Acute Kidney Injury Induces Oxidative Stress and Hepatic Lipid Accumulation through AMPK Signaling Pathway
Bibliographic record
Abstract
Acute kidney injury (AKI) often impairs the function of other organs leading to distant organ injury. The liver is the major organ that regulates metabolism and lipid homeostasis in the body. It has been reported that AKI causes liver injury with increased oxidative stress, inflammatory response and steatosis. In the present study, we investigated the mechanisms by which ischemia-reperfusion-induced AKI caused hepatic lipid accumulation. Kidney ischemia (45 min)-reperfusion (24 h) led to a significant increase in plasma creatinine and transaminase in Sprague Dawley rats, indicating kidney and liver injury. Histological and biochemical analyses revealed hepatic lipid accumulation with a significant elevation of triglyceride and cholesterol levels in the liver. This was accompanied by a decreased AMP-activated protein kinase (AMPK) phosphorylation, indicating the reduced activation of AMPK, which is an energy sensor that regulates lipid metabolism. The expression of AMPK-regulated genes that were responsible for fatty acid oxidation (CPTIα, ACOX) was significantly decreased, while the expression of lipogenesis genes (SREPB-1c, ACC1) was significantly elevated. The oxidative stress biomarker malondialdehyde was elevated in the plasma and liver. Incubation of HepG2 cells with an oxidative stress inducer hydrogen peroxide inhibited AMPK phosphorylation and caused cellular lipid accumulation. This was accompanied by decreased expression of genes responsible for fatty acid oxidation and increased expression of genes responsible for lipogenesis. These results suggest that AKI elicits hepatic lipid accumulation through decreased fatty acid metabolism and increased lipogenesis. Oxidative stress may contribute, in part, to the downregulation of the AMPK signaling pathway leading to hepatic lipid accumulation and injury.
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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 | 0.000 | 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".