ReviewBiomedical chromatography : BMC2026
Stable Isotope-Resolved Metabolomics in Elucidating Mitochondrial Metabolic Reprogramming and Therapeutic Targets.
Review in Biomedical chromatography : BMC, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
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Authors and funding
7 authors.
Funding
Abstract
Stable isotope-resolved metabolomics (SIRM) has emerged as a pivotal methodology for dissecting mitochondrial metabolic reprogramming and its connection to therapeutic targets. By combining isotopically labeled substrates with metabolic flux analysis (MFA), SIRM enables dynamic, quantitative tracking of carbon flux through mitochondrial pathways. This review focuses on three disease contexts where SIRM has provided transformative insights: cancer, neurodegenerative disorders (Alzheimer's and Parkinson's diseases), and metabolic syndrome (type 2 diabetes and non-alcoholic fatty liver disease). Recent applications have delineated reprogramming signatures, identified metabolic dependencies, and elucidated drug mechanisms. SIRM also facilitates therapeutic monitoring and resistance assessment, offering quantitative biomarkers for patient stratification. We summarize recent advances, technical challenges, AI-powered innovations, and future directions, providing a foundation for optimizing metabolism-targeted therapies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.