Amyotrophic Lateral Sclerosis Subjects Research Articles

An Effective DNA Methylation Biomarker Screening Mechanism for Amyotrophic Lateral Sclerosis (ALS) Based on Comorbidities and Gene Function Analysis.

This study used epigenomic methylation differential expression analysis to identify primary biomarkers in patients with amyotrophic lateral sclerosis (ALS). We combined electronic medical record datasets from MIMIC-IV (United States) and NHIRD (Taiwan) to explore ALS comorbidities in depth and discover any comorbidity-related biomarkers. We also applied word2vec to these two clinical diagnostic medical databases to measure similarities between ALS and other similar diseases and evaluated the statistical assessment of the odds ratio to discover significant comorbidities for ALS subjects. Important and representative DNA methylation biomarker candidates could be effectively selected by cross-comparing similar diseases to ALS, comorbidity-related genes, and differentially expressed methylation loci for ALS subjects. The screened epigenomic and comorbidity-related biomarkers were clustered based on their genetic functions. The candidate DNA methylation biomarkers associated with ALS were comprehensively discovered. Gene ontology annotations were then applied to analyze and cluster the candidate biomarkers into three different groups based on gene function annotations. The results showed that a potential testing kit for ALS detection can be composed of SOD3, CACNA1H, and ERBB4 for effective early screening of ALS using blood samples. By developing an effective DNA methylation biomarker screening mechanism, early detection and prophylactic treatment of high-risk ALS patients can be achieved.

Exploiting the role of CSF NfL, CHIT1, and miR-181b as potential diagnostic and prognostic biomarkers for ALS.

Amyotrophic lateral sclerosis (ALS) is a rare neurodegenerative disorder characterized by relentless and progressive loss of motor neurons. A molecular diagnosis, supported by the identification of specific biomarkers, might promote the definition of multiple biological subtypes of ALS, improving patient stratification and providing prognostic information. Here, we investigated the levels of neurofilament light chain (NfL), chitotriosidase (CHIT1) and microRNA-181b (miR-181b) in the cerebrospinal fluid (CSF) of ALS subjects (N = 210) as well as neurologically healthy and neurological disease controls (N = 218, including N = 74 with other neurodegenerative diseases) from a large European multicentric cohort, evaluating their specific or combined utility as diagnostic and prognostic biomarkers. NfL, CHIT1 and miR-181b all showed significantly higher levels in ALS subjects compared to controls, with NfL showing the most effective diagnostic performance. Importantly, all three biomarkers were increased compared to neurodegenerative disease controls and, specifically, to patients with Alzheimer's disease (AD; N = 44), with NfL and CHIT1 being also higher in ALS than in alpha-synucleinopathies (N = 22). Notably, ALS patients displayed increased CHIT1 levels despite having, compared to controls, a higher prevalence of a polymorphism lowering CHIT1 expression. While no relationship was found between CSF miR-181b and clinical measures in ALS (disease duration, functional disability, and disease progression rate), CSF NfL was the best independent predictor of disease progression and survival. This study deepens our knowledge of ALS biomarkers, highlighting the relative specificity of CHIT1 for ALS among neurodegenerative diseases and appraising the potential diagnostic utility of CSF miR-181b.

Prevalence of anti-myelin oligodendrocyte glycoprotein antibodies across neuroinflammatory and neurodegenerative diseases

Inflammatory central nervous system (CNS) diseases, such as multiple sclerosis (MS) and myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD), are characterized by humoral immune abnormalities. Anti-MOG antibodies are not specific to MOGAD, with their presence described in MS. Autoantibodies may also be present and play a role in various neurodegenerative diseases. Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease driven by motor neuron dysfunction. While immune involvement in ALS has been recognized, the presence of antibodies targeting CNS myelin antigens has not been established. We aimed to establish a live cell-based assay for quantification of serum anti-MOG IgG1 in patients with CNS diseases, including MS and ALS. In total, 771 serum samples from the John L. Trotter MS Center and the Northeast ALS Consortium were examined using a live cell-based assay for detection of anti-MOG IgG1. Samples from three cohorts were tested in blinded fashion: healthy control (HC) subjects, patients with clinically diagnosed MOGAD, and an experimental group of ALS and MS patients. All samples from established MOGAD cases were positive for anti-MOG antibodies, while all HC samples were negative. Anti-MOG IgG1 was detected in 65 of 658 samples (9.9%) from MS subjects and 4 of 108 (3.7%) samples from ALS subjects. The presence of serum anti-MOG IgG1 in MS and ALS patients raises questions about the contribution of these antibodies to disease pathophysiology as well as accuracy of diagnostic approaches for CNS inflammatory diseases.

Exploring the Disease-Associated Microglia State in Amyotrophic Lateral Sclerosis.

Neuroinflammation, and specifically microglia, plays an important but not-yet well-understood role in the pathophysiology of amyotrophic lateral sclerosis (ALS), constituting a potential therapeutic target for the disease. Recent studies have described the involvement of different microglial transcriptional patterns throughout neurodegenerative processes, identifying a new state of microglia: disease-associated microglia (DAM). The aim of this study is to investigate expression patterns of microglial-related genes in ALS spinal cord. We analyzed mRNA expression levels via RT-qPCR of several microglia-related genes in their homeostatic and DAM state in postmortem tissue (anterior horn of the spinal cord) from 20 subjects with ALS-TDP43 and 19 controls donors from the Navarrabiomed Biobank. The expression levels of TREM2, MS4A, CD33, APOE and TYROBP were found to be elevated in the spinal cord from ALS subjects versus controls (p-value < 0.05). However, no statistically significant gene expression differences were observed for TMEM119, SPP1 and LPL. This study suggests that a DAM-mediated inflammatory response is present in ALS, and TREM2 plays a significant role in immune function of microglia. It also supports the role of C33 and MS4A in the physiopathology of ALS.

Insights on the Multifaceted Roles of Wild-Type and Mutated Superoxide Dismutase 1 in Amyotrophic Lateral Sclerosis Pathogenesis.

Amyotrophic Lateral Sclerosis (ALS) is a progressive motor neurodegenerative disease. Cell damage in ALS is the result of many different, largely unknown, pathogenetic mechanisms. Astrocytes and microglial cells play a critical role also for their ability to enhance a deranged inflammatory response. Excitotoxicity, due to excessive glutamate levels and increased intracellular Ca2+ concentration, has also been proposed to play a key role in ALS pathogenesis/progression. Reactive Oxygen Species (ROS) behave as key second messengers for multiple receptor/ligand interactions. ROS-dependent regulatory networks are usually mediated by peroxides. Superoxide Dismutase 1 (SOD1) physiologically mediates intracellular peroxide generation. About 10% of ALS subjects show a familial disease associated with different gain-of-function SOD1 mutations. The occurrence of sporadic ALS, not clearly associated with SOD1 defects, has been also described. SOD1-dependent pathways have been involved in neuron functional network as well as in immune-response regulation. Both, neuron depolarization and antigen-dependent T-cell activation mediate SOD1 exocytosis, inducing increased interaction of the enzyme with a complex molecular network involved in the regulation of neuron functional activity and immune response. Here, alteration of SOD1-dependent pathways mediating increased intracellular Ca2+ levels, altered mitochondria functions and defective inflammatory process regulation have been proposed to be relevant for ALS pathogenesis/progression.

SF2Former: Amyotrophic lateral sclerosis identification from multi-center MRI data using spatial and frequency fusion transformer.

Amyotrophic Lateral Sclerosis (ALS) is a complex neurodegenerative disorder characterized by motor neuron degeneration. Significant research has begun to establish brain magnetic resonance imaging (MRI) as a potential biomarker to diagnose and monitor the state of the disease. Deep learning has emerged as a prominent class of machine learning algorithms in computer vision and has shown successful applications in various medical image analysis tasks. However, deep learning methods applied to neuroimaging have not achieved superior performance in classifying ALS patients from healthy controls due to insignificant structural changes correlated with pathological features. Thus, a critical challenge in deep models is to identify discriminative features from limited training data. To address this challenge, this study introduces a framework called SF2Former, which leverages the power of the vision transformer architecture to distinguish ALS subjects from the control group by exploiting the long-range relationships among image features. Additionally, spatial and frequency domain information is combined to enhance the network's performance, as MRI scans are initially captured in the frequency domain and then converted to the spatial domain. The proposed framework is trained using a series of consecutive coronal slices and utilizes pre-trained weights from ImageNet through transfer learning. Finally, a majority voting scheme is employed on the coronal slices of each subject to generate the final classification decision. The proposed architecture is extensively evaluated with multi-modal neuroimaging data (i.e., T1-weighted, R2*, FLAIR) using two well-organized versions of the Canadian ALS Neuroimaging Consortium (CALSNIC) multi-center datasets. The experimental results demonstrate the superiority of the proposed strategy in terms of classification accuracy compared to several popular deep learning-based techniques.

Increased total daily energy expenditure in mild to moderate ALS: greater contribution from physical activity energy expenditure than hyper-metabolism

Objective It is unknown whether the relative contribution to energy imbalance in amyotrophic lateral sclerosis (ALS) is due to decreased energy intake, or increased energy expenditure from hyper-metabolism and/or physical activity, or both. Methods We studied 10 free-living sporadic ALS subjects with mild to moderate disease and 10 matched healthy controls to address this question. We estimated energy intake by 24-h recall in ALS subjects and three-day food diary in all. We estimated body composition by dual energy X-ray absorptiometry and resting metabolic rate by indirect calorimetry; and measured total daily energy expenditure (TEE) and physical activity-energy expenditure using doubly labeled water. Results Daily energy intake was no different between ALS subjects and controls. Despite lower fat-free mass, unadjusted TEE was higher in ALS subjects than controls (2844 ± 319 vs. 2505 ± 261 kcal/d, p = 0.005 by paired t-test). Compared to controls, hyper-metabolism occurred in 80% of ALS subjects. Physical activity-energy expenditure was higher in ALS subjects than controls (718 ± 262 kcal/d vs. 487 ± 196 kcal/d, p = 0.04). In controls, energy intake matched TEE; in ALS subjects TEE was higher than energy intake. Conclusions We found higher TEE in ALS subjects than controls, with larger contribution to difference from physical activity-energy expenditure than hyper-metabolism. Although daily energy intake in ALS subjects was similar to that in controls, they were unable to compensate for increased energy needs. To accurately determine energy balance and optimize nutrition in ALS, future studies should consider measuring energy intake, energy expenditure, and physical activity.

A store-and-forward cloud-based telemonitoring system for automatic assessing dysarthria evolution in neurological diseases from video-recording analysis

Background and objectives:Patients suffering from neurological diseases may develop dysarthria, a motor speech disorder affecting the execution of speech. Close and quantitative monitoring of dysarthria evolution is crucial for enabling clinicians to promptly implement patients’ management strategies and maximizing effectiveness and efficiency of communication functions in term of restoring, compensating or adjusting. In the clinical assessment of orofacial structures and functions, at rest condition or during speech and non-speech movements, a qualitative evaluation is usually performed, throughout visual observation. Methods:To overcome limitations posed by qualitative assessments, this work presents a store-and-forward self-service telemonitoring system that integrates, within its cloud architecture, a convolutional neural network (CNN) for analyzing video recordings acquired by individuals with dysarthria. This architecture – called facial landmark Mask RCNN – aims at locating facial landmarks as a prior for assessing the orofacial functions related to speech and examining dysarthria evolution in neurological diseases. Results:When tested on the Toronto NeuroFace dataset, a publicly available annotated dataset of video recordings from patients with amyotrophic lateral sclerosis (ALS) and stroke, the proposed CNN achieved a normalized mean error equal to 1.79 on localizing the facial landmarks. We also tested our system in a real-life scenario on 11 bulbar-onset ALS subjects, obtaining promising outcomes in terms of facial landmark position estimation. Discussion and conclusions:This preliminary study represents a relevant step towards the use of remote tools to support clinicians in monitoring the evolution of dysarthria.

Large-scale differentiation of iPSC-derived motor neurons from ALS and control subjects

Using induced pluripotent stem cells (iPSCs) to understand the mechanisms of neurological disease holds great promise; however, there is a lack of well-curated lines from a large array of participants. Answer ALS has generated over 1,000 iPSC lines from control and amyotrophic lateral sclerosis (ALS) patients along with clinical and whole-genome sequencing data. The current report summarizes cell marker and gene expression in motor neuron cultures derived from 92 healthy control and 341 ALS participants using a 32-day differentiation protocol. This is the largest set of iPSCs to be differentiated into motor neurons, and characterization suggests that cell composition and sex are significant sources of variability that need to be carefully controlled for in future studies. These data are reported as a resource for the scientific community that will utilize Answer ALS data for disease modeling using a wider array of omics being made available for these samples.

Dysregulation of Gene Expressions in Multiple Sclerosis: TNFSF13B and Other Candidate Genes.

In previous investigations of combined miRNAs/mRNAs expressions in neurodegenerative diseases like Multiple Sclerosis (MS) and Amyotrophic Lateral Sclerosis (ALS) we have targeted some interesting genes and molecular pathways that needed further confirmation. By nanofluidic qPCR analysis, we aimed to verify the expression of genes that resulted differentially expressed in the previous analyses. Data from MS patients - either the pediatric and the adult occurrence of the disease (adMS and pedMS, respectively) - was compared to age-matched healthy groups. As neurological controls we recruited a cohort of ALS subjects, considering published searches of possible genetic similarities between the two diseases. The main results confirmed the involvement of most of the investigated genes in pedMS and adMS, like BACH2 and MICAL3. On the other hand, suggestive MS candidate genes like TNFSF13B showed an interesting trend possibly influenced by interfering factors, such as concomitant disease-modifying treatments; it is worth noting that TNFSF13B was one of the genes upregulated in ALS compared to age-matched adMS patients, together with the transcription factor TFDP1. Although with caution due to the small sample size, this study confirms the interest in transcriptomic analysis supported by integrated and educated bioinformatics evaluations, to shed further light in complex neurological diseases.

Modulation of spontaneous motor unit potentials by a new motor cortical magnetic stimulation method in amyotrophic lateral sclerosis

Patients with amyotrophic lateral sclerosis (ALS) show altered cortical excitability. In this study, we measure modulation of spontaneous motor unit potentials (sMUPs) in hand muscles by multifocal cortical stimulation with a newly developed wearable transcranial rotating permanent magnet stimulator (TRPMS). We conducted cross-sectional and longitudinal electromyographic assessments in 40 and 20 ALS patients, respectively, of the stimulation-induced peak increase in the count of sMUPs in two hand muscles modulated by unilateral TRPMS stimulation of the primary motor cortex. We measured peak sMUP counts during several short sessions consisting of 10 stimuli over 60s and 30s post-stimulation periods. The longitudinal component involved an initial assessment at an early stage of the disease and up to five follow-up assessments at least 3months apart. TRPMS stimulation produced no device-related adverse effects. It showed an inverted V-shaped modulation of the peak sMUP counts as a function of ALS functional rating scale revised scores. The ratios of ALS subjects showing peak sMUP count increases between early and intermediate stages (χ2 = 4.086, df = 1, p = 0.043) and intermediate and late stages (χ2 = 4.29, df = 1, p = 0.038) in cross-sectional data were significantly different. Longitudinal assessment also produced a significant (z = 2.31, p = 0.021) result, with all subjects showing a post-initial visit increase in peak sMUP counts. These results are consistent with delayed onset of upper motor neuronal dysfunction with respect to onset of clinical features. However, the above results need to be confirmed in a larger sample of patients and with multiple lines of evidence.

HLA and amyotrophic lateral sclerosis: a systematic review and meta-analysis

Background: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease associated with loss of upper and lower motor neurones. It leads to death by respiratory failure and has a typical prognosis of 2–3 years. The immune system has been shown to play a role in the pathophysiology of ALS. Some of the most important immune genes are within the human leukocyte antigen (HLA) region, and a recent genome-wide association study (GWAS) has identified a risk allele for ALS within the HLA region. Older studies have also suggested an HLA association with ALS, with certain HLA alleles showing differing expression between patients and controls. This systematic review and meta-analysis examines the previous studies performed in this field. Methods: We used established publication search engines. Findings were excluded if they did not meet the selection criteria. We then undertook statistical meta-analysis on the eligible papers, using a fixed effects model. Results: There were eight eligible papers. There were three statistically significant meta-analysis findings, although these would not be significant after correction for multiple comparisons. The frequencies of HLA-A9 and HLA-DR4 genotypes were lower in ALS subjects than controls, and HLA-B35 was higher in ALS subjects. Discussion: This systematic review and meta-analysis do not confirm all the previously reported associations of HLA with ALS, but shows three alleles of interest. However, there are limitations to the studies, which include the use of older serotyping methodology and the small numbers of subjects. Given the recent GWAS association with HLA, further modern HLA studies are warranted.

Body composition in amyotrophic lateral sclerosis subjects and its effect on disease progression and survival

Motor neuron degeneration and malnutrition alter body composition in amyotrophic lateral sclerosis (ALS). Resulting losses of weight, fat mass (FM), and fat-free mass (FFM) shorten survival. Nutritional management relies on body weight or BMI; neither reliably indicates malnutrition nor differentiates body compartments. We aimed to 1) develop an equation to compute FM and FFM using clinical data, validated against DXA; and 2) examine the effect of computed FM and FFM on disease course and survival. We studied 364 ALS patients from 3 cohorts. In Cohort #1 we used logistic regression on clinical and demographic data to create an equation (test cohort). In Cohort #2 we validated FM and FFM computed using this equation against DXA (validation cohort). In Cohort #3, we examined the effect of computed body composition on disease course and survival. In Cohort #1 (n=29) the model incorporated sex, age, BMI, and bulbar-onset to create an equation to estimate body fat: % body fat=1.73 - [19.80*gender (1 if male or 0 if female)] + [0.25*weight (kg)] + [0.95*BMI (kg/m2)] - (5.20*1 if bulbar-onset or *0 if limb-onset). In Cohort #2 (n=104), body composition using this equation, compared to other published equations, showed the least variance from DXA values. In Cohort #3 (n=314), loss of body composition over 6 mo was greater in males. Adjusted survival was predicted by low baseline FM (HR: 1.39; 95% CI: 1.07, 1.80), and loss of FM (HR: 1.87; 95% CI: 1.30, 2.69) and FFM (HR: 1.73; 95% CI: 1.20, 2.49) over 6 mo. Our equation broadens the traditional nutritional evaluation in clinics and reliably estimates body composition. Measuring body composition could target FM as a focus for nutritional management to ensure adequate energy intake and complement measures, such as the ALS functional rating scale-revised score and forced vital capacity, currently used.

A specific gene-splicing alteration in the SNRNP70 gene as a hallmark of an ALS subtype.

Amyotrophic lateral sclerosis (ALS) has been considered as one of the progressive neurodegenerative diseases. Numerous genetic factors in divergent molecular pathways have been identified as causative factors of ALS. However, the underlying molecular mechanism that causes this disease remains undetermined; as a result, this has driven the search to find consensus disease-specific hallmarks. In this study, we focused on the alteration of the ratio of two specific gene-splicing events in the SNRNP70 gene from RNA-seq data derived from patients with ALS and control subjects. The splicing profile was significantly and specifically changed in one previously identified ALS subtype. Conversely, the gene expression profile of other ALS cases containing a splicing alteration in the SNRNP70 gene was similar to that of the subtype, whereas ALS cases without this change have exhibited less similarity. These results indicate that this splicing event in the SNRNP70 gene could represent a novel and broadly applicable molecular hallmark of a subtype of ALS.

Altered Metabolic Profiles of the Plasma of Patients with Amyotrophic Lateral Sclerosis.

Currently, there is no objective biomarker to indicate disease progression and monitor therapeutic effects for amyotrophic lateral sclerosis (ALS). This study aimed to identify plasma biomarkers for ALS using a targeted metabolomics approach. Plasma levels of 185 metabolites in 36 ALS patients and 36 age- and sex-matched normal controls (NCs) were quantified using an assay combining liquid chromatography with tandem mass spectrometry and direct flow injection. Identified candidates were correlated with the scores of the revised ALS Functional Rating Scale (ALSFRS-r). Support vector machine (SVM) learning applied to selected metabolites was used to differentiate ALS and NC subjects. Forty-four metabolites differed significantly between ALS and NC subjects. Significant correlations with ALSFRS-r score were seen in 23 metabolites. Six of them showing potential to distinguish ALS from NC—asymmetric dimethylarginine (area under the curve (AUC): 0.829), creatinine (AUC: 0.803), methionine (AUC: 0.767), PC-acyl-alkyl C34:2 (AUC: 0.808), C34:2 (AUC: 0.763), and PC-acyl-acyl C42:2 (AUC: 0.751)—were selected for machine learning. The SVM algorithm using selected metabolites achieved good performance, with an AUC of 0.945. In conclusion, our findings indicate that a panel of metabolites were correlated with disease severity of ALS, which could be potential biomarkers for monitoring ALS progression and therapeutic effects.

Urine specific gravity to identify and predict hydration need in ALS

Introduction: Multiple factors contribute to increased risk of dehydration in amyotrophic lateral sclerosis (ALS), which contributes to shortened survival independent of nutritional status. The assessment of hydration by doubly labeled water is restricted due to the limited availability of this gold standard technique for clinical use. This prompted us to examine the utility of urine-specific gravity (USG) as a predictor of hydration need in ALS subjects. Material and Methods: Using data from a multicenter study of 80 ALS subjects with 250 visits, we conducted a secondary analysis of the original data set from doubly labeled water experiments. We used a cross-section of the data (one visit per 75 subjects) in the model selection step (“test set”), and a repeated measures analysis in the validation step with data from 63 subjects and 142 follow-up visits. The sensitivity to detect inadequate water turnover rate (a surrogate for water intake) was the goal of the predictive model presented for clinical use. Results and discussion: The final predictive model to estimate water requirement included USG, gender, body mass index, and the ALSFRS gross motor subscale score. We developed a best-fit equation to estimate water intake from USG, determine hydration status, and improve clinical care of real-world ALS subjects.

Longitudinal Quantitative MRI Evaluation of Muscle Involvement in Amyotrophic Lateral Sclerosis.

Background: Biomarkers of disease progression and outcome measures are still lacking for patients with amyotrophic lateral sclerosis (ALS). Muscle MRI can be a promising candidate to track longitudinal changes and to predict response to the therapy in clinical trials.Objective: Our aim is to apply quantitative muscle MRI in the evaluation of disease progression, focusing on thigh and leg muscles of patients with ALS, and to explore the correlation between radiological and clinical scores.Methods: We enrolled newly diagnosed patients with ALS, longitudinally scored using the ALS Functional Rating Scale-Revised (ALSFRS-R), who underwent a 3T muscle MRI protocol including a 6-point Dixon gradient-echo sequence and multi-echo turbo spin echo (TSE) T2-weighted sequence for quantification of fat fraction (FF), cross-sectional area (CSA), and water T2 (wT2). A total of 12 muscles of the thigh and six muscles of the leg were assessed by the manual drawing of 18 regions of interest (ROIs), for each side. A group of 11 age-matched healthy controls (HCs) was enrolled for comparison.Results: 15 patients (M/F 8/7; mean age 62.2 years old, range 29–79) diagnosed with possible (n = 2), probable (n = 12), or definite (n = 1) ALS were enrolled. Eleven patients presented spinal onset, whereas four of them had initial bulbar involvement. All patients performed MRI at T0, nine of them at T1, and seven of them at T2. At baseline, wT2 was significantly elevated in ALS subjects compared to HCs for several muscles of the thigh and mainly for leg muscles. By contrast, FF was elevated in few muscles, and mainly at the level of the thigh. The applied mixed effects model showed that FF increased significantly in the leg muscles over time (mainly in the triceps surae) and that wT2 decreased significantly in line with worsening in the leg subscore of ALSFRS-R, mainly at the leg level and in the anterior and medial compartment of the thigh.Conclusions: Quantitative MRI represents a non-invasive tool that is able to outline the trajectory of pathogenic modifications at the muscle level in ALS. In particular, wT2 was found to be increased early in the clinical history of ALS and also tended to decrease over time, also showing a positive correlation with leg subscore of ALSFRS-R.

Acute intermittent hypoxia and respiratory muscle recruitment in people with amyotrophic lateral sclerosis: A preliminary study

Respiratory failure is the main cause of death in amyotrophic lateral sclerosis (ALS). Since no effective treatments to preserve independent breathing are available, there is a critical need for new therapies to preserve or restore breathing ability. Since acute intermittent hypoxia (AIH) elicits spinal respiratory motor plasticity in rodent ALS models, and may restore breathing ability in people with ALS, we performed a proof-of-principle study to investigate this possibility in ALS patients. Quiet breathing, sniff nasal inspiratory pressure (SNIP) and maximal inspiratory pressure (MIP) were tested in 13 persons with ALS and 10 age-matched controls, before and 60 min post-AIH (15, 1 min episodes of 10% O2, 2 min normoxic intervals) or sham AIH (continuous normoxia). The root mean square (RMS) of the right and left diaphragm, 2nd parasternal, scalene and sternocleidomastoid muscles were monitored. A vector analysis was used to calculate summated vector magnitude (Mag) and similarity index (SI) of collective EMG activity during quiet breathing, SNIP and MIP maneuvers. AIH facilitated tidal volume and minute ventilation (treatment main effects: p < 0.05), and Mag (ie. collective respiratory muscle activity; p < 0.001) during quiet breathing in ALS and control subjects, but there was no effect on SI during quiet breathing. SNIP SI decreased in both groups post-AIH (p < 0.005), whereas Mag was unchanged (p = 0.09). No differences were observed in SNIP or MIP post AIH in either group. Discomfort was not reported during AIH by any subject, nor were adverse events observed. Thus, AIH may be a safe way to increase collective inspiratory muscle activity during quiet breathing in ALS patients, although a single AIH presentation was not sufficient to significantly increase peak inspiratory pressure generation. These preliminary results provide evidence that AIH may improve breathing function in people with ALS, and that future studies of prolonged, repetitive AIH protocols are warranted.

Disruption of the white matter structural network and its correlation with baseline progression rate in patients with sporadic amyotrophic lateral sclerosis

ObjectiveThere is increasing evidence that amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease impacting large-scale brain networks. However, it is still unclear which structural networks are associated with the disease and whether the network connectomics are associated with disease progression. This study was aimed to characterize the network abnormalities in ALS and to identify the network-based biomarkers that predict the ALS baseline progression rate.MethodsMagnetic resonance imaging was performed on 73 patients with sporadic ALS and 100 healthy participants to acquire diffusion-weighted magnetic resonance images and construct white matter (WM) networks using tractography methods. The global and regional network properties were compared between ALS and healthy subjects. The single-subject WM network matrices of patients were used to predict the ALS baseline progression rate using machine learning algorithms.ResultsCompared with the healthy participants, the patients with ALS showed significantly decreased clustering coefficient Cp (P = 0.0034, t = 2.98), normalized clustering coefficient γ (P = 0.039, t = 2.08), and small‐worldness σ (P = 0.038, t = 2.10) at the global network level. The patients also showed decreased regional centralities in motor and non-motor systems including the frontal, temporal and subcortical regions. Using the single-subject structural connection matrix, our classification model could distinguish patients with fast versus slow progression rate with an average accuracy of 85%.ConclusionDisruption of the WM structural networks in ALS is indicated by weaker small-worldness and disturbances in regions outside of the motor systems, extending the classical pathophysiological understanding of ALS as a motor disorder. The individual WM structural network matrices of ALS patients are potential neuroimaging biomarkers for the baseline disease progression in clinical practice.

Experimentally verified finite element modeling and analysis of a conformable piezoelectric sensor

This paper presents development of a three dimensional finite element model for simulations of a conformable piezoelectric sensor utilizing COMSOL Multiphysics. The sensor has a multi-layer structure composed of four circular piezoelectric elements arranged in an array structure laminated on a soft substrate and is capable of providing a strain mapping of soft tissue surfaces for spatiotemporal biokinematic assessment of the facial skin. Here, we provide the finite element method (FEM) for the sensor to predict its electromechanical behavior. This paper studies the effect of the design parameters such as dimensions of the piezoelectric sensor and the substrate on voltage sensitivity and sensor compliance. The FEM model is established to understand the underlying physics and guide the mechanical characterization of the system. The developed model is experimentally verified through two series of tests. The first set of tests involve comprehensive in vitro mechanical testing to provide accurate measurements of strain during compression, stretching, and bending. The second set of tests present in vivo experiments on healthy and amyotrophic lateral sclerosis subjects. The experimentally verified FEM model provides a detailed insight into analyzing the response of the sensor which establishes new design rules for next generations of conformable piezoelectric sensors.