The ABCD of obesity: An EASO position statement on a diagnostic term with clinical and scientific implications

Obesity is a frequent, serious, complex, relapsing, and chronic disease process that represents a major public health problem. The coining of obesity as an adiposity-based chronic disease (ABCD) is of particular relevance being in line with EASO’s proposal to improve the International Classification of Diseases ICD-11 diagnostic criteria for obesity based on three dimensions, namely etiology, degree of adiposity, and health risks. The body mass index as a unique measurement of obesity does not reflect the whole complexity of the disease. Obesity complications are mainly determined by 2 pathological processes, i.e., physical forces (fat mass disease) as well as endocrine and immune responses (sick fat disease), which are embedded in a cultural and physical context leading to a specific ABCD stage

Performance deficits of NK1 receptor knockout mice in the 5 choice serial reaction time task: effects of d Amphetamine, stress and time of day.

Background The neurochemical status and hyperactivity of mice lacking functional substance P-preferring NK1 receptors (NK1R-/-) resemble abnormalities in Attention Deficit Hyperactivity Disorder (ADHD). Here we tested whether NK1R-/- mice express other core features of ADHD (impulsivity and inattentiveness) and, if so, whether they are diminished by d-amphetamine, as in ADHD. Prompted by evidence that circadian rhythms are disrupted in ADHD, we also compared the performance of mice that were trained and tested in the morning or afternoon. Methods and Results The 5-Choice Serial Reaction-Time Task (5-CSRTT) was used to evaluate the cognitive performance of NK1R-/- mice and their wildtypes. After training, animals were tested using a long (LITI) and a variable (VITI) inter-trial interval: these tests were carried out with, and without, d-amphetamine pretreatment (0.3 or 1 mg/kg i.p.). NK1R-/- mice expressed greater omissions (inattentiveness), perseveration and premature responses (impulsivity) in the 5-CSRTT. In NK1R-/- mice, perseveration in the LITI was increased by injection-stress but reduced by d-amphetamine. Omissions by NK1R-/- mice in the VITI were unaffected by d-amphetamine, but premature responses were exacerbated by this psychostimulant. Omissions in the VITI were higher, overall, in the morning than the afternoon but, in the LITI, premature responses of NK1R-/- mice were higher in the afternoon than the morning. Conclusion In addition to locomotor hyperactivity, NK1R-/- mice express inattentiveness, perseveration and impulsivity in the 5-CSRTT, thereby matching core criteria for a model of ADHD. Because d-amphetamine reduced perseveration in NK1R-/- mice, this action does not require functional NK1R. However, the lack of any improvement of omissions and premature responses in NK1R-/- mice given d-amphetamine suggests that beneficial effects of this psychostimulant in other rodent models, and ADHD patients, need functional NK1R. Finally, our results reveal experimental variables (stimulus parameters, stress and time of day) that could influence translational studies

Democratized image analytics by visual programming through integration of deep models and small-scale machine learning

Analysis of biomedical images requires computational expertize that are uncommon among biomedical scientists. Deep learning approaches for image analysis provide an opportunity to develop user-friendly tools for exploratory data analysis. Here, we use the visual programming toolbox Orange (http://orange.biolab.si) to simplify image analysis by integrating deep-learning embedding, machine learning procedures, and data visualization. Orange supports the construction of data analysis workflows by assembling components for data preprocessing, visualization, and modeling. We equipped Orange with components that use pre-trained deep convolutional networks to profile images with vectors of features. These vectors are used in image clustering and classification in a framework that enables mining of image sets for both novel and experienced users. We demonstrate the utility of the tool in image analysis of progenitor cells in mouse bone healing, identification of developmental competence in mouse oocytes, subcellular protein localization in yeast, and developmental morphology of social amoebae

Sj\uf6gren's syndrome: state of the art on clinical practice guidelines

Sj\uf6gren's syndrome (SS) is a complex autoimmune rheumatic disease that specifically targets salivary and lachrymal glands. As such, patients typically had ocular and oral dryness and salivary gland swelling. Moreover, skin, nasal and vaginal dryness are frequently present. In addition to dryness, musculoskeletal pain and fatigue are the hallmarks of this disease and constitute the classic symptom triad presented by the vast majority of patients. Up to 30% to 50 % of patients with SS may present systemic disease; moreover, there is an increased risk for the development of non-Hodgkin's lymphoma that occurs in a minority of patients. The present work was developed in the framework of the European Reference Network (ERN) dedicated to Rare and Complex Connective Tissue and Musculoskeletal Diseases (ReCONNET). In line with its goals of aiming to improve early diagnosis, treatment and care of rare connective and musculoskeletal diseases, ERN-ReCONNET set to review the current state of clinical practice guidelines (CPGs) in the rare and complex connective tissue diseases of interest of the network. Therefore, the present work was aimed at providing a state of the art of CPGs for SS