The Effects of Steroid Hormones on Long-Chain 3-Hydroxyacyl- CoA Dehydrogenase (LCHAD) Enzyme Expression in LCHAD Deficient Cells and Induction of Long-Chain Fatty Acid Binding Proteins on Long-Chain Fatty Acid-Induced Hepatotoxicity
Bibliographic record
Abstract
Background: Long-chain 3-hydroxyacyl-CoA dehydrogenase (LCHAD) deficiency has been implicated in the pathogenesis of acute fatty liver of pregnancy (AFLP) and the Hemolysis Elevated Liver Enzyme, Low Platelet (HELLP) syndrome. Yet not all pregnant women with LCHAD deficiency develop these conditions and whether induction of long-chain fatty acid binding proteins (L-FABP) might be of therapeutic value remains to be determined. Objectives: To document: (1) the effects of pregnancy associated steroid hormones on LCHAD expression and (2) induction of L-FABP on long-chain fatty acid (LCFA)-induced hepatotoxicity. Methods: LCHAD deficient B2325 cells were exposed to various concentrations of β-estradiol and/or progesterone in vitro and LCHAD mRNA and protein expression documented by RT-PCR and Western Blot analysis for 24-72 hours thereafter. In addition, Huh-7 hepatocytes exposed to toxic concentrations of LCFA (a mixture of oleic and palmitic acid) for 24 hours were treated with L-FABP inducers clofibrate or simvastatin (6.25-100 mM) for a subsequent 48 hours prior to documenting cell toxicity. Results: Neither β-estradiol, progesterone or a combination thereof consistently decreased LCHAD mRNA or protein expression. Moreover, hepatocyte survival was not altered by either clofibrate or simvastatin. Conclusions: Increases in steroid hormones associated with pregnancy are unlikely to contribute to LCFA-induced hepatotoxicity in LCHAD deficient women. Induction of L-FABP does not hold promise as a therapeutic strategy for pregnant women with AFLP or HELLP.
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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".