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Record W4290342828 · doi:10.1111/jne.13194

Time of day influences stress hormone response to ketamine

2022· article· en· W4290342828 on OpenAlexfundno aff
Matthew T. Birnie, Alen Eapen, Yvonne M. Kershaw, David Lodge, Graham L. Collingridge, Becky Conway-Campbell, Stafford L. Lightman

Bibliographic record

VenueJournal of Neuroendocrinology · 2022
Typearticle
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsnot available
FundersMedical Research CouncilMedical Research Council CanadaWellcome Trust
KeywordsInternal medicineEndocrinologyFight-or-flight responseStress hormoneHormoneKetamineMedicinePsychologyBiologyAnesthesia

Abstract

fetched live from OpenAlex

Over 50% of depressed patients show hyperactivity of the hypothalamic-pituitary-adrenal (HPA) axis. Conventional therapy takes weeks to months to improve symptoms. Ketamine has rapid onset antidepressant effects. Yet its action on HPA axis activity is poorly understood. Here, we measured the corticosterone (CORT) response to ketamine administered at different times of day in the Wistar-Kyoto (WKY) rat. In male rats, blood was collected every 10 min for 28 h using an automated blood sampling system. Ketamine (5/10/25 mg · kg) was infused through a subcutaneous cannula at two time points-during the active and inactive period. CORT levels in blood were measured in response to ketamine using a radioimmunoassay. WKY rats displayed robust circadian secretion of corticosterone and was not overly different to Sprague Dawley rats. Ketamine (all doses) significantly increased CORT response at both infusion times. However, a dose dependent effect and marked increase over baseline was observed when ketamine was administered during the inactive phase. Ketamine has a robust and rapid effect on HPA axis function. The timing of ketamine injection may prove crucial for glucocorticoid-mediated action in depression.

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)0.002
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 score0.324
Threshold uncertainty score0.512

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.025
GPT teacher head0.283
Teacher spread0.258 · 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

Citations16
Published2022
Admission routes1
Has abstractyes

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