Regulation of the cecal microbiota community and the fatty liver deposition by the addition of brewers' spent grain to feed of Landes geese.

The effects of brewers' spent grain (BSG) diets on the fatty liver deposition and the cecal microbial community were investigated in a total of 320 healthy 5-day-old Landes geese. These geese were randomly and evenly divided into 4 groups each containing 8 replicates and 10 geese per replicate. These four groups of geese were fed from the rearing stage (days 5-60) to the overfeeding stage (days 61-90). The Landes geese in group C (control) were fed with basal diet (days 5-90); group B fed first with basal diet in the rearing stage and then basal diet + 4% BSG in the overfeeding stage; group F first with basal diet + 4% BSG during the rearing stage and then basal diet in the overfeeding stage; and group W with basal diet + 4% BSG (days 5-90). The results showed that during the rearing stage, the body weight (BW) and the average daily gain (ADG) of Landes geese were significantly increased in groups F and W, while during the overfeeding stage, the liver weights of groups W and B were significantly higher than that of group C. The taxonomic structure of the intestinal microbiota revealed that during the overfeeding period, the relative abundance of Bacteroides in group W was increased compared to group C, while the relative abundances of Escherichia-Shigella and prevotellaceae_Ga6A1_group were decreased. Results of the transcriptomics analysis showed that addition of BSG to Landes geese diets altered the expression of genes involved in PI3K-Akt signaling pathway and sphingolipid metabolism in the liver. Our study provided novel experimental evidence based on the cecal microbiota to support the application of BSG in the regulation of fatty liver deposition by modulating the gut microbiota in Landes geese.

Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Cancer Using CNN Based on Multiparametric MRI.

BACKGROUND: Multiparametric magnetic resonance imaging (MRI) is widely used in breast cancer screening. Accurate prediction of the axillary lymph nodes metastasis (ALNM) is essential for breast cancer surgery and treatment. However, there is no mature and effective discerning method for ALNM based on multiparametric MRI. PURPOSE: To evaluate the ALNM using T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and diffusion-weighted imaging (DWI) sequences, respectively, and construct a quantitative ALNM discerning model of integrated multiparametric MRI. STUDY TYPE: Retrospective. POPULATION: Three-hundred forty-eight breast cancer patients, 163 with ALNM (99.39% females), and 185 without ALNM (100% females). The dataset was randomly divided into the training set (315 cases) and the testing set (33 cases). FIELD STRENGTH/SEQUENCE: 1.5 T; T1WI (VIBRANT), T2WI (FSE), and DWI (echo planar imaging [EPI]). ASSESSMENT: The lesion region of interest images were cropped and sent to a pretrained ResNet50 network. Then, the results of different sequences were sent to a classifier for ensemble learning to construct the ALNM model of multiparametric MRI. STATISTICAL TESTS: Performance indicators such as accuracy, the receiver operating characteristic (ROC) curve, and the area under the ROC curve (AUC) were calculated. Student's t-test, chi-square test, Fisher's exact test, and Delong test were performed, and P < 0.05 was considered statistically significant. RESULTS: T2WI performed the best among the three sequences, and achieved the accuracy and AUC of 0.933/0.989 in the testing set. Compared to T1WI with the accuracy and AUC of 0.691/0.806, the increase is significant. While compared to DWI with the accuracy and AUC of 0.800/0.910, the improvement is not significant (P = 0.126). After integrating three sequences, the accuracy and AUC improved to 0.970 and 0.996. DATA CONCLUSION: T2WI performed better than DWI and T1WI in discerning ALNM in this breast cancer dataset. The proposed quantitative model of integrated multiparametric MRI could effectively help the ALNM diagnosis. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 2.

Improving the Performance of ZnS Photocatalyst in Degrading Organic Pollutants by Constructing Composites with Ag2O.

ZnS is a promising photocatalyst in water purification, whereas its low photon efficiency and poor visible-light response restrict its application. Constructing composites may help solve these problems. In this work, Ag2O was introduced to ZnS for the first time based on their energy band characteristics to form a novel ZnS/Ag2O composite photocatalyst. In the model reaction of degrading methylene blue, the as-designed catalyst exhibited high catalytic activity among a series of ZnS-based composite photocatalysts under similar conditions. The catalytic rate constant was up to 0.138 min-1, which is 27.4- and 15.6-times higher than those of ZnS and Ag2O. This composite degraded 92.4% methylene blue in 50 min, while the ratios were 31.9% and 68.8% for ZnS and Ag2O. Catalytic mechanism study based on photoluminescence and radical-scavenging experiments revealed that the enhanced photocatalytic activity was attributed to the composite structure of ZnS/Ag2O. The structure not only facilitated the separation and transmission of photogenerated carriers but also extended the light response range of the catalyst. The as-designed ZnS/Ag2O composite is promising in degrading organic pollutants in water.