Metabolic Syndrome as a Multifaceted Risk Factor for Oxidative Stress
Bibliographic record
Abstract
SIGNIFICANCE: Metabolic syndrome (MetS) is associated with a greater risk of diabetes and cardiovascular diseases. It is estimated that this multifactorial condition affects 20%-30% of the world's population. A detailed understanding of MetS mechanisms is crucial for the development of effective prevention strategies and adequate intervention tools that could curb its increasing prevalence and limit its comorbidities, particularly in younger age groups. With advances in basic redox biology, oxidative stress (OxS) involvement in the complex pathophysiology of MetS has become widely accepted. Nevertheless, its clear association with and causative effects on MetS require further elucidation. Recent Advances: Although a better understanding of the causes, risks, and effects of MetS is essential, studies suggest that oxidant/antioxidant imbalance is a key contributor to this condition. OxS is now understood to be a major underlying mechanism for mitochondrial dysfunction, ectopic lipid accumulation, and gut microbiota impairment. CRITICAL ISSUES: Further studies, particularly in the field of translational research, are clearly required to understand and control the production of reactive oxygen species (ROS) levels, especially in the mitochondria, since the various therapeutic trials conducted to date have not targeted this major ROS-generating system, aimed to delay MetS onset, or prevent its progression. FUTURE DIRECTIONS: Multiple relevant markers need to be identified to clarify the role of ROS in the etiology of MetS. Future clinical trials should provide important proof of concept for the effectiveness of antioxidants as useful therapeutic approaches to simultaneously counteract mitochondrial OxS, alleviate MetS symptoms, and prevent complications. Antioxid. Redox Signal. 26, 445-461.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".