A reappraisal of the 6-<i>O</i>-desmethylnaproxen-sulfating activity of the human cytosolic sulfotransferases
Bibliographic record
Abstract
In this study, we aimed to obtain a comprehensive account of the human cytosolic sulfotransferases (SULTs) that are capable of sulfating 6-O-desmethylnaproxen (O-DMN), a major metabolite of naproxen. Of the 13 known human SULTs tested, 7 (SULT1A1, SULT1A2, SULT1A3, SULT1B1, SULT1C2, SULT1C4, and SULT1E1) displayed O-DMN-sulfating activity, when analyzed using an elevated substrate concentration (500 μmol·L−1) together with 14 μmol·L−1 of the sulfate donor, 3′-phosphoadenosine-5′-phosphosulfate (PAPS). At 10 μmol·L−1 O-DMN concentration, however, only SULT1A1 and SULT1A3 displayed detectable activity, with the former being nearly 2 orders of magnitude more active than the latter. A pH-dependence study indicated that SULT1A1 exhibited a broad pH optimum spanning pH 5.5–7. Kinetic parameters of the sulfation of O-DMN by SULT1A1 were determined. The production and release of sulfated O-DMN was demonstrated using cultured human HepG2 hepatoma cells and Caco-2 colon carcinoma cells. Moreover, assays using human organ specimens revealed that the O-DMN-sulfating activities present in the cytosols of liver and small intestine (at 502.5 and 497.2 pmol·min−1·(mg protein)−1, respectively) were much higher than those detected for the cytosols of lung and kidney. Taken together, these results provided relevant information concerning the sulfation of O-DMN both in vitro and in vivo.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".