Exercise training increases hepatic endoplasmic reticulum (er) stress protein expression in MTP‐inhibited high‐fat fed rats
Bibliographic record
Abstract
The purpose of the study was: (1) to determine the effects of microsomal triglyceride transfer protein (MTP) inhibition on endoplasmic reticulum (ER) stress in liver, and (2) to determine if this response is altered in exercise-trained rats. Female Sprague-Dawley rats (6 weeks) fed either a standard (SD) or a high-saturated fat (HF; 43% as energy) diet were trained (Tr) or kept sedentary (Sed) for 6 week. Exercise training consisted of continuous running on a motor-driven rodent treadmill 5 times/week. Ten days before the end of these interventions, rats were administrated (ip) daily a MTP inhibitor (MTPX) or a placebo (P). MTPX injection resulted in a large (p < 0.01) liver triacylglycerol (TAG) accumulation in SD and HF-fed rats (approximately 200 mg g(-1)), irrespective of the training status, while plasma TAG levels were largely (approximately 80%) decreased (p < 0.01). MTPX injection in HF but not in SD-fed animals resulted in an increase in BiP/GRP78, ATF6, PERK, and XBP-1 mRNA levels, (p < 0.01) indicating an increase in the unfolding protein response (UPR) to ER stress. Interestingly, exercise training in rats fed the HF diet resulted in a further increase in BiP/GRP78 and XBP-1 mRNA levels in MTPX animals (p < 0.01). It is concluded that: (1) ER stress induced by MTPX occurs only in HF-fed rats despite the fact that liver TAG levels were largely increased in both dietary models; (2) the increase in gene expression of UPR markers with training may constitute a protective mechanism against ER stress in liver.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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) | 0.002 | 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".