Integration of metabolomics methodologies for the development of predictive models for mortality risk in elderly patients with severe COVID-19

BMC Infectious Diseases, Journal Year: 2025, Volume and Issue: 25(1)

Published: Jan. 2, 2025

The rapid evolution of the COVID-19 pandemic and subsequent global immunization efforts have rendered early metabolomics studies potentially outdated, as they primarily involved non-exposed, non-vaccinated populations. This paper presents a predictive model developed from up-to-date data integrated with clinical to estimate mortality risk in critically ill patients. Our study addresses critical gap current research by utilizing patient samples, providing fresh insights into pathophysiology disease partially immunized population. One hundred elderly patients severe infection, including 46 survivors 54 non-survivors, were recruited January-February 2023 at Second Hospital affiliated Harbin Medical University. A within 24 h admission was using blood data. Differential metabolite analysis other techniques used identify relevant characteristics. Model performance assessed comparing area under receiver operating characteristic curve (AUROC). final prediction externally validated cohort 50 First University during same period. Significant disparities laboratory parameters noted between individuals who survived those did not. indicator, Itaconic acid, four tests (LYM, IL-6, PCT, CRP), identified five variables all models. external validation set demonstrated that KNN exhibited highest AUC 0.952 among When considering 50% threshold, displayed sensitivity 0.963 specificity 0.957. prognostic outcome is significantly influenced levels LYM, CRP upon admission. These indicators can be utilized assess affected individuals.

Language: Английский

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Integral-Omics: Serial Extraction and Profiling of Metabolome, Lipidome, Genome, Transcriptome, Whole Proteome and Phosphoproteome Using Biopsy Tissue

Analytical Chemistry, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 7, 2025

The integrative multiomics characterization of minute amounts clinical tissue specimens has become increasingly important. Here, we present an approach called Integral-Omics, which enables sequential extraction metabolites, lipids, genomic DNA, total RNA, proteins, and phosphopeptides from a single biopsy-level specimen. We benchmarked this method with various samples, applied the workflow to perform profiling tissues six patients colorectal cancer, found that tumor exhibited suppressed ferroptosis pathways at levels. Together, study presents methodology metabolomics, lipidomics, genomics, transcriptomics, proteomics, phosphoproteomics using biopsy specimens.

Language: Английский

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High-speed centrifugation reduces immune rejection by removing bone marrow elements from fresh osteochondral allografts

Journal of Orthopaedic Translation, Journal Year: 2025, Volume and Issue: 51, P. 37 - 50

Published: Jan. 22, 2025

Language: Английский

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Bifidobacterium animalis BD400 protects from collagen-induced arthritis through histidine metabolism

Frontiers in Immunology, Journal Year: 2025, Volume and Issue: 16

Published: Jan. 22, 2025

Background Rheumatoid arthritis (RA) is a common chronic and systemic autoimmune disease. Numerous clinical studies have indicated correlation between alterations in gut microbiota the onset progression of RA. This research aims to restore intestinal healthy state through oral administration Bifidobacterium early stages with goal delaying Methods Collagen-induced (CIA) rat model was constructed assess development RA using scores, paw thickness, pathological analysis knee joint. The immune response evaluated by determinating specific antibodies cytokines serum synovial fluid. expression barrier protein analyzed qPCR evaluate function. Alterations metabolites were assessed 16S rDNA non-targeted metabolomics. Results findings reveal that administering animalis BD400 orally led significant reduction scores swelling thickness CIA rats. Additionally, there decrease osteo-facial fusion calcified cartilage thickening Furthermore, B. resulted down-regulation inflammatory factors TNF-α collagenase MMP-13 Levels (anti-CII IgG, anti-CII IgG1, IgG2a) cytokine IL-17A serum, as well (TNF-α IL-1β) fluid BD400-treated rats, significantly reduced ( p < 0.05). gene levels proteins (occludin-1, MUC-2, ZO-1) showed increase 0.05) altered composition microorganisms rats at phylum genus levels, particularly affecting HT002. alleviates down-regulating 1-methyl-L-histidine urocanate histidine metabolism, laying foundation for prevention. Conclusion By HT002 metabolism restored permeability, inhibited response, ultimately slowed down

Language: Английский

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Transcriptome and metabolome analysis reveals response mechanisms and biomarkers of pink Auricularia cornea on baijiu lees substrate

Industrial Crops and Products, Journal Year: 2025, Volume and Issue: 226, P. 120683 - 120683

Published: Feb. 21, 2025

Language: Английский

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Toward an integrated omics approach for plant biosynthetic pathway discovery in the age of AI

Trends in Biochemical Sciences, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 1, 2025

Language: Английский

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Advances in AI-based strategies and tools to facilitate natural product and drug development

Critical Reviews in Biotechnology, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 32

Published: March 30, 2025

Natural products and their derivatives have been important for treating diseases in humans, animals, plants. However, discovering new structures from natural sources is still challenging. In recent years, artificial intelligence (AI) has greatly aided the discovery development of drugs. AI facilitates to: connect genetic data to chemical or vice-versa, repurpose known products, predict metabolic pathways, design optimize metabolites biosynthesis. More recently, emergence improvement neural networks such as deep learning ensemble automated web based bioinformatics platforms sped up process. Meanwhile, also improves identification structure elucidation unknown compounds raw like mass spectrometry nuclear magnetic resonance. This article reviews these AI-driven methods tools, highlighting practical applications guide efficient product drug development.

Language: Английский

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A mass spectrum-oriented computational method for ion mobility-resolved untargeted metabolomics

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: March 31, 2023

Abstract Ion mobility (IM) adds a new dimension to liquid chromatography-mass spectrometry-based untargeted metabolomics which significantly enhances coverage, sensitivity, and resolving power for analyzing the metabolome, particularly metabolite isomers. However, high dimensionality of IM-resolved data presents great challenge processing, restricting its widespread applications. Here, we develop mass spectrum-oriented bottom-up assembly algorithm that utilizes spectra assemble four-dimensional peaks in reverse order multidimensional separation. We further end-to-end computational framework Met4DX peak detection, quantification identification metabolites metabolomics. Benchmarking validation demonstrates superior performance compared existing tools with regard fidelity precision. Importantly, successfully detects differentiates co-eluted isomers small differences chromatographic IM dimensions. Together, advances discovery biological organisms by deciphering complex 4D data.

Language: Английский

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Analytical opportunities and challenges for data handling with chemometrics strategies from LC-MS based food metabolomics

Trends in Food Science & Technology, Journal Year: 2023, Volume and Issue: 143, P. 104298 - 104298

Published: Dec. 17, 2023

Language: Английский

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Identifying plasma metabolic characteristics of major depressive disorder, bipolar disorder, and schizophrenia in adolescents

Translational Psychiatry, Journal Year: 2024, Volume and Issue: 14(1)

Published: March 26, 2024

Abstract Major depressive disorder (MDD), bipolar (BD), and schizophrenia (SCZ) are classified as major mental disorders together account for the second-highest global disease burden, half of these patients experience symptom onset in adolescence. Several studies have reported both similar unique features regarding risk factors clinical symptoms three disorders. However, it is still unclear whether or metabolic characteristics adolescents. We conducted a metabolomics analysis plasma samples from adolescent healthy controls (HCs) with MDD, BD, SCZ. identified differentially expressed metabolites between HCs. Based on metabolites, correlation analysis, pathway potential diagnostic biomarker identification were Our results showed significant changes metabolism HCs; most distinct observed SCZ patients. Moreover, differences BD shared those MDD SCZ, although profile was closer to that than Additionally, we responsible multiple pathways. The among found fatty acid, steroid-hormone, purine, nicotinate, glutamate, tryptophan, arginine, proline metabolism. Interestingly, significantly altered glycolysis, glycerophospholipid, sphingolipid SCZ; lysine, cysteine, methionine BD; phenylalanine, tyrosine, aspartate BD. Finally, five panels biomarkers MDD-HC, BD-HC, SCZ-HC, MDD-SCZ, BD-SCZ comparisons. findings suggest vary across psychiatric critical provide new clues molecular mechanisms

Language: Английский

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