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您的检索式：作者名="LONGCHAO QIN"
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| 1 | Bioinspired tungsten-copper composites with Bouligand-type architectures mimicking fish scales显示文摘The microscopic Bouligand-type architectures of fish scales demonstrate a notable efficiency in enhancing the damage tolerance of materials;nevertheless,it is challenging to reproduce in metals.Here bioinspired tungsten-copper composites with different Bouligand-type architectures mimicking fish scales were fabricated by infiltrating a copper melt into woven contextures of tungsten fibers.These composites exhibit a synergetic enhancement in both strength and ductility at room temperature along with an improved resistance to high-temperature oxidization.The strengths were interpreted by adapting the classical laminate theory to incorporate the characteristics of Bouligand-type architectures.In particular,under load the tungsten fibers can reorient adaptively within the copper matrix by their straightening,stretching,interfacial sliding with the matrix,and the cooperative kinking deformation of fiber grids,representing a successful implementation of the optimizing mechanisms of the Bouligand-type architectures to enhance strength and toughness.This study may serve to promote the development of new high-performance tungsten-copper composites for applications,e.g.,as electrical contacts or heat sinks,and offer a viable approach for constructing bioinspired architectures in metallic materials. | Yuan Zhang Guoqi Tan Mingyang Zhang Qin Yu Zengqian Liu Yanyan Liu Jian Zhang Da Jiao Faheng Wang Longchao Zhuo Zhefeng Zhang Robert O.Ritchie | 2022 | Journal of Materials Science & Technology2022，，1： | 3 |
| 2 | Novel defined N7-methylguanosine modification-related lncRNAs for predicting the prognosis of laryngeal squamous cell carcinoma显示文摘Objective:Through integrated bioinformatics analysis,the goal of this work was to find new,characterised N7-methylguanosine modification-related long non-coding RNAs(m7G-lncRNAs)that might be used to predict the prognosis of laryngeal squamous cell carcinoma(LSCC).Methods:The clinical data and LSCC gene expression data for the current investigation were initially retrieved from the TCGA database&sanitised.Then,using co-expression analysis of m7G-associated mRNAs&lncRNAs&differential expression analysis(DEA)among LSCC&normal sample categories,we discovered lncRNAs that were connected to m7G.The prognosis prediction model was built for the training category using univariate&multivariate COX regression&LASSO regression analyses,&the model’s efficacy was checked against the test category data.In addition,we conducted DEA of prognostic m7G-lncRNAs among LSCC&normal sample categories&compiled a list of co-expression networks&the structure of prognosis m7G-lncRNAs.To compare the prognoses for individuals with LSCC in the high-&low-risk categories in the prognosis prediction model,survival and risk assessments were also carried out.Finally,we created a nomogram to accurately forecast the outcomes of LSCC patients&created receiver operating characteristic(ROC)curves to assess the prognosis prediction model’s predictive capability.Results:Using co-expression network analysis&differential expression analysis,we discovered 774 m7G-lncRNAs and 551 DEm7G-lncRNAs,respectively.We then constructed a prognosis prediction model for six m7G-lncRNAs(FLG−AS1,RHOA−IT1,AC020913.3,AC027307.2,AC010973.2 and AC010789.1),identified 32 DEPm7G-lncRNAs,analyzed the correlation between 32 DEPm7G-lncRNAs and 13 DEPm7G-mRNAs,and performed survival analyses and risk analyses of the prognosis prediction model to assess the prognostic performance of LSCC patients.By displaying ROC curves and a nomogram,we finally checked the prognosis prediction model's accuracy.Conclusion:By creating novel predictive lncRNA signatures for clinical diagnosis&therapy,our findings will contribute to understanding the pathogenetic process of LSCC. | ZHAOXU YAO HAIBIN MA LIN LIU QIAN ZHAO LONGCHAO QIN XUEYAN REN CHUANJUN WU KAILI SUN | 2023 | BIOCELL2023，47，9： | 0 |
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