Ranirestat (AS-3201), a Potent Aldose Reductase Inhibitor, Reduces Sorbitol Levels and Improves Motor Nerve Conduction Velocity in Streptozotocin-Diabetic Rats
Bibliographic record
Abstract
Ranirestat (AS-3201) is a novel aldose reductase (AR) inhibitor with potentially beneficial effects on diabetic sensorimotor polyneuropathy. In this study, we performed a kinetic analysis to determine the mode of inhibition of ranirestat on AR and investigated the effects of ranirestat on sorbitol levels in the sciatic nerves and lens of streptozotocin (STZ)-diabetic rats. We also evaluated the effects on motor nerve conduction velocity (MNCV) in STZ-diabetic rats. Kinetic analyses revealed that the ranirestat inhibition of AR is uncompetitive and reversible. In the sciatic nerve and lens of STZ-diabetic rats, single oral administration of ranirestat slightly reduced sorbitol levels. However, repeated oral administration of ranirestat for 5, 21, or 60 days enhanced the reducing effect of the ranirestat on sorbitol levels in the sciatic nerves and lens of STZ-diabetic rats with maximum effects after 21 days of treatment. Finally, repeated oral administration of ranirestat for 21 or 42 days dose-dependently improved the STZ-induced decrease in MNCV in STZ-diabetic rats. These findings demonstrate that repeated oral administration of ranirestat reduces sorbitol accumulation and improves MNCV in STZ-diabetic rats, indicating that ranirestat is an agent for the management of diabetic sensorimotor polyneuropathy.
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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 | 0.001 | 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".