Biology subjects

Sarker, S.

Publications and source records attributed to Sarker, S..

7 recordsLinked to original sources

bioRxiv2026

Plant Molecules Protect Against Inflammatory Bowel Disease by Restoring Gut Microbiota-Immune Homeostasis and Suppressing Pro-inflammatory Markers

Inflammatory bowel disease (IBD) is associated with chronic intestinal inflammation and gut microbial dysbiosis, yet effective microbiome-targeted therapeutics remain limited. Here, we investigated the anti-inflammatory and microbiome-modulating activities of metabolites isolated from Garcinia brassii, an endemic species of the Australian Wet Tropics. Five compounds, including a new natural product named garcitine, were isolated and structurally characterised. In human immune cells, garcinol and garcinia biflavonoid 1 significantly suppressed lipopolysaccharide-induced production of IL-1{beta}, IL-6, and TNF without detectable cytotoxicity, while parvifoliol F selectively inhibited IL-1{beta} release. Therapeutic efficacy was further evaluated in a TNBS-induced murine colitis model, where garcinia biflavonoid 1 and parvifoliol F significantly reduced colonic inflammation and improved histopathological outcomes. 16S rRNA sequencing demonstrated that both compounds restored gut microbial homeostasis by reversing colitis-associated dysbiosis and reducing inflammation-associated microbial signatures. Functional pathway prediction further suggested suppression of pro-inflammatory microbial metabolic pathways following treatment. Together, these findings demonstrate that Garcinia-derived metabolites alleviate experimental colitis through coordinated immunomodulatory and microbiome-reprogramming mechanisms and identify garcinia biflavonoid 1 and parvifoliol F as promising candidates for microbiome-targeted IBD therapeutics.

immunology↗

bioRxiv2026

Spike antibodies targeting GRP78 predispose to cardiovascular complications compared to Dengue

One major aftermath of COVID-19 pandemic is cardiovascular consequences. SARS-CoV-2 binds to ACE2 and downregulates vasodilation. Dengue favors hypotension by weakening endothelial glycocalyx leading to plasma leakage. C1q levels, immune complexes (ICs), and proteomic profiles in serum samples from 52 COVID-19 and 19 pre-pandemic Dengue cases were studied. Unlike Dengue, COVID-19 serums showed elevated coagulation proteins promoting vaso-occlusion and peripheral artery diseases. The stress-induced chaperone and atherosclerosis marker, GRP78 (gene/ protein) was found upregulated upon SARS-CoV-2 spike expression in cardiac/ lung cell lines. Elevated GRP78 levels were also observed in serum samples from COVID-19-diagnosed individuals and subjects with myocardial infarction (MI) in post COVID-era. Surprisingly, spike antibodies (Abs) showed cross-binding to GRP78 and possibly contributed to the observed higher-level ICs in COVID-19 serums (cardiovascular embolism?). Co-localization studies showed that spike Abs (analogous to pro-atherosclerotic GRP78 auto-Abs) could directly bind to upregulated cellular GRP78 (type II hypersensitivity?). Both pathways could worsen vascular injury and atherosclerosis, leading to cardiac complications in COVID-19 cases with narrowed vessels.

microbiology↗

bioRxiv2025

omicML: An Integrative Bioinformatics and Machine Learning Framework for Transcriptomic Biomarker Identification

IntroductionTranscriptomic biomarker discovery has been a challenge due to variation in datasets and platforms, complexity in statistical and computational methods, integration of multiple programming languages, and intricacy of ML workflow to evaluate biomarkers. Standard workflows necessitate several stages (quality control, normalization, differential expression), typically executed in R or Python, resulting in bottlenecks for non-experts. Existing platforms have alleviated certain challenges by offering graphical interfaces for data loading, normalization, differential gene expression analysis, and functional analysis; nevertheless, they typically do not incorporate integrated machine learning procedures for biomarker selection. MethodIn this regard, we present omicML, an intuitive graphical user interface (GUI) that combines transcriptomic data analysis with machine learning (ML)-based classification via integrating R and Python packages/libraries. It supports both RNA-Seq and microarray data, automating preprocessing (data import, quality control, and normalization) and differential expression analysis. The tool annotates differentially expressed genes (DEGs) with descriptions, gene ontology, and pathway information and incorporates comparative analysis. Our extensive ML pipeline enables both supervised and unsupervised learning, integrates various datasets based on candidate gene signatures, standardizes and eliminates less significant features, benchmarks multiple ML classifiers with robust performance metrics (e.g., AUROC, AUPRC), assesses feature importance, develops single-gene and multi-gene predictive models, and systematically finalizes the biomarker algorithm. All functionalities are available in omicML, hence reducing the barrier for biologists without computational proficiency. ResultIn a case study, omicML identified a six-gene diagnostic model that distinguishes Mpox (monkeypox virus) infections from those caused by other viruses, including SARS-CoV-2, HIV, Ebola, and varicella-zoster. These results illustrate omicMLs capacity to discern clinically relevant biomarkers from complex transcriptome data. ConclusionThrough the unified system, omicML (https://omicml.org), integrating data preprocessing, differential gene expression analysis, annotation, heatmap analysis, dataset integration, batch effect correction, machine learning approach, and functional analysis can diminish technical barriers and accelerates the conversion of expression data into diagnostic insights for clinicians and bench scientists.

bioinformatics↗

bioRxiv2025

An Innovative Framework for Heart Sound Classification Integrating Adaptive Fuzzy Rank-Based Ensemble of Transfer Learning Models with Multi-Dimensional Features

Heart sound identification for diagnosing cardiovascular diseases is a complex challenge due to the intricate, spectro-temporal characteristics of conditions like Aortic Stenosis, Mitral Regurgitation, and multi-valvular disorders. Conventional methods frequently inadequately encompass the complete range of diagnostic characteristics, depending on fragmented or simplistic approaches that lack generalizability across varied patient demographics, clinical settings, and recording circumstances. To address these limitations, we offer an innovative, multi-dimensional feature fusion framework that integrates Wavelet Scattering Transform (WST) and Mel-Frequency Cepstral Coefficients (MFCC) to capture both temporal stability and perceptually optimal frequency patterns from cardiac sounds. This method is further refined by an adaptive fuzzy rank-based ensemble technique utilizing the Gompertz function, which dynamically modifies model weights according to confidence metrics, hence assuring more dependable and precise predictions amidst fluctuating clinical uncertainty. We meticulously assess our model utilizing eight advanced fine-tuned transfer learning architectures across four feature extraction techniques (WST, MFCC, STFT, Multi-Dimensional) on the clinically validated BUET Multi-disease Heart Sound (BMD-HS) dataset. This dataset comprises 864 phonocardiogram recordings from 108 participants with echocardiographically confirmed diagnoses. The multi-dimensional feature fusion method attains 97% accuracy with EfficientNetB2, whereas the adaptive fuzzy ensemble strategy achieves 98% accuracy, surpassing both individual models and conventional ensemble methods. Moreover, Explainable AI with Audio-LIME offers transparent, clinically interpretable insights, achieving fidelity scores surpassing 0.85 and clinical relevance ratings exceeding 90%, facilitating the identification of critical time-frequency regions that hold diagnostic significance. This system establishes a novel benchmark for heart sound classification, enhances the differentiation of intricate valvular disorders, and provides dependable, evidence-based decision support for cardiovascular diagnosis in clinical settings. Our research illustrates the capability for resilient, scalable, and interpretable heart sound classification systems that can improve clinical decision-making and promote the integration of automated diagnostic tools in healthcare.

bioengineering↗

bioRxiv2025

Nuclear trafficking of Anelloviridae capsid protein ORF1 reflects modular evolution of subcellular targeting signals

Anelloviridae members are ubiquitous viruses with a small, negative sense, single-stranded DNA genome which is replicated by host cell DNA polymerases. Anelloviruses are postulated to interact with the host cell nuclear transport machinery, however, the lack of reliable cell culture models strongly limits our knowledge regarding Anelloviridae-host interactions. In particular, capsid nuclear import is a largely uncharacterized process. We addressed this by investigating the relationship between host cell nuclear transport receptors (NTRs) and ORF1, the putative capsid protein from torque teno douroucouli virus (TTDoV). We identified the subcellular targeting signals and NTRs responsible for its nucleolar and nuclear localization, and characterized their relative contribution to ORF1 subcellular localization. In the absence of other viral proteins, ORF1 accumulated in the nucleoli. Bioinformatics analysis revealed a putative nuclear localization signal (NLS) within the highly conserved N-terminal arginine rich motif (ARM) ("NLSn", 27-RRWRRRPRRRRRPYR-RRPYRRYGRRRKVRRR-57), and an additional C-terminal NLS ("NLSc", 632-LPPPEKRARWGF-643), which has been specifically acquired by Anelloviridae capsids with larger projection domains. Such NLSs play distinct roles in ORF1 subcellular localization. NLSn features broad importin (IMP) binding affinity yet plays a minor role in nuclear import, being responsible for nucleolar targeting likely through interaction with nucleolar components. NLSc specifically interacts with IMP and is the main driver of active nuclear transport in an IMP/{beta}1-dependent fashion. These findings suggest an evolutionary correlation between the acquisition of progressively larger projection domains and the presence of additional NLSs in Anelloviridae capsids, aimed at maximizing IMP/{beta}1-mediated nuclear import.

microbiology↗

bioRxiv2023

Determining the shelf life of an erythropoietin alfa biosimilar GBPD002 through stability study

GBPD002 is a recombinant human erythropoietin (rhEPO) produced by recombinant DNA technology using mammalian cell expression system. In this study, samples were analyzed according to current Good Laboratory Practice (cGLP) and regulatory guidelines to evaluate the quality of the product under the influence of variety of environmental factors in a time-dependent manner. Accelerated (25 {+/-} 2 {degrees}C and relative humidity: 60 {+/-} 5 %) and real-time (5 {+/-} 3 {degrees}C) stability study were conducted up to 6 months and 12 months, respectively; samples were analyzed in every 3 months. After 12 months, real-time stability studies were performed with 6 months interval up to18 months, which to be continued up to 24 months. Appearance and pH were assessed using standard methods, and molecular weight was determined by Western blotting. Chromatographic identification and quantitative assays were performed by reversed- phase chromatography (RPC). High-molecular weight aggregatesand degradants were determined using size exclusion chromatography (SEC) and particle size distribution (PSD) analysis. Biofunctionality of the samples were evaluated by in vitro and in vivo bioassays. Bacterial endotoxin and sterility test were performed as safety parameters. All samples met the acceptance criteria, and the data were extrapolated using the regulatory guideline to determine the shelf life. The data revealed that the GBPD002 is stable up to 24 months.

pharmacology and toxicology↗

bioRxiv2022

A mechanistic insight into Nigella sativa mediated anticancer effect on breast cancer through regulation of various miRNAs: An in vitro & in vivo study

BackgroundCancer continues to threat the mortal alongside scientific community with its burgeoning grasp. Although efforts have been directed to tame cancer by radiotherapy, photodynamic therapy, chemotherapy it came at a cost of fatal side effects. PurposePlant derived bioactive compounds carries an inevitable advantage of being safer, bioavailable & less toxic compared to contemporary chemotherapeutics. This study analyzed anti-cancerous potential of volatile oil, extracted from Nigella sativa, in-vitro against MDA-MB-231, MCF-7 & in-vivo on tumor growth in mice after successful oral administration. Study DesignOur strategic approach employed solvent extraction of black seed oil (BSO) to highlight orchestrated use of its potent integrants - TQ, Carvacrol & TA which in modest amounts show anti-cancerous properties compared to their individual treatment. We attempted to show this cost effective, safe & bioavailable form of dealing with the atrocities of breast cancer by means of MTT, Apoptotic, Western Blot Assays besides Transwell & Wound healing Assay. Reduction in the solid tumour in-vivo & near normalcy restoration of tissue section architecture from the BSO treated tumour sets are indicative of the better anti-tumorigenic potential of BSO. MethodsBSOs Solvent extraction was performed followed by its characterization. MTT aided cytotoxicity study of BSO alongside major components in PBMC & cancer cells while its efficacy was presented by flow cytometric ROS analysis, cell cycle arrest & apoptosis assessment. Anti-migratory potential evaluated by Wound Healing, Transwell Migration & Western Blot while the expression study of a wide range of proteins, miRNAs & the in-vivo studies undertaken climaxed the confirmation of the anti-cancerous potential of BSO. ResultsComparatively reduced concentrations of TQ, TA & Carvacrol in BSO played a synergistic role to enhance apoptotic potential via Caspase 7 & 9, through enhanced ROS & expression of apoptotic family of proteins, miRNAs besides uplifting the anti-migratory perspective by effectively enhancing E-cad & downregulating lamellipodia, filopodia assembly & MMPs in MCF-7 & MDA-MB-231. Similar observations in-vivo outlined the therapeutic potential of BSO. ConclusionThis study culminates isolation & processing of BSO in a simplified procedure, thereby aiming at a more lucrative paradigm to be accepted in contemporary phytomedicine research.

cancer biology↗