1932

Abstract

Enzymes are appealing diagnostic targets because of their centrality in human health and disease. Continuous efforts spanning several decades have yielded methods for magnetically detecting the interactions of enzymes with exogenous molecular substrates. Nevertheless, measuring enzymatic activity in vivo remains challenging due to background noise, insufficient selectivity, and overlapping enzymatic functions. Magnetic micro- and nanoagents are poised to help overcome these issues by offering possible advantages such as site-selective sampling, modular architectures, new forms of magnetic detection, and favorable biocompatibility. Here, we review relevant control and detection strategies and consider examples of magnetic enzyme detection demonstrated with micro- or nanorobotic systems. Most cases have focused on proteolytic enzymes, leaving ample opportunity to expand to other classes of enzymes. Enzyme-responsive magnetic micro- and nanoagents hold promise for lowering barriers of translation and enabling preemptive, point-of-care medical applications.

Loading

Article metrics loading...

/content/journals/10.1146/annurev-control-042920-013605
2022-05-03
2024-06-13
Loading full text...

Full text loading...

/deliver/fulltext/control/5/1/annurev-control-042920-013605.html?itemId=/content/journals/10.1146/annurev-control-042920-013605&mimeType=html&fmt=ahah

Literature Cited

  1. 1. 
    Merindol R, Walther A. 2017. Materials learning from life: concepts for active, adaptive and autonomous molecular systems. Chem. Soc. Rev. 46:5588–619
    [Google Scholar]
  2. 2. 
    Vidal M, Cusick ME, Barabási A-L. 2011. Interactome networks and human disease. Cell 144:986–98
    [Google Scholar]
  3. 3. 
    Bray D. 1995. Protein molecules as computational elements in living cells. Nature 376:307–12
    [Google Scholar]
  4. 4. 
    Soleimany AP, Bhatia SN. 2020. Activity-based diagnostics: an emerging paradigm for disease detection and monitoring. Trends Mol. Med. 26:450–68
    [Google Scholar]
  5. 5. 
    Yang C, Wang Q, Ding W 2019. Recent progress in the imaging detection of enzyme activities in vivo. RSC Adv 9:25285–302
    [Google Scholar]
  6. 6. 
    Uhlén M, Fagerberg L, Hallström BM, Lindskog C, Oksvold P et al. 2015. Tissue-based map of the human proteome. Science 347:1260419
    [Google Scholar]
  7. 7. 
    Grüning N-M, Lehrach H, Ralser M 2010. Regulatory crosstalk of the metabolic network. Trends Biochem. Sci. 35:220–27
    [Google Scholar]
  8. 8. 
    Soto F, Wang J, Ahmed R, Demirci U 2020. Medical micro/nanorobots in precision medicine. Adv. Sci. 7:2002203
    [Google Scholar]
  9. 9. 
    Wang B, Kostarelos K, Nelson BJ, Zhang L 2021. Trends in micro-/nanorobotics: materials development, actuation, localization, and system integration for biomedical applications. Adv. Mater. 33:e2002047
    [Google Scholar]
  10. 10. 
    Hu C, Pané S, Nelson BJ. 2018. Soft micro- and nanorobotics. Annu. Rev. Control Robot. Auton. Syst. 1:53–75
    [Google Scholar]
  11. 11. 
    Schmidt CK, Medina-Sánchez M, Edmondson RJ, Schmidt OG. 2020. Engineering microrobots for targeted cancer therapies from a medical perspective. Nat. Commun. 11:5618
    [Google Scholar]
  12. 12. 
    Swierczewska M, Liu G, Lee S, Chen X 2012. High-sensitivity nanosensors for biomarker detection. Chem. Soc. Rev. 41:2641–55
    [Google Scholar]
  13. 13. 
    Schomburg I, Jeske L, Ulbrich M, Placzek S, Chang A, Schomburg D 2017. The BRENDA enzyme information system—from a database to an expert system. J. Biotechnol. 261:194–206
    [Google Scholar]
  14. 14. 
    Vinogradov E, Sherry AD, Lenkinski RE. 2013. CEST: from basic principles to applications, challenges and opportunities. J. Magn. Reson. 229:155–72
    [Google Scholar]
  15. 15. 
    Rosenthal EL, Warram JM, de Boer E, Basilion JP, Biel MA et al. 2016. Successful translation of fluorescence navigation during oncologic surgery: a consensus report. J. Nucl. Med. 57:144–50
    [Google Scholar]
  16. 16. 
    Tringale KR, Pang J, Nguyen QT. 2018. Image-guided surgery in cancer: a strategy to reduce incidence of positive surgical margins. Wiley Interdiscip. Rev. Syst. Biol. Med. 10:e1412
    [Google Scholar]
  17. 17. 
    Widen JC, Tholen M, Yim JJ, Antaris A, Casey KM et al. 2021. AND-gate contrast agents for enhanced fluorescence-guided surgery. Nat. Biomed. Eng. 5:264–77
    [Google Scholar]
  18. 18. 
    Ofori LO, Withana NP, Prestwood TR, Verdoes M, Brady JJ et al. 2015. Design of protease activated optical contrast agents that exploit a latent lysosomotropic effect for use in fluorescence-guided surgery. ACS Chem. Biol. 10:1977–88
    [Google Scholar]
  19. 19. 
    Wadas TJ, Wong EH, Weisman GR, Anderson CJ. 2010. Coordinating radiometals of copper, gallium, indium, yttrium, and zirconium for PET and SPECT imaging of disease. Chem. Rev. 110:2858–2902
    [Google Scholar]
  20. 20. 
    Brown RW, Cheng Y-CN, Haacke EM, Thompson MR, Venkatesan R. 2014. Magnetic Resonance Imaging: Physical Principles and Sequence Design Hoboken, NJ: Wiley & Sons
    [Google Scholar]
  21. 21. 
    Vlaardingerbroek MT, den Boer JA. 1999. Magnetic Resonance Imaging: Theory and Practice Berlin: Springer
    [Google Scholar]
  22. 22. 
    Hingorani DV, Yoo B, Bernstein AS, Pagel MD. 2014. Detecting enzyme activities with exogenous MRI contrast agents. Chemistry 20:9840–50
    [Google Scholar]
  23. 23. 
    Ou Y, Wilson RE, Weber SG 2018. Methods of measuring enzyme activity ex vivo and in vivo. Annu. Rev. Anal. Chem. 11:509–33
    [Google Scholar]
  24. 24. 
    Alger JR, Shulman RG. 1984. NMR studies of enzymatic rates in vitro and in vivo by magnetization transfer. Q. Rev. Biophys. 17:83–124
    [Google Scholar]
  25. 25. 
    Shoubridge EA, Briggs RW, Radda GK. 1982. 31P NMR saturation transfer measurements of the steady state rates of creatine kinase and ATP synthetase in the rat brain. FEBS Lett. 140:289–92
    [Google Scholar]
  26. 26. 
    Yoo B, Pagel MD. 2006. A PARACEST MRI contrast agent to detect enzyme activity. J. Am. Chem. Soc. 128:14032–33
    [Google Scholar]
  27. 27. 
    Slack CC, Finbloom JA, Jeong K, Bruns CJ, Wemmer DE et al. 2017. Rotaxane probes for protease detection by 129Xe hyperCEST NMR. Chem. Commun. 53:1076–79
    [Google Scholar]
  28. 28. 
    Rogosnitzky M, Branch S. 2016. Gadolinium-based contrast agent toxicity: a review of known and proposed mechanisms. Biometals 29:365–76
    [Google Scholar]
  29. 29. 
    Moats RA, Fraser SE, Meade TJ 1997. A “smart” magnetic resonance imaging agent that reports on specific enzymatic activity. Angew. Chem. Int. Ed. 36:726–28
    [Google Scholar]
  30. 30. 
    Louie AY, Hüber MM, Ahrens ET, Rothbächer U, Moats R et al. 2000. In vivo visualization of gene expression using magnetic resonance imaging. Nat. Biotechnol. 18:321–25
    [Google Scholar]
  31. 31. 
    Yu J-X, Kodibagkar VD, Liu L, Mason RP. 2008. A 19F-NMR approach using reporter molecule pairs to assess β-galactosidase in human xenograft tumors in vivo. NMR Biomed. 21:704–12
    [Google Scholar]
  32. 32. 
    Allouche-Arnon H, Hovav Y, Friesen-Waldner L, Sosna J, Moshe Gomori J et al. 2014. Quantification of rate constants for successive enzymatic reactions with DNP hyperpolarized MR. NMR Biomed 27:656–62
    [Google Scholar]
  33. 33. 
    Mizukami S, Takikawa R, Sugihara F, Hori Y, Tochio H et al. 2008. Paramagnetic relaxation-based 19F MRI probe to detect protease activity. J. Am. Chem. Soc. 130:794–95
    [Google Scholar]
  34. 34. 
    Sanzhaeva U, Xu X, Guggilapu P, Tseytlin M, Khramtsov VV, Driesschaert B. 2018. Imaging of enzyme activity by electron paramagnetic resonance: concept and experiment using a paramagnetic substrate of alkaline phosphatase. Angew. Chem. Int. Ed. 57:11701–5
    [Google Scholar]
  35. 35. 
    Audran G, Jacoutot S, Jugniot N, Marque SRA, Mellet P. 2019. Shifting-nitroxides to investigate enzymatic hydrolysis of fatty acids by lipases using electron paramagnetic resonance in turbid media. Anal. Chem. 91:5504–7
    [Google Scholar]
  36. 36. 
    Koonjoo N, Parzy E, Massot P, Lepetit-Coiffé M, Marque SRA et al. 2014. In vivo Overhauser-enhanced MRI of proteolytic activity. Contrast Media Mol. Imaging 9:363–71
    [Google Scholar]
  37. 37. 
    Palagi S, Fischer P. 2018. Bioinspired microrobots. Nat. Rev. Mater. 3:113–24
    [Google Scholar]
  38. 38. 
    Ceylan H, Giltinan J, Kozielski K, Sitti M. 2017. Mobile microrobots for bioengineering applications. Lab Chip 17:1705–24
    [Google Scholar]
  39. 39. 
    Yang L, Zhang L 2021. Motion control in magnetic microrobotics: from individual and multiple robots to swarms. Annu. Rev. Control Robot. Auton. Syst. 4:509–34
    [Google Scholar]
  40. 40. 
    Nelson BJ, Kaliakatsos IK, Abbott JJ. 2010. Microrobots for minimally invasive medicine. Annu. Rev. Biomed. Eng. 12:55–85
    [Google Scholar]
  41. 41. 
    Greiner W 1998. Faraday's law of induction. Classical Electrodynamics W Greiner 237–49 New York: Springer
    [Google Scholar]
  42. 42. 
    Guanying M, Guozheng Y, Xiu H. 2007. Power transmission for gastrointestinal microsystems using inductive coupling. Physiol. Meas. 28:N9–18
    [Google Scholar]
  43. 43. 
    Lum KY, Chow J-S, Yiauw KH. 2020. Wireless power transfer framework for minirobot based on resonant inductive coupling and impedance matching. Int. J. Power Electron. Drive Syst. 11:317–25
    [Google Scholar]
  44. 44. 
    Purcell EM. 1977. Life at low Reynolds number. Am. J. Phys. 45:3–11
    [Google Scholar]
  45. 45. 
    Peyer KE, Zhang L, Nelson BJ. 2013. Bio-inspired magnetic swimming microrobots for biomedical applications. Nanoscale 5:1259–72
    [Google Scholar]
  46. 46. 
    Zhang L, Abbott JJ, Dong L, Peyer KE, Kratochvil BE et al. 2009. Characterizing the swimming properties of artificial bacterial flagella. Nano Lett 9:3663–67
    [Google Scholar]
  47. 47. 
    Ghosh A, Fischer P. 2009. Controlled propulsion of artificial magnetic nanostructured propellers. Nano Lett 9:2243–45
    [Google Scholar]
  48. 48. 
    Alouges F, DeSimone A, Giraldi L, Zoppello M. 2015. Can magnetic multilayers propel artificial microswimmers mimicking sperm cells?. Soft Robot 2:117–28
    [Google Scholar]
  49. 49. 
    Cicconofri G, DeSimone A. 2016. Motion planning and motility maps for flagellar microswimmers. Eur. Phys. J. E 39:72
    [Google Scholar]
  50. 50. 
    Schuerle S, Soleimany AP, Yeh T, Anand GM, Häberli M et al. 2019. Synthetic and living micropropellers for convection-enhanced nanoparticle transport. Sci. Adv. 5:eaav4803
    [Google Scholar]
  51. 51. 
    Vollmers K, Frutiger DR, Kratochvil BE, Nelson BJ. 2008. Wireless resonant magnetic microactuator for untethered mobile microrobots. Appl. Phys. Lett. 92:144103
    [Google Scholar]
  52. 52. 
    Frutiger DR, Vollmers K, Kratochvil BE, Nelson BJ. 2010. Small, fast, and under control: wireless resonant magnetic micro-agents. Int. J. Robot. Res. 29:613–36
    [Google Scholar]
  53. 53. 
    Tung H-W, Frutiger DR, Pané S, Nelson BJ. 2012. Polymer-based wireless resonant magnetic microrobots. IEEE Trans. Robot. 30:26–32
    [Google Scholar]
  54. 54. 
    Kadiri VM, Günther J-P, Kottapalli SN, Goyal R, Peter F et al. 2021. Light- and magnetically actuated FePt microswimmers. Eur. Phys. J. E 44:74
    [Google Scholar]
  55. 55. 
    Ullrich F, Bergeles C, Pokki J, Ergeneman O, Erni S et al. 2013. Mobility experiments with microrobots for minimally invasive intraocular surgery. Investig. Ophthalmol. Vis. Sci. 54:2853–63
    [Google Scholar]
  56. 56. 
    Servant A, Qiu F, Mazza M, Kostarelos K, Nelson BJ 2015. Controlled in vivo swimming of a swarm of bacteria-like microrobotic flagella. Adv. Mater. 27:2981–88
    [Google Scholar]
  57. 57. 
    Blanco E, Shen H, Ferrari M. 2015. Principles of nanoparticle design for overcoming biological barriers to drug delivery. Nat. Biotechnol. 33:941–51
    [Google Scholar]
  58. 58. 
    Da Silva-Candal A, Brown T, Krishnan V, Lopez-Loureiro I, Ávila-Gómez P et al. 2019. Shape effect in active targeting of nanoparticles to inflamed cerebral endothelium under static and flow conditions. J. Control. Release 309:94–105
    [Google Scholar]
  59. 59. 
    Mitchell MJ, Billingsley MM, Haley RM, Wechsler ME, Peppas NA, Langer R. 2021. Engineering precision nanoparticles for drug delivery. Nat. Rev. Drug Discov. 20:101–24
    [Google Scholar]
  60. 60. 
    Choi HS, Liu W, Misra P, Tanaka E, Zimmer JP et al. 2007. Renal clearance of quantum dots. Nat. Biotechnol. 25:1165–70
    [Google Scholar]
  61. 61. 
    Lu Y, Gu Z. 2017. Kidney physiology: a size bandpass filter. Nat. Nanotechnol. 12:1023–25
    [Google Scholar]
  62. 62. 
    Sykes EA, Dai Q, Sarsons CD, Chen J, Rocheleau JV et al. 2016. Tailoring nanoparticle designs to target cancer based on tumor pathophysiology. PNAS 113:E1142–51
    [Google Scholar]
  63. 63. 
    Perry JL, Reuter KG, Luft JC, Pecot CV, Zamboni W, DeSimone JM. 2017. Mediating passive tumor accumulation through particle size, tumor type, and location. Nano Lett 17:2879–86
    [Google Scholar]
  64. 64. 
    Yu W, Liu R, Zhou Y, Gao H. 2020. Size-tunable strategies for a tumor targeted drug delivery system. ACS Cent. Sci. 6:100–16
    [Google Scholar]
  65. 65. 
    Wong C, Stylianopoulos T, Cui J, Martin J, Chauhan VP et al. 2011. Multistage nanoparticle delivery system for deep penetration into tumor tissue. PNAS 108:2426–31
    [Google Scholar]
  66. 66. 
    Yamankurt G, Berns EJ, Xue A, Lee A, Bagheri N et al. 2019. Exploration of the nanomedicine-design space with high-throughput screening and machine learning. Nat. Biomed. Eng. 3:318–27
    [Google Scholar]
  67. 67. 
    Hauert S, Bhatia SN. 2014. Mechanisms of cooperation in cancer nanomedicine: towards systems nanotechnology. Trends Biotechnol 32:448–55
    [Google Scholar]
  68. 68. 
    Wilhelm S, Tavares AJ, Dai Q, Ohta S, Audet J et al. 2016. Analysis of nanoparticle delivery to tumours. Nat. Rev. Mater. 1:16014
    [Google Scholar]
  69. 69. 
    Hughes MP, Morgan H. 1999. Measurement of bacterial flagellar thrust by negative dielectrophoresis. Biotechnol. Prog. 15:245–49
    [Google Scholar]
  70. 70. 
    Lighthill J. 1976. Flagellar hydrodynamics. SIAM Rev. 18:161–230
    [Google Scholar]
  71. 71. 
    Riglar DT, Silver PA. 2018. Engineering bacteria for diagnostic and therapeutic applications. Nat. Rev. Microbiol. 16:214–25
    [Google Scholar]
  72. 72. 
    Forbes NS. 2010. Engineering the perfect (bacterial) cancer therapy. Nat. Rev. Cancer 10:785–94
    [Google Scholar]
  73. 73. 
    Clairmont C, Lee KC, Pike J, Ittensohn M, Low KB et al. 2000. Biodistribution and genetic stability of the novel antitumor agent VNP20009, a genetically modified strain of Salmonella typhimuvium. J. Infect. Dis. 181:1996–2002
    [Google Scholar]
  74. 74. 
    Taylor BL, Zhulin IB, Johnson MS. 1999. Aerotaxis and other energy-sensing behavior in bacteria. Annu. Rev. Microbiol. 53:103–28
    [Google Scholar]
  75. 75. 
    Mishler DM, Topp S, Reynoso CMK, Gallivan JP. 2010. Engineering bacteria to recognize and follow small molecules. Curr. Opin. Biotechnol. 21:653–56
    [Google Scholar]
  76. 76. 
    Duong MT-Q, Qin Y, You S-H, Min J-J. 2019. Bacteria-cancer interactions: bacteria-based cancer therapy. Exp. Mol. Med. 51:152
    [Google Scholar]
  77. 77. 
    Felfoul O, Mohammadi M, Taherkhani S, de Lanauze D, Zhong Xu Y et al. 2016. Magneto-aerotactic bacteria deliver drug-containing nanoliposomes to tumour hypoxic regions. Nat. Nanotechnol. 11:941–47
    [Google Scholar]
  78. 78. 
    Alapan Y, Yasa O, Yigit B, Yasa IC, Erkoc P, Sitti M. 2019. Microrobotics and microorganisms: biohybrid autonomous cellular robots. Annu. Rev. Control Robot. Auton. Syst. 2:205–30
    [Google Scholar]
  79. 79. 
    Adem S, Jain S, Sveiven M, Zhou X, O'Donoghue AJ, Hall DA. 2020. Giant magnetoresistive biosensors for real-time quantitative detection of protease activity. Sci. Rep. 10:7941
    [Google Scholar]
  80. 80. 
    Murzin D, Mapps DJ, Levada K, Belyaev V, Omelyanchik A et al. 2020. Ultrasensitive magnetic field sensors for biomedical applications. Sensors 20:1569
    [Google Scholar]
  81. 81. 
    Chemla YR, Grossman HL, Poon Y, McDermott R, Stevens R et al. 2000. Ultrasensitive magnetic biosensor for homogeneous immunoassay. PNAS 97:14268–72
    [Google Scholar]
  82. 82. 
    Chieh JJ, Yang S-Y, Horng H-E, Yu CY, Lee CL et al. 2010. Immunomagnetic reduction assay using high-Tc superconducting-quantum-interference-device-based magnetosusceptometry. J. Appl. Phys. 107:074903
    [Google Scholar]
  83. 83. 
    Chieh JJ, Yang SY, Jian ZF, Wang WC, Horng HE et al. 2008. Hyper-high-sensitivity wash-free magnetoreduction assay on biomolecules using high-Tc superconducting quantum interference devices. J. Appl. Phys. 103:014703
    [Google Scholar]
  84. 84. 
    Gamarra LF, daCosta-Filho AJ, Mamani JB, de Cassia Ruiz R, Pavon LF et al. 2010. Ferromagnetic resonance for the quantification of superparamagnetic iron oxide nanoparticles in biological materials. Int. J. Nanomed. 5:203–11
    [Google Scholar]
  85. 85. 
    Salvador M, Gallo-Cordova Á, Moyano A, Martínez-García JC, Blanco-López MC et al. 2020. Improved magnetic lateral flow assays with optimized nanotags for point-of-use inductive biosensing. Analyst 145:5905–14
    [Google Scholar]
  86. 86. 
    Perez JM, Simeone FJ, Tsourkas A, Josephson L, Weissleder R 2004. Peroxidase substrate nanosensors for MR imaging. Nano Lett 4:119–22
    [Google Scholar]
  87. 87. 
    Perez JM, Grimm J, Josephson L, Weissleder R 2008. Integrated nanosensors to determine levels and functional activity of human telomerase. Neoplasia 10:1066–72
    [Google Scholar]
  88. 88. 
    Zhao M, Josephson L, Tang Y, Weissleder R. 2003. Magnetic sensors for protease assays. Angew. Chem. Int. Ed. 42:1375–78
    [Google Scholar]
  89. 89. 
    Hergt R, Dutz S. 2007. Magnetic particle hyperthermia—biophysical limitations of a visionary tumour therapy. J. Magn. Magn. Mater. 311:187–92
    [Google Scholar]
  90. 90. 
    Saritas EU, Goodwill PW, Conolly SM. 2015. Effects of pulse duration on magnetostimulation thresholds. Med. Phys. 42:3005–12
    [Google Scholar]
  91. 91. 
    Kiessling F, Mertens ME, Grimm J, Lammers T. 2014. Nanoparticles for imaging: top or flop?. Radiology 273:10–28
    [Google Scholar]
  92. 92. 
    Lee N, Yoo D, Ling D, Cho MH, Hyeon T, Cheon J 2015. Iron oxide based nanoparticles for multimodal imaging and magnetoresponsive therapy. Chem. Rev. 115:10637–89
    [Google Scholar]
  93. 93. 
    Slack H. 1949. Intravenous treatment of anæmia with an iron-sucrose preparation. Lancet 253:11–14
    [Google Scholar]
  94. 94. 
    Lartigue L, Alloyeau D, Kolosnjaj-Tabi J, Javed Y, Guardia P et al. 2013. Biodegradation of iron oxide nanocubes: high-resolution in situ monitoring. ACS Nano 7:3939–52
    [Google Scholar]
  95. 95. 
    Gilder SA, Wack M, Kaub L, Roud SC, Petersen N et al. 2018. Distribution of magnetic remanence carriers in the human brain. Sci. Rep. 8:11363
    [Google Scholar]
  96. 96. 
    Kirschvink JL, Kobayashi-Kirschvink A, Woodford BJ. 1992. Magnetite biomineralization in the human brain. PNAS 89:7683–87
    [Google Scholar]
  97. 97. 
    Fubini B, Fenoglio I, Tomatis M, Turci F 2011. Effect of chemical composition and state of the surface on the toxic response to high aspect ratio nanomaterials. Nanomedicine 6:899–920
    [Google Scholar]
  98. 98. 
    Wetterskog E, Tai C-W, Grins J, Bergström L, Salazar-Alvarez G. 2013. Anomalous magnetic properties of nanoparticles arising from defect structures: topotaxial oxidation of Fe1–xO|Fe3–δO4 core|shell nanocubes to single-phase particles. ACS Nano 7:7132–44
    [Google Scholar]
  99. 99. 
    Redl FX, Black CT, Papaefthymiou GC, Sandstrom RL, Yin M et al. 2004. Magnetic, electronic, and structural characterization of nonstoichiometric iron oxides at the nanoscale. J. Am. Chem. Soc. 126:14583–99
    [Google Scholar]
  100. 100. 
    Almeida TP, Muxworthy AR, Kovács A, Williams W, Brown PD, Dunin-Borkowski RE. 2016. Direct visualization of the thermomagnetic behavior of pseudo-single-domain magnetite particles. Sci. Adv 2:e1501801
    [Google Scholar]
  101. 101. 
    Matsumoto Y, Jasanoff A. 2008. T2 relaxation induced by clusters of superparamagnetic nanoparticles: Monte Carlo simulations. Magn. Reson. Imaging 26:994–98
    [Google Scholar]
  102. 102. 
    Lee H, Sun E, Ham D, Weissleder R 2008. Chip-NMR biosensor for detection and molecular analysis of cells. Nat. Med. 14:869–74
    [Google Scholar]
  103. 103. 
    Wang Y-XJ. 2015. Current status of superparamagnetic iron oxide contrast agents for liver magnetic resonance imaging. World J. Gastroenterol. 21:13400–2
    [Google Scholar]
  104. 104. 
    Jeon M, Halbert MV, Stephen ZR, Zhang M. 2021. Iron oxide nanoparticles as T1 contrast agents for magnetic resonance imaging: fundamentals, challenges, applications, and prospectives. Adv. Mater. 33:e1906539
    [Google Scholar]
  105. 105. 
    Kim BH, Lee N, Kim H, An K, Park YI et al. 2011. Large-scale synthesis of uniform and extremely small-sized iron oxide nanoparticles for high-resolution T1 magnetic resonance imaging contrast agents. J. Am. Chem. Soc. 133:12624–31
    [Google Scholar]
  106. 106. 
    Lu J, Sun J, Li F, Wang J, Liu J et al. 2018. Highly sensitive diagnosis of small hepatocellular carcinoma using pH-responsive iron oxide nanocluster assemblies. J. Am. Chem. Soc. 140:10071–74
    [Google Scholar]
  107. 107. 
    Zabow G, Dodd SJ, Koretsky AP. 2015. Shape-changing magnetic assemblies as high-sensitivity NMR-readable nanoprobes. Nature 520:73–77
    [Google Scholar]
  108. 108. 
    Dieckhoff J, Lak A, Schilling M, Ludwig F. 2014. Protein detection with magnetic nanoparticles in a rotating magnetic field. J. Appl. Phys. 115:024701
    [Google Scholar]
  109. 109. 
    Wu K, Su D, Saha R, Wong D, Wang J-P. 2019. Magnetic particle spectroscopy-based bioassays: methods, applications, advances, and future opportunities. J. Phys. D 52:173001
    [Google Scholar]
  110. 110. 
    Shasha C, Krishnan KM. 2021. Nonequilibrium dynamics of magnetic nanoparticles with applications in biomedicine. Adv. Mater. 33:e1904131
    [Google Scholar]
  111. 111. 
    Wu K, Su D, Saha R, Liu J, Wang J-P. 2019. Investigating the effect of magnetic dipole-dipole interaction on magnetic particle spectroscopy: implications for magnetic nanoparticle-based bioassays and magnetic particle imaging. J. Phys. D 52:335002
    [Google Scholar]
  112. 112. 
    Biederer S, Knopp T, Sattel TF, Lüdtke-Buzug K, Gleich B et al. 2009. Magnetization response spectroscopy of superparamagnetic nanoparticles for magnetic particle imaging. J. Phys. D 42:205007
    [Google Scholar]
  113. 113. 
    Gandhi S, Arami H, Krishnan KM. 2016. Detection of cancer-specific proteases using magnetic relaxation of peptide-conjugated nanoparticles in biological environment. Nano Lett 16:3668–74
    [Google Scholar]
  114. 114. 
    Chung S-H, Hoffmann A, Guslienko K, Bader SD, Liu C et al. 2005. Biological sensing with magnetic nanoparticles using Brownian relaxation (invited). J. Appl. Phys. 97:10R101
    [Google Scholar]
  115. 115. 
    Wu K, Liu J, Su D, Saha R, Wang J-P. 2019. Magnetic nanoparticle relaxation dynamics-based magnetic particle spectroscopy for rapid and wash-free molecular sensing. ACS Appl. Mater. Interfaces 11:22979–86
    [Google Scholar]
  116. 116. 
    Astalan AP, Ahrentorp F, Johansson C, Larsson K, Krozer A 2004. Biomolecular reactions studied using changes in Brownian rotation dynamics of magnetic particles. Biosens. Bioelectron. 19:945–51
    [Google Scholar]
  117. 117. 
    Connolly J, St Pierre TG. 2001. Proposed biosensors based on time-dependent properties of magnetic fluids. J. Magn. Magn. Mater. 225:156–60
    [Google Scholar]
  118. 118. 
    Krause H-J, Wolters N, Zhang Y, Offenhäusser A, Miethe P et al. 2007. Magnetic particle detection by frequency mixing for immunoassay applications. J. Magn. Magn. Mater. 311:436–44
    [Google Scholar]
  119. 119. 
    Nikitin PI, Vetoshko PM, Ksenevich TI. 2007. New type of biosensor based on magnetic nanoparticle detection. J. Magn. Magn. Mater. 311:445–49
    [Google Scholar]
  120. 120. 
    Knopp T, Buzug TM. 2012. Magnetic Particle Imaging: An Introduction to Imaging Principles and Scanner Instrumentation Berlin: Springer
    [Google Scholar]
  121. 121. 
    Graeser M, Thieben F, Szwargulski P, Werner F, Gdaniec N et al. 2019. Human-sized magnetic particle imaging for brain applications. Nat. Commun. 10:1936
    [Google Scholar]
  122. 122. 
    Rahmer J, Stehning C, Gleich B. 2018. Remote magnetic actuation using a clinical scale system. PLOS ONE 13:e0193546
    [Google Scholar]
  123. 123. 
    Anani T, Panizzi P, David AE. 2016. Nanoparticle-based probes to enable noninvasive imaging of proteolytic activity for cancer diagnosis. Nanomedicine 11:2007–22
    [Google Scholar]
  124. 124. 
    Li F, Lu J, Kong X, Hyeon T, Ling D 2017. Dynamic nanoparticle assemblies for biomedical applications. Adv. Mater. 29:1605897
    [Google Scholar]
  125. 125. 
    Perez JM, Josephson L, O'Loughlin T, Högemann D, Weissleder R 2002. Magnetic relaxation switches capable of sensing molecular interactions. Nat. Biotechnol. 20:816–20
    [Google Scholar]
  126. 126. 
    Gallo J, Kamaly N, Lavdas I, Stevens E, Nguyen Q-D et al. 2014. CXCR4-targeted and MMP-responsive iron oxide nanoparticles for enhanced magnetic resonance imaging. Angew. Chem. Int. Ed. 53:9550–54
    [Google Scholar]
  127. 127. 
    Yuan Y, Ding Z, Qian J, Zhang J, Xu J et al. 2016. Casp3/7-instructed intracellular aggregation of Fe3O4 nanoparticles enhances T2 MR imaging of tumor apoptosis. Nano Lett 16:2686–91
    [Google Scholar]
  128. 128. 
    Husain SF, Lam RWM, Hu T, Ng MWF, Liau ZQG et al. 2019. Locating the site of neuropathic pain in vivo using MMP-12-targeted magnetic nanoparticles. Pain Res. Manag. 2019:9394715
    [Google Scholar]
  129. 129. 
    Meng T, Fan B, Li Q, Peng X, Xu J, Zhang R. 2020. Matrix metalloproteinase-initiated aggregation of melanin nanoparticles as highly efficient contrast agent for enhanced tumor accumulation and dual-modal imaging. J. Mater. Chem. B 8:9888–98
    [Google Scholar]
  130. 130. 
    Cao C-Y, Shen Y-Y, Wang J-D, Li L, Liang G-L 2013. Controlled intracellular self-assembly of gadolinium nanoparticles as smart molecular MR contrast agents. Sci. Rep. 3:1024
    [Google Scholar]
  131. 131. 
    Cao Y, Mao Z, He Y, Kuang Y, Liu M et al. 2020. Extremely small iron oxide nanoparticle-encapsulated nanogels as a glutathione-responsive T1 contrast agent for tumor-targeted magnetic resonance imaging. ACS Appl. Mater. Interfaces 12:26973–81
    [Google Scholar]
  132. 132. 
    Choi J-S, Kim S, Yoo D, Shin T-H, Kim H et al. 2017. Distance-dependent magnetic resonance tuning as a versatile MRI sensing platform for biological targets. Nat. Mater. 16:537–42
    [Google Scholar]
  133. 133. 
    Yuan Y, Ge S, Sun H, Dong X, Zhao H et al. 2015. Intracellular self-assembly and disassembly of 19F nanoparticles confer respective “off” and “on” 19F NMR/MRI signals for legumain activity detection in zebrafish. ACS Nano 9:5117–24
    [Google Scholar]
  134. 134. 
    Akazawa K, Sugihara F, Minoshima M, Mizukami S, Kikuchi K 2018. Sensing caspase-1 activity using activatable 19F MRI nanoprobes with improved turn-on kinetics. Chem. Commun. 54:11785–88
    [Google Scholar]
  135. 135. 
    Akazawa K, Sugihara F, Nakamura T, Mizukami S, Kikuchi K 2018. Highly sensitive detection of caspase-3/7 activity in living mice using enzyme-responsive 19F MRI nanoprobes. Bioconjug. Chem. 29:1720–28
    [Google Scholar]
  136. 136. 
    Harris TJ, von Maltzahn G, Lord ME, Park J-H, Agrawal A et al. 2008. Protease-triggered unveiling of bioactive nanoparticles. Small 4:1307–12
    [Google Scholar]
  137. 137. 
    Olson ES, Jiang T, Aguilera TA, Nguyen QT, Ellies LG et al. 2010. Activatable cell penetrating peptides linked to nanoparticles as dual probes for in vivo fluorescence and MR imaging of proteases. PNAS 107:4311–16
    [Google Scholar]
  138. 138. 
    Schuerle S, Dudani JS, Christiansen MG, Anikeeva P, Bhatia SN 2016. Magnetically actuated protease sensors for in vivo tumor profiling. Nano Lett 16:6303–10
    [Google Scholar]
  139. 139. 
    Ansari C, Tikhomirov GA, Hong SH, Falconer RA, Loadman PM et al. 2014. Development of novel tumor-targeted theranostic nanoparticles activated by membrane-type matrix metalloproteinases for combined cancer magnetic resonance imaging and therapy. Small 10:566–75
    [Google Scholar]
  140. 140. 
    Lee GY, Qian WP, Wang L, Wang YA, Staley CA et al. 2013. Theranostic nanoparticles with controlled release of gemcitabine for targeted therapy and MRI of pancreatic cancer. ACS Nano 7:2078–89
    [Google Scholar]
  141. 141. 
    Li E, Yang Y, Hao G, Yi X, Zhang S et al. 2018. Multifunctional magnetic mesoporous silica nanoagents for in vivo enzyme-responsive drug delivery and MR imaging. Nanotheranostics 2:233–42
    [Google Scholar]
  142. 142. 
    Yuan Y, Zhang J, Qi X, Li S, Liu G et al. 2019. Furin-mediated intracellular self-assembly of olsalazine nanoparticles for enhanced magnetic resonance imaging and tumour therapy. Nat. Mater. 18:1376–83
    [Google Scholar]
  143. 143. 
    von Maltzahn G, Harris TJ, Park J-H, Min D-H, Schmidt AJ et al. 2007. Nanoparticle self-assembly gated by logical proteolytic triggers. J. Am. Chem. Soc. 129:6064–65
    [Google Scholar]
/content/journals/10.1146/annurev-control-042920-013605
Loading
/content/journals/10.1146/annurev-control-042920-013605
Loading

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error