Mechanism of Sarpogrelate Action in Improving Cardiac Function in Diabetes
Bibliographic record
Abstract
Although sarpogrelate, a 5-HT(2A) receptor antagonist, has been reported to exert beneficial effects in diabetes, the mechanisms of its action are not understood. In this study, diabetes was induced in rats by an injection of streptozotocin (65 mg/kg) and the animals were assessed 7 weeks later. Decreased serum insulin as well as increased serum glucose, cholesterol, and triglyceride levels in diabetic animals were associated with increased blood pressure and heart/body weight ratio. Impaired cardiac performance in diabetic animals was evident by decreased heart rate, left ventricular developed pressure, rate of pressure development, and rate of pressure decay. Treatment of diabetic animals with sarpogrelate (5 mg/kg) or insulin (10 units/kg) daily for 6 weeks attenuated the observed changes in serum insulin, glucose, and lipid levels as well as blood pressure and cardiac function by varying degrees. Protein content for membrane glucose transporters (GLUT-1 and GLUT-4) was depressed in diabetic heart; the observed alteration in GLUT-4 was partially prevented by both sarpogrelate and insulin, whereas that in GLUT-1 was attenuated by sarpogrelate only. Incubation of myoblast cells with sarpogrelate and insulin stimulated glucose uptake; these effects were additive. 5-hydroxytryptamine was found to inhibit glucose-induced insulin release from the pancreas; this effect was prevented by sarpogrelate. These results suggest that sarpogrelate may improve cardiac function in chronic diabetes by promoting the expression of membrane glucose transporters as well as by releasing insulin from the pancreas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.001 | 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".