Hydrogen Sulfide-Releasing Therapeutics: Translation to the Clinic
Bibliographic record
Abstract
Significance: Shortly after the discovery of the role of hydrogen sulfide (H 2 S) in many physiological and pathological processes, attempts were made to develop novel pharmaceuticals that may be of benefit for treatment or prevention of a wide range of disorders. The promise of H 2 S-based therapeutics is now being demonstrated in clinical trials. Recent Advances: H 2 S-releasing drugs, such as SG1002 for cardiovascular disorders, and ATB-346 for arthritis, have progressed into clinical trials and have shown considerable promise. Some older drugs, such as zofenopril, have now been recognized to produce at least some of the beneficial effects through release of H 2 S. Critical Issues: There remains a need to better understand the underlying mechanisms for some of the observed effects of H 2 S-releasing drugs in a clinical setting, such as the marked increase in analgesic potency that has been observed with ATB-346. Future Directions: The proof-of-concept clinical studies reviewed herein pave the way for examination, in a clinical setting, of several other potential applications of H 2 S-based drugs in a wide range of disorders, including diabetes, hypertension, and cancer chemoprevention. Antioxid. Redox Signal. 28, 1533–1540.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".