Ethanol and its Nonoxidative Metabolites Promote Acute Liver Injury by Inducing ER Stress, Adipocyte Death, and Lipolysis
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND & AIMS: Binge drinking in patients with metabolic syndrome accelerates the development of alcohol-associated liver disease. However, the underlying mechanisms remain elusive. We investigated if oxidative and nonoxidative alcohol metabolism pathways, diet-induced obesity, and adipose tissues influenced the development of acute liver injury in a single ethanol binge model. METHODS: A single ethanol binge was administered to chow-fed or high-fat diet (HFD)-fed wild-type and genetically modified mice. RESULTS: Oral administration of a single dose of ethanol induced acute liver injury and hepatic endoplasmic reticulum (ER) stress in chow- or HFD-fed mice. Disruption of the Adh1 gene increased blood ethanol concentration and exacerbated acute ethanol-induced ER stress and liver injury in both chow-fed and HFD-fed mice, while disruption of the Aldh2 gene did not affect such hepatic injury despite high blood acetaldehyde levels. Mechanistic studies showed that alcohol, not acetaldehyde, promoted hepatic ER stress, fatty acid synthesis, and increased adipocyte death and lipolysis, contributing to acute liver injury. Increased serum fatty acid ethyl esters (FAEEs), which are formed by an enzyme-mediated esterification of ethanol with fatty acids, were detected in mice after ethanol gavage, with higher levels in Adh1 knockout mice than in wild-type mice. Deletion of the Ces1d gene in mice markedly reduced the acute ethanol-induced increase of blood FAEE levels with a slight but significant reduction of serum aminotransferase levels. CONCLUSIONS: Ethanol and its nonoxidative metabolites, FAEEs, not acetaldehyde, promoted acute alcohol-induced liver injury by inducing ER stress, adipocyte death, and lipolysis.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.000 | 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 it