Oval Cell Response Is Attenuated by Depletion of Liver Resident Macrophages in the 2-AAF/Partial Hepatectomy Rat
Bibliographic record
Abstract
BACKGROUND/AIMS: Macrophages are known to play an important role in hepatocyte mediated liver regeneration by secreting inflammatory mediators. However, there is little information available on the role of resident macrophages in oval cell mediated liver regeneration. In the present study we aimed to investigate the role of macrophages in oval cell expansion induced by 2-acetylaminofluorene/partial hepatectomy (2-AAF/PH) in rats. METHODOLOGY/PRINCIPAL FINDINGS: We depleted macrophages in the liver of 2-AAF/PH treated rats by injecting liposome encapsulated clodronate 48 hours before PH. Regeneration of remnant liver mass, as well as proliferation and differentiation of oval cells were measured. We found that macrophage-depleted rats suffered higher mortality and liver transaminase levels. We also showed that depletion of macrophages yielded a significant decrease of EPCAM and PCK positive oval cells in immunohistochemical stained liver sections 9 days after PH. Meanwhile, oval cell differentiation was also attenuated as a result of macrophage depletion, as large foci of small basophilic hepatocytes were observed by day 9 following hepatectomy in control rats whereas they were almost absent in macrophage depleted rats. Accordingly, real-time polymerase chain reaction analysis showed lower expression of albumin mRNA in macrophage depleted livers. Then we assessed whether macrophage depletion may affect hepatic production of stimulating cytokines for liver regeneration. We showed that macrophage-depletion significantly inhibited hepatic expression of tumor necrosis factor-α and interleukin-6, along with a lack of signal transducer and activator of transcription 3 phosphorylation during the early period following hepatectomy. CONCLUSIONS: These data indicate that macrophages play an important role in oval cell mediated liver regeneration in the 2-AAF/PH model.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".