Abstract 2278: Isoform Specific PKC Responses Modulate ET-1 and Hypoxia Reperfusion Induced Injury
Bibliographic record
Abstract
Background: Hypoxia and reperfusion (H/R) injury is a predominant cause of allograft failure following heart transplantation. Several investigators have shown that endothelin-1 (ET) reduces myocardial function and survival via modulation of protein kinase C (PKC). We examined the role of ET and PKC modulation on human saphenous vein endothelial cells (HSVEC). Methods: HSVEC were submitted to 24 hours of hypoxia (PO 2 <0.1%) and 24 hour of reperfusion (PO 2 =21%). Normoxic controls were incubated at PO 2 =21%. Cells were incubated with either ET:100nM, BOS (ET antagonist):10μM, ET+BOS or PBS during H/R. Cells were also treated with PKCδ, PKCλ and PKCϵ inhibitors. Caspase activity was measured. Free radical (ROS) and NO production were measured. Protein expression and translocation of PKC isoforms and eNOS were assessed using Western Blot analysis. Results: Apoptosis (35% increase in caspase 3,8,9 activity) was observed following H/R compared to normoxia. BOS therapy prevented apoptosis while ET exposure increased caspase activity by 75%, p<0.01. H/R resulted in PKCδ and ϵ translocation while reducing PKCλ activity. BOS exposure prevented H/R induced PKCδ and ϵ activation and PKCλ inhibition while incubation with ET enhanced H/R induced PKC effects. PKCδ and ϵ inhibition reduced caspase activity after H/R and abrogated ET induced apoptosis, p<0.01. PKCλ inhibition enhanced apoptosis. NO production was impaired following H/R, p<0.05. BOS therapy restored NO homeostasis while ET exposure worsened NO production compared to H/R alone, p<0.05. PKCδ and ϵ inhibition improved NO production while PKCλ inhibition worsened NO release. H/R driven ROS production was inhibited by BOS and enhanced by ET exposure, p<0.01. PKCλ inhibition raised ROS production while PKCδ and ϵ inhibition reduced ROS release, p<0.01. eNOS protein expression was reduced by H/R while BOS treatment prevented downregulation. Conclusions: Our findings revealed that ET plays a crucial role in cellular injury following H/R via specific PKC isoforms. ET via PKC modulation leads to endothelial dysfunction and cell death. Therefore, targeted isoform specific PKC modulation as well as BOS may prove to be optimal strategy to prevent endothelial injury during allograft storage and transplantation.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".