Preventive effects of cyclohexenonic long-chain fatty alcohol on diabetic cystopathy in the rat
Bibliographic record
Abstract
In this study, we investigated the preventive effect of n-hexacosanol on diabetes-induced bladder dysfunction in the rat. Diabetes was induced in 8-week-old male Sprague-Dawley rats by administering an injection of streptozotocin (50 mg/kg, i.p.). The rats were randomly divided into 4 groups (age-matched control rats, diabetic rats without treatment with n-hexacosanol, and diabetic rats treated with n-hexacosanol (2 and 8 mg/kg, i.p. every day)) and maintained for 4 weeks. The serum glucose and serum insulin levels were determined, and the functions of bladder were estimated by voiding behavior, cystometric, and functional studies to carbachol and KCl. Furthermore, we examined possible diabetic induced histological changes in these rats. Treatment with n-hexacosanol did not alter diabetic status including body mass, bladder mass, and serum glucose and serum insulin levels, but significantly improved the maximum contraction pressure of the detrusor and residual urine volume in cystometric studies and Emax values to carbachol in functional studies in a dose-dependent manner. Diabetes induced bladder smooth muscle hypertrophy, which tended to be ameliorated by treatment with n-hexacosanol in a dose-dependent manner. Treatment with n-hexacosanol did not alter the diabetic status, but significantly improved diabetic cystopathy in a dose-dependent manner.
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) | 0.000 | 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".