<i>gdnf</i> affects early diencephalic dopaminergic neuron development through regulation of differentiation‐associated transcription factors in zebrafish
Bibliographic record
Abstract
Glial cell line-derived neurotrophic factor (GDNF) has been reported to enhance dopaminergic neuron survival and differentiation in vitro and in vivo, although those results are still being debated. Glial cell line-derived neurotrophic factor (gdnf) is highly conserved in zebrafish and plays a role in enteric nervous system function. However, little is known about gdnf function in the teleost brain. Here, we employed clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 to impede gdnf function in the maintenance of dopaminergic neuron development. Genotyping of gdnf crispants revealed successful deletions of the coding region with various mutant band sizes and down-regulation of gdnf transcripts at 1, 3 and 7 day(s) post fertilization. Notably, ~20% reduction in ventral diencephalic dopaminergic neuron numbers in clusters 8 and 13 was observed in the gdnf-deficient crispants. In addition, gdnf depletion caused a modest reduction in dopaminergic neurogenesis as determined by 5-ethynyl-2'-deoxyuridine pulse chase assay. These deleterious effects could be partly attributed to deregulation of dopaminergic neuron fate specification-related transcription factors (otp,lmx1b,shha,and ngn1) in both crispants and established homozygous mutants with whole mount in-situ hybridization (WISH) on gdnf mutants showing reduced otpb and lmx1b.1 expression in the ventral diencephalon. Interestingly, locomotor function of crispants was only impacted at 7 dpf, but not earlier. Lastly, as expected, gdnf deficiency heightened crispants vulnerability to 1-methyl-4-phenylpyridinium toxic insult. Our results suggest conservation of teleost gdnf brain function with mammals and revealed the interactions between gdnf and transcription factors in dopaminergic neuron differentiation.
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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 | 0.001 |
| 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) | 0.000 | 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".