Plasmonic nanoparticles are endowed profound capability for sensing,biomedicine,and cancer therapy.However,the inaccessibly adjustable wavelength in near infrared(NIR)region window and size limit for the particles pen...Plasmonic nanoparticles are endowed profound capability for sensing,biomedicine,and cancer therapy.However,the inaccessibly adjustable wavelength in near infrared(NIR)region window and size limit for the particles penetration in tumor strongly hinder their developments.Miniature gold nanorods(mini-Au NRs)with diameter less than 12 nm can effectively address this challenge due to the tiny size and tailorable NIR absorption.Herein,we adopt ternary surfactants(hexadecyl trimethyl ammonium bromide(CTAB),sodium oleate(NaOL),and sodium salicylate(NaSal))mediated growth strategy to precisely synthesize miniature Au NRs under micelle space-confinement.Importantly,the selectively dense accumulation of ternary surfactants can efficiently improve the micellar stacking parameters(p)and lower micellar free energy(F),further tends to achieve the formation of Au NRs with tiny diameter and high purity.Compared with that of conventional methods,the purity of mini-Au NRs up to 100%can be dramatically improved via varying the relative concentration of ternary surfactants.The diameter of Au NRs can be dynamically controlled to 6,8,and 11 nm through regulating the concentration of silver nitrate and the mole ratio of ternary surfactants.Such ternary surfactants system is favorable for the aging of tiny Au NRs,and further enables the aspect ratio-tunable in the region from 2.70 to 7.32,as well as tailorable plasmonic wavelength in wide NIR window from 700 to 1,147 nm.Therefore,our findings shed a light on the precise preparation of small sized plasmonic nanoparticles and pave the way to applications in biomedicine,imaging,and cancer therapy.展开更多
应用便携式近红外光谱仪采集320份生鲜猪肉在近红外光谱中波区的光谱信息,采用不同优化方法建立猪肉胆固醇预测模型,并对异常样品的剔除及组合预处理方法对模型性能的改善进行了分析。研究表明:通过对异常值的二次剔除,并使用SG一阶导数...应用便携式近红外光谱仪采集320份生鲜猪肉在近红外光谱中波区的光谱信息,采用不同优化方法建立猪肉胆固醇预测模型,并对异常样品的剔除及组合预处理方法对模型性能的改善进行了分析。研究表明:通过对异常值的二次剔除,并使用SG一阶导数(savitzky-golay first derivative,SG 1st D)、SG平滑(savitzky-golay smoothing,SGS)和正交信号校正(OSC)的组合预处理方法,可获得最佳生鲜猪肉胆固醇预测模型,其参数如下:校正集相关系数(Rc)=0.9137,校正标准差(standard error of calibration,SEC)=2.5607,验证集相关系数(Rp)=0.656 7,预测标准差(standard error of prediction,SEP)=4.985 5,主因子数(principal factor,PF)=4,范围误差比(ratio of performance to standard deviation,RPD)=2.5032,相对预测标准差(relative standard error of prediction,RSEP)=8.625 4%,SEP/SEC=1.946 8,说明模型在近红外光谱中波区对猪肉胆固醇的分辨能力和预测准确度较好,通过向校正集中补充代表性样品可使模型稳健性进一步改善。对检验集样品预测值(prediction value,PV)与参比值(reference value,RV)的t检验显示二者之间无显著性差异(p>0.05),检验集样品总体预测准确率为62.5%,其中50~70mg·(100g)-1区段的局部预测准确率达到91.7%,可以用于生鲜猪肉胆固醇浓度的在线快速初步定量分析。该研究将便携式近红外光谱用于在近红外中波区对生鲜猪肉及肉制品中胆固醇浓度的分析和检测,通过进一步的研究和改进,可将其应用于产品的原料分级、品质和过程控制及市售产品的抽检等。展开更多
近红外二区(900~1 880 nm,the Second Near-Infrared Region,NIR-Ⅱ)荧光宽场显微成像技术是当前大深度活体成像的一大研究热点,在基础研究和临床应用方面都拥有巨大的潜力。对比可见光(360~760 nm)和近红外一区(760~900 nm,the First N...近红外二区(900~1 880 nm,the Second Near-Infrared Region,NIR-Ⅱ)荧光宽场显微成像技术是当前大深度活体成像的一大研究热点,在基础研究和临床应用方面都拥有巨大的潜力。对比可见光(360~760 nm)和近红外一区(760~900 nm,the First Near-Infrared Region,NIR-Ⅰ)的成像,NIR-Ⅱ荧光宽场显微成像技术在活体层面具有更高的清晰度和更深的组织穿透。在NIR-Ⅱ宏观成像基础上,对组织微结构清晰成像的需求迫使成像试剂持续发展,成像系统不断精进。目前,NIR-Ⅱ荧光宽场显微成像技术在脉管显微造影、肿瘤精确分析、炎症准确追踪等生物应用上都获得一系列突破,相关研究对象包含啮齿类动物(如小鼠,大鼠)及灵长类动物(如狨猴,猕猴)等。将来随着仪器商业化和国产化突破,成像试剂安全性逐步提高,NIR-Ⅱ荧光宽场显微成像应用价值将不断攀升。本文从NIR-Ⅱ荧光成像的机制及优势展开讨论,综述NIR-Ⅱ荧光宽场显微成像的系统特点和演进历史,以及其在不同生物模型上活体成像方面的最新探索和前景展望,以期推动NIR-Ⅱ荧光宽场显微成像技术进一步普及。展开更多
基金the financial support from the National Natural Science Foundation of China(Nos.52222316,52103325,and 52111530128)the Zhejiang Provincial Natural Science Foundation of China(No.Z22B050001)+1 种基金Ten Thousand People Plan of Zhejiang Province(No.2019R51012)China Postdoctoral Science Foundation(No.2022M713020).
文摘Plasmonic nanoparticles are endowed profound capability for sensing,biomedicine,and cancer therapy.However,the inaccessibly adjustable wavelength in near infrared(NIR)region window and size limit for the particles penetration in tumor strongly hinder their developments.Miniature gold nanorods(mini-Au NRs)with diameter less than 12 nm can effectively address this challenge due to the tiny size and tailorable NIR absorption.Herein,we adopt ternary surfactants(hexadecyl trimethyl ammonium bromide(CTAB),sodium oleate(NaOL),and sodium salicylate(NaSal))mediated growth strategy to precisely synthesize miniature Au NRs under micelle space-confinement.Importantly,the selectively dense accumulation of ternary surfactants can efficiently improve the micellar stacking parameters(p)and lower micellar free energy(F),further tends to achieve the formation of Au NRs with tiny diameter and high purity.Compared with that of conventional methods,the purity of mini-Au NRs up to 100%can be dramatically improved via varying the relative concentration of ternary surfactants.The diameter of Au NRs can be dynamically controlled to 6,8,and 11 nm through regulating the concentration of silver nitrate and the mole ratio of ternary surfactants.Such ternary surfactants system is favorable for the aging of tiny Au NRs,and further enables the aspect ratio-tunable in the region from 2.70 to 7.32,as well as tailorable plasmonic wavelength in wide NIR window from 700 to 1,147 nm.Therefore,our findings shed a light on the precise preparation of small sized plasmonic nanoparticles and pave the way to applications in biomedicine,imaging,and cancer therapy.
文摘应用便携式近红外光谱仪采集320份生鲜猪肉在近红外光谱中波区的光谱信息,采用不同优化方法建立猪肉胆固醇预测模型,并对异常样品的剔除及组合预处理方法对模型性能的改善进行了分析。研究表明:通过对异常值的二次剔除,并使用SG一阶导数(savitzky-golay first derivative,SG 1st D)、SG平滑(savitzky-golay smoothing,SGS)和正交信号校正(OSC)的组合预处理方法,可获得最佳生鲜猪肉胆固醇预测模型,其参数如下:校正集相关系数(Rc)=0.9137,校正标准差(standard error of calibration,SEC)=2.5607,验证集相关系数(Rp)=0.656 7,预测标准差(standard error of prediction,SEP)=4.985 5,主因子数(principal factor,PF)=4,范围误差比(ratio of performance to standard deviation,RPD)=2.5032,相对预测标准差(relative standard error of prediction,RSEP)=8.625 4%,SEP/SEC=1.946 8,说明模型在近红外光谱中波区对猪肉胆固醇的分辨能力和预测准确度较好,通过向校正集中补充代表性样品可使模型稳健性进一步改善。对检验集样品预测值(prediction value,PV)与参比值(reference value,RV)的t检验显示二者之间无显著性差异(p>0.05),检验集样品总体预测准确率为62.5%,其中50~70mg·(100g)-1区段的局部预测准确率达到91.7%,可以用于生鲜猪肉胆固醇浓度的在线快速初步定量分析。该研究将便携式近红外光谱用于在近红外中波区对生鲜猪肉及肉制品中胆固醇浓度的分析和检测,通过进一步的研究和改进,可将其应用于产品的原料分级、品质和过程控制及市售产品的抽检等。
