Ascorbic acid reduces insulin resistance and pancreatic steatosis by regulating adipocyte hypertrophy in obese ovariectomized mice
Bibliographic record
Abstract
Ascorbic acid has been suggested to regulate obesity in obese male rodents. Moreover, increased adipocyte size has been associated with metabolic disease. Thus, we investigated the effects of ascorbic acid on adipocyte hypertrophy and insulin resistance in high-fat diet (HFD)-induced obese ovariectomized (OVX) C57BL/6J mice, an animal model of obese postmenopausal women. Administration of ascorbic acid (5% w/w in diet for 18 weeks) reduced the size of visceral adipocytes without changes in body weight and adipose tissue mass in HFD-fed obese OVX mice compared with obese OVX mice that did not receive ascorbic acid. Ascorbic acid inhibited adipose tissue inflammation, as shown by the decreased number of crown-like structures and CD68-positive macrophages in visceral adipose tissues. Ascorbic acid-treated mice exhibited improved hyperglycemia, hyperinsulinemia, and glucose and insulin tolerance compared with nontreated obese mice. Pancreatic islet size and insulin-positive β-cell area in ascorbic acid-treated obese OVX mice decreased to the levels observed in low-fat diet-fed lean mice. Ascorbic acid also suppressed pancreatic triglyceride accumulation in obese mice. These results suggest that ascorbic acid may reduce insulin resistance and pancreatic steatosis partly by suppressing visceral adipocyte hypertrophy and adipose tissue inflammation in obese OVX mice.
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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 | 0.001 | 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".