AIMC Topic: Mitochondria

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Predicting depression severity using machine learning models: Insights from mitochondrial peptides and clinical factors.

PloS one Jan 1, 2025
Depression presents a significant challenge to global mental health, often intertwined with factors including oxidative stress. Although the precise relationship with mitochondrial pathways remains elusive, recent advances in machine learning present...
Adult Male Middle Aged Biomarkers Female Depression Oxidative Stress Mitochondria Peptides Depressive Disorder, Major Severity of Illness Index Humans Machine Learning Algorithms
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Bayesian-optimized deep learning for identifying essential genes of mitophagy and fostering therapies to combat drug resistance in human cancers.

Journal of cellular and molecular medicine Jan 1, 2025
Dysregulated mitophagy is essential for mitochondrial quality control within human cancers. However, identifying hub genes regulating mitophagy and developing mitophagy-based treatments to combat drug resistance remains challenging. Herein, BayeDEM (...
Bayes Theorem Cisplatin Mitochondria Osteosarcoma Genes, Essential Drug Resistance, Neoplasm Mitophagy Humans Neoplasms Deep Learning Cell Line, Tumor Gene Expression Regulation, Neoplastic Apoptosis
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Immunoinfiltration Analysis of Mitochondrial Damage-Related Genes in Lung Adenocarcinoma and Construction of a Classification and Prognostic Model Integrated With WGCNA and Machine Learning Algorithms.

Cancer medicine Jan 1, 2025
BACKGROUND: Lung adenocarcinoma (LUAD) exhibits molecular heterogeneity, with mitochondrial damage affecting progression. The relationship between mitochondrial damage and immune infiltration, and Weighted Gene Co-expression Network Analysis (WGCNA)-...
Machine Learning Prognosis Biomarkers, Tumor Humans Databases, Genetic Lung Neoplasms Gene Expression Profiling Mitochondria Computational Biology Gene Regulatory Networks Adenocarcinoma of Lung Gene Expression Regulation, Neoplastic
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AI-recognized mitochondrial phenotype enables identification of drug targets.

Nature computational science Aug 1, 2024
Phenotype Drug Discovery Mitochondria Humans Artificial Intelligence
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[An artificial neural network diagnostic model for scleroderma and immune cell infiltration analysis based on mitochondria-associated genes].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University May 20, 2024
OBJECTIVE: To establish a diagnostic model for scleroderma by combining machine learning and artificial neural network based on mitochondria-related genes.
Humans Neural Networks, Computer ROC Curve Mice Disease Models, Animal Machine Learning Biomarkers Computational Biology Mitochondria Algorithms Animals Scleroderma, Systemic Gene Expression Profiling
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Deep-learning based flat-fielding quantitative phase contrast microscopy.

Optics express Mar 25, 2024
Quantitative phase contrast microscopy (QPCM) can realize high-quality imaging of sub-organelles inside live cells without fluorescence labeling, yet it requires at least three phase-shifted intensity images. Herein, we combine a novel convolutional ...
Mice Mitochondria Lipid Droplets Quantitative Phase Imaging Animals Deep Learning
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Instance segmentation of mitochondria in electron microscopy images with a generalist deep learning model trained on a diverse dataset.

Cell systems Jan 18, 2023
Mitochondria are extremely pleomorphic organelles. Automatically annotating each one accurately and precisely in any 2D or volume electron microscopy (EM) image is an unsolved computational challenge. Current deep learning-based approaches train mode...
Mitochondria Microscopy, Electron Volume Electron Microscopy Deep Learning
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Evaluation of Image Classification for Quantifying Mitochondrial Morphology Using Deep Learning.

Endocrine, metabolic & immune disorders drug targets Jan 1, 2023
BACKGROUND: Mitochondrial morphology reversibly changes between fission and fusion. As these changes (mitochondrial dynamics) reflect the cellular condition, they are one of the simplest indicators of cell state and predictors of cell fate. However, ...
Mitochondria Deep Learning Cell Line
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Fear memory-associated synaptic and mitochondrial changes revealed by deep learning-based processing of electron microscopy data.

Cell reports Aug 2, 2022
Serial section electron microscopy (ssEM) can provide comprehensive 3D ultrastructural information of the brain with exceptional computational cost. Targeted reconstruction of subcellular structures from ssEM datasets is less computationally demandin...
Neuronal Plasticity Animals Mitochondria Deep Learning Microscopy, Electron Mice Synapses Fear
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High-Throughput Image Analysis of Lipid-Droplet-Bound Mitochondria.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2021
Changes to mitochondrial architecture are associated with various adaptive and pathogenic processes. However, quantification of changes to mitochondrial structures is limited by the yet unmet challenge of defining the borders of each individual mitoc...
High-Throughput Screening Assays Algorithms Lipid Droplets Humans Optical Imaging Image Processing, Computer-Assisted Adipocytes, Brown Machine Learning Mitochondria
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