The Metabolic Adaptation to Exercise Following Intensity-Specific Aerobic Training in Female Rats
Bibliographic record
Abstract
INTRODUCTION: Limited research has examined the impact of training intensity on substrate utilization during acute exercise. Despite sex differences in the metabolic response to exercise, few studies have examined females. PURPOSE: This study compared the utilization of substrate during acute exercise following 8 wk of low-intensity (LoT) and high-intensity (HiT) aerobic training (AT) in female rats. It was hypothesized that both training programs would result in increased fat oxidation during acute exercise, with HiT demonstrating a higher shift toward fat oxidation. METHODS: Thirty-six female rodents were divided into four groups: sedentary control (Control), acute exercise only (AC), LoT, and HiT. The LoT and HiT groups performed progressive exercise up to an intensity of 21 and 36 m·min -1 , respectively. After training, the trained and AC groups performed an acute bout of 60-min exercise (30 m·min -1 ) and were sacrificed 30 min later. RESULTS: Levels of epinephrine and protein kinase A activity were significantly higher ( P < 0.05) in both the trained and control groups. Both LoT and HiT exhibited higher muscle glycogen content in comparison to AC ( P < 0.05), suggesting muscle glycogen sparing in the trained animals. Moreover, hepatic glycogen in the HiT animals was significantly higher than LoT, suggesting that hepatic glycogenolysis was reduced. An increase in HSL activation in the HiT indicates a shift toward fat utilization during exercise and a directed role of protein kinase A to a preferable activation and utilization of fat. CONCLUSIONS: These findings increase our understanding of various metabolic adaptations in response to different AT intensities in females.
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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 | 0.000 | 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 | 0.000 |
| 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".