The role of dopamine receptors in lymphocytes and their changes in schizophrenia
Bibliographic record
Abstract
Dopamine and its 5 receptors, which are grouped into two families (D1-like and D2-like), modulate functions at a systemic level in both the central nervous system and periphery. The central nervous system and the immune system are the main adaptive systems, which participate in a continuous and functional crosstalk to guarantee homeostasis. On binding to its 5 dopamine receptors, dopamine acts as a co-regulator of the immune system, contributing to the interaction of the central nervous system and inflammatory events and as a source of communication between the different immune cells. Dopaminergic perturbations in the central nervous system are observed in several neurological and psychiatric disorders. Schizophrenia is one of the most common mental disorders with a poorly understood pathoaetiology that includes genetic and environmental components that promote alterations in the dopaminergic system. Interestingly, abnormalities in dopamine receptors expression in lymphocytes of schizophrenia patients have been reported, often significantly correlating with the severity of the psychotic illness. Here, we review the current literature regarding the dopaminergic system in human lymphocytes and its alterations in schizophrenia.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".