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Background: This update of the guideline on the management of amyotrophic lateral sclerosis (ALS) was commissioned by the European Academy of Neurology (EAN) and prepared in collaboration with the European Reference Network for Neuromuscular Diseases (ERN EURO‐NMD) and the support of the European Network for the Cure ALS (ENCALS) and the European Organization for Professionals and Patients with ALS (EUpALS). Methods: Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology was used to assess the effectiveness of interventions for ALS. Two systematic reviewers from Cochrane Response supported the guideline panel. The working group identified a total of 26 research questions, performed systematic reviews, assessed the quality of the available evidence, and made specific recommendations. Expert consensus statements were provided where insufficient evidence was available. Results: A guideline mapping effort revealed only one other ALS guideline that used GRADE methodology (a National Institute for Health and Care Excellence [NICE] guideline). The available evidence was scarce for many research questions. Of the 26 research questions evaluated, the NICE recommendations could be adapted for 8 questions. Other recommendations required updates of existing systematic reviews or de novo reviews. Recommendations were made on currently available disease‐modifying treatments, multidisciplinary care, nutritional and respiratory support, communication aids, psychological support, treatments for common ALS symptoms (e.g., muscle cramps, spasticity, pseudobulbar affect, thick mucus, sialorrhea, pain), and end‐of‐life management. Conclusions: This update of the guideline using GRADE methodology provides a framework for the management of ALS. The treatment landscape is changing rapidly, and further updates will be prepared when additional evidence becomes available. [ABSTRACT FROM AUTHOR]

Raman spectroscopy shows promise as a biomarker for complex nerve and muscle (neuromuscular) diseases. To maximise its potential, several challenges remain. These include the sensitivity to different instrument configurations, translation across preclinical/human tissues and the development of multivariate analytics that can derive interpretable spectral outputs for disease identification. Nonnegative matrix factorisation (NMF) can extract features from high‐dimensional data sets and the nonnegative constraint results in physically realistic outputs. In this study, we have undertaken NMF on Raman spectra of muscle obtained from different clinical and preclinical settings. First, we obtained and combined Raman spectra from human patients with mitochondrial disease and healthy volunteers, using both a commercial microscope and in‐house fibre optic probe. NMF was applied across all data, and spectral patterns common to both equipment configurations were identified. Linear discriminant models utilising these patterns were able to accurately classify disease states (accuracy 70.2–84.5%). Next, we applied NMF to spectra obtained from the mdx mouse model of a Duchenne muscular dystrophy and patients with dystrophic muscle conditions. Spectral fingerprints common to mouse/human were obtained and able to accurately identify disease (accuracy 79.5–98.8%). We conclude that NMF can be used to analyse Raman data across different equipment configurations and the preclinical/clinical divide. Thus, the application of NMF decomposition methods could enhance the potential of Raman spectroscopy for the study of fatal neuromuscular diseases. [ABSTRACT FROM AUTHOR]