Increase in acute pancreatitis, especially gallstone related, as the cause for emergency admissions: Temporal trend from Kashmir, India.

BACKGROUND: The incidence of acute pancreatitis is increasing globally. Gallstones (GS) and ascariasis are the major causes for acute pancreatitis in the Kashmiri population. In recent years, we have observed an increase in the admission rate of acute pancreatitis. Many patients who present first time as gallstone pancreatitis have asymptomatic gallstones. We aimed at studying the etiology and yearly admission rate of acute pancreatitis with main focus on gallstone pancreatitis and the contribution of asymptomatic gallstones. METHODS: This was a hospital-based, prospective, observational study from January 2015 to December 2019 for a period of five years. Patients of acute pancreatitis were evaluated for etiology and yearly admission rate. Patients of gallstone pancreatitis were evaluated in terms of clinical profile, risk factors, nature (symptomatic/asymptomatic, known/unknown gallstones), size of stones, treatment and outcome in terms of severity and mortality. The data was analyzed by Statistical Package for the Social Sciences (SPSS) version 20.0, as mean (SD), frequencies and percentages. RESULTS: As many as 702 (8.5%) patients of acute pancreatitis were admitted among 8245 gastrointestinal emergencies in five years. The yearly admission rate of acute pancreatitis was 5.6%, 7.3%, 8.7%, 9.5% and 10.3%, respectively (p = 0.013). Gallstones, Ascariasis, alcohol and idiopathic acute pancreatitis were 47.7%, 6.9%, 1.2% and 33.7%, respectively. Gallstone pancreatitis increased from 31% in 2015 to 52.4% in 2019 (p = 0.045) and ascariasis-related acute pancreatitis declined from 14.4% to 1.6% (p = 0.034). Asymptomatic gallstones constituted 87.7% of cases. Known/unknown asymptomatic gallstones and symptomatic gallstones were 24.4%, 63.2% and 12.2%, respectively. Gallstones < 5 mm and > 5 mm were76.1% and 23.8% respectively (p = 0.027). Cholecystectomy rate in index admission was 4.7%. Mild, moderate and severe gallstone pancreatitis was 60.2%, 18.8% and 20.8%, respectively. Mortality in gallstone pancreatitis was 10.4%. CONCLUSION: The incidence of acute pancreatitis is increasing due to gallstone pancreatitis. Ascariasis-related acute pancreatitis has declined. There is significant contribution of asymptomatic gallstones in patients who present for the first time as acute pancreatitis. Small gallstones < 5 mm are likely to be the risk factors for gallstone pancreatitis.

Functional insight into multi-omics-based interventions for climatic resilience in sorghum (Sorghum bicolor): a nutritionally rich cereal crop.

MAIN CONCLUSION: The article highlights omics-based interventions in sorghum to combat food and nutritional scarcity in the future. Sorghum with its unique ability to thrive in adverse conditions, has become a tremendous highly nutritive, and multipurpose cereal crop. It is resistant to various types of climatic stressors which will pave its way to a future food crop. Multi-omics refers to the comprehensive study of an organism at multiple molecular levels, including genomics, transcriptomics, proteomics, and metabolomics. Genomic studies have provided insights into the genetic diversity of sorghum and led to the development of genetically improved sorghum. Transcriptomics involves analysing the gene expression patterns in sorghum under various conditions. This knowledge is vital for developing crop varieties with enhanced stress tolerance. Proteomics enables the identification and quantification of the proteins present in sorghum. This approach helps in understanding the functional roles of specific proteins in response to stress and provides insights into metabolic pathways that contribute to resilience and grain production. Metabolomics studies the small molecules, or metabolites, produced by sorghum, provides information about the metabolic pathways that are activated or modified in response to environmental stress. This knowledge can be used to engineer sorghum varieties with improved metabolic efficiency, ultimately leading to better crop yields. In this review, we have focused on various multi-omics approaches, gene expression analysis, and different pathways for the improvement of Sorghum. Applying omics approaches to sorghum research allows for a holistic understanding of its genome function. This knowledge is invaluable for addressing challenges such as climate change, resource limitations, and the need for sustainable agriculture.

Sorghum SbGhd7 is a major regulator of floral transition and directly represses genes crucial for flowering activation.

Molecular genetic understanding of flowering time regulation is crucial for sorghum development. GRAIN NUMBER, PLANT HEIGHT AND HEADING DATE 7 (SbGhd7) is one of the six classical loci conferring photoperiod sensitivity of sorghum flowering. However, its functions remain poorly studied. The molecular functions of SbGhd7 were characterized. The gene regulatory network controlled by SbGhd7 was constructed and validated. The biological roles of SbGhd7 and its major targets were studied. SbGhd7 overexpression (OE) completely prevented sorghum flowering. Additionally, we show that SbGhd7 is a major negative regulator of flowering, binding to the promoter motif TGAATG(A/T)(A/T/C) and repressing transcription of the major florigen FLOWERING LOCUS T 10 (SbFT10) and floral activators EARLY HEADING DATE (SbEhd1), FLAVIN-BINDING, KELCH REPEAT, F-BOX1 (SbFKF1) and EARLY FLOWERING 3 (SbELF3). Reinforcing the direct effect of SbGhd7, SbEhd1 OE activated the promoters of three functional florigens (SbFT1, SbFT8 and SbFT10), dramatically accelerating flowering. Our studies demonstrate that SbGhd7 is a major repressor of sorghum flowering by directly and indirectly targeting genes for flowering activation. The mechanism appears ancient. Our study extends the current model of floral transition regulation in sorghum and provides a framework for a comprehensive understanding of sorghum photoperiod response.

Ascorbic acid: a metabolite switch for designing stress-smart crops.

Plant growth and productivity are continually being challenged by a diverse array of abiotic stresses, including: water scarcity, extreme temperatures, heavy metal exposure, and soil salinity. A common theme in these stresses is the overproduction of reactive oxygen species (ROS), which disrupts cellular redox homeostasis causing oxidative damage. Ascorbic acid (AsA), commonly known as vitamin C, is an essential nutrient for humans, and also plays a crucial role in the plant kingdom. AsA is synthesized by plants through the d-mannose/l-galactose pathway that functions as a powerful antioxidant and protects plant cells from ROS generated during photosynthesis. AsA controls several key physiological processes, including: photosynthesis, respiration, and carbohydrate metabolism, either by acting as a co-factor for metabolic enzymes or by regulating cellular redox-status. AsA's multi-functionality uniquely positions it to integrate and recalibrate redox-responsive transcriptional/metabolic circuits and essential biological processes, in accordance to developmental and environmental cues. In recognition of this, we present a systematic overview of current evidence highlighting AsA as a central metabolite-switch in plants. Further, a comprehensive overview of genetic manipulation of genes involved in AsA metabolism has been provided along with the bottlenecks and future research directions, that could serve as a framework for designing "stress-smart" crops in future.

Machine Learning Made Easy (MLme): a comprehensive toolkit for machine learning-driven data analysis.

BACKGROUND: Machine learning (ML) has emerged as a vital asset for researchers to analyze and extract valuable information from complex datasets. However, developing an effective and robust ML pipeline can present a real challenge, demanding considerable time and effort, thereby impeding research progress. Existing tools in this landscape require a profound understanding of ML principles and programming skills. Furthermore, users are required to engage in the comprehensive configuration of their ML pipeline to obtain optimal performance. RESULTS: To address these challenges, we have developed a novel tool called Machine Learning Made Easy (MLme) that streamlines the use of ML in research, specifically focusing on classification problems at present. By integrating 4 essential functionalities-namely, Data Exploration, AutoML, CustomML, and Visualization-MLme fulfills the diverse requirements of researchers while eliminating the need for extensive coding efforts. To demonstrate the applicability of MLme, we conducted rigorous testing on 6 distinct datasets, each presenting unique characteristics and challenges. Our results consistently showed promising performance across different datasets, reaffirming the versatility and effectiveness of the tool. Additionally, by utilizing MLme's feature selection functionality, we successfully identified significant markers for CD8+ naive (BACH2), CD16+ (CD16), and CD14+ (VCAN) cell populations. CONCLUSION: MLme serves as a valuable resource for leveraging ML to facilitate insightful data analysis and enhance research outcomes, while alleviating concerns related to complex coding scripts. The source code and a detailed tutorial for MLme are available at https://github.com/FunctionalUrology/MLme.

Multi-omics approach reveals dysregulated genes during hESCs neuronal differentiation exposure to paracetamol.

Prenatal paracetamol exposure has been associated with neurodevelopmental outcomes in childhood. Pharmacoepigenetic studies show differences in cord blood DNA methylation between unexposed and paracetamol-exposed neonates, however, causality and impact of long-term prenatal paracetamol exposure on brain development remain unclear. Using a multi-omics approach, we investigated the effects of paracetamol on an in vitro model of early human neurodevelopment. We exposed human embryonic stem cells undergoing neuronal differentiation with paracetamol concentrations corresponding to maternal therapeutic doses. Single-cell RNA-seq and ATAC-seq integration identified paracetamol-induced chromatin opening changes linked to gene expression. Differentially methylated and/or expressed genes were involved in neurotransmission and cell fate determination trajectories. Some genes involved in neuronal injury and development-specific pathways, such as KCNE3, overlapped with differentially methylated genes previously identified in cord blood associated with prenatal paracetamol exposure. Our data suggest that paracetamol may play a causal role in impaired neurodevelopment.

Diversity of intratumoral regulatory T cells in B-cell non-Hodgkin lymphoma.

Tumor-infiltrating regulatory T cells (Tregs) contribute to an immunosuppressive tumor microenvironment. Despite extensive studies, the prognostic impact of tumor-infiltrating Tregs in B-cell non-Hodgkin lymphomas (B-NHLs) remains unclear. Emerging studies suggest substantial heterogeneity in the phenotypes and suppressive capacities of Tregs, emphasizing the importance of understanding Treg diversity and the need for additional markers to identify highly suppressive Tregs. Here, we applied single-cell RNA sequencing and T-cell receptor sequencing combined with high-dimensional cytometry to decipher the heterogeneity of intratumoral Tregs in diffuse large B-cell lymphoma and follicular lymphoma (FL), compared with that in nonmalignant tonsillar tissue. We identified 3 distinct transcriptional states of Tregs: resting, activated, and unconventional LAG3+FOXP3- Tregs. Activated Tregs were enriched in B-NHL tumors, coexpressed several checkpoint receptors, and had stronger immunosuppressive activity compared with resting Tregs. In FL, activated Tregs were found in closer proximity to CD4+ and CD8+ T cells than other cell types. Furthermore, we used a computational approach to develop unique gene signature matrices, which were used to enumerate each Treg subset in cohorts with bulk gene expression data. In 2 independent FL cohorts, activated Tregs was the major subset, and high abundance was associated with adverse outcome. This study demonstrates that Tregs infiltrating B-NHL tumors are transcriptionally and functionally diverse. Highly immunosuppressive activated Tregs were enriched in tumor tissue but absent in the peripheral blood. Our data suggest that a deeper understanding of Treg heterogeneity in B-NHL could open new paths for rational drug design, facilitating selective targeting to improve antitumor immunity.

Comprehensive genome-wide identification and transferability of chromosome-specific highly variable microsatellite markers from citrus species.

Citrus species among the most important and widely consumed fruit in the world due to Vitamin C, essential oil glands, and flavonoids. Highly variable simple sequence repeats (SSR) markers are one of the most informative and versatile molecular markers used in perennial tree genetic research. SSR survey of Citrus sinensis and Citrus maxima were identified perfect SSRs spanning nine chromosomes. Furthermore, we categorized all SSR motifs into three major classes based on their tract lengths. We designed and validated a class I SSRs in the C. sinensis and C. maxima genome through electronic polymerase chain reaction (ePCR) and found 83.89% in C. sinensis and 78.52% in C. maxima SSRs producing a single amplicon. Then, we selected extremely variable SSRs (> 40 nt) from the ePCR-verified class I SSRs and in silico validated across seven draft genomes of citrus, which provided us a subset of 84.74% in C. sinensis and 77.53% in C. maxima highly polymorphic SSRs. Out of these, 129 primers were validated on 24 citrus genotypes through wet-lab experiment. We found 127 (98.45%) polymorphic HvSSRs on 24 genotypes. The utility of the developed HvSSRs was demonstrated by analysing genetic diversity of 181 citrus genotypes using 17 HvSSRs spanning nine citrus chromosomes and were divided into 11 main groups through 17 HvSSRs. These chromosome-specific SSRs will serve as a powerful genomic tool used for future QTL mapping, molecular breeding, investigation of population genetic diversity, comparative mapping, and evolutionary studies among citrus and other relative genera/species.

Machine Learning Made Easy (MLme): A Comprehensive Toolkit for Machine Learning-Driven Data Analysis.

Background: Machine learning (ML) has emerged as a vital asset for researchers to analyze and extract valuable information from complex datasets. However, developing an effective and robust ML pipeline can present a real challenge, demanding considerable time and effort, thereby impeding research progress. Existing tools in this landscape require a profound understanding of ML principles and programming skills. Furthermore, users are required to engage in the comprehensive configuration of their ML pipeline to obtain optimal performance. Results: To address these challenges, we have developed a novel tool called Machine Learning Made Easy (MLme) that streamlines the use of ML in research, specifically focusing on classification problems at present. By integrating four essential functionalities, namely Data Exploration, AutoML, CustomML, and Visualization, MLme fulfills the diverse requirements of researchers while eliminating the need for extensive coding efforts. To demonstrate the applicability of MLme, we conducted rigorous testing on six distinct datasets, each presenting unique characteristics and challenges. Our results consistently showed promising performance across different datasets, reaffirming the versatility and effectiveness of the tool. Additionally, by utilizing MLme's feature selection functionality, we successfully identified significant markers for CD8+ naive (BACH2), CD16+ (CD16), and CD14+ (VCAN) cell populations. Conclusion: MLme serves as a valuable resource for leveraging machine learning (ML) to facilitate insightful data analysis and enhance research outcomes, while alleviating concerns related to complex coding scripts. The source code and a detailed tutorial for MLme are available at https://github.com/FunctionalUrology/MLme.

ERCP practice at a tertiary care hospital in Kashmir, North India: a large single-center cross-sectional study with focus on quality indicators, success rate, and indications.

Endoscopic retrograde cholangiopancreatography (ERCP) is the most technically demanding endoscopic procedure with significant adverse events that mandate appropriate training, competence and careful decision-making. The American Society for Gastrointestinal Endoscopy (ASGE) and the European Society of Gastrointestinal Endoscopy (ESGE) updated a list of quality indicators and performance measures for pancreatobiliary endoscopy. Nevertheless, real-life data are scarce, especially from developing countries. The study aimed to assess overall quality, procedural success, and indications of ERCP at our center. Methods: An audit of our endoscopy center at the start of the study for quality and performance indicators and a retrospective analysis of the 4 years of the prospectively maintained data of patients who underwent ERCP regarding procedural success and indications was done. Results: The study showed that ERCP is performed by meeting good quality standards, but structured training, sedation practice, and microbiological surveillance are subpar. A total of 3544 procedures were carried out with successful cannulation of the naive papilla in 93%, with 60% of procedures carried out on females, 80.5% of procedures done for benign diseases, and 19.5% on suspected or proven malignancy (47% men and 53% women) with perihilar obstruction being commonest in both sexes (32-33%) followed by carcinoma gallbladder in women (21%) and distal cholangiocarcinoma in men (27%). Among benign diseases (2711), 12% had benign pancreatic diseases, and 64.8% had common bile duct (CBD) stones, with 31% of CBD stones requiring more than one session for clearance. Conclusion: ERCP at our center is performed by meeting quality standards and by competent endoscopists with good procedural success. Improving sedation strategies, microbiological surveillance, and training programs remains an unmet need.

Interactions between genes altered during cardiotoxicity and neurotoxicity in zebrafish revealed using induced network modules analysis.

As the manufacturing and development of new synthetic compounds increase to keep pace with the expanding global demand, adverse health effects due to these compounds are emerging as critical public health concerns. Zebrafish have become a prominent model organism to study toxicology due to their genomic similarity to humans, optical clarity, well-defined developmental stages, short generation time, and cost-effective maintenance. It also provides a shorter time frame for in vivo toxicology evaluation compared to the mammalian experimental systems. Here, we used meta-analysis to examine the alteration in genes during cardiotoxicity and neurotoxicity in zebrafish, caused by chemical exposure of any kind. First, we searched the literature comprehensively for genes that are altered during neurotoxicity and cardiotoxicity followed by meta-analysis using ConsensusPathDB. Since constant communication between the heart and the brain is an important physiological phenomenon, we also analyzed interactions among genes altered simultaneously during cardiotoxicity and neurotoxicity using induced network modules analysis in ConsensusPathDB. We observed inflammation and regeneration as the major pathways involved in cardiotoxicity and neurotoxicity. A large number of intermediate genes and input genes anchored in these pathways are molecular regulators of cell cycle progression and cell death and are implicated in tumor manifestation. We propose potential predictive biomarkers for neurotoxicity and cardiotoxicity and the major pathways potentially implicated in the manifestation of a particular toxicity phenotype.

Voltage-Gated T-Type Calcium Channel Modulation by Kinases and Phosphatases: The Old Ones, the New Ones, and the Missing Ones.

Calcium (Ca2+) can regulate a wide variety of cellular fates, such as proliferation, apoptosis, and autophagy. More importantly, changes in the intracellular Ca2+ level can modulate signaling pathways that control a broad range of physiological as well as pathological cellular events, including those important to cellular excitability, cell cycle, gene-transcription, contraction, cancer progression, etc. Not only intracellular Ca2+ level but the distribution of Ca2+ in the intracellular compartments is also a highly regulated process. For this Ca2+ homeostasis, numerous Ca2+ chelating, storage, and transport mechanisms are required. There are also specialized proteins that are responsible for buffering and transport of Ca2+. T-type Ca2+ channels (TTCCs) are one of those specialized proteins which play a key role in the signal transduction of many excitable and non-excitable cell types. TTCCs are low-voltage activated channels that belong to the family of voltage-gated Ca2+ channels. Over decades, multiple kinases and phosphatases have been shown to modulate the activity of TTCCs, thus playing an indirect role in maintaining cellular physiology. In this review, we provide information on the kinase and phosphatase modulation of TTCC isoforms Cav3.1, Cav3.2, and Cav3.3, which are mostly described for roles unrelated to cellular excitability. We also describe possible potential modulations that are yet to be explored. For example, both mitogen-activated protein kinase and citron kinase show affinity for different TTCC isoforms; however, the effect of such interaction on TTCC current/kinetics has not been studied yet.

A multi-omics approach to visualize early neuronal differentiation from hESCs in 4D.

Neuronal differentiation of pluripotent stem cells is an established method to study physiology, disease, and medication safety. However, the sequence of events in human neuronal differentiation and the ability of in vitro models to recapitulate early brain development are poorly understood. We developed a protocol optimized for the study of early human brain development and neuropharmacological applications. We comprehensively characterized gene expression and epigenetic profiles at four timepoints, because the cells differentiate from embryonic stem cells towards a heterogeneous population of progenitors, immature and mature neurons bearing telencephalic signatures. A multi-omics roadmap of neuronal differentiation, combined with searchable interactive gene analysis tools, allows for extensive exploration of early neuronal development and the effect of medications.

Asporin, an extracellular matrix protein, is a beneficial regulator of cardiac remodeling.

Heart failure is accompanied by adverse cardiac remodeling involving extracellular matrix (ECM). Cardiac ECM acts as a major reservoir for many proteins including growth factors, cytokines, collagens, and proteoglycans. Activated fibroblasts during cardiac injury can alter the composition and activity of these ECM proteins. Through unbiased analysis of a microarray dataset of human heart tissue comparing normal hearts (n = 135) to hearts with ischemic cardiomyopathy (n = 94), we identified Asporin (ASPN) as the top differentially regulated gene (DEG) in ischemic cardiomyopathy; its gene-ontology terms relate closely to fibrosis and cell death. ASPN is a Class I small leucine repeat protein member implicated in cancer, osteoarthritis, and periodontal ligament mineralization. However, its role in cardiac remodeling is still unknown. Here, we initially confirmed our big dataset analysis through cells, mice, and clinical atrial biopsy samples to demonstrate increased Aspn expression after pressure overload or cardiac ischemia/reperfusion injury. We tested the hypothesis that Aspn, being a TGFß1 inhibitor, can attenuate fibrosis in mouse models of cardiac injury. We found that Aspn is released by cardiac fibroblasts and attenuates TGFß signaling. Moreover, Aspn-/- mice displayed increased fibrosis and decreased cardiac function after pressure overload by transverse aortic constriction (TAC) in mice. In addition, Aspn protected cardiomyocytes from hypoxia/reoxygenation-induced cell death and regulated mitochondrial bioenergetics in cardiomyocytes. Increased infarct size after ischemia/reperfusion injury in Aspn-/- mice confirmed Aspn's contribution to cardiomyocyte viability. Echocardiography revealed greater reduction in left ventricular systolic function post-I/R in the Aspn-/- animals compared to wild type. Furthermore, we developed an ASPN-mimic peptide using molecular modeling and docking which when administered to mice prevented TAC-induced fibrosis and preserved heart function. The peptide also reduced infarct size after I/R in mice, demonstrating the translational potential of ASPN-based therapy. Thus, we establish the role of ASPN as a critical ECM molecule that regulates cardiac remodeling to preserve heart function.

Non-Coding RNAs Are Brokers in Breast Cancer Interactome Networks and Add Discrimination Power between Subtypes.

Despite the power of high-throughput genomics, most non-coding RNA (ncRNA) biotypes remain hard to identify, characterize, and validate. This is a clear indication that intensive next-generation sequencing research has led to great efficiency and accuracy in detecting ncRNAs, but not in their functionalization. Computational scientists continue to support the discovery process by spotting significant data features (expression or mutational profiles), elucidating phenotype uncertainty, and delineating complex regulation landscapes for biological pathways and pathophysiological processes. With reference to transcriptome regulation dynamics in cancer, this work introduces a novel network-driven inference approach designed to reveal the potential role of computationally identified ncRNAs in discriminating between breast cancer (BC) subtypes beyond the traditional gene expression signatures. As heterogeneity cast in the subtypes is a characteristic of most cancers, the proposed approach is generalizable beyond BC. Expression profiles of a wide transcriptome spectrum were obtained for a number of BC patients (and controls) listed in TCGA and processed with RNA-Seq. The well-known PAM50 subtype signature was available for the samples and used to move from differentially expressed transcript profiles to subtype-specific biclusters associating gene patterns with patients. Co-expressed gene networks were then generated and annotations were provided, focusing on the biclusters with basal and luminal signatures. These were used to build template maps, i.e., networks in which to embed the ncRNAs and contextually functionalize them based on their interactors. This inference approach is able to assess the influence of ncRNAs at the level of BC subtype. Network topology was considered through the brokerage measure to account for disruptiveness effects induced by the removal of nodes corresponding to ncRNAs. Equivalently, it is shown that ncRNAs can act as brokers of network interactome dynamics, and removing them allows the refinement of subtype-related characteristics previously obtained by gene signatures only. The results of the study elucidate the role of pseudogenes in two major BC subtypes, considering the contextual annotations. Put into a wider perspective, ncRNA brokers may help predictive functionalization studies targeted to new disease phenotypes, for instance those linked to the tumor microenvironment or metabolism, or those specifically involving metastasis. Overall, the approach may represent an in silico prioritization strategy toward the systems identification of new diagnostic and prognostic biomarkers.

ShinyArchR.UiO: user-friendly,integrative and open-source tool for visualization of single-cell ATAC-seq data using ArchR.

MOTIVATION: Mapping of chromatin accessibility landscapes in single-cells and the integration with gene expression enables a better understanding of gene regulatory mechanisms defining cell identities and cell-fate determination in development and disease. Generally, raw data generated from single-cell Assay for Transposase-Accessible Chromatin sequencing (scATAC-seq) are deposited in repositories that are generally inaccessible due to lack of in-depth knowledge of computational programming. RESULTS: We have developed ShinyArchR.UiO, an R-based shiny app, that facilitates scATAC-seq data accessibility and visualization in a user-friendly, interactive and open-source web interface. ShinyArchR.UiO is an application that can streamline collaborative efforts for interpretation of massive chromatin accessibility datasets and allow for open access data sharing for wider audiences. AVAILABILITY AND IMPLEMENTATION: https://Github.com/EskelandLab/ShinyArchRUiO and a demo server with a hematopoietic tutorial dataset https://cancell.medisin.uio.no/ShinyArchR.UiO. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Proteomics of Mouse Heart Ventricles Reveals Mitochondria and Metabolism as Major Targets of a Post-Infarction Short-Acting GLP1Ra-Therapy.

Cardiovascular disease is the main cause of death worldwide, making it crucial to search for new therapies to mitigate major adverse cardiac events (MACEs) after a cardiac ischemic episode. Drugs in the class of the glucagon-like peptide-1 receptor agonists (GLP1Ra) have demonstrated benefits for heart function and reduced the incidence of MACE in patients with diabetes. Previously, we demonstrated that a short-acting GLP1Ra known as DMB (2-quinoxalinamine, 6,7-dichloro-N-[1,1-dimethylethyl]-3-[methylsulfonyl]-,6,7-dichloro-2-methylsulfonyl-3-N-tert-butylaminoquinoxaline or compound 2, Sigma) also mitigates adverse postinfarction left ventricular remodeling and cardiac dysfunction in lean mice through activation of parkin-mediated mitophagy following infarction. Here, we combined proteomics with in silico analysis to characterize the range of effects of DMB in vivo throughout the course of early postinfarction remodeling. We demonstrate that the mitochondrion is a key target of DMB and mitochondrial respiration, oxidative phosphorylation and metabolic processes such as glycolysis and fatty acid beta-oxidation are the main biological processes being regulated by this compound in the heart. Moreover, the overexpression of proteins with hub properties identified by protein-protein interaction networks, such as Atp2a2, may also be important to the mechanism of action of DMB. Data are available via ProteomeXchange with identifier PXD027867.

Carbamazepine-associated Drug Reaction with Eosinophilia and Systemic Symptoms Syndrome.

Drug reaction with eosinophilia and systemic symptoms syndrome is a severe type IV (delayed T-cell-dependent reaction) hypersensitivity reaction, characterized by fever, mucocutaneous eruptions, eosinophilia, and systemic inflammatory involvement. It usually begins a few weeks after the exposure to offending drug. Commonly implicated drugs are aromatic anticonvulsants (phenytoin, phenobarbitone, and carbamazepine) and sulfa drugs (sulfonamides, sulfasalazine, and dapsone). It is a potentially life-threatening hypersensitivity reaction. Here we report a case of drug reaction with eosinophilia and systemic symptoms syndrome associated with carbamazepine, which was successfully treated with intravenous methylprednisolone.

Reckoning γ-Glutamyl-S-allylcysteine as a potential main protease (mpro) inhibitor of novel SARS-CoV-2 virus identified using docking and molecular dynamics simulation.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2 or COVID-19), outbreak was first reported in December 2019 in the Wuhan, China. COVID-19 managed to spread worldwide and so far more than 9.1 million cases and more than 4.7 lakh death has been reported globally. Children, pregnant women, elderly population, immunocompromised patients, and patients with conditions like asthma, diabetes, etc. are highly vulnerable to COVID infection. Currently, there is no treatment available for COVID-19 infection. Traditional medicinal plants have provided bioactive molecules in the past that are efficiently used during conditions like cancer, malaria, microbial infections, immune-compromised states, etc. AYUSH India has recommended the use of Curcuma longa, Allium sativum, Ocimum tenuiflorum, and Withania somnifera for immune-boosting during SARS-CoV-2 infection. In the present study, we investigated the potential of 63-major bioactive molecules of these plants against SARS-CoV-2 main protease (Mpro) through docking studies and compared the results with known inhibitor 11a. Our results proposed cuscohygrine, γ-Glutamyl-S-allylcysteine, anahygrine, and S-allylcystein as the potent inhibitors against Mpro identified using molecular docking and molecular simulation dynamics. Interestingly, these molecules are from A. sativum, and W. somnifera, which are known for their antimicrobial and immunomodulatory potential. None of the proposed molecules have earlier been reported as antiviral molecules. Our results predict very strong potential of these four-molecules against SARS-CoV-2 Mpro, especially γ-glutamyl-S-allylcysteine, as all four form hydrogen bonding with Glu166 that is a crucial residue for the formation of the biologically active dimeric form of Mpro. Therefore, we strongly recommend further research on these biomolecules against SARS-CoV-2.