荧光寿命数据的相量分析及其应用

林丹樱; 牛敬敬; 刘雄波; 张潇; 张娇; 于斌; 屈军乐

doi:10.7498/aps.69.20200554

摘要

荧光寿命显微成像技术(fluorescence lifetime imaging microscopy, FLIM)具有特异性强、灵敏度高、可定量测量等优点, 被广泛应用于生物医学、材料学等领域的研究. 为使FLIM技术更好地适用于高通量数据的快速分析, 近年来涌现出多种荧光寿命分析的新算法. 其中, 相量分析法(phasor analysis, PA)通过将时间域的拟合转化为频率域的直接计算来获得荧光寿命值, 与传统的最小二乘拟合法相比, 不仅更加简便快速, 适用于低光子数情形, 而且便于使数据内容可视化和对数据进行聚类分析, 因此越来越受到科研人员的青睐. 本文详细阐述了相量分析法的基本原理及运用方法, 并在此基础上介绍了该方法在细胞代谢状态测量、蛋白质相互作用研究、细胞微环境测量, 以及辅助病理诊断和提高超分辨成像分辨率等方面的应用, 着重讨论了PA法在这些FLIM应用实例中的优势所在, 为相关领域的研究提供有益的参考. 最后, 对荧光寿命数据的相量分析及其应用的发展方向进行展望.

关键词:

Abstract

Fluorescence lifetime imaging microscopy (FLIM) is widely used in biomedical, materials and other fields. It not only has strong specificity and high sensitivity, but also has the capability of quantitative measurement because the fluorescence lifetime is not affected by the intensity of excitation, the concentration of fluorophores and photobleaching, and consequently is able to monitor the changes of microenvironment and reflecting the interaction between molecules. However, its application is limited to some extent by the complexity of data analysis. In order to make FLIM technology more suitable for fast analysis of high-throughput data, a variety of new algorithms for fluorescence lifetime analysis have emerged in recent years, such as phasor analysis, maximum likelihood estimation, first-order moment, Bayesian analysis, and compressed sensing. Among them, the phasor analysis (PA) method obtains the fluorescence lifetime by converting the fitting in the time domain to the direct calculation in the frequency domain. Compared with traditional least-square fitting method, it is not only simpler and faster, but also more suitable for the case of low photon counts. In addition, in the PA approach to FLIM, the fluorescence decay is directly converted into a phasor diagram by simple mathematics, where the phasor points originating from different pixels in the image are represented by the positions in the phasor plot, and thus the graphical representation obtained by PA method is convenient for data visualization and cluster analysis. Therefore, it has become a simple and powerful analysis method for FLIM, and is increasingly favored by researchers. In this paper, the basic principle of PA method and how we can use it are described in detail. And on this basis, the latest application research progress of the method in cell metabolism state measurement, protein interaction study, cell microenvironment measurement, auxiliary pathological diagnosis, and resolution improvement in super-resolution imaging are introduced and summarized. The advantages of PA method in these FLIM applications are focused on, providing useful reference for the research in related fields. Finally, the phasor analysis method for FLIM data analysis and the development trend of its application are prospected.

Keywords:

作者及机构信息

深圳大学物理与光电工程学院, 光电子器件与系统教育部/广东省重点实验室, 深圳　518060

通信作者: 林丹樱, dylin@szu.edu.cn ; 屈军乐, jlqu@szu.edu.cn

基金项目: 国家重点研发计划(批准号: 2017YFA0700500)、国家自然科学基金(批准号: 61775144, 61975131, 61620106016, 61525503, 61835009)、广东省高等学校科技创新(重点)项目(批准号: 2016KCXTD007)、广东省自然科学基金(批准号: 2018A030313362)和深圳市基础研究项目(批准号: JCYJ20170818144012025, JCYJ20170818141701667, JCYJ20170412105003520)资助的课题

Authors and contacts

Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China

Corresponding author: Lin Dan-Ying, dylin@szu.edu.cn ; Qu Jun-Le, jlqu@szu.edu.cn

Funds: Project supported by the National Key R&D Program of China (Grant No. 2017YFA0700500), the National Natural Science Foundation of China (Grant Nos. 61775144, 61975131, 61620106016, 61525503, 61835009), the (Key) Project of Department of Education of Guangdong Province, China (Grant No. 2016KCXTD007), the Natural Science Foundation of Guangdong Province, China (Grant No. 2018A030313362), and the Shenzhen Basic Research Project, China (Grant Nos. JCYJ20170818144012025, JCYJ20170818141701667, JCYJ20170412105003520)

文章全文 : translate this paragraph

参考文献

[1]	刘雄波, 林丹樱, 吴茜茜, 严伟, 罗腾, 杨志刚, 屈军乐 2018 物理学报 67 178701 Google Scholar Liu X B, Lin D Y, Wu Q Q, Yan W, Luo T, Yang Z G, Qu J L 2018 Acta Phys. Sin. 67 178701 Google Scholar
[2]	Levchenko S M, Pliss A, Qu J 2018 J. Innovative Opt. Health Sci. 11 1730009 Google Scholar
[3]	刘超, 周燕, 王新伟, 刘育梁 2011 激光与光电子学进展 48 111102 Google Scholar Liu C, Zhou Y, Wang X, Liu Y 2011 Laser Optoelectron. Prog. 48 111102 Google Scholar
[4]	Fitzgerald C, Hosny N A, Tong H, Seville P C, Gallimore P J, Davidson N M, Athanasiadis A, Botchway S W, Ward A D, Kalberer M, Kuimov M K, Pope F D 2016 Phys. Chem. Chem. Phys. 18 21710 Google Scholar
[5]	Gratton E, Breusegem S, Sutin J, Ruan Q, Barry N 2003 J. Biomed. Opt. 8 38190
[6]	Suman R, Leonel M, Jameson D M, Gratton E 2018 Nat. Protoc. 13 1979 Google Scholar
[7]	Chessel A, Waharte F, Salamero J, Kervrann C 2013 21st European Signal Processing Conference Marrakech, Morocco, September 9–13, 2013 p1
[8]	徐玲玲 2013 博士学位论文 (武汉: 华中科技大学) Xu L L 2013 Ph. D. Dissertation (Wuhan: Huazhong University of Science and Technology) (in Chinese)
[9]	Rowley M I, Coolen A C C, Vojnovic B, Barber P R 2016 PLoS One 11 e0158404 Google Scholar
[10]	Yang S, Lee J, Lee Y, Lee M, Lee B U 2015 J. Biomed. Opt. 20 096003 Google Scholar
[11]	Liu X, Lin D, Becker W, Niu J, Yu B, Liu L, Qu J 2019 J. Innovative. Opt. Health Sci. 12 1930003 Google Scholar
[12]	Stefl M, James N G, Ross J A, Jameson D M 2011 Anal. Biochem. 410 62 Google Scholar
[13]	Jameson D M, Gratton E, Hall R D 1984 Appl. Spectrosc. Rev. 20 55 Google Scholar
[14]	Weber G 1981 J. Phys. Chem. B 85 949 Google Scholar
[15]	Redford G I, Clegg R M 2005 J. Fluoresc. 15 805 Google Scholar
[16]	Digman M A, Caiolfa V R, Zamai M, Gratton E 2008 Biophys. J. 94 L14 Google Scholar
[17]	Bird D K, Yan L, Vrotsos K M, Eliceiri K W, Vaughan E M, Keely P J, White J G, Ramanujam N 2005 Cancer Res. 65 8766 Google Scholar
[18]	Stringari C, Cinquin A, Cinquin O, Digman M A, Donovan P J, Gratton E 2011 Proc. Natl. Acad. Sci. U.S.A. 108 13582 Google Scholar
[19]	Stringari C, Edwards R A, Pate K T, Waterman M L, Donovan P J, Gratton E 2012 Sci. Rep. 2 568 Google Scholar
[20]	Stringari C, Donovan P, Gratton E 2012 Proc. SPIE San Francisco, CA January 22–24, 2012 p9
[21]	Lee D H, Li X, Ma N, Digman M A, Lee A P 2018 Lab Chip 18 1349 Google Scholar
[22]	Romero-López M, Trinh A L, Sobrino A, Hatch M M S, Keating M T, Fimbres C, Lewis D E, Gershon P D, Botvinick E L, Digman M, Lowengrub J S, Hughes C C W 2016 Biomaterials 116 118
[23]	Sameni S, Syed A, Marsh J L, Digman M A 2016 Sci. Rep. 6 34755 Google Scholar
[24]	Dong Y, Sameni1 S, Digman M A, Brewer G J 2019 Sci. Rep. 9 11274 Google Scholar
[25]	Dong Y, Digman M A, Brewer G J 2019 GeroScience 41 51 Google Scholar
[26]	Hato T, Winfree S, Day R, Sandoval R M, Molitoris B A, Yoder M C, Wiggins R C, Zheng Y, Dunn K W, Dagher P C 2017 J. Am. Soc. Nephrol. 28 2420 Google Scholar
[27]	Datta R, Heylman C, George S C, Gratton E 2016 Biomed. Opt. Express 7 1690 Google Scholar
[28]	Hinde E, Digman M A, Hahn K M, Hahn K M, Gratton E 2012 Microsc. Res. Tech. 75 271 Google Scholar
[29]	Hinde E, Digman M A, Hahn K M, Gratton E 2013 Proc. Natl. Acad. Sci. U.S.A. 110 135 Google Scholar
[30]	Lou J Q, Scipioni L, Wright B K, Bartolec T K, Zhang J, Masamsetti V P, Gaus K, Gratton E, Cesare A J, Hinde E 2019 Proc. Natl. Acad. Sci. U.S.A. 116 7323 Google Scholar
[31]	Chen H, Ma N, Kagawa K, Kawahito S, Digman M, Gratton E 2018 J. Biophotonics 12 e201800223
[32]	Battisti A, Digman M A, Gratton E, Storti B, Beltram F, Bizzarri R 2012 Chem. Commun. 48 5127 Google Scholar
[33]	Zhou T, Luo T, Song J, Qu J 2018 Anal. Chem. 90 2170 Google Scholar
[34]	Ferri G, Nucara L, Biver T, Battisti A, Signore G, Bizzarri R 2016 Biophys. J. 110 163a Google Scholar
[35]	Luo T, Lu Y, Liu S, Lin D, Qu J 2017 Anal. Chem. 89 8104 Google Scholar
[36]	Luo T, Lu Y, Liu S, Lin D, Qu J 2017 Anal. Chem. 89 9224 Google Scholar
[37]	Ranjit S, Dvornikov A, Levi M, Furgeson S, Gratton E 2016 Biomed. Opt. Express 7 3519 Google Scholar
[38]	Lanzanò L, Hernandez I C, Castello M, Gratton E, Diaspro A, Vicidomini G 2015 Nat. Commun. 6 6701 Google Scholar
[39]	Wang L, Chen B, Yan W, Yang Z, Peng X, Lin D, Weng X, Ye T, Qu J 2018 Nanoscale 10 16252 Google Scholar
[40]	Tortarolo G, Sun Y, Teng K W, Ishitsuka Y, Lanzano L, Selvin P R, Barbieri B, Diaspro A, Vicidomini G 2019 Nanoscale 11 1754 Google Scholar
[41]	周宇会, 魏九峰, 李国东, 刘明 2017 国际肿瘤学杂志 44 762 Google Scholar Zhou Y, Wei J, Li G, Liu M 2017 J. Int. Oco. 44 762 Google Scholar
[42]	林丹樱, 屈军乐 2017 物理学报 66 148703 Google Scholar Lin D Y, Qu J L 2017 Acta Phys. Sin. 66 148703 Google Scholar

施引文献

图 1 荧光寿命的测量方法及相量分析(PA)法示意图　(a)频域法测量原理示意图; (b)单指数衰减的寿命相量示例图; (c)双指数衰减的寿命相量示例图; (d)时间相关单光子计数(TCSPC)测量原理示意图

Fig. 1. Schematic diagram of fluorescence lifetime measurement and phasor analysis (PA):(a) Frequency domain method; (b) lifetime phasor of single-exponential decay; (c) lifetime phasor of bi-exponential decay; (d) time-correlated single photon counting (TCSPC) method.

下载: 全尺寸图片幻灯片

图 2 Phasor-FLIM的应用思路示意图　(a)包含未处理寿命信息的荧光强度图; (b)经PA法分析得到的寿命相量图; (c)对寿命相量直接进行分析; (d)通过相量聚类分析和伪彩色标记得到的荧光寿命图

Fig. 2. Schematic diagram of phasor-FLIM application:(a) Fluorescence intensity image with untreated lifetime information; (b) lifetime phasor plot obtained by PA analysis; (c) direct analysis of lifetime phasors; (d) phasor-mapped FLIM image based on phasor clustering analysis and pseudo-color assignment.

下载: 全尺寸图片幻灯片

图 3 Phasor-FLIM 的应用分类示意图

Fig. 3. Application classification diagram of phasor-FLIM.

下载: 全尺寸图片幻灯片

图 4 Phasor-FLIM用于分析细胞在缺氧和线粒体毒性药物氰化钾刺激下NADH/NAD+比例的变化, 研究代谢状态的转变^[27]

Fig. 4. Phasor-FLIM was used to analyze the change of NADH/NAD+ ratio under the stimulation of hypoxia and mitochondrial toxic drug potassium cyanide, for studying the change of metabolic state of cells^[27].

下载: 全尺寸图片幻灯片

图 5 Phasor-FLIM用于定量测量RhoA-kRas单链生物传感器的荧光共振能量转移(FRET)效率, 研究蛋白互作^[28]

Fig. 5. Phasor-FLIM was used in quantitative FRET efficiency detection of a RhoA-kRas single chain biosensor, studying interaction between proteins^[28].

下载: 全尺寸图片幻灯片

图 6 Phasor-FLIM用于分析细胞在正常(静止)状态和氧化应激状态下pH值的变化^[32]

Fig. 6. Phasor-FLIM was used to analyze the changes of pH value of cells in normal state (at rest) and under oxidative stress^[32].

下载: 全尺寸图片幻灯片

图 7 Phasor-FLIM聚类分析和伪彩色标记用于增强H&E染色基底细胞癌(BCC)切片病理学特征的可视化, 可辅助病理诊断^[36]

Fig. 7. Phasor-FLIM clustering analysis and pseudo-color assignment was used to enhance visualization of pathological features of basal cell carcinoma (BCC) sections stained with H&E, assisting pathological diagnosis^[36].

下载: 全尺寸图片幻灯片

图 8 Phasor-FLIM聚类分析用于滤除受激辐射耗尽(STED)成像中环形擦除光区域的光子, 可辅助提升超分辨成像分辨率^[39]

Fig. 8. Phasor-FLIM cluster analysis was used to filter out the photons in the annular depletion region in stimulated radiation depletion (STED) imaging, improving the resolution of super-resolution imaging^[39].

下载: 全尺寸图片幻灯片

[1]	刘雄波, 林丹樱, 吴茜茜, 严伟, 罗腾, 杨志刚, 屈军乐 2018 物理学报 67 178701 Google Scholar Liu X B, Lin D Y, Wu Q Q, Yan W, Luo T, Yang Z G, Qu J L 2018 Acta Phys. Sin. 67 178701 Google Scholar
[2]	Levchenko S M, Pliss A, Qu J 2018 J. Innovative Opt. Health Sci. 11 1730009 Google Scholar
[3]	刘超, 周燕, 王新伟, 刘育梁 2011 激光与光电子学进展 48 111102 Google Scholar Liu C, Zhou Y, Wang X, Liu Y 2011 Laser Optoelectron. Prog. 48 111102 Google Scholar
[4]	Fitzgerald C, Hosny N A, Tong H, Seville P C, Gallimore P J, Davidson N M, Athanasiadis A, Botchway S W, Ward A D, Kalberer M, Kuimov M K, Pope F D 2016 Phys. Chem. Chem. Phys. 18 21710 Google Scholar
[5]	Gratton E, Breusegem S, Sutin J, Ruan Q, Barry N 2003 J. Biomed. Opt. 8 38190
[6]	Suman R, Leonel M, Jameson D M, Gratton E 2018 Nat. Protoc. 13 1979 Google Scholar
[7]	Chessel A, Waharte F, Salamero J, Kervrann C 2013 21st European Signal Processing Conference Marrakech, Morocco, September 9–13, 2013 p1
[8]	徐玲玲 2013 博士学位论文 (武汉: 华中科技大学) Xu L L 2013 Ph. D. Dissertation (Wuhan: Huazhong University of Science and Technology) (in Chinese)
[9]	Rowley M I, Coolen A C C, Vojnovic B, Barber P R 2016 PLoS One 11 e0158404 Google Scholar
[10]	Yang S, Lee J, Lee Y, Lee M, Lee B U 2015 J. Biomed. Opt. 20 096003 Google Scholar
[11]	Liu X, Lin D, Becker W, Niu J, Yu B, Liu L, Qu J 2019 J. Innovative. Opt. Health Sci. 12 1930003 Google Scholar
[12]	Stefl M, James N G, Ross J A, Jameson D M 2011 Anal. Biochem. 410 62 Google Scholar
[13]	Jameson D M, Gratton E, Hall R D 1984 Appl. Spectrosc. Rev. 20 55 Google Scholar
[14]	Weber G 1981 J. Phys. Chem. B 85 949 Google Scholar
[15]	Redford G I, Clegg R M 2005 J. Fluoresc. 15 805 Google Scholar
[16]	Digman M A, Caiolfa V R, Zamai M, Gratton E 2008 Biophys. J. 94 L14 Google Scholar
[17]	Bird D K, Yan L, Vrotsos K M, Eliceiri K W, Vaughan E M, Keely P J, White J G, Ramanujam N 2005 Cancer Res. 65 8766 Google Scholar
[18]	Stringari C, Cinquin A, Cinquin O, Digman M A, Donovan P J, Gratton E 2011 Proc. Natl. Acad. Sci. U.S.A. 108 13582 Google Scholar
[19]	Stringari C, Edwards R A, Pate K T, Waterman M L, Donovan P J, Gratton E 2012 Sci. Rep. 2 568 Google Scholar
[20]	Stringari C, Donovan P, Gratton E 2012 Proc. SPIE San Francisco, CA January 22–24, 2012 p9
[21]	Lee D H, Li X, Ma N, Digman M A, Lee A P 2018 Lab Chip 18 1349 Google Scholar
[22]	Romero-López M, Trinh A L, Sobrino A, Hatch M M S, Keating M T, Fimbres C, Lewis D E, Gershon P D, Botvinick E L, Digman M, Lowengrub J S, Hughes C C W 2016 Biomaterials 116 118
[23]	Sameni S, Syed A, Marsh J L, Digman M A 2016 Sci. Rep. 6 34755 Google Scholar
[24]	Dong Y, Sameni1 S, Digman M A, Brewer G J 2019 Sci. Rep. 9 11274 Google Scholar
[25]	Dong Y, Digman M A, Brewer G J 2019 GeroScience 41 51 Google Scholar
[26]	Hato T, Winfree S, Day R, Sandoval R M, Molitoris B A, Yoder M C, Wiggins R C, Zheng Y, Dunn K W, Dagher P C 2017 J. Am. Soc. Nephrol. 28 2420 Google Scholar
[27]	Datta R, Heylman C, George S C, Gratton E 2016 Biomed. Opt. Express 7 1690 Google Scholar
[28]	Hinde E, Digman M A, Hahn K M, Hahn K M, Gratton E 2012 Microsc. Res. Tech. 75 271 Google Scholar
[29]	Hinde E, Digman M A, Hahn K M, Gratton E 2013 Proc. Natl. Acad. Sci. U.S.A. 110 135 Google Scholar
[30]	Lou J Q, Scipioni L, Wright B K, Bartolec T K, Zhang J, Masamsetti V P, Gaus K, Gratton E, Cesare A J, Hinde E 2019 Proc. Natl. Acad. Sci. U.S.A. 116 7323 Google Scholar
[31]	Chen H, Ma N, Kagawa K, Kawahito S, Digman M, Gratton E 2018 J. Biophotonics 12 e201800223
[32]	Battisti A, Digman M A, Gratton E, Storti B, Beltram F, Bizzarri R 2012 Chem. Commun. 48 5127 Google Scholar
[33]	Zhou T, Luo T, Song J, Qu J 2018 Anal. Chem. 90 2170 Google Scholar
[34]	Ferri G, Nucara L, Biver T, Battisti A, Signore G, Bizzarri R 2016 Biophys. J. 110 163a Google Scholar
[35]	Luo T, Lu Y, Liu S, Lin D, Qu J 2017 Anal. Chem. 89 8104 Google Scholar
[36]	Luo T, Lu Y, Liu S, Lin D, Qu J 2017 Anal. Chem. 89 9224 Google Scholar
[37]	Ranjit S, Dvornikov A, Levi M, Furgeson S, Gratton E 2016 Biomed. Opt. Express 7 3519 Google Scholar
[38]	Lanzanò L, Hernandez I C, Castello M, Gratton E, Diaspro A, Vicidomini G 2015 Nat. Commun. 6 6701 Google Scholar
[39]	Wang L, Chen B, Yan W, Yang Z, Peng X, Lin D, Weng X, Ye T, Qu J 2018 Nanoscale 10 16252 Google Scholar
[40]	Tortarolo G, Sun Y, Teng K W, Ishitsuka Y, Lanzano L, Selvin P R, Barbieri B, Diaspro A, Vicidomini G 2019 Nanoscale 11 1754 Google Scholar
[41]	周宇会, 魏九峰, 李国东, 刘明 2017 国际肿瘤学杂志 44 762 Google Scholar Zhou Y, Wei J, Li G, Liu M 2017 J. Int. Oco. 44 762 Google Scholar
[42]	林丹樱, 屈军乐 2017 物理学报 66 148703 Google Scholar Lin D Y, Qu J L 2017 Acta Phys. Sin. 66 148703 Google Scholar

[1]	杨志刚, 刘颖超, 张仕青, 罗瑞鉴, 赵需谦, 连加荣, 屈军乐. 活细胞应激反应过程中线粒体和核仁微环境动力学的荧光寿命成像研究. 物理学报, 2024, 73(7): 078702. doi: 10.7498/aps.73.20231990
[2]	王雨, 张慧敏, 覃欢. 生物医学微波热声成像. 物理学报, 2023, 72(20): 204301. doi: 10.7498/aps.72.20230732
[3]	张坤, 罗涛, 王菲菲, 孙刚, 刘庆, 青春, 李学彬, 翁宁泉, 朱文越. 基于探空数据分析低云对大气折射率结构常数的影响. 物理学报, 2022, 71(8): 089202. doi: 10.7498/aps.71.20211792
[4]	朱栋, 徐晗, 周寅, 吴彬, 程冰, 王凯楠, 陈佩军, 高世腾, 翁堪兴, 王河林, 彭树萍, 乔中坤, 王肖隆, 林强. 基于扩展卡尔曼滤波算法的船载绝对重力测量数据处理. 物理学报, 2022, 71(13): 133702. doi: 10.7498/aps.71.20220071
[5]	李少强, 耿俊娴, 李艳萍, 刘雄波, 彭晓, 屈军乐, 刘丽炜, 胡睿. 多光子成像技术的生物医学应用新进展. 物理学报, 2020, 69(22): 228702. doi: 10.7498/aps.69.20201039
[6]	刘雄波, 林丹樱, 吴茜茜, 严伟, 罗腾, 杨志刚, 屈军乐. 荧光寿命显微成像技术及应用的最新研究进展. 物理学报, 2018, 67(17): 178701. doi: 10.7498/aps.67.20180320
[7]	孙东永, 张洪波, 王义民. 滑动移除小波分析法在动力学结构突变检验中的应用. 物理学报, 2017, 66(7): 079201. doi: 10.7498/aps.66.079201
[8]	梁铭辉, 郑飞虎, 安振连, 张冶文. 基于Monte Carlo的热脉冲法数据分析. 物理学报, 2016, 65(7): 077702. doi: 10.7498/aps.65.077702
[9]	王丽吉, 陈泽宇, 凌超, 吕达仁. 中层大气静力稳定性减弱趋势——历史火箭探空数据分析. 物理学报, 2015, 64(16): 169201. doi: 10.7498/aps.64.169201
[10]	殷杰, 陶超, 刘晓峻. 多参量光声成像及其在生物医学领域的应用. 物理学报, 2015, 64(9): 098102. doi: 10.7498/aps.64.098102
[11]	石红, 田立成, 杨生胜. 嫦娥一号卫星太阳风离子探测器数据分析. 物理学报, 2014, 63(6): 069601. doi: 10.7498/aps.63.069601
[12]	韩祥临, 欧阳成, 宋涛, 戴孙圣. 交通拥堵相变问题的同伦分析法. 物理学报, 2013, 62(17): 170203. doi: 10.7498/aps.62.170203
[13]	万文博, 华灯鑫, 乐静, 刘美霞, 曹宁. 激光诱导叶绿素荧光寿命的测量及其特性分析. 物理学报, 2013, 62(19): 190601. doi: 10.7498/aps.62.190601
[14]	帅文娟, 冯少彤, 聂守平, 朱竹青. 基于主分量分析法的小波域三维目标序列图像隐藏技术. 物理学报, 2011, 60(3): 034203. doi: 10.7498/aps.60.034203
[15]	石玉仁, 杨红娟. 同伦分析法在求解耗散系统中的应用. 物理学报, 2010, 59(1): 67-74. doi: 10.7498/aps.59.67
[16]	谭延亮, 肖德涛, 赵桂芝. 理想条件下氡及其子体垂直运移实验数据分析. 物理学报, 2008, 57(9): 5452-5457. doi: 10.7498/aps.57.5452
[17]	石玉仁, 许新建, 吴枝喜, 汪映海, 杨红娟, 段文山, 吕克璞. 同伦分析法在求解非线性演化方程中的应用. 物理学报, 2006, 55(4): 1555-1560. doi: 10.7498/aps.55.1555
[18]	乐贵明, 韩延本. 用银河宇宙线数据分析1991年3月24日CME的结构. 物理学报, 2005, 54(1): 467-470. doi: 10.7498/aps.54.467
[19]	王瑞峰, 赵士平, 徐凤枝, 陈赓华, 杨乾声. 超导体磁场穿透深度测量中的数据分析问题. 物理学报, 2002, 51(4): 889-893. doi: 10.7498/aps.51.889
[20]	何元金, 曹必松. 正电子湮没寿命谱的傅里叶变换分析法. 物理学报, 1984, 33(12): 1745-1752. doi: 10.7498/aps.33.1745

计量

文章访问数: 13685
PDF下载量: 315
被引次数: 0

姓名
邮箱
手机号码
标题
留言内容
验证码

搜索

留言板

荧光寿命数据的相量分析及其应用