Administration of the KCa channel activator SKA-31 improves long-term endothelial function, blood pressure regulation and cardiac performance in rats with type 2 diabetes
Bibliographic record
Abstract
OBJECTIVE: channel activator SKA-31 would mitigate the development/severity of type 2 diabetes (T2D)-associated cardiovascular (CV) complications in adult male Goto-Kakizaki (GK) rats with spontaneous T2D. METHODS: channel activator SKA-31 (10 mg/kg) at ~14 weeks of age by daily intraperitoneal injection for 12 consecutive weeks. In vivo and ex vivo analyses of CV function, immune system status, vascular signaling and metabolic hormones were performed following treatment. RESULTS: Vehicle-treated T2D GK rats exhibited gradual increases in systolic and diastolic blood pressure, whereas SKA-31 administration led to lower mean arterial pressure, along with improvements in cardiac function (i.e., ejection fraction, fractional shortening) and structure (i.e., end systolic and diastolic volumes), as determined by echocardiography. SKA-31 treatment in vivo further improved vascular endothelial function in small mesenteric arteries, as determined by arterial pressure myography, and increased the protein expression of vasodilatory signaling molecules in the vascular wall. Prolonged SKA-31 treatment did not impair vasodilatory responsiveness in skeletal muscle and coronary arteries, elicit a pro-inflammatory profile in T2D GK rats or produce any adverse histological effects in brain, kidney or liver. CONCLUSIONS: channel activator SKA-31 improved CV function in an established rat model of spontaneous T2D and reveal a potential novel strategy to oppose CV-related morbidity in T2D.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".