monocytogenes, as a foodborne pathogen, during storage; therefore, it is a good choice to be applied in the meat industry.Staphylococcus aureus is among the most common zoonotic pathogens originating from animals consumed as food, especially raw chicken meat (RCM). As far as we know, this might be the first report that explores the efficacy of metal oxide nanoparticles (MONPs), such as zinc peroxide nanoparticles (ZnO2-NPs), zinc oxide nanoparticles (ZnO-NPs), and titanium dioxide nanoparticles (TiO2-NPs) against multidrug resistant (MDR) and/or pandrug resistant (PDR) S. aureus strains with a strong biofilm-producing ability isolated from RCM and giblets. The overall prevalence of coagulase-positive staphylococci was 21%, with a contamination level range between 102 and 104 CFU/g. The incidence of virulence genes See (21/36), pvl (16/36), clfA (15/36), sec (12/36), tst (12/36), and sea (11/36) among S. aureus strains were relatively higher those of seb, sed, fnbA, and fnbB. For antimicrobial resistance gene distribution, most strains harbored the blaZ gene (25/36), aacA-aphD gene (24/36), mecA gene (22/36), vanA gene (20/36), ail RCM and giblets.Currants are prone to contamination by ochratoxin during cultivation, processing and storage conditions. Saccharomyces cerevisiae is considered to be among the main species of grape yeast flora able to control antagonistic fungi. In this study, the potential of S. cerevisiae Y33 was investigated to inhibit the growth of several fungal species indigenous to the microbiota of grapes. Moreover, the efficacy of this yeast species was investigated to inhibit OTA by toxin producing fungi both in vitro and in situ. For this purpose thirty-five different fungal species, belonging to the genera Aspergillus, Penicillium, Cladosporium, Fusarium and Alternaria interacted in vitro with S. cerevisiae on Malt Extract agar plates, stored at 25 °C for 14 days. Results showed that the highest OTA producer A. carbonarius F71 was inhibited more than 99% from day 7, in contrast to A. niger strains that presented enhanced OTA production at day 14 due to interaction with S. cerevisiae Y33. Additionally, the antifungal potential of the selected yeast was also studied in situ on currants subjected to different treatments and stored at 25 °C for 28 days. Microbiological analysis was undertaken for the enumeration of the bacterial and fungal flora, together with OTA determination at 7 and 21 days. To quantify A. carbonarius on all treated currant samples, molecular analysis with Real Time PCR was employed. A standard curve was prepared with A. carbonarius DNA. The efficiency of the curve was estimated to 10.416, the slope to -3.312 and the range of haploid genome that could be estimated was from 1.05 to 105∙105. The amount of A. carbonarius DNA in all treated currants samples, where the fungus was positively detected, ranged from as low as 0.08 to 562 ng DNA/g currants. The antifungal activity of S. cerevisiae Y33 was observed in all studied cases, causing inhibition of fungal growth and OTA production. Infectious morbidity is the most common and costly among all surgery-related complications, and infections by multidrug-resistant microorganisms (MDR) are associated with poor outcomes. Derangements of body composition is a recognized risk factor for infections. The aim of this study was to investigate the potential association between specific traits of body composition and the risk of having MDR-related infections. This was a prospective study with patients scheduled for major abdominal surgery for gastrointestinal cancer. Bioimpedance vector analysis (BIVA), a reliable tool for body composition assessment, was performed the day before the operation. Postoperative complications were collected focusing on resistance patterns and site of infection. Patterns of resistance were compared with BIVA parameters. Data from 182 patients suffering from pancreatic (n=76, 41.7%), rectal (n=38, 20.9%), gastric (n=31, 17%), or hepatic (n=37, 20.3%) malignancy were collected. Overall complications occurred in 108 patients (59%), and in 45 patients (28%) bacterial infections were proven at culture. https://www.selleckchem.com/products/gpr84-antagonist-8.html Of these, 15 (8%) were multidrug-sensitive (MDS), 38 MDR, and 2 extended drug-resistant (XDR) infections. The standardized phase angle measured (SPA) at BIVA was significantly lower in the MDR/XDR infections (-0.02 ± 1.20) than for no infection/MDS (0.56 ± 1.53; P=0.029). A multivariate analysis showed that SPA was the only independent variable for MDR/XDR infections with an odds ratio of 3.057 (95% confidence interval, 1.354-6903; P=0.007). The predictive ability of SPA revealed an area under the receiver operating characteristic curve of 0.662, with an optimal threshold of -0.3. In surgical cancer patients, preoperative value of SPA lower than -0.3 is associated with the outbreak of MDR bacterial infections. In surgical cancer patients, preoperative value of SPA lower than -0.3 is associated with the outbreak of MDR bacterial infections. Preterm infants are at increased risk of developing extrauterine growth restriction, which is associated with worse health outcomes. The energy needs are not well known, as the measurement of resting energy expenditure (REE) using indirect calorimetry has critical issues when applied to infants. One of the main issues is the time required to obtain reliable data owing to the difficulty in keeping infants quiet during the entire examination. Thus, the aim of this study was to define the minimum duration of calorimetry to obtain reliable data. The volume of oxygen consumption (VO ) and the volume of carbon dioxide production (VCO ) were recorded for a mean duration of 90 consecutive minutes. REE was calculated using a neonatal prototype calculator. We extracted data regarding VO , VCO , and REE at 10(T1), 20(T2), 30(T3), 40(T4), and 50(T5) minutes of steady state and compared these data to those of entire steady state period. Twenty-six very low birth weight preterm infants were evaluated at 36.58 ± 0 in stable, very low birth weight infants.We derive the fast convergence rates of a deep neural network (DNN) classifier with the rectified linear unit (ReLU) activation function learned using the hinge loss. We consider three cases for a true model (1) a smooth decision boundary, (2) smooth conditional class probability, and (3) the margin condition (i.e., the probability of inputs near the decision boundary is small). We show that the DNN classifier learned using the hinge loss achieves fast rate convergences for all three cases provided that the architecture (i.e., the number of layers, number of nodes and sparsity) is carefully selected. An important implication is that DNN architectures are very flexible for use in various cases without much modification. In addition, we consider a DNN classifier learned by minimizing the cross-entropy, and show that the DNN classifier achieves a fast convergence rate under the conditions that the noise exponent and margin exponent are large. Even though they are strong, we explain that these two conditions are not too absurd for image classification problems.