Ethanesulfohydroxamic Acid Ester Prodrugs of Nonsteroidal Anti-inflammatory Drugs (NSAIDs): Synthesis, Nitric oxide and Nitroxyl Release, Cyclooxygenase Inhibition, Anti-inflammatory, and Ulcerogenicity Index Studies
Bibliographic record
Abstract
The carboxylic acid group of the anti-inflammatory (AI) drugs indo-methacin, (S)-naproxen and ibuprofen was covalently linked via a two-carbon ethyl spacer to a sulfohydroxamic acid moiety (CH(2)CH(2)SO(2)NHOH) to furnish a group of hybrid ester prodrugs that release nitric oxide (NO) and nitroxyl (HNO). Biological data acquired for this hitherto unknown class of ethanesulfohydroxamic acid ester prodrugs showed (i) all compounds exhibited superior NO, but similar HNO, release properties relative to arylsulfohydroxamic acids, (ii) the (S)-naproxen and ibuprofen prodrug esters are more potent AI agents than their parent NSAID, (iii) the indomethacin prodrug ester, in contrast to indomethacin which is highly ulcerogenic, showed no visible stomach lesions [ulcer index (UI) = 0 for a 80 μmol/kg oral dose] while retaining potent AI activity, and iv) that the indomethacin prodrug ester, unlike indomethacin which is an ulcerogenic selective COX-1 inhibitor, is a selective COX-2 inhibitor (COX-2 selectivity index = 184) devoid of ulcerogenicity that is attributed to its high COX-2 SI and/or ability to release cytoprotective NO.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".