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Record W2114045316 · doi:10.1002/cne.23834

Sex, social status, and CRF receptor densities in naked mole‐rats

2015· article· en· W2114045316 on OpenAlexaff
Annaliese K. Beery, Lucy Bicks, Skyler J. Mooney, Nastacia L. Goodwin, Melissa M. Holmes

Bibliographic record

VenueThe Journal of Comparative Neurology · 2015
Typearticle
Languageen
FieldPsychology
TopicNeuroendocrine regulation and behavior
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBiologyReceptorMoleEndocrinologyZoologyInternal medicineNeuroscienceGeneticsBiochemistry

Abstract

fetched live from OpenAlex

Naked mole-rats (Heterocephalus glaber) live in groups that are notable for their large size and caste structure, with breeding monopolized by a single female and a small number of males. Recent studies have demonstrated substantial differences between the brains of breeders and subordinates induced by changes in social standing. Corticotropin-releasing factor (CRF) receptors-which bind the hormone CRF as well as related peptides-are important regulators of stress and anxiety, and are emerging as factors affecting social behavior. We conducted autoradiographic analyses of CRF1 and CRF2 receptor binding densities in female and male naked mole-rats varying in breeding status. Both globally and in specific brain regions, CRF1 receptor densities varied with breeding status. CRF1 receptor densities were higher in subordinates across brain regions, and particularly in the piriform cortex and cortical amygdala. Sex differences were present in CRF2 receptor binding densities, as is the case in multiple vole species. CRF2 receptor densities were higher in females, both globally and in the cortical amygdala and lateral amygdalar nucleus. These results provide novel insights into the neurobiology of social hierarchy in naked mole-rats, and add to a growing body of work that links changes in the CRF system with social behavior.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.107
GPT teacher head0.385
Teacher spread0.278 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations17
Published2015
Admission routes1
Has abstractyes

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