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Record W4415643065 · doi:10.1111/jne.70104

Food and the brain: Neural and endocrine control of feeding, metabolism, and reproduction

2025· review· en· W4415643065 on OpenAlexafffund
Naira da Silva Mansano, Calvin V. Lieu, Alfonso Abizaid

Bibliographic record

VenueJournal of Neuroendocrinology · 2025
Typereview
Languageen
FieldNeuroscience
TopicRegulation of Appetite and Obesity
Canadian institutionsCarleton UniversityUniversity of Toronto
FundersNational Institute of Neurological Disorders and StrokeNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsLeptinGhrelinHormoneHypothalamusEndocrine systemOvulationAppetiteReproductionOrexigenicReproductive system

Abstract

fetched live from OpenAlex

Feeding and reproductive function are regulated by intricate systems that monitor food availability and energy stores, and on the basis of energy status, promote or put a brake on reproduction. This is particularly evident in the systems that regulate feeding and reproductive state in female mammals. Here we describe some of the systems that regulate feeding and reproductive state focusing on how metabolic hormones impact the onset of puberty as discussed in the panel session presented at the recent Panamerican Neuroendocrine Society meeting in Santos, Brazil. Indeed, hormones like leptin and insulin, which are released when levels of energy resources are increasing, may be critical signals that activate hypothalamic pathways related to ovulation in females to cause the onset of puberty. In adults, increasing levels of these hormones signal to the hypothalamus to reduce food intake and increase energy expenditure. In contrast, hormones like ghrelin impact hypothalamic and extrahypothalamic brain regions to drive hunger and the motivation to eat ultimately increasing feeding behavior and decreasing energy expenditure. Based on these actions, we describe some potential targets for the treatment of obesity and the mechanisms by which these targets work to improve human health.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.969
Threshold uncertainty score0.682

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.034
GPT teacher head0.303
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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