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- 저자 : Liu Chengxia (검색결과 4 건)
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Novel Method for Measurement of Fabric Multi-directional Bending Performance
Chengxia Liu 한국섬유공학회 2022 Fibers and polymers Vol.23 No.12
A method that can measure fabric bending performance in different directions simultaneously is proposed. Newparameters, projection area, projection length and falling height are extracted for the bending characterization. 30 fabrics aretested with the new method as well as the conventional cantilever method. Results show that the new parameters have goodcorrelationship with bending length. Bending performance in four directions and two groups of bending indexes in eachdirection can be acquired with only one fabric sample. Compared with the conventional cantilever method widely used, themethod proposed in this paper is more efficient and time-saving.
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Feasibility of a Clinical-Radiomics Model to Predict the Outcomes of Acute Ischemic Stroke
Zhou Yiran,Wu Di,Yan Su,Xie Yan,Zhang Shun,Lv Wenzhi,Qin Yuanyuan,Liu Yufei,Liu Chengxia,Lu Jun,Li Jia,Zhu Hongquan,Liu Weiyin Vivian,Liu Huan,Zhang Guiling,Zhu Wenzhen 대한영상의학회 2022 Korean Journal of Radiology Vol.23 No.8
Objective: To develop a model incorporating radiomic features and clinical factors to accurately predict acute ischemic stroke (AIS) outcomes. Materials and Methods: Data from 522 AIS patients (382 male [73.2%]; mean age ± standard deviation, 58.9 ± 11.5 years) were randomly divided into the training (n = 311) and validation cohorts (n = 211). According to the modified Rankin Scale (mRS) at 6 months after hospital discharge, prognosis was dichotomized into good (mRS ≤ 2) and poor (mRS > 2); 1310 radiomics features were extracted from diffusion-weighted imaging and apparent diffusion coefficient maps. The minimum redundancy maximum relevance algorithm and the least absolute shrinkage and selection operator logistic regression method were implemented to select the features and establish a radiomics model. Univariable and multivariable logistic regression analyses were performed to identify the clinical factors and construct a clinical model. Ultimately, a multivariable logistic regression analysis incorporating independent clinical factors and radiomics score was implemented to establish the final combined prediction model using a backward step-down selection procedure, and a clinical-radiomics nomogram was developed. The models were evaluated using calibration, receiver operating characteristic (ROC), and decision curve analyses. Results: Age, sex, stroke history, diabetes, baseline mRS, baseline National Institutes of Health Stroke Scale score, and radiomics score were independent predictors of AIS outcomes. The area under the ROC curve of the clinical-radiomics model was 0.868 (95% confidence interval, 0.825–0.910) in the training cohort and 0.890 (0.844–0.936) in the validation cohort, which was significantly larger than that of the clinical or radiomics models. The clinical radiomics nomogram was well calibrated (p > 0.05). The decision curve analysis indicated its clinical usefulness. Conclusion: The clinical-radiomics model outperformed individual clinical or radiomics models and achieved satisfactory performance in predicting AIS outcome
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Jian Wang,Qiong Niu,Ning Shi,Chengxia Liu,Haifeng Lian,Jiancheng Li,Kun Li,K. Li 대한독성 유전단백체 학회 2017 Molecular & cellular toxicology Vol.13 No.3
Drug resistance remains to be one of the major challenges in clinical treatment of gastric cancer (GC). Accumulating evidences have highlighted the involvement of long non-coding RNA (lncRNA) in carcinogenesis, chemoresistance, and metastasis. NEAT1, a recently identified lncRNA, was identified as an oncogene to regulate carcinogenesis. This present study aimed to investigate the role of NEAT1 in the drug resistance in GC. Our study found that NEAT1 expression was significantly upregulated in relapsed GC patients and cisplatin (CDDP)-resistant cell lines compared with primary GC patients and parental GC cell lines. NEAT1 upregulation was largely companied with the induction of P-gp. Overexpression of NEAT1 significantly increased the expression of several drug-resistance proteins, thereby compromising the sensitivity of GC cells to CDDP. In contrast, NEAT1 knockdown by RNAi did the opposite. Therefore, lncRNA NEAT1 is an important modulator for drug resistance of GC via promoting the expression of P-gp and other associated proteins.
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Cheng Xia,Rui-Tang Guo,Zhen-rui Zhang,Chen-yuan Fan,Yu-zhe Liu,Yu-cheng Lin,Chu-fan Li,Wei-Guo Pan 한국공업화학회 2023 Journal of Industrial and Engineering Chemistry Vol.128 No.-
Recently, the photocatalytic CO2 reduction technology is an effective solution to remit the energy crisis. Inorder to improve the photocatalytic performance, Z-scheme W18O49/NiAl-LDH composite catalysts wereprepared by hydrothermal method. Fortunately, the prepared catalysts revealed excellent photocatalyticperformance under the simulated sunlight, and CO and CH4 could be detected in the reduction products. WO/LDH-0.5 catalyst possessed the optimal activity, with CO and CH4 yield of 37.09 and 8.01 lmol g-1h1separately, which were 7.9 and 3.6 times that of NiAl-LDH monomer. In addition, W18O49 endowedW18O49/NiAl-LDH catalysts with photothermal effect, which raised the surface temperature andfacilitated the catalytic reaction. Meanwhile, the Z-scheme heterojunction composed of flower-likeNiAl-LDH and urchin-like W18O49 accelerated the separation of photoexcited carriers and enhanced theredox ability. Through a series of characterizations and investigations, this work is promising to breaknew ground for the design of photocatalysts with photothermal effect.
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