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Background Spinal muscular atrophy type 1 (SMA1) is the most severe and early form of SMA, a genetic disease with motor neuron degeneration. Onasemnogene abeparvovec gene transfer therapy (GT) has changed the natural history of SMA1, but real-world data are scarce. Methods A French national expert committee identified 95 newly diagnosed treatment-naive SMA1 patients between June 2019 and June 2022. We prospectively report on children treated with GT as the first and only therapy who had more than one-year of follow-up. Results Forty-six SMA1 patients received GT. Twelve patients received other treatments. Patients with respiratory insufficiency were oriented toward palliative care after discussion with families. Twenty-nine of the treated patients with more than 12 months of follow-up were included in the follow-up analysis. Among them, 17 had 24 months of follow-up. The mean age at treatment was 7.5 (2.1–12.5) months. Twenty-two patients had two SMN2 copies, and seven had three copies. One infant died in the month following GT due to severe thrombotic microangiopathy, and another died due to respiratory distress. Among the 17 patients with 24 months of follow-up, 90% required spinal bracing (15/17), three patients required nocturnal noninvasive ventilation, and two needed gastrostomy. Concerning motor milestones at the 24-month follow-up, all patients held their head, 15/17 sat for 30 s unassisted, and 12/17 stood with aid. Motor scores (CHOPINTEND and HINE-2) and thoracic circumference significantly improved in all patients. Conclusions Our study shows favorable motor outcomes and preserved respiratory and feeding functions in treatment-naive SMA1 infants treated by GT as the first and only therapy before respiratory and bulbar dysfunctions occurred. Nevertheless, almost all patients developed spinal deformities.

The paradigm type I interferonopathy Aicardi-Goutières syndrome (AGS) is most typically characterized by severe neurological involvement. AGS is considered an immune-mediated disease, poorly responsive to conventional immunosuppression. Premised on a chronic enhancement of type I interferon signaling, JAK1/2 inhibition has been trialed in AGS, with clear improvements in cutaneous and systemic disease manifestations. Contrastingly, treatment efficacy at the level of the neurological system has been less conclusive. Here, we report our real-word approach study of JAK1/2 inhibition in 11 patients with AGS, providing extensive assessments of clinical and radiological status; interferon signaling, including in cerebrospinal fluid (CSF); and drug concentrations in blood and CSF. Over a median follow-up of 17 months, we observed a clear benefit of JAK1/2 inhibition on certain systemic features of AGS, and reproduced results reported using the AGS neurologic severity scale. In contrast, there was no change in other scales assessing neurological status; using the caregiver scale, only patient comfort, but no other domain of everyday-life care, was improved. Serious bacterial infections occurred in 4 out of the 11 patients. Overall, our data lead us to conclude that other approaches to treatment are urgently required for the neurologic features of AGS. We suggest that earlier diagnosis and adequate central nervous system penetration likely remain the major factors determining the efficacy of therapy in preventing irreversible brain damage, implying the importance of early and rapid genetic testing and the consideration of intrathecal drug delivery.

Objective Genetic testing is now included in the diagnostic assessment of childhood onset epilepsies. We evaluated the yield of a targeted next generation sequencing (TNGS) panel dedicated to pediatric epilepsies. Methods We tested by TNGS panel 1000 consecutive patients presenting with childhood onset epilepsies and including mainly patients with early onset epilepsies (under 2 years, 61%). Results Causal variants were identified in 31% of patients, spanning 78 different genes. Patients with benign familial neonatal/infantile epilepsy (BFN/IS) exhibited the highest rate of positive findings (82%). Developmental and epileptic encephalopathies (DEEs) had a global diagnostic yield of 37%, with epilepsy of infancy with migrating focal seizures (EIMFSI) and Dravet syndrome (DS) presenting the highest yield in this group (78%) and early infantile DEE (EIDEE) laying next with a yield of 43%. The lowest rates of genetic diagnosis were observed in infantile epileptic spasms syndrome (IESS, 17%), epilepsy with myoclonic‐atonic seizures (EMAtS, 19%), and DEE‐SWAS (14%). Patients with GEFS+ had a yield of 16%. Among patients with developmental encephalopathies and refractory seizures with onset after 2 years, TNGS yielded a 33% diagnostic rate. Atypical absences yielded 16%, focal epilepsy yielded 18%, and generalized epilepsies with refractory seizures yielded 13%. These groups exhibited a high genetic heterogeneity. Significance TNGS is an effective first‐step genetic screening in patients with high diagnostic yields (BFN/IS, EIMFS, DS, EIDEE) and for epilepsy syndromes associated with one or a few major genes (BFN/IS, EIMFS, DS, GEFS+, DEE‐SWAS). Whole exome or genome sequencing (WES/WGS) should be considered as a second step in these groups with a probably relevant Mendelian inheritance. WES/WGS could be proposed as first‐tier analysis in patients with IESS, EMAtS, generalized or focal epilepsies refractory to ASMs, and developmental encephalopathies with seizure onset after 2 years. However, the lower diagnostic yield obtained in these groups may suggest a complex inheritance. Plain Language Summary This study emphasizes the importance of accurately identifying different types of epilepsy and epilepsy syndromes to improve genetic testing strategies. We suggest that a targeted gene panel can be a good first step for some genetic conditions, such as benign familial neonatal/infantile epilepsy, Dravet syndrome, and epilepsy of infancy with migrating focal seizures.

The increasing number of frail elderly people in our aging society is becoming problematic: about 11% of community‐dwelling older persons are frail and another 42% are pre‐frail. Consequently, a major challenge in the coming years will be to test people over the age of 60 years to detect pre‐frailty at the earliest stage and to return them to robustness using the targeted interventions that are becoming increasingly available. This challenge requires individual longitudinal monitoring (ILM) or follow‐up of community‐dwelling older persons using quantitative approaches. This paper briefly describes an effort to tackle this challenge. Extending the detection of the pre‐frail stages to other population groups is also suggested. Appropriate algorithms have been used to begin the tracing of faint physiological signals in order to detect transitions from robustness to pre‐frailty states and from pre‐frailty to frailty states. It is hoped that these studies will allow older adults to receive preventive treatment at the correct institutions and by the appropriate professionals as early as possible, which will prevent loss of autonomy. Altogether, ILM is conceived as an emerging property of databases (“digital twins”) and not the reverse. Furthermore, ILM should facilitate a coordinated set of actions by the caregivers, which is a complex challenge in itself. This approach should be gradually extended to all ages, because frailty has no age, as is testified by overwork, burnout, and post‐traumatic syndrome.

This article presents a method for step detection from accelerometer and gyrometer signals recorded with Inertial Measurement Units (IMUs). The principle of our step detection algorithm is to recognize the start and end times of the steps in the signal thanks to a predefined library of templates. The algorithm is tested on a database of 1020 recordings, composed of healthy subjects and patients with various neurological or orthopedic troubles. Simulations on more than 40,000 steps show that the template-based method achieves remarkable results with a 98% recall and a 98% precision. The method adapts well to pathological subjects and can be used in a medical context for robust step estimation and gait characterization.

Open access, clean, annotated databases are key for future significant advances in gait quantification with inertial sensors. This multi-pathology and clinically annotated dataset provides 1356 gait trials from 260 participants equipped with four inertial measurement units placed on the head, lower back, and dorsal part of each foot. Participants followed a standardized protocol: standing still, walking 10 meters, turning around, walking back 10 meters, and stopping. It results in a large human walking dataset with over 11 hours of gait time series data. The quality is ensured by the documentation and metadata provided. The study population encompasses healthy individuals and patients with neurological (parkinson disease, cerebrovascular accident, radiation-induced leukoencephalopathy and chemotherapy-induced peripheral neuropathy) or orthopedic (hip osteoarthritis, knee osteoarthritis and anterior cruciate ligament injury) conditions. For each pathology, the most relevant clinical or radioclinical score has been calculated to provide insight into the gravity of the disease. This dataset can be used to study kinematic parameters, gait cycles time series, and various indicators for quantifying gait in routine clinical practice.

Nowadays, it becomes of paramount societal importance to support many frail-prone groups in our society (elderly, patients with neurodegenerative diseases, etc.) to remain socially and physically active, maintain their quality of life, and avoid their loss of autonomy. Once older people enter the prefrail stage, they are already likely to experience falls whose consequences may accelerate the deterioration of their quality of life (injuries, fear of falling, reduction of physical activity). In that context, detecting frailty and high risk of fall at an early stage is the first line of defense against the detrimental consequences of fall. The second line of defense would be to develop original protocols to detect future fallers before any fall occur. This paper briefly summarizes the current advancements and perspectives that may arise from the combination of affordable and easy-to-use non-wearable systems (force platforms, 3D tracking motion systems), wearable systems (accelerometers, gyroscopes, inertial measurement units-IMUs) with appropriate machine learning analytics, as well as the efforts to address these challenges.

We investigate the formation of fingered flow in dry granular media under simulated rainfall using a quasi-2D experimental set-up composed of a random close packing of mono-disperse glass beads. Using controlled experiments, we analyze the finger instabilities that develop from the wetting front as a function of fundamental granular (particle size) and fluid properties (rainfall, viscosity).These finger instabilities act as precursors for water channels, which serve as outlets for water drainage. We look into the characteristics of the homogeneous wetting front and channel size as well as estimate relevant time scales involved in the instability formation and the velocity of the channel finger tip. We compare our experimental results with that of the well-known prediction developed by Parlange and Hill [1976]. This model is based on linear stability analysis of the growth of perturbations arising at the interface between two immiscible fluids. Results show that in terms of morphology, experiments agree with the proposed model. However, in terms of kinetics we nevertheless account for another term that describes the homogenization of the wetting front. This result shows that the manner we introduce the fluid to a porous medium can also influence the formation of finger instabilities.