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Record W7133075871

Endocannabinoid Metabolism in Posttraumatic Stress Disorder: Preliminary Results from a Neuroimaging Study with the Novel Fatty Acid Amide Hydrolase Probe [C-11] CURB

2020· dissertation· W7133075871 on OpenAlexaff
Erin Victoria Gaudette

Bibliographic record

VenueTSpace · 2020
Typedissertation
Language
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFatty acid amide hydrolaseEndocannabinoid systemAmygdalaNeuroimagingAnandamideEnzymeMonoacylglycerol lipasePosttraumatic stress
DOInot available

Abstract

fetched live from OpenAlex

Background: Preclinical studies suggest that levels of Fatty Acid Amide Hydrolase (FAAH)—the catabolic enzyme for the endocannabinoid anandamide—may be elevated in the amygdala in posttraumatic stress disorder (PTSD). However, the status of FAAH in vivo in posttraumatic stress disorder remains unknown. Methods: Healthy subjects (n=29) and individuals with PTSD (n=16) completed a positron emission tomography scan following injection of the FAAH probe [C-11]CURB. Results: We find no evidence for elevated [C-11]CURB binding in PTSD. Instead, we find marginally lower [C-11]CURB binding in whole brain (-9.38%, p=0.079) and significantly lower [C-11]CURB binding in the amygdala (-14.50%, p=0.020) in PTSD subjects. [C-11]CURB binding did not correlate with PTSD symptomatology. Conclusion: Our data provide preliminary evidence contrary to preclinical literature, suggesting that FAAH may be lower in people with PTSD. These findings have implications for treatment strategies targeting this enzyme (i.e. FAAH inhibitors) in PTSD.

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 score0.005
Threshold uncertainty score0.018

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)0.0050.001

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 head0.022
GPT teacher head0.317
Teacher spread0.295 · 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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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