Introduction of Gamma-Aminobutyric Acid into the Bloodstream to Negate NMDA Receptor Hypofunction Induced by Delta 9-Tetrahydrocannabinol
Bibliographic record
Abstract
Glutamate is the most abundant neurotransmitter found in the brain, controlling fast signalling throughout all sections and being especially involved in memory recollection and learning. Long-Term Potentiation (LTP) is the strengthening of neural connections through receptor synthesis over consistent usage, first triggered by synapse activation by a small amount of glutamate. However, in heavy (prolonged instance of exposure) and habitual users of cannabis, the effects of LTP are exacerbated by N-methyl-D-Aspartic Acid (NMDA) Receptor Hypofunction (NRHypo) which in turn affects memory, learning, reasoning and other aspects of one’s function. Emerging evidence has associated the inhibition of long-term potentiation by Delta 9-Tetrahydrocannabinol (D9-THC) activating presynaptic Cannabinoid Receptor Type 1 (CB1) receptors to the inhibition of the ability to stop production of glutamate (GLU). An excess of glutamate will overstimulate the postsynaptic NMDA and α-Amino-3-Hydroxy-5-Methyl-4-Isoxazolepropionic Acid (AMPA) receptors in the neurons commonly in the hippocampus, basal ganglia, and prefrontal cortex, which allow excessive influx of calcium Ca2+ ions, causing neurotoxic conditions. Glutamate Decarboxylase 67 molecule has been shown bind in high concentrations with GLU and lower the harmful effects of D9-THC on the brain by converting GLU to Gamma-Aminobutyric Acid (GABA), an inhibitory neurotransmitter. GAD67 will be distributed to mice in this proposed experiment and the behaviour of the mice will be monitored. D9-THC affected, D9-THC and GAD67 affected, and normal mice will be subjected to behavioral interaction and maze tests which will show differences in their learning, spatial awareness and orientation, and reasoning abilities. Chemical analysis of cerebral fluid and brain slices will determine chemical concentrations of GAD67 and D9-THC in the brain. Using direct injections into the cerebrospinal fluid (CSF) and bloodstream in mouse models, our aim is to determine the selectivity of the blood brain barrier (BBB) to enzymes such as GAD67 via both channels as well as assess the interaction GAD67 has with cascading neurological effects caused by NRHypo and LTP.
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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) | 0.001 | 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".