AIMC Topic: Mitochondria

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Protein interactions, network pharmacology, and machine learning work together to predict genes linked to mitochondrial dysfunction in hypertrophic cardiomyopathy.

Scientific reports
This study looked at possible targets for hypertrophic cardiomyopathy (HCM), a condition marked by thickening of the ventricular wall, primarily in the left ventricle. We employed differential gene analysis and weighted gene co-expression network ana...

Identification and verification of mitochondria-related genes biomarkers associated with immune infiltration for COPD using WGCNA and machine learning algorithms.

Scientific reports
Mitochondrial dysfunction plays a pivotal role in the pathogenesis of chronic obstructive pulmonary disease (COPD). This study combines bioinformatics analysis with machine learning to elucidate potential key mitochondrial-related genes associated wi...

Unveiling mitochondrial-targeting compounds in Qishenyiqi dropping pills for heart failure treatment: An integrative UHPLC-QTOF MS and high-content imaging strategy.

Journal of pharmaceutical and biomedical analysis
Mitochondrial dysfunction, a central pathogenic driver of heart failure (HF), underscores the therapeutic imperative to preserve mitochondrial homeostasis. Qishenyiqi dropping pills (QSYQ), a clinically validated traditional Chinese formulation, exhi...

Identification of Mitochondrial and Succinylation Modification-Related Gene Signature in Ischemic Stroke.

Molecular neurobiology
Ischemic stroke (IS) is a leading cause of death and disability worldwide, often associated with immune dysregulation, mitochondrial dysfunction, and altered protein succinylation. This study aimed to identify mitochondrial and succinylation-related ...

Gui-Pi-Tang Defers Skeletal Muscle and Cardiac Muscle Aging by Promoting Mitochondrial Remodeling.

Drug design, development and therapy
PURPOSE: To determine whether Gui-Pi-Tang (GPT) has protective effects on skeletal muscle and cardiac muscle in aged mice.

Convolutional Neural Network approach to classify mitochondrial morphologies.

Computational biology and chemistry
The morphology of the mitochondrial network is a major indicator of cellular health and function, with changes often linked to various physiological and pathological conditions. As a result, efficient methods to quickly assess mitochondrial shape in ...

The role and machine learning analysis of mitochondrial autophagy-related gene expression in lung adenocarcinoma.

Frontiers in immunology
OBJECTIVE: Lung adenocarcinoma (LUAD) continues to be a primary cause of cancer-related mortality globally, highlighting the urgent need for novel insights finto its molecular mechanisms. This study aims to investigate the relationship between gene e...

Mitochondrial toxic prediction of marine alga toxins using a predictive model based on feature coupling and ensemble learning algorithms.

Toxicology mechanisms and methods
Alga toxins have recently emerged as environmental risk factors to multiple human health issues. Mitochondrial toxicity is an essential element in the field of ecotoxicology, it is necessary to screen and manage mitochondrial toxicants from common al...

Automated mitochondrial oxygen consumption (mitoVO) analysis via a bi-directional long short-term memory neural network.

Journal of clinical monitoring and computing
Monitoring in vivo mitochondrial oxygen tension (mitoPO) enables the measurement of mitochondrial oxygen consumption (mitoVO), providing deeper insights into the skin's mitochondrial environment. However, current mitoVO analysis often relies on manua...

Ultrastructural Morphometry of Mitochondria: Comparison Between Conventional Operator-Dependent and Artificial Intelligence (AI)-Operated Machine Learning Methods.

Microscopy research and technique
Morphometric analysis of digital images is fundamental to substantiate the visual observations with objective quantitative data suitable for statistical analysis. The recent advances in artificial intelligence (AI) have allowed the development of mac...