Guaifenesin Derivatives Promote Neurite Outgrowth and Protect Diabetic Mice from Neuropathy
Bibliographic record
Abstract
In diabetic patients, an early index of peripheral neuropathy is the slowing of conduction velocity in large myelinated neurons and a lack of understanding of the basic pathogenic mechanisms hindered therapeutics development. Racemic (R/S)-guaifenesin (1) was identified as a potent enhancer of neurite outgrowth using an in vitro screen. Its R-enantiomer (R)-1 carried the most biological activity, whereas the S-enantiomer (S)-1 was inactive. Focused structural variations to (R/S)-1 was conducted to identify potentially essential groups for the neurite outgrowth activity. In vivo therapeutic studies indicated that both (R/S)-1 and (R)-1 partially prevented motor nerve conduction velocity slowing in a mouse model of type 1 diabetes. In vitro microsomal assays suggested that compounds (R)-1 and (S)-1 are not metabolized rapidly, and PAMPA assay indicated moderate permeability through the membrane. Findings revealed here could lead to the development of novel drugs for diabetic neuropathy.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".