Vitamin D alleviates oxidative stress in adipose tissue and mesenteric vessels from obese patients with subclinical inflammation
Bibliographic record
Abstract
Obesity is an age-independent, lifestyle-triggered, pandemic disease associated with both endothelial and visceral adipose tissue (VAT) dysfunction leading to cardiometabolic complications mediated via increased oxidative stress and persistent chronic inflammation. The purpose of the present study was to assess the oxidative stress in VAT and vascular samples and the effect of in vitro administration of vitamin D. VAT and mesenteric artery branches were harvested during abdominal surgery performed on patients referred for general surgery (n = 30) that were randomized into two subgroups: nonobese and obese. Serum levels of C-reactive protein (CRP) and vitamin D were measured. Tissue samples were treated or not with the active form of vitamin D: 1,25(OH)2D3 (100 nmol/L, 12 h). The main findings are that in obese patients, (i) a low vitamin D status was associated with increased inflammatory markers and reactive oxygen species generation in VAT and vascular samples and (ii) in vitro incubation with vitamin D alleviated oxidative stress in VAT and vascular preparations and also improved the vascular function. We report here that the serum level of vitamin D is inversely correlated with the magnitude of oxidative stress in the adipose tissue. Ex vivo treatment with active vitamin D mitigated obesity-related oxidative stress.
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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 | 0.000 | 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) | 0.001 | 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".