Inhibition of either UA or IL-1β during RSV infection led to chronic reductions in pulmonary immune cell composition and reduced type 2 immune responses and reduced similar responses after challenge with cockroach antigen. CONCLUSIONS Inhibiting UA and IL-1β during RSV infection ameliorates RSV immunopathology, reduces the consequences of allergen-induced asthma, and presents new therapeutic targets to reduce early-life viral-induced asthma development. This article is protected by copyright. All rights reserved.AIM To describe the clinical and neurogenetic spectrum of paediatric-onset hereditary spastic paraplegias (HSPs) diagnosed in our unit. METHOD We report on 47 patients (30 males, 17 females; mean [SD] age 12y 7mo [6y 2mo], range 4-34y) clinically diagnosed with an HSP at the Child Neurology Unit, IRCCS-ASMN (Reggio Emilia, Italy) between 1990 and 2018, who were genetically investigated by means of single-gene direct sequencing and/or next-generation sequencing technologies (targeted panels, whole-exome sequencing [WES]). RESULTS Complex forms prevailed slightly (n=26), autosomal dominant being the main inheritance pattern (n=11), followed by recessive (n=5) and X-linked (n=1). A definite genetic diagnosis was achieved in 17 patients. Spastic paraplegia 3A (n=4) was the most frequent cause of autosomal dominant HSP in our cohort, while no genetic variant prevailed in autosomal recessive forms and pathogenic/likely pathogenic variants were disclosed in a wide range of different genes. INTERPRETATION We found wide phenotypic and genetic heterogeneity. With increasing accessibility to WES, a higher number of patients receive a diagnosis, allowing detection of variants in ultra-rare disease-causing genes and refining genotype-phenotype correlations. WHAT THIS PAPER ADDS A genetic diagnosis of paediatric-onset hereditary spastic paraplegia was achieved in one-third of patients. Pathogenic/likely pathogenic variants in rare genes were found. Genotypic and phenotypic heterogeneity favours targeted panel/whole-exome sequencing for diagnosis. © 2020 Mac Keith Press.This review and synthesis discusses recent work that has utilized brain imaging methods, such as the electroencephalogram (EEG) and magnetoencephalogram, to provide insights into the ways that the body is represented in the infant brain. One aspect of body representation concerns somatotopic maps of the body surface in somatosensory cortex. A good deal is known about the properties of these maps in adults, but there has been relatively little developmental work. Recent studies have provided new insights into the organization of infant neural body maps and have laid the foundations for examining their plasticity in relation to behavioral development. Other work has suggested that neural body maps may be involved in the registration of correspondences between self and other, with implications for early social development. Here, body representations are discussed in the context of preterm birth and autism spectrum disorder, providing novel perspectives relevant to developmental medicine and child neurology. WHAT THIS PAPER ADDS ●Somatotopic body maps develop prenatally through intrinsic and activity-dependent mechanisms. ●There is increasing interest in understanding postnatal plasticity in body maps. ●Body representations may be involved in the registration of preverbal, interpersonal relationships. © 2020 Mac Keith Press.The effect of selection on female genitalia is poorly studied, but such selection could affect mating success. House et al. (2020) studied the form and strength of selection acting on male and female Tribolium castaneum. They found that the sex organs of both male and female T. castaneum are under multivariate stabilizing selection and that both male and female genitalia interact to influence mating success. © 2020 The Authors. Evolution © 2020 The Society for the Study of Evolution.Epithelial ovarian cancer (EOC) is a complex disease comprising discrete histological and molecular subtypes, for which survival rates remain unacceptably low. Tailored approaches for this deadly heterogeneous disease are urgently needed. Efflux pumps belonging to the ATP-binding cassette (ABC) family of transporters are known for roles in both drug resistance and cancer biology and are also highly targetable. Here we have investigated the association of ABCC4/MRP4 expression to clinical outcome and its biological function in endometrioid and serous tumors, common histological subtypes of EOC. We found high expression of ABCC4/MRP4, previously shown to be directly regulated by c-Myc/N-Myc, was associated with poor prognosis in endometrioid EOC (P = 0.001) as well as in a subset of serous EOC with a "high-MYCN" profile (C5/Proliferative; P = 0.019). Transient siRNA-mediated suppression of MRP4 in EOC cells led to reduced growth, migration and invasion, with the effects being most pronounced in endometrioid and C5-like serous cells compared to non-C5 serous EOC cells. Sustained knockdown of MRP4 also sensitized endometrioid cells to MRP4 substrate drugs. Furthermore, suppression of MRP4 decreased the growth of patient-derived EOC cells in vivo. Together, our findings provide the first evidence that MRP4 plays an important role in the biology of Myc-associated ovarian tumors and highlight this transporter as a potential therapeutic target for EOC. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.PURPOSE Gliomas are the most common primary tumor of the brain and are classified into grades I-IV of the World Health Organization (WHO), based on their invasively histological appearance. Gliomas grading plays an important role to determine the treatment plan and prognosis prediction. In this study we propose two novel methods for automatic, non-invasively distinguishing low-grade (Grades II and III) glioma (LGG) and high-grade (grade IV) glioma (HGG) on conventional MRI images by using deep convolutional neural networks (CNNs). https://www.selleckchem.com/products/cx-5461.html METHODS All MRI images have been preprocessed first by rigid image registration and intensity inhomogeneity correction. Both proposed methods consist of two steps (1) 3D brain tumor segmentation based on a modification of the popular U-Net model; (2) tumor classification on segmented brain tumor. In the first method, the slice with largest area of tumor is determined and the state-of-the-art mask R-CNN model is employed for tumor grading. To improve the performance of the grading model, a 2D data augmentation has been implemented to increase both the amount and the diversity of the training images.