Nitric oxide can function as either a killer molecule or an antiapoptotic effector in cardiomyocytes

AbstractCaspase enzymes are a family of cysteine proteases that play a central role in apoptosis. Recently, it has been demonstrated that caspases can be S-nitrosylated and inhibited by nitric oxide (NO). The present report shows that in chick embryo heart cells (CEHC), NO donor molecules such as S-nitroso-N-acetylpenicillamine (SNAP), S-nitrosoglutathione, spermine-NO or sodium nitroprusside inhibit caspase activity in both basal and staurosporine-treated cells. However, the inhibitory effect of NO donors on caspase activity is accompanied by a parallel cytotoxic effect, that precludes NO to exert its antiapoptotic capability. N-Acetylcysteine (NAC) at a concentration of 10 mM blocks depletion of cellular glutathione and cell death in SNAP-treated CEHC, but it poorly affects the ability of SNAP to inhibit caspase activity. Consequently, in the presence of NAC, SNAP attenuates not only caspase activity but also cell death of staurosporine-treated CEHC. These data show that changes in the redox environment may inhibit NO-mediated toxicity, without affecting the antiapoptotic capability of NO, mediated by inhibition of caspase enzymes. NO may thus be transformed from a killer molecule into an antiapoptotic agent

The progressive loss of brain network fingerprints in Amyotrophic Lateral Sclerosis predicts clinical impairment

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterised by functional connectivity alterations in both motor and extra-motor brain regions. Within the framework of network analysis, fingerprinting represents a reliable approach to assess subject-specific connectivity features within a given population (healthy or diseased). Here, we applied the Clinical Connectome Fingerprint (CCF) analysis to source-reconstructed magnetoencephalography (MEG) signals in a cohort of seventy-eight subjects: thirty-nine ALS patients and thirty-nine healthy controls. We set out to develop an identifiability matrix to assess the extent to which each patient was recognisable based on his/her connectome, as compared to healthy controls. The analysis was performed in the five canonical frequency bands. Then, we built a multilinear regression model to test the ability of the “clinical fingerprint” to predict the clinical evolution of the disease, as assessed by the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-r), the King’s disease staging system, and the Milano-Torino Staging (MiToS) disease staging system. We found a drop in the identifiability of patients in the alpha band compared to the healthy controls. Furthermore, the “clinical fingerprint” was predictive of the ALSFRS-r (p = 0.0397; β = 32.8), the King’s (p = 0.0001; β = − 7.40), and the MiToS (p = 0.0025; β = − 4.9) scores. Accordingly, it negatively correlated with the King’s (Spearman’s rho = -0.6041, p = 0.0003) and MiToS scales (Spearman’s rho = − 0.4953, p = 0.0040). Our results demonstrated the ability of the CCF approach to predict the individual motor impairment in patients affected by ALS. Given the subject-specificity of our approach, we hope to further exploit it to improve disease management

Physical Exercise Moderates the Effects of Disability on Depression in People with Multiple Sclerosis during the COVID-19 Outbreak

Physical disability impacts psychosocial wellbeing in people with multiple sclerosis. However, the role of physical activity in this context is still debated. By taking advantage of a previous survey, conducted online from 22 April to 7 May 2020, we performed a post-hoc analysis with the aim to assess the associations between disability, physical exercise, and mental health in multiple sclerosis. We retrieved the following data: (i) sociodemographic information, (ii) changes in lifestyle (including exercise), (iii) physical disability, as measured with the Patient-Determined Disease Steps scale, and (iv) anxiety feelings and depressive symptoms assessed via the items included in the Quality of Life in Neurological Disorders measurement system. Examination of the interaction plot showed that the effect of disability on depression, but not on anxious symptoms, was significant for all levels of physical exercise (low: b = 1.22, 95% C.I. 0.85, 1.58, p < 0.001; moderate: b = 0.95, 95% C.I. 0.66, 1.24, p < 0.001; and high: b = 0.68, 95% C.I. 0.24, 1.13, p = 0.003). Based on these data, we can conclude that disability significantly impacted depression during the COVID-19 pandemic, with physical activity playing a moderating role. Our results suggest that favoring exercise in multiple sclerosis (MS) would ameliorate psychological wellbeing regardless of the level of physical disability

Disability assessment using Google Maps

Objectives To evaluate the concordance between Google Maps  application (GM ) and clinical practice measurements of ambulatory function (e.g., Ambulation Score (AS) and respective Expanded Disability Status Scale (EDSS)) in people with multiple sclerosis (pwMS). Materials and methods This is a cross-sectional multicenter study. AS and EDSS were calculated using GM  and routine clinical methods; the correspondence between the two methods was assessed. A multinomial logistic model is investigated which demographic (age, sex) and clinical features (e.g., disease subtype, fatigue, depression) might have influenced discrepancies between the two methods. Results Two hundred forty-three pwMS were included; discrepancies in AS and in EDDS assessments between GM  and routine clinical methods were found in 81/243 (33.3%) and 74/243 (30.4%) pwMS, respectively. Progressive phenotype (odds ratio [OR] = 2.8; 95% confidence interval [CI] 1.1–7.11, p = 0.03), worse fatigue (OR = 1.03; 95% CI 1.01–1.06, p = 0.01), and more severe depression (OR = 1.1; 95% CI 1.04–1.17, p = 0.002) were associated with discrepancies between GM  and routine clinical scoring. Conclusion GM  could easily be used in a real-life clinical setting to calculate the AS and the related EDSS scores. GM  should be considered for validation in further clinical studies

Digital work engagement among Italian neurologists

Background: Digital health, including telemedicine, is increasingly recommended for the management of chronic neurological disorders, and it has changed the roles of patients and clinicians. Methods: In this cross-sectional study we aimed to investigate the digital work engagement of Italian neurologists through a survey collected between September 2020 and January 2021. Questionnaires were anonymous and collected demographic characteristics, attitudes towards digital devices and social media, and details about the clinician–patient relationship. We used logistic-regression models to identify characteristics associated with the propensity to communicate with patients using social media. Results: Among the 553 neurologists who participated to the study, smartphones and computers were widely preferred compared with tablets; wearable devices were not common, although some neurologists desired them. A total of 48% of participants reported communicating with patients using social media but only a few were in favor of social friendship with patients; WhatsApp was the social media most popular for professional (86%) and personal (98%) purposes. Propensity to communicate with social media was significantly higher among those who were older (p < 0.001) and lived in regions outside northern Italy (center: p = 0.006; south and the islands: p < 0.001). For 58% of responders, social media improved their relationship with patients, but 72% usually warned patients about unreliable websites. Conclusions: The preferred social media were those which were rapid and which safeguard privacy more effectively; neurologists made many efforts to disprove fake news circulating online, providing help to patients in various ways. This analysis can help direct future interventions for the management of chronic neurological disorders

COVID-19 Severity in Multiple Sclerosis: Putting Data Into Context

Background and objectives: It is unclear how multiple sclerosis (MS) affects the severity of COVID-19. The aim of this study is to compare COVID-19-related outcomes collected in an Italian cohort of patients with MS with the outcomes expected in the age- and sex-matched Italian population. Methods: Hospitalization, intensive care unit (ICU) admission, and death after COVID-19 diagnosis of 1,362 patients with MS were compared with the age- and sex-matched Italian population in a retrospective observational case-cohort study with population-based control. The observed vs the expected events were compared in the whole MS cohort and in different subgroups (higher risk: Expanded Disability Status Scale [EDSS] score &gt; 3 or at least 1 comorbidity, lower risk: EDSS score ≤ 3 and no comorbidities) by the χ2 test, and the risk excess was quantified by risk ratios (RRs). Results: The risk of severe events was about twice the risk in the age- and sex-matched Italian population: RR = 2.12 for hospitalization (p &lt; 0.001), RR = 2.19 for ICU admission (p &lt; 0.001), and RR = 2.43 for death (p &lt; 0.001). The excess of risk was confined to the higher-risk group (n = 553). In lower-risk patients (n = 809), the rate of events was close to that of the Italian age- and sex-matched population (RR = 1.12 for hospitalization, RR = 1.52 for ICU admission, and RR = 1.19 for death). In the lower-risk group, an increased hospitalization risk was detected in patients on anti-CD20 (RR = 3.03, p = 0.005), whereas a decrease was detected in patients on interferon (0 observed vs 4 expected events, p = 0.04). Discussion: Overall, the MS cohort had a risk of severe events that is twice the risk than the age- and sex-matched Italian population. This excess of risk is mainly explained by the EDSS score and comorbidities, whereas a residual increase of hospitalization risk was observed in patients on anti-CD20 therapies and a decrease in people on interferon