Pickering emulsion transport in skeletal muscle tissue: A dissipative particle dynamics simulation approach

doi:10.1016/j.cjche.2024.01.002

中国化学工程学报 ›› 2024, Vol. 68 ›› Issue (4): 65-75.DOI: 10.1016/j.cjche.2024.01.002

Pickering emulsion transport in skeletal muscle tissue: A dissipative particle dynamics simulation approach

Xuwei Liu^1,2, Wei Chen^1,4,5, Yufei Xia^3,4,5, Guanghui Ma^3,4,5, Reiji Noda², Wei Ge^1,2,4,5

1. State Key Laboratory of Mesoscience and Engineering, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China;
2. Division of Environmental Engineering Science, Graduate School of Science and Technology, Gunma University, 1-5-1 Tenjin-cho, Kiryu, Gunma 376-8515, Japan;
3. State Key Laboratory of Biochemical Engineering, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China;
4. School of Chemical Engineering, University of Chinese Academy of Sciences, Beijing 100049, China;
5. Innovation Academy for Green Manufacture, Chinese Academy of Sciences, Beijing 100190, China

收稿日期:2023-11-07 修回日期:2024-01-02 出版日期:2024-04-28 发布日期:2024-06-28
通讯作者: Wei Chen,E-mail address:chenwei@ipe.ac.cn;Yufei Xia,E-mail address:yfxia@ipe.ac.cn
基金资助:
This study is financially supported by the National Natural Science Foundation of China (22373104 and 22293024) and the Science Fund for Creative Research Groups of the National Natural Science Foundation of China (21821005). This study is also supported by the National Key Research and Development Program of China (2021YFE020527). Yufei Xia is grateful for the support by the Distinguished Young Scholars of the National Natural Science Foundation of China (T2222022). We also acknowledge the computational resources provided by upgraded Mole-8.5E supercomputing system developed by Institute of Process Engineering, Chinese Academy of Sciences.

Pickering emulsion transport in skeletal muscle tissue: A dissipative particle dynamics simulation approach

Xuwei Liu^1,2, Wei Chen^1,4,5, Yufei Xia^3,4,5, Guanghui Ma^3,4,5, Reiji Noda², Wei Ge^1,2,4,5

1. State Key Laboratory of Mesoscience and Engineering, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China;
2. Division of Environmental Engineering Science, Graduate School of Science and Technology, Gunma University, 1-5-1 Tenjin-cho, Kiryu, Gunma 376-8515, Japan;
3. State Key Laboratory of Biochemical Engineering, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China;
4. School of Chemical Engineering, University of Chinese Academy of Sciences, Beijing 100049, China;
5. Innovation Academy for Green Manufacture, Chinese Academy of Sciences, Beijing 100190, China

Received:2023-11-07 Revised:2024-01-02 Online:2024-04-28 Published:2024-06-28
Contact: Wei Chen,E-mail address:chenwei@ipe.ac.cn;Yufei Xia,E-mail address:yfxia@ipe.ac.cn
Supported by:
This study is financially supported by the National Natural Science Foundation of China (22373104 and 22293024) and the Science Fund for Creative Research Groups of the National Natural Science Foundation of China (21821005). This study is also supported by the National Key Research and Development Program of China (2021YFE020527). Yufei Xia is grateful for the support by the Distinguished Young Scholars of the National Natural Science Foundation of China (T2222022). We also acknowledge the computational resources provided by upgraded Mole-8.5E supercomputing system developed by Institute of Process Engineering, Chinese Academy of Sciences.

摘要/Abstract

摘要： Lymph node targeting is a commonly used strategy for particulate vaccines, particularly for Pickering emulsions. However, extensive research on the internal delivery mechanisms of these emulsions, especially the complex intercellular interactions of deformable Pickering emulsions, has been surprisingly sparse. This gap in knowledge holds significant potential for enhancing vaccine efficacy. This study aims to address this by summarizing the process of lymph-node-targeting transport and introducing a dissipative particle dynamics simulation method to evaluate the dynamic processes within cell tissue. The transport of Pickering emulsions in skeletal muscle tissue is specifically investigated as a case study. Various factors impacting the transport process are explored, including local cellular tissue environmental factors and the properties of the Pickering emulsion itself. The simulation results primarily demonstrate that an increase in radial repulsive interaction between emulsion particles can decrease the transport efficiency. Additionally, larger intercellular gaps also diminish the transport efficiency of emulsion droplet particles due to the increased motion complexity within the intricate transport space compared to a single channel. This study sheds light on the nuanced interplay between engineered and biological systems influencing the transport dynamics of Pickering emulsions. Such insights hold valuable potential for optimizing transport processes in practical biomedical applications such as drug delivery. Importantly, the desired transport efficiency varies depending on the specific application. For instance, while a more rapid transport might be crucial for lymph-node-targeted drug delivery, certain applications requiring a slower release of active components could benefit from the reduced transport efficiency observed with increased particle repulsion or larger intercellular gaps.

关键词: Pickering emulsion, Skeletal muscular cells, Transport phenomena, Dissipative particle dynamics, Drug delivery

Abstract: Lymph node targeting is a commonly used strategy for particulate vaccines, particularly for Pickering emulsions. However, extensive research on the internal delivery mechanisms of these emulsions, especially the complex intercellular interactions of deformable Pickering emulsions, has been surprisingly sparse. This gap in knowledge holds significant potential for enhancing vaccine efficacy. This study aims to address this by summarizing the process of lymph-node-targeting transport and introducing a dissipative particle dynamics simulation method to evaluate the dynamic processes within cell tissue. The transport of Pickering emulsions in skeletal muscle tissue is specifically investigated as a case study. Various factors impacting the transport process are explored, including local cellular tissue environmental factors and the properties of the Pickering emulsion itself. The simulation results primarily demonstrate that an increase in radial repulsive interaction between emulsion particles can decrease the transport efficiency. Additionally, larger intercellular gaps also diminish the transport efficiency of emulsion droplet particles due to the increased motion complexity within the intricate transport space compared to a single channel. This study sheds light on the nuanced interplay between engineered and biological systems influencing the transport dynamics of Pickering emulsions. Such insights hold valuable potential for optimizing transport processes in practical biomedical applications such as drug delivery. Importantly, the desired transport efficiency varies depending on the specific application. For instance, while a more rapid transport might be crucial for lymph-node-targeted drug delivery, certain applications requiring a slower release of active components could benefit from the reduced transport efficiency observed with increased particle repulsion or larger intercellular gaps.

Key words: Pickering emulsion, Skeletal muscular cells, Transport phenomena, Dissipative particle dynamics, Drug delivery

Xuwei Liu, Wei Chen, Yufei Xia, Guanghui Ma, Reiji Noda, Wei Ge. Pickering emulsion transport in skeletal muscle tissue: A dissipative particle dynamics simulation approach[J]. 中国化学工程学报, 2024, 68(4): 65-75.

参考文献

[1] Y.Q. Yang, Z.W. Fang, X. Chen, W.W. Zhang, Y.M. Xie, Y.H. Chen, Z.G. Liu, W.E. Yuan, An overview of Pickering emulsions: Solid-particle materials, classification, morphology, and applications, Front. Pharmacol. 8(2017) 287.
[2] Y.F. Xia, J. Wu, W. Wei, Y.Q. Du, T. Wan, X.W. Ma, W.Q. An, A.Y. Guo, C.Y. Miao, H. Yue, S.G. Li, X.T. Cao, Z.G. Su, G.H. Ma, Exploiting the pliability and lateral mobility of Pickering emulsion for enhanced vaccination, Nat. Mater. 17(2018) 187-194.
[3] A. Azuar, H.Y.R. Madge, J.C. Boer, J.L. Gonzalez Cruz, J. Wang, Z.G. Khalil, C. Deceneux, G. Goodchild, J. Yang, P. Koirala, W.M. Hussein, R.J. Capon, M. Plebanski, I. Toth, M. Skwarczynski, Poly(hydrophobic amino acids) and liposomes for delivery of vaccine against group A streptococcus, Vaccines 10(8) (2022) 1212.
[4] J. Liu, X.D. Yan, X.Q. Li, Y.H. Du, L.L. Zhu, T.T. Ye, Z.Y. Cao, Z.W. Dong, S.T. Li, X. Xu, W. Bai, D. Li, J.W. Zhang, S.J. Wang, S.H. Li, J. Sun, X.Z. Yin, Chrysanthemum sporopollenin: A novel vaccine delivery system for nasal mucosal immunity, Front. Immunol. 14(2023) 1132129.
[5] L.S. Ming, H.L. Wu, A. Liu, A. Naeem, Z.S. Dong, Q.M. Fan, G.C. Zhang, H.N. Liu, Z. Li, Evolution and critical roles of particle properties in Pickering emulsion: A review, J. Mol. Liq. 388(2023) 122775.
[6] J. Pielenhofer, J. Sohl, M. Windbergs, P. Langguth, M.P. Radsak, Current progress in particle-based systems for transdermal vaccine delivery, Front. Immunol. 11(2020) 266.
[7] Y.L. Ming, Y.F. Xia, G.H. Ma, Aggregating particles on the O/W interface: Tuning Pickering emulsion for the enhanced drug delivery systems, Aggregate 3(2) (2022) e162.
[8] A. Schudel, D.M. Francis, S.N. Thomas, Material design for lymph node drug delivery, Nat. Rev. Mater. 4(6) (2019) 415-428.
[9] T.T. Song, Y.F. Xia, Y.Q. Du, M.W. Chen, H. Qing, G.H. Ma, Engineering the deformability of albumin-stabilized emulsions for lymph-node vaccine delivery, Adv. Mater. 33(26) (2021) e2100106.
[10] J.J. Chen, Z.F. Ye, C.F. Huang, M. Qiu, D.H. Song, Y.M. Li, Q.B. Xu, Lipid nanoparticle-mediated lymph node-targeting delivery of mRNA cancer vaccine elicits robust CD⁸⁺ T cell response, Proc. Natl. Acad. Sci. USA 119(34) (2022) e2207841119.
[11] G.P. Howard, N.G. Bender, P. Khare, B. Lopez-Gutierrez, V. Nyasembe, W.J. Weiss, J.W. Simecka, T. Hamerly, H.Q. Mao, R.R. Dinglasan, Immunopotentiation by lymph-node targeting of a malaria transmission-blocking nanovaccine, Front. Immunol. 12(2021) 729086.
[12] H. Qin, R.F. Zhao, Y.T. Qin, J. Zhu, L. Chen, C.Z. Di, X.X. Han, K.M. Cheng, Y.L. Zhang, Y. Zhao, J. Shi, G.J. Anderson, Y.L. Zhao, G.J. Nie, Development of a cancer vaccine using in vivo click-chemistry-mediated active lymph node accumulation for improved immunotherapy, Adv. Mater. 33(20) (2021) e2006007.
[13] P. Baluk, J. Fuxe, H. Hashizume, T. Romano, E. Lashnits, S. Butz, D. Vestweber, M. Corada, C. Molendini, E. Dejana, D.M. McDonald, Functionally specialized junctions between endothelial cells of lymphatic vessels, J. Exp. Med. 204(10) (2007) 2349-2362.
[14] J.W. Breslin, Mechanical forces and lymphatic transport, Microvasc. Res. 96(2014) 46-54.
[15] A.R. Gillies, R.L. Lieber, Structure and function of the skeletal muscle extracellular matrix, Muscle Nerve 44(3) (2011) 318-331.
[16] S. Jalkanen, M. Salmi, Lymphatic endothelial cells of the lymph node, Nat. Rev. Immunol. 20(9) (2020) 566-578.
[17] K.N. Margaris, R.A. Black, Modelling the lymphatic system: Challenges and opportunities, J. R. Soc. Interface 9(69) (2012) 601-612.
[18] J.P. Nederveen, M.W. Betz, T. Snijders, G. Parise, The importance of muscle capillarization for optimizing satellite cell plasticity, Exerc. Sport Sci. Rev. 49(4) (2021) 284-290.
[19] L.H. Nicoll, A. Hesby, Intramuscular injection: An integrative research review and guideline for evidence-based practice, Appl. Nurs. Res. 15(3) (2002) 149-162.
[20] O. Ohtani, Y. Ohtani, C.J. Carati, B.J. Gannon, Fluid and cellular pathways of rat lymph nodes in relation to lymphatic labyrinths and Aquaporin-1 expression, Arch. Histol. Cytol. 66(3) (2003) 261-272.
[21] F. Zhang, G. Zarkada, S.J. Yi, A. Eichmann, Lymphatic endothelial cell junctions: Molecular regulation in physiology and diseases, Front. Physiol. 11(2020) 509.
[22] E. Mendoza, G.W. Schmid-Schonbein, A model for mechanics of primary lymphatic valves, J. Biomech. Eng. 125(3) (2003) 407-414.
[23] N.P. Reddy, K. Patel, A mathematical model of flow through the terminal lymphatics, Med. Eng. Phys. 17(2) (1995) 134-140.
[24] N.Q. Gong, Y.X. Zhang, Z. Zhang, X.L. Li, X.J. Liang, Functional nanomaterials optimized to circumvent tumor immunological tolerance, Adv. Funct. Mater. 29(3) (2019) 1806087.
[25] D.A. Fedosov, B. Caswell, G.E. Karniadakis, A multiscale red blood cell model with accurate mechanics, rheology, and dynamics, Biophys. J. 98(10) (2010) 2215-2225.
[26] N. Liu, M. Becton, L.Y. Zhang, X.Q. Wang, Mechanism of coupling nanoparticle stiffness with shape for endocytosis: From rodlike penetration to wormlike wriggling, J. Phys. Chem. B 124(49) (2020) 11145-11156.
[27] W. Pan, A.M. Tartakovsky, Dissipative particle dynamics model for colloid transport in porous media, Adv. Water Resour. 58(2013) 41-48.
[28] L. Zhou, S.L. Feng, H.T. Liu, J.Z. Chang, Dissipative particle dynamics simulation of cell entry into a micro-channel, Eng. Anal. Bound. Elem. 107(2019) 47-52.
[29] H.J. Liu, Y. Sun, C.A. Simmons, Determination of local and global elastic moduli of valve interstitial cells cultured on soft substrates, J. Biomech. 46(11) (2013) 1967-1971.
[30] I.V. Pivkin, G.E. Karniadakis, Accurate coarse-grained modeling of red blood cells, Phys. Rev. Lett. 101(11) (2008) 118105.
[31] P.J. Hoogerbrugge, J.M.V.A. Koelman, Simulating microscopic hydrodynamic phenomena with dissipative particle dynamics, Europhys. Lett. 19(3) (1992) 155-160.
[32] J.M.V.A. Koelman, P.J. Hoogerbrugge, Dynamic simulations of hard-sphere suspensions under steady shear, Europhys. Lett. 21(3) (1993) 363-368.
[33] X.J. Fan, N. Phan-Thien, S. Chen, X.H. Wu, T. Yong Ng, Simulating flow of DNA suspension using dissipative particle dynamics, Phys. Fluids 18(6) (2006) 063102.
[34] D.A. Fedosov, G.E. Karniadakis, B. Caswell, Dissipative particle dynamics simulation of depletion layer and polymer migration in micro- and nanochannels for dilute polymer solutions, J. Chem. Phys. 128(14) (2008) 144903.
[35] P. Espanol, P. Warren, Statistical mechanics of dissipative particle dynamics, Europhys. Lett. 30(4) (1995) 191-196.
[36] P. Espanol, Fluid particle model, Phys. Rev. E 57(3) (1998) 2930-2948.
[37] W. Pan, D.A. Fedosov, G.E. Karniadakis, B. Caswell, Hydrodynamic interactions for single dissipative-particle-dynamics particles and their clusters and filaments, Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 78(4 Pt 2) (2008) 046706.
[38] W. Pan, I.V. Pivkin, G.E. Karniadakis, Single-particle hydrodynamics in DPD: A new formulation, Europhys. Lett. 84(1) (2008) 10012.
[39] D.E. Discher, D.H. Boal, S.K. Boey, Simulations of the erythrocyte cytoskeleton at large deformation. II. Micropipette aspiration, Biophys. J. 75(3) (1998) 1584-1597.
[40] J. Li, M. Dao, C.T. Lim, S. Suresh, Spectrin-level modeling of the cytoskeleton and optical tweezers stretching of the erythrocyte, Biophys. J. 88(5) (2005) 3707-3719.
[41] D.A. Fedosov, G. Gompper, White blood cell margination in microcirculation, Soft Matter 10(17) (2014) 2961-2970.
[42] A. Yazdani, Y. Deng, H. Li, E. Javadi, Z. Li, S. Jamali, C. Lin, J.D. Humphrey, C.S. Mantzoros, G.E. Karniadakis, Integrating blood cell mechanics, platelet adhesive dynamics and coagulation cascade for modelling thrombus formation in normal and diabetic blood, J. R. Soc. Interface 18(175) (2021) 20200834.
[43] M. Razizadeh, M. Nikfar, R. Paul, Y.L. Liu, Coarse-grained modeling of pore dynamics on the red blood cell membrane under large deformations, Biophys. J. 119(3) (2020) 471-482.
[44] X. Shi, G. Lin, J.F. Zou, D.A. Fedosov, A lattice Boltzmann fictitious domain method for modeling red blood cell deformation and multiple-cell hydrodynamic interactions in flow, Int. J. Numer. Meth. Fluids 72(8) (2013) 895-911.
[45] A.L. Blumers, Y.H. Tang, Z. Li, X.J. Li, G.E. Karniadakis, GPU-accelerated red blood cells simulations with transport dissipative particle dynamics, Comput. Phys. Commun. 217(2017) 171-179.
[46] C. Pozrikidis, Computational hydrodynamics of capsules and biological cells. Boca Raton, FL: CRC Press, (2010).
[47] M.P. Allen, D.J. Tildesley, Computer simulation of liquids, Second edition, Oxford University Press, Oxford, United Kingdom, 2017.
[48] M. Dao, J. Li, S. Suresh, Molecularly based analysis of deformation of spectrin network and human erythrocyte, Mater. Sci. Eng. C 26(8) (2006) 1232-1244.
[49] B. Liu, X. Qiu, How to compute the atomic stress objectively? J. Comput. Theor. Nanos. 6 (5) (2008) 1082-1089.
[50] L.L. Zhang, J. Jasa, G. Gazonas, A. Jerusalem, M. Negahban, Extracting continuum-like deformation and stress from molecular dynamics simulations, Comput. Meth. Appl. Mech. Eng. 283(2015) 1010-1031.
[51] Y.H. Tang, G.E. Karniadakis, Accelerating dissipative particle dynamics simulations on GPUs: Algorithms, numerics and applications, Comput. Phys. Commun. 185(11) (2014) 2809-2822.
[52] P.O. Persson, G. Strang, A simple mesh generator in MATLAB, SIAM Rev. 46(2) (2004) 329-345.
[53] S. Eloul, E. Katelhon, R.G. Compton, When does near-wall hindered diffusion influence mass transport towards targets? Phys. Chem. Chem. Phys. 18(38) (2016) 26539-26549.
[54] M. Gonzalez-Melchor, E. Mayoral, M.E. Velazquez, J. Alejandre, Electrostatic interactions in dissipative particle dynamics using the Ewald sums, J. Chem. Phys. 125(22) (2006) 224107.
[55] R.D. Groot, Electrostatic interactions in dissipative particle dynamics-simulation of polyelectrolytes and anionic surfactants, J. Chem. Phys. 118(24) (2003) 11265-11277.
[56] A. Gubbiotti, M. Chinappi, C.M. Casciola, EH-DPD: A dissipative particle dynamics approach to electrohydrodynamics, Eur. Phys. J. Plus 137(5) (2022) 572.
[57] J. Smiatek, F. Schmid, Mesoscopic simulations of electroosmotic flow and electrophoresis in nanochannels, Comput. Phys. Commun. 182(9) (2011) 1941-1944.

Pickering emulsion transport in skeletal muscle tissue: A dissipative particle dynamics simulation approach

Pickering emulsion transport in skeletal muscle tissue: A dissipative particle dynamics simulation approach

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 13

编辑推荐

Metrics

本文评价

[1]	Yi Wu, Hongzhou Shang, Shisheng Lai, Yali Di, Xiaoran Sun, Ning Qiao, Lihua Han, Zheng Zhao, Yujin Lu. Preparation and evaluation of controllable drug delivery system: A light responsive nanosphere based on β-cyclodextrin/mesoporous silica[J]. 中国化学工程学报, 2023, 62(10): 159-167.
[2]	Guina Yi, Ziqi Cai, Zhengming Gao, J.J. Derksen. Impingement and mixing dynamics of micro-droplets on a solid surface[J]. 中国化学工程学报, 2022, 52(12): 66-77.
[3]	Jing Zhao, Zhiguang Duan, Xiaoxuan Ma, Yannan Liu, Daidi Fan. Recent advances in systemic and local delivery of ginsenosides using nanoparticles and nanofibers[J]. 中国化学工程学报, 2021, 29(2): 291-300.
[4]	Dong Wan, Sunfan Li, Jianxin Zhang, Guilei Ma, Jie Pan. Intelligent self-assembly prodrug micelles loading doxorubicin in response to tumor microenvironment for targeted tumors therapy[J]. 中国化学工程学报, 2021, 39(11): 219-227.
[5]	Xuhua Liang, Yanyan Zhao, Min Cheng, Fei Zhang. Rational design and synthesis of upconversion luminescence-based optomagnetic multifunctional nanorattles for drug delivery[J]. 中国化学工程学报, 2021, 38(10): 286-293.
[6]	Yinfeng Zhang, Fang Fang, Yongjie Chen, Min Li, Li Li, Wenyue Li, Jinfeng Zhang. Hollow mesoporous polyaniline nanoparticles with high drug payload and robust photothermal capability for cancer combination therapy[J]. 中国化学工程学报, 2021, 38(10): 221-228.
[7]	Akbar Mohammadi, Jafarsadegh Moghaddas. Mesoporous tablet-shaped potato starch aerogels for loading and release of the poorly water-soluble drug celecoxib[J]. 中国化学工程学报, 2020, 28(7): 1778-1787.
[8]	Zaisha Mao, Chao Yang. Computational chemical engineering-Towards thorough understanding and precise application[J]. Chinese Journal of Chemical Engineering, 2016, 24(8): 945-951.
[9]	Alexandru Woinaroschy. A paradigm-based evolution of chemical engineering[J]. Chinese Journal of Chemical Engineering, 2016, 24(5): 553-557.
[10]	李文锋, 刘贵金, 李黎仙, 伍娟, 吕扬效, 江燕斌. Effect of Process Parameters on Co-precipitation of Paclitaxel and Poly(L-lactic Acid) by Supercritical Antisolvent Process[J]. Chinese Journal of Chemical Engineering, 2012, 20(4): 803-813.
[11]	黎新明, 崔英德. Study on Synthesis and Chloramphenicol Release of Poly(2-hydroxyethylmethacrylate-co-acrylamide)Hydrogels[J]. , 2008, 16(4): 640-645.
[12]	蒋国强, 朱德权, 昝佳, 丁富新. 电致孔经皮给药：表面活性剂对孔道存在时间和药物传输的影响[J]. , 2007, 15(3): 397-402.
[13]	刘亮, 晋平, 程明, 张国亮, 张凤宝. 载5-氟尿嘧啶的pH敏感自组装纳米粒制备及体外释放[J]. , 2006, 14(3): 377-382.