Comparative analysis of expression profiles of chemokines, chemokine receptors, and components of signaling pathways mediated by chemokines in eight cell types during rat liver regeneration
Bibliographic record
Abstract
It has been documented that chemokines can positively regulate liver regeneration at the tissue level after partial hepatectomy. However, the precise mechanism of the effects of chemokines on regeneration at the cellular level remains poorly defined. In this study, 8 cell types from rat regenerating liver at 8 recovery time points after 2/3 hepatectomy were isolated and purified using Percoll density gradient centrifugation and immunomagnetic bead methods. The expression profiles of each cell type were monitored using a microarray. RT-PCR analysis was performed to validate the reliability of the microarray results. The results showed that, on the whole, the expression profiles of chemokine and receptor genes varied among different cell types; most genes involved in chemokine signaling pathways showed an increase in expression across the 8 liver cell types during liver regeneration. The implication of these genes in regeneration was analyzed by bioinformatics and systems biology methods. According to the microarray results and gene synergy, activation of chemokine signaling pathways at 24 h in biliary epithelial cells and at 2-12 h in dendritic cells may be triggered by CCL2-CCR2 and CCL7-CCR3, respectively; activation of Plc/Pkc and Pi3k/Akt pathways at 2-12 h in sinusoidal endothelial cells might be caused by CCL7-CCR1; and activation of the Src/Ptk, Src/Vav, and Plc/Pkc pathways at the priming stage may be related to the inductive effect of CCL7. These data suggest the potential relevance of the pro-inflammatory chemokines for liver regeneration at the cellular level.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".