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Record W2600971053 · doi:10.1093/schbul/sbx024.066

SU68. Effect of Cannabis on Neuroinflammation in Clinical High Risk for Psychosis: An In Vivo PET Study With [18F]-FEPPA

2017· article· en· W2600971053 on OpenAlexaff
Tânia Maria Sarmento Silva, Sina Hafizi

Bibliographic record

VenueSchizophrenia Bulletin · 2017
Typearticle
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsNeuroinflammationTranslocator proteinPsychosisCannabisPsychologySchizophrenia (object-oriented programming)Dorsolateral prefrontal cortexMedicineNeuroprotectionPrefrontal cortexInternal medicinePsychiatryNeuroscienceCognitionInflammation

Abstract

fetched live from OpenAlex

Background: Clinical high risk for psychosis (CHR) is the (putative) prodromal phase of psychosis characterized by attenuated psychotic symptoms and/or genetic risk with recent functional deterioration. Epidemiological evidence suggests that early cannabis use is associated with psychosis particularly in predisposed individuals. However, cannabinoids, including cannabis, have also been suggested to have neuroprotective and anti-inflammatory effects. This is particularly important as neuroinflammation has been implicated in the pathophysiology of several brain disorders including schizophrenia. Neuroinflammation is characterized by microglial activation in the brain. Upon activation, microglia increase the expression of a mitochondrial Translocator protein 18 kDa (TSPO). Therefore, increased TSPO expression represents an important marker of neuroinflammation/microglial activation. The purpose of this study is to image neuroinflammation in vivo in brain in CHR for psychosis with (CHR-CU) and without (CHR) concurrent cannabis use. Methods: Eighteen CHRs and 5 CHR-CUs underwent an MRI and a high-resolution [18F]-FEPPA PET scan to quantify neuroinflammation in vivo in brain. CHR-CUs were included if they met criteria for DSM-V cannabis use disorder and/or current cannabis use as determined by a positive drug screen (at least 3 times weekly for 12 months in lifetime). All participants completed a series of neuropsychological and clinical assessments. PET images were analyzed using the validated 2-tissue compartment model to obtain total distribution volumes (VT) in the hippocampus and dorsolateral prefrontal cortex (DLPFC). Results: No significant differences in [18F]-FEPPA binding were observed between groups (F(2,19) = 1.447, P = .260). In the CHR group, there was a positive correlation between apathy and [18F]-FEPPA binding in the hippocampus (r = 0.543, P = .024) and a trend in the DLPFC (r = 0.475, P = .054). In the CHR-CU group, there was a negative correlation between cumulative cannabis use and [18F]-FEPPA binding in the DLPFC (r = −0.982, P = .018). There were no significant correlations between [18F]-FEPPA binding and measures symptom severity or cognition. Conclusion: This is the first in vivo study to investigate the role of cannabinoids on neuroinflammation, and its relevance for psychosis. Results, although preliminary, suggest no difference in the level of neuroinflammation between CHR-CUs compared to CHRs. Increased sample size is required to confirm the results.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.019
GPT teacher head0.311
Teacher spread0.292 · 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 designObservational
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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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