Effects of Metformin on Burn-Induced Hepatic Endoplasmic Reticulum Stress in Male Rats
Bibliographic record
Abstract
Severe burn injury causes hepatic dysfunction that results in major metabolic derangements including insulin resistance and hyperglycemia and is associated with hepatic endoplasmic reticulum (ER) stress. We have recently shown that insulin reduces ER stress and improves liver function and morphology; however, it is not clear whether these changes are directly insulin mediated or are due to glucose alterations. Metformin is an antidiabetic agent that decreases hyperglycemia by different pathways than insulin; therefore, we asked whether metformin affects postburn ER stress and hepatic metabolism. The aim of the present study is to determine the effects of metformin on postburn hepatic ER stress and metabolic markers. Male rats were randomized to sham, burn injury and burn injury plus metformin and were sacrificed at various time points. Outcomes measured were hepatic damage, function, metabolism and ER stress. Burn-induced decrease in albumin mRNA and increase in alanine transaminase (p < 0.01 versus sham) were not normalized by metformin treatment. In addition, ER stress markers were similarly increased in burn injury with or without metformin compared with sham (p < 0.05). We also found that gluconeogenesis and fatty acid metabolism gene expressions were upregulated with or without metformin compared with sham (p < 0.05). Our results indicate that, whereas thermal injury results in hepatic ER stress, metformin does not ameliorate postburn stress responses by correcting hepatic ER stress.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".