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We aimed to compare the ability of diffusion tensor imaging and multi‐compartment spherical mean technique to detect focal tissue damage and in distinguishing between different connectivity patterns associated with varying clinical outcomes in multiple sclerosis (MS). Seventy‐six people diagnosed with MS were scanned using a SIEMENS Prisma Fit 3T magnetic resonance imaging (MRI), employing both conventional (T1w and fluid‐attenuated inversion recovery) and advanced diffusion MRI sequences from which fractional anisotropy (FA) and microscopic FA (μFA) maps were generated. Using automated fiber quantification (AFQ), we assessed diffusion profiles across multiple white matter (WM) pathways to measure the sensitivity of anisotropy diffusion metrics in detecting localized tissue damage. In parallel, we analyzed structural brain connectivity in a specific patient cohort to fully grasp its relationships with cognitive and physical clinical outcomes. This evaluation comprehensively considered different patient categories, including cognitively preserved (CP), mild cognitive deficits (MCD), and cognitively impaired (CI) for cognitive assessment, as well as groups distinguished by physical impact: those with mild disability (Expanded Disability Status Scale [EDSS] <=3) and those with moderate–severe disability (EDSS >3). In our initial objective, we employed Ridge regression to forecast the presence of focal MS lesions, comparing the performance of μFA and FA. μFA exhibited a stronger association with tissue damage and a higher predictive precision for focal MS lesions across the tracts, achieving an R‐squared value of.57, significantly outperforming the R‐squared value of.24 for FA (p‐value <.001). In structural connectivity, μFA exhibited more pronounced differences than FA in response to alteration in both cognitive and physical clinical scores in terms of effect size and number of connections. Regarding cognitive groups, FA differences between CP and MCD groups were limited to 0.5% of connections, mainly around the thalamus, while μFA revealed changes in 2.5% of connections. In the CP and CI group comparison, which have noticeable cognitive differences, the disparity was 5.6% for FA values and 32.5% for μFA. Similarly, μFA outperformed FA in detecting WM changes between the MCD and CI groups, with 5% versus 0.3% of connections, respectively. When analyzing structural connectivity between physical disability groups, μFA still demonstrated superior performance over FA, disclosing a 2.1% difference in connectivity between regions closely associated with physical disability in MS. In contrast, FA spotted a few regions, comprising only 0.6% of total connections. In summary, μFA emerged as a more effective tool than FA in predicting MS lesions and identifying structural changes across patients with different degrees of cognitive and global disability, offering deeper insights into the complexities of MS‐related impairments. [ABSTRACT FROM AUTHOR]

A railway infrastructure capable of supporting a high frequency of light and heavy traffic, sometimes at high speed, requires the implementation of a high quality track. A correct definition of all track components leads to a high degree of safety and comfort for travelers as well as reduced operating costs. One factor that determines the elastic behaviour of the track is the rail fastening system. In this paper, the mechanical, electrical, and environmental sustainability characterization tests based on European standards UNE-EN have been carried out, verifying that the TK04 fastening system with a lateral adjustment of ± 1 cm, manufactured by ThyssenKrupp Gleistechnik GmbH, satisfies the conditions and requirements of European standards UNE-EN for installation on slab track systems for light rail. [ABSTRACT FROM AUTHOR]

Interstitial lung diseases (ILDs) are pathologies affecting the pulmonary interstitium and, less frequently, the alveolar and vascular epithelia. Bronchoalveolar lavage (BAL) is commonly used in ILD evaluation since it allows the sampling of the lower respiratory tract. The prognostic value of BAL cell counts in ILD is unknown. Flow cytometry quantification of lymphocytes and neutrophils in BAL of 1074 real-life consecutive patients were retrospectively correlated with clinical, radiological, anatomopathological, functional/spirometry, and evolutionary data. Cut-offs with predictive value were established at 7% and 5% for lymphocytes and neutrophils, respectively. Three risk stratification groups (Risk-LN) were established: FAVORABLE (lymphocytes > 7% and neutrophils < 5%), INTERMEDIATE (rest of patients), and UNFAVORABLE (lymphocytes < 7% and neutrophils > 5%), showing 75th percentile overall survival (OS) of 10.0 ± 1.4, 5.8 ± 0.6, and 3.0 ± 0.3 years ( p < 0.001), respectively. A scoring model combining Risk-LN and the age of the patients with great predictive capacity for OS on fibrotic and non-fibrotic ILDs is proposed. This score is an independent predictive factor (HR = 1.859, p = 0.002) complementary to the fibrosis status (HR = 2.081, p < 0.001) and the type of treatment. Flow cytometry of BAL provides rapid and accurate quantification of lymphocytes and neutrophils, allowing the establishment of a risk score model that is useful in the clinical management of fibrotic and non-fibrotic ILDs from the time of diagnosis.

Background and Objectives: Recovery of vision after acute optic neuritis (AON) is critical to improving the quality of life of people with demyelinating diseases. The objective of the study was to prospectively assess the changes in visual acuity, retinal layer thickness, and cortical visual network in patients with AON to identify the predictors of permanent visual disability., Methods: We studied a prospective cohort of 88 consecutive patients with AON with 6-month follow-up using high and low-contrast (2.5%) visual acuity, color vision, retinal thickness from optical coherence tomography, latencies and amplitudes of multifocal visual evoked potentials, mean deviation of visual fields, and diffusion-based structural (n = 53) and functional (n = 19) brain MRI to analyze the cortical visual network. The primary outcome was 2.5% low-contrast vision, and data were analyzed with mixed-effects and multivariate regression models., Results: We found that after 6 months, low-contrast vision and quality of vision remained moderately impaired. The thickness of the ganglion cell layer at baseline was a predictor of low-contrast vision 6 months later (ß = 0.49 [CI 0.11-0.88], p = 0.012). The structural cortical visual network at baseline predicted low-contrast vision, the best predictors being the betweenness of the right parahippocampal cortex (ß = -036 [CI -0.66 to 0.06], p = 0.021), the node strength of the right V3 (ß = 1.72 [CI 0.29-3.15], p = 0.02), and the clustering coefficient of the left intraparietal sulcus (ß = 57.8 [CI 12.3-103.4], p = 0.015). The functional cortical visual network at baseline also predicted low-contrast vision, the best predictors being the betweenness of the left ventral occipital cortex (ß = 8.6 [CI: 4.03-13.3], p = 0.009), the node strength of the right intraparietal sulcus (ß = -2.79 [CI: -5.1-0.4], p = 0.03), and the clustering coefficient of the left superior parietal lobule (ß = 501.5 [CI 50.8-952.2], p = 0.03)., Discussion: The assessment of the visual pathway at baseline predicts permanent vision disability after AON, indicating that damage is produced early after disease onset and that it can be used for defining vision impairment and guiding therapy.

Local protein synthesis in axons and dendrites underpins synaptic plasticity. However, the composition of the protein synthesis machinery in distal neuronal processes and the mechanisms for its activity-driven deployment to local translation sites remain unclear. Here, we employed cryo-electron tomography, volume electron microscopy, and live-cell imaging to identify Ribosome-Associated Vesicles (RAVs) as a dynamic platform for moving ribosomes to distal processes. Stimulation via chemically-induced long-term potentiation causes RAV accumulation in distal sites to drive local translation. We also demonstrate activity-driven changes in RAV generation and dynamics in vivo , identifying tubular ER shaping proteins in RAV biogenesis. Together, our work identifies a mechanism for ribosomal delivery to distal sites in neurons to promote activity-dependent local translation., Competing Interests: Competing interests: The authors declare that they have no competing interests.

Huntington's disease (HD) is an inherited neurodegenerative disorder caused by an expanded CAG repeat in the coding sequence of huntingtin protein. Initially, it predominantly affects medium-sized spiny neurons (MSSNs) of the corpus striatum. No effective treatment is still available, thus urging the identification of potential therapeutic targets. While evidence of mitochondrial structural alterations in HD exists, previous studies mainly employed 2D approaches and were performed outside the strictly native brain context. In this study, we adopted a novel multiscale approach to conduct a comprehensive 3D in situ structural analysis of mitochondrial disturbances in a mouse model of HD. We investigated MSSNs within brain tissue under optimal structural conditions utilizing state-of-the-art 3D imaging technologies, specifically FIB/SEM for the complete imaging of neuronal somas and Electron Tomography for detailed morphological examination, and image processing-based quantitative analysis. Our findings suggest a disruption of the mitochondrial network towards fragmentation in HD. The network of interlaced, slim and long mitochondria observed in healthy conditions transforms into isolated, swollen and short entities, with internal cristae disorganization, cavities and abnormally large matrix granules., (© 2024. The Author(s).)

Given their highly polarized morphology and functional singularity, neurons require precise spatial and temporal control of protein synthesis. Alterations in protein translation have been implicated in the development and progression of a wide range of neurological and neurodegenerative disorders, including Huntington's disease (HD). In this study we examined the architecture of polysomes in their native brain context in striatal tissue from the zQ175 knock-in mouse model of HD. We performed 3D electron tomography of high-pressure frozen and freeze-substituted striatal tissue from HD models and corresponding controls at different ages. Electron tomography results revealed progressive remodelling towards a more compacted polysomal architecture in the mouse model, an effect that coincided with the emergence and progression of HD related symptoms. The aberrant polysomal architecture is compatible with ribosome stalling phenomena. In fact, we also detected in the zQ175 model an increase in the striatal expression of the stalling relief factor EIF5A2 and an increase in the accumulation of eIF5A1, eIF5A2 and hypusinated eIF5A1, the active form of eIF5A1. Polysomal sedimentation gradients showed differences in the relative accumulation of 40S ribosomal subunits and in polysomal distribution in striatal samples of the zQ175 model. These findings indicate that changes in the architecture of the protein synthesis machinery may underlie translational alterations associated with HD, opening new avenues for understanding the progression of the disease., Competing Interests: Declaration of competing interest The authors declare no competing interests., (Copyright © 2023. Published by Elsevier Inc.)

Clinical research emphasizes the implementation of rigorous and reproducible study designs that rely on between-group matching or controlling for sources of biological variation such as subject's sex and age. However, corrections for body size (i.e. height and weight) are mostly lacking in clinical neuroimaging designs. This study investigates the importance of body size parameters in their relationship with spinal cord (SC) and brain magnetic resonance imaging (MRI) metrics. Data were derived from a cosmopolitan population of 267 healthy human adults (age 30.1±6.6 years old, 125 females). We show that body height correlated strongly or moderately with brain gray matter (GM) volume, cortical GM volume, total cerebellar volume, brainstem volume, and cross-sectional area (CSA) of cervical SC white matter (CSA-WM; 0.44≤r≤0.62). In comparison, age correlated weakly with cortical GM volume, precentral GM volume, and cortical thickness (-0.21≥r≥-0.27). Body weight correlated weakly with magnetization transfer ratio in the SC WM, dorsal columns, and lateral corticospinal tracts (-0.20≥r≥-0.23). Body weight further correlated weakly with the mean diffusivity derived from diffusion tensor imaging (DTI) in SC WM (r=-0.20) and dorsal columns (-0.21), but only in males. CSA-WM correlated strongly or moderately with brain volumes (0.39≤r≤0.64), and weakly with precentral gyrus thickness and DTI-based fractional anisotropy in SC dorsal columns and SC lateral corticospinal tracts (-0.22≥r≥-0.25). Linear mixture of sex and age explained 26±10% of data variance in brain volumetry and SC CSA. The amount of explained variance increased at 33±11% when body height was added into the mixture model. Age itself explained only 2±2% of such variance. In conclusion, body size is a significant biological variable. Along with sex and age, body size should therefore be included as a mandatory variable in the design of clinical neuroimaging studies examining SC and brain structure., Competing Interests: Declaration of interests Since June 2022, Dr. A.K. Smith has been employed by GE HealthCare. This article was co-authored by Dr. Smith in his personal capacity. The opinions expressed in the article are his in and do not necessarily reflect the views of GE HealthCare. Since August 2022, Dr. M. M. Laganà has been employed by Canon Medical Systems srl, Rome, Italy. This article was co-authored by Dr. M. M. Laganà in her personal capacity. The opinions expressed in the article are her own and do not necessarily reflect the views of Canon Medical Systems. Since September 2023, Dr. Papp has been an employee of Siemens Healthcare AB, Sweden. This article was co-authored by Dr. Papp in his personal capacity. The views and opinions expressed in this article are his own and do not necessarily reflect the views of Siemens Healthcare AB, or Siemens Healthineers AG. Since January 2024, Dr. Barry has been employed by the National Institute of Biomedical Imaging and Bioengineering at the NIH. This article was co-authored by Robert Barry in his personal capacity. The opinions expressed in the article are his own and do not necessarily reflect the views of the NIH, the Department of Health and Human Services, or the United States government. Guillaume Gilbert is an employee of Philips Healthcare. S Llufriu received compensation for consulting services and speaker honoraria from Biogen Idec, Novartis, Bristol Myer Squibb Genzyme, Sanofi Jansen and Merck. The Max Planck Institute for Human Cognitive and Brain Sciences and Wellcome Centre for Human Neuroimaging have institutional research agreements with Siemens Healthcare. NW holds a patent on acquisition of MRI data during spoiler gradients (US 10,401,453 B2). NW was a speaker at an event organized by Siemens Healthcare and was reimbursed for the travel expenses. The other authors declare no competing interests.

Background: We investigated the association between changes in retinal thickness and cognition in people with MS (PwMS), exploring the predictive value of optical coherence tomography (OCT) markers of neuroaxonal damage for global cognitive decline at different periods of disease., Method: We quantified the peripapillary retinal nerve fibre (pRFNL) and ganglion cell-inner plexiform (GCIPL) layers thicknesses of 207 PwMS and performed neuropsychological evaluations. The cohort was divided based on disease duration (≤5 years or >5 years). We studied associations between changes in OCT and cognition over time, and assessed the risk of cognitive decline of a pRFNL≤88 µm or GCIPL≤77 µm and its predictive value., Results: Changes in pRFNL and GCIPL thickness over 3.2 years were associated with evolution of cognitive scores, in the entire cohort and in patients with more than 5 years of disease (p<0.01). Changes in cognition were related to less use of disease-modifying drugs, but not OCT metrics in PwMS within 5 years of onset. A pRFNL≤88 µm was associated with earlier cognitive disability (3.7 vs 9.9 years) and higher risk of cognitive deterioration (HR=1.64, p=0.022). A GCIPL≤77 µm was not associated with a higher risk of cognitive decline, but a trend was observed at ≤91.5 µm in PwMS with longer disease (HR=1.81, p=0.061)., Conclusions: The progressive retinal thinning is related to cognitive decline, indicating that cognitive dysfunction is a late manifestation of accumulated neuroaxonal damage. Quantifying the pRFNL aids in identifying individuals at risk of cognitive dysfunction., Competing Interests: Competing interests: ES received travel reimbursement from Sanofi, Merck and ECTRIMS. EL-S holds a predoctoral grant from the University of Barcelona (APIF) and she received travel support from Sanofi, IP-V received travel reimbursement from Roche and Genzyme, and she holds stock options in Aura Innovative Robotics. Currently, she is an employee at UCB Pharma, her contribution to this work is associated with her previous work at IDIBAPS; MA holds equity shares of Bionure, S.L. and Goodgut S.L. and stock options of Attune Neurosciences. He is currently an employee of Roche, although his contribution to this work is associated with his previous work at IDIBAPS; MS received speaker honoraria from Genzyme, Novartis and Biogen; JMC received speaker honoraria from Sanfi; EF received funding for an ECTRIMS Clinical Training Fellowship Programme; AC is supported by the ECTRIMS post-doc fellowship (2022), previously received a UK MS Society PhD studentship (2020), a Guarantors of Brain “Entry” clinical fellowship (2019), and an ECTRIMS-MAGNIMS fellowship (2018). He received travel reimbursement from UK MS society, ECTRIMS, NAIMS. AS received compensation for consulting services and speaker honoraria from Bayer-Schering, Merck-Serono, Biogen-Idec, Sanofi-Aventis, TEVA, Novartis and Roche; EHML received travel support for international and national meetings from Roche and Sanofi-Genzyme, and honoraria for consultancies from Novartis, Roche and Sanofi before 16 April 2019. She is currently employed by the European Medicines Agency (Human Medicines) since 16 April 2019. This article is related to her activity under Hospital Clinic of Barcelona/IDIBAPS affiliation and consequently, as external activity, it does not represent the views of the Agency or its Committees. She is a member of the International Multiple Sclerosis Visual System (IMSVISUAL) Consortium; PV is a shareholder and has received consultancy fees from Accure Therapeutics SL, Attune Neurosciences, QMenta, Spiral Therapeutix, CLight and NeuroPrex, as well as having held grants from the Instituto de Salud Carlos III and the European Commissions; YB received speaking honoraria from Biogen, Novartis and Genzyme; BS-D received compensation for consulting services and speaker honoraria from Chiesi and Sanofi-Genzyme and holds equity shares of Accure Therapeutics S.L. SL received compensation for consulting services and speaker honoraria from Biogen Idec, Novartis, TEVA, Genzyme, Sanofi, Merck and Bristol-Myers Squibb, and holds grants from the Instituto de Salud Carlos III., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Multiple sclerosis patients would benefit from machine learning algorithms that integrates clinical, imaging and multimodal biomarkers to define the risk of disease activity., Methods: We have analysed a prospective multi-centric cohort of 322 MS patients and 98 healthy controls from four MS centres, collecting disability scales at baseline and 2 years later. Imaging data included brain MRI and optical coherence tomography, and omics included genotyping, cytomics and phosphoproteomic data from peripheral blood mononuclear cells. Predictors of clinical outcomes were searched using Random Forest algorithms. Assessment of the algorithm performance was conducted in an independent prospective cohort of 271 MS patients from a single centre., Results: We found algorithms for predicting confirmed disability accumulation for the different scales, no evidence of disease activity (NEDA), onset of immunotherapy and the escalation from low- to high-efficacy therapy with intermediate to high-accuracy. This accuracy was achieved for most of the predictors using clinical data alone or in combination with imaging data. Still, in some cases, the addition of omics data slightly increased algorithm performance. Accuracies were comparable in both cohorts., Conclusion: Combining clinical, imaging and omics data with machine learning helps identify MS patients at risk of disability worsening., (© 2023. The Author(s).)

Complex diseases such as Multiple Sclerosis (MS) cover a wide range of biological scales, from genes and proteins to cells and tissues, up to the full organism. In fact, any phenotype for an organism is dictated by the interplay among these scales. We conducted a multilayer network analysis and deep phenotyping with multi-omics data (genomics, phosphoproteomics and cytomics), brain and retinal imaging, and clinical data, obtained from a multicenter prospective cohort of 328 patients and 90 healthy controls. Multilayer networks were constructed using mutual information for topological analysis, and Boolean simulations were constructed using Pearson correlation to identified paths within and among all layers. The path more commonly found from the Boolean simulations connects protein MK03, with total T cells, the thickness of the retinal nerve fiber layer (RNFL), and the walking speed. This path contains nodes involved in protein phosphorylation, glial cell differentiation, and regulation of stress-activated MAPK cascade, among others. Specific paths identified were subsequently analyzed by flow cytometry at the single-cell level. Combinations of several proteins (GSK3AB, HSBP1 or RS6) and immune cells (Th17, Th1 non-classic, CD8, CD8 Treg, CD56 neg, and B memory) were part of the paths explaining the clinical phenotype. The advantage of the path identified from the Boolean simulations is that it connects information about these known biological pathways with the layers at higher scales (retina damage and disability). Overall, the identified paths provide a means to connect the molecular aspects of MS with the overall phenotype., Competing Interests: We have read the journal’s policy and the authors of this manuscript have the following competing interests: KK reports no disclosures. NKdR reports no disclosures. AU received grants and contracts from FISM, Novartis, Biogen, Merck, Fondazione Cariplo, Italian Ministry of Health, received honoraria, or consultation fees from Biogen, Roche, Teva, Merck, Genzyme, Novartis. FI reports no disclosures. MC reports no disclosures. HFH has received honoraria for lecturing or advice from Biogen, Merck, Roche, Novartis and Sanofi. TB has received unrestricted research grants from Biogen and Sanofi-Genzyme. SDB reports no disclosures. EH received honoraria for lecturing and advisory board activity from Biogen, Merck and Sanofi-Genzyme and unrestricted research grant from Merck. SBI reports no disclosures. SAdRB reports no disclosures. FP received honoraria and research support from Alexion, Bayer, Biogen, Chugai, Merck Serono, Novartis, Genzyme, MedImmune, Shire, Teva, and serves on scientific advisory boards for Alexion, MedImmune, and Novartis. He has received funding from Deutsche Forschungsgemeinschaft (DFG Exc 257), Bundesministerium fu?r Bildung und Forschung (Competence Network Multiple Sclerosis), Guthy Jackson Charitable Foundation, EU Framework Program 7, National Multiple Sclerosis Society of the USA. AUB is named as inventor on multiple patents and patents pending owned by Charité - Universitätsmedizin Berlin and/or University of California Irvine for visual computing-based motor function analysis, multiple sclerosis serum biomarkers, and retinal image analysis. He is cofounder and holds shares of Motognosis GmbH and Nocturne GmbH. He serves on the executive board and is Treasurer/Secretary of IMSVISUAL. He received research support from BMWi, BMBF, NIH ICTS, the Kathleen C. Moore Foundation and the Guthy- Jackson Charitable Foundation. Priscilla Ba?cker-Koduah is funded by the DFG Excellence grant to FP (DFG exc 257) and is a Junior scholar of the Einstein Foundation. CC received honoraria for speaking from Bayer and research funding from Novartis, unrelated to this study. SA received a conference grant from Celgene and honoraria for speaking from Alexion, Bayer and Roche. JB reports no disclosures. JSR declares funding from GSK & Sanofi and fees from Travere Therapeutics & Singularity Bio. MR reports no disclosures. LGA is founder and hold stocks at ProtATonce. MA is an employee of Hoffman-La Roche AG, yet this article is related to his activity at the Hospital Clinic of Barcelona. EHML is an employee of the European Medicines Agency (Human Medicines) since 16 April 2019, yet this article is related to her activity at the Hospital Clinic of Barcelona and consequently, it does not in any way represent the views of the Agency or its Committees. SL received compensation for consulting services and speaker honoraria from Biogen Idec, Novartis, TEVA, Genzyme, Sanofi and Merck. AS received compensation for consulting services and speaker honoraria from Bayer-Schering, Merck- Serono, Biogen-Idec, Sanofi-Aventis, TEVA, Novartis and Roche. EMH reports no disclosures. Elisabeth Solana received travel reimbursement from Sanofi and ECTRIMS and reports personal fees from Roche Spain. IPV is currently an employee of UCB pharma, yet this article is related to her activity at the Hospital Clinic of Barcelona. She has received travel reimbursement from Roche Spain and Genzyme-Sanofi, European Academy of Neurology, and European Committee for Treatment and Research in Multiple Sclerosis for international and national meetings over the last 3 years; she holds a patent for an affordable eye-tracking system to measure eye movement in neurologic diseases, and she holds stock in Aura Innovative Robotics. JGO reports no disclosures. PV has received consultancy fees and held stocks from Accure Therapeutics SL, Attune Neurosciences Inc, Spiral Therapeutics Inc, QMenta Inc, CLight Inc, NeuroPrex Inc, StimuSIL and Adhera Health Inc, (Copyright: © 2024 Kennedy et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: We aimed to describe the severity of the changes in brain diffusion-based connectivity as multiple sclerosis (MS) progresses and the microstructural characteristics of these networks that are associated with distinct MS phenotypes., Methods: Clinical information and brain MRIs were collected from 221 healthy individuals and 823 people with MS at 8 MAGNIMS centres. The patients were divided into four clinical phenotypes: clinically isolated syndrome, relapsing-remitting, secondary progressive and primary progressive. Advanced tractography methods were used to obtain connectivity matrices. Then, differences in whole-brain and nodal graph-derived measures, and in the fractional anisotropy of connections between groups were analysed. Support vector machine algorithms were used to classify groups., Results: Clinically isolated syndrome and relapsing-remitting patients shared similar network changes relative to controls. However, most global and local network properties differed in secondary progressive patients compared with the other groups, with lower fractional anisotropy in most connections. Primary progressive participants had fewer differences in global and local graph measures compared with clinically isolated syndrome and relapsing-remitting patients, and reductions in fractional anisotropy were only evident for a few connections. The accuracy of support vector machine to discriminate patients from healthy controls based on connection was 81%, and ranged between 64% and 74% in distinguishing among the clinical phenotypes., Conclusions: In conclusion, brain connectivity is disrupted in MS and has differential patterns according to the phenotype. Secondary progressive is associated with more widespread changes in connectivity. Additionally, classification tasks can distinguish between MS types, with subcortical connections being the most important factor., Competing Interests: Competing interests: ES and EL-S received travel reimbursement from Sanofi and ECTRIMS; AC received support from the ECTRIMS-MAGNIMS fellowship (2018) and, was granted a postdoctoral fellowship from ECTRIMS in 2022; AS received compensation for consulting services and speaker honoraria from Merck, Biogen-Idec, Sanofi, Novartis, Roche, Janssen and Horizon Therapeutics; YB received speaking honoraria from Biogen, Novartis and Genzyme; SL received compensation for consulting services and speaker honoraria from Biogen Idec, Novartis, TEVA, Genzyme, Sanofi and Merck. MMS serves on the editorial board of Neurology and Frontiers in Neurology, receives research support from the Dutch MS Research Foundation, Eurostars-EUREKA, ARSEP, Amsterdam Neuroscience, MAGNIMS and ZonMW and has served as a consultant for or received research support from Atara Biotherapeutics, Biogen, Celgene/Bristol Meyers Squibb, Genzyme, MedDay and Merck. HV has received research grants from Pfizer, Merck Serono, Novartis. and Teva; speaker honoraria from Novartis; and consulting fees from Merck Serono, all paid directly to his institution. FB: Steering committee and iDMC member for Biogen, Merck, Roche, EISAI. Consultant for Roche, Biogen, Merck, IXICO, Jansen, Combinostics. Research agreements with Novartis, Merck, Biogen, GE, Roche. Co-founder and shareholder of Queen Square Analytics LTD. MAR received speaker honoraria from Bayer, Biogen, Bristol Myers Squibb, Celgene, Genzyme, Merck Serono, Novartis, Roche, and Teva and research support from the Canadian MS Society and Fondazione Italiana Sclerosi Multipla. MF is editor-in-chief of the Journal of Neurology and Associate Editor of Human Brain Mapping, Neurological Sciences, and Radiology, received compensation for consulting services and/or speaking activities from Alexion, Almirall, Bayer, Biogen, Celgene, Eli Lilly, Genzyme, Merck-Serono, Novartis, Roche, Sanofi, Takeda, and Teva Pharmaceutical Industries, and receives research support from Biogen Idec, Merck-Serono, Novartis, Roche, Teva Pharmaceutical Industries, the Italian Ministry of Health, Fondazione Italiana Sclerosi Multipla, and ARiSLA (Fondazione Italiana di Ricerca per la SLA). BB received financial support by the German Federal Ministry for Education and Research, BMBF, German Competence Network Multiple Sclerosis (KKNMS), grant no.01GI1601I. CL received a research grant by the German Federal Ministry for Education and Research, BMBF, German Competence Network Multiple Sclerosis (KKNMS), grant no.01GI1601I, has received consulting and speaker’s honoraria from Biogen Idec, Bayer Schering, Daiichi Sanykyo, Merck Serono, Novartis, Sanofi, Genzyme and TEVA. AR serves on scientific advisory boards for Novartis, Sanofi-Genzyme, Synthetic MR, TensorMedical, Roche, Biogen, and OLEA Medical, and has received speaker honoraria from Bayer, Sanofi-Genzyme, Merck-Serono, Teva Pharmaceutical Industries, Novartis, Roche, Bristol-Myers and Biogen. JS-G serves as co-editor for Europe on the editorial board of Multiple Sclerosis Journal and as editor-in-chief in Revista de Neurología, receives research support from Fondo de Investigaciones Sanitarias (19/950) and has served as a consultant/speaker for Biogen, Celgene/Bristol Meyers Squibb, Genzyme, Novartis, Merck and Roche. AT has been supported by grants from MRC (MR/S026088/1), NIHR BRC (541/CAP/OC/818837) and RoseTrees Trust (A1332 and PGL21/10079), has had meeting expenses from Merck, Biomedia and Biogen Idec and was UK PI for two clinical trials sponsored by MEDDAY (MS-ON-NCT02220244 and MS-SPI2-NCT02220244). OC acts as a consultant for Novartis and Merck, and has received research funding from: NIHR, UK MS Society, NIHR UCLH BRC, MRC, Rosetrees Trust., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)

Background and Objective: In people with multiple sclerosis (pwMS), concern for potential disease exacerbation or triggering of other autoimmune disorders contributes to vaccine hesitancy. We assessed the humoral and T-cell responses to SARS-CoV-2 after mRNA vaccination, changes in disease activity, and development of antibodies against central or peripheral nervous system antigens., Methods: This was a prospective 1-year longitudinal observational study of pwMS and a control group of patients with other inflammatory neurologic disorders (OIND) who received an mRNA vaccine. Blood samples were obtained before the first dose (T1), 1 month after the first dose (T2), 1 month after the second dose (T3), and 6 (T4), 9 (T5), and 12 (T6) months after the first dose. Patients were assessed for the immune-specific response, annualized relapse rate (ARR), and antibodies to onconeuronal, neural surface, glial, ganglioside, and nodo-paranodal antigens., Results: Among 454 patients studied, 390 had MS (22 adolescents) and 64 OIND; the mean (SD) age was 44 (14) years; 315 (69%) were female; and 392 (87%) were on disease-modifying therapies. Antibodies to the receptor-binding domain were detected in 367 (86%) patients at T3 and 276 (83%) at T4. After a third dose, only 13 (22%) of 60 seronegative patients seroconverted, and 255 (92%) remained seropositive at T6. Cellular responses were present in 381 (93%) patients at T3 and in 235 (91%) patients at T6 including all those receiving anti-CD20 therapies and in 79% of patients receiving fingolimod. At T3 (429 patients) or T6 (395 patients), none of the patients had developed CNS autoantibodies. Seven patients had neural antibodies that were already present before immunization (3 adult patients with MS had MOG-IgG, 2 with MG and 1 with MS had neuronal cell surface antibodies [unknown antigen], and 1 with MS had myelin antibody reactivity [unknown antigen]. Similarly, no antibodies against PNS antigens were identified at T3 (427 patients). ARR was lower in MS and not significantly different in patients with OIND. Although 182 (40%) patients developed SARS-CoV-2 infection, no cases of severe COVID-19 or serious adverse events occurred., Discussion: In this study, mRNA COVID-19 vaccination was safe and did not exacerbate the autoimmune disease nor triggered neural autoantibodies or immune-mediated neurologic disorders. The outcome of patients who developed SARS-CoV-2 infection was favorable., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

Multisite machine-learning neuroimaging studies, such as those conducted by the ENIGMA Consortium, need to remove the differences between sites to avoid effects of the site (EoS) that may prevent or fraudulently help the creation of prediction models, leading to impoverished or inflated prediction accuracy. Unfortunately, we have shown earlier that current Methods Aiming to Remove the EoS (MAREoS, e.g., ComBat) cannot remove complex EoS (e.g., including interactions between regions). And complex EoS may bias the accuracy. To overcome this hurdle, groups worldwide are developing novel MAREoS. However, we cannot assess their effectiveness because EoS may either inflate or shrink the accuracy, and MAREoS may both remove the EoS and degrade the data. In this work, we propose a strategy to measure the effectiveness of a MAREoS in removing different types of EoS. FOR MAREOS DEVELOPERS, we provide two multisite MRI datasets with only simple true effects (i.e., detectable by most machine-learning algorithms) and two with only simple EoS (i.e., removable by most MAREoS). First, they should use these datasets to fit machine-learning algorithms after applying the MAREoS. Second, they should use the formulas we provide to calculate the relative accuracy change associated with the MAREoS in each dataset and derive an EoS-removal effectiveness statistic. We also offer similar datasets and formulas for complex true effects and EoS that include first-order interactions. FOR MACHINE-LEARNING RESEARCHERS, we provide an extendable benchmark website to show: a) the types of EoS they should remove for each given machine-learning algorithm and b) the effectiveness of each MAREoS for removing each type of EoS. Relevantly, a MAREoS only able to remove the simple EoS may suffice for simple machine-learning algorithms, whereas more complex algorithms need a MAREoS that can remove more complex EoS. For instance, ComBat removes all simple EoS as needed for predictions based on simple lasso algorithms, but it leaves residual complex EoS that may bias the predictions based on standard support vector machine algorithms., (Copyright © 2022. Published by Elsevier Inc.)

T 2 -hyperintense lesions are the key imaging marker of multiple sclerosis (MS). Previous studies have shown that the white matter surrounding such lesions is often also affected by MS. Our aim was to develop a new method to visualize and quantify the extent of white matter tissue changes in MS based on relaxometry properties. We applied a fast, multi-parametric quantitative MRI approach and used a multi-component MR Fingerprinting (MC-MRF) analysis. We assessed the differences in the MRF component representing prolongedrelaxation time between patients with MS and controls and studied the relation between this component's volume and structural white matter damage identified on FLAIR MRI scans in patients with MS. A total of 48 MS patients at two different sites and 12 healthy controls were scanned with FLAIR and MRF-EPI MRI scans. MRF scans were analyzed with a joint-sparsity multi-component analysis to obtain magnetization fraction maps of different components, representing tissues such as myelin water, white matter, gray matter and cerebrospinal fluid. In the MS patients, an additional component was identified with increased transverse relaxation times compared to the white matter, likely representing changes in free water content. Patients with MS had a higher volume of the long- component in the white matter of the brain compared to healthy controls (B (95%-CI) = 0.004 (0.0006-0.008), p = 0.02). Furthermore, this MRF component had a moderate correlation (correlation coefficient R 0.47) with visible structural white matter changes on the FLAIR scans. Also, the component was found to be more extensive compared to structural white matter changes in 73% of MS patients. In conclusion, our MRF acquisition and analysis captured white matter tissue changes in MS patients compared to controls. In patients these tissue changes were more extensive compared to visually detectable white matter changes on FLAIR scans. Our method provides a novel way to quantify the extent of white matter changes in MS patients, which is underestimated using only conventional clinical MRI scans., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

The consequences of extremely intense long-term exercise for brain health remain unknown. We studied the effects of strenuous exercise on brain structure and function, its dose-response relationship, and mechanisms in a rat model of endurance training. Five-week-old male Wistar rats were assigned to moderate (MOD) or intense (INT) exercise or a sedentary (SED) group for 16 weeks. MOD rats showed the highest motivation and learning capacity in operant conditioning experiments; SED and INT presented similar results. In vivo MRI demonstrated enhanced global and regional connectivity efficiency and clustering as well as a higher cerebral blood flow (CBF) in MOD but not INT rats compared with SED. In the cortex, downregulation of oxidative phosphorylation complex IV and AMPK activation denoted mitochondrial dysfunction in INT rats. An imbalance in cortical antioxidant capacity was found between MOD and INT rats. The MOD group showed the lowest hippocampal brain-derived neurotrophic factor levels. The mRNA and protein levels of inflammatory markers were similar in all groups. In conclusion, strenuous long-term exercise yields a lesser improvement in learning ability than moderate exercise. Blunting of MOD-induced improvements in CBF and connectivity efficiency, accompanied by impaired mitochondrial energetics and, possibly, transient local oxidative stress, may underlie the findings in intensively trained rats., (© 2022 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals LLC on behalf of New York Academy of Sciences.)

Multiple sclerosis (MS) is a chronic autoimmune disease characterized by demyelinating lesions that are often visible on magnetic resonance imaging (MRI). Segmentation of these lesions can provide imaging biomarkers of disease burden that can help monitor disease progression and the imaging response to treatment. Manual delineation of MRI lesions is tedious and prone to subjective bias, while automated lesion segmentation methods offer objectivity and speed, the latter being particularly important when analysing large datasets. Lesion segmentation can be broadly categorised into two groups: cross-sectional methods, which use imaging data acquired at a single time-point to characterise MRI lesions; and longitudinal methods, which use imaging data from the same subject acquired at two or more different time-points to characterise lesions over time. The main objective of longitudinal segmentation approaches is to more accurately detect the presence of new MS lesions and the growth or remission of existing lesions, which may be effective biomarkers of disease progression and treatment response. This paper reviews articles on longitudinal MS lesion segmentation methods published over the past 10 years. These are divided into traditional machine learning methods and deep learning techniques. PubMed articles using longitudinal information and comparing fully automatic two time point segmentations in any step of the process were selected. Nineteen articles were reviewed. There is an increasing number of deep learning techniques for longitudinal MS lesion segmentation that are promising to help better understand disease progression., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

In recent years, research on network analysis applied to MRI data has advanced significantly. However, the majority of the studies are limited to single networks obtained from resting-state fMRI, diffusion MRI, or gray matter probability maps derived from T1 images. Although a limited number of previous studies have combined two of these networks, none have introduced a framework to combine morphological, structural, and functional brain connectivity networks. The aim of this study was to combine the morphological, structural, and functional information, thus defining a new multilayer network perspective. This has proved advantageous when jointly analyzing multiple types of relational data from the same objects simultaneously using graph- mining techniques. The main contribution of this research is the design, development, and validation of a framework that merges these three layers of information into one multilayer network that links and relates the integrity of white matter connections with gray matter probability maps and resting-state fMRI. To validate our framework, several metrics from graph theory are expanded and adapted to our specific domain characteristics. This proof of concept was applied to a cohort of people with multiple sclerosis, and results show that several brain regions with a synchronized connectivity deterioration could be identified., (© 2022 Massachusetts Institute of Technology.)

Background: The frequency of cognitive impairment (CI) reported in neuromyelitis optica spectrum disorder (NMOSD) is highly variable, and its relationship with demographic and clinical characteristics is poorly understood. We aimed to describe the cognitive profile of NMOSD patients, and to analyse the cognitive differences according to their serostatus; furthermore, we aimed to assess the relationship between cognition, demographic and clinical characteristics, and other aspects linked to health-related quality of life (HRQoL). Methods: This cross-sectional study included 41 patients (median age, 44 years; 85% women) from 13 Spanish centres. Demographic and clinical characteristics were collected along with a cognitive z-score (Rao’s Battery) and HRQoL patient-centred measures, and their relationship was explored using linear regression. We used the Akaike information criterion to model which characteristics were associated with cognition. Results: Fourteen patients (34%) had CI, and the most affected cognitive domain was visual memory. Cognition was similar in AQP4-IgG-positive and -negative patients. Gender, mood, fatigue, satisfaction with life, and perception of stigma were associated with cognitive performance (adjusted R2 = 0.396, p < 0.001). Conclusions: The results highlight the presence of CI and its impact on HRQoL in NMOSD patients. Cognitive and psychological assessments may be crucial to achieve a holistic approach in patient care.

The BDNF Val66Met gene polymorphism is a relevant factor explaining inter-individual differences to TMS responses in studies of the motor system. However, whether this variant also contributes to TMS-induced memory effects, as well as their underlying brain mechanisms, remains unexplored. In this investigation, we applied rTMS during encoding of a visual memory task either over the left frontal cortex (LFC; experimental condition) or the cranial vertex (control condition). Subsequently, individuals underwent a recognition memory phase during a functional MRI acquisition. We included 43 young volunteers and classified them as 19 Met allele carriers and 24 as Val/Val individuals. The results revealed that rTMS delivered over LFC compared to vertex stimulation resulted in reduced memory performance only amongst Val/Val allele carriers. This genetic group also exhibited greater fMRI brain activity during memory recognition, mainly over frontal regions, which was positively associated with cognitive performance. We concluded that BDNF Val66Met gene polymorphism, known to exert a significant effect on neuroplasticity, modulates the impact of rTMS both at the cognitive as well as at the associated brain networks expression levels. This data provides new insights on the brain mechanisms explaining cognitive inter-individual differences to TMS, and may inform future, more individually-tailored rTMS interventions., (© 2022. The Author(s).)

Quadrantanopia caused by inadvertent severing of Meyer's Loop of the optic radiation is a well-recognised complication of temporal lobectomy for conditions such as epilepsy. Dissection studies indicate that the anterior extent of Meyer's Loop varies considerably between individuals. Quantifying this for individual patients is thus an important step to improve the safety profile of temporal lobectomies. Previous attempts to delineate Meyer's Loop using diffusion MRI tractography have had difficulty estimating its full anterior extent, required manual ROI placement, and/or relied on advanced diffusion sequences that cannot be acquired routinely in most clinics. Here we present CONSULT: a pipeline that can delineate the optic radiation from raw DICOM data in a completely automated way via a combination of robust pre-processing, segmentation, and alignment stages, plus simple improvements that bolster the efficiency and reliability of standard tractography. We tested CONSULT on 696 scans of predominantly healthy participants (539 unique brains), including both advanced acquisitions and simpler acquisitions that could be acquired in clinically acceptable timeframes. Delineations completed without error in 99.4% of the scans. The distance between Meyer's Loop and the temporal pole closely matched both averages and ranges reported in dissection studies for all tested sequences. Median scan-rescan error of this distance was 1 mm. When tested on two participants with considerable pathology, delineations were successful and realistic. Through this, we demonstrate not only how to identify Meyer's Loop with clinically feasible sequences, but also that this can be achieved without fundamental changes to tractography algorithms or complex post-processing methods., (© 2021 Commonwealth of Australia. Human Brain Mapping published by Wiley Periodicals LLC.)