GDNF enhances the synaptic efficacy of dopaminergic neurons in culture
Bibliographic record
Abstract
Glial cell line-derived neurotrophic factor (GDNF) is known to promote the survival and differentiation of dopaminergic neurons of the midbrain. GDNF also causes an enhancement of dopamine release by a mechanism which is presently unclear. Using isolated dopaminergic neurons of the rat ventral tegmental area in culture, we have tested the hypothesis that GDNF regulates the establishment and functional properties of synaptic terminals. Previous studies have shown that single dopaminergic neurons in culture can co-release glutamate in addition to dopamine, leading to the generation of a fast excitatory autaptic current via glutamate receptors. Using excitatory autaptic currents as an assay for the activity of synapses established by identified dopaminergic neurons, we found that chronically applied GDNF produced a threefold increase in the amplitude of excitatory autaptic currents. This action was specific for dopaminergic neurons because GDNF had no such effect on ventral tegmental area GABAergic neurons. The enhancement of excitatory autaptic current amplitude caused by GDNF was accompanied by an increase in the frequency of spontaneous miniature excitatory autaptic currents. These observations confirmed a presynaptic locus of change. We identified synaptic terminals by using synapsin-1 immunofluorescence. In single tyrosine hydroxylase-positive neurons, the number of synapsin-positive puncta which represent putative synaptic terminals was found to be approximately doubled in GDNF-treated cells at 5, 10 and 15 days in culture. The number of such morphologically identified terminals in isolated GABAergic neurons was unchanged by GDNF. These results suggest that one mechanism through which GDNF may enhance dopamine release is through promoting the establishment of new functional synaptic terminals.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".