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Record W1988819628 · doi:10.1159/000126980

Relationship of Plasma Growth Hormone to Slow-Wave Sleep in African Sleeping Sickness

2008· article· en· W1988819628 on OpenAlexaff
Manny W. Radomski, Alain Buguet, F. Doua, Pascal Bogui, P Tapie

Bibliographic record

VenueNeuroendocrinology · 2008
Typearticle
Languageen
FieldMedicine
TopicLysosomal Storage Disorders Research
Canadian institutionsDepartment of National DefenceDefence Research and Development Canada
Fundersnot available
KeywordsEndocrinologyInternal medicineSleep (system call)Circadian rhythmPolysomnographyWakefulnessProlactinSlow-wave sleepSleep onsetSleep StagesHormoneMelatoninMedicinePsychologyInsomniaApneaElectroencephalographyPsychiatry

Abstract

fetched live from OpenAlex

Human African trypanosomiasis (sleeping sickness) is a unique disease model of disrupted circadian rhythms in the sleep-wake cycle and cortisol and prolactin secretion. This study examined the temporal relationship between growth hormone (GH) secretion and the sleep-wake cycle in 8 infected African patients and 6 healthy indigenous African subjects. Twenty-four-hour sleep patterns were recorded by polysomnography and hourly blood samples analyzed for plasma GH. No relationships between the mean normalized plasma GH levels (Z scores) and the sleep stages (wakefulness, sleep stages 1 and 2 ('light' sleep), slow-wave sleep (stages 3 and 4, SWS), and rapid eye movement (REM) sleep) were found in the patients or healthy subjects. However, when the time of sampling of the plasma GH concentrations was lagged by 16 min with respect to the occurrence of the various sleep stages, significant correlations were found between plasma GH concentrations and SWS in both healthy subjects and patients. Thus, the association between SWS and GH secretion persisted even in the presence of disrupted circadian rhythms, further supporting the concept that sleep and the stimulation of GH secretion are outputs of a common 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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.737

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.056
GPT teacher head0.286
Teacher spread0.230 · 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

Citations27
Published2008
Admission routes1
Has abstractyes

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