Evidence for two enzymatic pathways for ω-oxidation of docosanoic acid in rat liver microsomes
Bibliographic record
Abstract
We studied the omega-oxidation of docosanoic acid (C22:0) in rat liver microsomes. C22:0 and 22-hydroxy-docosanoic acid (omega-hydroxy-C22:0) were used as substrates, and the reaction products were analyzed by electrospray ionization mass spectrometry. In the presence of NADPH, omega-oxidation of C22:0 produced not only the hydroxylated product, omega-hydroxy-C22:0, but also the dicarboxylic acid of C22:0, docosanedioic acid (C22:0-DCA). When rat liver microsomes were incubated with omega-hydroxy-C22:0 in the presence of either NAD+ or NADPH, C22:0-DCA was formed readily. Formation of C22:0-DCA from either C22:0 or omega-hydroxy-C22:0 with NADPH as cofactor was inhibited strongly by miconazole and disulfiram, whereas no inhibition was found with NAD+ as cofactor. Furthermore, omega-oxidation of C22:0 was reduced significantly when molecular oxygen was depleted. The high sensitivity toward the more specific cytochrome P450 inhibitors ketoconazole and 17-octadecynoic acid suggests that hydroxylation of C22:0 and omega-hydroxy-C22:0 may be catalyzed by one or more cytochrome P450 hydroxylases belonging to the CYP4A and/or CYP4F subfamily. This study demonstrates that C22:0 is a substrate for the omega-oxidation system in rat liver microsomes and that the product of the first hydroxylation step, omega-hydroxy-C22:0, may undergo further oxidation via two distinct pathways driven by NAD+ or NADPH.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".