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Background: One of the major objectives of the Multiple Sclerosis Data Alliance (MSDA) is to enable better discovery of multiple sclerosis (MS) real-world data (RWD). Methods: We implemented the MSDA Catalogue, which is available worldwide. The current version of the MSDA Catalogue collects descriptive information on governance, purpose, inclusion criteria, procedures for data quality control, and how and which data are collected, including the use of e-health technologies and data on collection of COVID-19 variables. The current cataloguing procedure is performed in several manual steps, securing an effective catalogue. Results: Herein we summarize the status of the MSDA Catalogue as of January 6, 2021. To date, 38 data sources across five continents are included in the MSDA Catalogue. These data sources differ in purpose, maturity, and variables collected, but this landscaping effort shows that there is substantial alignment on some domains. The MSDA Catalogue shows that personal data and basic disease data are the most collected categories of variables, whereas data on fatigue measurements and cognition scales are the least collected in MS registries/cohorts. Conclusions: The Web-based MSDA Catalogue provides strategic overview and allows authorized end users to browse metadata profiles of data cohorts and data sources. There are many existing and arising RWD sources in MS. Detailed cataloguing of MS RWD is a first and useful step toward reducing the time needed to discover MS RWD sets and promoting collaboration.

Made available in DSpace on 2022-04-28T19:46:29Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-11-09 Background and ObjectivesPeople with multiple sclerosis MS are a vulnerable group for severe coronavirus disease 2019 COVID-19, particularly those taking immunosuppressive disease-modifying therapies DMTs. We examined the characteristics of COVID-19 severity in an international sample of people with MS.MethodsData from 12 data sources in 28 countries were aggregated sources could include patients from 1-12 countries. Demographic age, sex, clinical MS phenotype, disability, and DMT untreated, alemtuzumab, cladribine, dimethyl fumarate, glatiramer acetate, interferon, natalizumab, ocrelizumab, rituximab, siponimod, other DMTs covariates were queried, along with COVID-19 severity outcomes, hospitalization, intensive care unit ICU admission, need for artificial ventilation, and death. Characteristics of outcomes were assessed in patients with suspected/confirmed COVID-19 using multilevel mixed-effects logistic regression adjusted for age, sex, MS phenotype, and Expanded Disability Status Scale EDSS score.ResultsSix hundred fifty-seven 28.1% with suspected and 1,683 61.9% with confirmed COVID-19 were analyzed. Among suspected plus confirmed and confirmed-only COVID-19, 20.9% and 26.9% were hospitalized, 5.4% and 7.2% were admitted to ICU, 4.1% and 5.4% required artificial ventilation, and 3.2% and 3.9% died. Older age, progressive MS phenotype, and higher disability were associated with worse COVID-19 outcomes. Compared to dimethyl fumarate, ocrelizumab and rituximab were associated with hospitalization adjusted odds ratio [aOR] 1.56, 95% confidence interval [CI] 1.01-2.41; aOR 2.43, 95% CI 1.48-4.02 and ICU admission aOR 2.30, 95% CI 0.98-5.39; aOR 3.93, 95% CI 1.56-9.89, although only rituximab was associated with higher risk of artificial ventilation aOR 4.00, 95% CI 1.54-10.39. Compared to pooled other DMTs, ocrelizumab and rituximab were associated with hospitalization aOR 1.75, 95% CI 1.29-2.38; aOR 2.76, 95% CI 1.87-4.07 and ICU admission aOR 2.55, 95% CI 1.49-4.36; aOR 4.32, 95% CI 2.27-8.23, but only rituximab was associated with artificial ventilation aOR 6.15, 95% CI 3.09-12.27. Compared to natalizumab, ocrelizumab and rituximab were associated with hospitalization aOR 1.86, 95% CI 1.13-3.07; aOR 2.88, 95% CI 1.68-4.92 and ICU admission aOR 2.13, 95% CI 0.85-5.35; aOR 3.23, 95% CI 1.17-8.91, but only rituximab was associated with ventilation aOR 5.52, 95% CI 1.71-17.84. Associations persisted on restriction to confirmed COVID-19 cases. No associations were observed between DMTs and death. Stratification by age, MS phenotype, and EDSS score found no indications that DMT associations with COVID-19 severity reflected differential DMT allocation by underlying COVID-19 severity.DiscussionUsing the largest cohort of people with MS and COVID-19 available, we demonstrated consistent associations of rituximab with increased risk of hospitalization, ICU admission, and need for artificial ventilation and of ocrelizumab with hospitalization and ICU admission. Despite the cross-sectional design of the study, the internal and external consistency of these results with prior studies suggests that rituximab/ocrelizumab use may be a risk factor for more severe COVID-19. CORe Department of Medicine and Neuroepidemiology Unit Melbourne School of Population and Global Health Menzies Institute for Medical Research University of Tasmania ESAT-STADIUS KU Leuven Department of Neurology Melbourne MS Centre Royal Melbourne Hospital MS International Federation Department of Clinical Neuroscience Swedish MS Registry Department of Neurology CHU Pontchaillou Karolinska Institutet Biomedical Research Institute-Data Science Institute Hasselt University Department of Medical Informatics University Medical Center Department of Computer Science and AI KU Leuven QMENTA Medpace Reference Laboratories Molecular Unit IConquerMS People-Powered Research Network Accelerated Cure Project for MS NeuroTransData Study Group NeuroTransData German MS-Register by the National MS Society MS Forschungs- und Projektentwicklungs-gGmbH MS Register Swansea University COViMS Division of Biostatistics Washington University in St. Louis Mellen Center for Multiple Sclerosis Cleveland Clinic Department of Neuroscience Central Clinical School Monash University Al-Amiri Hospital Kuwait City Dokuz Eylul University Neurology Department Hospital Universitario de CEMIC RELACOEM Australian MS Longitudinal Study Menzies Institute for Medical Research University of Tasmania Bulgarian SmartMS COVID-19 Dataset ABEM-Brazilian MS Patients Association Danish Multiple Sclerosis Registry Department of Neurology University Hospital Rigshospitalet Universidade Estadual Paulista Unesp Faculdade de Medicina REDONE.br-Brazilian Registry of Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorders Irmandade da Santa Casa de Misericórdia de São Paulo Multiple Sclerosis University Center Ramos Mejia Hospital-EMA Imperial College Swansea University Mental Health Area MS and Demyelinating Diseases Hospital Británico de Buenos Aires EMA Servei de Neurologia-Neuroimmunologia Centre d'Esclerosi Múltiple de Catalunya Cemcat Vall d'Hebron Institut de Recerca Vall d'Hebron Hospital Universitari Universitat Autònoma de Barcelona Institute of Experimental Neurology Ospedale San Raffaele Universidade Estadual Paulista Unesp Faculdade de Medicina

Interferon-β, a disease-modifying therapy (DMT) for MS, may be associated with less severe COVID-19 in people with MS.Among 5,568 patients (83.4% confirmed COVID-19), interferon-treated patients had lower risk of severe COVID-19 compared to untreated, but not to glatiramer-acetate, dimethyl-fumarate, or pooled other DMTs.In comparison to other DMTs, we did not find evidence of protective effects of interferon-β on the severity of COVID-19, though compared to the untreated, the course of COVID19 was milder among those on interferon-β. This study does not support the use of interferon-β as a treatment to reduce COVID-19 severity in MS.

Background and Objectives Certain demographic and clinical characteristics, including the use of some disease-modifying therapies (DMTs), are associated with severe acute respiratory syndrome coronavirus 2 infection severity in people with multiple sclerosis (MS). Comprehensive exploration of these relationships in large international samples is needed.Methods Clinician-reported demographic/clinical data from 27 countries were aggregated into a data set of 5,648 patients with suspected/confirmed coronavirus disease 2019 (COVID-19). COVID-19 severity outcomes (hospitalization, admission to intensive care unit [ICU], requiring artificial ventilation, and death) were assessed using multilevel mixed-effects ordered probit and logistic regression, adjusted for age, sex, disability, and MS phenotype. DMTs were individually compared with glatiramer acetate, and anti-CD20 DMTs with pooled other DMTs and with natalizumab.Results Of 5,648 patients, 922 (16.6%) with suspected and 4,646 (83.4%) with confirmed COVID-19 were included. Male sex, older age, progressive MS, and higher disability were associated with more severe COVID-19. Compared with glatiramer acetate, ocrelizumab and rituximab were associated with higher probabilities of hospitalization (4% [95% CI 1–7] and 7% [95% CI 4–11]), ICU/artificial ventilation (2% [95% CI 0–4] and 4% [95% CI 2–6]), and death (1% [95% CI 0–2] and 2% [95% CI 1–4]) (predicted marginal effects). Untreated patients had 5% (95% CI 2–8), 3% (95% CI 1–5), and 1% (95% CI 0–3) higher probabilities of the 3 respective levels of COVID-19 severity than glatiramer acetate. Compared with pooled other DMTs and with natalizumab, the associations of ocrelizumab and rituximab with COVID-19 severity were also more pronounced. All associations persisted/enhanced on restriction to confirmed COVID-19.Discussion Analyzing the largest international real-world data set of people with MS with suspected/confirmed COVID-19 confirms that the use of anti-CD20 medication (both ocrelizumab and rituximab), as well as male sex, older age, progressive MS, and higher disability are associated with more severe course of COVID-19. BACKGROUND AND OBJECTIVES: Certain demographic and clinical characteristics, including the use of some disease-modifying therapies (DMTs), are associated with severe acute respiratory syndrome coronavirus 2 infection severity in people with multiple sclerosis (MS). Comprehensive exploration of these relationships in large international samples is needed. METHODS: Clinician-reported demographic/clinical data from 27 countries were aggregated into a data set of 5,648 patients with suspected/confirmed coronavirus disease 2019 (COVID-19). COVID-19 severity outcomes (hospitalization, admission to intensive care unit [ICU], requiring artificial ventilation, and death) were assessed using multilevel mixed-effects ordered probit and logistic regression, adjusted for age, sex, disability, and MS phenotype. DMTs were individually compared with glatiramer acetate, and anti-CD20 DMTs with pooled other DMTs and with natalizumab. RESULTS: Of 5,648 patients, 922 (16.6%) with suspected and 4,646 (83.4%) with confirmed COVID-19 were included. Male sex, older age, progressive MS, and higher disability were associated with more severe COVID-19. Compared with glatiramer acetate, ocrelizumab and rituximab were associated with higher probabilities of hospitalization (4% [95% CI 1-7] and 7% [95% CI 4-11]), ICU/artificial ventilation (2% [95% CI 0-4] and 4% [95% CI 2-6]), and death (1% [95% CI 0-2] and 2% [95% CI 1-4]) (predicted marginal effects). Untreated patients had 5% (95% CI 2-8), 3% (95% CI 1-5), and 1% (95% CI 0-3) higher probabilities of the 3 respective levels of COVID-19 severity than glatiramer acetate. Compared with pooled other DMTs and with natalizumab, the associations of ocrelizumab and rituximab with COVID-19 severity were also more pronounced. All associations persisted/enhanced on restriction to confirmed COVID-19. DISCUSSION: Analyzing the largest international real-world data set of people with MS with suspected/confirmed COVID-19 confirms that the use of anti-CD20 medication (both ocrelizumab and rituximab), as well as male sex, older age, progressive MS, and higher disability are associated with more severe course of COVID-19.

Personalized treatment is highly desirable in multiple sclerosis (MS). We believe that multidisciplinary measurements including clinical, functional and patient-reported outcome measures in combination with extensive patient profiling can enhance personalized treatment and rehabilitation strategies. We elaborate on four reasons behind this statement: (1) MS disease activity and progression are complex and multidimensional concepts in nature and thereby defy a one-size-fits-all description, (2) functioning, progression, treatment, and rehabilitation effects are interdependent and should be investigated together, (3) personalized healthcare is based on the dynamics of system biology and on technology that confirms a patient’s fundamental biology and (4) inclusion of patient-reported outcome measures can facilitate patient-relevant healthcare. We discuss currently available multidisciplinary MS data initiatives and introduce joint actions to further increase the overall success. With this topical review, we hope to drive the MS community to invest in expanding towards more multidisciplinary and longitudinal data collection.

Background The COVID-19 pandemic has resulted in uncertain access to medical treatment for people with multiple sclerosis (pwMS) all over the world. However, there is no data regarding its impact on access to health care of pwMS from Latin America. Objectives We investigated and described changes in health care delivery for pwMS from Latin America during the COVID-19 pandemic. Methods PwMS from 18 patient organizations of the region completed a web-based survey hosted from May to October 2020. Results A total of 602 pwMS completed the questionnaire. Changes in disease-modifying therapies (DMTs) use: 6.7% of pwMS on continuous DMTs claimed to stopped them; 14.1% of those on infusion therapies declared to postpone their dosing; 68.8% declared delaying the initiation of a DMT. Disruptions in accessing rehabilitation services were reported by 65.7%. Changes in laboratory and MRI monitoring were reported by 30% and 33%, respectively. In a multivariable-adjusted logistic regression model, changes in laboratory monitoring were significantly associated with increased odds of postponing MRI monitoring (OR 4.09 CI95% 2.79–6.00, p Conclusions The COVID-19 pandemic has disrupted all aspects of the routine care for pwMS from Latin America. Consequences are yet to be determined.

Multiple sclerosis (MS) is a chronic disease affecting millions of people worldwide. Through the demyelinating and axonal pathology of MS, the signal conduction in the central nervous system is affected. Evoked potential measurements allow clinicians to monitor this process and can be used for decision support. We share a dataset that contains motor evoked potential (MEP) measurements, in which the brain is stimulated and the resulting signal is measured in the hands and feet. This results in time series of 100 milliseconds long. Typically, both hands and feet are measured in one hospital visit. The dataset contains 5586 visits of 963 patients, performed in day-to-day clinical care over a period of 6 years. The dataset consists of approximately 100,000 MEP. Clinical metadata such as the expanded disability status scale, sex, and age is also available. This dataset can be used to explore the role of evoked potentials in MS research and patient care. It may also be used as a benchmark for time series analysis and predictive modelling. Te authors would like to thank the personnel working at the MS clinic for their help while collecting the data. In particular, we would like to thank Henny Strackx for his help with extracting the data from the local servers, Daisy Mobers for her input on how the measurements were performed, and Filip Van Elsen for his input on the technical aspects of the measurement devices used. Furthermore, we thank Patricia Tielens, Dieter Flament, An Voets, Jorina Nickmans and Benny Daems for their legal counsel and Wim Lamotte for answering our questions about the security measures that had to be taken for data transfer. Finally, we thank P95 for their work in assessing the re-identifcation risk of the dataset. Te computational resources and services used in this work were provided by the VSC (Flemish Supercomputer Center), funded by the Research Foundation - Flanders (FWO) and the Flemish Government - department EWI. Tis research received funding from the Flemish Government under the “Onderzoeksprogramma Artifciële Intelligentie (AI) Vlaanderen” programme. This work was supported by Research Foundation—Flanders (FWO) for ELIXIR Belgium (I002819N), and Hermesfonds for ELIXIR Belgium (AH.2017.051, IO 17001306).

BackgroundPeople with multiple sclerosis (MS) are a vulnerable group for severe COVID-19, particularly those taking immunosuppressive disease-modifying therapies (DMTs). We examined the characteristics of COVID-19 severity in an international sample of people with MS.MethodsData from 12 data-sources in 28 countries were aggregated. Demographic and clinical covariates were queried, alongside COVID-19 clinical severity outcomes, hospitalisation, admission to ICU, requiring artificial ventilation, and death. Characteristics of outcomes were assessed in patients with suspected/confirmed COVID-19 using multilevel mixed-effects logistic regression.Results657 (28.1%) with suspected and 1,683 (61.9%) with confirmed COVID-19 were analysed. Older age, progressive MS-phenotype, and higher disability were associated with worse COVID-19 outcomes. Compared to dimethyl fumarate, ocrelizumab and rituximab were associated with hospitalisation (aOR=1.56,95%CI=1.01-2.41; aOR=2.43,95%CI=1.48-4.02) and ICU admission (aOR=2.30,95%CI=0.98-5.39; aOR=3.93,95%CI=1.56-9.89), though only rituximab was associated with higher risk of artificial ventilation (aOR=4.00,95%CI=1.54-10.39). Compared to pooled other DMTs, ocrelizumab and rituximab were associated with hospitalisation (aOR=1.75,95%CI=1.29-2.38; aOR=2.76,95%CI=1.87-4.07) and ICU admission (aOR=2.55,95%CI=1.49-4.36; aOR=4.32,95%CI=2.27-8.23) but only rituximab with artificial ventilation (aOR=6.15,95%CI=3.09-12.27). Compared to natalizumab, ocrelizumab and rituximab were associated with hospitalisation (aOR=1.86,95%CI=1.13-3.07; aOR=2.88,95%CI=1.68-4.92) and ICU admission (aOR=2.13,95%CI=0.85-5.35; aOR=3.23,95%CI=1.17-8.91), but only rituximab with ventilation (aOR=5.52,95%CI=1.71-17.84). Importantly, associations persisted on restriction to confirmed COVID-19 cases. No associations were observed between DMTs and death.ConclusionsUsing the largest cohort of people with MS and COVID-19 available, we demonstrated consistent associations of rituximab with increased risk of hospitalisation, ICU admission, and requiring artificial ventilation, and ocrelizumab with hospitalisation and ICU admission, suggesting their use may be a risk factor for more severe COVID-19.

The Multiple Sclerosis Data Alliance (MSDA), a global multi-stakeholder collaboration, is working to accelerate research insights for innovative care and treatment for people with multiple sclerosis (MS) through better use of real-world data (RWD). Despite the increasing reliance on RWD, challenges and limitations complicate the generation, collection, and use of these data. MSDA aims to tackle sociological and technical challenges arising with scaling up RWD, specifically focused on MS data. MSDA envisions a patient-centred data ecosystem in which all stakeholders contribute and use big data to co-create the innovations needed to advance timely treatment and care of people with MS. We would like to thank the sponsors of the MS Data Alliance. The MSDA receives income from a range of corporate sponsors, recently including: Biogen, BristolMyersSquibb (formerly Celgene), Canopy Growth Corporation, Genzyme, Icometrix, Janssen, Merck, Mylan, Novartis, QMENTA, Quanterix, Roche. We would like to thank the European MS Platform and the University MS Center of Hasselt University for founding the initiative. Next to this, we would like to thank the other core partners for their continued support: the European Charcot Foundation, The European Institute for Innovation through Health Data, the University of Gottingen and KULeuven. A special thanks to our pioneer registries: the UK MS registry and the German MS registry. Peeters, LM (corresponding author), Agoralaan C Bis, B-3590 Diepenbeek, Belgium. Liesbet.peeters@uhasselt.be

Cytotoxic CD4+ T cells (CD4 CTL) are terminally differentiated T helper cells that contribute to autoimmune diseases, such as multiple sclerosis. We developed a novel triple co-culture transwell assay to study mutual interactions between CD4 CTL, conventional TH cells, and regulatory T cells (Tregs) simultaneously. We show that, while CD4 CTL are resistant to suppression by Tregs in vitro, the conditioned medium of CD4 CTL accentuates the suppressive phenotype of Tregs by upregulating IL-10, Granzyme B, CTLA-4, and PD-1. We demonstrate that CD4 CTL conditioned medium skews memory TH cells to a TH17 phenotype, suggesting that the CD4 CTL induce bystander polarization. In our triple co-culture assay, the CD4 CTL secretome promotes the proliferation of TH cells, even in the presence of Tregs. However, when cell−cell contact is established between CD4 CTL and TH cells, the proliferation of TH cells is no longer increased and Treg-mediated suppression is restored. Taken together, our results suggest that when TH cells acquire cytotoxic properties, these Treg-resistant CD4 CTL affect the proliferation and phenotype of conventional TH cells in their vicinity. By creating such a pro-inflammatory microenvironment, CD4 CTL may favor their own persistence and expansion, and that of other potentially pathogenic TH cells, thereby contributing to pathogenic responses in autoimmune disorders.

Made available in DSpace on 2020-12-12T02:15:20Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-09-01 Multiple Sclerosis International Federation Background: We need high-quality data to assess the determinants for COVID-19 severity in people with MS (PwMS). Several studies have recently emerged but there is great benefit in aligning data collection efforts at a global scale. Objectives: Our mission is to scale-up COVID-19 data collection efforts and provide the MS community with data-driven insights as soon as possible. Methods: Numerous stakeholders were brought together. Small dedicated interdisciplinary task forces were created to speed-up the formulation of the study design and work plan. First step was to agree upon a COVID-19 MS core data set. Second, we worked on providing a user-friendly and rapid pipeline to share COVID-19 data at a global scale. Results: The COVID-19 MS core data set was agreed within 48 hours. To date, 23 data collection partners are involved and the first data imports have been performed successfully. Data processing and analysis is an on-going process. Conclusions: We reached a consensus on a core data set and established data sharing processes with multiple partners to address an urgent need for information to guide clinical practice. First results show that partners are motivated to share data to attain the ultimate joint goal: better understand the effect of COVID-19 in PwMS. Biomedical Research Institute and Data Science Institute Hasselt University Department of Medical Informatics University Medical Center Göttingen MS International Federation ESAT-STADIUS KU Leuven Biomedical Research Institute and Data Science Institute Hasselt University Diepenbeek Belgium/ESAT-STADIUS KU Leuven Clinical Outcomes Research (CORe) Unit The University of Melbourne Department of Neurology CHU Pontchaillou Neuroepidemiology Unit Melbourne School of Population Global Health The University of Melbourne Department of Computer Science and Leuven.AI KU Leuven QMENTA Department of Clinical Neuroscience Swedish MS Registry iConquerMS People-Powered Research Network Accelerated Cure Project for MS NeuroTransData Study Group NeuroTransData MS Forschungs- und Projektentwicklungs-gGmbH UK MS Register COViMS St Louis USA/ Division of Biostatistics Washington University in St. Louis COViMS USA/National Multiple Sclerosis Society Neurology Department Hospital Universitario de CEMIC MSBase Registry Department of Neuroscience Central Clinical School Monash University The Australian MS Longitudinal Study (AMSLS) Menzies Institute for Medical Research University of Tasmania Bulgarian SmartMS COVID-19 Dataset LEOSS Department of Neurology Katholisches Klinikum Bochum Brazilian Multiple Sclerosis Association (ABEM) Cleveland Clinic MS COVID-19 Registry Mellen MS Center Cleveland Clinic Icometrix – Icompanion OptimiseMS Preventive Neurology Unit Queen Mary University of London The Danish Multiple Sclerosis Registry Department of Neurology University Hospital Rigshospitalet Universidade Estadual Paulista (Unesp) Faculdade de Medicina Botucatu/REDONE – Brazilian Registry of Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorders RELACOEM Mental Health Area EMA MS and Demyelinating Diseases Hospital Británico de Buenos Aires – EMA Department of Neurology Strasbourg University Hospital COVISEP Institute of Experimental Neurology Ospedale San Raffaele Melbourne MS Centre Department of Neurology Royal Melbourne Hospital Institut du Cerveau ICM APHP – Hôpital Pitié Salpêtrière Sorbonne University Menzies Institute for Medical Research University of Tasmania Imperial College London Swansea University Multiple Sclerosis University Center Ramos Mejia Hospital – EMA Universidade Estadual Paulista (Unesp) Faculdade de Medicina Botucatu/REDONE – Brazilian Registry of Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorders

Background Evoked potentials (EPs) are a measure of the conductivity of the central nervous system. They are used to monitor disease progression of multiple sclerosis patients. Previous studies only extracted a few variables from the EPs, which are often further condensed into a single variable: the EP score. We perform a machine learning analysis of motor EP that uses the whole time series, instead of a few variables, to predict disability progression after two years. Obtaining realistic performance estimates of this task has been difficult because of small data set sizes. We recently extracted a dataset of EPs from the Rehabiliation & MS Center in Overpelt, Belgium. Our data set is large enough to obtain, for the first time, a performance estimate on an independent test set containing different patients. Methods We extracted a large number of time series features from the motor EPs with the highly comparative time series analysis software package. Mutual information with the target and the Boruta method are used to find features which contain information not included in the features studied in the literature. We use random forests (RF) and logistic regression (LR) classifiers to predict disability progression after two years. Statistical significance of the performance increase when adding extra features is checked. Results Including extra time series features in motor EPs leads to a statistically significant improvement compared to using only the known features, although the effect is limited in magnitude (ΔAUC = 0.02 for RF and ΔAUC = 0.05 for LR). RF with extra time series features obtains the best performance (AUC = 0.75±0.07 (mean and standard deviation)), which is good considering the limited number of biomarkers in the model. RF (a nonlinear classifier) outperforms LR (a linear classifier). Conclusions Using machine learning methods on EPs shows promising predictive performance. Using additional EP time series features beyond those already in use leads to a modest increase in performance. Larger datasets, preferably multi-center, are needed for further research. Given a large enough dataset, these models may be used to support clinicians in their decision making process regarding future treatment.

Additional file 1 Most important TS features / alternative feature preselection algorithms. This file contains tables of the 20 most prominent TS features across the 1000 train/test splits, for both APB and AH anatomies. It also provides a way of obtaining the code used to generate these features. There is also a section on a few alternatives for the feature preselection step. Lastly the process of chosing hyperparameters is discussed and motivated.

BACKGROUND AND OBJECTIVES: Research in Multiple Sclerosis (MS) has recently focused on extracting knowledge from real-world clinical data sources. This type of data is more abundant than data produced during clinical trials and potentially more informative about real-world clinical practice. However, this comes at the cost of less curated and controlled data sets. In this work we aim to predict disability progression by optimally extracting information from longitudinal patient data in the real-world setting, with a special focus on the sporadic sampling problem. METHODS: We use machine learning methods suited for patient trajectories modeling, such as recurrent neural networks and tensor factorization. A subset of 6682 patients from the MSBase registry is used. RESULTS: We can predict disability progression of patients in a two-year horizon with an ROC-AUC of 0.85, which represents a 32% decrease in the ranking pair error (1-AUC) compared to reference methods using static clinical features. CONCLUSIONS: Compared to the models available in the literature, this work uses the most complete patient history for MS disease progression prediction and represents a step forward towards AI-assisted precision medicine in MS. ispartof: COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE vol:208 ispartof: location:Ireland status: published

Insect bite hypersensitivity (IBH), which is a cutaneous allergic reaction to antigens from Culicoides spp., is the most prevalent skin disorder in horses. Misdiagnosis is possible, as IBH is usually diagnosed based on clinical signs. Our study is the first to employ IgE levels against several recombinant Culicoides spp. allergens as an objective, independent, and quantitative phenotype to improve the power to detect genetic variants that underlie IBH. Genotypes of 200 Shetland ponies, 127 Icelandic horses, and 223 Belgian Warmblood horses were analyzed while using a mixed model approach. No single-nucleotide polymorphism (SNP) passed the Bonferroni corrected significance threshold, but several regions were identified within and across breeds, which confirmed previously identified regions of interest and, in addition, identifying new regions of interest. Allergen-specific IgE levels are a continuous and objective phenotype that allow for more powerful analyses when compared to a case-control set-up, as more significant associations were obtained. However, the use of a higher density array seems necessary to fully employ the use of IgE levels as a phenotype. While these results still require validation in a large independent dataset, the use of allergen-specific IgE levels showed value as an objective and continuous phenotype that can deepen our understanding of the biology underlying IBH. The research leading to these results has received funding fromthe EuropeanUnion's Seventh Framework Programme managed by REA-Research Executive Agency, http://ec.europa.eu/research/rea (FP7/2007-2013) under grant agreement No. 606142.

BACKGROUND: There is no data regarding COVID-19 in Multiple Sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) patients in Latin America. OBJECTIVE: The objective of this study was to describe the clinical characteristics and outcomes of patients included in RELACOEM, a LATAM registry of MS and NMOSD patients infected with COVID-19. METHODS: RELACOEM is a longitudinal, strictly observational registry of MS and NMOSD patients who suffer COVID-19 and Dengue in LATAM. Inclusion criteria to the registry were either: (1) a biologically confirmed COVID-19 diagnosis based on a positive result of a COVID-19 polymerase chain reaction (PCR) test on a nasopharyngeal swab; or (2) COVID-19-typical symptoms (triad of cough, fever, and asthenia) in an epidemic zone of COVID-19. Descriptive statistics were performed on demographic and clinical variables. The cohort was later stratified for MS and NMOSD and univariate and multivariate logistic regression analysis was performed to identify variables associated with hospitalizations/intensive critical units (ICU) admission. RESULTS: 145 patients were included in the registry from 15 countries and 51 treating physicians. A total of 129 (89%) were MS patients and 16 (11%) NMOSD. 81.4% patients had confirmed COVID-19 and 18.6% were suspected cases. 23 (15.8%) patients were hospitalized, 9 (6.2%) required ICU and 5 (3.4 %) died due to COVID-19. In MS patients, greater age (OR 1.17, 95% CI 1.05 - 1.25) and disease duration (OR 1.39, 95%CI 1.14-1.69) were associated with hospitalization/ICU. In NMOSD patients, a greater age (54.3 vs. 36 years, p=

The lysis cassette of Pseudomonas aeruginosa phage ϕKMV encodes a holin, endolysin, Rz and Rz1 in the canonical order. It has a tight organization with a high degree of overlapping genes and is highly conserved (between 96 and 100% identity at the protein level) among several other members of the "phiKMV-like viruses." The endolysin KMV45 exhibits characteristics as expected for a signal-arrest-release (SAR) endolysin, whereas the holin KMV44 is a typical pinholin. KMV45 is initially secreted as an inactive, membrane-anchored endolysin, which is subsequently released by membrane depolarization driven by the pinholin KMV44. The SAR domain of KMV45 is necessary for its full enzymatic activity, suggesting a refolding of the catalytic cleft upon release from the membrane. The physical proximity of the catalytic glutamic acid residue close to SAR domain suggests an alternative activation mechanism compared to the SAR endolysin of phages P1, ERA103 and 21. Expression of KMV44 leads to a quick cell lysis when paired with SAR endolysin KMV45, but not with the cytoplasmic phage λ endolysin, indicating the membrane depolarizing function of KMV44 rather than the large hole-making function characteristic of classical holins. ispartof: Bacteriophage vol:1 issue:1 pages:1-1 ispartof: location:United States status: published