AIMC Topic: Cell Death

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Identification of Disulfidptosis-Related Genes in Ischemic Stroke by Combining Single-Cell Sequencing, Machine Learning Algorithms, and In Vitro Experiments.

Neuromolecular medicine Sep 15, 2024
BACKGROUND: Ischemic stroke (IS) is a severe neurological disorder with a pathogenesis that remains incompletely understood. Recently, a novel form of cell death known as disulfidptosis has garnered significant attention in the field of ischemic stro...
Animals Humans Microglia Male Single-Cell Analysis Machine Learning Ischemic Stroke Transcriptome Mice Algorithms Cell Death Nomograms
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Integrated machine learning survival framework to decipher diverse cell death patterns for predicting prognosis in lung adenocarcinoma.

Genes and immunity Aug 31, 2024
Various forms of programmed cell death (PCD) collectively regulate the occurrence, development and metastasis of tumors. Nevertheless, a comprehensive analysis of the diverse types of PCD in lung adenocarcinoma (LUAD) is currently lacking. The study ...
Adenocarcinoma of Lung Machine Learning Prognosis Female Male Lung Neoplasms Cell Death Humans
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Identification of copper death-associated molecular clusters and immunological profiles for lumbar disc herniation based on the machine learning.

Scientific reports Aug 20, 2024
Lumbar disc herniation (LDH) is a common clinical spinal disorder, yet its etiology remains unclear. We aimed to explore the role of cuproptosis-related genes (CRGs) and identify potential diagnostic biomarkers. Our analysis involved interrogating th...
Machine Learning Biomarkers Gene Expression Profiling Humans Lumbar Vertebrae Cell Death Intervertebral Disc Displacement Transcriptome Cluster Analysis Copper
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Machine learning-based biomarker screening for acute myeloid leukemia prognosis and therapy from diverse cell-death patterns.

Scientific reports Aug 2, 2024
Acute myeloid leukemia (AML) exhibits pronounced heterogeneity and chemotherapy resistance. Aberrant programmed cell death (PCD) implicated in AML pathogenesis suggests PCD-related signatures could serve as biomarkers to predict clinical outcomes and...
Leukemia, Myeloid, Acute Male Prognosis Middle Aged Female Transcriptome Biomarkers, Tumor Apoptosis Humans Cell Death Machine Learning
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Identification of potential cell death-related biomarkers for diagnosis and treatment of osteoporosis.

BMC musculoskeletal disorders Mar 25, 2024
BACKGROUND: This study aimed to identify potential biomarkers for the diagnosis and treatment of osteoporosis (OP).
Apoptosis Cell Death Humans Databases, Factual Machine Learning Biomarkers
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Postbiotic Activities of : Impacts on Viability, Structural Integrity, and Cell Death Markers in Human Intestinal C2BBe1 Cells.

Pathogens (Basel, Switzerland) Dec 23, 2023
Acute diarrheal disease (ADD) caused by rotavirus (RV) contributes significantly to morbidity and mortality in children under five years of age. Currently, there are no specific drugs for the treatment of RV infections. Previously, we reported the an...
Tight Junctions Probiotics Bacterial Proteins Apoptosis Rotavirus Infections Humans Rotavirus Cell Line Bifidobacterium adolescentis Intestines Cell Survival Cell Death
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DeXtrusion: automatic recognition of epithelial cell extrusion through machine learning in vivo.

Development (Cambridge, England) Jun 30, 2023
Accurately counting and localising cellular events from movies is an important bottleneck of high-content tissue/embryo live imaging. Here, we propose a new methodology based on deep learning that allows automatic detection of cellular events and the...
Machine Learning Epithelial Cells Microscopy Neural Networks, Computer Cell Death
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An artificial intelligence-based model for cell killing prediction: development, validation and explainability analysis of the ANAKIN model.

Physics in medicine and biology Apr 10, 2023
The present work develops ANAKIN: an. ANAKIN is trained and tested over 513 cell survival experiments with different types of radiation contained in the publicly available PIDE database. We show how ANAKIN accurately predicts several relevant biologi...
Artificial Intelligence Radiobiology Relative Biological Effectiveness Cell Line Cell Death
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Deep Learning to Decipher the Progression and Morphology of Axonal Degeneration.

Cells Sep 25, 2021
Axonal degeneration (AxD) is a pathological hallmark of many neurodegenerative diseases. Deciphering the morphological patterns of AxD will help to understand the underlying mechanisms and develop effective therapies. Here, we evaluated the progressi...
Neurodegenerative Diseases Neurons Cell Death Axons Nerve Degeneration Animals Deep Learning Disease Models, Animal Humans
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Derivation, characterisation and analysis of an adverse outcome pathway network for human hepatotoxicity.

Toxicology Jul 10, 2021
Adverse outcome pathways (AOPs) and their networks are important tools for the development of mechanistically based non-animal testing approaches, such as in vitro and/or in silico assays, to assess toxicity induced by chemicals. In the present study...
Neural Networks, Computer Computer Simulation Risk Assessment Humans Adverse Outcome Pathways Fatty Acids Chemical and Drug Induced Liver Injury Mitochondria, Liver Oxidative Stress Treatment Outcome Cell Death
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