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Record W3024199902 · doi:10.1016/j.molmet.2020.101011

Interaction of glucose sensing and leptin action in the brain

2020· review· en· W3024199902 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMolecular Metabolism · 2020
Typereview
Languageen
FieldNeuroscience
TopicRegulation of Appetite and Obesity
Canadian institutionsUniversity of TorontoToronto General Hospital
FundersCanadian Institutes of Health Research
KeywordsLeptinGlucose homeostasisEnergy homeostasisHomeostasisEndocrinologyInternal medicineNutrient sensingHypothalamusDiabetes mellitusHormoneBlood sugar regulationBiologyObesityChemistryMedicineSignal transductionInsulin resistanceCell biology

Abstract

fetched live from OpenAlex

BACKGROUND: In response to energy abundant or deprived conditions, nutrients and hormones activate hypothalamic pathways to maintain energy and glucose homeostasis. The underlying CNS mechanisms, however, remain elusive in rodents and humans. SCOPE OF REVIEW: Here, we first discuss brain glucose sensing mechanisms in the presence of a rise or fall of plasma glucose levels, and highlight defects in hypothalamic glucose sensing disrupt in vivo glucose homeostasis in high-fat fed, obese, and/or diabetic conditions. Second, we discuss brain leptin signalling pathways that impact glucose homeostasis in glucose-deprived and excessed conditions, and propose that leptin enhances hypothalamic glucose sensing and restores glucose homeostasis in short-term high-fat fed and/or uncontrolled diabetic conditions. MAJOR CONCLUSIONS: In conclusion, we believe basic studies that investigate the interaction of glucose sensing and leptin action in the brain will address the translational impact of hypothalamic glucose sensing in diabetes and obesity.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.978
Threshold uncertainty score0.573

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.059
GPT teacher head0.341
Teacher spread0.282 · 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