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Introduction: Understanding the prevalence of multiple sclerosis (MS) provides information for healthcare planning and helps identify trends and patterns of disease occurrence. For Switzerland, the number of persons with MS (pwMS) was last estimated at approximately 15,000 in 2016. The study's objectives are to update estimates of MS prevalence and characterise the change in MS prevalence in Switzerland between 2016 and 2021, the last year with complete administrative data., Methods: The Swiss MS Registry (SMSR) is an ongoing, longitudinal study in Switzerland. It has previously established a methodology to assess the epidemiology of MS in Switzerland by integrating SMSR data with administrative data on reimbursement approvals for disease-modifying therapies (DMTs). Subsequently, the benchmark-multiplier method is applied to the combined data. Using the same methodology, we calculated overall and sex- and age-specific prevalence rates for 2021. Furthermore, we descriptively analysed changes since 2016 by comparing the prevalence figures and demographic and clinical characteristics of pwMS in both years., Results: We estimated the population of pwMS in Switzerland at 18,140 [95% simulation interval 17,550-18,750], corresponding to a period prevalence of 200.8-214.5/100,000 inhabitants. Peak prevalence was observed in the 50 to 55-year age group. Compared to 2016, the 2021 estimate corresponds to a 20% increase (n=3,000). Extrapolating from Swiss population growth, we estimated that one-fifth of the observed prevalence increase may be attributed to a rising population. The proportion of pwMS in the age range from 50 to 64 (32.5% vs. 35.9%) and above 65 (8.0% vs. 11.1%) years increased. Consequently, the median [interquartile range] age increased from 47 [37-55] to 49 [38-57] years. The median age at diagnosis (36 [28-45] years) and the female-to-male ratio (2.7:1) remained stable since 2016. The proportion of pwMS treated with DMTs increased from 62.1% to 69.0%, with the largest change observed in infusion therapies (15.7% vs. 23.3%)., Conclusion: The estimated MS prevalence in Switzerland has increased since the previous estimate in 2016, with a shift in peak prevalence towards older ages. Population growth explained around one-fifth of this increase, thus leaving room for contributions by additional factors, which require further investigation. The rising MS prevalence has several implications for healthcare, research and society., (The Author(s). Published by S. Karger AG, Basel.)

Introduction: Self-reports are a valuable and cost-effective method of data collection, though they can be influenced by bias. Limited evidence exists on the quality of self-reports by persons with multiple sclerosis (pwMS), particularly since more potent disease-modifying therapies (DMTs) have been introduced. This study aimed to assess the reliability and validity of self-reported DMT use and multiple sclerosis (MS) type in the Swiss Multiple Sclerosis Registry (SMSR) by comparing self-reports with reimbursement approval requests from the Swiss Association for Joint Tasks of Health Insurers., Methods: The self-reported and reimbursement approval data were linked using privacy-preserving methods based on information available in both databases, i.e., date of birth, canton of residence, sex, and year of MS diagnosis. The SMSR baseline questionnaire data was utilized for the main analysis, while the SMSR follow-up survey data was utilized for the sensitivity analysis. For both analyses, we compared self-reported data with reimbursement approval data that corresponded to the respective periods of the SMSR data collection. Thus, the main analysis included the entirety of the data over the six-year period, while the sensitivity analysis captured a more recent snapshot of the data. To assess reliability, we estimated agreement using Cohen's kappa, and for validity, we estimated accuracy parameters using reimbursement approvals as the reference standard. Univariable and multivariable logistic regression models were employed to investigate factors associated with discordance between self-reports and reimbursement approvals in the main analysis., Results: The main analysis included 446 participants, and the sensitivity analysis included 193 participants. The agreement between self-reported and reimbursement approval data for medication use was near-perfect in both analyses (κ = 0.87, 95% confidence interval (CI) 0.85, 0.90 and κ = 0.82, 95% CI 0.76, 0.88). However, the agreement between self-reported and reimbursement approval-documented MS types ranged from fair to moderate (κ = 0.37, 95% CI 0.25, 0.48 to κ = 0.61, 95% CI 0.46, 0.77). The accuracy estimates for self-reported DMT use were generally high (≥ 0.80) with narrow CIs, except for less frequently reported drugs. While the sensitivity and specificity for RRMS were high, there was a notable possibility of false-negative self-reports for RRMS (NPV = 0.33, 95% CI 0.22, 0.45), and false-positive reports for SPMS (PPV = 0.36, 95% CI 0.21, 0.54). Multivariable logistic regression models showed that age (OR = 1.07, 95% CI 1.04, 1.10 per year) and education level (OR = 0.27, 95% CI 0.11, 0.65) were associated with discordance in reported and documented MS types, whereas possession of Swiss citizenship (OR = 0.32, 95% CI 0.14, 0.72) was associated with discordance in DMT use., Conclusion: Self-reported DMT use in pwMS is a reliable and valid information source, with near-perfect agreement and high accuracy. Self-reported MS types showed fair to moderate agreement and varying accuracy, likely reflecting the complexity of diagnosing progressive forms of MS and access to DMTs. In population-based MS research, self-reports of MS types, and particularly DMT use, can serve as a suitable surrogate for healthcare provider data., Competing Interests: Declaration of Competing Interest Mina Stanikić, Julia Braun, Vladeta Ajdacic-Gross, Zina-Mary Manyali, Benjamin Victor Ineichen, Stefania Iaquinto, and Viktor von Wyl declare no competing interests. Özgür Yaldizli received grants from ECTRIMS/MAGNIMS, University of Basel, Pro-Patient Stiftung University Hospital Basel, Free Academy Basel, Swiss National Science Foundation, Swiss Multiple Sclerosis Society and advisory board/lecture and consultancy fees from Roche, Sanofi Genzyme, Allmirall, Biogen and Novartis. Christian P Kamm has received honoraria for lectures as well as research support from Biogen, Novartis, Almirall, Teva, Merck, Sanofi Genzyme, Roche, Janssen, Eli Lilly, Celgene and the Swiss MS Society. Ente Ospedaliero Cantonale (employer) received compensation for Chiara Zecca's speaking activities, consulting fees, or research grants from Almirall, Biogen Idec, Bristol Meyer Squibb, Lundbeck, Merck, Novartis, Sanofi, Teva Pharma, Roche. Chiara Zecca is recipient of a grant for senior researchers provided by AFRI (Area Formazione accademica, Ricerca e Innovazione), EOC. Ente Ospedaliero Cantonale (employer) received compensation for Claudio Gobbi's speaking activities, consulting fees, or research grants from Almirall, Biogen Idec, Bristol Meyer Squibb, Lundbeck, Merck, Novartis, Sanofi, Teva Pharma, Roche. Pasquale Calabrese has received honoraria for speaking at scientific meetings, serving at scientific advisory boards and consulting activities from Abbvie, Actelion, Almirall, Bayer-Schering, Biogen, EISAI, Lundbeck, Merck Serono, Novartis, Sanofi-Aventis and Teva. He also receives research grants from the Swiss Multiple Sclerosis Society, and the Swiss National Research Foundation., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

The emergence of new digital technologies has enabled a new way of doing research, including active collaboration with the public ('citizen science'). Innovation in machine learning (ML) and natural language processing (NLP) has made automatic analysis of large-scale text data accessible to study individual perspectives in a convenient and efficient fashion. Here we blend citizen science with innovation in NLP and ML to examine (1) which categories of life events persons with multiple sclerosis (MS) perceived as central for their MS; and (2) associated emotions. We subsequently relate our results to standardized individual-level measures. Participants (n = 1039) took part in the 'My Life with MS' study of the Swiss MS Registry which involved telling their story through self-selected life events using text descriptions and a semi-structured questionnaire. We performed topic modeling ('latent Dirichlet allocation') to identify high-level topics underlying the text descriptions. Using a pre-trained language model, we performed a fine-grained emotion analysis of the text descriptions. A topic modeling analysis of totally 4293 descriptions revealed eight underlying topics. Five topics are common in clinical research: 'diagnosis', 'medication/treatment', 'relapse/child', 'rehabilitation/wheelchair', and 'injection/symptoms'. However, three topics, 'work', 'birth/health', and 'partnership/MS' represent domains that are of great relevance for participants but are generally understudied in MS research. While emotions were predominantly negative (sadness, anxiety), emotions linked to the topics 'birth/health' and 'partnership/MS' was also positive (joy). Designed in close collaboration with persons with MS, the 'My Life with MS' project explores the experience of living with the chronic disease of MS using NLP and ML. Our study thus contributes to the body of research demonstrating the potential of integrating citizen science with ML-driven NLP methods to explore the experience of living with a chronic condition., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Haag 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.)

Numerous disorders are characterised by fatigue as a highly disabling symptom. Fatigue plays a particularly important clinical role in multiple sclerosis (MS) where it exerts a profound impact on quality of life. Recent concepts of fatigue grounded in computational theories of brain-body interactions emphasise the role of interoception and metacognition in the pathogenesis of fatigue. So far, however, for MS, empirical data on interoception and metacognition are scarce. This study examined interoception and (exteroceptive) metacognition in a sample of 71 persons with a diagnosis of MS. Interoception was assessed by prespecified subscales of a standard questionnaire (Multidimensional Assessment of Interoceptive Awareness [MAIA]), while metacognition was investigated with computational models of choice and confidence data from a visual discrimination paradigm. Additionally, autonomic function was examined by several physiological measurements. Several hypotheses were tested based on a preregistered analysis plan. In brief, we found the predicted association of interoceptive awareness with fatigue (but not with exteroceptive metacognition) and an association of autonomic function with exteroceptive metacognition (but not with fatigue). Furthermore, machine learning (elastic net regression) showed that individual fatigue scores could be predicted out-of-sample from our measurements, with questionnaire-based measures of interoceptive awareness and sleep quality as key predictors. Our results support theoretical concepts of interoception as an important factor for fatigue and demonstrate the general feasibility of predicting individual levels of fatigue from simple questionnaire-based measures of interoception and sleep., (© 2023 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Background: Multiple sclerosis (MS) impacts education, future career pathways and working capability and therefore may negatively impact the financial situation of persons with MS (pwMS) in Switzerland. We therefore investigated the financial situation and its influencing sociodemographic and disease-specific factors of pwMS compared to the general Swiss population with focus on material deprivation (MD)., Methods: Data on the financial situation of pwMS were collected via a specific questionnaire added to the regular, semi-annual follow-up assessments of the Swiss Multiple Sclerosis Registry. Questions were taken in an unmodified format from the standardized "Statistics on Income and Living Conditions" (SILC) questionnaire 2019 of the Federal Statistical Office of Switzerland which evaluates the financial situation of the general Swiss population, enabling a direct comparison of pwMS with the general Swiss population., Results: PwMS were 1.5 times more frequently affected by MD than the general Swiss population (6.3% of pwMS versus 4.2% of the general Swiss population) which was confirmed in a multivariable logistic regression analysis of pooled SILC and Swiss Multiple Sclerosis Registry (SMSR) data. High symptom burden, having only mandatory schooling, well as having a pending disability insurance application (as opposed to no application or receiving benefits) were associated with a higher odds of MD whereas higher education, older age, having a Swiss citizenship, living with a spouse or a partner or being currently employed were independently associated with a lower odds of MD., Conclusion: MS has a negative impact on the financial situation and is associated with MD. PwMS with a high symptom burden at the transition from work force to receiving disability benefits appeared to be vulnerable for MD. Higher education, older age, having a Swiss citizenship, living with a spouse or a partner or being currently employed were independently associated with a lower odds of MD., Competing Interests: Declaration of Competing Interest Kamm CP has received honoraria for lectures as well as research support from Biogen, Novartis, Almirall, Teva, Merck, Sanofi Genzyme, Roche, Janssen, Eli Lilly, Celgene and the Swiss MS Society (SMSG). Sanak L has no disclosures to report. Von Wyl V has no disclosures to report. Chan A has received speakers’/board honoraria from Actelion (Janssen/J&J), Almirall, Bayer, Biogen, Celgene (BMS), Genzyme, Merck KGaA (Darmstadt, Germany), Novartis, Roche, and Teva, all for hospital research funds. He received research support from Biogen, Genzyme, and UCB, the European Union, and the Swiss National Foundation. He serves as associate editor of the European Journal of Neurology, on the editorial board for Clinical and Translational Neuroscience and as topic editor for the Journal of International Medical Research. Stanikic M reports employment by Roche branch in Serbia, Roche d.o.o. from February 2019 to February 2020. Zina-Mary Manjaly has no disclosures to report. Zecca C is recipient of a grant for senior reseachers provided by AFRI (Area Formazione accademica, Ricerca e Innovazione), EOC. Ente Ospedaliero Cantonale (employer) received compensation for C.Z.’s speaking activities, consulting fees, or research grants from Almirall, Biogen Idec, Bristol Meyer Squibb, Lundbeck, Merck, Novartis, Sanofi, Teva Pharma, Roche. Calabrese P. has received speakers’/board honoraria from Almirall, Biogen, Celgene (BMS), Genzyme, Novartis, Roche, Schwabe and Teva., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: The increasing availability of "real-world" data in the form of written text holds promise for deepening our understanding of societal and health-related challenges. Textual data constitute a rich source of information, allowing the capture of lived experiences through a broad range of different sources of information (eg, content and emotional tone). Interviews are the "gold standard" for gaining qualitative insights into individual experiences and perspectives. However, conducting interviews on a large scale is not always feasible, and standardized quantitative assessment suitable for large-scale application may miss important information. Surveys that include open-text assessments can combine the advantages of both methods and are well suited for the application of natural language processing (NLP) methods. While innovations in NLP have made large-scale text analysis more accessible, the analysis of real-world textual data is still complex and requires several consecutive steps., Objective: We developed and subsequently examined the utility and scientific value of an NLP pipeline for extracting real-world experiences from textual data to provide guidance for applied researchers., Methods: We applied the NLP pipeline to large-scale textual data collected by the Swiss Multiple Sclerosis (MS) registry. Such textual data constitute an ideal use case for the study of real-world text data. Specifically, we examined 639 text reports on the experienced impact of the first COVID-19 lockdown from the perspectives of persons with MS. The pipeline has been implemented in Python and complemented by analyses of the "Linguistic Inquiry and Word Count" software. It consists of the following 5 interconnected analysis steps: (1) text preprocessing; (2) sentiment analysis; (3) descriptive text analysis; (4) unsupervised learning-topic modeling; and (5) results interpretation and validation., Results: A topic modeling analysis identified the following 4 distinct groups based on the topics participants were mainly concerned with: "contacts/communication;" "social environment;" "work;" and "errands/daily routines." Notably, the sentiment analysis revealed that the "contacts/communication" group was characterized by a pronounced negative emotional tone underlying the text reports. This observed heterogeneity in emotional tonality underlying the reported experiences of the first COVID-19-related lockdown is likely to reflect differences in emotional burden, individual circumstances, and ways of coping with the pandemic, which is in line with previous research on this matter., Conclusions: This study illustrates the timely and efficient applicability of an NLP pipeline and thereby serves as a precedent for applied researchers. Our study thereby contributes to both the dissemination of NLP techniques in applied health sciences and the identification of previously unknown experiences and burdens of persons with MS during the pandemic, which may be relevant for future treatment., (©Deborah Chiavi, Christina Haag, Andrew Chan, Christian Philipp Kamm, Chloé Sieber, Mina Stanikić, Stephanie Rodgers, Caroline Pot, Jürg Kesselring, Anke Salmen, Irene Rapold, Pasquale Calabrese, Zina-Mary Manjaly, Claudio Gobbi, Chiara Zecca, Sebastian Walther, Katharina Stegmayer, Robert Hoepner, Milo Puhan, Viktor von Wyl. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 10.11.2022.)

The aim of our study was to investigate whether self-reported feeling of loneliness (FoL) and COVID-19-specific health anxiety were associated with the presence of depressive symptoms during the first coronavirus disease 2019 (COVID-19) wave. Questionnaires of 603 persons of the Swiss Multiple Sclerosis Registry (SMSR) were cross-sectionally analyzed using descriptive and multivariable regression methods. The survey response rate was 63.9%. Depressive symptoms were assessed by the Beck Depression Inventory-Fast Screen (BDI-FS). COVID-19-specific health anxiety and FoL were measured using two 5-item Likert scaled pertinent questions. High scoring FoL (2.52, 95% confidence interval (CI) (2.06-2.98)) and/or COVID-19 specific health anxiety (1.36, 95% CI (0.87-1.85)) were significantly associated with depressive symptoms. Further stratification analysis showed that the impact of FoL on depressive symptoms affected all age groups. However, it was more pronounced in younger PwMS, whereas an impact of COVID-19 specific health anxiety on depressive symptoms was particularly observed in middle-aged PwMS. FoL and COVID-19-specific health anxiety were age-dependently associated with depressive symptoms during the first COVID-19 wave in Switzerland. Our findings could guide physicians, health authorities, and self-help groups to better accompany PwMS in times of public health crises., (© 2022. The Author(s).)

Hair cosmetics such as shampoos, hair dyes, bleaching agents or hair straightening creams contain frequent contact allergens. These can lead to allergic contact dermatitis especially in hairdressers, but also in their customers and in others who use hair products at home. While hairdressers suffer mainly from hand dermatitis, in customers and home-users, dermatitis primarily affects the head, neck and face. In this mini-review, we propose a diagnostic algorithm in two steps, based on patch testing, that can be used for the assessment of suspected hair product-induced contact dermatitis. In a first step, we recommend testing the German Contact Allergy Group (DKG) standard series, DKG ointment series, DKG preservative series, DKG hairdresser series, DKG fragrance series as well as (especially in hairdressers) the DKG rubber series. In a second step, if the culprit allergen cannot be identified with the help of the standardized test series and there is a well-founded suspicion, testing the patient's own products, such as shampoos, hair sprays and hair dyes, is recommended., (© 2021 Deutsche Dermatologische Gesellschaft (DDG). Published by John Wiley & Sons Ltd.)

Background: Multiple sclerosis (MS) symptoms are expected to aggregate in specific patterns across different stages of the disease. Here, we studied the clustering of onset symptoms and examined their characteristics, comorbidity patterns and associations with potential risk factors. Methods: Data stem from the Swiss Multiple Sclerosis Registry, a prospective study including 2,063 participants by November 2019. MS onset symptoms were clustered using latent class analysis (LCA). The latent classes were further examined using information on socio-demographic characteristics, MS-related features, potential risk factors, and comorbid diseases. Results: The LCA model with six classes (frequencies ranging from 12 to 24%) was selected for further analyses. The latent classes comprised a multiple symptoms class with high probabilities across several symptoms, contrasting with two classes with solitary onset symptoms: vision problems and paresthesia. Two gait classes emerged between these extremes: the gait-balance class and the gait-paralysis class. The last class was the fatigue-weakness-class, also accompanied by depression symptoms, memory, and gastro-intestinal problems. There was a moderate variation by sex and by MS types. The multiple symptoms class yielded increased comorbidity with other autoimmune disorders. Similar to the fatigue-weakness class, the multiple symptoms class showed associations with angina, skin diseases, migraine, and lifetime prevalence of smoking. Mononucleosis was more frequently reported in the fatigue-weakness and the paresthesia class. Familial aggregation did not differ among the classes. Conclusions: Clustering of MS onset symptoms provides new perspectives on the heterogeneity of MS. The clusters comprise different potential risk factors and comorbidities. They point toward different risk mechanisms., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Ajdacic-Gross, Steinemann, Horváth, Rodgers, Kaufmann, Xu, Kamm, Kesselring, Manjaly, Zecca, Calabrese, Puhan and Wyl.)

The interrelations between fatigue, depression and health-related quality of life (HRQoL) in persons with multiple sclerosis (PwMS) are complex, and the directionality of the effects is unclear. To address this gap, the current study used a longitudinal design to assess direct and indirect effects of fatigue and depression on HRQoL in a one-year follow-up survey. A sample of 210 PwMS from the nationwide Swiss MS Registry was used. HRQoL was assessed using the European Quality of Life 5-Dimension 5-Level questionnaire. Path analysis on HRQoL, with fatigue and depression as predictors, was applied. Fatigue was measured by the Modified Fatigue Impact Scale (MFIS), including physical, cognitive and psychosocial subscales, and non-somatic depressive symptomatology was examined with the Beck Depression Inventory-Fast Screen (BDI-FS). Fatigue acted as a fully mediating variable (B = -0.718, SE = 0.253) between non-somatic depressive symptomatology and HRQoL. This indirect effect became apparent in the physical (B = -0.624, SE = 0.250), psychosocial (B = -0.538, SE = 0.256) and cognitive subscales (B = -0.485, SE = 0.192) of fatigue. In contrast, non-somatic depressive symptomatology did not act as a mediator. Our findings provide novel and clinically relevant longitudinal evidence showing that the debilitating effect of non-somatic aspects of depression on HRQoL was fully mediated and therefore explainable via fatigue.

Hand dermatitis is a widespread problem among cleaners. In most cases, it is caused by a combination of wet work and contact with irritants, which can result in irritant (toxic) contact dermatitis. In some cases, the irritant contact eczema then evolves into allergic contact dermatitis, although not all cases of allergic contact dermatitis are preceded by irritant contact dermatitis. This mini-review proposes a two-step diagnostic algorithm based on patch testing, which can be used if allergic contact dermatitis is suspected in cleaning workers. As a first step, we recommend performing the DKG standard series (German Contact allergy research group, DKG), the DKG rubber series, both DKG "further fragrances" series as well as the DKG preservative and disinfectant series. If there are clear hints of an occupational contact dermatitis, the first step can also involve testing patients' own products alongside the standardized tests. In a second step (at the latest), if standardized tests do not suffice to identify the culprit allergen and there is well-founded suspicion, we recommend testing the patients' own products. If necessary, the second step can also include testing the individual contact allergens contained in the screening mixes that are part of the standard series., (© 2021 Deutsche Dermatologische Gesellschaft (DDG). Published by John Wiley & Sons Ltd.)

Objective: To compare and characterize major depressive disorder (MDD) subtypes (i.e., pure atypical, pure melancholic and mixed atypical-melancholic) and depression symptoms in persons with multiple sclerosis (PwMS) with persons without MS (Pw/oMS) fulfilling the DSM-5 criteria for a past 12-month MDD., Methods: MDD in PwMS (n = 92) from the Swiss Multiple Sclerosis Registry was compared with Pw/oMS (n = 277) from a Swiss community-based study. Epidemiological MDD diagnoses were based on the Mini-SPIKE (shortened form of the Structured Psychopathological Interview and Rating of the Social Consequences for Epidemiology). Logistic and multinomial regression analyses (adjusted for sex, age, civil status, depression and severity) were computed for comparisons and characterization. Latent class analysis (LCA) was conducted to empirically identify depression subtypes in PwMS., Results: PwMS had a higher risk for the mixed atypical-melancholic MDD subtype (OR = 2.22, 95% CI = 1.03-4.80) compared to Pw/oMS. MDD in PwMS was specifically characterized by a higher risk of the two somatic atypical depression symptoms 'weight gain' (OR = 6.91, 95% CI = 2.20-21.70) and 'leaden paralysis' (OR = 3.03, 95% CI = 1.35-6.82) and the symptom 'irritable/angry' (OR = 3.18, 95% CI = 1.08-9.39)., Conclusions: MDD in PwMS was characterized by a higher risk for specific somatic atypical depression symptoms and the mixed atypical-melancholic MDD subtype. The pure atypical MDD subtype, however, did not differentiate between PwMS and Pw/oMS. Given the high phenomenological overlap with MS symptoms, the mixed atypical-melancholic MDD subtype represents a particular diagnostic challenge., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Aspirin is considered a potential confound for functional magnetic resonance imaging (fMRI) studies. This is because aspirin affects the synthesis of prostaglandin, a vasoactive mediator centrally involved in neurovascular coupling, a process underlying blood oxygenated level dependent (BOLD) responses. Aspirin-induced changes in BOLD signal are a potential confound for fMRI studies of at-risk individuals or patients (e.g. with cardiovascular conditions or stroke) who receive low-dose aspirin prophylactically and are compared to healthy controls without aspirin. To examine the severity of this potential confound, we combined high field (7 Tesla) MRI during a simple hand movement task with a biophysically informed hemodynamic model. We compared elderly individuals receiving aspirin for primary or secondary prophylactic purposes versus age-matched volunteers without aspirin medication, testing for putative differences in BOLD responses. Specifically, we fitted hemodynamic models to BOLD responses from 14 regions activated by the task and examined whether model parameter estimates were significantly altered by aspirin. While our analyses indicate that hemodynamics differed across regions, consistent with the known regional variability of BOLD responses, we neither found a significant main effect of aspirin (i.e., an average effect across brain regions) nor an expected drug × region interaction. While our sample size is not sufficiently large to rule out small-to-medium global effects of aspirin, we had adequate statistical power for detecting the expected interaction. Altogether, our analysis suggests that patients with cardiovascular risk receiving low-dose aspirin for primary or secondary prophylactic purposes do not show strongly altered BOLD signals when compared to healthy controls without aspirin., (© 2020 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Connectomics is essential for understanding large-scale brain networks but requires that individual connection estimates are neurobiologically interpretable. In particular, a principle of brain organization is that reciprocal connections between cortical areas are functionally asymmetric. This is a challenge for fMRI-based connectomics in humans where only undirected functional connectivity estimates are routinely available. By contrast, whole-brain estimates of effective (directed) connectivity are computationally challenging, and emerging methods require empirical validation. Here, using a motor task at 7T, we demonstrate that a novel generative model can infer known connectivity features in a whole-brain network (>200 regions, >40,000 connections) highly efficiently. Furthermore, graph-theoretical analyses of directed connectivity estimates identify functional roles of motor areas more accurately than undirected functional connectivity estimates. These results, which can be achieved in an entirely unsupervised manner, demonstrate the feasibility of inferring directed connections in whole-brain networks and open new avenues for human connectomics., Competing Interests: Declaration of Competing Interest We confirm that there are no conflicts of interest associated with this publication and that there has been no financial support for this work that could have influenced its outcome. Further, we confirm that the manuscript has been read and approved by all authors and that there are no other persons who satisfied the criteria for authorship but are not listed. We confirm that the order of authors listed in the manuscript has been approved by all of us. We confirm that we have given due consideration to the protection of intellectual property associated with this work and that there are no impediments to publication, including the timing of publication, with respect to intellectual property. In so doing we confirm that we have followed the regulations of our institutions concerning intellectual property. We further confirm that any aspect of the work covered in this manuscript that has involved human subjects has been conducted with the ethical approval of all relevant bodies. We understand that the Corresponding Author is the sole contact for the Editorial process (including Editorial Manager and direct communications with the office). He is responsible for communicating with the other authors about progress, submission of revisions and final approval of proofs. We confirm that we have provided a current, correct email address which is accessible by the Corresponding Author., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Mindfulness Based Cognitive Therapy (MBCT) was developed to combine methods from cognitive behavioral therapy and meditative techniques, with the specific goal of preventing relapse in recurrent depression. While supported by empirical evidence from multiple clinical trials, the cognitive mechanisms behind the effectiveness of MBCT are not well understood in computational (information processing) or biological terms. This article introduces a testable theory about the computational mechanisms behind MBCT that is grounded in "Bayesian brain" concepts of perception from cognitive neuroscience, such as predictive coding. These concepts regard the brain as embodying a model of its environment (including the external world and the body) which predicts future sensory inputs and is updated by prediction errors, depending on how precise these error signals are. This article offers a concrete proposal how core concepts of MBCT-(i) the being mode (accepting whatever sensations arise, without judging or changing them), (ii) decentering (experiencing thoughts and percepts simply as events in the mind that arise and pass), and (iii) cognitive reactivity (changes in mood reactivate negative beliefs)-could be understood in terms of perceptual and metacognitive processes that draw on specific computational mechanisms of the "Bayesian brain." Importantly, the proposed theory can be tested experimentally, using a combination of behavioral paradigms, computational modelling, and neuroimaging. The novel theoretical perspective on MBCT described in this paper may offer opportunities for finessing the conceptual and practical aspects of MBCT., (Copyright © 2020 Manjaly and Iglesias.)

Background: Multiple sclerosis (MS) is the most common chronic, non-traumatic, neurologic disease in young adults. While approximate values of the disease burden of MS are known, individual drivers are unknown. Objective: To estimate the age-, sex-, and disease severity-specific contributions to the disease burden of MS. Methods: We estimated the disease burden of MS using disability-adjusted life years (DALYs) following the Global Burden of Disease study (GBD) methodology. The data sources consisted of the Swiss MS Registry, a recent prevalence estimation, and the Swiss mortality registry. Results: The disease burden of MS in Switzerland in 2016 was 6,938 DALYs (95%-interval: 6,018-7,955), which corresponds to 97 DALYs per 100,000 adult inhabitants. Morbidity contributed 59% of the disease burden. While persons in an asymptomatic (EDSS-proxy 0) and mild (EDSS-proxy >0-3.5) disease stage represent 68.4% of the population, they make up 39.8% of the MS-specific morbidity. The remaining 60.2% of the MS-specific morbidity stems from the 31.6% of persons in a moderate (EDSS-proxy 4-6.5) or severe (EDSS-proxy ≥7) disease stage. Conclusions: Morbidity has a larger influence on the disease burden of MS than mortality and is shared in a ratio of 2:3 between persons in an asymptomatic/mild and moderate/severe disease stage in Switzerland. Interventions to reduce severity worsening in combination with tailored, symptomatic treatments are important future paths to lower the disease burden of MS., (Copyright © 2020 Kaufmann, Puhan, Salmen, Kamm, Manjaly, Calabrese, Schippling, Müller, Kuhle, Pot, Gobbi, Steinemann and von Wyl.)

Background: This phase I trial evaluated the safety and immunogenicity of a candidate tuberculosis vaccination regimen, ChAdOx1 85A prime-MVA85A boost, previously demonstrated to be protective in animal studies, in healthy UK adults., Methods: We enrolled 42 healthy, BCG-vaccinated adults into 4 groups: low dose Starter Group (n = 6; ChAdOx1 85A alone), high dose groups; Group A (n = 12; ChAdOx1 85A), Group B (n = 12; ChAdOx1 85A prime - MVA85A boost) or Group C (n = 12; ChAdOx1 85A - ChAdOx1 85A prime - MVA85A boost). Safety was determined by collection of solicited and unsolicited vaccine-related adverse events (AEs). Immunogenicity was measured by antigen-specific ex-vivo IFN-γ ELISpot, IgG serum ELISA, and antigen-specific intracellular IFN-γ, TNF-α, IL-2 and IL-17., Results: AEs were mostly mild/moderate, with no Serious Adverse Events. ChAdOx1 85A induced Ag85A-specific ELISpot and intracellular cytokine CD4+ and CD8+ T cell responses, which were not boosted by a second dose, but were boosted with MVA85A. Polyfunctional CD4+ T cells (IFN-γ, TNF-α and IL-2) and IFN-γ+, TNF-α+ CD8+ T cells were induced by ChAdOx1 85A and boosted by MVA85A. ChAdOx1 85A induced serum Ag85A IgG responses which were boosted by MVA85A., Conclusion: A ChAdOx1 85A prime - MVA85A boost is well tolerated and immunogenic in healthy UK adults., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Immune activation is associated with increased risk of tuberculosis (TB) disease in infants. We performed a case-control analysis to identify drivers of immune activation and disease risk. Among 49 infants who developed TB disease over the first 2 years of life, and 129 healthy matched controls, we found the cytomegalovirus-stimulated (CMV-stimulated) IFN-γ response to be associated with CD8+ T cell activation (Spearman's rho, P = 6 × 10-8). A CMV-specific IFN-γ response was also associated with increased risk of developing TB disease (conditional logistic regression; P = 0.043; OR, 2.2; 95% CI, 1.02-4.83) and shorter time to TB diagnosis (Log Rank Mantel-Cox, P = 0.037). CMV+ infants who developed TB disease had lower expression of NK cell-associated gene signatures and a lower frequency of CD3-CD4-CD8- lymphocytes. We identified transcriptional signatures predictive of TB disease risk among CMV ELISpot-positive (area under the receiver operating characteristic [AUROC], 0.98, accuracy, 92.57%) and -negative (AUROC, 0.9; accuracy, 79.3%) infants; the CMV- signature was validated in an independent infant study (AUROC, 0.71; accuracy, 63.9%). A 16-gene signature that previously identified adolescents at risk of developing TB disease did not accurately classify case and control infants in this study. Understanding the microbial drivers of T cell activation, such as CMV, could guide new strategies for prevention of TB disease in infants.

Background: Chronic itch is the most common skin-related condition, associated with a high psychosocial and economic burden. In recent years, increasing evidence of sex differences in the perception, clinical presentation and treatment requirements of itch points towards potential benefits when using sex-adapted therapies. It is well-known that body composition, absorption, metabolism, elimination and adverse drug reactions (ADRs) differ between sexes, but only little is known about the impact of sex in the pharmacology of itch treatments, which could help to rationalise sex-adapted treatment strategies., Aim: To evaluate and review sex effects in the pharmacokinetics and /-dynamics of drugs used to treat itch., Methods: In this narrative review we performed a PubMed and MEDLINE (Ovid) search using the terms (itch OR pruritus) AND (gender OR sex) AND (drug OR medication OR pharmacokinetics OR pharmacodynamics). Additional searches were performed for the topical and systemic drugs recommended by the European Guideline on Chronic Pruritus., Results: We found numerous reports with variable levels of evidence of sex effects with respect to the pharmacokinetics and/or pharmacodynamics of 14 drug classes used for the treatment of itch, including a total of 19 systemic and 3 topical drugs. Women seem to present higher plasma levels of several drugs used in itch treatment, including tri- and tetracyclic antidepressants (e.g. doxepin, amitriptyline, mirtazapine), serotonin reuptake inhibitors (e.g. paroxetine, sertraline, fluoxetine), immunosuppressive drugs (e.g. cyclosporine, mycophenolate mofetil), serotonin receptor antagonists (e.g. ondansetron) and betablockers (e.g. propranolol). Adverse drug reactions (ADRs) were generally more common in women. Being female was reported to be an independent risk factor for QTc-prolongation associated with antihistamines and tetracyclic antidepressants. Additionally, women seem to be more prone to sedative effects of antihistamines, and to suffer from a higher frequency as well as severity of side effects with systemic calcineurin inhibitors, opioid agonists, and opioid antagonists. Women were also sensitised more often to topically applied drugs. Of note, apart from only one experimental study with capsaicin, none of these reports were designed specifically to assess the effect of sex (and gender) in the treatment of itch., Discussion/conclusion: Our review supports previous reports that sex is of importance in the pharmacokinetics and /-dynamics of several drugs used to treat itch although those drugs were mostly evaluated for non-itch indications. However, the results are limited by methodological limitations evident in most studies such as underrepresentation of women in clinical trials. This emphasises the need to study the impact of sex (and gender) in future itch trials to yield better outcomes and prevent ADRs in both sexes., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Fatigue is one of the most common symptoms in multiple sclerosis (MS), with a major impact on patients' quality of life. Currently, treatment proceeds by trial and error with limited success, probably due to the presence of multiple different underlying mechanisms. Recent neuroscientific advances offer the potential to develop tools for differentiating these mechanisms in individual patients and ultimately provide a principled basis for treatment selection. However, development of these tools for differential diagnosis will require guidance by pathophysiological and cognitive theories that propose mechanisms which can be assessed in individual patients. This article provides an overview of contemporary pathophysiological theories of fatigue in MS and discusses how the mechanisms they propose may become measurable with emerging technologies and thus lay a foundation for future personalised treatments., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

The development of whole-brain models that can infer effective (directed) connection strengths from fMRI data represents a central challenge for computational neuroimaging. A recently introduced generative model of fMRI data, regression dynamic causal modeling (rDCM), moves towards this goal as it scales gracefully to very large networks. However, large-scale networks with thousands of connections are difficult to interpret; additionally, one typically lacks information (data points per free parameter) for precise estimation of all model parameters. This paper introduces sparsity constraints to the variational Bayesian framework of rDCM as a solution to these problems in the domain of task-based fMRI. This sparse rDCM approach enables highly efficient effective connectivity analyses in whole-brain networks and does not require a priori assumptions about the network's connectivity structure but prunes fully (all-to-all) connected networks as part of model inversion. Following the derivation of the variational Bayesian update equations for sparse rDCM, we use both simulated and empirical data to assess the face validity of the model. In particular, we show that it is feasible to infer effective connection strengths from fMRI data using a network with more than 100 regions and 10,000 connections. This demonstrates the feasibility of whole-brain inference on effective connectivity from fMRI data - in single subjects and with a run-time below 1 min when using parallelized code. We anticipate that sparse rDCM may find useful application in connectomics and clinical neuromodeling - for example, for phenotyping individual patients in terms of whole-brain network structure., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Physiological noise is one of the major confounds for fMRI. A common class of correction methods model noise from peripheral measures, such as ECGs or pneumatic belts. However, physiological noise correction has not emerged as a standard preprocessing step for fMRI data yet due to: (1) the varying data quality of physiological recordings, (2) non-standardized peripheral data formats and (3) the lack of full automatization of processing and modeling physiology, required for large-cohort studies., New Methods: We introduce the PhysIO Toolbox for preprocessing of physiological recordings and model-based noise correction. It implements a variety of noise models, such as RETROICOR, respiratory volume per time and heart rate variability responses (RVT/HRV). The toolbox covers all intermediate steps - from flexible read-in of data formats to GLM regressor/contrast creation - without any manual intervention., Results: We demonstrate the workflow of the toolbox and its functionality for datasets from different vendors, recording devices, field strengths and subject populations. Automatization of physiological noise correction and performance evaluation are reported in a group study (N=35)., Comparison With Existing Methods: The PhysIO Toolbox reproduces physiological noise patterns and correction efficacy of previously implemented noise models. It increases modeling robustness by outperforming vendor-provided peak detection methods for physiological cycles. Finally, the toolbox offers an integrated framework with full automatization, including performance monitoring, and flexibility with respect to the input data., Conclusions: Through its platform-independent Matlab implementation, open-source distribution, and modular structure, the PhysIO Toolbox renders physiological noise correction an accessible preprocessing step for fMRI data., (Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.)

This paper outlines a hierarchical Bayesian framework for interoception, homeostatic/allostatic control, and meta-cognition that connects fatigue and depression to the experience of chronic dyshomeostasis. Specifically, viewing interoception as the inversion of a generative model of viscerosensory inputs allows for a formal definition of dyshomeostasis (as chronically enhanced surprise about bodily signals, or, equivalently, low evidence for the brain's model of bodily states) and allostasis (as a change in prior beliefs or predictions which define setpoints for homeostatic reflex arcs). Critically, we propose that the performance of interoceptive-allostatic circuitry is monitored by a metacognitive layer that updates beliefs about the brain's capacity to successfully regulate bodily states (allostatic self-efficacy). In this framework, fatigue and depression can be understood as sequential responses to the interoceptive experience of dyshomeostasis and the ensuing metacognitive diagnosis of low allostatic self-efficacy. While fatigue might represent an early response with adaptive value (cf. sickness behavior), the experience of chronic dyshomeostasis may trigger a generalized belief of low self-efficacy and lack of control (cf. learned helplessness), resulting in depression. This perspective implies alternative pathophysiological mechanisms that are reflected by differential abnormalities in the effective connectivity of circuits for interoception and allostasis. We discuss suitably extended models of effective connectivity that could distinguish these connectivity patterns in individual patients and may help inform differential diagnosis of fatigue and depression in the future.

Previous studies found normal or even superior performance of autistic patients on visuospatial tasks requiring local search, like the Embedded Figures Task (EFT). A well-known interpretation of this is "weak central coherence", i.e. autistic patients may show a reduced general ability to process information in its context and may therefore have a tendency to favour local over global aspects of information processing. An alternative view is that the local processing advantage in the EFT may result from a relative amplification of early perceptual processes which boosts processing of local stimulus properties but does not affect processing of global context. This study used functional magnetic resonance imaging (fMRI) in 12 autistic adolescents (9 Asperger and 3 high-functioning autistic patients) and 12 matched controls to help distinguish, on neurophysiological grounds, between these two accounts of EFT performance in autistic patients. Behaviourally, we found autistic individuals to be unimpaired during the EFT while they were significantly worse at performing a closely matched control task with minimal local search requirements. The fMRI results showed that activations specific for the local search aspects of the EFT were left-lateralised in parietal and premotor areas for the control group (as previously demonstrated for adults), whereas for the patients these activations were found in right primary visual cortex and bilateral extrastriate areas. These results suggest that enhanced local processing in early visual areas, as opposed to impaired processing of global context, is characteristic for performance of the EFT by autistic patients.

The Embedded Figures Task (EFT) involves search for a target hidden in a complex geometric pattern. Even though the EFT is designed to probe local visual search functions, not language-related processes, neuropsychological studies have demonstrated a strong association between aphasia and impairment on this task. A potential explanation for this relationship was offered by a recent functional MRI study (Manjaly et al., 2003), which demonstrated that a part of the left posterior inferior frontal gyrus (pIFG), overlapping with Broca's region, is crucially involved in the execution of the EFT. This result suggested that pIFG, an area strongly associated with language-related functions, is also part of a network subserving cognitive functions unrelated to language. In this study, we tested this conjecture by analysing the data of Manjaly et al. for context-dependent functional interactions of the pIFG during execution of the EFT. The results showed that during EFT, compared to a similar visual matching task with minimal local search components, pIFG changed its interactions with areas commonly involved in visuospatial processing: Increased contributions to neural activity in left posterior parietal cortex, cerebellar vermis, and extrastriate areas bilaterally, as well as decreased contributions to bilateral temporo-parietal cortex, posterior cingulate cortex, and left dorsal premotor cortex were found. These findings demonstrate that left pIFG can be involved in nonlanguage processes. More generally, however, they provide a concrete example of the notion that there is no general one-to-one mapping between cognitive functions and the activations of individual areas. Instead, it is the spatiotemporal pattern of functional interactions between areas that is linked to a particular cognitive context.

The Embedded Figures Task involves a search for a target hidden in a more complex visual pattern. The task has been used to study local perception and visual search in a range of normal and pathological populations. After acquired brain damage, impairment on embedded figures is strongly associated with aphasia; in the context of developmental disorder, people with autism or with Asperger's syndrome are reliably found to be better than normal controls on the task. The current study employed functional MRI with healthy volunteers to elucidate the brain regions that are specifically involved in the local search aspects of the Embedded Figures Task. We did so by analyzing the neural activations that are implicated in the task over and above those involved in an easier visual search task and in a straightforward shape recognition task. Significant activations (P < 0.05, corrected) specific in the above sense to the Embedded Figures Task were found in left inferior and left superior parietal cortex and in left ventral premotor cortex (inferior frontal gyrus). By contrast, comparing the overall effect of visual search within geometric figures to pure recognition of geometric shapes revealed more widespread activations in parietal, occipital, cerebellar, and frontal areas bilaterally. The implications of these findings for some developmental and acquired pathologies of perceptual functioning are outlined. We also relate our results to studies of local/global processing in other tasks.