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Soon RH, Yin Z, Dogan MA, Dogan NO, Tiryaki ME, Karacakol AC, Aydin A, Esmaeili-Dokht P, Sitti M. Pangolin-inspired untethered magnetic robot for on-demand biomedical heating applications. Nat Commun 2023; 14:3320. [PMID: 37339969 PMCID: PMC10282021 DOI: 10.1038/s41467-023-38689-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 05/11/2023] [Indexed: 06/22/2023] Open
Abstract
Untethered magnetic miniature soft robots capable of accessing hard-to-reach regions can enable safe, disruptive, and minimally invasive medical procedures. However, the soft body limits the integration of non-magnetic external stimuli sources on the robot, thereby restricting the functionalities of such robots. One such functionality is localised heat generation, which requires solid metallic materials for increased efficiency. Yet, using these materials compromises the compliance and safety of using soft robots. To overcome these competing requirements, we propose a pangolin-inspired bi-layered soft robot design. We show that the reported design achieves heating > 70 °C at large distances > 5 cm within a short period of time <30 s, allowing users to realise on-demand localised heating in tandem with shape-morphing capabilities. We demonstrate advanced robotic functionalities, such as selective cargo release, in situ demagnetisation, hyperthermia and mitigation of bleeding, on tissue phantoms and ex vivo tissues.
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Affiliation(s)
- Ren Hao Soon
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
- Institute for Biomedical Engineering, ETH Zürich, 8092, Zürich, Switzerland
| | - Zhen Yin
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
- Department of Control Science and Engineering, Tongji University, Shanghai, China
- Frontiers Science Center for Intelligent Autonomous Systems, Shanghai, China
| | - Metin Alp Dogan
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
| | - Nihal Olcay Dogan
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
- Institute for Biomedical Engineering, ETH Zürich, 8092, Zürich, Switzerland
| | - Mehmet Efe Tiryaki
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
- Institute for Biomedical Engineering, ETH Zürich, 8092, Zürich, Switzerland
| | - Alp Can Karacakol
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
| | - Asli Aydin
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
| | - Pouria Esmaeili-Dokht
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
| | - Metin Sitti
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany.
- Institute for Biomedical Engineering, ETH Zürich, 8092, Zürich, Switzerland.
- School of Medicine and College of Engineering, Koç University, 34450, Istanbul, Turkey.
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2
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Lee YW, Kim JK, Bozuyuk U, Dogan NO, Khan MTA, Shiva A, Wild AM, Sitti M. Multifunctional 3D-Printed Pollen Grain-Inspired Hydrogel Microrobots for On-Demand Anchoring and Cargo Delivery. Adv Mater 2023; 35:e2209812. [PMID: 36585849 DOI: 10.1002/adma.202209812] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 12/22/2022] [Indexed: 06/17/2023]
Abstract
While a majority of wireless microrobots have shown multi-responsiveness to implement complex biomedical functions, their functional executions are strongly dependent on the range of stimulus inputs, which curtails their functional diversity. Furthermore, their responsive functions are coupled to each other, which results in the overlap of the task operations. Here, a 3D-printed multifunctional microrobot inspired by pollen grains with three hydrogel components is demonstrated: iron platinum (FePt) nanoparticle-embedded pentaerythritol triacrylate (PETA), poly N-isopropylacrylamide (pNIPAM), and poly N-isopropylacrylamide acrylic acid (pNIPAM-AAc) structures. Each of these structures exhibits their respective targeted functions: responding to magnetic fields for torque-driven surface rolling and steering, exhibiting temperature responsiveness for on-demand surface attachment (anchoring), and pH-responsive cargo release. The versatile multifunctional pollen grain-inspired robots conceptualized here pave the way for various future medical microrobots to improve their projected performance and functional diversity.
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Affiliation(s)
- Yun-Woo Lee
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
| | - Jae-Kang Kim
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
| | - Ugur Bozuyuk
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
- Institute for Biomedical Engineering, ETH Zurich, Zurich, 8092, Switzerland
| | - Nihal Olcay Dogan
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
- Institute for Biomedical Engineering, ETH Zurich, Zurich, 8092, Switzerland
| | - Muhammad Turab Ali Khan
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
| | - Anitha Shiva
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
| | - Anna-Maria Wild
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
| | - Metin Sitti
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
- Institute for Biomedical Engineering, ETH Zurich, Zurich, 8092, Switzerland
- School of Medicine and College of Engineering, Koç University, Istanbul, 34450, Turkey
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3
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Dogan NO, Ceylan H, Suadiye E, Sheehan D, Aydin A, Yasa IC, Wild AM, Richter G, Sitti M. Remotely Guided Immunobots Engaged in Anti-Tumorigenic Phenotypes for Targeted Cancer Immunotherapy. Small 2022; 18:e2204016. [PMID: 36202751 DOI: 10.1002/smll.202204016] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 09/08/2022] [Indexed: 06/16/2023]
Abstract
Building medical microrobots from the body's own cells may circumvent the biocompatibility concern and hence presents more potential in clinical applications to improve the possibility of escaping from the host defense mechanism. More importantly, live cells can enable therapeutically relevant functions with significantly higher efficiency than synthetic systems. Here, live immune cell-derived microrobots from macrophages, i.e., immunobots, which can be remotely steered with externally applied magnetic fields and directed toward anti-tumorigenic (M1) phenotypes, are presented. Macrophages engulf the engineered magnetic decoy bacteria, composed of 0.5 µm diameter silica Janus particles with one side coated with anisotropic FePt magnetic nanofilm and the other side coated with bacterial lipopolysaccharide (LPS). This study demonstrates the torque-based surface rolling locomotion of the immunobots along assigned trajectories inside blood plasma, over a layer of endothelial cells, and under physiologically relevant flow rates. The immunobots secrete signature M1 cytokines, IL-12 p40, TNF-α, and IL-6, and M1 cell markers, CD80 and iNOS, via toll-like receptor 4 (TLR4)-mediated stimulation with bacterial LPS. The immunobots exhibit anticancer activity against urinary bladder cancer cells. This study further demonstrates such immunobots from freshly isolated primary bone marrow-derived macrophages since patient-derivable macrophages may have a strong clinical potential for future cell therapies in cancer.
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Affiliation(s)
- Nihal Olcay Dogan
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
- Institute for Biomedical Engineering, ETH Zurich, Zurich, 8092, Switzerland
| | - Hakan Ceylan
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Scottsdale, AZ, 85259, USA
| | - Eylül Suadiye
- Materials Central Scientific Facility, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
| | - Devin Sheehan
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
| | - Asli Aydin
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
| | - Immihan Ceren Yasa
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
| | - Anna-Maria Wild
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
| | - Gunther Richter
- Materials Central Scientific Facility, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
| | - Metin Sitti
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569, Stuttgart, Germany
- Institute for Biomedical Engineering, ETH Zurich, Zurich, 8092, Switzerland
- School of Medicine and College of Engineering, Koç University, Istanbul, 34450, Turkey
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4
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Akolpoglu MB, Alapan Y, Dogan NO, Baltaci SF, Yasa O, Aybar Tural G, Sitti M. Magnetically steerable bacterial microrobots moving in 3D biological matrices for stimuli-responsive cargo delivery. Sci Adv 2022; 8:eabo6163. [PMID: 35857516 PMCID: PMC9286503 DOI: 10.1126/sciadv.abo6163] [Citation(s) in RCA: 48] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Bacterial biohybrids, composed of self-propelling bacteria carrying micro/nanoscale materials, can deliver their payload to specific regions under magnetic control, enabling additional frontiers in minimally invasive medicine. However, current bacterial biohybrid designs lack high-throughput and facile construction with favorable cargoes, thus underperforming in terms of propulsion, payload efficiency, tissue penetration, and spatiotemporal operation. Here, we report magnetically controlled bacterial biohybrids for targeted localization and multistimuli-responsive drug release in three-dimensional (3D) biological matrices. Magnetic nanoparticles and nanoliposomes loaded with photothermal agents and chemotherapeutic molecules were integrated onto Escherichia coli with ~90% efficiency. Bacterial biohybrids, outperforming previously reported E. coli-based microrobots, retained their original motility and were able to navigate through biological matrices and colonize tumor spheroids under magnetic fields for on-demand release of the drug molecules by near-infrared stimulus. Our work thus provides a multifunctional microrobotic platform for guided locomotion in 3D biological networks and stimuli-responsive delivery of therapeutics for diverse medical applications.
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Affiliation(s)
- Mukrime Birgul Akolpoglu
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569 Stuttgart, Germany
- Institute for Biomedical Engineering, ETH-Zürich, Zürich 8092, Switzerland
| | - Yunus Alapan
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569 Stuttgart, Germany
| | - Nihal Olcay Dogan
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569 Stuttgart, Germany
- Institute for Biomedical Engineering, ETH-Zürich, Zürich 8092, Switzerland
| | - Saadet Fatma Baltaci
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569 Stuttgart, Germany
- Stuttgart Center for Simulation Science (SC SimTech), University of Stuttgart, 70569 Stuttgart, Germany
| | - Oncay Yasa
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569 Stuttgart, Germany
| | - Gulsen Aybar Tural
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569 Stuttgart, Germany
- Department of Pharmaceutical Technology, Faculty of Pharmacy, Ege University, 35040 Izmir, Turkey
| | - Metin Sitti
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569 Stuttgart, Germany
- Institute for Biomedical Engineering, ETH-Zürich, Zürich 8092, Switzerland
- School of Medicine and College of Engineering, Koç University, 34450 Istanbul, Turkey
- Corresponding author.
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5
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Dogan NO, Bozuyuk U, Erkoc P, Karacakol AC, Cingoz A, Seker-Polat F, Nazeer MA, Sitti M, Bagci-Onder T, Kizilel S. Parameters Influencing Gene Delivery Efficiency of PEGylated Chitosan Nanoparticles: Experimental and Modeling Approach. Advanced NanoBiomed Research 2021. [DOI: 10.1002/anbr.202100033] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Affiliation(s)
- Nihal Olcay Dogan
- Chemical and Biological Engineering Koc University Istanbul 34450 Turkey
- Physical Intelligence Department Max Planck Institute for Intelligent Systems Stuttgart 70569 Germany
- Institute for Biomedical Engineering ETH Zurich Zurich 8092 Switzerland
| | - Ugur Bozuyuk
- Physical Intelligence Department Max Planck Institute for Intelligent Systems Stuttgart 70569 Germany
- Institute for Biomedical Engineering ETH Zurich Zurich 8092 Switzerland
| | - Pelin Erkoc
- Institute of Pharmaceutical Biology Goethe University Frankfurt Frankfurt 60438 Germany
| | - Alp Can Karacakol
- Physical Intelligence Department Max Planck Institute for Intelligent Systems Stuttgart 70569 Germany
- Department of Mechanical Engineering Carnegie Mellon University Pittsburgh PA 15213 USA
| | - Ahmet Cingoz
- School of Medicine Koc University Istanbul 34450 Turkey
| | | | | | - Metin Sitti
- Physical Intelligence Department Max Planck Institute for Intelligent Systems Stuttgart 70569 Germany
- Institute for Biomedical Engineering ETH Zurich Zurich 8092 Switzerland
- School of Medicine Koc University Istanbul 34450 Turkey
| | | | - Seda Kizilel
- Chemical and Biological Engineering Koc University Istanbul 34450 Turkey
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6
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Ceylan H, Dogan NO, Yasa IC, Musaoglu MN, Kulali ZU, Sitti M. 3D printed personalized magnetic micromachines from patient blood-derived biomaterials. Sci Adv 2021; 7:eabh0273. [PMID: 34516907 PMCID: PMC8442928 DOI: 10.1126/sciadv.abh0273] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
While recent wireless micromachines have shown increasing potential for medical use, their potential safety risks concerning biocompatibility need to be mitigated. They are typically constructed from materials that are not intrinsically compatible with physiological environments. Here, we propose a personalized approach by using patient blood–derivable biomaterials as the main construction fabric of wireless medical micromachines to alleviate safety risks from biocompatibility. We demonstrate 3D printed multiresponsive microswimmers and microrollers made from magnetic nanocomposites of blood plasma, serum albumin protein, and platelet lysate. These micromachines respond to time-variant magnetic fields for torque-driven steerable motion and exhibit multiple cycles of pH-responsive two-way shape memory behavior for controlled cargo delivery and release applications. Their proteinaceous fabrics enable enzymatic degradability with proteinases, thereby lowering risks of long-term toxicity. The personalized micromachine fabrication strategy we conceptualize here can affect various future medical robots and devices made of autologous biomaterials to improve biocompatibility and smart functionality.
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Affiliation(s)
- Hakan Ceylan
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569 Stuttgart, Germany
| | - Nihal Olcay Dogan
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569 Stuttgart, Germany
- Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
| | - Immihan Ceren Yasa
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569 Stuttgart, Germany
| | - Mirac Nur Musaoglu
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569 Stuttgart, Germany
- School of Medicine and College of Engineering, Koç University, 34450 Istanbul, Turkey
| | - Zeynep Umut Kulali
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569 Stuttgart, Germany
- School of Medicine and College of Engineering, Koç University, 34450 Istanbul, Turkey
| | - Metin Sitti
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569 Stuttgart, Germany
- Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland
- School of Medicine and College of Engineering, Koç University, 34450 Istanbul, Turkey
- Corresponding author.
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7
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Akolpoglu MB, Dogan NO, Bozuyuk U, Ceylan H, Kizilel S, Sitti M. High-Yield Production of Biohybrid Microalgae for On-Demand Cargo Delivery. Adv Sci (Weinh) 2020; 7:2001256. [PMID: 32832367 PMCID: PMC7435244 DOI: 10.1002/advs.202001256] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2020] [Indexed: 05/06/2023]
Abstract
Biohybrid microswimmers exploit the swimming and navigation of a motile microorganism to target and deliver cargo molecules in a wide range of biomedical applications. Medical biohybrid microswimmers suffer from low manufacturing yields, which would significantly limit their potential applications. In the present study, a biohybrid design strategy is reported, where a thin and soft uniform coating layer is noncovalently assembled around a motile microorganism. Chlamydomonas reinhardtii (a single-cell green alga) is used in the design as a biological model microorganism along with polymer-nanoparticle matrix as the synthetic component, reaching a manufacturing efficiency of ≈90%. Natural biopolymer chitosan is used as a binder to efficiently coat the cell wall of the microalgae with nanoparticles. The soft surface coating does not impair the viability and phototactic ability of the microalgae, and allows further engineering to accommodate biomedical cargo molecules. Furthermore, by conjugating the nanoparticles embedded in the thin coating with chemotherapeutic doxorubicin by a photocleavable linker, on-demand delivery of drugs to tumor cells is reported as a proof-of-concept biomedical demonstration. The high-throughput strategy can pave the way for the next-generation generation microrobotic swarms for future medical active cargo delivery tasks.
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Affiliation(s)
- Mukrime Birgul Akolpoglu
- Physical Intelligence DepartmentMax Planck Institute for Intelligent SystemsStuttgart70569Germany
| | - Nihal Olcay Dogan
- Physical Intelligence DepartmentMax Planck Institute for Intelligent SystemsStuttgart70569Germany
- Chemical and Biological Engineering DepartmentKoç UniversityIstanbul34450Turkey
| | - Ugur Bozuyuk
- Physical Intelligence DepartmentMax Planck Institute for Intelligent SystemsStuttgart70569Germany
| | - Hakan Ceylan
- Physical Intelligence DepartmentMax Planck Institute for Intelligent SystemsStuttgart70569Germany
| | - Seda Kizilel
- Chemical and Biological Engineering DepartmentKoç UniversityIstanbul34450Turkey
| | - Metin Sitti
- Physical Intelligence DepartmentMax Planck Institute for Intelligent SystemsStuttgart70569Germany
- School of Medicine and School of EngineeringKoç UniversityIstanbul34450Turkey
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Bozuyuk U, Gokulu IS, Dogan NO, Kizilel S. A novel method for PEGylation of chitosan nanoparticles through photopolymerization. RSC Adv 2019; 9:14011-14015. [PMID: 35519348 PMCID: PMC9063996 DOI: 10.1039/c9ra00780f] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Accepted: 04/24/2019] [Indexed: 11/24/2022] Open
Abstract
An ultrafast and convenient method for PEGylation of chitosan nanoparticles has been established through a photopolymerization reaction between the acrylate groups of PEG and methacrylated-chitosan nanoparticles. The nanoparticle characteristics under physiological pH conditions were optimized through altered PEG chain length, concentration and duration of UV exposure. The method developed here has potential for clinical translation of chitosan nanoparticles. It also allows for the scalable and fast synthesis of nanoparticles with colloidal stability. An ultrafast and convenient method for PEGylation of chitosan nanoparticles has been established through a photopolymerization reaction between the acrylate groups of PEG and methacrylated-chitosan nanoparticles.![]()
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Affiliation(s)
- Ugur Bozuyuk
- Chemical and Biological Engineering
- Koç University
- Istanbul 34450
- Turkey
| | - Ipek S. Gokulu
- Chemical and Biological Engineering
- Koç University
- Istanbul 34450
- Turkey
| | - Nihal Olcay Dogan
- Chemical and Biological Engineering
- Koç University
- Istanbul 34450
- Turkey
| | - Seda Kizilel
- Chemical and Biological Engineering
- Koç University
- Istanbul 34450
- Turkey
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Bozuyuk U, Dogan NO, Kizilel S. Deep Insight into PEGylation of Bioadhesive Chitosan Nanoparticles: Sensitivity Study for the Key Parameters Through Artificial Neural Network Model. ACS Appl Mater Interfaces 2018; 10:33945-33955. [PMID: 30212622 DOI: 10.1021/acsami.8b11178] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Ionically cross-linked chitosan nanoparticles have great potential in nanomedicine due to their tunable properties and cationic nature. However, low solubility of chitosan severely limits their potential clinical translation. PEGylation is a well-known method to increase solubility of chitosan and chitosan nanoparticles in neutral media; however, effect of PEG chain length and chitosan/PEG ratio on particle size and zeta potential of nanoparticles are not known. This study presents a systematic analysis of the effect of PEG chain length and chitosan/PEG ratio on size and zeta potential of nanoparticles. We prepared PEGylated chitosan chains prior to the nanoparticle synthesis with different PEG chain lengths and chitosan/PEG ratios. To precisely estimate the influence of critical parameters on size and zeta potential of nanoparticles, we both developed an artificial neural network (ANN) model and performed experimental characterization using the three independent input variables: (i) PEG chain length, (ii) chitosan/PEG ratio, and (iii) pH of solution. We studied the influence of PEG chain lengths of 2, 5, and 10 kDa and three different chitosan/PEG ratios (25 mg chitosan to 4, 12, and 20 μmoles of PEG) for the synthesis of chitosan nanoparticles within the pH range of 6.0-7.4. Artificial neural networks is a modeling tool used in nanomedicine to optimize and estimate inherent properties of the system. Inherent properties of a nanoparticle system such as size and zeta potential can be estimated based on previous experiment results, thus, nanoparticles with desired properties can be obtained using an ANN. With the ANN model, we were able to predict the size and zeta potential of nanoparticles under different experimental conditions and further confirmed the cell-nanoparticle adhesion behavior through experiments. Nanoparticle groups that had higher zeta potentials promoted adhesion of HEK293-T cells to nanoparticle-coated surfaces in cell culture medium, which was predicted through ANN model prior to experiments. Overall, this study comprehensively presents the PEGylation of chitosan, synthesis of PEGylated chitosan nanoparticles, utilizes ANN model as a tool to predict important properties such as size and zeta potential, and further captures the adhesion behavior of cells on surfaces prepared with these engineered nanoparticles.
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Affiliation(s)
- Ugur Bozuyuk
- Chemical and Biological Engineering , Koç University , Sariyer , Istanbul 34450 , Turkey
| | - Nihal Olcay Dogan
- Chemical and Biological Engineering , Koç University , Sariyer , Istanbul 34450 , Turkey
| | - Seda Kizilel
- Chemical and Biological Engineering , Koç University , Sariyer , Istanbul 34450 , Turkey
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