Calcium signaling cascade links dopamine D1–D2 receptor heteromer to striatal BDNF production and neuronal growth
Bibliographic record
Abstract
Although the perturbation of either the dopaminergic system or brain-derived neurotrophic factor (BDNF) levels has been linked to important neurological and neuropsychiatric disorders, there is no known signaling pathway linking these two major players. We found that the exclusive stimulation of the dopamine D1-D2 receptor heteromer, which we identified in striatal neurons and adult rat brain by using confocal FRET, led to the activation of a signaling cascade that links dopamine signaling to BDNF production and neuronal growth through a cascade of four steps: (i) mobilization of intracellular calcium through Gq, phospholipase C, and inositol trisphosphate, (ii) rapid activation of cytosolic and nuclear calcium/calmodulin-dependent kinase IIalpha, (iii) increased BDNF expression, and (iv) accelerated morphological maturation and differentiation of striatal neurons, marked by increased microtubule-associated protein 2 production. These effects, although robust in striatal neurons from D5(-/-) mice, were absent in neurons from D1(-/-) mice. We also demonstrated that this signaling cascade was activated in adult rat brain, although with regional specificity, being largely limited to the nucleus accumbens. This dopaminergic pathway regulating neuronal growth and maturation through BDNF may have considerable significance in disorders such as drug addiction, schizophrenia, and depression.
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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".