Acute Seizure to Modulate α-Synuclein Induced Parkinsonian Pathology
Bibliographic record
Abstract
Parkinson's Disease (PD) involves degeneration of the nigrostriatal dopaminergic system causing a multitude of motor symptoms, whereas epilepsy is characterized by intermittent spontaneous seizures and generally involves different brain regions.Yet, it is intriguing that the two diseases rarely co-exist.Furthermore, electrical stimulation [electroconvulsive therapy (ECT) or deep brain stimulation (DBS)] has been shown to have clinically beneficial effects for PD motor and non-motor symptoms.The current thesis hypothesized that the seizure evident in epileptic patients may provoke neuroprotective effects against PD-related pathology.Specifically, we hypothesized that a chemically induced seizure would prevent the accumulation of the pathological protein, -synuclein, in mice that received central infusion of pre-formed fibrils within the brain and hence, positively impact motor functioning.Unfortunately, there were no significant PTZ or synuclein treatment effects currently observed.However, we failed to observe positive synuclein labelling, or any behavioral changes which raises the possibility of methodological problems.Whatever the case, this work presents a starting point and problems encountered will hopefully inform future studies assessing potential neuroprotective effects of seizure in PD animal models.iii
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".