MétaCan
Menu
Back to cohort

Repeated Stress Impairs Endocannabinoid Signaling in the Paraventricular Nucleus of the Hypothalamus

2010· article· en· W2003823489 on OpenAlexafffund
Jaclyn I. Wamsteeker, J. Brent Kuzmiski, Jaideep S. Bains

Bibliographic record

VenueJournal of Neuroscience · 2010
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health ResearchAlberta Heritage Foundation for Medical ResearchFondation pour la Recherche Médicale
KeywordsEndocannabinoid systemHypothalamusNeuroscienceNucleusPsychologyInternal medicineEndocrinologyBiologyMedicineReceptor

Abstract

fetched live from OpenAlex

Endocannabinoids (eCBs) are ubiquitous retrograde signaling molecules in the nervous system that are recruited in response to robust neuronal activity or the activation of postsynaptic G-protein-coupled receptors. Physiologically, eCBs have been implicated as important mediators of the stress axis and they may contribute to the rapid feedback inhibition of the hypothalamic-pituitary-adrenal axis (HPA) by circulating corticosteroids (CORTs). Understanding the relationship between stress and eCBs, however, is complicated by observations that eCB signaling is itself sensitive to stress. The mechanisms that link stress to changes in synaptic eCB signaling and the impact of these changes on CORT-mediated negative feedback have not been resolved. Here, we show that repetitive immobilization stress, in juvenile male rats, causes a functional downregulation of CB(1) receptors in the paraventricular nucleus of the hypothalamus (PVN). This loss of CB(1) receptor signaling, which requires the activation of genomic glucocorticoid receptors, impairs both activity and receptor-dependent eCB signaling at GABA and glutamate synapses on parvocellular neuroendocrine cells in PVN. Our results provide a plausible mechanism for how stress can lead to alterations in CORT-mediated negative feedback and may contribute to the development of plasticity of HPA responses.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.771
Threshold uncertainty score0.409

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.018
GPT teacher head0.286
Teacher spread0.268 · 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

Citations143
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueJournal of NeuroscienceSame topicCannabis and Cannabinoid ResearchFrench-language works237,207