AIMC Topic: Single-Cell Analysis

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Deep learning-powered high-efficient atomic force microscopy single-cell nanomechanical analysis on diverse biointerfaces.

Biochemical and biophysical research communications
The extracellular matrix (ECM) is crucial in tuning cellular behavior, and quantifying cellular mechanical changes in response to ECM stimuli can help reveal the underlying physical mechanisms of cell-ECM interactions for a comprehensive understandin...

Biology-driven insights into the power of single-cell foundation models.

Genome biology
BACKGROUND: Single-cell foundation models (scFMs) have emerged as powerful tools for integrating heterogeneous datasets and exploring biological systems. Despite high expectations, their ability to extract unique biological insights beyond standard m...

Immune system development-related signature predicts prognosis and sorafenib-treatment resistance of hepatocellular carcinoma by intergrating machine learning and single-cell analyses.

Scientific reports
The development of the immune system (ISD) plays a pivotal role in both the genesis and progression of tumors, yet its specific functions in hepatocellular carcinoma (HCC) and the mechanisms behind sorafenib resistance remain elusive. In our investig...

Single-Cell Raman Spectroscopy Combined with Metabolomics Reveals Distinct Metabolic Profiles in Medulloblastoma Subtypes.

Analytical chemistry
Tumor heterogeneity poses a major challenge to the precision treatment of medulloblastoma (MB). Rapid and accurate subtyping tools are urgently needed for informed clinical decision-making. Herein, we demonstrate the utility of Raman spectroscopy (RS...

A specific gene expression program underlies antigen archiving by lymphatic endothelial cells in mammalian lymph nodes.

Nature communications
Lymph node (LN) lymphatic endothelial cells (LEC) actively acquire and archive foreign antigens. Here, we address questions of how LECs achieve durable antigen archiving and whether LECs with high levels of antigen express unique transcriptional prog...

Integrative single-cell and machine learning approach to characterize immunogenic cell death and tumor microenvironment in LUAD.

Journal of translational medicine
BACKGROUND: Immunogenic cell death (ICD) triggers antitumor immune responses and plays a critical role in shaping the tumor microenvironment (TME). However, its specific contribution to lung adenocarcinoma (LUAD) progression and immunotherapy respons...

scKAN: interpretable single-cell analysis for cell-type-specific gene discovery and drug repurposing via Kolmogorov-Arnold networks.

Genome biology
BACKGROUND: Analysis of single-cell RNA sequencing (scRNA-seq) data has revolutionized our understanding of cellular heterogeneity, yet current approaches face challenges in efficiency, interpretability, and connecting molecular insights to therapeut...

Comprehensive characterization of the molecular feature of acetylation in colorectal cancer using integrated single-cell and bulk RNA sequencing.

Scientific reports
Colorectal cancer (CRC) remains a major global health burden with high mortality rates, underscoring the need for effective therapies. This study explores the acetylation characteristics in CRC using single-cell RNA sequencing (scRNA-seq) and weighte...

High-speed cell partitioning through reactive machine learning-guided inkjet printing.

Lab on a chip
Partitioning cells in open nanowells permits high confidence in single cell occupancy and enables flexibility in the development of different molecular assays. A challenge for this approach however is to print cells sufficiently quickly to enable exp...