Dietary methionine/choline deficiency affects behavioural and molecular circadian rhythms
Bibliographic record
Abstract
Abstract The feeding/fasting cycles controlled by our circadian clock impose great daily metabolic and physiological changes, and yet investigations into the consequences of metabolic deficiencies, either dietary or genetic, have often ignored the time of day or the circadian time of the animals or subjects. In addition, these deficiencies may themselves disrupt our circadian clock, causing secondary metabolic, physiological and behavioural disorders. Dietary methionine/choline deficiency in rodents is a common model for human non-alcoholic steatohepatitis, but methionine and choline are nutrients essential for many other processes beyond fatty acid synthesis in the liver, including biological methylations and 1-carbon metabolism, regulation of translation notably via the mTOR pathway, phospholipid synthesis, polyamine pathway and glutathione synthesis. We have previously shown that circadian rhythms in many organisms are highly sensitive to deficiency or excesses of 1-carbon metabolites. Using a methionine/choline deficient diet in mice, we illustrate the nutrigenomic crosstalk between circadian rhythms and 1-carbon metabolism. We show not only that circadian locomotor activity behaviour is profoundly, rapidly and reversibly affected by methionine/choline deficiency, but also that the effects of methionine/choline deficiency on gene expression and 1-carbon metabolites are dependent on circadian time, illustrating the importance of considering circadian rhythms in metabolic studies. This study also highlights the impact of what we eat, or don’t, on our behaviour and biological rhythms.
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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) | 0.002 | 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".