AIMC Topic: Metabolome
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The inconsistent pathogenesis of endometriosis and adenomyosis: insights from endometrial metabolome and microbiome.
mSystems
Apr 22, 2025
UNLABELLED: Endometriosis (EM) and adenomyosis (AM) are interrelated gynecological disorders characterized by the aberrant presence of endometrial tissue and are frequently linked with chronic pelvic pain and infertility, yet their pathogenetic mecha...
Machine learning-guided Orbitrap-HRAMS-based metabolomic fingerprinting for geographical origin, variety and tissue specific authentication, and adulteration detection of turmeric and ashwagandha.
Food chemistry
Mar 28, 2025
The increasing global demand for herbs and spices in food and nutraceutical industries highlights their key functional benefits, including antioxidant and anti-inflammatory properties. Ensuring authenticity and traceability is essential to counteract...
AI-driven framework to map the brain metabolome in three dimensions.
Nature metabolism
Mar 18, 2025
High-resolution spatial imaging is transforming our understanding of foundational biology. Spatial metabolomics is an emerging field that enables the dissection of the complex metabolic landscape and heterogeneity from a thin tissue section. Currentl...
Bootstrap inference and machine learning reveal core differential plasma metabolic connectome signatures in major depressive disorder.
Journal of affective disorders
Mar 3, 2025
BACKGROUND: Major depressive disorder (MDD) involves molecular alterations and pathway dysregulation. Metabolic interconnections are crucial for normal functioning, yet current analysis focuses on individual pathways or biomarkers, overlooking intric...
Identification of metabolite-disease associations based on knowledge graph.
Metabolomics : Official journal of the Metabolomic Society
Feb 22, 2025
BACKGROUND: Despite the insights that metabolite analysis can provide into the onset, development, and progression of diseases-thus offering new concepts and methodologies for prevention, diagnosis, and treatment-traditional wet lab experiments are o...
A metabolic fingerprint of ovarian cancer: a novel diagnostic strategy employing plasma EV-based metabolomics and machine learning algorithms.
Journal of ovarian research
Feb 12, 2025
Ovarian cancer (OC) is the third most common malignant tumor of women and is accompanied by an alteration of systemic metabolism. A liquid biopsy that captures and detects tumor-related biomarkers in body fluids has great potential for OC diagnosis. ...
Rapid metabolic profiling and authentication of Cordyceps using ambient ionization mass spectrometry and machine learning.
Analytical and bioanalytical chemistry
Feb 11, 2025
Cordyceps sinensis, a symbiotic organism formed between a fungus and an insect, is celebrated for its substantial medicinal benefits and economic significance in traditional Chinese medicine. However, the market for Cordyceps sinensis is rife with co...
Precision fetal cardiology detects cyanotic congenital heart disease using maternal saliva metabolome and artificial intelligence.
Scientific reports
Jan 15, 2025
Prenatal sonographic diagnosis of congenital heart disease (CHD) can lead to improved morbidity and mortality. However, the diagnostic accuracy of ultrasound, the sole prenatal screening tool, remains limited. Failed prenatal or early newborn detecti...
Metabolomic age (MileAge) predicts health and life span: A comparison of multiple machine learning algorithms.
Science advances
Dec 18, 2024
Biological aging clocks produce age estimates that can track with age-related health outcomes. This study aimed to benchmark machine learning algorithms, including regularized regression, kernel-based methods, and ensembles, for developing metabolomi...
Mapping Thrombosis Serum Markers by H-NMR Allied with Machine Learning Tools.
Molecules (Basel, Switzerland)
Dec 13, 2024
Machine learning and artificial intelligence tools were used to investigate the discriminatory potential of blood serum metabolites for thromboembolism and antiphospholipid syndrome (APS). H-NMR-based metabonomics data of the serum samples of patient...
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