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The effects of sex and neonatal stress on pituitary adenylate cyclase‐activating peptide expression

2014· article· en· W1586546003 on OpenAlexafffund
Erin V. Mosca, A. Rousse, Roumiana Gulemetova, Richard Kinkead, Richard J. A. Wilson

Bibliographic record

VenueExperimental Physiology · 2014
Typearticle
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsUniversité LavalAlberta Children's HospitalCentre hospitalier universitaire de QuébecUniversity of Calgary
FundersCanadian Institutes of Health ResearchUniversité Laval
KeywordsAdenylate kinaseEndocrinologyInternal medicineReceptorCyclaseHormonePituitary adenylate cyclase-activating peptideGene expressionBiologyAnterior pituitaryGeneNeuropeptideMedicineVasoactive intestinal peptideGenetics

Abstract

fetched live from OpenAlex

NEW FINDINGS: What is the central question of this study? Does sex or neonatal stress affect the expression of pituitary adenylate cyclase-activating peptide or its receptors? What is the main finding and its importance? Neonatal-maternal separation stress has little long-lasting effect on the expression of pituitary adenylate cyclase-activating peptide or its receptors, but sex differences exist in these genes between males and females at baseline. Sex differences in classic stress hormones have been studied in depth, but pituitary adenylate cyclase-activating peptide (PACAP), recently identified as playing a critical role in the stress axes, has not. Here we studied whether baseline levels of PACAP differ between sexes in various stress-related tissues and whether neonatal-maternal separation stress has a sex-dependent effect on PACAP gene expression in stress pathways. Using quantitative RT-PCR, we found sex differences in PACAP and PACAP receptor gene expression in several respiratory and/or stress-related tissues, while neonatal-maternal separation stress did little to affect PACAP signalling in adult animals. We propose that sex differences in PACAP expression are likely to contribute to differences between males and females in responses to stress.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.385

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.009
GPT teacher head0.263
Teacher spread0.254 · 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 designBench or experimental
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

Citations10
Published2014
Admission routes2
Has abstractyes

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