Debamestrocel multimodal effects on biomarker pathways in amyotrophic lateral sclerosis are linked to clinical outcomes.

INTRODUCTION/AIMS: Biomarkers have shown promise in amyotrophic lateral sclerosis (ALS) research, but the quest for reliable biomarkers remains active. This study evaluates the effect of debamestrocel on cerebrospinal fluid (CSF) biomarkers, an exploratory endpoint. METHODS: A total of 196 participants randomly received debamestrocel or placebo. Seven CSF samples were to be collected from all participants. Forty-five biomarkers were analyzed in the overall study and by two subgroups characterized by the ALS Functional Rating Scale-Revised (ALSFRS-R). A prespecified model was employed to predict clinical outcomes leveraging biomarkers and disease characteristics. Causal inference was used to analyze relationships between neurofilament light chain (NfL) and ALSFRS-R. RESULTS: We observed significant changes with debamestrocel in 64% of the biomarkers studied, spanning pathways implicated in ALS pathology (63% neuroinflammation, 50% neurodegeneration, and 89% neuroprotection). Biomarker changes with debamestrocel show biological activity in trial participants, including those with advanced ALS. CSF biomarkers were predictive of clinical outcomes in debamestrocel-treated participants (baseline NfL, baseline latency-associated peptide/transforming growth factor beta1 [LAP/TGFß1], change galectin-1, all p < .01), with baseline NfL and LAP/TGFß1 remaining (p < .05) when disease characteristics (p < .005) were incorporated. Change from baseline to the last measurement showed debamestrocel-driven reductions in NfL were associated with less decline in ALSFRS-R. Debamestrocel significantly reduced NfL from baseline compared with placebo (11% vs. 1.6%, p = .037). DISCUSSION: Following debamestrocel treatment, many biomarkers showed increases (anti-inflammatory/neuroprotective) or decreases (inflammatory/neurodegenerative) suggesting a possible treatment effect. Neuroinflammatory and neuroprotective biomarkers were predictive of clinical response, suggesting a potential multimodal mechanism of action. These results offer preliminary insights that need to be confirmed.

Motor band sign is specific for amyotrophic lateral sclerosis and corresponds to motor symptoms.

OBJECTIVE: Magnetic resonance imaging can detect neurodegenerative iron accumulation in the motor cortex, called the motor band sign. This study aims to evaluate its sensitivity/specificity and correlations to symptomatology, biomarkers, and clinical outcome in amyotrophic lateral sclerosis. METHODS: This prospective study consecutively enrolled 114 persons with amyotrophic lateral sclerosis and 79 mimics referred to Karolinska University Hospital, and also 31 healthy controls. All underwent 3-Tesla brain susceptibility-weighted imaging. Three raters independently assessed motor cortex susceptibility with total and regional motor band scores. Survival was evaluated at a median of 34.2 months after the imaging. RESULTS: The motor band sign identified amyotrophic lateral sclerosis with a sensitivity of 59.6% and a specificity of 91.1% versus mimics and 96.8% versus controls. Higher motor band scores were more common with genetic risk factors (p = 0.032), especially with C9orf72 mutation, and were associated with higher neurofilament light levels (std. ß 0.22, p = 0.019). Regional scores correlated strongly with focal symptoms (medial region vs. gross motor dysfunction, std. ß -0.64, p = 0.001; intermediate region vs. fine motor dysfunction, std. ß -0.51, p = 0.031; lateral region vs. bulbar symptoms std. ß -0.71, p < 0.001). There were no associations with cognition, progression rate, or survival. INTERPRETATION: In a real-life clinical setting, the motor band sign has high specificity but relatively low sensitivity for identifying amyotrophic lateral sclerosis. Associations with genetic risk factors, neurofilament levels and somatotopic correspondence to focal motor weakness suggest that the motor band sign could be a suitable biomarker for diagnostics and clinical trials in amyotrophic lateral sclerosis.

Modelos experimentales murinos en la esclerosis lateral amiotrófica. Puesta al día / Murine experimental models of amyotrophic lateral sclerosis: An update

Introducción: La esclerosis lateral amiotrófica (ELA) es una enfermedad neurodegenerativa, progresiva y de etiología desconocida caracterizada por la degeneración de motoneuronas superiores e inferiores. Aproximadamente el 90% de los casos de ELA son esporádicos, mientras que el 10% restante se consideran familiares. Independientemente de si son familiares o esporádicas, los pacientes desarrollan una debilidad progresiva, atrofia muscular con espasticidad y contracturas. Por lo general, la esperanza de vida en los pacientes de ELA es de 2 a 5 años. Desarrollo: Los modelos in vivo han ayudado a explicar la etiología y la patogénesis, así como los mecanismos de la ELA. Sin embargo, estos mecanismos no están del todo esclarecidos aún, por lo que los modelos experimentales son fundamentales para continuar con el estudio de los mismos, así como para la búsqueda de posibles dianas terapéuticas. A pesar de que el 90% de los casos son esporádicos, la mayoría de los modelos utilizados hasta la actualidad para estudiar la patogénesis están basados en las mutaciones genéticas asociadas a la enfermedad familiar, lo que provoca que la patogénesis de la ELA esporádica no sea aún conocida. Por tanto, sería fundamental el estudio de la enfermedad en modelos basados en la enfermedad esporádica. Conclusión: En el presente artículo se han revisado los principales modelos experimentales, tanto genéticos como esporádicos, utilizados en el estudio de esta enfermedad, enfocándonos en los que se han desarrollado utilizando el roedor como plataforma experimental.(AU)

Introduction: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease whose aetiology is unknown. It is characterised by upper and lower motor neuron degeneration. Approximately 90% of cases of ALS are sporadic, whereas the other 10% are familial. Regardless of whether the case is familial or sporadic, patients will develop progressive weakness, muscle atrophy with spasticity, and muscle contractures. Life expectancy of these patients is generally 2–5 years after diagnosis. Development: In vivo models have helped to clarify the aetiology and pathogenesis of ALS, as well as the mechanisms of the disease. However, as these mechanisms are not yet fully understood, experimental models are essential to the continued study of the pathogenesis of ALS, as well as in the search for possible therapeutic targets. Although 90% of cases are sporadic, most of the models used to study ALS pathogenesis are based on genetic mutations associated with the familial form of the disease; the pathogenesis of sporadic ALS remains unknown. Therefore, it would be critical to establish models based on the sporadic form. Conclusion: This article reviews the main genetic and sporadic experimental models used in the study of this disease, focusing on those that have been developed using rodents.(AU)

Biomarkers for Managing Neurodegenerative Diseases.

Neurological disorders are the leading cause of cognitive and physical disability worldwide, affecting 15% of the global population. Due to the demographics of aging, the prevalence of neurological disorders, including neurodegenerative diseases, will double over the next two decades. Unfortunately, while available therapies provide symptomatic relief for cognitive and motor impairment, there is an urgent unmet need to develop disease-modifying therapies that slow the rate of pathological progression. In that context, biomarkers could identify at-risk and prodromal patients, monitor disease progression, track responses to therapy, and parse the causality of molecular events to identify novel targets for further clinical investigation. Thus, identifying biomarkers that discriminate between diseases and reflect specific stages of pathology would catalyze the discovery and development of therapeutic targets. This review will describe the prevalence, known mechanisms, ongoing or recently concluded therapeutic clinical trials, and biomarkers of three of the most prevalent neurodegenerative diseases, including Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), and Parkinson's disease (PD).

Neurofilaments in Sporadic and Familial Amyotrophic Lateral Sclerosis: A Systematic Review and Meta-Analysis.

BACKGROUND: Neurofilament proteins have been implicated to be altered in amyotrophic lateral sclerosis (ALS). The objectives of this study were to assess the diagnostic and prognostic utility of neurofilaments in ALS. METHODS: Studies were conducted in electronic databases (PubMed/MEDLINE, Embase, Web of Science, and Cochrane CENTRAL) from inception to 17 August 2023, and investigated neurofilament light (NfL) or phosphorylated neurofilament heavy chain (pNfH) in ALS. The study design, enrolment criteria, neurofilament concentrations, test accuracy, relationship between neurofilaments in cerebrospinal fluid (CSF) and blood, and clinical outcome were recorded. The protocol was registered with PROSPERO, CRD42022376939. RESULTS: Sixty studies with 8801 participants were included. Both NfL and pNfH measured in CSF showed high sensitivity and specificity in distinguishing ALS from disease mimics. Both NfL and pNfH measured in CSF correlated with their corresponding levels in blood (plasma or serum); however, there were stronger correlations between CSF NfL and blood NfL. NfL measured in blood exhibited high sensitivity and specificity in distinguishing ALS from controls. Both higher levels of NfL and pNfH either measured in blood or CSF were correlated with more severe symptoms as assessed by the ALS Functional Rating Scale Revised score and with a faster disease progression rate; however, only blood NfL levels were associated with shorter survival. DISCUSSION: Both NfL and pNfH measured in CSF or blood show high diagnostic utility and association with ALS functional scores and disease progression, while CSF NfL correlates strongly with blood (either plasma or serum) and is also associated with survival, supporting its use in clinical diagnostics and prognosis. Future work must be conducted in a prospective manner with standardized bio-specimen collection methods and analytical platforms, further improvement in immunoassays for quantification of pNfH in blood, and the identification of cut-offs across the ALS spectrum and controls.

Improving the measurement properties of the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R): deriving a valid measurement total for the calculation of change.

BACKGROUND: The Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R) total score is a widely used measure of functional status in Amyotrophic Lateral Sclerosis/Motor Neuron Disease (ALS), but recent evidence has raised doubts about its validity. The objective was to examine the measurement properties of the ALSFRS-R, aiming to produce valid measurement from all 12 scale items. METHOD: Longitudinal ALSFRS-R data were collected between 2013-2020 from 1120 people with ALS recruited from 35 centers, together with other scales in the Trajectories of Outcomes in Neurological Conditions-ALS (TONiC-ALS) study. The ALSFRS-R was analyzed by confirmatory factor analysis (CFA), Rasch Analysis (RA) and Mokken scaling. RESULTS: No definite factor structure of the ALSFRS-R was confirmed by CFA. RA revealed the raw score total to be invalid even at the ordinal level because of multidimensionality; valid interval level subscale measures could be found for the Bulbar, Fine-Motor and Gross-Motor domains but the Respiratory domain was only valid at an ordinal level. All four domains resolved into a single valid, interval level measure by using a bifactor RA. The smallest detectable difference was 10.4% of the range of the interval scale. CONCLUSION: A total ALSFRS-R ordinal raw score can lead to inferential bias in clinical trial results due to its non-linear nature. On the interval level transformation, more than 5 points difference is required before a statistically significant detectable difference can be observed. Transformation to interval level data should be mandatory in clinical trials.

Conformational fingerprinting with Raman spectroscopy reveals protein structure as a translational biomarker of muscle pathology.

Neuromuscular disorders are a group of conditions that can result in weakness of skeletal muscles. Examples include fatal diseases such as amyotrophic lateral sclerosis and conditions associated with high morbidity such as myopathies (muscle diseases). Many of these disorders are known to have abnormal protein folding and protein aggregates. Thus, easy to apply methods for the detection of such changes may prove useful diagnostic biomarkers. Raman spectroscopy has shown early promise in the detection of muscle pathology in neuromuscular disorders and is well suited to characterising the conformational profiles relating to protein secondary structure. In this work, we assess if Raman spectroscopy can detect differences in protein structure in muscle in the setting of neuromuscular disease. We utilise in vivo Raman spectroscopy measurements from preclinical models of amyotrophic lateral sclerosis and the myopathy Duchenne muscular dystrophy, together with ex vivo measurements of human muscle samples from individuals with and without myopathy. Using quantitative conformation profiling and matrix factorisation we demonstrate that quantitative 'conformational fingerprinting' can be used to identify changes in protein folding in muscle. Notably, myopathic conditions in both preclinical models and human samples manifested a significant reduction in α-helix structures, with concomitant increases in ß-sheet and, to a lesser extent, nonregular configurations. Spectral patterns derived through non-negative matrix factorisation were able to identify myopathy with a high accuracy (79% in mouse, 78% in human tissue). This work demonstrates the potential of conformational fingerprinting as an interpretable biomarker for neuromuscular disorders.

Ensemble-imbalance-based classification for amyotrophic lateral sclerosis prognostic prediction: identifying short-survival patients at diagnosis.

Prognosticating Amyotrophic Lateral Sclerosis (ALS) presents a formidable challenge due to patients exhibiting different onset sites, progression rates, and survival times. In this study, we have developed and evaluated Machine Learning (ML) algorithms that integrate Ensemble and Imbalance Learning techniques to classify patients into Short and Non-Short survival groups based on data collected during diagnosis. We aimed to identify individuals at high risk of mortality within 24 months of symptom onset through analysis of patient data commonly encountered in daily clinical practice. Our Ensemble-Imbalance approach underwent evaluation employing six ML algorithms as base classifiers. Remarkably, our results outperformed those of individual algorithms, achieving a Balanced Accuracy of 88% and a Sensitivity of 96%. Additionally, we used the Shapley Additive Explanations framework to elucidate the decision-making process of the top-performing model, pinpointing the most important features and their correlations with the target prediction. Furthermore, we presented helpful tools to visualize and compare patient similarities, offering valuable insights. Confirming the obtained results, our approach could aid physicians in devising personalized treatment plans at the time of diagnosis or serve as an inclusion/exclusion criterion in clinical trials.

Fluctuating salience in those living with genetic risk of motor neuron disease: A qualitative interview study.

BACKGROUND: Motor neuron disease (MND) (also known as amyotrophic lateral sclerosis) is a life-limiting neurodegenerative condition. In up to 20% of people with MND, a pathogenic variant associated with autosomal dominant inheritance can be identified. Children of people carrying a pathogenic variant have a 50% chance of inheriting this and a higher, although harder to predict, chance of developing the disease compared to the general adult population. This paper explores the experience of living with the genetic risk of MND. METHODS: We undertook a UK-based interview study with 35 individuals, including: 7 people living with genetically-mediated forms of MND; 24 asymptomatic relatives, the majority of whom had an increased risk of developing the disease; and 4 unrelated partners. RESULTS: We explore how individuals make sense of genetic risk, unpacking the interplay between genetic knowledge, personal perception, experiences of the disease in the family, age and life stage and the implications that living with risk has for different aspects of their lives. We balance an emphasis on the emotional and psychological impact described by participants, with a recognition that the salience of risk fluctuates over time. Furthermore, we highlight the diverse strategies and approaches people employ to live well in the face of uncertainty and the complex ways they engage with the possibility of developing symptoms in the future. Finally, we outline the need for open-ended, tailored support and information provision. CONCLUSIONS: Drawing on wider literature on genetic risk, we foreground how knowledge of MND risk can disrupt individuals' taken-for-granted assumptions on life and perceptions of the future, but also its contextuality, whereby its relevance becomes more prominent at critical junctures. This research has been used in the development of a public-facing resource on the healthtalk.org website. PATIENT OR PUBLIC CONTRIBUTION: People with experience of living with genetic risk were involved throughout the design and conduct of the study and advised on aspects including the topic guide, sampling and recruitment and the developing analysis. Two patient and public involvement contributors joined a formal advisory panel.

Prognostic value of geriatric nutritional risk index in patients with amyotrophic lateral sclerosis.

BACKGROUND: The geriatric nutritional risk index (GNRI) is a prognostic indicator for several diseases, meanwhile, nutrition and inflammation play important roles in the disease progression of amyotrophic lateral sclerosis (ALS). However, the association between the GNRI and ALS remains unknown. METHODS: 443 patients diagnosed with ALS were divided into two groups based on the GNRI levels. Associations between GNRI and survival time were analyzed using Kaplan-Meier curves and compared by the log-rank test. Univariate and multivariate analyses were used to assess their prognostic values for survival time. Spearman correlation analysis was used to evaluate the correlation coefficients between GNRI and other clinical variables. RESULTS: No significant differences were found in diagnostic delay between the two groups. The onset age and disease progression rate (DPR) were significantly lower in high GNRI group while forced vital capacity (FVC), revised version of the ALS functional rating scale (ALSFRS-R), serum albumin and body mass index (BMI) were significantly lower in low GNRI group. Lower GNRI levels were linked with shorter ALS patients' survival time by Kaplan-Meier curves. The univariate and multivariate analysis identified the onset age, gender, onset site, diagnostic delay, DRP and GNRI as predictors of survival time in patients with ALS. CONCLUSION: Nutritional status was closely corelated with ALS progression. The GNRI may be used as a potential prognostic indictor for ALS patients.

Upper limb movements as digital biomarkers in people with ALS.

BACKGROUND: Objective evaluation of people with amyotrophic lateral sclerosis (PALS) in free-living settings is challenging. The introduction of portable digital devices, such as wearables and smartphones, may improve quantifying disease progression and hasten therapeutic development. However, there is a need for tools to characterize upper limb movements in neurologic disease and disability. METHODS: Twenty PALS wore a wearable accelerometer, ActiGraph Insight Watch, on their wrist for six months. They also used Beiwe, a smartphone application that collected self-entry ALS Functional Rating Scale-Revised (ALSFRS-RSE) survey responses every 1-4 weeks. We developed several measures that quantify count and duration of upper limb movements: flexion, extension, supination, and pronation. New measures were compared against ALSFRS-RSE total score (Q1-12), and individual responses to specific questions related to handwriting (Q4), cutting food (Q5), dressing and performing hygiene (Q6), and turning in bed and adjusting bed clothes (Q7). Additional analysis considered adjusting for total activity counts (TAC). FINDINGS: At baseline, PALS with higher Q1-12 performed more upper limb movements, and these movements were faster compared to individuals with more advanced disease. Most upper limb movement metrics had statistically significant change over time, indicating declining function either by decreasing count metrics or by increasing duration metric. All count and duration metrics were significantly associated with Q1-12, flexion and extension counts were significantly associated with Q6 and Q7, supination and pronation counts were also associated with Q4. All duration metrics were associated with Q6 and Q7. All duration metrics retained their statistical significance after adjusting for TAC. INTERPRETATION: Wearable accelerometer data can be used to generate digital biomarkers on upper limb movements and facilitate patient monitoring in free-living environments. The presented method offers interpretable monitoring of patients' functioning and versatile tracking of disease progression in the limb of interest. FUNDING: Mitsubishi-Tanabe Pharma Holdings America, Inc.

Remote pulmonary function testing allows for early identification of need for non-invasive ventilation in a subset of persons with ALS.

The traditional ALS multidisciplinary clinical practice of quarterly respiratory assessment may leave some individuals in danger of developing untreated respiratory insufficiency between visits or beginning non-invasive ventilation (NIV) later than would be optimal. Remote, or home-based, pulmonary function testing (rPFT) allows patients with ALS to perform regular respiratory testing at more frequent intervals in the home. The aim of this study was to determine the clinical benefit of weekly rPFT compared to standard, quarterly in-clinic respiratory assessments: the number of individuals with earlier identification of NIV need, the magnitude of this advance notice, and the individual factors predicting benefit. Participants with ALS (n = 39) completed rPFT training via telemedicine and then completed one year of weekly self-guided assessments in the home. Over this period, 17 individuals exhibited remotely-measured FVC dropping below 50% of predicted, the value often used for recommendation of NIV initiation. In 13 individuals with clinical detection of this event, the median and range of advance notice of need for NIV was 53 (-61-294) days. Prescription of NIV occurred for 21 individuals on the study, six of whom began NIV as a result of remote testing, prior to indication of need as determined by in-person assessments. Weekly home assessments appeared to be of greatest clinical value in a subset of patients with low baseline respiratory test values and rapid respiratory decline. This has potential implications for clinical management of ALS as well as the conduct of clinical trials that rely on respiratory endpoints.

A new potential therapeutic approach for ALS: A case report with NGS analysis.

RATIONALE: Amyotrophic lateral sclerosis (ALS) poses a significant clinical challenge due to its rapid progression and limited treatment options, often leading to deadly outcomes. Looking for effective therapeutic interventions is critical to improve patient outcomes in ALS. PATIENT CONCERNS: The patient, a 75-year-old East Asian male, manifested an insidious onset of right-hand weakness advancing with dysarthria. Comprehensive Next-generation sequencing analysis identified variants in specific genes consistent with ALS diagnosis. DIAGNOSES: ALS diagnosis is based on El Escorial diagnostic criteria. INTERVENTIONS: This study introduces a novel therapeutic approach using artificial intelligence phenotypic response surface (AI-PRS) technology to customize personalized drug-dose combinations for ALS. The patient underwent a series of phases of AI-PRS-assisted trials, initially incorporating a 4-drug combination of Ibudilast, Riluzole, Tamoxifen, and Ropinirole. Biomarkers and regular clinical assessments, including nerve conduction velocity, F-wave, H-reflex, electromyography, and motor unit action potential, were monitored to comprehensively evaluate treatment efficacy. OUTCOMES: Neurophysiological assessments supported the ALS diagnosis and revealed the co-presence of diabetic polyneuropathy. Hypotension during the trial necessitated an adaptation to a 2-drug combinational trial (ibudilast and riluzole). Disease progression assessment shifted exclusively to clinical tests of muscle strength, aligning with the patient's well-being. LESSONS: The study raises the significance of personalized therapeutic strategies in ALS by AI-PRS. It also emphasizes the adaptability of interventions based on patient-specific responses. The encountered hypotension incident highlights the importance of attentive monitoring and personalized adjustments in treatment plans. The described therapy using AI-PRS, offering personalized drug-dose combinations technology is a potential approach in treating ALS. The promising outcomes warrant further evaluation in clinical trials for searching a personalized, more effective combinational treatment for ALS patients.

Cerebrospinal fluid and blood exosomes as biomarkers for amyotrophic lateral sclerosis; a systematic review.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a progressive and fatal motor neuron disease. Due to the limited knowledge about potential biomarkers that help in early diagnosis and monitoring disease progression, today's diagnoses are based on ruling out other diseases, neurography, and electromyography examination, which takes a time-consuming procedure. METHODS: PubMed, ScienceDirect, and Web of Science were explored to extract articles published from January 2015 to June 2023. In the searching strategy following keywords were included; amyotrophic lateral sclerosis, biomarkers, cerebrospinal fluid, serum, and plama. RESULTS: A total number of 6 studies describing fluid-based exosomal biomarkers were included in this study. Aggregated proteins including SOD1, TDP-43, pTDP-43, and FUS could be detected in the microvesicles (MVs). Moreover, TDP-43 and NFL extracted from plasma exosomes could be used as prognostic biomarkers. Also, downregulated miR-27a-3p detected through exoEasy Maxi and exoQuick Kit in the plasma could be measured as a diagnostic biomarker. Eventually, the upregulated level of CORO1A could be used to monitor disease progression. CONCLUSION: Based on the results, each biomarker alone is insufficient to evaluate ALS. CNS-derived exosomes contain multiple ALS-related biomarkers (SOD1, TDP-43, pTDP-43, FUS, and miRNAs) that are detectable in cerebrospinal fluid and blood is a proper alternation. Exosome detecting kits listed as exoEasy, ExoQuick, Exo-spin, ME kit, ExoQuick Plus, and Exo-Flow, are helpful to reach this purpose.

Harnessing Big Data in Amyotrophic Lateral Sclerosis: Machine Learning Applications for Clinical Practice and Pharmaceutical Trials.

The arrival of genotype-specific therapies in amyotrophic lateral sclerosis (ALS) signals the dawn of precision medicine in motor neuron diseases (MNDs). After decades of academic studies in ALS, we are now witnessing tangible clinical advances. An ever increasing number of well-designed descriptive studies have been published in recent years, characterizing typical disease-burden patterns in vivo and post mortem. Phenotype- and genotype-associated traits and "typical" propagation patterns have been described based on longitudinal clinical and biomarker data. The practical caveat of these studies is that they report "group-level", stereotyped trajectories representative of ALS as a whole. In the clinical setting, however, "group-level" biomarker signatures have limited practical relevance and what matters is the meaningful interpretation of data from a single individual. The increasing availability of large normative data sets, national registries, extant academic data, consortium repositories, and emerging data platforms now permit the meaningful interpretation of individual biomarker profiles and allow the categorization of single patients into relevant diagnostic, phenotypic, and prognostic categories. A variety of machine learning (ML) strategies have been recently explored in MND to demonstrate the feasibility of interpreting data from a single patient. Despite the considerable clinical prospects of classification models, a number of pragmatic challenges need to be overcome to unleash the full potential of ML in ALS. Cohort size limitations, administrative hurdles, data harmonization challenges, regulatory differences, methodological obstacles, and financial implications and are just some of the barriers to readily implement ML in routine clinical practice. Despite these challenges, machine-learning strategies are likely to be firmly integrated in clinical decision-making and pharmacological trials in the near future.

The clinical practice guideline for the management of amyotrophic lateral sclerosis in Japan-update 2023.

Amyotrophic lateral sclerosis (ALS) is an adult-onset intractable motor neuron disease characterized by selective degeneration of cortical neurons in the frontotemporal lobe and motor neurons in the brainstem and spinal cord. Impairment of these neural networks causes progressive muscle atrophy and weakness that spreads throughout the body, resulting in life-threatening bulbar palsy and respiratory muscle paralysis. However, no therapeutic strategy has yet been established to halt ALS progression. Although evidence for clinical practice in ALS remains insufficient, novel research findings have steadily accumulated in recent years. To provide updated evidence-based or expert consensus recommendations for the diagnosis and management of ALS, the ALS Clinical Practice Guideline Development Committee, approved by the Japanese Society of Neurology, revised and published the Japanese clinical practice guidelines for the management of ALS in 2023. In this guideline, disease-modifying therapies that have accumulated evidence from randomized controlled trials were defined as "Clinical Questions," in which the level of evidence was determined by systematic reviews. In contrast, "Questions and Answers" were defined as issues of clinically important but insufficient evidence, according to reports of a small number of cases, observational studies, and expert opinions. Based on a literature search performed in February 2022, recommendations were reached by consensus, determined by an independent panel, reviewed by external reviewers, and submitted for public comments by Japanese Society of Neurology members before publication. In this article, we summarize the revised Japanese guidelines for ALS, highlighting the regional and cultural diversity of care processes and decision-making. The guidelines cover a broad range of essential topics such as etiology, diagnostic criteria, disease monitoring and treatments, management of symptoms, respiration, rehabilitation, nutrition, metabolism, patient instructions, and various types of care support. We believe that this summary will help improve the daily clinical practice for individuals living with ALS and their caregivers.

Clinical and Genetic Aspects of Juvenile Amyotrophic Lateral Sclerosis: A Promising Era Emerges.

Juvenile Amyotrophic Lateral Sclerosis is a genetically heterogeneous neurodegenerative disorder, which is frequently misdiagnosed due to low clinical suspicion and little knowledge about disease characteristics. More than 20 different genetic loci have been associated with both sporadic and familial juvenile Amyotrophic Lateral Sclerosis. Currently, almost 40% of cases have an identifiable monogenic basis; type 6, associated with FUS gene variants, is the most prevalent globally. Despite several upper motor neuron-dominant forms being generally associated with long-standing motor symptoms and slowly progressive course, certain subtypes with lower motor neuron-dominant features and early bulbar compromise lead to rapidly progressive motor handicap. For some monogenic forms, there is a well-established genotypic-phenotypic correlation. There are no specific biochemical and neuroimaging biomarkers for the diagnosis of juvenile Amyotrophic Lateral Sclerosis. There are several inherited neurodegenerative and neurometabolic disorders which can lead to the signs of motor neuron impairment. This review emphasizes the importance of high clinical suspicion, assessment, and proper diagnostic work-up for juvenile Amyotrophic Lateral Sclerosis.

Pearls & Oy-sters: Bibrachial Amyotrophy From a Dural Tear.

Bibrachial amyotrophy signifies a clinical phenotype characterized by weakness in both upper extremities with preserved strength in the face, neck, and lower extremities. The underlying causes of bibrachial amyotrophy are broad. We report a patient exhibiting bibrachial amyotrophy who initially received a diagnosis of amyotrophic lateral sclerosis (ALS); however, his clinical course and NCS/EMG were atypical for ALS. Further evaluation demonstrated dural tears with CSF leak, resulting in a compressive extradural fluid collection, ventral myelopathy, and intracranial hypotension. Dural tear and ALS have overlapping features, including the manifestation of the bibrachial amyotrophy phenotype and the presence of T2 hyperintensities in the anterior horn cells, recognized by an "owl's eye" appearance on spine MRI. Clinical and radiologic vigilance is required to identify rare cases of dural tear causing ventral myelopathy that manifest as bibrachial amyotrophy.