Neuronal systems and circuits involved in the control of food intake and adaptive thermogenesis
Bibliographic record
Abstract
With the still-growing prevalence of obesity worldwide, major efforts are made to understand the various behavioral, environmental, and genetic factors that promote excess fat gain. Obesity results from an imbalance between energy intake and energy expenditure, which emphasizes the importance of deciphering the mechanisms behind energy balance regulation to understand its physiopathology. The control of energy balance is assured by brain systems/circuits capable of generating adequate ingestive and thermogenic responses to maintain the stability of energy reserves, which implies a proper integration of the homeostatic signals that inform about the status of the energy stores. In this article, we overview the organization and functionality of key neuronal circuits or pathways involved in the control of food intake and energy expenditure. We review the role of the corticolimbic (executive and reward) and autonomic systems that integrate their activities to regulate energy balance. We also describe the mechanisms and pathways whereby homeostatic sensing is achieved in response to variations of homeostatic hormones, such as leptin, insulin, and ghrelin, while putting some emphasis on the prominent importance of the mechanistic target of the rapamycin signaling pathway in coordinating the homeostatic sensing process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".