Upregulation of Krebs cycle and anaerobic glycolysis activity early after onset of liver ischemia
Bibliographic record
Abstract
The liver is a highly vascularized organ receiving a dual input of oxygenated blood from the hepatic artery and portal vein. The impact of decreased blood flow on glucose metabolism and how hepatocytes could adapt to this restrictive environment are still unclear. Using the left portal vein ligation (LPVL) rat model, we found that cellular injury was delayed after the onset of liver ischemia. We hypothesized that a metabolic adaptation by hepatocytes to maintain energy homeostasis could account for this lag phase. Liver glucose metabolism was characterized by 13C- and 1H-NMR spectroscopy and analysis of high-energy metabolites. ALT levels and caspase 3 activity in LPVL animals remained normal during the first 12 h following surgery (P<0.05). Ischemia rapidly led to decreased intrahepatic tissue oxygen tension and blood flow (P<0.05) and increased expression of Hypoxia-inducible factor 1-alpha. Intrahepatic glucose uptake, ATP/ADP ratio and energy charge level remained stable for up to 12 h after ligation. Entry of glucose in the Krebs cycle was impaired with lowered incorporation of 13C from [U-13C]glucose into glutamate and succinate from 0.25 to 12 h after LPVL. However, total hepatic succinate and glutamate increased 6 and 12 h after ischemia (P<0.05). Glycolysis was initially reduced (P<0.05) but reached maximum 13C-lactate (P<0.001) and 13C-alanine (P<0.01) enrichments 12 h after LPVL. In conclusion, early liver homeostasis stems from an inherent ability of ischemic hepatocytes to metabolically adapt through increased Krebs cycle and glycolysis activity to preserve bioenergetics and cell viability. This metabolic plasticity of hepatocytes could be harnessed to develop novel metabolic strategies to prevent ischemic liver damage.
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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) | 0.001 | 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) | 0.001 | 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".