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Record W2089872706 · doi:10.1159/000124190

Bovine Neurophysin II Has Prolactin-Releasing Activity in the Estradiol-Primed Male Rat

2008· article· en· W2089872706 on OpenAlexaff
Seon H. Shin, Marc C. Obonsawin

Bibliographic record

VenueNeuroendocrinology · 2008
Typearticle
Languageen
FieldMedicine
TopicHypothalamic control of reproductive hormones
Canadian institutionsQueen's University
FundersMedical Research Council
KeywordsProlactinEndocrinologyInternal medicineNeurophysinsSephadexChemistryPituitary glandOvariectomized ratProlactin cellAnterior pituitaryHormoneBiologyBiochemistryMedicineEnzyme

Abstract

fetched live from OpenAlex

In the course of the search for the prolactin-releasing factor (PRF), we noticed that the posterior pituitary contained strong PRF activity and subsequently traced this activity to that of bovine neurophysin-II (NP-II). NP-II prepared in our lab was judged to be a homogeneous preparation according to Sephadex G-75 gel filtration, DEAE ion exchange chromatography and polyacrylamide gel electrophoresis. While neurophysin-I (NP-I) injections of 100 micrograms/kg and 1,000 micrograms/kg elevated plasma prolactin in estradiol-primed male rats to 30% and 50% over the control value, respectively, NP-II doses of 100, 1,000 micrograms/kg increased plasma prolactin concentration in estradiol-primed male rats to 130% and 170% over the control value, respectively. The lowest dose of NP-II needed to increase plasma prolactin concentration was 10 micrograms/kg. Since neurophysin does not stimulate prolactin release from the ectopic pituitary under the kidney capsule nor from lactotrophs in a primary monolayer culture system, neurophysin is believed to act indirectly on the pituitary, presumably through a neurotransmitter and/or hypothalamic releasing (or inhibiting) factor. We propose that NP-II may be one element in the complex chain of the prolactin-releasing mechanism.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.841
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.052
GPT teacher head0.264
Teacher spread0.211 · 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 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

Citations9
Published2008
Admission routes1
Has abstractyes

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