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Record W2744690554 · doi:10.1101/cshperspect.a031666

Regulation of Energy Metabolism by Bone-Derived Hormones

2017· review· en· W2744690554 on OpenAlexafffund
Paula Mera, Mathieu Ferron, Ioanna Mosialou

Bibliographic record

VenueCold Spring Harbor Perspectives in Medicine · 2017
Typereview
Languageen
FieldNeuroscience
TopicRegulation of Appetite and Obesity
Canadian institutionsMontreal Clinical Research Institute
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsEndocrinologyInternal medicineHypothalamusOsteocalcinBone remodelingHormoneChemistryReceptorSecretionAppetiteLipid metabolismBiologyMedicineBiochemistry

Abstract

fetched live from OpenAlex

Like many other organs, bone can act as an endocrine organ through the secretion of bone-specific hormones or "osteokines." At least two osteokines are implicated in the control of glucose and energy metabolism: osteocalcin (OCN) and lipocalin-2 (LCN2). OCN stimulates the production and secretion of insulin by the pancreatic β-cells, but also favors adaptation to exercise by stimulating glucose and fatty acid (FA) utilization by the muscle. Both of these OCN functions are mediated by the G-protein-coupled receptor GPRC6A. In contrast, LCN2 influences energy metabolism by activating appetite-suppressing signaling in the brain. This action of LCN2 occurs through its binding to the melanocortin 4 receptor (MC4R) in the paraventricular nucleus of the hypothalamus (PVN) and ventromedial neurons of the hypothalamus.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.068
GPT teacher head0.340
Teacher spread0.272 · 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 source (direct Gemma or distilled Codex), 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

Citations89
Published2017
Admission routes2
Has abstractyes

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