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Functional Interactions between Stress and the Endocannabinoid System: From Synaptic Signaling to Behavioral Output

2010· review· en· W2133859389 on OpenAlexafffund
Matthew N. Hill, Sachin Patel, Patrizia Campolongo, Jeffrey G. Tasker, Carsten T. Wotjak, Jaideep S. Bains

Bibliographic record

VenueJournal of Neuroscience · 2010
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of Calgary
FundersNational Institute of Mental HealthCanadian Institutes of Health ResearchNational Institutes of HealthTulane University
KeywordsEndocannabinoid systemNeuroscienceAmygdalaRegulatorExcitatory postsynaptic potentialInhibitory postsynaptic potentialBiologyPsychologyInternal medicineMedicineReceptor

Abstract

fetched live from OpenAlex

Endocannabinoid signaling is distributed throughout the brain, regulating synaptic release of both excitatory and inhibitory neurotransmitters. The presence of endocannabinoid signaling within stress-sensitive nuclei of the hypothalamus, as well as upstream limbic structures such as the amygdala, suggests it may play an important role in regulating the neuroendocrine and behavioral effects of stress. The evidence reviewed here demonstrates that endocannabinoid signaling is involved in both activating and terminating the hypothalamic-pituitary-adrenal axis response to both acute and repeated stress. In addition to neuroendocrine function, however, endocannabinoid signaling is also recruited by stress and glucocorticoid hormones to modulate cognitive and emotional processes such as memory consolidation and extinction. Collectively, these data demonstrate the importance of endocannabinoid signaling at multiple levels as both a regulator and an effector of the stress response.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.095
GPT teacher head0.379
Teacher spread0.284 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations251
Published2010
Admission routes2
Has abstractyes

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