Inactivation of human liver bile acid CoA:amino acid N-acyltransferase by the electrophilic lipid, 4-hydroxynonenal
Bibliographic record
Abstract
The hepatic enzyme bile acid CoA:amino acid N-acyltransferase (BAT) catalyzes the formation of amino acid-conjugated bile acids. In the present study, protein carbonylation of BAT, consistent with modification by reactive oxygen species and their products, was increased in hepatic homogenates of apolipoprotein E knock-out mice. 4-Hydroxynonenal (4HNE), an electrophilic lipid generated by oxidation of polyunsaturated long-chain fatty acids, typically reacts with the amino acids Cys, His, Lys, and Arg to form adducts, some of which (Michael adducts) preserve the aldehyde (i.e., carbonyl) moiety. Because two of these amino acids (Cys and His) are members of the catalytic triad of human BAT, it was proposed that 4HNE would cause inactivation of this enzyme. As expected, human BAT (1.6 microM) was inactivated by 4HNE in a dose-dependent manner. To establish the sites of 4HNE's reaction with BAT, peptides from proteolysis of 4HNE-treated, recombinant human BAT were analyzed by peptide mass fingerprinting and by electrospray ionization-tandem mass spectrometry using a hybrid linear ion trap Fourier transform-ion cyclotron resonance mass spectrometer. The data revealed that the active-site His (His362) dose-dependently formed a 4HNE adduct, contributing to loss of activity, although 4HNE adducts on other residues may also contribute.
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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) | 0.001 | 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".