AIMC Topic: Single-Cell Analysis

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Circular RNA discovery with emerging sequencing and deep learning technologies.

Nature genetics Apr 17, 2025
Circular RNA (circRNA) represents a type of RNA molecule characterized by a closed-loop structure that is distinct from linear RNA counterparts. Recent studies have revealed the emerging role of these circular transcripts in gene regulation and disea...
Animals Deep Learning Single-Cell Analysis Sequence Analysis, RNA Humans Artificial Intelligence Algorithms High-Throughput Nucleotide Sequencing RNA, Circular
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Molecular features and diagnostic modeling of synovium- and IPFP-derived OA macrophages in the inflammatory microenvironment via scRNA-seq and machine learning.

Journal of orthopaedic surgery and research Apr 17, 2025
BACKGROUND: Osteoarthritis (OA) is the leading cause of degenerative joint disease, with total joint replacement as the only definitive cure. However, no disease-modifying therapy is currently available. Inflammation and fibrosis in the infrapatellar...
Macrophages Female Animals Male Middle Aged Single-Cell Analysis RNA-Seq Single-Cell Gene Expression Analysis Adipose Tissue Humans Osteoarthritis Machine Learning Cellular Microenvironment Rats Inflammation Synovial Membrane Rats, Sprague-Dawley
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Deep Visual Proteomics maps proteotoxicity in a genetic liver disease.

Nature Apr 16, 2025
Protein misfolding diseases, including α1-antitrypsin deficiency (AATD), pose substantial health challenges, with their cellular progression still poorly understood. We use spatial proteomics by mass spectrometry and machine learning to map AATD in h...
alpha 1-Antitrypsin Deficiency alpha 1-Antitrypsin Disease Progression Single-Cell Analysis Proteomics Proteome Liver Cirrhosis Machine Learning Humans Liver Phenotype Hepatocytes Female Unfolded Protein Response Male
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Artificial intelligence-assisted RNA-binding protein signature for prognostic stratification and therapeutic guidance in breast cancer.

Frontiers in immunology Apr 16, 2025
BACKGROUND: Breast cancer is the most common malignancy in women globally, with significant heterogeneity affecting prognosis and treatment. RNA-binding proteins play vital roles in tumor progression, yet their prognostic potential remains unclear. T...
Biomarkers, Tumor Prognosis Gene Expression Profiling Female Transcriptome Breast Neoplasms Single-Cell Analysis Tumor Microenvironment RNA-Binding Proteins Gene Expression Regulation, Neoplastic Humans Artificial Intelligence Machine Learning
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Single-Cell Sequencing-Guided Annotation of Rare Tumor Cells for Deep Learning-Based Cytopathologic Diagnosis of Early Lung Cancer.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Apr 15, 2025
Deep learning (DL) models for medical image analysis are majorly bottlenecked by the lack of well-annotated datasets. Bronchoalveolar lavage (BAL) is a minimally invasive procedure to diagnose lung cancer, but BAL cytology suffers from low sensitivit...
Male Deep Learning Single-Cell Analysis Lung Neoplasms Humans Female Early Detection of Cancer Cytodiagnosis Bronchoalveolar Lavage Fluid
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Integrating Machine Learning and Bulk and Single-Cell RNA Sequencing to Decipher Diverse Cell Death Patterns for Predicting the Prognosis of Neoadjuvant Chemotherapy in Breast Cancer.

International journal of molecular sciences Apr 13, 2025
Breast cancer (BRCA) continues to pose a serious risk to women's health worldwide. Neoadjuvant chemotherapy (NAC) is a critical treatment strategy. Nevertheless, the heterogeneity in treatment outcomes necessitates the identification of reliable biom...
Neoadjuvant Therapy Cell Death Single-Cell Analysis Female Sequence Analysis, RNA Breast Neoplasms Gene Expression Regulation, Neoplastic Biomarkers, Tumor Humans Middle Aged Machine Learning Prognosis
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Generating realistic single-cell images from CellProfiler representations.

Medical image analysis Apr 10, 2025
High-throughput imaging techniques acquire large amounts of images efficiently. These images contain rich biological information including cellular processes. A common method to analyse them is to encode them into quantitative representation vectors....
Machine Learning Algorithms Single-Cell Analysis Image Processing, Computer-Assisted Humans
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Identification of novel metabolism-related biomarkers of Kawasaki disease by integrating single-cell RNA sequencing analysis and machine learning algorithms.

Frontiers in immunology Apr 10, 2025
BACKGROUND: The bile acid metabolism (BAM) and fatty acid metabolism (FAM) have been implicated in Kawasaki disease (KD), but their precise mechanisms remain unclear. Identifying signature cells and genes related to BAM and FAM could offer a deeper u...
Single-Cell Analysis Monocytes Sequence Analysis, RNA Mucocutaneous Lymph Node Syndrome Biomarkers Gene Expression Profiling Transcriptome Humans Fatty Acids Machine Learning
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Comprehensive analysis of scRNA-seq and bulk RNA-seq data via machine learning and bioinformatics reveals the role of lysine metabolism-related genes in gastric carcinogenesis.

BMC cancer Apr 9, 2025
BACKGROUND: Gastric cancer (GC) is a highly aggressive and heterogeneous cancer with extremely complex biological characteristics. Lysine and its metabolism are closely related to human cancer, but little is known about how lysine metabolism-related ...
Vimentin Lysine Machine Learning Gene Expression Regulation, Neoplastic Prognosis Nomograms Stomach Neoplasms Cell Proliferation Single-Cell Gene Expression Analysis Biomarkers, Tumor Carcinogenesis Humans Computational Biology Cell Line, Tumor Sequence Analysis, RNA Single-Cell Analysis RNA-Seq Gene Regulatory Networks
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Unique and shared transcriptomic signatures underlying localized scleroderma pathogenesis identified using interpretable machine learning.

JCI insight Apr 8, 2025
Using transcriptomic profiling at single-cell resolution, we investigated cell-intrinsic and cell-extrinsic signatures associated with pathogenesis and inflammation-driven fibrosis in both adult and pediatric patients with localized scleroderma (LS)....
Child Single-Cell Analysis RNA-Seq Scleroderma, Systemic Gene Expression Profiling Transcriptome Case-Control Studies Adolescent Scleroderma, Localized Humans Machine Learning Female Adult Male Middle Aged
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