Multiple Adenosine-Dopamine (A2A-D2 Like) Heteroreceptor Complexes in the Brain and Their Role in Schizophrenia
Bibliographic record
Abstract
In the 1980s and 1990s, the concept was introduced that molecular integration in the Central Nervous System could develop through allosteric receptor–receptor interactions in heteroreceptor complexes presents in neurons. A number of adenosine–dopamine heteroreceptor complexes were identified that lead to the A2A-D2 heteromer hypothesis of schizophrenia. The hypothesis is based on strong antagonistic A2A-D2 receptor–receptor interactions and their presence in the ventral striato-pallidal GABA anti-reward neurons leading to reduction of positive symptoms. Other types of adenosine A2A heteroreceptor complexes are also discussed in relation to this disease, such as A2A-D3 and A2A-D4 heteroreceptor complexes as well as higher order A2A-D2-mGluR5 and A2A-D2-Sigma1R heteroreceptor complexes. The A2A receptor protomer can likely modulate the function of the D4 receptors of relevance for understanding cognitive dysfunction in schizophrenia. A2A-D2-mGluR5 complex is of interest since upon A2A/mGluR5 coactivation they appear to synergize in producing strong inhibition of the D2 receptor protomer. For understanding the future of the schizophrenia treatment, the vulnerability of the current A2A-D2like receptor complexes will be tested in animal models of schizophrenia. A2A-D2-Simag1R complexes hold the highest promise through Sigma1R enhancement of inhibition of D2R function. In line with this work, Lara proposed a highly relevant role of adenosine for neurobiology of schizophrenia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".