Cloning of monkey RALDH1 and characterization of retinoid metabolism in monkey kidney proximal tubule cells
Bibliographic record
Abstract
All-trans and 9-cis retinoic acids function as ligands for retinoic acid receptors (RARs and RXRs), which are ligand-dependent transcription factors and play important roles in development and cellular differentiation. Several retinal dehydrogenases are likely to contribute to the production of all-trans and 9-cis RAs in vivo, but their respective roles in different tissues are still poorly characterized. We have previously characterized and cloned from kidney tissues the rat retinal dehydrogenase type 1 (RALDH1), which oxidizes all-trans and 9-cis retinal with high efficiency but is inactive with 13-cis retinal. Here we have characterized the retinal-oxidizing activity in monkey JTC12 cells, which are derived from kidney proximal tubules. In vitro assay of cell lysates revealed the presence of a NAD+-dependent dehydrogenase that catalyzed the oxidation of all-trans, 9-cis, and 13-cis retinal. Northern blot analysis of JTC12 RNAs and cloning by reverse transcription-polymerase chain reaction demonstrated expression of a monkey homolog of RALDH1. Bacterially expressed JTC12 RALDH1 catalyzed conversion of all three retinal isomers, with a higher catalytic efficiency for 9-cis retinal than for all-trans and 13-cis retinal. Accordingly, live JTC12 produced 9-cis retinoic acid more efficiently than all-trans retinoic acid from their respective retinal precursors. Only metabolites corresponding to the same steric conformation were formed from 9-cis or all-trans retinal, indicating a lack of detectable isomerizing activity in JTC12 cells.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".