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Record W4412649347 · doi:10.1177/23523689261444878

Propofol’s Anti-Inflammatory Action Is Independent of Endocannabinoid System Activation in Microglia

2025· preprint· en· W4412649347 on OpenAlexaff
Pouria Abdolmohammadi, Bashir Bietar, Juan Zhou, Christine Lehmann

Bibliographic record

VenueJournal of Cellular Biotechnology · 2025
Typepreprint
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMicrogliaEndocannabinoid systemPropofolAction (physics)NeurosciencePharmacologyMedicineChemistryInflammationInternal medicinePsychologyReceptorPhysics

Abstract

fetched live from OpenAlex

Propofol is well-known for its inhibitory effects in the central nervous system (CNS) as an intravenous anesthetic. Less is known about propofol's impact on microglial activity. Studies have suggested a link to the endocannabinoid system (ECS). Propofol has been shown to indirectly modulate cannabinoid type 1 (CB1R) and type 2 (CB2R) receptors on microglia, with CB2R playing a key role in regulating anti-inflammatory immune responses. The objective of this study was to evaluate potential anti-inflammatory effects of propofol on microglia and to determine whether any observed effects are associated with the ECS. To investigate this, we treated LPS-stimulated SIMA9 microglial cells with propofol, both in the presence and absence of antagonists for CB2R and CB1R, and assessed the cell viability and the production of the cytokines TNF and IL-6. The results demonstrated that cell viability was stable at propofol concentrations of 20, 40, and 80 µM. Production of TNF and IL-6 was reduced significantly upon propofol treatment. This effect of cytokine production did not change following administration of CB1R and/or CB2R antagonists. In conclusion, the results demonstrated that propofol exhibits anti-inflammatory effects, which do not appear to be mediated through ECS activation.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
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 score0.005
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.003
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 head0.037
GPT teacher head0.321
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 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

Citations1
Published2025
Admission routes1
Has abstractyes

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