Choline Redistribution during Adaptation to Choline Deprivation
Bibliographic record
Abstract
Choline is an important nutrient for mammals. Choline can also be generated by the catabolism of phosphatidylcholine synthesized in the liver by the methylation of phosphatidylethanolamine by phosphatidylethanolamine N-methyltransferase (PEMT). Complete choline deprivation is achieved by feeding Pemt(-)(/)(-) mice a choline-deficient diet and is lethal due to liver failure. Mice that lack both PEMT and MDR2 (multiple drug-resistant protein 2) successfully adapt to choline deprivation via hepatic choline recycling. We now report another mechanism involved in this adaptation, choline redistribution. Normal levels of choline-containing metabolites were maintained in the brains of choline-deficient Mdr2(-)(/)(-)/Pemt(-)(/)(-) mice for 90 days despite continued choline consumption via oxidation. Choline oxidase activity had not been previously detected in the brain. Plasma levels of choline were also maintained for 90 days, whereas plasma phosphatidylcholine levels decreased by >60%. The injection of [(3)H]choline into Mdr2(-)(/)(-)/Pemt(-)(/)(-) mice revealed a redistribution of choline among tissues. Although CD-Pemt(-)(/)(-) mice failed to adapt to choline deprivation, choline redistribution was also initiated in these mice. The data suggest that adaptation to choline deprivation is not restricted to liver via choline recycling but also occurs in the whole animal via choline redistribution.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".