Homocysteine, a sulfur-containing amino acid, is an intermediate product during the metabolism of methionine, a vital amino acid. An elevated concentration of homocysteine in the plasma, named hyperhomocysteinemia, has been significantly related to the onset of several diseases, including diabetes, multiple sclerosis, osteoporosis, cancer, and neurodegenerative disorders such as dementia, Alzheimer’s and Parkinson’s diseases. An interaction between metabolic pathways of homocysteine and gut microbiota has been reported, and specific microbial signatures have been found in individuals experiencing hyperhomocysteinemia. Furthermore, some evidence suggests that gut microbial modulation may exert an influence on homocysteine levels and related disease progression. Conventional approaches for managing hyperhomocysteinemia typically involve dietary interventions alongside the administration of supplements such as B vitamins and betaine. The present review aims to synthesize recent advancements in understanding interventions targeted at mitigating hyperhomocysteinemia, with a particular emphasis on the role of gut microbiota in these strategies. The emerging therapeutic potential of gut microbiota has been reported for several diseases. Indeed, a better understanding of the complex interaction between microbial species and homocysteine metabolism may help in finding novel therapeutic strategies to counteract hyperhomocysteinemia.

Background: Exercise has been proposed as the “Universal Prescription for Parkinson’s Disease”; however, the specificity of exercise dose in terms of frequency, intensity, duration, and type to be prescribed remains to be elucidated. The 2018 US updated guidelines and WHO Guidelines on Physical Activity and Sedentary Behavior recommend older adults (> 65+ years) to achieve weekly minimal activity levels, indicating the intensity of aerobic exercise as the metabolic equivalent of task and duration as minutes/week (150–300 min/week at a moderate intensity of 3–5.9 MET- or 75–150 min/week of a vigorous intensity of ≥6 MET). Translating these recommendations to PD patients, the study aimed to assess the dose–response effects of standardized volume of structured exercise, measured as METs-minutes/week (weekly energy expenditure) of two different rehabilitation settings to quantify the change in neurotrophic factors. The exercise-induced benefits between the two rehabilitation settings will be evaluated based on motor and non-motor symptoms, kinematic parameters of gait, cognitive function, quality of life, and cortical activity and brain connectivity.Methods: METEX-PD is a pilot, prospective, observational, cohort study. The study will enroll consecutively thirty (N = 30) participants with mild-to-moderate Parkinson’s disease diagnosis to be assigned to a non-intensive or intensive rehabilitation group. The non-intensive rehabilitation group will achieve a range of 180–270 METs-min/week (90 min/week of low-intensity aerobic exercise, 2–3 METs), while the intensive rehabilitation group will exercise at 1350–1980 METs-min/week (225 min/week of high-intensity aerobic exercise, 6–8.8 METs). The METEX-PD trial will last 12 weeks, including 4 weeks of aerobic training program and two follow-ups. Assessments will be performed at baseline (T0), at the end of the exercise program (T1—end of the program), and 4- and 8 weeks after the end of the training program (FU-1 and FU-2). The primary outcome is the change from baseline in peripheral blood BDNF levels. Secondary outcomes are differences in peripheral biomarkers, functional-motor assessments, clinical-functional evaluations, and brain imaging.Conclusion: METEX-PD trial will enable us to estimate the change in BDNF levels and other peripheral biomarkers under precise exercise-induced energy expenditure. The primary results of the METEX-PD study will allow the development of a larger multicenter randomized controlled trial to investigate the molecular pathways inducing the change in selected neurotrophic factors, such as BDNF, IGF-1, or irisin, and the downstream mechanisms of neuroplasticity in PD patients.

Accurate and accessible motor function quantification is important for monitoring the movement disorders’ progression. Manual muscle testing models and wearable sensors can be costly or reduce degrees of freedom. Artificial intelligence, especially human pose estimation (PE), offers promising alternatives. This work aims to compare the accuracy of a 2D PE tool for the Finger Tapping Test (FTT) with a 3D infrared motion capture system (MoCap). PE tracked three anatomical landmarks (wrist, thumb, index finger), while reflective markers were placed at corresponding locations on both tools to measure wrist-centered angles. Different trials of slow and rapid FTT sessions were statistically analyzed by rank correlation analysis, Friedman, Bland–Altman, and Kruskal–Wallis to assess agreement and repeatability. PE and MoCap measurements showed no significant differences (p > 0.05), with high reliability (ICC 0.87–0.91), low variability (CV 6–8.6%), and negligible effect size. Bland–Altman slopes indicated minor amplitude-dependent bias, while RMSE (2.92–4.48°) and MAPE (6.38–8.22%) errors occurred in slow and rapid conditions. These results demonstrate that 2D PE provides a reliable, accessible, and low-cost alternative for quantifying finger movement. The findings suggest that PE can serve as an assistive method for monitoring motor function. Future studies can be population-level studies with patients with neurological disorders.