Background: Amyotrophic lateral sclerosis (ALS) is a multifactorial, multisystem motor neuron disease for which currently there is no effective treatment. There is an urgent need to identify biomarkers to tackle the disease’s complexity and help in early diagnosis, prognosis, and therapy. Extracellular vesicles (EVs) are nanostructures released by any cell type into body fluids. Their biophysical and biochemical characteristics vary with the parent cell’s physiological and pathological state and make them an attractive source of multidimensional data for patient classification and stratification. Methods: We analyzed plasma-derived EVs of ALS patients ( n = 106) and controls ( n = 96), and SOD1 ^G93A and TDP-43 ^Q331K mouse models of ALS. We purified plasma EVs by nickel-based isolation, characterized their EV size distribution and morphology respectively by nanotracking analysis and transmission electron microscopy, and analyzed EV markers and protein cargos by Western blot and proteomics. We used machine learning techniques to predict diagnosis and prognosis. Results: Our procedure resulted in high-yield isolation of intact and polydisperse plasma EVs, with minimal lipoprotein contamination. EVs in the plasma of ALS patients and the two mouse models of ALS had a distinctive size distribution and lower HSP90 levels compared to the controls. In terms of disease progression, the levels of cyclophilin A with the EV size distribution distinguished fast and slow disease progressors, a possibly new means for patient stratification. Immuno-electron microscopy also suggested that phosphorylated TDP-43 is not an intravesicular cargo of plasma-derived EVs. Conclusions: Our analysis unmasked features in plasma EVs of ALS patients with potential straightforward clinical application. We conceived an innovative mathematical model based on machine learning which, by integrating EV size distribution data with protein cargoes, gave very high prediction rates for disease diagnosis and prognosis.

Summary: Objective: The new epilepsy definition adopted by the International League Against Epilepsy (ILAE) includes patients with one unprovoked seizure with a probability of further seizures, similar to the general recurrence risk after two unprovoked seizures, occurring in a 10‐year period. Long‐term follow‐up of patients diagnosed after a single seizure is needed to assess the applicability of the new epilepsy definition in clinical practice.Methods: Patients with newly diagnosed epilepsy were recruited retrospectively with a minimum follow‐up of 10 years. Patients were stratified in two groups depending on the occurrence of one (new definition, ND) or two or more unprovoked seizures (traditional definition, TD) at the time of epilepsy diagnosis and compared for disease characteristics and factors predicting seizure recurrence. The primary outcome was the occurrence of a new unprovoked seizure during follow‐up in the ND group. The secondary outcome was the achievement of an early remission in both groups.Results: Among 1,006 patients with newly diagnosed epilepsy, 152 (15.1%) were diagnosed after a single seizure. Compared to patients diagnosed using the TD, patients diagnosed according to the ND showed a higher proportion of subjects with an abnormal neurologic examination (19.9% vs. 13.7%, p = 0.0504) and with focal seizures (69.3% vs. 60.4%, p = 0.0021). The two samples differed in the presence of at least one of the factors predicting seizure recurrence (focal seizures or abnormal findings in at least one among the following: neurologic examination, electroencephalography [EEG], and neuroimaging) (94.6% vs. 89.1%, p = 0.0376). Long‐term recurrence in patients diagnosed with the new definition was 83.6% at 10 years and 89.1% at 15 years. The probability of early remission did not differ between the two groups.Significance: Our results support the applicability of the new epilepsy definition in clinical practice. Individual patient characteristics and a personalized diagnostic approach can justify treatment after a single unprovoked seizure.

Nonsuicidal self-injury (NSSI) is recognized as a public health concern for its association with unfavorable outcomes, including suicidal behavior. The aim of this study is to identify factors asso...

The management of Medication overuse headache (MOH) represents a difficult challenge for clinicians and headache experts, particularly for the responder rate after a successful withdrawal treatment. The purpose of this study was to investigate the role of demographic and clinical characteristics as well as the score of Migraine-Specific Quality of Life Questionnaire (MSQ), Migraine Disability Questionnaire and Leeds Dependence Questionnaire in predicting a response after a successful withdrawal treatment in patients with MOH. This ancillary study is part of a randomized trial that demonstrated the safety and the efficacy of a 3-month treatment with sodium valproate (VPA) (800 mg/day vs placebo) in MOH. Demographic and clinical characteristics and questionnaire results were obtained from the entire sample. A significant correlation was found only between MOH relapse and the total MSQ score, the Role Preventive sub-scale and the Emotional Function sub-scale, suggesting a poorer quality of life in non responders. A high MSQ score could be associated with a poor short-term outcome in MOH patients after a successful treatment with detoxification followed by a new treatment.