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Effects of neonatal maternal separation on HVR are no longer present in middle‐aged female rats.

2008· article· en· W3176340809 on OpenAlexafffund
Sébastien Fournier, Roumiana Gulemetova, Vincent Joseph, Richard Kinkead

Bibliographic record

VenueThe FASEB Journal · 2008
Typearticle
Languageen
FieldPsychology
TopicNeuroendocrine regulation and behavior
Canadian institutionsUniversité Laval
FundersCanadian Institutes of Health Research
KeywordsHypoxic ventilatory responseMedicinePhysiologyPlethysmographEndocrinologyInternal medicineHormoneRespiratory systemBiology

Abstract

fetched live from OpenAlex

Neonatal maternal separation (NMS) disrupts normal neurological development in mammals. The hypoxic ventilatory response (HVR) of adult male rats previously subjected to NMS is ∼25% greater than controls while the response of NMS females is reduced by ∼30% (Genest et al., 2004). To address the role of ovarian hormones on the respiratory phenotype observed in NMS females, we compared the HVR of adult (10–14 weeks old) with that of more mature females (53–60 weeks old) in which circulating estradiol and progesterone levels are significantly reduced. Pups subjected to NMS were placed in an incubator 3h/day for 10 consecutive days (P3 to P12). Controls were undisturbed. Rats were then reared normally until adulthood or middle age when HVR was measured with plethysmography (12% O 2 , 20 min). The HVR of middle‐aged females was greatly reduced compared to adults. The effects of NMS on HVR were attenuated in middle‐aged compared to younger adult females. Middle‐aged NMS females tended to have a higher HVR than controls, as observed in adult NMS males vs. controls. These results highlight the interaction between endogenous hormones and the respiratory phenotype observed in NMS animals. Supported by the CIHR.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.039
GPT teacher head0.315
Teacher spread0.276 · 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 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

Citations0
Published2008
Admission routes2
Has abstractyes

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