GDNF-induced cerebellar toxicity: A brief review
Bibliographic record
Abstract
Recombinant-methionyl human glial cell line-derived neurotrophic factor (GDNF) is known for its neurorestorative and neuroprotective effects in rodent and primate models of Parkinson's disease (PD). When administered locally into the putamen of Parkinsonian subjects, early clinical studies showed its potential promise as a disease-modifying agent. However, the development of GDNF for the treatment of PD has been significantly clouded by findings of cerebellar toxicity after continuous intraputamenal high-dose administration in a 6-month treatment/3-month recovery toxicology study in rhesus monkeys. Specifically, multifocal cerebellar Purkinje cell loss affecting 1-21% of the cerebellar cortex was observed in 4 of 15 (26.7%; 95% confidence interval [CI]: 10.5-52.4%) animals treated at the highest dose level tested (3000μg/month). No cerebellar toxicity was observed at lower doses (450 and 900μg/month) in the same study, or at similar or higher doses (up to 10,000μg/month) in subchronic or chronic toxicology studies testing intermittent intracerebroventricular administration. While seemingly associated with the use of GDNF, the pathogenesis of the cerebellar lesions has not been fully understood to date. This review integrates available information to evaluate potential pathogenic mechanisms and provide a consolidated assessment of the findings. While other explanations are considered, the existing evidence is most consistent with the hypothesis that leakage of GDNF into cerebrospinal fluid during chronic infusions into the putamen down-regulates GDNF receptors on Purkinje cells, and that subsequent acute withdrawal of GDNF generates the observed lesions. The implications of these findings for clinical studies with GDNF are discussed.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".