Activity-dependent and use-dependent regulation of dopamine-receptor clustering
Bibliographic record
Abstract
In this study, fluorescence-conjugated ligands were employed to label dopaminergic D1-like and D2-like receptors, respectively, in neurons derived from the frontal cortex of embryonic rats. The receptor binding sites were visualized and analyzed using confocal microscopy. Our results showed that fluorescently labeled receptors tended to form clusters with a diameter of about one micrometer and were distributed on both somata and dendrites. Chronic treatment with tetrodotoxin reduced the number of fluorescent clusters of both D1-like and D2-like receptors, while chronic treatment with a high concentration of potassium increased the number of fluorescent clusters of both D1-like and D2-like receptors. Further, chronic treatment with SCH23390 up-regulated the number of D1-like receptor clusters, whereas chronic treatment with bromocriptine down-regulated the number of D2-like receptor clusters. In addition, chronic treatment with spiperone down-regulated the number of D1-like receptor clusters. These results suggest that both neuronal activity and dopaminergic receptor occupancy are important factors that determine dopaminergic receptor clustering which is an essential step toward synaptogenesis during neuronal maturation process.
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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) | 0.000 | 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 | 0.000 |
| 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".