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Abstract Objective The present study aimed to identify the clinical and MRI features of the distinct cognitive phenotypes in pediatric multiple sclerosis (pedMS). Methods PedMS patients (n = 73) and healthy controls (n = 30) underwent clinical examination and 3.0T MRI. All patients completed neuropsychological testing, and cognitive phenotypes were identified by performing K‐means clustering on cognitive scores. MRI metrics included brain T2‐hyperintese lesion volume and normalized brain volumes. Within seven cognitively relevant cortical networks, structural disconnectivity (i.e., the mean percentage of streamlines connecting each pair of cortical regions passing through a lesion) and resting‐state (RS) functional connectivity (FC) were estimated. Results Three cognitive phenotypes emerged: Preserved cognition (PC; n = 27, 37%), mild verbal learning and memory/semantic fluency involvement (MVS; n = 28, 38%), and multidomain involvement (MI; n = 18, 25%). Age, sex, and disease duration did not differ among groups. Compared with healthy subjects, PC patients had decreased RS FC within the default mode network (p = 0.045); MVS patients exhibited lower cortical volume and reduced RS FC within the frontoparietal network (all p = 0.045); and MI patients showed decreased volumes in all brain compartments except the hippocampus, and reduced RS FC within the frontoparietal network (all p ≤ 0.045). Compared to PC, MI patients had more severe disability and higher structural disconnectivity within four cortical networks (all p ≤ 0.045). Compared to PC and MVS, MI patients had lower intelligence quotient (all p ≤ 0.005). Interpretation We identified three cognitive phenotypes in pedMS that demonstrate the existence of a spectrum of impairment. Such phenotypes showed distinct clinical and MRI characteristics that contributed to explain their cognitive profiles.

ADCs have emerged as a promising class of therapeutics, combining the targeting specificity of monoclonal antibodies with the cytotoxic potency of small-molecule drugs. Although the majority of approved ADCs are still based on microtubule binder payloads, the recent success of topoisomerase I inhibitors has revitalized interest in the identification of novel agents overcoming present limitations in the field including narrow therapeutic window and chemoresistance. The success of DNA binders as payload for ADCs has been very limited, up to now, due, among other factors, to high hydrophobicity and planar chemical structures resulting in most cases in ADCs with a strong tendency to aggregate, poor plasma stability, and limited therapeutic index. Some of these molecules, however, continue to be of interest due to their favorable properties in terms of cytotoxic potency even in chemoresistant settings, bystander and immunogenic cell death effects, and known combinability with approved drugs. We critically evaluated several clinically tested ADCs containing DNA binders, focusing on payload physicochemical properties, cytotoxic potency, and obtained clinical results. Our analysis suggests that further exploration of certain chemical classes, specifically anthracyclines and duocarmycins, based on the optimization of physicochemical parameters, reduction of cytotoxic potency, and careful design of targeting molecules is warranted. This approach will possibly result in a novel generation of payloads overcoming the limitations of clinically validated ADCs.

Despite important efforts to solve the clinico-radiological paradox, correlation between lesion load and physical disability in patients with multiple sclerosis remains modest. One hypothesis could be that lesion location in corticospinal tracts plays a key role in explaining motor impairment. In this study, we describe the distribution of lesions along the corticospinal tracts from the cortex to the cervical spinal cord in patients with various disease phenotypes and disability status. We also assess the link between lesion load and location within corticospinal tracts, and disability at baseline and 2-year follow-up. We retrospectively included 290 patients (22 clinically isolated syndrome, 198 relapsing remitting, 39 secondary progressive, 31 primary progressive multiple sclerosis) from eight sites. Lesions were segmented on both brain (T2-FLAIR or T2-weighted) and cervical (axial T2- or T2*-weighted) MRI scans. Data were processed using an automated and publicly available pipeline. Brain, brainstem and spinal cord portions of the corticospinal tracts were identified using probabilistic atlases to measure the lesion volume fraction. Lesion frequency maps were produced for each phenotype and disability scores assessed with Expanded Disability Status Scale score and pyramidal functional system score. Results show that lesions were not homogeneously distributed along the corticospinal tracts, with the highest lesion frequency in the corona radiata and between C2 and C4 vertebral levels. The lesion volume fraction in the corticospinal tracts was higher in secondary and primary progressive patients (mean = 3.6 ± 2.7% and 2.9 ± 2.4%), compared to relapsing-remitting patients (1.6 ± 2.1%, both P

Spinal cord lesions detected on MRI hold important diagnostic and prognostic value for multiple sclerosis. Previous attempts to correlate lesion burden with clinical status have had limited success, however, suggesting that lesion location may be a contributor. Our aim was to explore the spatial distribution of multiple sclerosis lesions in the cervical spinal cord, with respect to clinical status. We included 642 suspected or confirmed multiple sclerosis patients (31 clinically isolated syndrome, and 416 relapsing-remitting, 84 secondary progressive, and 73 primary progressive multiple sclerosis) from 13 clinical sites. Cervical spine lesions were manually delineated on T2- and T2*-weighted axial and sagittal MRI scans acquired at 3 or 7 T. With an automatic publicly-available analysis pipeline we produced voxelwise lesion frequency maps to identify predilection sites in various patient groups characterized by clinical subtype, Expanded Disability Status Scale score and disease duration. We also measured absolute and normalized lesion volumes in several regions of interest using an atlas-based approach, and evaluated differences within and between groups. The lateral funiculi were more frequently affected by lesions in progressive subtypes than in relapsing in voxelwise analysis (P < 0.001), which was further confirmed by absolute and normalized lesion volumes (P < 0.01). The central cord area was more often affected by lesions in primary progressive than relapse-remitting patients (P < 0.001). Between white and grey matter, the absolute lesion volume in the white matter was greater than in the grey matter in all phenotypes (P < 0.001); however when normalizing by each region, normalized lesion volumes were comparable between white and grey matter in primary progressive patients. Lesions appearing in the lateral funiculi and central cord area were significantly correlated with Expanded Disability Status Scale score (P < 0.001). High lesion frequencies were observed in patients with a more aggressive disease course, rather than long disease duration. Lesions located in the lateral funiculi and central cord area of the cervical spine may influence clinical status in multiple sclerosis. This work shows the added value of cervical spine lesions, and provides an avenue for evaluating the distribution of spinal cord lesions in various patient groups.

The spinal cord is frequently affected by atrophy and/or lesions in multiple sclerosis (MS) patients. Segmentation of the spinal cord and lesions from MRI data provides measures of damage, which are key criteria for the diagnosis, prognosis, and longitudinal monitoring in MS. Automating this operation eliminates inter-rater variability and increases the efficiency of large-throughput analysis pipelines. Robust and reliable segmentation across multi-site spinal cord data is challenging because of the large variability related to acquisition parameters and image artifacts. In particular, a precise delineation of lesions is hindered by a broad heterogeneity of lesion contrast, size, location, and shape. The goal of this study was to develop a fully-automatic framework - robust to variability in both image parameters and clinical condition - for segmentation of the spinal cord and intramedullary MS lesions from conventional MRI data of MS and non-MS cases. Scans of 1042 subjects (459 healthy controls, 471 MS patients, and 112 with other spinal pathologies) were included in this multi-site study (n = 30). Data spanned three contrasts (T1-, T2-, and T2∗-weighted) for a total of 1943 vol and featured large heterogeneity in terms of resolution, orientation, coverage, and clinical conditions. The proposed cord and lesion automatic segmentation approach is based on a sequence of two Convolutional Neural Networks (CNNs). To deal with the very small proportion of spinal cord and/or lesion voxels compared to the rest of the volume, a first CNN with 2D dilated convolutions detects the spinal cord centerline, followed by a second CNN with 3D convolutions that segments the spinal cord and/or lesions. CNNs were trained independently with the Dice loss. When compared against manual segmentation, our CNN-based approach showed a median Dice of 95% vs. 88% for PropSeg (p ≤ 0.05), a state-of-the-art spinal cord segmentation method. Regarding lesion segmentation on MS data, our framework provided a Dice of 60%, a relative volume difference of -15%, and a lesion-wise detection sensitivity and precision of 83% and 77%, respectively. In this study, we introduce a robust method to segment the spinal cord and intramedullary MS lesions on a variety of MRI contrasts. The proposed framework is open-source and readily available in the Spinal Cord Toolbox.

Objectives To assess the effectiveness of Neuroaspis plp10 nutritional supplement when added to interferon (IFN)-β treatment in patients with relapsing-remitting multiple sclerosis (RRMS).Design A 30-month phase III multicentre, randomised, double-blind, placebo-controlled trial. Randomisation stratified by centre using a computer-generated procedure with Neuroaspis plp10 versus placebo in 1:1 ratio. The first 6 months were used as both the pre-entry and normalisation period.Setting 3 teaching hospitals in Greece and 1 Neurology Institute in Cyprus.Participants 61 patients with RRMS on IFN-β were randomly assigned to receive Neuroaspis plp10 (n=32) or placebo (n=29), 20 mL, orally, once daily, for 30 months.Intervention Neuroaspis plp10, a cocktail mixture, containing specific PUFA (12 150 mg) and γ-tocopherol (760 mg) versus virgin olive oil (placebo).Main outcome measure The primary end point was the annual relapse rate (ARR) whereas the secondary ones were the rate of sustained progression of disability, as measured by the Expanded Disability Status Scale (EDSS) and the brain T2 and gadolinium-enhancing lesions, at 2 years.Results For the intention-to-treat analyses Neuroaspis plp10 significantly reduced the ARR by 80%, (RRR, 0.20; 95% CI: 0.09 to 0.45; p=0.0001) and the risk of sustained progression of disability by 73% (HR, 0.27; 95% CI: 0.09 to 0.83; p=0.022) versus placebo, at 2 years. The number of T1 gadolinium-enhancing lesions and the number of new/enlarged T2-hyperintense lesions were significantly reduced (p=0.01 and p

Multiple sclerosis (MS) is a neurological disorder affecting the central nervous system and features extensive functional brain changes that are poorly understood but relate strongly to clinical impairments. Functional magnetic resonance imaging (fMRI) is a non-invasive, powerful technique able to map activity of brain regions and to assess how such regions interact for an efficient brain network. FMRI has been widely applied to study functional brain changes in MS, allowing to investigate functional plasticity consequent to disease-related structural injury. The first studies in MS using active fMRI tasks mainly aimed to study such plastic changes by identifying abnormal activity in salient brain regions (or systems) involved by the task. In later studies the focus shifted towards resting state (RS) functional connectivity (FC) studies, which aimed to map large-scale functional networks of the brain and to establish how MS pathology impairs functional integration, eventually leading to the hypothesized network collapse as patients clinically progress. This review provides a summary of the main findings from studies using task-based and RS fMRI and illustrates how functional brain alterations relate to clinical disability and cognitive deficits in this condition. We also give an overview of longitudinal studies that used task-based and RS fMRI to monitor disease evolution and effects of motor and cognitive rehabilitation. In addition, we discuss the results of studies using newer technologies involving time-varying FC to investigate abnormal dynamism and flexibility of network configurations in MS. Finally, we show some preliminary results from two recent topics (i.e., multimodal MRI analysis and artificial intelligence) that are receiving increasing attention. Together, these functional studies could provide new (conceptual) insights into disease stage-specific mechanisms underlying progression in MS, with recommendations for future research.

There is an increasing need of sharing harmonized data from large, cooperative studies as this is essential to develop new diagnostic and prognostic biomarkers. In the field of multiple sclerosis (MS), the issue has become of paramount importance due to the need to translate into the clinical setting some of the most recent MRI achievements. However, differences in MRI acquisition parameters, image analysis and data storage across sites, with their potential bias, represent a substantial constraint. This review focuses on the state of the art, recent technical advances, and desirable future developments of the harmonization of acquisition, analysis and storage of large-scale multicentre MRI data of MS cohorts. Huge efforts are currently being made to achieve all the requirements needed to provide harmonized MRI datasets in the MS field, as proper management of large imaging datasets is one of our greatest opportunities and challenges in the coming years. Recommendations based on these achievements will be provided here. Despite the advances that have been made, the complexity of these tasks requires further research by specialized academical centres, with dedicated technical and human resources. Such collective efforts involving different professional figures are of crucial importance to offer to MS patients a personalised management while minimizing consumption of resources.

Background: Considerable spinal cord (SC) atrophy occurs in multiple sclerosis (MS). While MRI-based techniques for SC cross-sectional area (CSA) quantification have improved over time, there is no common agreement on whether to measure at single vertebral levels or across larger regions and whether upper SC CSA can be reliably measured from brain images.Aim: To compare in a multicenter setting three CSA measurement methods in terms of repeatability at different anatomical levels. To analyze the agreement between measurements performed on the cervical cord and on brain MRI.Method: One healthy volunteer was scanned three times on the same day in six sites (three scanner vendors) using a 3T MRI protocol including sagittal 3D T1-weighted imaging of the brain (covering the upper cervical cord) and of the SC. Images were analyzed using two semiautomated methods [NeuroQLab (NQL) and the Active Surface Model (ASM)] and the fully automated Spinal Cord Toolbox (SCT) on different vertebral levels (C1–C2; C2/3) on SC and brain images and the entire cervical cord (C1–C7) on SC images only.Results: CSA estimates were significantly smaller using SCT compared to NQL and ASM (p < 0.001), regardless of the cord level. Inter-scanner repeatability was best in C1–C7: coefficients of variation for NQL, ASM, and SCT: 0.4, 0.6, and 1.0%, respectively. CSAs estimated in brain MRI were slightly lower than in SC MRI (all p ≤ 0.006 at the C1–C2 level). Despite protocol harmonization between the centers with regard to image resolution and use of high-contrast 3D T1-weighted sequences, the variability of CSA was partly scanner dependent probably due to differences in scanner geometry, coil design, and details of the MRI parameter settings.Conclusion: For CSA quantification, dedicated isotropic SC MRI should be acquired, which yielded best repeatability in the entire cervical cord. In the upper part of the cervical cord, use of brain MRI scans entailed only a minor loss of CSA repeatability compared to SC MRI. Due to systematic differences between scanners and the CSA quantification software, both should be kept constant within a study. The MRI dataset of this study is available publicly to test new analysis approaches.

Background and rationale: Thalamus atrophy has been linked to cognitive decline in multiple sclerosis (MS) using various segmentation methods. We investigated the consistency of the association between thalamus volume and cognition in MS for two common automated segmentation approaches, as well as fully manual outlining. Methods: Standardized neuropsychological assessment and 3-Tesla 3D-T1-weighted brain MRI were collected (multi-center) from 57 MS patients and 17 healthy controls. Thalamus segmentations were generated manually and using five automated methods. Agreement between the algorithms and manual outlines was assessed with Bland-Altman plots; linear regression assessed the presence of proportional bias. The effect of segmentation method on the separation of cognitively impaired (CI) and preserved (CP) patients was investigated through Generalized Estimating Equations; associations with cognitive measures were investigated using linear mixed models, for each method and vendor. Results: In smaller thalami, automated methods systematically overestimated volumes compared to manual segmentations [ρ=(-0.42)-(-0.76); p-values

PIN1 is a promising therapeutic target for cancer treatment. In this study, the authors identify a covalent inhibitor of PIN1 with anti-tumour and anti-metastatic properties thanks to PIN1 inactivation and to the release, after binding to PIN1, of a quinone-mimicking compound that elicits reactive oxygen generation and causes DNA damage.

Functional magnetic resonance imaging (fMRI) at resting state (RS) has been widely used to characterize the main brain networks. Functional connectivity (FC) has been mostly assessed assuming that FC is static across the whole fMRI examination. However, FC is highly variable at a very fast time-scale, as demonstrated by neurophysiological techniques. Time-varying functional connectivity (TVC) is a novel approach that allows capturing reoccurring patterns of interaction among functional brain networks. Aim of this review is to provide a description of the methods currently used to assess TVC on RS fMRI data, and to summarize the main results of studies applying TVC in healthy controls and patients with multiple sclerosis (MS). An overview of the main results obtained in neurodegenerative and psychiatric conditions is also provided. The most popular TVC approach is based on the so-called “sliding windows,” in which the RS fMRI acquisition is divided in small temporal segments (windows). A window of fixed length is shifted over RS fMRI time courses, and data within each window are used to calculate FC and its variability over time. Sliding windows can be combined with clustering techniques to identify recurring FC states or used to assess global TVC properties of large-scale functional networks or specific brain regions. TVC studies have used heterogeneous methodologies so far. Despite this, similar results have been obtained across investigations. In healthy subjects, the default-mode network (DMN) exhibited the highest degree of connectivity dynamism. In MS patients, abnormal global TVC properties and TVC strengths were found mainly in sensorimotor, DMN and salience networks, and were associated with more severe structural MRI damage and with more severe physical and cognitive disability. Conversely, abnormal TVC measures of the temporal network were correlated with better cognitive performances and less severe fatigue. In patients with neurodegenerative and psychiatric conditions, TVC abnormalities of the DMN, attention and executive networks were associated to more severe clinical manifestations. TVC helps to provide novel insights into fundamental properties of functional networks, and improves the understanding of brain reorganization mechanisms. Future technical advances might help to clarify TVC association with disease prognosis and response to treatment.

HER-3 is becoming an attractive target for antibody–drug conjugate (ADC)-based therapy. Indeed, this receptor and its ligands are found to be overexpressed in several malignancies, and re-activation of its downstream signaling axis is known to play a critical role in modulating the sensitivity of targeted therapeutics in different tumors. In this study, we generated a novel ADC named EV20/NMS-P945 by coupling the anti-HER-3 antibody EV20 with a duocarmycin-like derivative, the thienoindole (TEI) NMS-P528, a DNA minor groove alkylating agent through a peptidic cleavable linker. This ADC showed target-dependent cytotoxic activity in vitro on several tumor cell lines and therapeutic activity in mouse xenograft tumor models, including those originating from pancreatic, prostatic, head and neck, gastric and ovarian cancer cells and melanoma. Pharmacokinetics and toxicological studies in monkeys demonstrated that this ADC possesses a favorable terminal half-life and stability and it is well tolerated. These data support further EV20/NMS-P945 clinical development as a therapeutic agent against HER-3-expressing malignancies.

We assessed abnormalities of brain functional magnetic resonance imaging (fMRI) activity during a sustained attention task (Conners’ Continuous Performance Test (CCPT)) in 20 right-handed pediatric acquired brain injury (ABI) patients versus 7 right-handed age-matched healthy controls, and we estimated the correlation of such abnormalities with clinical and cognitive deficits. Patients underwent the Wechsler Intelligence Scale for Children (WISC), Wisconsin Card Sorting Test, and Functional Independence Measure (FIM) evaluations. During fMRI, patients and controls activated regions of the attention network. Compared to controls, ABI patients experienced a decreased average fMRI recruitment of the left cerebellum and a decreased deactivation of the left anterior cingulate cortex. With increasing task demand, compared to controls, ABI patients had an impaired ability to increase the recruitment of several posterior regions of the attention network. They also experienced a greater activation of frontal regions, which was correlated with worse performance on FIM, WISC, and fMRI CCPT. Such abnormal brain recruitment was significantly influenced by the type of lesion (focal versus diffuse axonal injury) and time elapsed from the event. Pediatric ABI patients experienced an inability to optimize attention network recruitment, especially when task difficulty was increased, which likely contributes to their clinical and cognitive deficits.