Modulation of brain activity and tremor severity by NeuroEpo in Parkinson’s patients with varying tremor amplitudes
Bibliographic record
Abstract
Background Tremors, particularly those related to Parkinson’s disease (PD), significantly affect quality of life. In this study, we inspected the effects of NeuroEpo versus placebo on brain function and tremor inhibition in patients with high-amplitude tremors (HAT) and low-amplitude tremors (LAT). Objectives To assess the efficacy of NeuroEpo in enhancing coherence and power spectral density (PSD) relative to tremor severity, and to explore differences in stimulation parameters and medication requirements between patients with HAT and LAT. Methods A double-blind randomized controlled trial was conducted on 16 participants diagnosed with PD. Participants were stratified into the HAT (n = 8) and LAT (n = 8) groups. Deep brain stimulation (DBS) parameters were individualized, and participants received either NeuroEpo or a placebo. The study was approved by the IRP on October 2, 2001, and all research participants gave informed consent. This research was conducted at the University of Quebec at Montreal, McGill University in Montreal, Quebec, Canada, and CHU de Bordeaux at Hôpital du Haut-Lévêque, Pessac, France. Data were obtained from authentic online platforms using DOI-referenced sources. Outcome measures included tremor severity, brain activity via EEG, and medication dosage. Results NeuroEpo treatment produced a significant increase in coherence and PSD, particularly in the 20–21 Hz frequency band, compared with placebo. Patients with LAT required higher stimulation intensities and medication doses than those with HAT, suggesting a more complex disease profile. The combination of NeuroEpo and DBS resulted in improved both motor and cognitive functions. A two-way ANOVA indicated a significant main effect of treatment (p < 0.05), with the NeuroEpo group exhibiting a significantly greater PSD than the placebo group. Conclusion NeuroEpo may provide an adjuvant therapeutic aid for the control of tremor and improvement in brain function in PD patients. Customized treatment approaches incorporating tremor amplitude may improve therapeutic benefit and patient well-being. Future research should follow up on the long-term psychosocial effects of combined interventions.
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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 | 0.001 | 0.001 |
| 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".