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Record W2003151896 · doi:10.1159/000125186

Effect of Corticotropin-Releasing Factor on the Release and Synthesis of Prolactin

2008· article· en· W2003151896 on OpenAlexaff
Gérard Morel, A Enjalbert, L. Proulx, G. Pelletier, N. Barden, Francis Grossard, Paul Dubois

Bibliographic record

VenueNeuroendocrinology · 2008
Typearticle
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsBiotechnology Research Institute
Fundersnot available
KeywordsInternal medicineEndocrinologyCorticotropic cellProlactinProlactin cellAnterior pituitaryPituitary glandAdrenocorticotropic hormoneCorticotropin-releasing hormoneSecretionHypothalamusImmunocytochemistryChemistryBiologyHormoneMedicine

Abstract

fetched live from OpenAlex

Corticotropin-releasing factor (CRF) has been characterized on the basis of its intrinsic activity to release corticotropin from cultured rat anterior pituitary cells. Injected in intact rats, CRF increases adrenocorticotropic hormone (ACTH) release. Endogenous CRF-like immunoreactivity was detected in the cytoplasm and nucleus of corticotrophs. Using an antirat CRF serum, a similar location of CRF-like immunoreactivity was observed in lactotrophs: cytoplasmic matrix, secretory granules, nucleus and, to a lesser degree, the plasma membrane level were stained. One injection of CRF increased the plasma ACTH concentration 4-fold after 15 min, while plasma prolactin (PRL) increased 2.7-fold 5 min after injection. In vitro, incubation of female pituitary cells with rat CRF (10(-10)-10(-8) M) had no significant effect on PRL secretion. In contrast, after 4 days of in vitro pretreatment with 17 beta-estradiol (10(-9) M), rat CRF stimulated PRL secretion by 42%. In situ hybridization of whole pituitary slices showed that rat CRF injection significantly increased the labeling of corticotrophs using an ACTH-cDNA probe, but had no significant effect on the labeling of lactotrophs using a PRL riboprobe. These results indicate that CRF is a factor which can modulate PRL release but not the synthesis of PRL.

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)0.003
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 score0.130
Threshold uncertainty score0.346

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
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 head0.032
GPT teacher head0.271
Teacher spread0.239 · 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

Citations22
Published2008
Admission routes1
Has abstractyes

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