The effects of motor rehabilitation training on clinical symptoms and serum BDNF levels in Parkinson’s disease subjects
Bibliographic record
Abstract
Increasing evidence suggests that motor rehabilitation may delay Parkinson's disease (PD) progression. Moreover, parallel treatments in animals up-regulate brain-derived neurotrophic factor (BDNF). Thus, we investigated the effect of a motor rehabilitation protocol on PD symptoms and BDNF serum levels. Motor rehabilitation training consisted of a cycle of 20 days/month of physiotherapy divided in 3 daily sessions. Clinical data were collected at the beginning, at the end, and at 90 days follow-up. BDNF serum levels were detected by ELISA at 0, 7, 14, 21, 30, and 90 days. The follow-up period had a duration of 60 days (T30-T90). The results showed that at the end of the treatment (day 30), an improvement in extrapyramidal signs (UPDRS III; UPDRS III - Gait and Balance items), motor (6 Minute Walking Test), and daily living activities (UPDRS II; PDQ-39) was observed. BDNF levels were increased at day 7 as compared with baseline. After that, no changes in BDNF were observed during the treatment and in the successive follow-up. This study demonstrates that motor rehabilitation training is able to ameliorate PD symptoms and to increase temporarily BDNF serum levels. The latter effect may potentially contribute to the therapeutic action.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".