Biomarkers of Oxidative Stress in Metabolic Syndrome and Associated Diseases
Bibliographic record
Abstract
Metabolic syndrome (MS) represents worldwide public health issue characterized by a set of cardiovascular risk factors including obesity, diabetes, dyslipidemia, hypertension, and impaired glucose tolerance. The link between the MS and the associated diseases is represented by oxidative stress (OS) and by the intracellular redox imbalance, both caused by the persistence of chronic inflammatory conditions that characterize MS. The increase in oxidizing species formation in MS has been accepted as a major underlying mechanism for mitochondrial dysfunction, accumulation of protein and lipid oxidation products, and impairment of the antioxidant systems. These oxidative modifications are recognized as relevant OS biomarkers potentially able to (i) clarify the role of reactive oxygen and nitrogen species in the etiology of the MS, (ii) contribute to the diagnosis/evaluation of the disease's severity, and (iii) evaluate the utility of possible therapeutic strategies based on natural antioxidants. The antioxidant therapies indeed could be able to (i) counteract systemic as well as mitochondrial-derived OS, (ii) enhance the endogenous antioxidant defenses, (iii) alleviate MS symptoms, and (iv) prevent the complications linked to MS-derived cardiovascular diseases. The focus of this review is to summarize the current knowledge about the role of OS in the development of metabolic alterations characterizing MS, with particular regard to the occurrence of OS-correlated biomarkers, as well as to the use of therapeutic strategies based on natural antioxidants.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".