The effect of high-dose sodium salicylate on chronically elevated plasma nonesterified fatty acid-induced insulin resistance and β-cell dysfunction in overweight and obese nondiabetic men
Bibliographic record
Abstract
Prolonged elevation of plasma nonesterified fatty acids (NEFA) induces insulin resistance and impairs pancreatic β-cell adaptation to insulin resistance. Studies in rodents suggest that inflammation may play a role in this "lipotoxicity." We studied the effects of sodium salicylate, an anti-inflammatory agent, on lipid-induced alterations in β-cell function and insulin sensitivity in six overweight and obese nondiabetic men. Each subject underwent four separate studies, 4-6 wk apart, in random order: 1) SAL, 1-wk placebo followed by intravenous (iv) infusion of saline for 48 h; 2) IH, 1-wk placebo followed by iv infusion of intralipid plus heparin for 48 h to raise plasma NEFA approximately twofold; 3) IH + SS, 1-wk sodium salicylate (4.5 g/day) followed by 48-h IH infusion; and 4) SS, 1-wk oral sodium salicylate followed by 48-h saline infusion. After 48-h saline or lipid infusion, insulin secretion and sensitivity were assessed by hyperglycemic clamp and euglycemic hyperinsulinemic clamp, respectively, in sequential order. Insulin sensitivity was reduced by lipid infusion (IH = 67% of SAL) and was not improved by salicylate (IH + SS = 56% of SAL). Lipid infusion also reduced the disposition index (P < 0.05), which was not prevented by sodium salicylate. Salicylate reduced insulin clearance. These data suggest that oral sodium salicylate at this dose impairs insulin clearance but does not ameliorate lipid-induced insulin resistance and β-cell dysfunction in overweight and obese nondiabetic men.
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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 | 0.001 |
| 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".