Brain imaging studies of appetite in the context of obesity and the menstrual cycle
Bibliographic record
Abstract
BACKGROUND Obesity affects many aspects of health, including reproduction. Despite unrelenting warnings about the health consequences of obesity, its prevalence continues to rise. Beginning with the discovery of leptin in 1994, the endocrinology of energy homeostasis has been significantly advanced. More recently, brain imaging studies have been providing novel insights into homeostatic and hedonic aspects of human ingestive behavior. METHODS A comprehensive MEDLINE search was conducted on the topic of neuroendocrine control of ingestive behavior with an emphasis on functional magnetic resonance imaging studies. Additional articles were collected by hand searching the bibliographies of all relevant articles retrieved. RESULTS This review describes recent advances in our understanding of endocrine signals that respond to acute and chronic energy states and regulate ingestive behavior so as to achieve a balance between energy intake and energy expenditure. Recently published brain imaging studies, describing the neural networks that process endocrine signals of energy state and hedonic cues associated with highly palatable foods, are highlighted. Brain responses to food cues are described in the context of appetite changes during the menstrual cycle both in normal physiology and under the conditions anorexia nervosa and bulimia nervosa. CONCLUSIONS The prevalence of obesity belies the plethora of endocrine signals in place to ensure energy homeostasis. However, satiety signals appear to be counteracted by hedonic signals derived from highly palatable foods typical of today's diet. A better understanding of the interaction between homeostatic and hedonic signals is needed to devise effective strategies for dealing with obesity. Menstrual cycle dependent changes in brain responses to food cues may provide insight into the normal physiological control of ingestive behavior as well as dysfunctional regulation associated with disordered eating.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".