Lipolysis, lipogenesis, and adiposity are reduced while fatty acid oxidation is increased in visceral and subcutaneous adipocytes of endurance-trained rats
Bibliographic record
Abstract
This study examined the alterations in triglyceride (TG) breakdown and storage in subcutaneous inguinal (SC Ing) and epididymal (Epid) fat depots following chronic endurance training. Male Wistar rats were either kept sedentary (Sed) or subjected to endurance training (Ex) at 70-85% peak VO2 for 6 weeks. At weeks 0, 3, and 6 blood was collected at rest and immediately after a bout of submaximal exercise of similar relative intensity to assess whole-body lipolysis. At week 6, adipocytes were isolated from Epid and SC Ing fat pads for the determination of lipolysis under basal or isoproterenol- and forskolin-stimulated conditions, basal and insulin-stimulated glucose incorporation into lipids, and fatty acid oxidation (FAO). Body weight, fat pad mass, and insulin were reduced by endurance training. Also, circulating non-esterified fatty acids (NEFAs) were 33% lower in Ex than Sed rats when exercising at the same relative intensity. This coincided with reduced isoproterenol-stimulated lipolysis in the Epid (27%) and SC Ing (25%) adipocytes in Ex rats. Similarly, forskolin-stimulated lipolysis was reduced in Epid (51%) and SC Ing (49%) adipocytes from Ex rats. Insulin-stimulated glucose incorporation into lipids in adipocytes from both fat depots from Ex rats was also lower (∼43%) than Sed controls. Conversely, FAO was increased in Epid (1.71-fold) and SC Ing (1.82-fold) adipocytes of Ex rats. In conclusion, chronic endurance exercise reduced lipolysis and lipogenesis while increasing FAO in Epid and SC Ing adipocytes. These are compatible with an energy-sparing adaptive response to reduced adiposity under chronic endurance training conditions.
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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) | 0.001 | 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) | 0.002 | 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".