Activation of endothelial Ca2+‐activated potassium channels can improve endothelial function in basilar arteries from diabetic rats
Bibliographic record
Abstract
Endothelium‐dependent relaxation of isolated rat basilar artery to acetylcholine (ACh) can be fully accounted for by the release of endothelium‐derived NO. In addition, activation of endothelial Ca 2+ ‐activated potassium channels (K Ca ) plays a key role in modulating ACh‐stimulated production of endothelium‐derived nitric oxide (NO) in this artery. Thus, we have investigated whether activation of endothelial small (SK Ca ) and intermediate (IK Ca ) K Ca by 1‐ethyl‐2‐benzimidazolinone (1‐EBIO) can improve endothelial function in basilar arteries from diabetic rats. Relaxations to ACh (0.01–30 μM) were significantly depressed in isolated basilar arteries from Streptozotocin‐treated (STZ) diabetic rats compared to vessels from control animals. In contrast, relaxation of basilar arteries evoked by 1‐EBIO (1–300 μM), was not significantly different in arteries from STZ and control rats. Application of low concentrations of 1‐EBIO (1–5 μM) significantly enhanced ACh‐evoked relaxations in basilar arteries from STZ‐treated rats. Pre‐incubation with L‐NAME abolished relaxations to ACh both in the presence and absence of 1‐EBIO indicating that the enhancement of ACh‐evoked responses was due to increased production of NO. Quantitative real‐time PCR analysis demonstrated that mRNA levels for both SK Ca and IK Ca were not significantly different in basilar arteries from control and STZ‐treated rats. It is concluded that activation of K Ca may significantly improve endothelial function in basilar arteries from STZ‐treated diabetic rats. Supported by CIHR.
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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) | 0.001 | 0.001 |
| 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 | 0.001 | 0.002 |
| 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".