Protective roles of hepatic gamma‐aminobutyric acid signaling in acute ethanol exposure‐induced liver injury
Bibliographic record
Abstract
Abstract Alcoholic liver disease (ALD) is a consequence of heavy and prolonged alcohol consumptions. We previously demonstrated a hepatic gamma‐aminobutyric acid (GABA) signaling system that protects the liver from toxic injury. The present study was designed to investigate the role of the hepatic GABA signaling system in the process of acute ethanol exposure‐induced liver injury. Our results showed that the expression of GABA synthesizing enzyme glutamic acid decarboxylase and type A GABA receptor (GABA A R) subunits was upregulated in ethanol‐treated mice compared with saline‐treated controls. Remarkably, pretreatment of mice with GABA (1.5 mg kg −1 body weight, intraperitoneal injection [i.p.]) or with the GABA A R agonist muscimol (1.2 mg kg −1 body weight, i.p.) protected the liver against ethanol toxicity and improved liver function, whereas pretreatment of mice with the GABA A R antagonist bicuculline (2.0 mg kg −1 body weight, i.p.) worsened the liver function. Further analyses suggest that GABA A R‐mediated signaling protects the liver from ethanol injury by, at least partially, inhibiting the IRE1α‐ASK1‐JNK pro‐apoptotic pathway in hepatocytes in the process of ethanol‐induced endoplasmic reticulum stress response.
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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 | 0.000 |
| 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".