Human aldose reductase and human small intestine aldose reductase are efficient retinal reductases: consequences for retinoid metabolism
Bibliographic record
Abstract
Aldo-keto reductases (AKRs) are NAD(P)H-dependent oxidoreductases that catalyse the reduction of a variety of carbonyl compounds, such as carbohydrates, aliphatic and aromatic aldehydes and steroids. We have studied the retinal reductase activity of human aldose reductase (AR), human small-intestine (HSI) AR and pig aldehyde reductase. Human AR and HSI AR were very efficient in the reduction of all- trans -, 9- cis - and 13- cis -retinal ( k (cat)/ K (m)=1100-10300 mM(-1).min(-1)), constituting the first cytosolic NADP(H)-dependent retinal reductases described in humans. Aldehyde reductase showed no activity with these retinal isomers. Glucose was a poor inhibitor ( K (i)=80 mM) of retinal reductase activity of human AR, whereas tolrestat, a classical AKR inhibitor used pharmacologically to treat diabetes, inhibited retinal reduction by human AR and HSI AR. All- trans -retinoic acid failed to inhibit both enzymes. In this paper we present the AKRs as an emergent superfamily of retinal-active enzymes, putatively involved in the regulation of retinoid biological activity through the assimilation of retinoids from beta-carotene and the control of retinal bioavailability.
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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) | 0.000 | 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) | 0.002 | 0.001 |
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".