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For: Ko J, Bhagwat N, Yee SS, Ortiz N, Sahmoud A, Black T, Aiello NM, McKenzie L, O'Hara M, Redlinger C, Romeo J, Carpenter EL, Stanger BZ, Issadore D. Combining Machine Learning and Nanofluidic Technology To Diagnose Pancreatic Cancer Using Exosomes. ACS Nano. 2017;11:11182-11193. [PMID: 29019651 DOI: 10.1021/acsnano.7b05503] [Cited by in Crossref: 95] [Cited by in F6Publishing: 77] [Article Influence: 23.8] [Reference Citation Analysis]
Number Citing Articles
1 Huang G, Lin G, Zhu Y, Duan W, Jin D. Emerging technologies for profiling extracellular vesicle heterogeneity. Lab Chip 2020;20:2423-37. [PMID: 32537618 DOI: 10.1039/d0lc00431f] [Cited by in Crossref: 13] [Cited by in F6Publishing: 8] [Article Influence: 13.0] [Reference Citation Analysis]
2 Paeglis A, Strumfs B, Mezale D, Fridrihsone I. A Review on Machine Learning and Deep Learning Techniques Applied to Liquid Biopsy. In: Strumfa I, Gardovskis J, editors. Liquid Biopsy. IntechOpen; 2019. [DOI: 10.5772/intechopen.79404] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
3 Zhao Z, Zhao G, Yang S, Zhu S, Zhang S, Li P. The significance of exosomal RNAs in the development, diagnosis, and treatment of pancreatic cancer. Cancer Cell Int 2021;21:364. [PMID: 34243775 DOI: 10.1186/s12935-021-02059-8] [Reference Citation Analysis]
4 Muraoka S, Deleo AM, Sethi MK, Yukawa‐takamatsu K, Yang Z, Ko J, Hogan JD, Ruan Z, You Y, Wang Y, Medalla M, Ikezu S, Chen M, Xia W, Gorantla S, Gendelman HE, Issadore D, Zaia J, Ikezu T. Proteomic and biological profiling of extracellular vesicles from Alzheimer's disease human brain tissues. Alzheimer's & Dementia 2020;16:896-907. [DOI: 10.1002/alz.12089] [Cited by in Crossref: 27] [Cited by in F6Publishing: 14] [Article Influence: 27.0] [Reference Citation Analysis]
5 Deng L, Zhang H, Zhang Y, Luo S, Du Z, Lin Q, Zhang Z, Zhang L. An exosome-mimicking membrane hybrid nanoplatform for targeted treatment toward Kras-mutant pancreatic carcinoma. Biomater Sci 2021;9:5599-611. [PMID: 34250995 DOI: 10.1039/d1bm00446h] [Reference Citation Analysis]
6 Zhang X, Chen Z, Zuo X. Chloroauric Acid/Silver Nanoparticle Colorimetric Sensors for Antioxidant Discrimination Based on a Honeycomb Ag-Au Nanostructure. ACS Sustainable Chem Eng 2020;8:3922-8. [DOI: 10.1021/acssuschemeng.9b07523] [Cited by in Crossref: 9] [Cited by in F6Publishing: 3] [Article Influence: 9.0] [Reference Citation Analysis]
7 Nyberg KD, Bruce SL, Nguyen AV, Chan CK, Gill NK, Kim TH, Sloan EK, Rowat AC. Predicting cancer cell invasion by single-cell physical phenotyping. Integr Biol (Camb) 2018;10:218-31. [PMID: 29589844 DOI: 10.1039/c7ib00222j] [Cited by in Crossref: 18] [Cited by in F6Publishing: 9] [Article Influence: 9.0] [Reference Citation Analysis]
8 Lin X, Huang X, Zhu Y, Urmann K, Xie X, Hoffmann MR. Asymmetric Membrane for Digital Detection of Single Bacteria in Milliliters of Complex Water Samples. ACS Nano 2018;12:10281-90. [PMID: 30211534 DOI: 10.1021/acsnano.8b05384] [Cited by in Crossref: 18] [Cited by in F6Publishing: 10] [Article Influence: 6.0] [Reference Citation Analysis]
9 Kamyabi N, Bernard V, Maitra A. Liquid biopsies in pancreatic cancer. Expert Rev Anticancer Ther 2019;19:869-78. [PMID: 31533487 DOI: 10.1080/14737140.2019.1670063] [Cited by in Crossref: 7] [Cited by in F6Publishing: 6] [Article Influence: 3.5] [Reference Citation Analysis]
10 Lu J, Pang J, Chen Y, Dong Q, Sheng J, Luo Y, Lu Y, Lin B, Liu T. Application of Microfluidic Chips in Separation and Analysis of Extracellular Vesicles in Liquid Biopsy for Cancer. Micromachines (Basel) 2019;10:E390. [PMID: 31212643 DOI: 10.3390/mi10060390] [Cited by in Crossref: 6] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
11 Zhao Z, Fan J, Hsu YS, Lyon CJ, Ning B, Hu TY. Extracellular vesicles as cancer liquid biopsies: from discovery, validation, to clinical application. Lab Chip 2019;19:1114-40. [PMID: 30882822 DOI: 10.1039/c8lc01123k] [Cited by in Crossref: 36] [Cited by in F6Publishing: 21] [Article Influence: 18.0] [Reference Citation Analysis]
12 Tian Y, Ma L, Gong M, Su G, Zhu S, Zhang W, Wang S, Li Z, Chen C, Li L, Wu L, Yan X. Protein Profiling and Sizing of Extracellular Vesicles from Colorectal Cancer Patients via Flow Cytometry. ACS Nano 2018;12:671-80. [PMID: 29300458 DOI: 10.1021/acsnano.7b07782] [Cited by in Crossref: 142] [Cited by in F6Publishing: 116] [Article Influence: 47.3] [Reference Citation Analysis]
13 Lin B, Lei Y, Wang J, Zhu L, Wu Y, Zhang H, Wu L, Zhang P, Yang C. Microfluidic‐Based Exosome Analysis for Liquid Biopsy. Small Methods 2021;5:2001131. [DOI: 10.1002/smtd.202001131] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
14 Riordon J, Sovilj D, Sanner S, Sinton D, Young EW. Deep Learning with Microfluidics for Biotechnology. Trends in Biotechnology 2019;37:310-24. [DOI: 10.1016/j.tibtech.2018.08.005] [Cited by in Crossref: 70] [Cited by in F6Publishing: 48] [Article Influence: 35.0] [Reference Citation Analysis]
15 Wang X, Qin L, Zhou M, Lou Z, Wei H. Nanozyme Sensor Arrays for Detecting Versatile Analytes from Small Molecules to Proteins and Cells. Anal Chem 2018;90:11696-702. [PMID: 30175585 DOI: 10.1021/acs.analchem.8b03374] [Cited by in Crossref: 70] [Cited by in F6Publishing: 51] [Article Influence: 23.3] [Reference Citation Analysis]
16 Chu C, Wei S, Wang Y, Wang Y, Man Y, Qu Y. Extracellular vesicle and mesenchymal stem cells in bone regeneration: recent progress and perspectives. J Biomed Mater Res A. 2019;107:243-250. [PMID: 30378760 DOI: 10.1002/jbm.a.36518] [Cited by in Crossref: 20] [Cited by in F6Publishing: 19] [Article Influence: 6.7] [Reference Citation Analysis]
17 Zhang M, Jin K, Gao L, Zhang Z, Li F, Zhou F, Zhang L. Methods and Technologies for Exosome Isolation and Characterization. Small Methods 2018;2:1800021. [DOI: 10.1002/smtd.201800021] [Cited by in Crossref: 36] [Cited by in F6Publishing: 15] [Article Influence: 12.0] [Reference Citation Analysis]
18 Lim CZJ, Natalia A, Sundah NR, Shao H. Biomarker Organization in Circulating Extracellular Vesicles: New Applications in Detecting Neurodegenerative Diseases. Adv Biosyst 2020;4:e1900309. [PMID: 32597034 DOI: 10.1002/adbi.201900309] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 4.0] [Reference Citation Analysis]
19 Qin Z, Xu Q, Hu H, Yu L, Zeng S. Extracellular Vesicles in Renal Cell Carcinoma: Multifaceted Roles and Potential Applications Identified by Experimental and Computational Methods. Front Oncol 2020;10:724. [PMID: 32457844 DOI: 10.3389/fonc.2020.00724] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
20 Wang C, Senapati S, Chang HC. Liquid biopsy technologies based on membrane microfluidics: High-yield purification and selective quantification of biomarkers in nanocarriers. Electrophoresis 2020;41:1878-92. [PMID: 32180242 DOI: 10.1002/elps.202000015] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
21 Zhou S, Yang Y, Wu Y, Liu S. Review: Multiplexed profiling of biomarkers in extracellular vesicles for cancer diagnosis and therapy monitoring. Anal Chim Acta 2021;1175:338633. [PMID: 34330441 DOI: 10.1016/j.aca.2021.338633] [Reference Citation Analysis]
22 Wang W, Luo J, Wang S. Recent Progress in Isolation and Detection of Extracellular Vesicles for Cancer Diagnostics. Adv Healthcare Mater 2018;7:1800484. [DOI: 10.1002/adhm.201800484] [Cited by in Crossref: 48] [Cited by in F6Publishing: 47] [Article Influence: 16.0] [Reference Citation Analysis]
23 Yadavali S, Lee D, Issadore D. Robust Microfabrication of Highly Parallelized Three-Dimensional Microfluidics on Silicon. Sci Rep 2019;9:12213. [PMID: 31434933 DOI: 10.1038/s41598-019-48515-4] [Cited by in Crossref: 12] [Cited by in F6Publishing: 5] [Article Influence: 6.0] [Reference Citation Analysis]
24 Meng Y, Asghari M, Aslan MK, Yilmaz A, Mateescu B, Stavrakis S, deMello AJ. Microfluidics for extracellular vesicle separation and mimetic synthesis: Recent advances and future perspectives. Chemical Engineering Journal 2021;404:126110. [DOI: 10.1016/j.cej.2020.126110] [Cited by in Crossref: 6] [Cited by in F6Publishing: 1] [Article Influence: 6.0] [Reference Citation Analysis]
25 Peng F, Jeong S, Gonzalez G, Marks H, Ho A, Roussakis E, Krauledat PB, Hansen P, Evans CL. Assessment of Glial Fibrillary Acidic Protein Binding to the Surface of Leukocytes with Dark‐Field Imaging and Computational Analysis. Adv Funct Mater 2021;31:2009229. [DOI: 10.1002/adfm.202009229] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 3.0] [Reference Citation Analysis]
26 Lucien F, Lac V, Billadeau DD, Borgida A, Gallinger S, Leong HS. Glypican-1 and glycoprotein 2 bearing extracellular vesicles do not discern pancreatic cancer from benign pancreatic diseases. Oncotarget 2019;10:1045-55. [PMID: 30800217 DOI: 10.18632/oncotarget.26620] [Cited by in Crossref: 16] [Cited by in F6Publishing: 13] [Article Influence: 8.0] [Reference Citation Analysis]
27 Woo HK, Park J, Ku JY, Lee CH, Sunkara V, Ha HK, Cho YK. Urine-based liquid biopsy: non-invasive and sensitive AR-V7 detection in urinary EVs from patients with prostate cancer. Lab Chip 2018;19:87-97. [PMID: 30500003 DOI: 10.1039/c8lc01185k] [Cited by in Crossref: 26] [Cited by in F6Publishing: 15] [Article Influence: 13.0] [Reference Citation Analysis]
28 Nicoliche CYN, de Oliveira RAG, da Silva GS, Ferreira LF, Rodrigues IL, Faria RC, Fazzio A, Carrilho E, de Pontes LG, Schleder GR, Lima RS. Converging Multidimensional Sensor and Machine Learning Toward High-Throughput and Biorecognition Element-Free Multidetermination of Extracellular Vesicle Biomarkers. ACS Sens 2020;5:1864-71. [DOI: 10.1021/acssensors.0c00599] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 5.0] [Reference Citation Analysis]
29 Beard K, Meaney DF, Issadore D. Clinical Applications of Extracellular Vesicles in the Diagnosis and Treatment of Traumatic Brain Injury. J Neurotrauma 2020;37:2045-56. [PMID: 32312151 DOI: 10.1089/neu.2020.6990] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
30 Li TD, Zhang R, Chen H, Huang ZP, Ye X, Wang H, Deng AM, Kong JL. An ultrasensitive polydopamine bi-functionalized SERS immunoassay for exosome-based diagnosis and classification of pancreatic cancer. Chem Sci 2018;9:5372-82. [PMID: 30009009 DOI: 10.1039/c8sc01611a] [Cited by in Crossref: 86] [Cited by in F6Publishing: 21] [Article Influence: 28.7] [Reference Citation Analysis]
31 Phillips W, Willms E, Hill AF. Understanding extracellular vesicle and nanoparticle heterogeneity: Novel methods and considerations. Proteomics 2021;21:e2000118. [PMID: 33857352 DOI: 10.1002/pmic.202000118] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
32 Lee SH, Park SM, Kim BN, Kwon OS, Rho WY, Jun BH. Emerging ultrafast nucleic acid amplification technologies for next-generation molecular diagnostics. Biosens Bioelectron 2019;141:111448. [PMID: 31252258 DOI: 10.1016/j.bios.2019.111448] [Cited by in Crossref: 27] [Cited by in F6Publishing: 16] [Article Influence: 13.5] [Reference Citation Analysis]
33 Samandari M, Julia MG, Rice A, Chronopoulos A, del Rio Hernandez AE. Liquid biopsies for management of pancreatic cancer. Translational Research 2018;201:98-127. [DOI: 10.1016/j.trsl.2018.07.008] [Cited by in Crossref: 30] [Cited by in F6Publishing: 23] [Article Influence: 10.0] [Reference Citation Analysis]
34 Oh S, Jung SH, Seo H, Min M, Kim B, Hahn YK, Kang JH, Choi S. Magnetic activated cell sorting (MACS) pipette tip for immunomagnetic bacteria separation. Sensors and Actuators B: Chemical 2018;272:324-30. [DOI: 10.1016/j.snb.2018.05.146] [Cited by in Crossref: 15] [Cited by in F6Publishing: 7] [Article Influence: 5.0] [Reference Citation Analysis]
35 Kok VC, Yu CC. Cancer-Derived Exosomes: Their Role in Cancer Biology and Biomarker Development. Int J Nanomedicine 2020;15:8019-36. [PMID: 33116515 DOI: 10.2147/IJN.S272378] [Cited by in Crossref: 13] [Cited by in F6Publishing: 8] [Article Influence: 13.0] [Reference Citation Analysis]
36 Molinski J, Tadimety A, Burklund A, Zhang JXJ. Scalable Signature-Based Molecular Diagnostics Through On-chip Biomarker Profiling Coupled with Machine Learning. Ann Biomed Eng 2020;48:2377-99. [PMID: 32816167 DOI: 10.1007/s10439-020-02593-y] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 4.0] [Reference Citation Analysis]
37 Xiong H, Huang Z, Yang Z, Lin Q, Yang B, Fang X, Liu B, Chen H, Kong J. Recent Progress in Detection and Profiling of Cancer Cell-Derived Exosomes. Small 2021;17:e2007971. [PMID: 34075696 DOI: 10.1002/smll.202007971] [Reference Citation Analysis]
38 Atkinson SP, Andreu Z, Vicent MJ. Polymer Therapeutics: Biomarkers and New Approaches for Personalized Cancer Treatment. J Pers Med 2018;8:E6. [PMID: 29360800 DOI: 10.3390/jpm8010006] [Cited by in Crossref: 15] [Cited by in F6Publishing: 11] [Article Influence: 5.0] [Reference Citation Analysis]
39 Kim CJ, Dong L, Amend SR, Cho YK, Pienta KJ. The role of liquid biopsies in prostate cancer management. Lab Chip 2021. [PMID: 34346466 DOI: 10.1039/d1lc00485a] [Reference Citation Analysis]
40 Ma S, Zhao H, Galan EA. Integrating Engineering, Automation, and Intelligence to Catalyze the Biomedical Translation of Organoids. Adv Biol (Weinh) 2021;5:e2100535. [PMID: 33984193 DOI: 10.1002/adbi.202100535] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
41 Yang Z, LaRiviere MJ, Ko J, Till JE, Christensen T, Yee SS, Black TA, Tien K, Lin A, Shen H, Bhagwat N, Herman D, Adallah A, O'Hara MH, Vollmer CM, Katona BW, Stanger BZ, Issadore D, Carpenter EL. A Multianalyte Panel Consisting of Extracellular Vesicle miRNAs and mRNAs, cfDNA, and CA19-9 Shows Utility for Diagnosis and Staging of Pancreatic Ductal Adenocarcinoma. Clin Cancer Res 2020;26:3248-58. [PMID: 32299821 DOI: 10.1158/1078-0432.CCR-19-3313] [Cited by in Crossref: 10] [Cited by in F6Publishing: 7] [Article Influence: 10.0] [Reference Citation Analysis]
42 Berger AW, Schwerdel D, Reinacher-Schick A, Uhl W, Algül H, Friess H, Janssen KP, König A, Ghadimi M, Gallmeier E, Bartsch DK, Geissler M, Staib L, Tannapfel A, Kleger A, Beutel A, Schulte LA, Kornmann M, Ettrich TJ, Seufferlein T. A Blood-Based Multi Marker Assay Supports the Differential Diagnosis of Early-Stage Pancreatic Cancer. Theranostics 2019;9:1280-7. [PMID: 30867830 DOI: 10.7150/thno.29247] [Cited by in Crossref: 18] [Cited by in F6Publishing: 18] [Article Influence: 9.0] [Reference Citation Analysis]
43 Yelleswarapu V, Buser JR, Haber M, Baron J, Inapuri E, Issadore D. Mobile platform for rapid sub-picogram-per-milliliter, multiplexed, digital droplet detection of proteins. Proc Natl Acad Sci U S A 2019;116:4489-95. [PMID: 30765530 DOI: 10.1073/pnas.1814110116] [Cited by in Crossref: 63] [Cited by in F6Publishing: 46] [Article Influence: 31.5] [Reference Citation Analysis]
44 Wang Z, Sun X, Natalia A, Tang CSL, Ang CBT, Ong CJ, Teo MCC, So JBY, Shao H. Dual-Selective Magnetic Analysis of Extracellular Vesicle Glycans. Matter 2020;2:150-66. [DOI: 10.1016/j.matt.2019.10.018] [Cited by in Crossref: 10] [Cited by in F6Publishing: 6] [Article Influence: 10.0] [Reference Citation Analysis]
45 Shen T, Huang Z, Shi C, Pu X, Xu X, Wu Z, Ding G, Cao L. Pancreatic cancer-derived exosomes induce apoptosis of T lymphocytes through the p38 MAPK-mediated endoplasmic reticulum stress. FASEB J 2020;34:8442-58. [PMID: 32350913 DOI: 10.1096/fj.201902186R] [Cited by in Crossref: 12] [Cited by in F6Publishing: 5] [Article Influence: 12.0] [Reference Citation Analysis]
46 Yang KS, Lin HY, Curley C, Welch MW, Wolpin BM, Lee H, Weissleder R, Im H, Castro CM. Bead-Based Extracellular Vesicle Analysis Using Flow Cytometry. Adv Biosyst 2020;4:e2000203. [PMID: 33103361 DOI: 10.1002/adbi.202000203] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
47 Al-Sowayan BS, Al-Shareeda AT. Nanogenomics and Artificial Intelligence: A Dynamic Duo for the Fight Against Breast Cancer. Front Mol Biosci 2021;8:651588. [PMID: 33937332 DOI: 10.3389/fmolb.2021.651588] [Reference Citation Analysis]
48 Zhou S, Fu H, Liu C, Zhu Z, Zhang J, Weng W, Kang J, Liu Q. Value of 11C-Choline PET/CT-Based Multi-Metabolic Parameter Combination in Distinguishing Early-Stage Prostate Cancer From Benign Prostate Diseases. Front Oncol 2020;10:600380. [PMID: 33598428 DOI: 10.3389/fonc.2020.600380] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
49 Wang H, He D, Wan K, Sheng X, Cheng H, Huang J, Zhou X, He X, Wang K. In situ multiplex detection of serum exosomal microRNAs using an all-in-one biosensor for breast cancer diagnosis. Analyst 2020;145:3289-96. [PMID: 32255115 DOI: 10.1039/d0an00393j] [Cited by in Crossref: 15] [Cited by in F6Publishing: 3] [Article Influence: 15.0] [Reference Citation Analysis]
50 Abhange K, Makler A, Wen Y, Ramnauth N, Mao W, Asghar W, Wan Y. Small extracellular vesicles in cancer. Bioact Mater 2021;6:3705-43. [PMID: 33898874 DOI: 10.1016/j.bioactmat.2021.03.015] [Cited by in Crossref: 3] [Article Influence: 3.0] [Reference Citation Analysis]
51 Kim H, Park S, Jeong IG, Song SH, Jeong Y, Kim CS, Lee KH. Noninvasive Precision Screening of Prostate Cancer by Urinary Multimarker Sensor and Artificial Intelligence Analysis. ACS Nano 2021;15:4054-65. [PMID: 33296173 DOI: 10.1021/acsnano.0c06946] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 4.0] [Reference Citation Analysis]
52 Ito K, Ogawa Y, Yokota K, Matsumura S, Minamisawa T, Suga K, Shiba K, Kimura Y, Hirano-Iwata A, Takamura Y, Ogino T. Host Cell Prediction of Exosomes Using Morphological Features on Solid Surfaces Analyzed by Machine Learning. J Phys Chem B 2018;122:6224-35. [PMID: 29771528 DOI: 10.1021/acs.jpcb.8b01646] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]
53 Liu C, Zhao J, Tian F, Chang J, Zhang W, Sun J. λ-DNA- and Aptamer-Mediated Sorting and Analysis of Extracellular Vesicles. J Am Chem Soc 2019;141:3817-21. [PMID: 30789261 DOI: 10.1021/jacs.9b00007] [Cited by in Crossref: 76] [Cited by in F6Publishing: 64] [Article Influence: 38.0] [Reference Citation Analysis]
54 Zhang P, Samuel G, Crow J, Godwin AK, Zeng Y. Molecular assessment of circulating exosomes toward liquid biopsy diagnosis of Ewing sarcoma family of tumors. Transl Res 2018;201:136-53. [PMID: 30031766 DOI: 10.1016/j.trsl.2018.05.007] [Cited by in Crossref: 12] [Cited by in F6Publishing: 7] [Article Influence: 4.0] [Reference Citation Analysis]
55 DeCastro J, Littig J, Chou PP, Mack-Onyeike J, Srinivasan A, Conboy MJ, Conboy IM, Aran K. The Microfluidic Toolbox for Analyzing Exosome Biomarkers of Aging. Molecules 2021;26:535. [PMID: 33498573 DOI: 10.3390/molecules26030535] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
56 Kamyabi N, Abbasgholizadeh R, Maitra A, Ardekani A, Biswal SL, Grande-Allen KJ. Isolation and mutational assessment of pancreatic cancer extracellular vesicles using a microfluidic platform. Biomed Microdevices 2020;22:23. [PMID: 32162067 DOI: 10.1007/s10544-020-00483-7] [Cited by in Crossref: 9] [Cited by in F6Publishing: 8] [Article Influence: 9.0] [Reference Citation Analysis]
57 Galan EA, Zhao H, Wang X, Dai Q, Huck WT, Ma S. Intelligent Microfluidics: The Convergence of Machine Learning and Microfluidics in Materials Science and Biomedicine. Matter 2020;3:1893-922. [DOI: 10.1016/j.matt.2020.08.034] [Cited by in Crossref: 9] [Cited by in F6Publishing: 3] [Article Influence: 9.0] [Reference Citation Analysis]
58 Xin J, Deng C, Aras O, Zhou M, Wu C, An F. Chemodynamic nanomaterials for cancer theranostics. J Nanobiotechnology 2021;19:192. [PMID: 34183023 DOI: 10.1186/s12951-021-00936-y] [Reference Citation Analysis]
59 Lin H, Xue X, Wang X, Dang S, Gu M. Application of artificial intelligence for the diagnosis, treatment, and prognosis of pancreatic cancer. AIG 2020;1:19-29. [DOI: 10.35712/aig.v1.i1.19] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
60 Sancho-Albero M, Sebastián V, Sesé J, Pazo-Cid R, Mendoza G, Arruebo M, Martín-Duque P, Santamaría J. Isolation of exosomes from whole blood by a new microfluidic device: proof of concept application in the diagnosis and monitoring of pancreatic cancer. J Nanobiotechnology 2020;18:150. [PMID: 33092584 DOI: 10.1186/s12951-020-00701-7] [Cited by in Crossref: 7] [Cited by in F6Publishing: 4] [Article Influence: 7.0] [Reference Citation Analysis]
61 Ariston Gabriel AN, Wang F, Jiao Q, Yvette U, Yang X, Al-Ameri SA, Du L, Wang YS, Wang C. The involvement of exosomes in the diagnosis and treatment of pancreatic cancer. Mol Cancer 2020;19:132. [PMID: 32854710 DOI: 10.1186/s12943-020-01245-y] [Cited by in Crossref: 7] [Cited by in F6Publishing: 6] [Article Influence: 7.0] [Reference Citation Analysis]
62 Jiang C, Wang G, Hein R, Liu N, Luo X, Davis JJ. Antifouling Strategies for Selective In Vitro and In Vivo Sensing. Chem Rev 2020;120:3852-89. [DOI: 10.1021/acs.chemrev.9b00739] [Cited by in Crossref: 83] [Cited by in F6Publishing: 43] [Article Influence: 83.0] [Reference Citation Analysis]
63 Shen T, Jia S, Ding G, Ping D, Zhou L, Zhou S, Cao L. BxPC-3-Derived Small Extracellular Vesicles Induce FOXP3+ Treg through ATM-AMPK-Sirtuins-Mediated FOXOs Nuclear Translocations. iScience 2020;23:101431. [PMID: 32798974 DOI: 10.1016/j.isci.2020.101431] [Cited by in Crossref: 5] [Cited by in F6Publishing: 3] [Article Influence: 5.0] [Reference Citation Analysis]
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65 Tian F, Liu C, Lin L, Chen Q, Sun J. Microfluidic analysis of circulating tumor cells and tumor-derived extracellular vesicles. TrAC Trends in Analytical Chemistry 2019;117:128-45. [DOI: 10.1016/j.trac.2019.05.013] [Cited by in Crossref: 22] [Cited by in F6Publishing: 8] [Article Influence: 11.0] [Reference Citation Analysis]
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