The effect of preventive exercise on the neuroprotection in 6-hydroxydopamine-lesioned rat brain
Bibliographic record
Abstract
Parkinson’s disease is characterized by neurodegeneration and learning deficiency. Physical exercise can alleviate these symptoms by increasing the expression of some effective and relevant factors. The preventive effect of 16-week treadmill running in a rat model of Parkinson’s disease, before 6-hydroxydopamine (6-OHDA) induction, was assessed. Experimental groups consisted of sedentary (SED), SED+6-OHDA, exercised (EX), and EX+6-OHDA rats. Forty-eight hours after the last session of exercise, 6-OHDA was injected into the medial forebrain bundle (MFB). One week after the injection, behavioral tests, including spatial learning and memory, were assessed through Morris water maze (MWM) and apomorphine-induced rotation. Three weeks after the injection, mRNA expression and protein levels of the transcriptional co-activator peroxisome-proliferator-activated receptor-γ co-activator-1α (PGC-1α), fibronectin type III domain-containing protein 5 (FNDC5), brain-derived neurotrophic factor (BDNF), and tyrosine hydroxylase (TH) were measured in the striatum and the hippocampus of rats by applying real-time PCR and Western blotting. The findings indicate that exposure to 6-OHDA leads to impairments in behavioral and molecular functions. Exercise training prevents and reduces the symptoms caused by dopamine toxins. The results suggest that treadmill running can exert neuroprotective and have preventive effects to reduce Parkinson’s disease symptoms. Novelty Parkinson’s disease impairs spatial learning and memory. Parkinson’s disease reduced levels of PGC-1α, FNDC5, and BDNF and increased neurodegeneration in the striatum and the hippocampus. Treadmill running before disease attenuated 6-OHDA-induced memory deficit and elevated neuroprotection. Exercise has multiple effects on memory and biochemical factors.
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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) | 0.001 | 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) | 0.001 | 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".