DPVis: Visual Analytics with Hidden Markov Models for Disease Progression Pathways

Clinical researchers use disease progression models to understand patient status and characterize progression patterns from longitudinal health records. One approach for disease progression modeling is to describe patient status using a small number of states that represent distinctive distributions over a set of observed measures. Hidden Markov models (HMMs) and its variants are a class of models that both discover these states and make inferences of health states for patients. Despite the advantages of using the algorithms for discovering interesting patterns, it still remains challenging for medical experts to interpret model outputs, understand complex modeling parameters, and clinically make sense of the patterns. To tackle these problems, we conducted a design study with clinical scientists, statisticians, and visualization experts, with the goal to investigate disease progression pathways of chronic diseases, namely type 1 diabetes (T1D), Huntington's disease, Parkinson's disease, and chronic obstructive pulmonary disease (COPD). As a result, we introduce DPVis which seamlessly integrates model parameters and outcomes of HMMs into interpretable and interactive visualizations. In this study, we demonstrate that DPVis is successful in evaluating disease progression models, visually summarizing disease states, interactively exploring disease progression patterns, and building, analyzing, and comparing clinically relevant patient subgroups.Comment: to appear at IEEE Transactions on Visualization and Computer Graphic

Mapping the distribution of scale-rayed wrasse Acantholabrus palloni in Swedish Skagerrak using angling records

In this paper, we map the distribution of scale-rayed wrasse Acantholabrus palloni in eastern Skagerrak based on a combination of verified and personally communicated angling records. Long thought to be occasional vagrants outside its known range in the eastern Atlantic Ocean and Mediterranean Sea, we ask if this rare and understudied labrid has expanded its range and become established in Swedish waters. A recent surge in verified angling records in the Swedish Anglers Association’s specimen database Storfiskregistret provides information to suggest that this species should no longer be considered an occasional guest, but rather a species established in the Swedish parts of Skagerrak. These records are supported by additional personal communications with anglers. The species is currently well spread geographically along the Swedish Skagerrak coast, with many locations providing repeated captures of adult fish over multiple years. The typical Swedish catch sites are rocky reefs located between the general 40- and 80-m depth curves, likely influenced by currents bringing higher-salinity water from the North Sea. The present study show that angling records can provide an important, but underutilized, resource for mapping the distribution of data-deficient fish species

The Global Governance of Artificial Intelligence: Next Steps for Empirical and Normative Research

Artificial intelligence (AI) represents a technological upheaval with the potential to change human society. Because of its transformative potential, AI is increasingly becoming subject to regulatory initiatives at the global level. Yet, so far, scholarship in political science and international relations has focused more on AI applications than on the emerging architecture of global AI regulation. The purpose of this article is to outline an agenda for research into the global governance of AI. The article distinguishes between two broad perspectives: an empirical approach, aimed at mapping and explaining global AI governance; and a normative approach, aimed at developing and applying standards for appropriate global AI governance. The two approaches offer questions, concepts, and theories that are helpful in gaining an understanding of the emerging global governance of AI. Conversely, exploring AI as a regulatory issue offers a critical opportunity to refine existing general approaches to the study of global governance

Cord blood insulinoma-associated protein 2 autoantibodies are associated with increased risk of type 1 diabetes in the population-based Diabetes Prediction in Skane study

Aims/hypothesis The aim of this study was to examine the effect of cord blood autoantibodies on the risk for type 1 diabetes in children followed prospectively from birth. Methods The Diabetes Prediction in Skane (DiPiS) study consists of 35,853 children from the general population born during 2000-2004. Samples were collected at birth and analysed for HLA genotypes and autoantibodies to glutamate decarboxylase 65 (GAD65), insulin and insulinoma-associated protein 2 (IA-2). After adjusting for HLA, sex, maternal age and parental type 1 diabetes, independent associations with risk of diabetes were assessed using multivariate Cox proportional hazards models. Results In total, 151 children (0.4%) had developed type 1 diabetes by the end of 2013 at a median age of 5.8 years (0.8-12.2 years). In the multivariate analysis, the presence of IA-2 autoantibodies (IA-2A) in cord blood (HR 6.88, 95% CI 1.46,32.4; p = 0.003), but not maternal diabetes (HR 1.38, 95% CI 0.24,7.84; p = 0.71), was associated with risk of developing type 1 diabetes. No increased risk could be seen for the presence of autoantibodies to GAD65 or insulin. Conclusions/interpretation Our study indicates that the presence of cord blood IA-2A superimposes maternal diabetes and other cord blood islet autoantibodies as a predictor of type 1 diabetes development in the child. These findings may be of significance for future screening and study protocols on type 1 diabetes prediction

Practical management in Wolcott-Rallison syndrome with associated hypothyroidism, neutropenia, and recurrent liver failure: A case report

Wolcott-Rallison syndrome is a rare genetic syndrome of neonatal diabetes, liver failure, and growth retardation. We present a case with a EIF2AK3 p.(Arg902Ter) mutation, additionally complicated by hypothyroidism, impaired renal function, and exocrine pancreas insufficiency, focusing on clinical management. For its optimization, thorough care of multiple organ systems is needed.This article is freely available via Open Access. Click on the Publisher URL to access the full-text from the publisher's site

BMI is positively associated with accelerated epigenetic aging in twin pairs discordant for body mass index

Background Obesity is a heritable complex phenotype that can increase the risk of age-related outcomes. Biological age can be estimated from DNA methylation (DNAm) using various "epigenetic clocks." Previous work suggests individuals with elevated weight also display accelerated aging, but results vary by epigenetic clock and population. Here, we utilize the new epigenetic clock GrimAge, which closely correlates with mortality. Objectives We aimed to assess the cross-sectional association of body mass index (BMI) with age acceleration in twins to limit confounding by genetics and shared environment. Methods and results Participants were from the Finnish Twin Cohort (FTC; n = 1424), including monozygotic (MZ) and dizygotic (DZ) twin pairs, and DNAm was measured using the Illumina 450K array. Multivariate linear mixed effects models including MZ and DZ twins showed an accelerated epigenetic age of 1.02 months (p-value = 6.1 x 10(-12)) per one-unit BMI increase. Additionally, heavier twins in a BMI-discordant MZ twin pair (Delta BMI >3 kg/m(2)) had an epigenetic age 5.2 months older than their lighter cotwin (p-value = 0.0074). We also found a positive association between log (homeostatic model assessment of insulin resistance) and age acceleration, confirmed by a meta-analysis of the FTC and two other Finnish cohorts (overall effect = 0.45 years, p-value = 4.1 x 10(-25)) from adjusted models. Conclusion We identified significant associations of BMI and insulin resistance with age acceleration based on GrimAge, which were not due to genetic effects on BMI and aging. Overall, these results support a role of BMI in aging, potentially in part due to the effects of insulin resistance.Peer reviewe

Imputing Longitudinal Growth Data in International Pediatric Studies: Does CDC Reference Suffice?

This study investigates a missing value imputation approach for longitudinal growth data in pediatric studies from multiple countries. We analyzed a combined cohort from five natural history studies of type 1 diabetes (T1D) in the US and EU with longitudinal growth measurements for 23,201 subjects. We developed a multiple imputation methodology using LMS parameters of CDC reference data. We measured imputation errors on both combined and individual cohorts using mean absolute percentage error (MAPE) and normalized root-mean-square error (NRMSE). Our results show low imputation errors using CDC reference. Overall height imputation errors were lower than for weight. The largest MAPE for weight and height among all age groups was 4.8% and 1.7%, respectively. When comparing performance between CDC reference and country-specific growth charts, we found no significant differences for height (CDC vs. German: p =0.993, CDC vs. Swedish: p=0.368) and for weight (CDC vs. Swedish: p=0.513) for all ages

Effectiveness of multimodal treatment for young people with body dysmorphic disorder in two specialist clinics

Body dysmorphic disorder (BDD) typically originates in adolescence and is associated with considerable adversity. Evidence-based treatments exist but research on clinical outcomes in naturalistic settings is extremely scarce. We evaluated the short- and long-term outcomes of a large cohort of adolescents with BDD receiving specialist multimodal treatment and examined predictors of symptom improvement. We followed 140 young people (age range 10-18) with a diagnosis of BDD treated at two national and specialist outpatient clinics in Stockholm, Sweden (n=96) and London, England (n=44), between January 2015 and April 2021. Participants received multimodal treatment consisting of cognitive behaviour therapy and, in 72% of cases, medication (primarily selective serotonin reuptake inhibitors). Data were collected at baseline, post-treatment, and 3, 6, and 12 months after treatment. The primary outcome measure was the clinician-rated Yale-Brown Obsessive-Compulsive Scale Modified for BDD, Adolescent version (BDD-YBOCS-A). Secondary outcomes included self-reported measures of BDD symptoms, depressive symptoms, and global functioning. Mixed-effects regression models showed that BDD-YBOCS-A scores decreased significantly from baseline to post-treatment (coefficient [95% confidence interval]=-16.33 [-17.90 to -14.76], p<0.001; within-group effect size (Cohen’s d)=2.08 (95% confidence interval, 1.81 to 2.35). At the end of the treatment, 79% of the participants were classified as responders and 59% as full or partial remitters. BDD symptoms continued to improve throughout the follow-up. Improvement was also seen on all secondary outcome measures. Linear regression models identified baseline BDD symptom severity as a predictor of treatment outcome at post-treatment, but no consistent predictors were found at the 12-month follow-up. To conclude, multimodal treatment for adolescent BDD is effective in both the short- and long-term when provided flexibly within a specialist setting. Considering the high personal and societal costs of BDD, specialist care should be made more widely available

A prospective service evaluation of acceptance and commitment therapy for patients with refractory epilepsy

Objective: The aims of this service evaluation were to explore the effectiveness of a psychotherapeutic treatment for patients with epilepsy based on the acceptance and commitment therapy (ACT) approach and to assess whether this treatment is likely to be cost-effective. Method: We conducted an uncontrolled prospective study of consecutive patients with refractory epilepsy referred for outpatient psychological treatment to a single psychotherapist because of emotional difficulties related to their seizure disorder. Participants were referred by consultant neurologists, neuropsychologists, or epilepsy nurses, completed a set of validated self-report questionnaires (Short Form - 12 version 2, Generalized Anxiety Disorder - 7, Neurological Disorders Depression Inventory for Epilepsy, Work and Social Adjustment Scale, and Rosenberg Self-Esteem Scale), and reported their seizure frequency at referral, the end of therapy, and six months posttherapy. Patients received a maximum of 20 sessions of one-to-one psychological treatment supported by a workbook. Cost-effectiveness was estimated based on the calculation of quality-adjusted life year (QALY) gains associated with the intervention. Results: Sixty patients completed the prepsychotherapy and postpsychotherapy questionnaires, among whom 41 also provided six-month follow-up data. Patients received six to 20 sessions of psychotherapy (mean = 11.5, S.D. = 9.6). Psychotherapy was associated with significant medium to large positive effects on depression, anxiety, quality of life, self-esteem, and work and social adjustment ( ps < .001), which were sustained six months after therapy. The mean cost of the psychotherapy was £445.6, and, assuming that benefits were maintained for at least six months after the end of therapy, the cost per QALY was estimated to be £11,140 (€14,119, $18,016; the cost per QALY would be half this amount if the benefits lasted one year). Conclusion: The findings of this pilot study indicate that the described psychotherapeutic intervention may be a cost-effective treatment for patients with epilepsy. The results suggest that a randomized controlled trial of the psychotherapy program is justified