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For: Wang H, Liang X, Gravot G, Thorling CA, Crawford DHG, Xu ZP, Liu X, Roberts MS. Visualizing liver anatomy, physiology and pharmacology using multiphoton microscopy. J Biophoton 2017;10:46-60. [DOI: 10.1002/jbio.201600083] [Cited by in Crossref: 19] [Cited by in F6Publishing: 17] [Article Influence: 3.2] [Reference Citation Analysis]
Number Citing Articles
1 Kuznetsova D, Rodimova S, Gulin A, Reunov D, Bobrov N, Polozova A, Vasin A, Shcheslavskiy V, Vdovina N, Zagainov V, Zagaynova E. Metabolic imaging and secondary ion mass spectrometry to define the structure and function of liver with acute and chronic pathology. J Biomed Opt 2019;25:1-14. [PMID: 31849207 DOI: 10.1117/1.JBO.25.1.014508] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
2 Jain D, Torres R, Celli R, Koelmel J, Charkoftaki G, Vasiliou V. Evolution of the liver biopsy and its future. Transl Gastroenterol Hepatol 2021;6:20. [PMID: 33824924 DOI: 10.21037/tgh.2020.04.01] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
3 [DOI: 10.1117/12.2507434] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
4 Hao X, Wang K, Dai C, Ding Z, Yang W, Wang C, Cheng S. Integrative analysis of scRNA-seq and GWAS data pinpoints periportal hepatocytes as the relevant liver cell types for blood lipids. Hum Mol Genet 2020;29:3145-53. [PMID: 32821946 DOI: 10.1093/hmg/ddaa188] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
5 Rodimova SA, Kuznetsova DS, Bobrov NV, Gulin AA, Vasin AA, Gubina MV, Scheslavsky VI, Elagin VV, Karabut MM, Zagainov VE, Zagaynova EV. Multiphoton Microscopy and Mass Spectrometry for Revealing Metabolic Heterogeneity of Hepatocytes in vivo. Sovrem Tekhnologii Med 2021;13:18-29. [PMID: 34513073 DOI: 10.17691/stm2021.13.2.02] [Reference Citation Analysis]
6 Wang H, Zhang R, Bridle KR, Jayachandran A, Thomas JA, Zhang W, Yuan J, Xu ZP, Crawford DH, Liang X, Liu X, Roberts MS. Two-photon dual imaging platform for in vivo monitoring cellular oxidative stress in liver injury. Sci Rep 2017;7:45374. [PMID: 28349954 DOI: 10.1038/srep45374] [Cited by in Crossref: 14] [Cited by in F6Publishing: 14] [Article Influence: 2.8] [Reference Citation Analysis]
7 Rodimova S, Elagin V, Karabut M, Koryakina I, Timin A, Zagainov V, Zyuzin M, Zagaynova E, Kuznetsova D. Toxicological Analysis of Hepatocytes Using FLIM Technique: In Vitro versus Ex Vivo Models. Cells 2021;10:2894. [PMID: 34831114 DOI: 10.3390/cells10112894] [Reference Citation Analysis]
8 Nozari E, Moradi A, Samadi M. Effect of Atorvastatin, Curcumin, and Quercetin on miR-21 and miR-122 and their correlation with TGFβ1 expression in experimental liver fibrosis. Life Sciences 2020;259:118293. [DOI: 10.1016/j.lfs.2020.118293] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 3.0] [Reference Citation Analysis]
9 Croce AC, Ferrigno A, Di Pasqua LG, Berardo C, Bottiroli G, Vairetti M. NAD(P)H and Flavin Autofluorescence Correlation with ATP in Rat Livers with Different Metabolic Steady-State Conditions. Photochem Photobiol 2017;93:1519-24. [PMID: 28696576 DOI: 10.1111/php.12804] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.4] [Reference Citation Analysis]
10 [DOI: 10.1117/12.2292315] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 0.8] [Reference Citation Analysis]
11 da Silva FAB, Racanelli AP, Lorand-Metze I, Metze K. Fluorescence lifetime imaging is able to recognize different hematopoietic precursors in unstained routine bone marrow films. Cytometry A 2021;99:641-6. [PMID: 33847043 DOI: 10.1002/cyto.a.24345] [Reference Citation Analysis]
12 Croce AC, Ferrigno A, Bottiroli G, Vairetti M. Autofluorescence-based optical biopsy: An effective diagnostic tool in hepatology. Liver Int 2018;38:1160-74. [PMID: 29624848 DOI: 10.1111/liv.13753] [Cited by in Crossref: 23] [Cited by in F6Publishing: 16] [Article Influence: 5.8] [Reference Citation Analysis]
13 Lin H, Wei C, Wang G, Chen H, Lin L, Ni M, Chen J, Zhuo S. Automated classification of hepatocellular carcinoma differentiation using multiphoton microscopy and deep learning. J Biophotonics 2019;12:e201800435. [PMID: 30868728 DOI: 10.1002/jbio.201800435] [Cited by in Crossref: 10] [Cited by in F6Publishing: 14] [Article Influence: 3.3] [Reference Citation Analysis]
14 Fu J, Zhang Q, Wu Z, Hong C, Zhu C. Transcriptomic Analysis Reveals a Sex-Dimorphic Influence of GAT-2 on Murine Liver Function. Front Nutr 2021;8:751388. [PMID: 34604287 DOI: 10.3389/fnut.2021.751388] [Reference Citation Analysis]
15 Rodimova S, Kuznetsova D, Bobrov N, Elagin V, Shcheslavskiy V, Zagainov V, Zagaynova E. Mapping metabolism of liver tissue using two-photon FLIM. Biomed Opt Express 2020;11:4458-70. [PMID: 32923056 DOI: 10.1364/BOE.398020] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
16 Lin H, Fan T, Sui J, Wang G, Chen J, Zhuo S, Zhang H. Recent advances in multiphoton microscopy combined with nanomaterials in the field of disease evolution and clinical applications to liver cancer. Nanoscale 2019;11:19619-35. [PMID: 31599299 DOI: 10.1039/c9nr04902a] [Cited by in Crossref: 7] [Cited by in F6Publishing: 4] [Article Influence: 2.3] [Reference Citation Analysis]
17 Barkauskas DS, Medley G, Liang X, Mohammed YH, Thorling CA, Wang H, Roberts MS. Using in vivo multiphoton fluorescence lifetime imaging to unravel disease-specific changes in the liver redox state. Methods Appl Fluoresc 2020;8:034003. [PMID: 32422610 DOI: 10.1088/2050-6120/ab93de] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
18 Bruce KD, Jonscher KR. Assessment of Fatty Liver in Models of Disease Programming. In: Guest PC, editor. Investigations of Early Nutrition Effects on Long-Term Health. New York: Springer; 2018. pp. 251-66. [DOI: 10.1007/978-1-4939-7614-0_15] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 1.0] [Reference Citation Analysis]
19 Saitou T, Takanezawa S, Ninomiya H, Watanabe T, Yamamoto S, Hiasa Y, Imamura T. Tissue Intrinsic Fluorescence Spectra-Based Digital Pathology of Liver Fibrosis by Marker-Controlled Segmentation. Front Med (Lausanne) 2018;5:350. [PMID: 30619861 DOI: 10.3389/fmed.2018.00350] [Reference Citation Analysis]