Metal-organic frameworks recently have been burgeoning and used as precursors to obtain various metal-nitrogen-carbon catalysts for oxygen reduction reaction(ORR).Although rarely studied,Mn-N-C is a promising catalyst...Metal-organic frameworks recently have been burgeoning and used as precursors to obtain various metal-nitrogen-carbon catalysts for oxygen reduction reaction(ORR).Although rarely studied,Mn-N-C is a promising catalyst for ORR due to its weak Fenton reaction activity and strong graphitization catalysis.Here,we developed a facile strategy for anchoring the atomically dispersed nitrogen-coordinated single Mn sites on carbon nanosheets(MnNCS)from an Mn-hexamine coordination framework.The atomically dispersed Mn-N_(4) sites were dispersed on ultrathin carbon nanosheets with a hierarchically porous structure.The optimized MnNCS displayed an excellent ORR performance in half-cells(0.89 V vs.reversible hydrogen electrode(RHE)in base and 0.76 V vs.RHE in acid in half-wave potential)and Zn-air batteries(233 mW cm^(−2)in peak power density),along with significantly enhanced stability.Density functional theory calculations further corroborated that the Mn-N_(4)-C(12)site has favorable adsorption of*OH as the rate-determining step.These findings demonstrate that the metal-hexamine coordination framework can be used as a model system for the rational design of highly active atomic metal catalysts for energy applications.展开更多
目的:建立和验证一个涉及多级临床场景的白内障协作通用的人工智能(artificial intelligence,AI)管理平台,探索基于AI的医疗转诊模式,以提高协作效率和资源覆盖率。方法:训练和验证的数据集来自中国AI医学联盟,涵盖多级医疗机构和采集...目的:建立和验证一个涉及多级临床场景的白内障协作通用的人工智能(artificial intelligence,AI)管理平台,探索基于AI的医疗转诊模式,以提高协作效率和资源覆盖率。方法:训练和验证的数据集来自中国AI医学联盟,涵盖多级医疗机构和采集模式。使用三步策略对数据集进行标记:1)识别采集模式;2)白内障诊断包括正常晶体眼、白内障眼或白内障术后眼;3)从病因和严重程度检测需转诊的白内障患者。此外,将白内障AI系统与真实世界中的居家自我监测、初级医疗保健机构和专科医院等多级转诊模式相结合。结果:通用AI平台和多级协作模式在三步任务中表现出可靠的诊断性能:1)识别采集模式的受试者操作特征(receiver operating characteristic curve,ROC)曲线下面积(area under the curve,AUC)为99.28%~99.71%);2)白内障诊断对正常晶体眼、白内障或术后眼,在散瞳-裂隙灯模式下的AUC分别为99.82%、99.96%和99.93%,其他采集模式的AUC均>99%;3)需转诊白内障的检测(在所有测试中AUC>91%)。在真实世界的三级转诊模式中,该系统建议30.3%的人转诊,与传统模式相比,眼科医生与人群服务比率大幅提高了10.2倍。结论:通用AI平台和多级协作模式显示了准确的白内障诊断性能和有效的白内障转诊服务。建议AI的医疗转诊模式扩展应用到其他常见疾病和资源密集型情景当中。展开更多
目的通过Meta分析综合评价γ突触核蛋白(SNCG)表达与胃癌患者临床病理特征的相关性。方法计算机检索PubMed、EmBase、Web of science、Cochrane Library、中国知网(CNKI)、维普中文科技期刊全文数据库(VIP)、万方和中国生物医学文献数据...目的通过Meta分析综合评价γ突触核蛋白(SNCG)表达与胃癌患者临床病理特征的相关性。方法计算机检索PubMed、EmBase、Web of science、Cochrane Library、中国知网(CNKI)、维普中文科技期刊全文数据库(VIP)、万方和中国生物医学文献数据库(CBM)等,检索时间均为建库至2019年1月1日。通过设置的纳入与排出标准筛选研究文献并提取资料,根据纽卡斯尔-渥太华量表(NOS)评价纳入资料的质量,采用Review Manager 5.3软件进行系统分析。结果符合条件的5篇文献中有4篇文献分析了SNCG在胃癌组和正常胃黏膜组中的表达(580个样本),胃癌组中SNCG的表达显著高于正常胃黏膜组(OR=18.47,95%CI:4.20~81.12,P=0.0001);在SNCG表达与胃癌浸润深度的相关分析中共纳入4篇文献,合计样本量为465例,SNCG在浅层浸润组和深层浸润表达有统计学意义(OR=0.25,95%CI为0.16~0.40,P<0.00001);在SNCG表达与淋巴结转移的Meta分析中共纳入5篇文献(485个样本),SNCG在胃癌患者有淋巴结转移组和无淋巴结转移组表达差异有统计学差异(OR=0.19,95%CI为0.07~0.51,P=0.0009);在SNCG表达与临床分期的Meta分析中共纳入2篇文献,样本量合计150例,SNCG在临床为Ⅰ~Ⅱ期和Ⅲ~Ⅳ期表达差异有统计学差异(OR=0.03,95%CI为0.01~0.08,P<0.00001);但SNCG表达与胃癌年龄、分化程度无相关性。结论SNCG可以作为胃癌临床诊断和评价生物学特性的重要参考指标,这将为胃癌的早期诊断、预后分析及靶向治疗提供重要的参考价值。展开更多
Rational design and facile preparation of low-cost and efficient catalysts for the selective converting of biomass-derived monosaccharides into high value-added chemicals is highly demanded,yet challenging.Herein,we f...Rational design and facile preparation of low-cost and efficient catalysts for the selective converting of biomass-derived monosaccharides into high value-added chemicals is highly demanded,yet challenging.Herein,we first demonstrate a N doped defect-rich carbon(NC-800-5)as metal-free catalyst for the selective oxidation of D-xylose into D-xylonic acid in alkaline aqueous solution at 100℃ for 30 min,with 57.4%yield.The doped graphitic N is found to be the active site and hydroxyl ion participating in the oxidation of D-xylose.Hydroxyl ion and D-xylose first adsorb on NC-800-5 surface,and the aldehyde group of D-xylose is catalyzed to form germinal diols ion.Then,C–H bond break to yield carboxylic group.Furthermore,NC-800-5 catalyst shows high stability in recycled test.展开更多
基金Basic and Applied Basic Research Foundation of Guangdong Province,Grant/Award Numbers:2021A1515110245,2022A1515140108,2023B1515040013National Youth Top-notch Talent Support Program,Grant/Award Number:x2qsA4210090+5 种基金Guangzhou Key Research and Development Program,Grant/Award Number:SL2022B03J01256Guangdong Provincial Key Laboratory of Distributed Energy Systems,Grant/Award Number:2020B1212060075Engineering Research Center of None-food Biomass Efficient Pyrolysis and Utilization Technology of Guangdong Higher Education Institutes,Grant/Award Number:2016GCZX009State Key Laboratory of Pulp and Paper Engineering,Grant/Award Numbers:202215,2022PY02Key projects of social science and technology development in Dongguan,Grant/Award Number:20231800936352National Natural Science Foundation of China,Grant/Award Numbers:21736003,21905044,31971614,32071714。
文摘Metal-organic frameworks recently have been burgeoning and used as precursors to obtain various metal-nitrogen-carbon catalysts for oxygen reduction reaction(ORR).Although rarely studied,Mn-N-C is a promising catalyst for ORR due to its weak Fenton reaction activity and strong graphitization catalysis.Here,we developed a facile strategy for anchoring the atomically dispersed nitrogen-coordinated single Mn sites on carbon nanosheets(MnNCS)from an Mn-hexamine coordination framework.The atomically dispersed Mn-N_(4) sites were dispersed on ultrathin carbon nanosheets with a hierarchically porous structure.The optimized MnNCS displayed an excellent ORR performance in half-cells(0.89 V vs.reversible hydrogen electrode(RHE)in base and 0.76 V vs.RHE in acid in half-wave potential)and Zn-air batteries(233 mW cm^(−2)in peak power density),along with significantly enhanced stability.Density functional theory calculations further corroborated that the Mn-N_(4)-C(12)site has favorable adsorption of*OH as the rate-determining step.These findings demonstrate that the metal-hexamine coordination framework can be used as a model system for the rational design of highly active atomic metal catalysts for energy applications.
文摘目的:建立和验证一个涉及多级临床场景的白内障协作通用的人工智能(artificial intelligence,AI)管理平台,探索基于AI的医疗转诊模式,以提高协作效率和资源覆盖率。方法:训练和验证的数据集来自中国AI医学联盟,涵盖多级医疗机构和采集模式。使用三步策略对数据集进行标记:1)识别采集模式;2)白内障诊断包括正常晶体眼、白内障眼或白内障术后眼;3)从病因和严重程度检测需转诊的白内障患者。此外,将白内障AI系统与真实世界中的居家自我监测、初级医疗保健机构和专科医院等多级转诊模式相结合。结果:通用AI平台和多级协作模式在三步任务中表现出可靠的诊断性能:1)识别采集模式的受试者操作特征(receiver operating characteristic curve,ROC)曲线下面积(area under the curve,AUC)为99.28%~99.71%);2)白内障诊断对正常晶体眼、白内障或术后眼,在散瞳-裂隙灯模式下的AUC分别为99.82%、99.96%和99.93%,其他采集模式的AUC均>99%;3)需转诊白内障的检测(在所有测试中AUC>91%)。在真实世界的三级转诊模式中,该系统建议30.3%的人转诊,与传统模式相比,眼科医生与人群服务比率大幅提高了10.2倍。结论:通用AI平台和多级协作模式显示了准确的白内障诊断性能和有效的白内障转诊服务。建议AI的医疗转诊模式扩展应用到其他常见疾病和资源密集型情景当中。
基金Supported by Fundamental Research Funds for the Central Universities(2019PY13)National Program for Support of Top-notch Young Professionals,Science and Technology Basic Resources Investigation Program of China(2019FY100903)+5 种基金National Natural Science Foundation of China(31971614)Guangdong Natural Science Funds for Distinguished Young Scholar(2016A030306027)Guangdong Natural Science Funds(2017A030313130)Guangzhou science and technology funds(201904010078)State Key Lab of Pulp and Paper Engineering(2020C03)China Postdoctoral Science Foundation Grant(2019T120725,2019M652882).
文摘Rational design and facile preparation of low-cost and efficient catalysts for the selective converting of biomass-derived monosaccharides into high value-added chemicals is highly demanded,yet challenging.Herein,we first demonstrate a N doped defect-rich carbon(NC-800-5)as metal-free catalyst for the selective oxidation of D-xylose into D-xylonic acid in alkaline aqueous solution at 100℃ for 30 min,with 57.4%yield.The doped graphitic N is found to be the active site and hydroxyl ion participating in the oxidation of D-xylose.Hydroxyl ion and D-xylose first adsorb on NC-800-5 surface,and the aldehyde group of D-xylose is catalyzed to form germinal diols ion.Then,C–H bond break to yield carboxylic group.Furthermore,NC-800-5 catalyst shows high stability in recycled test.
