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Extracellular Matrix Proteins

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Substrate stiffness affects neural network activity in an extracellular matrix proteins dependent manner.

Colloids and surfaces. B, Biointerfaces
Neuronal growth, differentiation, extension, branching and neural network activity are strongly influenced by the mechanical property of extracellular matrix (ECM). However, the mechanism by which substrate stiffness regulates a neural network activi...

Phrase mining of textual data to analyze extracellular matrix protein patterns across cardiovascular disease.

American journal of physiology. Heart and circulatory physiology
Extracellular matrix (ECM) proteins have been shown to play important roles regulating multiple biological processes in an array of organ systems, including the cardiovascular system. Using a novel bioinformatics text-mining tool, we studied six cate...

The anti-ageing effects of a natural peptide discovered by artificial intelligence.

International journal of cosmetic science
OBJECTIVE: As skin ages, impaired extracellular matrix (ECM) protein synthesis and increased action of degradative enzymes manifest as atrophy, wrinkling and laxity. There is mounting evidence for the functional role of exogenous peptides across many...

Predicting Proteolysis in Complex Proteomes Using Deep Learning.

International journal of molecular sciences
Both protease- and reactive oxygen species (ROS)-mediated proteolysis are thought to be key effectors of tissue remodeling. We have previously shown that comparison of amino acid composition can predict the differential susceptibilities of proteins t...

Deep learning boosts sensitivity of mass spectrometry-based immunopeptidomics.

Nature communications
Characterizing the human leukocyte antigen (HLA) bound ligandome by mass spectrometry (MS) holds great promise for developing vaccines and drugs for immune-oncology. Still, the identification of non-tryptic peptides presents substantial computational...

MicroRNA classification and discovery for major depressive disorder diagnosis: Towards a robust and interpretable machine learning approach.

Journal of affective disorders
BACKGROUND: Major depressive disorder (MDD) is notably underdiagnosed and undertreated due to its complex nature and subjective diagnostic methods. Biomarker identification would help provide a clearer understanding of MDD aetiology. Although machine...

Au-decorated TiCT/porous carbon immunoplatform for ECM1 breast cancer biomarker detection with machine learning computation for predictive accuracy.

Talanta
Electrochemical immunosensors, surpassing conventional diagnostics, exhibit significant potential for cancer biomarker detection. However, achieving a delicate balance between signal sensitivity and operational stability, especially at the heterostru...

Integration of single-cell and bulk RNA sequencing data using machine learning identifies oxidative stress-related genes LUM and PCOLCE2 as potential biomarkers for heart failure.

International journal of biological macromolecules
Oxidative stress (OS) is a pivotal mechanism driving the progression of cardiovascular diseases, particularly heart failure (HF). However, the comprehensive characterisation of OS-related genes in HF remains largely unexplored. In the present study, ...