Login Register Cart 0
Generic placeholder image

Current Nanoscience

Editor-in-Chief

ISSN (Print): 1573-4137
ISSN (Online): 1875-6786

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Research Article

Chaotic Dynamics and Stability of Liposomal Nanosystems

Author(s): Nikolaos Naziris, Maria Chountoulesi, Stavros Stavrinides*, Michael Hanias* and Costas Demetzos*

Volume 18, Issue 3, 2022

Published on: 26 August, 2021

Page: [375 - 390] Pages: 16

DOI: 10.2174/1573413717666210826144201

Abstract

Background: Natural and living systems are dynamical systems that demonstrate complex behavior, which appears to be deterministic chaotic, characterized and governed by entropy increase and loss of information throughout their entire lifespan. Lipidic nanoparticles, such as liposomes, as artificial biomembranes, have long been considered appropriate models for studying various membrane phenomena that cell systems exhibit. By utilizing these models, we can better comprehend cellular functions, stability, as well as factors that might alter the cell physiology, leading to severe disease states. In addition, liposomes are well-established drug and vaccine delivery nanosystems, which are present in the market, playing a significant role; therefore, due to their importance, issues concerning their effectiveness and stability are research topics that are constantly investigated and updated.

Methods: In this study, the emergent deterministic chaotic behavior of liposomes is described, while evaluation in accordance to their colloidal physical stability, by utilizing established nonlinear dynamics tools, is presented. Two liposomes of different composition and physical stability were developed and a chaotic evaluation on the time series of their size and polydispersity was conducted.

Results: The utilized models revealed instability, loss of information and order loss for both liposomes in due time, with important differentiations. An initial interpretation of the results is apposed, whereas the foundations for further investigating possible exploitation of the demonstrated nonlinearity and adaptability of artificial biomembranes is laid, with projection on biosystems.

Conclusion: The present approach is expected to impact the application of lipidic nanoparticles and liposomes in various crucial fields, such as drug and vaccine delivery, providing useful information for both the academia and industry.

Keywords: Liposomes, composition, light scattering, stability, complexity, chaotic behavior.

« Previous Next »
Graphical Abstract

[1]
Bayda, S.; Adeel, M.; Tuccinardi, T.; Cordani, M.; Rizzolio, F. The history of nanoscience and nanotechnology: From chemical-physical applications to nanomedicine. Molecules, 2019, 25(1), E112.
[http://dx.doi.org/10.3390/molecules25010112] [PMID: 31892180]
[2]
Singh, R. Nanotechnology based therapeutic application in cancer diagnosis and therapy. 3 Biotech., 2019, 9, 415.
[http://dx.doi.org/10.1007/s13205-019-1940-0]
[3]
Shi, J.; Votruba, A.R.; Farokhzad, O.C.; Langer, R. Nanotechnology in drug delivery and tissue engineering: From discovery to applications. Nano Lett., 2010, 10(9), 3223-3230.
[http://dx.doi.org/10.1021/nl102184c] [PMID: 20726522]
[4]
Nie, S.; Xing, Y.; Kim, G.J.; Simons, J.W. Nanotechnology applications in cancer. Annu. Rev. Biomed. Eng., 2007, 9, 257-288.
[http://dx.doi.org/10.1146/annurev.bioeng.9.060906.152025] [PMID: 17439359]
[5]
Bangham, A.D.; Standish, M.M.; Watkins, J.C. Diffusion of univalent ions across the lamellae of swollen phospholipids. J. Mol. Biol., 1965, 13(1), 238-252.
[http://dx.doi.org/10.1016/S0022-2836(65)80093-6] [PMID: 5859039]
[6]
Papahadjopoulos, D.; Watkins, J.C. Phospholipid model membranes. II. Permeability properties of hydrated liquid crystals. Biochim. Biophys. Acta, 1967, 135(4), 639-652.
[http://dx.doi.org/10.1016/0005-2736(67)90095-8] [PMID: 6048247]
[7]
Gregoriadis, G.; Leathwood, P.D.; Ryman, B.E. Enzyme entrapment in liposomes. FEBS Lett., 1971, 14(2), 95-99.
[http://dx.doi.org/10.1016/0014-5793(71)80109-6] [PMID: 11945728]
[8]
Tandrup Schmidt, S.; Foged, C.; Korsholm, K.S.; Rades, T.; Christensen, D. Liposome-based adjuvants for subunit vaccines: Formulation strategies for subunit antigens and immunostimulators. Pharmaceutics, 2016, 8(1), 1-22.
[http://dx.doi.org/10.3390/pharmaceutics8010007] [PMID: 26978390]
[9]
Allison, A.G.; Gregoriadis, G. Liposomes as immunological adjuvants. Nature, 1974, 252(5480), 252.
[http://dx.doi.org/10.1038/252252a0] [PMID: 4424229]
[10]
Nisini, R.; Poerio, N.; Mariotti, S.; De Santis, F.; Fraziano, M. The multirole of liposomes in therapy and prevention of infectious diseases. Front. Immunol., 2018, 9, 155.
[http://dx.doi.org/10.3389/fimmu.2018.00155] [PMID: 29459867]
[11]
Florindo, H.F.; Kleiner, R.; Vaskovich-Koubi, D.; Acúrcio, R.C.; Carreira, B.; Yeini, E.; Tiram, G.; Liubomirski, Y.; Satchi-Fainaro, R. Immune-mediated approaches against COVID-19. Nat. Nanotechnol., 2020, 15(8), 630-645.
[http://dx.doi.org/10.1038/s41565-020-0732-3] [PMID: 32661375]
[12]
McKay, P.F.; Hu, K.; Blakney, A.K.; Samnuan, K.; Brown, J.C.; Penn, R.; Zhou, J.; Bouton, C.R.; Rogers, P.; Polra, K.; Lin, P.J.C.; Barbosa, C.; Tam, Y.K.; Barclay, W.S.; Shattock, R.J. Self-amplifying RNA SARS-CoV-2 lipid nanoparticle vaccine candidate induces high neutralizing antibody titers in mice. Nat. Commun., 2020, 11(1), 3523.
[http://dx.doi.org/10.1038/s41467-020-17409-9] [PMID: 32647131]
[13]
Yang, D. Application of nanotechnology in the COVID-19 pandemic. Int. J. Nanomedicine, 2021, 16, 623-649.
[http://dx.doi.org/10.2147/IJN.S296383] [PMID: 33531805]
[14]
Zhang, N.N.; Li, X.F.; Deng, Y.Q.; Zhao, H.; Huang, Y.J.; Yang, G.; Huang, W.J.; Gao, P.; Zhou, C.; Zhang, R.R.; Guo, Y.; Sun, S.H.; Fan, H.; Zu, S.L.; Chen, Q.; He, Q.; Cao, T.S.; Huang, X.Y.; Qiu, H.Y.; Nie, J.H.; Jiang, Y.; Yan, H.Y.; Ye, Q.; Zhong, X.; Xue, X.L.; Zha, Z.Y.; Zhou, D.; Yang, X.; Wang, Y.C.; Ying, B.; Qin, C.F. A Thermostable mRNA Vaccine against COVID-19. Cell, 2020, 182(5), 1271-1283.e16.
[http://dx.doi.org/10.1016/j.cell.2020.07.024] [PMID: 32795413]
[15]
Flanagan, K.L.; Best, E.; Crawford, N.W.; Giles, M.; Koirala, A.; Macartney, K.; Russell, F.; Teh, B.W.; Wen, S.C.H. Progress and pitfalls in the quest for effective SARS-CoV-2 (COVID-19) vaccines. Front. Immunol., 2020, 11, 579250.
[http://dx.doi.org/10.3389/fimmu.2020.579250] [PMID: 33123165]
[16]
Rego, G.N.A.; Nucci, M.P.; Alves, A.H.; Oliveira, F.A.; Marti, L.C.; Nucci, L.P.; Mamani, J.B.; Gamarra, L.F. Current clinical trials protocols and the global effort for immunization against SARS-CoV-2. Vaccines (Basel), 2020, 8(3), 474.
[http://dx.doi.org/10.3390/vaccines8030474] [PMID: 32854391]
[17]
Sabín, J.; Prieto, G.; Ruso, J.M.; Hidalgo-Alvarez, R.; Sarmiento, F. Size and stability of liposomes: A possible role of hydration and osmotic forces. Eur. Phys. J. E Soft Matter, 2006, 20(4), 401-408.
[http://dx.doi.org/10.1140/epje/i2006-10029-9] [PMID: 16957831]
[18]
Bertalanffy, L.V. Problems of life; Watts: London, 1952.
[19]
Prigogine, I.; Strengers, I. Order out of chaos; Bantam Books: New York, 1984.
[20]
Naziris, N.; Demetzos, C. The formation of chimeric nanomorphologies, as a reflection of naturally occurring thermodynamic processes. J. Phys. Conf. Ser., 2017, 931, 012028.
[http://dx.doi.org/10.1088/1742-6596/931/1/012028]
[21]
Naziris, N.; Pippa, N.; Chrysostomou, V.; Pispas, S.; Demetzos, C.; Libera, M.; Trzebicka, B. Morphological diversity of block copolymer/lipid chimeric nanostructures. J. Nanopart. Res., 2017, 19, 347-357.
[http://dx.doi.org/10.1007/s11051-017-4021-5]
[22]
Demetzos, C. Biophysics and thermodynamics: The scientific building blocks of bio-inspired drug delivery nano systems. AAPS PharmSciTech, 2015, 16(3), 491-495.
[http://dx.doi.org/10.1208/s12249-015-0321-1] [PMID: 25899798]
[23]
Binder, W.H.; Barragan, V.; Menger, F.M. Domains and rafts in lipid membranes. Angew. Chem. Int. Ed. Engl., 2003, 42(47), 5802-5827.
[http://dx.doi.org/10.1002/anie.200300586] [PMID: 14673910]
[24]
Fox, S.W. Self-ordered polymers and propagative cell-like systems. Naturwissenschaften, 1969, 56(1), 1-9.
[http://dx.doi.org/10.1007/BF00599584] [PMID: 5358709]
[25]
Carter, J.D.; Lin, Ch.; Liu, Y.; Yan, H.; LaBean, Th.H. DNA-based self-assembly of nanostructures.Oxford handbook of nanoscience and technology: Volume II: Materials: Structures, properties, and characterization techniques; Narlikar, A. V.; Fu, Y. Y., Eds.; Oxford University Press , 2010.
[26]
Wang, Z.G.; Ding, B. DNA-based self-assembly for functional nanomaterials. Adv. Mater., 2013, 25(28), 3905-3914.
[http://dx.doi.org/10.1002/adma.201301450] [PMID: 24048977]
[27]
Sprott, J.C. Chaos and Time Series Analysis, 1st; Oxford University Press: Oxford, 2003.
[28]
Tsonis, A.A.; Elsner, J.B. Chaos, strange attractors, and weather. Bull. Am. Meteorol. Soc., 1989, 70, 14-23.
[http://dx.doi.org/10.1175/1520-0477(1989)070<0014:CSAAW>2.0.CO;2]
[29]
Moon, F.C. Chaotic and fractal dynamics: introduction for applied scientists and engineers; Wiley-VCH: Weinheim, 2008.
[30]
Sturis, J.; Mosekilde, E. Bifurcation sequence in a simple model of migratory dynamics. Syst. Dyn. Rev., 1988, 4, 208-217.
[http://dx.doi.org/10.1002/sdr.4260040112]
[31]
Karakotsou, C.; Kalomiros, J.A.; Hanias, M.P.; Anagnostopoulos, A.N.; Spyridelis, J. Nonlinear electrical conductivity of V2O5 single crystals. Phys. Rev. B Condens. Matter, 1992, 45(20), 11627-11631.
[http://dx.doi.org/10.1103/PhysRevB.45.11627] [PMID: 10001176]
[32]
Chawa, M.M.A.; Picos, R.; Garcia-Moreno, E.; Stavrinides, S.G.; Roldan, J.B.; Jimenez-Molinos, F. Proceedings of the 18th mediterranean electrotechnical conference (MELECON), Lemesos, CyprusApril 18-20, 20162016, pp. 1-4.
[33]
Field, R.J.; Györgyi, L. Chaos in chemistry and biochemistry; World Scientific: Singapore, 1993, p. 304.
[http://dx.doi.org/10.1142/1706]
[34]
Miliou, A.N.; Stavrinides, S.G.; Valaristos, A.P.; Anagnostopoulos, A.N. Nonlinear electronic circuit, Part II: Synchronization in a chaotic MODEM scheme. Nonlinear Anal-Theor, 2009, 71, e21-e31.
[http://dx.doi.org/10.1016/j.na.2009.05.076]
[35]
Miliou, A.N.; Stavrinides, S.G.; Valaristos, A.P.; Anagnostopoulos, A.N. Nonlinear electronic circuit, Part I: Multiple routes to chaos. Nonlinear Anal-Theor., 2009, 71, e3-e20.
[http://dx.doi.org/10.1016/j.na.2008.11.093]
[36]
Miliou, A.N.; Valaristos, A.P.; Stavrinides, S.G.; Kyritsi, K.; Anagnostopoulos, A.N. Characterization of a non-autonomous second-order non-linear circuit for secure data transmission. Chaos Solitons Fractals, 2007, 33, 1248-1255.
[http://dx.doi.org/10.1016/j.chaos.2006.01.079]
[37]
Stavrinides, S.G.; Anagnostopoulos, A.N. The route from synchronization to desynchronization of chaotic operating circuits and systems. Applications of Chaos and Nonlinear Dynamics in Science and Engineering; Banerjee, S; Rondoni, L., Ed.; Springer: Berlin, 2013, Vol. 3, pp. 229-275.
[http://dx.doi.org/10.1007/978-3-642-34017-8_9]
[38]
Kyprianidis, I.M.; Volos, C.K.; Stavrinides, S.G.; Stouboulos, I.N.; Anagnostopoulos, A.N. Master-Slave double-scroll circuit incomplete synchronization. J. Eng. Sci. Technol. Rev., 2010, 3, 41-45.
[http://dx.doi.org/10.25103/jestr.031.08]
[39]
Pippa, N.; Dokoumetzidis, A.; Demetzos, C.; Macheras, P. On the ubiquitous presence of fractals and fractal concepts in pharmaceutical sciences: a review. Int. J. Pharm., 2013, 456(2), 340-352.
[http://dx.doi.org/10.1016/j.ijpharm.2013.08.087] [PMID: 24025993]
[40]
Carstensen, J.T.; Franchini, M. The use of fractal geometry in pharmaceutical systems. Drug Dev. Ind. Pharm., 1993, 19, 85-100.
[http://dx.doi.org/10.3109/03639049309038762]
[41]
Hanias, M.P.; Magafas, L. Application of Physics Model in prediction of the Hellas National election results. J. Eng. Sci. Technol. Rev., 2009, 2, 112-117.
[http://dx.doi.org/10.25103/jestr.021.21]
[42]
Hanias, M.P.; Magafas, L.; Stavrinides, S.G. Chaotic analysis of gold price index. J. Eng. Sci. Technol. Rev., 2015, 8, 16-18.
[http://dx.doi.org/10.25103/jestr.081.04]
[43]
Volos, C.; Kyprianidis, I.; Stavrinides, S.G.; Stouboulos, I.N.; Magafas, L.; Anagnostopoulos, A.N. Nonlinear dynamics of a financial system from an engineer’s point of view. J. Eng. Sci. Technol. Rev., 2011, 4, 281-285.
[http://dx.doi.org/10.25103/jestr.043.16]
[44]
Stavrinides, S.G.; Hanias, M.P.; Magafas, L.; Banerjee, S. Control of economic situations by utilizing an electronic circuit. Int. J. Prod. Manag. Assess. Technol., 2015, 3, 1-15. [IJPMAT]
[http://dx.doi.org/10.4018/IJPMAT.2015070101]
[45]
Strogatz, S. Nonlinear dynamics and chaos: With applications to physics, biology, chemistry, and engineering (studies in nonlinearity); Westview: Colorado, 2001.
[46]
Robertson, R.; Combs, A. Chaos theory in psychology and the life sciences; Psychology Press: New York, 2014.
[http://dx.doi.org/10.4324/9781315806280]
[47]
Dokoumetzidis, A.; Iliadis, A.; Macheras, P. Nonlinear dynamics in clinical pharmacology: the paradigm of cortisol secretion and suppression. Br. J. Clin. Pharmacol., 2002, 54(1), 21-29.
[http://dx.doi.org/10.1046/j.1365-2125.2002.01600.x] [PMID: 12100221]
[48]
Pillai, N.; Schwartz, S.L.; Ho, T.; Dokoumetzidis, A.; Bies, R.; Freedman, I. Estimating parameters of nonlinear dynamic systems in pharmacology using chaos synchronization and grid search. J. Pharmacokinet. Pharmacodyn., 2019, 46(2), 193-210.
[http://dx.doi.org/10.1007/s10928-019-09629-4] [PMID: 30929120]
[49]
Takens, F. Detecting strange attractors in turbulence. Dynamical Systems and Turbulence, Lecture Notes in Mathematics; Rand, D.A; Young, D.L., Ed.; Springer: Berlin, 1981, Vol. 898, pp. 366-381.
[50]
Shuster, H.G.; Just, W. Deterministic chaos: An introduction, 4th; Wiley-VCH: Weinheim, 2005.
[http://dx.doi.org/10.1002/3527604804]
[51]
Grassberger, P.; Procaccia, I. Characterization of strange attractors. Phys. Rev. Lett., 1983, 50, 346-349.
[http://dx.doi.org/10.1103/PhysRevLett.50.346]
[52]
Grassberger, P.; Procaccia, I. Dimensions and entropies of strange attractors from a fluctuating dynamics approach. Physica D, 1984, 13, 34-54.
[http://dx.doi.org/10.1016/0167-2789(84)90269-0]
[53]
Bryant, P.; Brown, R.; Abarbanel, H.D.I. Lyapunov exponents from observed time series. Phys. Rev. Lett., 1990, 65(13), 1523-1526.
[http://dx.doi.org/10.1103/PhysRevLett.65.1523] [PMID: 10042292]
[54]
Kantz, H.; Schreiber, T. Nonlinear time series analysis, 2nd; Cambridge University Press: Cambridge, 2004.
[55]
Abarbanel, H.D.I. Analysis of observed chaotic data; Springer: New York, 1996.
[http://dx.doi.org/10.1007/978-1-4612-0763-4s]
[56]
Casals, E.; Soler, M.; Gallardo, M.; Estelrich, J. Electrophoretic behavior of stearylamine-containing liposomes. Langmuir, 1998, 14, 7522-7526.
[http://dx.doi.org/10.1021/la980444x]
[57]
Rajendran, V.; Rohra, S.; Raza, M.; Hasan, G.M.; Dutt, S.; Ghosh, P.C. Stearylamine liposomal delivery of monensin in combination with free artemisinin eliminates blood stages of Plasmodium falciparum in culture and P. berghei infection in murine malaria. Antimicrob. Agents Chemother., 2015, 60(3), 1304-1318.
[http://dx.doi.org/10.1128/AAC.01796-15] [PMID: 26666937]
[58]
Naziris, N.; Saitta, F.; Chrysostomou, V.; Libera, M.; Trzebicka, B.; Fessas, D.; Pispas, S.; Demetzos, C. pH-responsive chimeric liposomes: From nanotechnology to biological assessment. Int. J. Pharm., 2020, 574, 118849.
[http://dx.doi.org/10.1016/j.ijpharm.2019.118849] [PMID: 31759108]
[59]
Derjaguin, B.; Landau, L. Theory of the stability of strongly charged lyophobic sols and of the adhesion of strongly charged particles in solutions of electrolytes. Prog. Surf. Sci., 1941, 43, 30-59.
[http://dx.doi.org/10.1016/0079-6816(93)90013-L]
[60]
Verwey, E.J.; Overbeek, J.T.H.G. Theory of the stability of lyophobic colloids. J. Phys. Colloid Chem., 1947, 51(3), 631-636.
[http://dx.doi.org/10.1021/j150453a001] [PMID: 20238663]
[61]
Armengol, X.; Estelrich, J. Physical stability of different liposome compositions obtained by extrusion method. J. Microencapsul., 1995, 12(5), 525-535.
[http://dx.doi.org/10.3109/02652049509006783] [PMID: 8544096]
[62]
Cho, N.J.; Hwang, L.Y.; Solandt, J.J.R.; Frank, C.W. Comparison of extruded and sonicated vesicles for planar bilayer self-assembly. Materials (Basel), 2013, 6(8), 3294-3308.
[http://dx.doi.org/10.3390/ma6083294] [PMID: 28811437]
[63]
Velickov, S. Nonlinear dynamics and chaos with applications to hydrodynamics and hydrological modelling, 1st ed; Taylor & Francis: Oxfordshire, 2004.
[64]
Liebert, W.; Pawelzik, K.; Schuster, H.G. Optimal embeddings of chaotic attractors from topological considerations. Europhys. Lett., 1991, 14, 521-526.
[http://dx.doi.org/10.1209/0295-5075/14/6/004]
[65]
Abarbanel, H.D.; Brown, R.; Sidorowich, J.J.; Tsimring, L.S. The analysis of observed chaotic data in physical systems. Rev. Mod. Phys., 1993, 65, 1331-1392.
[http://dx.doi.org/10.1103/RevModPhys.65.1331]
[66]
Wolff, R.C. Local Lyapunov exponents: looking closely at chaos. J. R. Stat. Soc. Series B Stat. Methodol., 1992, 54, 353-371.
[67]
Provenzale, A.; Smith, L.A.; Vio, R.; Murante, G. Distinguishing between low-dimensional dynamics and randomness in measured time series. Physica D, 1992, 58, 31-49.
[http://dx.doi.org/10.1016/0167-2789(92)90100-2]
[68]
Rapp, P.E.; Albano, A.M.; Schmah, T.I.; Farwell, L.A. Filtered noise can mimic low-dimensional chaotic attractors. Phys. Rev. E Stat. Phys. Plasmas Fluids Relat. Interdiscip. Topics, 1993, 47(4), 2289-2297.
[http://dx.doi.org/10.1103/PhysRevE.47.2289] [PMID: 9960256]
[69]
Theiler, J.; Eubank, S.; Longtin, A.; Galdrikian, B.; Farmer, J.D. Testing for nonlinearity in time series: the method of surrogate data. Physica D, 1992, 58, 77-94.
[http://dx.doi.org/10.1016/0167-2789(92)90102-S]
[70]
Schreiber, T.; Schmitz, A. Surrogate time series. Physica D, 2000, 142, 346-382.
[http://dx.doi.org/10.1016/S0167-2789(00)00043-9]
[71]
Dolan, K.T.; Spano, M.L. Surrogate for nonlinear time series analysis. Phys. Rev. E Stat. Nonlin. Soft Matter Phys., 2001, 64(4 Pt 2), 046128.
[http://dx.doi.org/10.1103/PhysRevE.64.046128] [PMID: 11690111]
[72]
Temu. Surrogate Data MATLAB Central File Exchange. Retrieved November 17 2020.https://www.mathworks.com/matlabcentral/fileexchange/4612-surrogate-data
[73]
Danaei, M.; Dehghankhold, M.; Ataei, S.; Hasanzadeh Davarani, F.; Javanmard, R.; Dokhani, A.; Khorasani, S.; Mozafari, M.R. Impact of particle size and polydispersity index on the clinical applications of lipidic nanocarrier systems. Pharmaceutics, 2018, 10(2), 57.
[http://dx.doi.org/10.3390/pharmaceutics10020057] [PMID: 29783687]
[74]
Maistrenko, Y.L.; Mosekilde, E.; Postnov, D. Chaotic synchronization: Applications to living systemsWorld Scientific Publishing Co. Pte. Ltd.: Singapore , 2002.

Rights & Permissions Print Cite
Article Metrics
14
1
© 2024 Bentham Science Publishers | Privacy Policy