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Record W1971005192 · doi:10.1159/000126993

Effects of Sex Hormones on the Pineal Response to Isoproterenol and on Pineal Beta-Adrenergic Receptors

2008· article· en· W1971005192 on OpenAlexaff
Shang-Mian Yie, Gregor M. Brown

Bibliographic record

VenueNeuroendocrinology · 2008
Typearticle
Languageen
FieldNeuroscience
TopicCircadian rhythm and melatonin
Canadian institutionsMcMaster University
Fundersnot available
KeywordsEndocrinologyInternal medicineMelatoninOrchiectomyHormonePineal glandCastrationTestosterone (patch)AdrenergicReceptorStimulationAdrenergic receptorMedicine

Abstract

fetched live from OpenAlex

Several studies have shown sex hormone effects on pineal function. In order to clarify the role of adrenergic mechanisms in these effects, we investigated the pineal response to adrenergic stimulation and pineal beta-adrenergic receptors following castration and/or sex hormone treatment in 2-month-old male and female Sprague-Dawley rats. The urinary 6-sulphatoxymelatonin (aMT6s) response to isoproterenol (ISO) was compared in castrated and sham-operated animals. Ovariectomy caused an increase and orchiectomy a decrease in ISO-induced urinary aMT6s excretion. The melatonin response to ISO was examined in pineal glands and serum samples obtained from castrated, sex-hormone-treated castrated and sham-operated rats. Consistently, ovariectomy increased pineal and serum melatonin responses to ISO, while orchiectomy decreased the responses; oestradiol and testosterone treatments, respectively, reversed these effects. 3H-dihydroalprenolol binding was measured in single pineal glands from castrated, sex-hormone-treated castrated and sham-operated rats. Ovariectomy increased the density of beta-adrenoceptors, whereas orchiectomy decreased the density; oestradiol and testosterone replacement, respectively, blocked these effects. No significant effect on receptor Kd values was found. These data suggest that sex hormones regulate pineal melatonin production by modifying beta-adrenergic mechanisms.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.725

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.028
GPT teacher head0.245
Teacher spread0.218 · 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

Citations15
Published2008
Admission routes1
Has abstractyes

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