Carstensjarvis9730

Prevalence of nonalcoholic fatty liver disease (NAFLD) in children is rising with the epidemic of childhood obesity. Our objective was to perform digital image analysis (DIA) of ultrasound (US) images of the liver to develop a machine learning (ML) based classification model capable of differentiating NAFLD from healthy liver tissue and compare its performance with pixel intensity-based indices.

De-identified hepatic US images obtained as part of a cross-sectional study examining pediatric NAFLD prevalence were used to build an image database. Texture features were extracted from a representative region of interest (ROI) selected from US images of subjects with normal liver and subjects with confirmed NAFLD using ImageJ and MAZDA image analysis software. Multiple ML classification algorithms were evaluated.

Four-hundred eighty-four ROIs from images in 93 normal subjects and 260 ROIs from images in 39 subjects with NAFLD with 28 texture features extracted from each ROI were used to develop, train, and internally validate the model. An ensembled ML model comprising Support Vector Machine, Neural Net, and Extreme Gradient Boost algorithms was accurate in differentiating NAFLD from normal when tested in an external validation cohort of 211 ROIs from images in 42 children. The texture-based ML model was also superior in predictive accuracy to ML models developed using the intensity-based indices (hepatic-renal index and the hepatic echo-intensity attenuation index).

ML-based predictive models can accurately classify NAFLD US images from normal liver images with high accuracy using texture analysis features.

ML-based predictive models can accurately classify NAFLD US images from normal liver images with high accuracy using texture analysis features.This study compared longissimus lumborum (LL) and semitendinosus (ST) muscles, in 48 lamb carcasses, to determine their pH decline parameters and achievement of ideal pH criteria (hitting the window). These include the pH at temperature 18 °C (pH@18) and temperature at pH 6 (temp@pH6). No practical difference were found between muscles for pH@18 or the temp@pH6, although there were differences between the experimental carcasses evaluated. Indeed, for all but three carcasses, there were insignificant differences between the LL and ST in terms of their pH@18. This outcome suggests that the lower value and more accessible ST muscle can be measured to determine lamb carcass pH decline parameters, instead of the LL. Because of the scale of this study, additional investigation is advised prior to any adoption.This paper studies the effects of soy protein isolate (SPI; 0, 2% and 4%; Weight/Weight) on texture, rheological property, sulfhydryl groups, and the water distribution state of low-salt (1% NaCl) pork myofibrillar protein systems under high pressure processing (HPP, 200 MPa, 10 min). The L⁎ value, cooking yield, hardness, total and reactive sulfhydryl, surface hydrophobicity, and the G' value at 80 °C of pork myofibrillar protein increased significantly (P less then 0.05) when SPI was added; however, the springiness, cohesiveness, and chewiness of gels with 4% SPI were lower than of gels with 2% SPI. The rheological findings indicated that the thermal stability of the myofibrillar protein increased when SPI was added. The initial relaxation time of T2b, T21, and T22 decreased when SPI increased; meanwhile, the peak ratio of P21 increased significantly (P less then 0.05), implying that water had lower mobility. Overall, the 2% SPI could enhance gel characteristics and water-holding capacity of pork myofibrillar protein under 200 MPa.The fibrous structure of meat muscle makes it an anisotropic optical material. As such, spectral information varies with the orientation of the muscle. In this study, spectral data from pork cuts were obtained by a transverse scan (TRANSCAN), radial scan (RADISCAN), and longitudinal scan (LONGSCAN) by using hyperspectral imaging. The information was used to develop and compare the prediction models for intramuscular (IMF) content prediction by partial least square regression (PLSR), support vector machines regression (SVMR), and backpropagation artificial neural network (BPANN). The three modeling algorithms showed equal capability for modeling IMF in pork. The accuracy of the prediction models from the three scans was in the order of TRANSCAN ≥ RADISCAN ≥ LONGSCAN. Successive projection algorithm reduced the wavelengths to 93%. The reduced wavelengths were used to build new models that showed similar accuracy to the models of the original wavelengths. This study shows that muscle orientation influences the accuracy of the prediction models.Electrodeposited Ni-W alloy assisted by high-intensity ultrasound was evaluated considering the nominal power effect on the anticorrosive property. IRAK-1-4 Inhibitor I in vivo Temperature profiles demonstrated that using a nominal power of 400 W, the electrolytic bath at 30 °C reached values of 39 ± 1 °C. The maximum acoustic power corresponded to 6.7% of the nominal power value at 400 W. Increasing the nominal power from 0 to 400 W; the Ni content decreased from 85.3 to 75.2 wt%, and the W content increased from 15.1 to 25.1 wt%. The deposited coating at 200 W and 300 W had a smooth, homogeneous, and uniform surface. At 400 W, the acoustic cavitation promoted erosion, affecting the coating surface. X-ray diffraction analysis indicated that the nominal power of 200 W promoted electrodeposition of the Ni17W3 structure with the plane (111) as a preferred orientation. The crystallite size decreased for the planes (111) and (200) when increased nominal power from 100 to 200 W. The optimum condition for the improved corrosion resistance occurred with the nominal power of 200 W, providing a polarization resistance of 23.42 kΩ cm2.As a well known endocrine-disrupting and model chemical, bisphenol A (BPA) may pose a serious threat to human health, since it and its disinfection by-products (DBPs) have been detected in drinking water, urine, human colostrum, adipose tissue, and placenta samples. Although chlorinated BPAs (Cl-BPAs) and iodinated BPAs (I-BPAs) have been well studied, brominated BPAs (Br-BPAs), and mixed halogenated DBPs like bromo-iodo-BPAs (Br-I-BPAs), and bromo-chloro-iodo-BPAs (Cl-Br-I-BPAs) are less well understood. Notably, the role of iodide (I-) during chlorination is not well understood, since the studies of the I-DBPs mainly focus on their genotoxicity and cytotoxicity. To understand the formation mechanisms of halogenated bisphenol A (HBPs) during chlorination with bromide (Br-) and/or I-, and the role of I- during chlorination, three set of reactions were performed in the laboratory ("BPA + chlorine + Br-", "BPA + chlorine + I-" and "BPA + chlorine + Br- +I-" assigned as group A, B and C respectively). Thirty HBPs were identified and 18 of them were never reported before.