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Research over the past 20 years indicates the amount of task-specific walking practice provided to individuals with stroke, brain injury, or incomplete spinal cord injury can strongly influence walking recovery. However, more recent data suggest that attention towards 2 other training parameters, including the intensity and variability of walking practice, may maximize walking recovery and facilitate gains in non-walking outcomes. The combination of these training parameters represents a stark contrast from traditional strategies, and confusion regarding the potential benefits and perceived risks may limit their implementation in clinical practice.

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While the role of cancer stem cells (CSCs) in tumorigenesis, chemoresistance, metastasis, and relapse has been extensively studied in solid tumors, such as adenocarcinomas or sarcomas, the same cannot be said for neuroendocrine neoplasms (NENs). While lagging, CSCs have been described in numerous NENs, including gastrointestinal and pancreatic NENs (PanNENs), and they have been found to play critical roles in tumor initiation, progression, and treatment resistance. However, it seems that there is still skepticism regarding the role of CSCs in NENs, even in light of studies that support the CSC model in these tumors and the therapeutic benefits of targeting them.

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Nonconvulsive status epilepticus (NCSE) was initially described in patients with typical and atypical absence status epilepticus (ASE) characterized by states of confusion varying in severity and in focal epilepsies with or without alteration of consciousness. Continuous EEG monitoring of critically ill patients has further refined the classification of NCSE into two main categories: with coma and without coma. Hypnotic, soporific or somniferous epileptic seizures do not exist.

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In recent years, the utilization of motor imagery (MI) signals derived from electroencephalography (EEG) has shown promising applications in controlling various devices such as wheelchairs, assistive technologies, and driverless vehicles. However, decoding EEG signals poses significant challenges due to their complexity, dynamic nature, and low signal-to-noise ratio (SNR). Traditional EEG pattern recognition algorithms typically involve two key steps: feature extraction and feature classification, both crucial for accurate operation.

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Exploring the use and usefulness of living guidelines for consumers: international online survey of patients' and carers' views.

J Clin Epidemiol

January 2025

Australian Living Evidence Collaboration, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.

Background: Living guidelines contain continually updated, and potentially changing, clinical recommendations. The implications of living guidelines for consumers (e.g.

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