Rossencormier7015

New prognostic factors and targeted therapies are urgently needed to improve therapeutic outcomes in vulvar cancer patients and to reduce therapy related morbidity. Previous studies demonstrated the important role of prostaglandin receptors in inflammation and carcinogenesis in a variety of tumor entities. In this study, we aimed to investigate the expression of EP4 in vulvar cancer tissue and its association with clinicopathological data and its prognostic relevance on survival. Immunohistochemistry was performed on tumor specimens of 157 patients with vulvar cancer treated in the Department of Obstetrics and Gynecology, Ludwig-Maximilian-University of Munich, Germany, between 1990 and 2008. The expression of EP4 was analyzed using the well-established semiquantitative immunoreactivity score (IRS) and EP4 expression levels were correlated with clinicopathological data and patients' survival. To specify the tumor-associated immune cells, immunofluorescence double staining was performed on tissue samples. In vd possible target for endocrinological therapy, more research is needed on the influence of EP4 in the tumor environment and its impact in vulvar carcinoma.Graphene oxide-silver nanoparticle (GO-AgNPs) nanocomposites have drawn much attention for their potential in biomedical uses. However, the potential toxicity of GO-AgNPs in animals and humans remains unknown, particularly in the developing fetus. Here, we reported the GO-AgNP-mediated cytotoxicity and epigenetic alteration status in caprine fetal fibroblast cells (CFFCs). In brief, the proliferation and apoptosis rate of GO-AgNP-treated CFFCs (4 and 8 µg/mL of GO-AgNPs) were measured using the cell-counting kit (CCK-8) assay and the annexin V/propidium iodide (PI) assay, respectively. In addition, the oxidative stress induced by GO-AgNPs and detailed mechanisms were studied by evaluating the generation of reactive oxygen species (ROS), superoxide dismutase (SOD), lactate dehydrogenase (LDH), malondialdehyde (MDA), and caspase-3 and abnormal methylation. The expression of pro- and anti-apoptotic genes and DNA methyltransferases was measured using reverse transcription followed by RT-qPCR. Our data indicated that GO-AgNPs cause cytotoxicity in a dose-dependent manner. GO-AgNPs induced significant cytotoxicity by the loss of cell viability, production of ROS, increasing leakage of LDH and level of MDA, increasing expression of pro-apoptotic genes, and decreasing expression of anti-apoptotic genes. GO-AgNPs incited DNA hypomethylation and the decreased expression of DNMT3A. Taken together, this study showed that GO-AgNPs increase the generation of ROS and cause apoptosis and DNA hypomethylation in CFFCs. Therefore, the potential applications of GO-AgNPs in biomedicine should be re-evaluated.The fight against the spread of antibiotic resistance is one of the most important challenges facing health systems worldwide. Given the limitations of current diagnostic methods, the development of fast and accurate tests for the diagnosis of viral and bacterial infections would improve patient management and treatment, as well as contribute to reducing antibiotic misuse in clinical settings. In this scenario, analysis of host transcriptomics constitutes a promising target to develop new diagnostic tests based on the host-specific response to infections. We carried out a multi-cohort meta-analysis of blood transcriptomic data available in public databases, including 11 different studies and 1209 samples from virus- (n = 695) and bacteria- (n = 514) infected patients. We applied a Parallel Regularized Regression Model Search (PReMS) on a set of previously reported genes that distinguished viral from bacterial infection to find a minimum gene expression bio-signature. This strategy allowed us to detect three genes, namely BAFT, ISG15 and DNMT1, that clearly differentiate groups of infection with high accuracy (training set area under the curve (AUC) 0.86 (sensitivity 0.81; specificity 0.87); testing set AUC 0.87 (sensitivity 0.82; specificity 0.86)). BAFT and ISG15 are involved in processes related to immune response, while DNMT1 is related to the preservation of methylation patterns, and its expression is modulated by pathogen infections. We successfully tested this three-transcript signature in the 11 independent studies, demonstrating its high performance under different scenarios. The main advantage of this three-gene signature is the low number of genes needed to differentiate both groups of patient categories.Duchenne muscular dystrophy (DMD), caused by mutations in the dystrophin gene, is an inherited neuromuscular disorder that causes loss of muscle mass and motor skills. In the era of genomic medicine, there is still no known cure for DMD. In clinical practice, there is a growing awareness of the possible importance of nutrition in neuromuscular diseases. This is mostly the result of patients' or caregivers' empirical reports of how active substances derived from food have led to improved muscle strength and, thus, better quality of life. In this report, we investigate several nutraceutical principles in the sapje strain of zebrafish, a validated model of DMD, in order to identify possible natural products that, if supplemented in the diet, might improve the quality of life of DMD patients. DNA Damage inhibitor Gingerol, a constituent of fresh ginger, statistically increased the locomotion of mutant larvae and upregulated the expression of heme oxygenase 1, a target gene for therapy aimed at improving dystrophic symptoms. Although three other compounds showed a partial positive effect on locomotor and muscle structure phenotypes, our nutraceutical screening study lent preliminary support to the efficacy and safety only of gingerol. Gingerol could easily be proposed as a dietary supplement in DMD.Instead of a flag valid/non-valid usually proposed in the quality control (QC) processes of air quality (AQ), we proposed a method that predicts the p-value of each observation as a value between 0 and 1. We based our error predictions on three approaches the one proposed by the Working Group on Guidance for the Demonstration of Equivalence (European Commission (2010)), the one proposed by Wager (Journal of MachineLearningResearch, 15, 1625-1651 (2014)) and the one proposed by Lu (Journal of MachineLearningResearch, 22, 1-41 (2021)). Total Error framework enables to differentiate the different errors input, output, structural modeling and remnant. We thus theoretically described a one-site AQ prediction based on a multi-site network using Random Forest for regression in a Total Error framework. We demonstrated the methodology with a dataset of hourly nitrogen dioxide measured by a network of monitoring stations located in Oslo, Norway and implemented the error predictions for the three approaches. The results indicate that a simple one-site AQ prediction based on a multi-site network using Random Forest for regression provides moderate metrics for fixed stations.