Regulation of adipose tissue lipolysis by ghrelin is impaired with high-fat diet feeding and is not restored with exercise
Bibliographic record
Abstract
Ghrelin is released from the stomach as an anticipatory signal prior to a meal and decreases immediately after. Previous research has shown that both acylated (AG) and unacylated (UnAG) ghrelin blunt adrenoreceptor-stimulated lipolysis in rat white adipose tissue (WAT) ex vivo. We investigated whether acute or chronic consumption of a high fat diet (HFD) impaired the ability of ghrelin to regulate adipose tissue lipolysis, and if this impairment could be restored with exercise. After 5 days (5d) of a HFD, or 6 weeks (6 w) of a HFD (60% kcal from fat) with or without exercise training, inguinal and retroperitoneal WAT was collected from anesthetized rats for adipose tissue organ culture. Samples were treated with 1 μM CL 316,243 (CL; lipolytic control), 1 μM CL+150 ng/ml AG or 1 μM CL+150 ng/ml UnAG. Incubation media and tissue were collected after 2 hours. Colorometric assays were used to determine glycerol and free fatty acid (FFA) concentrations in media. Western blots were used to quantify the protein content of lipolytic enzymes and ghrelin receptors in both depots. CL stimulated lipolysis was evidenced by increases in glycerol (p < 0.0001) and FFA (p < 0.0001) concentrations in media compared to control. AG decreased CL-stimulated glycerol release in inguinal WAT from 5d LFD rats (p = 0.0097). Neither AG nor UnAG blunted lipolysis in adipose tissue from 5d or 6 w HFD-fed rats, and exercise did not restore ghrelin’s anti-lipolytic ability in 6 w HFD-fed rats. Overall, this study demonstrates that HFD consumption impairs ghrelin’s ability to regulate adipose tissue lipolysis.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".