Objective: To evaluate the course and predictors of neuropsychiatric symptoms (NPS) and cognition in patients with de novo Parkinson disease (PD). Methods: Cross-sectional study of the cohort of de novo, untreated (at enrollment) patients with PD and healthy controls (HCs) from the Parkinson9s Progression Markers Initiative. Participants have serial assessments of global cognition and symptoms of depression, anxiety, psychosis, impulse control disorders (ICDs), sleep and wakefulness, apathy, and fatigue. Available data up to 24 months of follow-up were included. Results: The available sample size was as follows: baseline (PD = 423, HCs = 196), 12 months (PD = 261, HCs = 145), and 24 months (PD = 96, HCs = 83). Patients with PD experienced more depression, fatigue, apathy, and anxiety than HCs at all time points, and apathy (p = 0.001) and psychosis (p = 0.003) increased over time in patients with PD. Approximately two-thirds of patients with PD who screened positive for depression at any given visit were not taking an antidepressant. The Montreal Cognitive Assessment score decreased significantly over time in patients with PD (p < 0.001), but the change was comparable to that in HCs. At the 24-month visit, 44% of patients had been on dopamine replacement therapy (DRT) for at least 1 year, and this group reported more incident ICDs (p = 0.009) and excessive daytime sleepiness (p = 0.03). Conclusion: Multiple NPS are more common in de novo, untreated patients with PD compared with the general population, but they also remain relatively stable in early disease, while global cognition slightly deteriorates. In contrast, initiation of DRT is associated with increasing frequency of several other NPS.

Despite recent advances in treatment options, stroke remains a highly prevalent and devastating condition with significant socioeconomic impact. Recanalization therapies, including intravenous thrombolysis and endovascular treatments, have revolutionized stroke management and prognosis, providing a promising framework for exploring new therapeutic strategies. Endothelial dysfunction plays a critical role in the pathophysiology, progression, and prognosis of stroke. This review aims to synthesize the current evidence regarding the involvement of the nitric oxide (NO)/endothelium pathway in ischemic stroke, with a particular focus on aging, response to recanalization therapies, and therapeutic approaches. While significant progress has been made in recent years in understanding the relationship between endothelial dysfunction and stroke, many uncertainties persist, and although treatments targeting this pathway are promising, they have yet to demonstrate clear clinical benefits.

Essential tremor (ET) is the most prevalent movement disorder, affecting millions of people in the USA. Although a positive family history is one of the most important risk factors for ET, the genetic causes of ET remain unknown. In an attempt to identify genetic causes for ET, we performed whole-exome sequencing analyses in a large Spanish family with ET, in which two patients also developed epilepsy. To further assess pathogenicity, site-directed mutagenesis, mouse and human brain expression analyses, and patch clamp techniques were performed. A disease-segregating mutation (p.Gly1537Ser) in the SCN4A gene was identified. Posterior functional analyses demonstrated that more rapid kinetics at near-threshold potentials altered ion selectivity and facilitated the conductance of both potassium and ammonium ions, which could contribute to tremor and increase susceptibility to epilepsy, respectively. In this report, for the first time, we associated the genetic variability of SCN4A with the development of essential tremor, which adds ET to the growing list of neurological channelopathies.

Biomedical systems produce biosignals that arise from interaction mechanisms. In a general form, those mechanisms occur across multiple scales, both spatial and temporal, and contain linear and non-linear information. In this framework, entropy measures are good candidates in order provide useful evidence about disorder in the system, lack of information in time-series and/or irregularity of the signals. The most common movement disorder is essential tremor (ET), which occurs 20 times more than Parkinson’s disease. Interestingly, about 50%–70% of the cases of ET have a genetic origin. One of the most used standard tests for clinical diagnosis of ET is Archimedes’ spiral drawing. This work focuses on the selection of non-linear biomarkers from such drawings and handwriting, and it is part of a wider cross study on the diagnosis of essential tremor, where our piece of research presents the selection of entropy features for early ET diagnosis. Classic entropy features are compared with features based on permutation entropy. Automatic analysis system settled on several Machine Learning paradigms is performed, while automatic features selection is implemented by means of ANOVA (analysis of variance) test. The obtained results for early detection are promising and appear applicable to real environments.