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Review

A Critical Review of the Use of Surfactant-Coated Nanoparticles in Nanomedicine and Food Nanotechnology

ORCID Icon, , ORCID Icon, &
Pages 3937-3999 | Published online: 09 Jun 2021

Figures & data

Figure 1 Classification of surfactants and structures of the ionic and nonionic surfactants mentioned in this review.

Figure 1 Classification of surfactants and structures of the ionic and nonionic surfactants mentioned in this review.

Figure 2 (A) Typical Illustration of surfactant-coated nanoparticles. (B) Various organic and inorganic materials used in the core of surfactant-coated nanoparticles.

Figure 2 (A) Typical Illustration of surfactant-coated nanoparticles. (B) Various organic and inorganic materials used in the core of surfactant-coated nanoparticles.

Figure 3 (A) Equations of the DLVO theory. (B) Relationship between two particles assuming the DLVO theory. (C) A typical example of potential energy presented in the DLVO theory.

Notes: (A) Data from Hamley63 and Ohshima.65
Figure 3 (A) Equations of the DLVO theory. (B) Relationship between two particles assuming the DLVO theory. (C) A typical example of potential energy presented in the DLVO theory.

Table 1 Summary of Surfactant-Coated Nanoparticles Used in the Field of Nanomedicine

Figure 4 Behavior and fate of surfactant-coated nanoparticles in the blood stream.

Notes: (A) Bare nanoparticles. (B) Poloxamer 188 coated nanoparticles. (C) Polysorbate 80 coated nanoparticles.
Figure 4 Behavior and fate of surfactant-coated nanoparticles in the blood stream.

Figure 5 Active and passive targeting of nanoparticles to the cancer cells.

Notes: (A) Normal vasculature. (B) Passive targeting in tumor vasculature. (C) Active targeting in tumor vasculature. (D) Types of active targeting ligands for nanoparticles and its considerations for optimization of their efficacy. Notes: (B, C) Adapted from Tran S, DeGiovanni P, Piel B, et al. Cancer nanomedicine: a review of recent success in drug delivery. Clin Transl Med. 2017;6(1):44. doi:10.1186/s40169-017-0175-0.153 (D) Adapted from Advanced Drug Delivery Reviews, 143, Alkilany AM, Zhu L, Weller H, et al, Ligand density on nanoparticles: a parameter with critical impact on nanomedicine, 22–36, Copyright 2019, with permission from Elsevier.158
Figure 5 Active and passive targeting of nanoparticles to the cancer cells.

Table 2 Summary of Surfactant-Coated Nanoparticles Used in the Field of Food Nanotechnology

Figure 6 The potential applications of food nanotechnology.

Notes: Data from Martirosyan.265
Figure 6 The potential applications of food nanotechnology.

Figure 7 Illustration of the relationships between diseases, free radicals, reactive oxygen species, and aging in the body, and its regulation by antioxidants from food source.

Notes: Data from Miyazawa241 and Adapted from Elsevier Books, 191, Fajardo AM, Bisoffi M, Chapter 18 - Curcumin analogs, oxidative stress, and prostate cancer, 191-202, Copyright 2014, with permission from Elsevier.267.
Figure 7 Illustration of the relationships between diseases, free radicals, reactive oxygen species, and aging in the body, and its regulation by antioxidants from food source.

Figure 8 Age-related decrease in plasma concentrations of antioxidants from food source.

Notes:Data from Mecocci .Citation268
Figure 8 Age-related decrease in plasma concentrations of antioxidants from food source.

Figure 9 The digestive stages after oral administration and the mechanisms of in vivo uptake of surfactant-coated nanoparticles through the small intestine.

Notes: (A-1) Transcellular route, through the M cells. (A-2) Transcellular route, through the enterocyte. (B) Paracellular route. (C) Persorption route. Data from these published studies Citation318 Citation295 Citation49
Figure 9 The digestive stages after oral administration and the mechanisms of in vivo uptake of surfactant-coated nanoparticles through the small intestine.

Figure 10 A wide variety of nanoscale materials potentially present in foods from both natural and artificial sources.

Notes: Data from McClements and Xiao.Citation291
Figure 10 A wide variety of nanoscale materials potentially present in foods from both natural and artificial sources.

Figure 11 Overlapping timelines of the development of artificial intelligence and nanomaterials. Since 2010, these two fields have developed a powerful synergy.

Notes: Modified from Singh AV, Rosenkranz D, Ansari MHD, etal Artificial intelligence and machine learning empower advanced biomedical material design to toxicity prediction. Advanced Intelligent Systems. 2020;2:2000084.Citation379
Figure 11 Overlapping timelines of the development of artificial intelligence and nanomaterials. Since 2010, these two fields have developed a powerful synergy.