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Cellular Microenvironment

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Quantitative diagnosis of breast tumors by morphometric classification of microenvironmental myoepithelial cells using a machine learning approach.

Scientific reports
Machine learning systems have recently received increased attention for their broad applications in several fields. In this study, we show for the first time that histological types of breast tumors can be classified using subtle morphological differ...

Environmental properties of cells improve machine learning-based phenotype recognition accuracy.

Scientific reports
To answer major questions of cell biology, it is often essential to understand the complex phenotypic composition of cellular systems precisely. Modern automated microscopes produce vast amounts of images routinely, making manual analysis nearly impo...

Prediction of disease-associated nsSNPs by integrating multi-scale ResNet models with deep feature fusion.

Briefings in bioinformatics
More than 6000 human diseases have been recorded to be caused by non-synonymous single nucleotide polymorphisms (nsSNPs). Rapid and accurate prediction of pathogenic nsSNPs can improve our understanding of the principle and design of new drugs, which...

Microfluidic Tissue Engineering and Bio-Actuation.

Advanced materials (Deerfield Beach, Fla.)
Bio-hybrid technologies aim to replicate the unique capabilities of biological systems that could surpass advanced artificial technologies. Soft bio-hybrid robots consist of synthetic and living materials and have the potential to self-assemble, rege...

Machine learning-based inverse design for electrochemically controlled microscopic gradients of O and HO.

Proceedings of the National Academy of Sciences of the United States of America
A fundamental understanding of extracellular microenvironments of O and reactive oxygen species (ROS) such as HO, ubiquitous in microbiology, demands high-throughput methods of mimicking, controlling, and perturbing gradients of O and HO at microscop...

Fisheye transformation enhances deep-learning-based single-cell phenotyping by including cellular microenvironment.

Cell reports methods
Incorporating information about the surroundings can have a significant impact on successfully determining the class of an object. This is of particular interest when determining the phenotypes of cells, for example, in the context of high-throughput...

Integrated analysis of single-cell sequencing and machine learning identifies a signature based on monocyte/macrophage hub genes to analyze the intracranial aneurysm associated immune microenvironment.

Frontiers in immunology
Monocytes are pivotal immune cells in eliciting specific immune responses and can exert a significant impact on the progression, prognosis, and immunotherapy of intracranial aneurysms (IAs). The objective of this study was to identify monocyte/macrop...

Spatiotemporal feature learning for actin dynamics.

PloS one
The social amoeba Dictyostelium discoideum is a standard model system for studying cell motility and formation of biological patterns. D. discoideum cells form protrusions and migrate via cytoskeletal reorganization driven by coordinated waves of act...

Robotic Microcapsule Assemblies with Adaptive Mobility for Targeted Treatment of Rugged Biological Microenvironments.

ACS nano
Microrobots are poised to transform biomedicine by enabling precise, noninvasive procedures. However, current magnetic microrobots, composed of solid monolithic particles, present fundamental challenges in engineering intersubunit interactions, limit...

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
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...