Expression patterns of ClC-3 mRNA and protein in aortic smooth muscle, kidney and brain in diabetic rats
Bibliographic record
Abstract
ClC-3, a member of the ClC family of voltage-gated chloride channels, regulates cell proliferation of cultured rat aortic vascular smooth muscle cells, pathogenesis of allergic rhinitis and tumor cell migration. However, its role in diabetic animals is still unknown. To address this issue, we investigated the expression patterns of ClC-3 in diabetic rats. Five-week-old Sprague-Dawley rats were divided into two groups, 50 non-diabetic control rats (non-DM) and 50 diabetic model rats (DM). ClC-3 mRNA and protein expression in aortic smooth muscle, kidney and brain tissues were examined by fluorimeter-based quantitive RT-PCR assay and Western blot analysis, respectively. ClC-3 mRNA and protein were endogenously expressed in aortic smooth muscle, kidney (cortex and medulla) and brain tissues of both control and streptozotocin-induced diabetic rats. ClC-3 mRNA and protein expression levels were significantly higher in aortic smooth muscle and brain tissues of diabetic rats, but significantly decreased in kidney medulla tissue, relative to non-DM controls. There were no significant differences in ClC-3 mRNA and protein expression in kidney cortex between non-diabetic control and diabetic rats. Furthermore, the altered ClC-3 expression patterns in diabetic rat aortic smooth muscle, brain, and kidney medulla tissues all correlated with the changes in blood glucose levels (p < 0.05). In conclusion, our data show for the first time that diabetes alters both the gene and protein expression of ClC-3 channels. These changes may contribute to the impaired vascular, brain and kidney functions observed in diabetes.
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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 | 0.001 | 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) | 0.001 | 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".