Decrease IL33 expression in cardiac fibroblasts with high concentration of glucose leads to collagen IV production: role of PKCβ
Bibliographic record
Abstract
Diabetic cardiomyopathy (DiCM) is one of major complications of diabetes mellitus. Increase in collagen production by cardiac fibroblasts has been implicated in the development of the DiCM. In the present study, we assessed the role of PKCβ/IL‐33 pathway in the high glucose (HG)‐induced collagen production in cardiac fibroblasts. Methods Cultures cardiac fibroblasts were exposed to medium containing high concentration of glucose. The PKCβ phosphorylation status, IL33 and collagen production were assessed with Western or real‐time RT‐PCR. Results Treatment of the cardiac fibroblasts with HG led to a decrease in IL33 mRNA and protein expression which was associated with an increase in collagen IV production. Administration of IL‐33 prevented HG‐induced collagen IV production. Expose of cardiac fibroblasts to HG resulted in PKCβ;activation as indicated by increase in phosphorylation of PKCβ;Furthermore, inhibition of PKCβ;with an inhibitor prevented the increase in collagen IV production in HG‐treated cardiac fibroblasts. Conclusion Our results suggest that PKCβ/IL33 pathway plays an important role in regulation of HG‐induced collagen IV production in cardiac fibroblasts. (CIHR MOP‐81303)
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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) | 0.002 | 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".