Metabolic Homeostasis: It’s All in the Timing
Bibliographic record
Abstract
Cross-talk between peripheral tissues is essential to ensure the coordination of nutrient intake with disposition during the feeding period, thereby preventing metabolic disease. This mini-review considers the interactions between the key peripheral tissues that constitute the metabolic clock, each of which is considered in a separate mini-review in this collation of articles published in Endocrinology in 2020 and 2021, by Martchenko et al (Circadian rhythms and the gastrointestinal tract: relationship to metabolism and gut hormones); Alvarez et al (The microbiome as a circadian coordinator of metabolism); Seshadri and Doucette (Circadian regulation of the pancreatic beta cell); McCommis et al (The importance of keeping time in the liver); Oosterman et al (The circadian clock, shift work, and tissue-specific insulin resistance); and Heyde et al (Contributions of white and brown adipose tissues to the circadian regulation of energy metabolism). The use of positive- and negative-feedback signals, both hormonal and metabolic, between these tissues ensures that peripheral metabolic pathways are synchronized with the timing of food intake, thus optimizing nutrient disposition and preventing metabolic disease. Collectively, these articles highlight the critical role played by the circadian clock in maintaining metabolic homeostasis.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".