Effect of (poly)phenol-rich ‘Daux Belan’ apple supplementation on diet-induced obesity and glucose intolerance in C57BL/6NCrl mice
Bibliographic record
Abstract
Obesity is a state of metabolic dysfunction that can lead to dyslipidemia and impaired glucose homeostasis. Apple polyphenols have been shown to ameliorate dyslipidemia/metabolic dysfunction in humans. The influence of apple (poly)phenols on energy metabolism in high-fat (HF) diet-induced obese mice remains controversial. This study examined the effect of dietary supplementation of (poly)phenol-rich 'Daux Belan' apple (DB; 6.2 mg gallic acid equivalence (GAE)/mouse/day; 0.15% (poly)phenol) in the form of freeze-dried powder on glucose and lipid metabolism in male HF-fed C57BL/6NCrl mice, in comparison to low-(poly)phenol-containing 'Zestar' apple (Z; 0.4 mg GAE/mouse/day). Obesity, glucose intolerance, hypertriglyceridemia, and hepatic lipid vacuolation were induced by HF feeding while circulating cholesterol levels remained unchanged. DB apple supplementation did not protect against HF-induced body weight gain, hyperglycemia, hepatic triglyceride level elevation, and hepatic lipid vacuolation at the tested dosage. Future studies should be conducted with increased DB dosage and employ apple (poly)phenols supplemented in the form of extracts or sugar-free powder.
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 | 0.000 | 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".