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Record W2280426197 · doi:10.1093/cercor/bhv335

Adolescent Cannabinoid Exposure Induces a Persistent Sub-Cortical Hyper-Dopaminergic State and Associated Molecular Adaptations in the Prefrontal Cortex

2016· article· en· W2280426197 on OpenAlexafffund
Justine Renard, Laura G. Rosen, Michaël Loureiro, Cleusa De Oliveira, Susanne Schmid, Walter J. Rushlow, Steven R. Laviolette

Bibliographic record

VenueCerebral Cortex · 2016
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsPrefrontal cortexEndophenotypeNeuroscienceDopaminergicDopaminePsychologySchizophrenia (object-oriented programming)PsychosisCannabinoidMedicineInternal medicinePsychiatryCognition

Abstract

fetched live from OpenAlex

Considerable evidence suggests that adolescent exposure to delta-9-tetrahydrocanabinol (THC), the psychoactive component in marijuana, increases the risk of developing schizophrenia-related symptoms in early adulthood. In the present study, we used a combination of behavioral and molecular analyses with in vivo neuronal electrophysiology to compare the long-term effects of adolescent versus adulthood THC exposure in rats. We report that adolescent, but not adult, THC exposure induces long-term neuropsychiatric-like phenotypes similar to those observed in clinical populations. Thus, adolescent THC exposure induced behavioral abnormalities resembling positive and negative schizophrenia-related endophenotypes and a state of neuronal hyperactivity in the mesocorticolimbic dopamine (DA) pathway. Furthermore, we observed profound alterations in several prefrontal cortical molecular pathways consistent with sub-cortical DAergic dysregulation. Our findings demonstrate a profound dissociation in relative risk profiles for adolescent versus adulthood exposure to THC in terms of neuronal, behavioral, and molecular markers resembling neuropsychiatric pathology.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.862
Threshold uncertainty score0.621

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)0.0000.000

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 head0.018
GPT teacher head0.257
Teacher spread0.239 · 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.

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

Citations119
Published2016
Admission routes2
Has abstractyes

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