Neuromyelitis optica (NMO) exhibits substantial similarities to multiple sclerosis (MS) in clinical manifestations and imaging results and has long been considered a variant of MS. With the advent of a specific biomarker in NMO, known as anti-aquaporin 4, this assumption has changed; however, the differential diagnosis remains challenging and it is still not clear whether a combination of neuroimaging and clinical data could be used to aid clinical decision-making. Computer-aided diagnosis is a rapidly evolving process that holds great promise to facilitate objective differential diagnoses of disorders that show similar presentations. In this study, we aimed to use a powerful method for multi-modal data fusion, known as a multi-kernel learning and performed automatic diagnosis of subjects. We included 30 patients with NMO, 25 patients with MS and 35 healthy volunteers and performed multi-modal imaging with T1-weighted high resolution scans, diffusion tensor imaging (DTI) and resting-state functional MRI (fMRI). In addition, subjects underwent clinical examinations and cognitive assessments. We included 18 a priori predictors from neuroimaging, clinical and cognitive measures in the initial model. We used 10-fold cross-validation to learn the importance of each modality, train and finally test the model performance. The mean accuracy in differentiating between MS and NMO was 88%, where visible white matter lesion load, normal appearing white matter (DTI) and functional connectivity had the most important contributions to the final classification. In a multi-class classification problem we distinguished between all of 3 groups (MS, NMO and healthy controls) with an average accuracy of 84%. In this classification, visible white matter lesion load, functional connectivity, and cognitive scores were the 3 most important modalities. Our work provides preliminary evidence that computational tools can be used to help make an objective differential diagnosis of NMO and MS.

Background: Among multiple sclerosis (MS) related symptoms and complications, fatigue might impact roughly 90% of patients. Decline in cognitive function is one of the other complications that occur in the first years after disease onset. The Mediterranean diet is one of the well-known anti-inflammatory dietary approaches. Therefore, this study aimed to explore the effects of a modified Mediterranean-like diet on cognitive changes and fatigue levels in comparison with a conventional standard diet over a 1-year follow-up. Methods: In the current single-blind randomized controlled trial, 34 MS patients in the Mediterranean- like diet group and 38 patients in the standard healthy diet group were studied for 1 year. The dietary interventions were modified each month by an expert nutritionist. MS-associated fatigue level was evaluated using the Modified Fatigue Impact Scale (MFIS). Cognitive assessment was also performed using Minimal Assessment of Cognitive Function in MS (MACFIMS). Results: Intergroup ‎comparisons demonstrated that after considering confounding variables in ANCOVA, fatigue scores appeared significantly lower in patients who were treated with the Mediterranean-like diet than those in the standard healthy diet group [Mean 95% confidence interval (CI)}: 33.93 (32.97-34.89) and 37.98 (36.99-38.97), respectively; P < 0.001]. However, the intergroup ‎analysis of cognitive status only showed a difference in the mean score of Brief Visuospatial Memory Test-Revised (BVMT-R) subtest of the MACFIMS. The BVMT-R‎ was higher among standard healthy diet patients compared to the Mediterranean-like diet group after the intervention following adjustment for covariates [Mean (95% CI): 23.73 (21.88-25.57) and 20.56 (18.60-22.51), respectively; P = 0.020]. Conclusion: In conclusion, the results of this study highlighted the higher protective effects of the Mediterranean-like diet against MS-related fatigue than the standard healthy diet. However, no significant improvement was observed in the cognitive status of MS patients after a 1-year treatment with the Mediterranean-like diet. More randomized clinical trials with larger sample sizes are needed to elucidate the effects of dietary modifications on MS-associated symptoms and complications.

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Objective: The prevalence of cognitive impairment in multiple sclerosis (MS) is significant and it is estimated that 40% to 70% of patients with MS suffer from this impairment. COVID-19 is also a new infectious disease. The symptoms of this disease, which include fever, shortness of breath, and cough, can be mild to severe and can even lead to death. Due to the use of immunosuppressive drugs by Patients with MS, they might be at greater risk of catching COVID-19. Thus, patients with MS may be more afraid of catching the virus. One of the important factors is the relationship between cognitive deficit and the increase in patients' fear of COVID-19. The aim of this study was to assess the relationship between fear of catching COVID-19 and cognitive impairment in patients with MS. Method: This cross-sectional study was conducted at the MS Clinic, Sina hospital, Tehran University of Medical Sciences, Tehran, Iran. Our participants in this project were Patients with MS who were over 18 years old and had no history of other neurological and psychiatric diseases. In addition to obtaining demographic and clinical information, we measured the fear of catching the COVID 2019 via Fear of COVID-19 Scale (FCV-19S), which is 7-item questionnaire. We also used Multiple Sclerosis Neuro Psychological Screening Questionnaire (MSNQ) to assess memory and information processing speed in Patients with MS. Results: After adjustment for age, gender, disease duration, highest level of education, MS type, and EDSS in linear regression model, as well as the MSNQ total score and fear score of catching coronavirus, the results demonstrated a significant positive correlation with P value of 0.00 and β: 0.024. Conclusion: The present study showed a direct relationship between cognitive disorder and level of fear regarding COVID-19. Patients with more cognitive disorders were more afraid of COVID-19.

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IntroductionDepression, fatigue, and anxiety are three common clinical comorbidities of multiple sclerosis (MS). We investigated the role of physical activity (PA) level and body mass index (BMI) as modifiable lifestyle factors in these three comorbidities.MethodsA cross-sectional study was conducted in the MS specialist clinic of Sina Hospital, Tehran, Iran. Demographic and clinical data were collected. BMI was categorized in accordance with the WHO’s standard classification. Physical activity (PA) level and sitting time per day were obtained using the short form of the International Physical Activity Questionnaire (IPAQ-SF). Fatigue, anxiety, and depression scores were measured using the Persian version of the Fatigue Severity Scale (FSS), Beck Anxiety Inventory (BAI), and Beck’s Depression Inventory II (BDI-II) questionnaires, respectively. The correlation between the metabolic equivalent of tasks (MET), BMI, and daily sitting hours with depression, anxiety, and fatigue were checked using the linear regression test. The normal BMI group was considered a reference, and the difference in quantitative variables between the reference and the other groups was assessed using an independent sample t-test. Physical activity was classified with tertiles, and the difference in depression, anxiety, and fatigue between the PA groups was evaluated by a one-way ANOVA test.ResultsIn total, 85 MS patients were recruited for the study. The mean ± SD age of the participants was 39.07 ± 8.84 years, and 72.9% (n: 62) of them were female. The fatigue score was directly correlated with BMI (P: 0.03; r: 0.23) and sitting hours per day (P: 0.01; r: 0.26) and indirectly correlated with PA level (P &lt; 0.01; r: −0.33). Higher depression scores were significantly correlated with elevated daily sitting hours (P: 0.01; r: 0.27). However, the correlation between depression with PA and BMI was not meaningful (p &gt; 0.05). Higher anxiety scores were correlated with BMI (P: 0.01; r: 0.27) and lower PA (P: 0.01; r: −0.26). The correlation between anxiety and sitting hours per day was not significant (p &gt; 0.05). Patients in the type I obesity group had significantly higher depression scores than the normal weight group (23.67 ± 2.30 vs. 14.05 ± 9.12; P: 0.001). Fatigue (32.61 ± 14.18 vs. 52.40 ± 12.42; P: &lt;0.01) and anxiety (14.66 ± 9.68 vs. 27.80 ± 15.48; P: 0.01) scores were significantly greater among participants in the type II obesity group in comparison with the normal weight group. Fatigue (P: 0.01) and anxiety (P: 0.03) scores were significantly different in the three levels of PA, but no significant difference was found in the depression score (P: 0.17).ConclusionOur data suggest that a physically active lifestyle and being in the normal weight category are possible factors that lead to lower depression, fatigue, and anxiety in patients with MS.