Portal vein ligation alters coding and noncoding gene expression in rat livers
Bibliographic record
Abstract
Portal vein occlusion increases the resectability of initially unresectable liver cancer by inducing hypertrophy in non-occluded liver lobes. However, the mechanisms of how portal vein occlusion induces hepatic hypertrophy remain unclear. A cDNA microarray was used to identify the gene expression signatures of ligated (LLLs) and nonligated liver lobes (NLLLs) at different time points after portal vein ligation (PVL). The results of a bioinformatics analysis revealed that LLLs and NLLLs displayed different gene expression profiles. Moreover, the expression levels of both coding and noncoding RNA were different between LLLs and NLLLs at different time points after PVL. A series test of cluster analysis revealed that the No. 22 and No. 5 expression patterns, which showed altered expression at 24 h and maintained this altered expression over the following 14 days, had the lowest P values and the highest number of differentially expressed genes in both the LLLs and NLLLs. The results of a GO analysis showed the activation of hypoxia pathways in LLLs and the activation of cell proliferation and cell-cycle pathways in NLLLs, suggesting the involvement of these pathways in PVL-induced hepatic hypertrophy and regeneration. These results provide insight into the molecular mechanisms underlying hepatic hypertrophy and regeneration induced by portal vein occlusion, and they identify potential targeting pathways that can promote the clinical application of PVL in liver cancer therapy.
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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".