Differential Metabolomics for Quantitative Assessment of Oxidative Stress with Strenuous Exercise and Nutritional Intervention: Thiol-Specific Regulation of Cellular Metabolism with <i>N</i>-Acetyl-<scp>l</scp>-Cysteine Pretreatment
Bibliographic record
Abstract
Despite several decades of active research, the success of large-scale clinical trials involving antioxidants remains equivocal given the complex biological interactions of reactive oxygen/nitrogen species in human health. Herein, we outline a differential metabolomics strategy by capillary electrophoresis-electrospray ionization-mass spectrometry (CE-ESI-MS) to assess the efficacy of nutritional intervention to attenuate oxidative stress induced by strenuous exercise. A healthy volunteer was recruited to perform a submaximal prolonged ergometer cycling trial until volitional exhaustion with frequent blood collection over a 6 h time interval, which included pre-, during, and postexercise periods while at rest. A follow-up study was subsequently performed by the same subject after high-dose oral intake of N-acetyl-L-cysteine (NAC) prior to performing the same exercise protocol under standardized conditions. Time-dependent changes in global metabolism of filtered red blood cell lysates by CE-ESI-MS were measured to reveal a significant attenuation of cellular oxidation associated with high-dose oral NAC intake relative to a control. Untargeted metabolite profiling allowed for the identification and quantification of several putative early- and late-stage biomarkers that reflected oxidative stress inhibition due to nutritional intervention, including oxidized glutathione (GSSG), reduced glutathione (GSH), 3-methylhistidine (3-MeHis), L-carnitine (C0), O-acetyl-L-carnitine (C2), and creatine (Cre). Our work demonstrates the proof-of-principle that NAC pretreatment is effective at dampening acute episodes of oxidative stress by reversible perturbations in global metabolism that can provide deeper insight into the mechanisms of thiol-specific protein inhibition relevant to its successful translation as a prophylaxis in clinical medicine.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".