Adolescent THC Exposure Causes Enduring Prefrontal Cortical Disruption of GABAergic Inhibition and Dysregulation of Sub-Cortical Dopamine Function
Bibliographic record
Abstract
Abstract Chronic adolescent marijuana use has been linked to the later development of psychiatric diseases such as schizophrenia. GABAergic hypofunction in the prefrontal cortex (PFC) is a cardinal pathological feature of schizophrenia and may be a mechanism by which the PFC loses its ability to regulate sub-cortical dopamine (DA) resulting in schizophrenia-like neuropsychopathology. In the present study, we exposed adolescent rats to Δ-9-tetra-hydrocannabinol (THC), the psychoactive component in marijuana. At adulthood, we characterized the functionality of PFC GABAergic neurotransmission and its regulation of sub-cortical DA function using molecular, behavioral andin-vivoelectrophysiological analyses. Our findings revealed a persistent attenuation of PFC GABAergic function combined with a hyperactive neuronal state in PFC neurons and associated disruptions in cortical gamma oscillatory activity. These PFC abnormalities were accompanied by hyperactive DAergic neuronal activity in the ventral tegmental area (VTA) and behavioral and cognitive abnormalities similar to those observed in psychiatric disorders. Remarkably, these neuronal and behavioral effects were reversed by pharmacological activation of GABAAreceptors in the PFC. Together, these results identify a mechanistic link between dysregulated frontal cortical GABAergic inhibition and sub-cortical DAergic dysregulation, characteristic of well-established neuropsychiatric endophenotypes.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".