MétaCan
Menu
Back to cohort
Record W3130730717 · doi:10.1097/shk.0000000000001763

Cannabinoid Receptor 1 and 2 Signaling Pathways Involved in Sepsis

2021· article· en· W3130730717 on OpenAlexaff

Bibliographic record

VenueShock · 2021
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsSepsisEndocannabinoid systemCannabinoid receptorCannabinoidImmune systemCannabinoid receptor type 2ReceptorSignal transduction

Abstract

fetched live from OpenAlex

ABSTRACT: Sepsis is defined as a life-threatening organ dysfunction, caused by a dysregulated host response to an infection and can progress to septic shock, which represents a major challenge in critical care with a high mortality rate. Currently, there is no definitive treatment available for the dysregulated immune response in sepsis. Therefore, a better understanding of the pathophysiological mechanisms may be useful for elucidating the molecular basis of sepsis and may contribute to the development of new therapeutic strategies. The endocannabinoid system is an emerging research topic for the modulation of the host immune response under various pathological conditions. Cannabinoid receptors include the cannabinoid type 1 receptor (CB1) and the cannabinoid type 2 receptor (CB2). This review addresses the main functionality of CB1 and CB2 in sepsis, which can contribute to a better understanding about the pathophysiology of sepsis. Specifically, we discuss the role of CB1 in the cardiovascular system which is one of the biological systems that are strongly affected by sepsis and septic shock. We are also reviewing the role of CB2 in sepsis, specially CB2 activation, which exerts anti-inflammatory activities with potential benefit in sepsis.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.263
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.280
Teacher spread0.255 · 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.

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

Citations9
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueShockSame topicCannabis and Cannabinoid ResearchFrench-language works237,207