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Stress-tolerance genes in rice: bridging gene discovery, functional validation, and breeding applications
Rice productivity is increasingly threatened by abiotic stresses, with drought being a major constraint to stable yields under changing climate conditions. Advances in genomics and high-throughput omics technologies have identified numerous drought-responsive genes in rice …
Read PDFInflammation-associated brain functional network topological disruption in female nurses with SWSD: associations with symptoms and transcriptomics
<h4>Introduction</h4>Shift work sleep disorder (SWSD) is prevalent among female nurses and is associated with significant health morbidities. While inflammation is implicated in SWSD, how it relates to brain network alterations and clinical symptoms remains underexplored. …
Read PDFSalmonAct deciphers transcription factor regulatory activity in <i>Salmonella</i> transcriptomics
Foodborne <i>Salmonella enterica</i> infection remains a major public health threat due to its prevalence in food, ease of transmission, and increasing antibiotic resistance. Consequently, understanding the molecular mechanisms underlying <i>Salmonella</i> pathogenesis is crucial for guiding …
Read PDFSpatial Multiomics Reveal Insights Into ADC Efficacy
Antibody-drug conjugates (ADCs) have transformed the therapeutic landscape of solid tumors; however, responses remain heterogeneous and complex to predict. In addition, a growing number of multiple ADC targets are either approved or in late-stage clinical …
Read PDFWBT-DC pipeline: a cross-cohort and cross-platform disease classification pipeline based on whole-blood transcriptomics
<h4>Background</h4>Machine-learning models based on tissue transcriptomic data are powerful tools for disease classification. However, their clinical adoption is limited by the invasive nature of tissue sampling. Furthermore, transcriptomic datasets are often affected by batch effects …
Read PDFTopological Data Analysis for Unsupervised Feature Selection in Large Scale Spatial Omics Data Sets
Spatial transcriptomics studies are becoming increasingly large and commonplace, necessitating simultaneous analysis of a large number of spatially resolved variables. Correspondingly, a diverse range of methodologies have been proposed to compare the spatial expression structure …
Read PDFIdentification of an immediate-early gene-activated fibroblast state in frozen shoulder capsular fibrosis
Frozen shoulder (adhesive capsulitis) is characterized by progressive fibrotic remodeling of the shoulder joint capsule. To investigate the cellular programs underlying the fibrotic process, we integrate spatial transcriptomics, pseudotime inference, and <i>in situ</i> validation to …
Read PDFIntegrative Molecular Analyses of Inflammatory and Autoimmune Signals in Cardiac Sarcoidosis
<h4>Background</h4>Cardiac sarcoidosis (CS) is an enigmatic disorder characterized by unexplained patchy, sterile granulomas intermixed with preserved myocardium and fibrotic regions without granuloma. CS causes arrhythmias, sudden cardiac death, and heart failure. The mechanisms producing this …
Read PDFSpatial Transcriptomics Meets Histochemistry: Insights from Glioblastoma as a Model System
High-resolution spatial transcriptomics has emerged as a powerful approach for linking genome-wide gene expression with preserved tissue architecture, enabling new insights into cellular heterogeneity and microenvironmental organization in complex tissues. In neuropathology, where morphological context …
Read PDFGraph informed biomarker discovery framework using transcriptomic machine learning for glioblastoma prognosis
Identifying reproducible, interpretable prognostic signals from high-dimensional transcriptomics remains challenging because gene-level models often ignore network context. We developed Graph-Informed Biomarker Discovery (GIBD), a locked transcriptomics-only framework for primary glioblastoma that integrates RNA-seq expression with …
Read PDFBridging the Precision Gap in Rheumatoid Arthritis: Spatial Transcriptomics, Spatial Proteomics, and Artificial Intelligence in Precision Health
Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by complex immune cell associations and continuous joint damage. Personalized clinical assessment and treatment options for RA remain hindered by a precision gap due to an …
Read PDFTranslating transcriptomics analysis into diagnostic workflows: clinical variant identification and interpretation in hypothesis-driven and hypothesis-free approaches
<h4>Background</h4>Despite significant advancements in genetic diagnosis, there are still bottlenecks in DNA-level testing. Challenges to diagnosis include the inability to identify the causal variant, and the lack of functional evidence leading to an accumulation of …
Read PDFTranscriptomics, Proteomics and Network Pharmacology Reveal the Mechanisms of Cantharidin-Induced Kidney Injury in Rats
Cantharidin (CTD), the principal active constituent of the traditional Chinese medicine (TCM) Mylabris, exhibits potent antitumor activity. However, its clinical application is limited by organ toxicity (especially nephrotoxicity), and the underlying mechanisms remain incompletely defined. …
Read PDFArtificial Intelligence in Transcriptomics: From Human-in-the-Loop to Agentic AI
To better understand the complexity of biological systems, research has shifted from a reductionist to a holistic approach, expanding the focus from single genes to a genome-scale view of gene activity and regulation. This is …
Read PDFIntegrative single-cell and spatial transcriptomics analysis reveals a baicalein-responsive 10-gene signature for non-small cell lung cancer
<h4>Background</h4>Non‑small cell lung cancer (NSCLC) remains a leading cause of cancer‑related mortality worldwide. Baicalein, a natural flavonoid, has shown anti‑cancer activity but its molecular targets and cell‑type‑specific effects in the tumor microenvironment (TME) are incompletely …
Read PDFPathway-centric visualization of cell-cell communication in single-cell transcriptomics data
Single-nuclei transcriptomics enables investigating ligand-receptor mediated cell-cell communication between different cell-types. However, current tools do not allow for non-programmatic means to access this analysis. Additionally, most methods can not account for molecular pathways involved in …
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