for India with a projected disease burden of 500 million in the year 2025. This study was aimed to decipher the genuine SCLD seasonal trends in the entire Indian population using GT and validate these trends in Indian climatic zones. METHODS: GT is used to study the temporal trends in web search using weekly Relative Search Volume (RSV) for the period 2004 to 2017. The relative search volume (RSV) of the four-severe seasonal comorbid diseases namely Asthma, Hypertension, Obesity and Fibrosis were collected with and without obesity as the reference. The RSV were collected using the GT selection options as (i) Whole India (ii) Jammu and Kashmir (Cold zone) (iii) Rajasthan (Hot and Dry zone) (iii) West Bengal (Hot and Humid zone) and (iv) Uttar Pradesh state (Composite zone). The time series analysis was carried out to find seasonal patterns, comorbidity, trends and periodicity in the entire India and four of its states (zones). RESULTS: Our analysis of entire India (2004-2017) revealed high significant seasonal patterns and comorbidity in all the four diseases of SCLD. The positive tau values indicated strong positive seasonal trends in the SCLD throughout the period (Table). The auto correlation analysis revealed that these diseases were subjected to 3, 4 and 6 months period seasonal variations. Similar seasonal patterns and trends were also observed in all the four Indian temperature zones. Overall study indicated that SCLD seasonal search patterns and trends are highly conserved in India even in drastic Indian climatic zones. CONCLUSIONS: The clinical outcome arise out of these observations could be of immense significance in handling the major chronic life style diseases asthma, hypertension, obesity and fibrosis. The possible strong comorbid relationship among asthma, hypertension, obesity and fibrosis may be useful to segregate Indian seasonal sensitive population. In disease activity-based chronotherapy, the search interest of segment of the population with access to Internet may be used as an indicator for public health sectors in the early detection of SCLD from a specific country or a region. As this disease population could be highly subject to the adverse effect of seasons in addition to life style and other environmental factors. Our study necessitates that these Indian populations need special attention from the Indian health care sectors.

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Salmonella is one of the key global causes of food and water borne enteric infections, responsible for significant morbidity and mortality worldwide especially in developing countries. Currently available vaccines against typhoid are moderately effective with several side effects and not efficacious against all Salmonella serovars. Due to limitations of these vaccines and emerging threats of multidrug resistance, developing an effective vaccine against these infections has increasingly become a priority. Heat shock proteins (Hsps), being evolutionarily conserved, represent dominant antigens in the host immune response. In continuation of our earlier studies on the development of S. Typhi DnaK and GroEL vaccine candidates, highly efficacious against Salmonella and multiple pathogens, in the present study, we have designed multi-epitope vaccine candidates common to multiple serovars of Salmonella using bioinformatics approach. Implementing various immunoinformatics tools such as IEDB, EpiJen, BCPRED, ElliPro and VaxiJen, led to the identification of many immunogenic B and T cell epitopes. The 3-D structure model of DnaK was generated to predict conformational B-cell epitopes using ElliPro server. Most promising T cell epitopes (29 CTLs, 18 T-helper cells) were selected based on their binding efficiency with commonly occurring MHC alleles. Finally we narrowed down to 5 protective antigenic peptides (PAPs), comprising highly conserved, antigenic and immunogenic B /T cell epitopes, least homologous with human host. These PAPs were predicted to be non-allergenic by allergenicity prediction tools (SORTALLER and AllerHunter). Hence, these immunogenic epitopes can be used for prophylactic or therapeutic usages specifically to defeat antibiotic-resistant Salmonella. These antigens have been reported for the first time and their conserved nature endow them as potential future vaccine candidates against other multiple pathogens as well.

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Oriental medicinal mushroom Ganoderma lucidum has been widely used for the promotion of health and longevity owing to its various bioactive constituents. Therefore, comprehending metabolomics of different G. lucidum parts could be of paramount importance for investigating their pharmacological properties. Ultra-performance convergence chromatography (UPC2) along with mass spectrometry (MS) is an emerging technique that has not yet been applied for metabolite profiling of G. lucidum. This study has been undertaken to establish metabolomics of the aqueous extracts of mycelium (GLM), fruiting body (GLF), and their mixture (GLMF) using ultra-performance convergence chromatography single quadrupole mass spectrometry (UPC2-SQD-MS). Aqueous extracts of G. lucidum prepared using an accelerated solvent extraction technique have been characterized for their mycochemical activities in terms of total flavonoid content, 1,1-diphenyl-2-picryl-hydrazyl scavenging activity, and ferric ion reducing antioxidant power. The UPC2-SQD-MS technique has been used for the first time for metabolite profiling of G. lucidum on a Princeton Diol column (4.6 × 250 mm; 5 µm) using supercritical CO2 (solvent) and 20 mM ammonium acetate in methanol (co-solvent). In the present study, UPC2-SQD-MS was found to be a rapid, efficient, and high-throughput analytical technique, whose coupling to principal component analysis (PCA) and phytochemical evaluation could be used as a powerful tool for elucidating metabolite diversity between mycelium and fruiting body of G. lucidum. PCA showed a clear distinction in the metabolite compositions of the samples. Mycochemical studies revealed that overall GLF possessed better antioxidant properties among the aqueous extracts of G. lucidum.

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This study demonstrated the protective efficiency of extracts of the Indian variety of Ophiocordyceps sinensis (=Cordyceps sinensis) (CSEs) in HT22 (murine hippocampal) cells under hypoxic conditions. Various parameters such as cell viability, reactive oxygen species, levels of endogenous antioxidants, inflammatory cytokines, transcription factors, and oxidation of macromolecules were analyzed. In addition, the radical scavenging abilities of hydroxyl radicals, nitric oxide, and superoxide radicals were also studied. Antioxidant compounds, ascorbic acid, hesperidin, and rutin were quantified by high-performance thin-layer chromatography. The information acquired from high-performance thin-layer chromatography profiling was subjected to principal component analysis for data clustering. Findings of this research revealed that ascorbic acid and rutin were highest in aqueous CSE, whereas the maximum amount of hesperidin was found in 25% alcoholic CSE. In vitro studies showed that all the CSEs protected HT22 cells well by upregulating the level of endogenous antioxidants and preventing the oxidation of lipids and proteins. These extracts also reduced the amount of hypoxia-induced inflammatory cytokines and transcription factors on par with the normoxic control with more or less equal protection in the cells under hypoxia, and indicated significant radical scavenging potential.

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Hypoxic respiratory diseases or hypoxia exposures are frequently accompanied by glucose intolerance and impaired nitric oxide (NO) availability. However, the molecular mechanism responsible for impaired NO production and insulin resistance (IR) during hypoxia remains obscure. In this study, we investigated the possible mechanism of impaired NO production and IR during hypoxia in a mouse model. Mice were exposed to hypoxia for different periods of time (0-24 h), and parameters of IR and endothelial dysfunctions were analyzed. Exposure to hypoxia resulted in a time-dependent increase in IR as well as multimeric forms of von Willebrand factor (vWF) and subsequently a decrease in eNOS activity. Preincubation with plasma of hypoxia-exposed animals (different time points) or human vWF inhibited insulin-induced NO production in a dose-dependent manner; larger doses of insulin reversed the effect. In contrast, preincubation of vWF-immunodepleted plasma failed to inhibit insulin-induced NO production, whereas vWF immunoneutralization abolished the effect of hypoxia-induced IR and D-[U-(14)C]glucose uptake. Furthermore, the interactions between vWF and eNOS were studied by far-Western blotting, co-immunoprecipitation, and surface plasma resonance spectroscopy. Kinetic analyses showed that the dissociation constant (KD), inhibitory constant (Ki), and half-maximal inhibitory concentration (IC50) were 1.79 × 10(-8) M, 250 pM, and 18.31 pM, respectively, suggesting that vWF binds to eNOS with a high affinity and greater efficacy for activator (insulin) inhibition. These results indicated that vWF, an antagonist of eNOS, inhibits insulin-induced NO production and causes IR.

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There has been intense interest in the cellular response to hypoxia, and a large number of differentially expressed proteins have been identified through various high-throughput experiments. These valuable data are scattered, and there have been no systematic attempts to document the various proteins regulated by hypoxia. Compilation, curation and annotation of these data are important in deciphering their role in hypoxia and hypoxia-related disorders. Therefore, we have compiled HypoxiaDB, a database of hypoxia-regulated proteins. It is a comprehensive, manually-curated, non-redundant catalog of proteins whose expressions are shown experimentally to be altered at different levels and durations of hypoxia. The database currently contains 72 000 manually curated entries taken on 3500 proteins extracted from 73 peer-reviewed publications selected from PubMed. HypoxiaDB is distinctive from other generalized databases: (i) it compiles tissue-specific protein expression changes under different levels and duration of hypoxia. Also, it provides manually curated literature references to support the inclusion of the protein in the database and establish its association with hypoxia. (ii) For each protein, HypoxiaDB integrates data on gene ontology, KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway, protein-protein interactions, protein family (Pfam), OMIM (Online Mendelian Inheritance in Man), PDB (Protein Data Bank) structures and homology to other sequenced genomes. (iii) It also provides pre-compiled information on hypoxia-proteins, which otherwise requires tedious computational analysis. This includes information like chromosomal location, identifiers like Entrez, HGNC, Unigene, Uniprot, Ensembl, Vega, GI numbers and Genbank accession numbers associated with the protein. These are further cross-linked to respective public databases augmenting HypoxiaDB to the external repositories. (iv) In addition, HypoxiaDB provides an online sequence-similarity search tool for users to compare their protein sequences with HypoxiaDB protein database. We hope that HypoxiaDB will enrich our knowledge about hypoxia-related biology and eventually will lead to the development of novel hypothesis and advancements in diagnostic and therapeutic activities. HypoxiaDB is freely accessible for academic and non-profit users via http://www.hypoxiadb.com.

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BACKGROUND: The tissue-specific Unigene Sets derived from more than one million expressed sequence tags (ESTs) in the NCBI, GenBank database offers a platform for identifying significantly and differentially expressed tissue-specific genes by in-silico methods. Digital differential display (DDD) rapidly creates transcription profiles based on EST comparisons and numerically calculates, as a fraction of the pool of ESTs, the relative sequence abundance of known and novel genes. However, the process of identifying the most likely tissue for a specific disease in which to search for candidate genes from the pool of differentially expressed genes remains difficult. Therefore, we have used 'Gene Ontology semantic similarity score' to measure the GO similarity between gene products of lung tissue-specific candidate genes from control (normal) and disease (cancer) sets. This semantic similarity score matrix based on hierarchical clustering represents in the form of a dendrogram. The dendrogram cluster stability was assessed by multiple bootstrapping. Multiple bootstrapping also computes a p-value for each cluster and corrects the bias of the bootstrap probability. RESULTS: Subsequent hierarchical clustering by the multiple bootstrapping method (α = 0.95) identified seven clusters. The comparative, as well as subtractive, approach revealed a set of 38 biomarkers comprising four distinct lung cancer signature biomarker clusters (panel 1-4). Further gene enrichment analysis of the four panels revealed that each panel represents a set of lung cancer linked metastasis diagnostic biomarkers (panel 1), chemotherapy/drug resistance biomarkers (panel 2), hypoxia regulated biomarkers (panel 3) and lung extra cellular matrix biomarkers (panel 4). CONCLUSIONS: Expression analysis reveals that hypoxia induced lung cancer related biomarkers (panel 3), HIF and its modulating proteins (TGM2, CSNK1A1, CTNNA1, NAMPT/Visfatin, TNFRSF1A, ETS1, SRC-1, FN1, APLP2, DMBT1/SAG, AIB1 and AZIN1) are significantly down regulated. All down regulated genes in this panel were highly up regulated in most other types of cancers. These panels of proteins may represent signature biomarkers for lung cancer and will aid in lung cancer diagnosis and disease monitoring as well as in the prediction of responses to therapeutics.

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To study the functional role of NADPH during mammalian catalase inhibition, the X-ray crystal structures of NADPH-depleted bovine liver catalase and its inhibitor complexes, cyanide and azide, determined at 2.8Å resolution. From the complex structures it is observed that subunits with and without an inhibitor/catalytic water molecule are linked by N-terminal domain swapping. Comparing mammalian- and fungal- catalases, we speculate that NADPH-depleted mammalian catalases may function as a domain-swapped dimer of dimers, especially during inactivation by inhibitors like cyanide and azide. We further speculate that in mammalian catalases the N-terminal hinge-loop region and α-helix is the structural element that senses NADPH binding. Although the above arguments are speculative and need further verification, as a whole our studies have opened up a new possibility, viz. that mammalian catalase acts as a domain-swapped dimer of dimers, especially during inhibitor binding. To generalize this concept to the formation of the inactive state in mammalian catalases in the absence of tightly bound NADPH molecules needs further exploration. The present study adds one more intriguing fact to the existing mysteries of mammalian catalases.