Effect of Red Pepper (Capsicum frutescens) Powder or Red Pepper Pigment on the Performance and Egg Yolk Color of Laying Hens

Li, Huaqiang,Jin, Liji,Wu, Feifei,Thacker, Philip,Li, Xiaoyu,You, Jiansong,Wang, Xiaoyan,Liu, Sizhao,Li, Shuying,Xu, Yongping Asian Australasian Association of Animal Productio 2012 Animal Bioscience Vol.25 No.11

Two experiments were conducted to study the effects of red pepper (Capsicum frutescens) powder or red pepper pigment on the performance and egg yolk color of laying hens. In Exp. 1, 210, thirty-wk old, Hy-line Brown laying hens were fed one of seven diets containing 0.3, 0.6, 1.2, 2.0, 4.8 or 9.6 ppm red pepper pigment or 0.3 ppm carophyll red. Each diet was fed to three replicate batteries of hens with each battery consisting of a row of five cages of hens with two hens per cage (n = 3). In Exp. 2, 180, thirty-wk old, Hyline Brown laying hens, housed similarly to those in Exp. 1, were fed an unsupplemented basal diet as well as treatments in which the basal diet was supplemented with 0.8% red pepper powder processed in a laboratory blender to an average particle size of $300{\mu}m$, 0.8% red pepper powder processed as a super fine powder with a vibrational mill ($44{\mu}m$) and finally 0.8% red pepper powder processed as a super fine powder with a vibrational mill but mixed with 5% $Na_2CO_3$ either before or after grinding. A diet supplemented with 0.3 ppm carophyll red pigment was also included (n = 3). In both experiments, hens were fed the red pepper powder or pigment for 14 days. After feeding of the powder or pigment was terminated, all hens were fed the basal diet for eight more days to determine if the dietary treatments had any residual effects. In Exp. 1, there were no differences in egg-laying performance, feed consumption or feed conversion ratio due to inclusion of red pepper pigment in the diet. Average egg weight was higher (p<0.05) for birds fed 1.2, 2.4 or 9.6 ppm red pepper pigment than for birds fed the diet containing 0.3 ppm red pepper pigment. On d 14, egg color scores increased linearly as the level of red pepper pigment in the diet increased. In Exp. 2, feeding red pepper powder did not affect egg-laying performance, feed consumption or feed conversion ratio (p>0.05). However, compared with the control group, supplementation with all of the red pepper powder treatments increased egg weight (p<0.05). All the red pepper powder treatments also increased (p<0.05) the yolk color score compared with the control. The results of the present study suggest that both red pepper powder and pigment are effective feed additives for improving egg yolk color for laying hens.

Altered Protein Expression Patterns of Mycobacterium tuberculosis Induced by ATB107

Hongbo Shen,Enzhuo Yang,Feifei Wang,Ruiliang Jin,Shengfeng Xu,Qiang Huang,Honghai Wang 한국미생물학회 2010 The journal of microbiology Vol.48 No.3

ATB107 is a potent inhibitor of indole-3-glycerol phosphate synthase (IGPS). It can effectively inhibit the growth of clinical isolates of drug-resistant Mycobacterium tuberculosis strains as well as M. tuberculosis H37Rv. To investigate the mechanism of ATB107 action in M. tuberculosis, two-dimensional gel electrophoresis coupled with MALDI-TOF-MS analysis (2-DE-MS) was performed to illustrate alterations in the protein expression profile in response to ATB107. Results show that ATB107 affected tryptophan biosynthesis by decreasing the expression of protein encoded by Rv3246c, the transcriptional regulatory protein of MtrA belonging to the MtrA-MtrB two-component regulatory system, in both drug-sensitive and drug-resistant virulent strains. ATB107 might present a stress condition similar to isoniazid (INH) or ethionamide for M. tuberculosis since the altered expression in response to ATB107 of some genes, such as Rv3140, Rv2243, and Rv2428, is consistent with INH or ethionamide treatment. After incubation with ATB107, the expression of 2 proteins encoded by Rv0685 and Rv2624c was down-regulated while that of protein encoded by Rv3140 was up-regulated in all M. tuberculosis strains used in this study. This may be the common response to tryptophan absence; however, relations to ATB107 are unknown and further evaluation is warranted.

Effect of Graphene/TiO2 (001) Interface on Threshold Voltage and Nonlinearity

Yuehua Dai,Shanshan Gong,Zhisheng Zhong,Fengyu Gao,Feifei Wang,Cheng Ding,Jin Yang,Fei Yang 성균관대학교(자연과학캠퍼스) 성균나노과학기술원 2018 NANO Vol.13 No.6

In this work, the threshold voltage (Vth) and nonlinearity (NL) of Graphene (Gra)/TiO2/Gra heterojunction were studied. First, the density functional tight binding (DFTB+) and much more dynamics were used to investigate the IV curves and the resistive switching properties of TiO2 slab and Gra/TiO2/Gra heterojunction. The NL of Gra/TiO2/Gra heterojunction is stronger than that of the TiO2 slab. The Vth of the resistive transition of the heterojunction is larger than that of the TiO2 slab. The tunneling probabilities and the Mulliken atomic population at the Gra/TiO2 interface under different electric fields were calculated by the Cambridge sequential total energy package (CASTEP). Results showed that both the parameters evidently increased under a certain numerical electric field. Finally, the movement of atom in the electric field and the change in the chemical bond were simulated by DFTB+ module. The effect of the Gra/TiO2 interface on Vth and NL was further illustrated. Postponed Vth and improved NL were found at the heterojunction relative to the TiO2 slab due to the presence of the interface barrier. This work provides guidance and reference for design and optimization of TiO2-based selectors.

Study of the Non-Linearity on TiO2(0 0 1) Surface with Oxygen Defects: A First-Principles Study

Yuehua Dai,Xu Zhang,Chengzhi Ma,Zhiyong Pan,Feifei Wang,Wenjuan Lu,Jin Yang,Fei Yang 성균관대학교(자연과학캠퍼스) 성균나노과학기술원 2017 NANO Vol.12 No.8

First-principles plane-wave pseudopotential calculations were performed to study the energetics and electronic structures of oxygen defects on rutile TiO2(0 0 1). The influence of the material thickness on non-linearity (NL) was studied. With the increase in the thickness, the NL became stronger. Calculating the site-projected density of states by applying an external electric field showed that the NL of the bulk is due to the exchange of electrons between O 2p orbitals and Ti 3d orbitals. Finally, the influence of oxygen defects—oxygen vacancies (Vo), oxygen interstitials (Oi), and oxygen vacancies/oxygen interstitial (Vo + Oi) pairs (Frenkel pair defects)—on the NL of TiO2 was studied. These results demonstrate that the band gap (Eg) of TiO2 became gradually narrower as the electric field increased. The Stark effect and defects can lead to the splitting of degenerate energy levels. Stronger electric fields increase the band splitting and reduce Eg. With the increase in the Vo concentration, the decrease in the splitting amplitude and width of the energy level lead to weakening of the transfer of electrons between O and Ti atoms and optimizing the NL of TiO2. Therefore, the incorporation of Vo plays a significant role in improving the NL of TiO2.

Development of a Malignancy Potential Binary Prediction Model Based on Deep Learning for the Mitotic Count of Local Primary Gastrointestinal Stromal Tumors

Yang Jiejin,Chen Zeyang,Liu Weipeng,Wang Xiangpeng,Ma Shuai,Jin Feifei,Wang Xiaoying 대한영상의학회 2021 Korean Journal of Radiology Vol.22 No.3

Objective: The mitotic count of gastrointestinal stromal tumors (GIST) is closely associated with the risk of planting and metastasis. The purpose of this study was to develop a predictive model for the mitotic index of local primary GIST, based on deep learning algorithm. Materials and Methods: Abdominal contrast-enhanced CT images of 148 pathologically confirmed GIST cases were retrospectively collected for the development of a deep learning classification algorithm. The areas of GIST masses on the CT images were retrospectively labelled by an experienced radiologist. The postoperative pathological mitotic count was considered as the gold standard (high mitotic count, > 5/50 high-power fields [HPFs]; low mitotic count, ≤ 5/50 HPFs). A binary classification model was trained on the basis of the VGG16 convolutional neural network, using the CT images with the training set (n = 108), validation set (n = 20), and the test set (n = 20). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated at both, the image level and the patient level. The receiver operating characteristic curves were generated on the basis of the model prediction results and the area under curves (AUCs) were calculated. The risk categories of the tumors were predicted according to the Armed Forces Institute of Pathology criteria. Results: At the image level, the classification prediction results of the mitotic counts in the test cohort were as follows: sensitivity 85.7% (95% confidence interval [CI]: 0.834–0.877), specificity 67.5% (95% CI: 0.636–0.712), PPV 82.1% (95% CI: 0.797–0.843), NPV 73.0% (95% CI: 0.691–0.766), and AUC 0.771 (95% CI: 0.750–0.791). At the patient level, the classification prediction results in the test cohort were as follows: sensitivity 90.0% (95% CI: 0.541–0.995), specificity 70.0% (95% CI: 0.354–0.919), PPV 75.0% (95% CI: 0.428–0.933), NPV 87.5% (95% CI: 0.467–0.993), and AUC 0.800 (95% CI: 0.563–0.943). Conclusion: We developed and preliminarily verified the GIST mitotic count binary prediction model, based on the VGG convolutional neural network. The model displayed a good predictive performance.