Concurrent exercise prevents high-fat-diet-induced macrovesicular hepatic steatosis
Bibliographic record
Abstract
The purpose of the present study was to assess the effect of an exercise training program conducted concurrently with a high-fat (HF)-diet regimen on the induction of hepatic steatosis. Two groups of rats were fed either a standard (SD) or a HF (40% kcal) diet for 8 wk and were additionally assigned either to a sedentary (Sed) or a treadmill-trained (TR) group. Training (5 days/wk) was initiated at the same time as the HF diet and was progressively increased, reaching 60 min at 26 m/min, 10% grade, for the last 4 wk. At the end of the 8-wk period, HF-Sed rats exhibited approximately 72% higher liver triacylglycerol concentration than SD-Sed rats (means +/- SE: 17.15 +/- 1.5 vs. 9.98 +/- 1.0 mg/g; P < 0.01). Histological quantification of lipid infiltration, with the use of an image analysis computing system, revealed that, although fat was mainly stored as microvesicles (<1 microm(2)), the HF-diet-induced hepatic steatosis occurred via the accumulation of macrovesicles (>1 microm(2)). Concurrent exercise training completely prevented the HF-diet-induced hepatic steatosis. The surface area of liver parenchyma infiltrated by lipid vacuoles was similar in HF-TR as in SD-Sed rats (26.4 +/- 1.8 vs. 29.3 +/- 5.9 x 10(3) microm(2)/200,000 microm(2) of liver parenchyma, respectively; P > 0.05). The different states of liver lipid infiltration after the HF diet in Sed and TR rats were associated with similar changes in plasma free fatty acids and glycerol, as well as with similar changes in fat pad weights, but not with plasma triacylglycerol levels. It is concluded that, after a HF-diet regimen of 8 wk in rats, hepatic steatosis occurs primarily via the accumulation of lipid as macrovesicles. Exercise training pursued at the same time completely prevents the HF-diet-induced macrovesicular hepatic steatosis.
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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".