http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Yunhui Li,Minhui Zhang,Xiaobo Li,Juan Zhang,Ran Liu,Geyu Liang,Yuepu Pu,Lihong Yin 대한독성 유전단백체 학회 2015 Molecular & cellular toxicology Vol.11 No.2
Caenorhabditis elegans (C. elegans), with homologous genes and conservative spermiogenesis in mammals, has a series of advantages to illuminate and study many biological processes including reproductive toxicity. So it is a very useful model to assess environmental and ecological toxicity. Here we introduce C. elegans as an animal model and three known mammalian sperm teratogens methyl methanesulfonate, mitomycin C and cyclophosphamide as experimental materials to elucidate the efficient and reliability for the assessment of chemicals altering spermiogenesis. The results showed that, with the aid of the brood size, spermatids activation, trans-activation, sperm competition as the endpoints, the adverse effects of three teratogens on C. elegans were detected. Thus, while the data of chemicals induced spermiogenesis abnormality is incomplete, we speculated that C. elegans could be a useful animal model to explore the effects on spermiogenesis of chemicals. And we propose an increased application of C. elegans that complements other model system in the reproductive toxicity.
Min Li,Minhui Huang,Zhiguo Zhang,Qiwei Yang,Yiwen Yang,Zongbi Bao,Qilong Ren 한국화학공학회 2018 Korean Journal of Chemical Engineering Vol.35 No.10
L-arabinose and D-galactose could be released during the hydrolysis process of Arabic gum. The development of a crystallization process of L-arabinose is highly dependent on the knowledge of the solubility of both saccharides. In this work, the solubility of L-arabinose and D-galactose in binary mixtures of methanol-water or ethanolwater (mole fraction of water 0.5816) was determined at temperatures between 278.15 and 333.15K by a static equilibrium method. The experimental data correlated well with the modified Apelblat equation, the simplified polynomial empirical equation, NRTL model and UNIQUAC model. Additionally, the thermodynamic properties including the dissolution enthalpy and entropy were obtained from the experimental data. Within the studied temperature range, the dissolution is endothermic and the dissolution process is non-spontaneous.
Shuguo Qu,Chenchen Zhang,Minhui Li,Yan Zhang,Lunbo Chen,Yushuai Yang,Bo Kang,Yiwei Wang,Jihai Duan,Weiwen Wang 한국화학공학회 2019 Korean Journal of Chemical Engineering Vol.36 No.12
Making inexpensive proton exchange membrane with high proton conductivity for the proton exchange membrane fuel cell (PEMFC) is still a challenging problem. Graphene oxide (GO) nanoparticles grafted with (3-aminopropyl) triethoxy silane (APTES) were prepared and then incorporated into sulfonated poly(ether ether ketone) (SPEEK) matrix by solution casting to make the composite proton exchange membrane. The obtained nanoparticles and composite membranes were characterized by XRD, FT-IR, Raman, TGA, SEM, and UTM. GO treated with the silane coupling agent improved the dispersion stability and compatibility of GO in SPEEK, which decreased the agglomeration of GO nanoparticles in the SPEEK membrane. The prepared nanocomposite membranes exhibited better water retention properties and proton conductivity. The proton conductivity of the SPEEK membrane with 2wt% amine functionalized GO (AGO) reached 11.32mS/cm at 120oC, which was 2.45-times higher than that of the pristine SPEEK membrane. The reason was that AGO nanoparticles disperse uniformly in the SPEEK membranes, which provides new channels for proton transfer. The potential application of this composite membrane in the PEMFC was indicated.
Shicai Chen,Song Shi,Yanghui Xia,Minhui Zhu,Caiyun Zhang,Siwen Xia,Hongliang Zheng 대한이비인후과학회 2015 Clinical and Experimental Otorhinolaryngology Vol.8 No.2
Objectives. To investigate the surgical outcomes of different uvulopalatopharyngoplasty (UPPP). Methods. All subjects underwent overnight polysomnography and were evaluated using the Epworth sleepiness scale (ESS), the Quebec sleep questionnaire and the snoring scale at the baseline and 3 and 12 months following operation. The primary endpoint was the overall effective rate representing the sum of the surgical success rate and effective rate. Results. The overall effective rate at 12 months post surgery was 55.6% for simple UPPP, 95.8% for UPPP+GA, and 92.3% for UPPP+TBA. The surgical success rate at 3 and 12 months postoperation for UPPP+GA or UPPP+TBA was significantly higher than simple UPPP (P<0.05). Marked improvement was observed in all patients in the snoring scale score and the ESS score 3 and 12 months following surgery compared to the baseline (P<0.05 in all). Conclusion. UPPP, UPPP+GA, and UPPP+TBA are all effective in improving the surgical outcome of obstructive sleep apnea hypopnea syndrome (OSAHS) patients with multilevel obstruction. UPPP+TBA appears to be the most effective in treating OSAHS patients.
Lu Yi,Wu Jiachuan,Hu Minhui,Zhong Qinghua,Er Limian,Shi Huihui,Cheng Weihui,Chen Ke,Liu Yuan,Qiu Bingfeng,Xu Qiancheng,Lai Guangshun,Wang Yufeng,Luo Yuxuan,Mu Jinbao,Zhang Wenjie,Zhi Min,Sun Jiachen 거트앤리버 소화기연관학회협의회 2023 Gut and Liver Vol.17 No.6
Background/Aims: The accuracy of endosonographers in diagnosing gastric subepithelial lesions (SELs) using endoscopic ultrasonography (EUS) is influenced by experience and subjectivity. Artificial intelligence (AI) has achieved remarkable development in this field. This study aimed to develop an AI-based EUS diagnostic model for the diagnosis of SELs, and evaluated its efficacy with external validation. Methods: We developed the EUS-AI model with ResNeSt50 using EUS images from two hospitals to predict the histopathology of the gastric SELs originating from muscularis propria. The diagnostic performance of the model was also validated using EUS images obtained from four other hospitals. Results: A total of 2,057 images from 367 patients (375 SELs) were chosen to build the models, and 914 images from 106 patients (108 SELs) were chosen for external validation. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the model for differentiating gastrointestinal stromal tumors (GISTs) and non-GISTs in the external validation sets by images were 82.01%, 68.22%, 86.77%, 59.86%, and 78.12%, respectively. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy in the external validation set by tumors were 83.75%, 71.43%, 89.33%, 60.61%, and 80.56%, respectively. The EUS-AI model showed better performance (especially specificity) than some endosonographers. The model helped improve the sensitivity, specificity, and accuracy of certain endosonographers. Conclusions: We developed an EUS-AI model to classify gastric SELs originating from muscularis propria into GISTs and non-GISTs with good accuracy. The model may help improve the diagnostic performance of endosonographers. Further work is required to develop a multi-modal EUS-AI system.