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Record W2443378893 · doi:10.1152/ajpregu.00168.2016

Nutrient-sensing mechanisms in hypothalamic cell models: neuropeptide regulation and neuroinflammation in male- and female-derived cell lines

2016· review· en· W2443378893 on OpenAlexafffund
Neruja Loganathan, Denise D. Belsham

Bibliographic record

VenueAmerican Journal of Physiology-Regulatory, Integrative and Comparative Physiology · 2016
Typereview
Languageen
FieldNeuroscience
TopicRegulation of Appetite and Obesity
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsGovernment of Canada
KeywordsHypothalamusNeuroinflammationSexual dimorphismEnergy homeostasisBiologyNeuropeptideNeuroscienceHomeostasisCell typeCellEndocrinologyOrganismInternal medicineObesityInflammationImmunologyMedicineReceptor

Abstract

fetched live from OpenAlex

The hypothalamus is responsible for the control of many of our physiological responses, including energy homeostasis. Of interest, there are a number of instances of sexual dimorphism documented with regard to metabolic processes. This review will discuss the necessity of utilizing both male and female models when studying the mechanisms underlying energy homeostasis, particularly those originating at the level of the hypothalamus. Because obesity often results in central neuroinflammation, we describe markers that could be used to study differences between male and female models, both the whole organism and also at the cellular level. Our laboratory has generated a wide array of immortalized hypothalamic cell models, originating from male and female rodents that we suggest could be beneficial for these types of studies. It is imperative that both sexes are considered before any recommendations for therapeutic interventions are considered.

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)0.001
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.050
GPT teacher head0.292
Teacher spread0.242 · 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

Citations7
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueAmerican Journal of Physiology-Regulatory, Integrative and Comparative Physiology→Same topicRegulation of Appetite and Obesity→French-language works237,207→