High-Fat High-Sucrose Diet Leads to Dynamic Structural and Inflammatory Alterations in the Rat Vastus Lateralis Muscle
Bibliographic record
Abstract
The influence of obesity on muscle integrity is not well understood. The purpose of this study 37 was to quantify structural and molecular changes in the rat vastus lateralis (VL) muscle as a 38 function of a 12-week obesity induction period and a subsequent adaptation period (additional 39 16-weeks). Male Sprague-Dawley rats consumed a high-fat, high-sucrose (DIO, n=40) diet or a 40 chow control-diet (n=14). At 12-weeks, DIO rats were grouped as prone (DIO-P, top 33% of 41 weight change) or resistant (DIO-R, bottom 33%). Animals were euthanized at 12-weeks or 28-42 weeks on the diet. At sacrifice, body composition was determined and VL muscles were 43 collected. Intramuscular fat, fibrosis, and CD68+ cells were quantified histologically and 44 relevant molecular markers were evaluated using RT-qPCR. At 12- and 28-weeks post obesity 45 induction, DIO-P rats had more mass and body fat than DIO-R and chow rats (p<0.05). DIO-P 46 and DIO-R rats had similar losses in muscle mass, which were greater than those in chow rats 47 (p<0.05). mRNA levels for MAFbx/atrogin1 were reduced in DIO-P and DIO-R rats at 12- and 48 28-weeks compared to chow rats (p<0.05), while expression of MURF was similar to chow 49 values. DIO-P rats demonstrated increased mRNA levels for pro-inflammatory mediators, 50 inflammatory cells, and fibrosis compared to DIO-R and chow animals, despite having similar 51 levels of intramuscular fat. The down-regulation of MAFbx/atrogin1 may suggest onset of 52 degenerative changes in VL muscle integrity of obese rats. DIO-R animals exhibited fewer 53 inflammatory changes compared to DIO-P animals, suggesting a protective effect of obesity 54 resistance on local inflammation.
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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".