Psoriatic Pseudobalanitis Circinata as a Post-Viral Koebner Phenomenon

In the absence of any other lesions on the body, the diagnosis of localized genital psoriasis can be difficult, requiring further examinations including a biopsy. We report a case of psoriatic pseudobalanitis circinata triggered by a herpes virus infection, and we discuss the Koebner phenomenon and the therapeutic management of psoriasis of the genital area

Label noise and self-learning label correction in cardiac abnormalities classification.

OBJECTIVE Learning to classify cardiac abnormalities requires large and high-quality labeled datasets, which is a challenge in medical applications. Small datasets from various sources are often aggregated to meet this requirement, resulting in a final dataset prone to label noise owing to inter- and intra-observer variability, and different expertise. It is well known that label noise can affect the performance and generalizability of the trained models. In this work, we explore the impact of label noise and self-learning label correction on the classification of cardiac abnormalities on large heterogeneous datasets of electrocardiogram (ECG) signals. APPROACH A state-of-the-art self-learning multi-class label correction method for image classification is adapted to learn a multi-label classifier for electrocardiogram signals. We evaluated our performance using 5-fold cross-validation on the publicly available PhysioNet/Computing in Cardiology (CinC) 2021 Challenge data, with full and reduced sets of leads. Due to the unknown label noise in the testing set, we tested our approach on the MNIST dataset. We investigated the performance under different levels of structured label noise for both datasets. MAIN RESULTS Under high levels of noise, the cross-validation results of self-learning label correction showed an improvement of approximately 3% in the Challenge score for the PhysioNet/CinC 2021 Challenge dataset and, an improvement in accuracy of 5$\%$ and reduction of the expected calibration error of 0.03 for the MNIST dataset. We demonstrate that self-learning label correction can be used to effectively deal with the presence of unknown label noise, also when using a reduced number of ECG leads

Urinary tract infection in the newborn and the infant: state of the art

Urinary tract infection is one of the most common causes of infection in newborns. Obtaining a urinary tract infections (UTIs) diagnosis just on the basis of the clinical findings is frequently difficult, however, being the pediatrician's goal to reduce the risk of renal scarring, a prompt diagnosis and treatment is of extreme importance. The key instrument for the diagnosis of UTIs is represented today by urine culture. However, in reality, the caregivers and investigators are increasingly demanding fast and cheap methods for a rapid and effective diagnosis

Pazopanib for the Treatment of Patients with Advanced Renal Cell Carcinoma

Dramatic advances in the care of patients with advanced renal cell carcinoma have occurred over the last ten years, including insights into the molecular pathogenesis of this disease, that have now been translated into paradigm-changing therapeutic strategies. Elucidating the importance of signaling cascades related to angiogenesis is notable among these achievements. Pazopanib is a novel small molecule tyrosine kinase inhibitor that targets VEGFR-1, -2, and -3; PDGFR-α, PDGFR-β; and c-kit tyrosine kinases. This agent exhibits a distinct pharmacokinetic profile as well as toxicity profile compared to other agents in the class of VEGF signaling pathway inhibitors. This review will discuss the scientific rationale for the development of pazopanib, as well as preclinical and clinical trials that led to approval of pazopanib for patients with advanced renal cell carcinoma. The most recent information, including data from 2010 national meeting of the American Society of Clinical Oncology, and the design of ongoing Phase III trials, will be discussed. Finally, an algorithm utilizing Level I evidence for the treatment of patients with this disease will be proposed

Quantifying cancer progression with conjunctive Bayesian networks

Motivation: Cancer is an evolutionary process characterized by accumulating mutations. However, the precise timing and the order of genetic alterations that drive tumor progression remain enigmatic

Unique functions for Notch4 in murine embryonic lymphangiogenesis

Publisher Copyright: © 2021, The Author(s).In mice, embryonic dermal lymphatic development is well understood and used to study gene functions in lymphangiogenesis. Notch signaling is an evolutionarily conserved pathway that modulates cell fate decisions, which has been shown to both inhibit and promote dermal lymphangiogenesis. Here, we demonstrate distinct roles for Notch4 signaling versus canonical Notch signaling in embryonic dermal lymphangiogenesis. Actively growing embryonic dermal lymphatics expressed NOTCH1, NOTCH4, and DLL4 which correlated with Notch activity. In lymphatic endothelial cells (LECs), DLL4 activation of Notch induced a subset of Notch effectors and lymphatic genes, which were distinctly regulated by Notch1 and Notch4 activation. Treatment of LECs with VEGF-A or VEGF-C upregulated Dll4 transcripts and differentially and temporally regulated the expression of Notch1 and Hes/Hey genes. Mice nullizygous for Notch4 had an increase in the closure of the lymphangiogenic fronts which correlated with reduced vessel caliber in the maturing lymphatic plexus at E14.5 and reduced branching at E16.5. Activation of Notch4 suppressed LEC migration in a wounding assay significantly more than Notch1, suggesting a dominant role for Notch4 in regulating LEC migration. Unlike Notch4 nulls, inhibition of canonical Notch signaling by expressing a dominant negative form of MAML1 (DNMAML) in Prox1+ LECs led to increased lymphatic density consistent with an increase in LEC proliferation, described for the loss of LEC Notch1. Moreover, loss of Notch4 did not affect LEC canonical Notch signaling. Thus, we propose that Notch4 signaling and canonical Notch signaling have distinct functions in the coordination of embryonic dermal lymphangiogenesis.Peer reviewe

Gene Expression Profiling Predicts Survival in Conventional Renal Cell Carcinoma

BACKGROUND: Conventional renal cell carcinoma (cRCC) accounts for most of the deaths due to kidney cancer. Tumor stage, grade, and patient performance status are used currently to predict survival after surgery. Our goal was to identify gene expression features, using comprehensive gene expression profiling, that correlate with survival. METHODS AND FINDINGS: Gene expression profiles were determined in 177 primary cRCCs using DNA microarrays. Unsupervised hierarchical clustering analysis segregated cRCC into five gene expression subgroups. Expression subgroup was correlated with survival in long-term follow-up and was independent of grade, stage, and performance status. The tumors were then divided evenly into training and test sets that were balanced for grade, stage, performance status, and length of follow-up. A semisupervised learning algorithm (supervised principal components analysis) was applied to identify transcripts whose expression was associated with survival in the training set, and the performance of this gene expression-based survival predictor was assessed using the test set. With this method, we identified 259 genes that accurately predicted disease-specific survival among patients in the independent validation group (p < 0.001). In multivariate analysis, the gene expression predictor was a strong predictor of survival independent of tumor stage, grade, and performance status (p < 0.001). CONCLUSIONS: cRCC displays molecular heterogeneity and can be separated into gene expression subgroups that correlate with survival after surgery. We have identified a set of 259 genes that predict survival after surgery independent of clinical prognostic factors