Computational modeling of superparamagnetic nanoparticle-based (affinity) diagnostics
IntroductionMagnetic nanoparticles (MNPs), particularly iron oxide nanoparticles (IONPs), are renowned for their superparamagnetic behavior, allowing precise control under external magnetic fields. This characteristic makes them ideal for biomedical applications, including diagnostics and drug deliv...
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Frontiers Media S.A.
2024-12-01
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| author | Loïc Van Dieren Loïc Van Dieren Loïc Van Dieren Loïc Van Dieren Loïc Van Dieren Vlad Tereshenko Haïzam Oubari Haïzam Oubari Haïzam Oubari Yanis Berkane Yanis Berkane Jonathan Cornacchini Jonathan Cornacchini Filip Thiessen EF Filip Thiessen EF Filip Thiessen EF Filip Thiessen EF Curtis L. Cetrulo Curtis L. Cetrulo Curtis L. Cetrulo Curtis L. Cetrulo Korkut Uygun Korkut Uygun Alexandre G. Lellouch Alexandre G. Lellouch Alexandre G. Lellouch Alexandre G. Lellouch Alexandre G. Lellouch Alexandre G. Lellouch |
| author_facet | Loïc Van Dieren Loïc Van Dieren Loïc Van Dieren Loïc Van Dieren Loïc Van Dieren Vlad Tereshenko Haïzam Oubari Haïzam Oubari Haïzam Oubari Yanis Berkane Yanis Berkane Jonathan Cornacchini Jonathan Cornacchini Filip Thiessen EF Filip Thiessen EF Filip Thiessen EF Filip Thiessen EF Curtis L. Cetrulo Curtis L. Cetrulo Curtis L. Cetrulo Curtis L. Cetrulo Korkut Uygun Korkut Uygun Alexandre G. Lellouch Alexandre G. Lellouch Alexandre G. Lellouch Alexandre G. Lellouch Alexandre G. Lellouch Alexandre G. Lellouch |
| author_sort | Loïc Van Dieren |
| collection | DOAJ |
| description | IntroductionMagnetic nanoparticles (MNPs), particularly iron oxide nanoparticles (IONPs), are renowned for their superparamagnetic behavior, allowing precise control under external magnetic fields. This characteristic makes them ideal for biomedical applications, including diagnostics and drug delivery. Superparamagnetic IONPs, which exhibit magnetization only in the presence of an external field, can be functionalized with ligands for targeted affinity diagnostics. This study presents a computational model to explore the induced voltage in a search coil when MNPs pass through a simulated blood vessel, aiming to improve non-invasive diagnostic methods for disease detection and monitoring.MethodsA finite element model was constructed using COMSOL Multiphysics to simulate the behavior of IONPs within a dynamic blood vessel environment. Governing equations such as Ampère’s law and Faraday’s law of induction were incorporated to simulate the induced voltage in a copper coil as MNPs of various sizes flowed through the vessel. Rheological parameters, including blood viscosity and flow rates, were factored into the model using a non-Newtonian fluid approach.ResultsThe amount of MNPs required for detection varies significantly based on the sensitivity of the detection equipment and the size of the nanoparticles themselves. For highly sensitive devices like a SQUID voltmeter, with a coil sensitivity approximately 10−12 V, very low MNP concentrations—approximately 10−4 μg/mL—are sufficient for detection, staying well within the safe range. As coil sensitivity decreases, such as with standard voltmeters at 10−8 V or 10−6 V, the MNP concentration required for detection rises, approaching or even exceeding potentially toxic levels. Additionally, the physical size of MNPs plays a role; larger nanoparticles (e.g., 50 nm radius) require fewer total particles for detection at the same sensitivity than smaller particles like those with a 2.5 nm radius. For instance, at a coil sensitivity of 10−10 V, a 2.5 nm particle requires approximately 1012 particles, whereas a 50-nm particle only needs 108. This highlights the importance of optimizing both detection sensitivity and particle size to balance effective detection with safety.ConclusionThis computational model demonstrates the feasibility of using superparamagnetic nanoparticles in real-time, non-invasive diagnostic systems. |
| format | Article |
| id | doaj-art-2ca75a2b2c6946c092b439b7f4c61e2d |
| institution | Kabale University |
| issn | 2296-4185 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Bioengineering and Biotechnology |
| spelling | doaj-art-2ca75a2b2c6946c092b439b7f4c61e2d2024-12-06T04:31:36ZengFrontiers Media S.A.Frontiers in Bioengineering and Biotechnology2296-41852024-12-011210.3389/fbioe.2024.15007561500756Computational modeling of superparamagnetic nanoparticle-based (affinity) diagnosticsLoïc Van Dieren0Loïc Van Dieren1Loïc Van Dieren2Loïc Van Dieren3Loïc Van Dieren4Vlad Tereshenko5Haïzam Oubari6Haïzam Oubari7Haïzam Oubari8Yanis Berkane9Yanis Berkane10Jonathan Cornacchini11Jonathan Cornacchini12Filip Thiessen EF13Filip Thiessen EF14Filip Thiessen EF15Filip Thiessen EF16Curtis L. Cetrulo17Curtis L. Cetrulo18Curtis L. Cetrulo19Curtis L. Cetrulo20Korkut Uygun21Korkut Uygun22Alexandre G. Lellouch23Alexandre G. Lellouch24Alexandre G. Lellouch25Alexandre G. Lellouch26Alexandre G. Lellouch27Alexandre G. Lellouch28Center for Engineering in Medicine and Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United StatesVascularized Composite Allotransplantation Laboratory, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United StatesDivision of Plastic and Reconstructive Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United StatesShriners Children’s Boston, Boston, MA, United StatesFaculty of Medicine and Health Sciences, University of Antwerp, Wilrijk, BelgiumDivision of Plastic and Reconstructive Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United StatesVascularized Composite Allotransplantation Laboratory, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United StatesDivision of Plastic and Reconstructive Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United StatesShriners Children’s Boston, Boston, MA, United StatesShriners Children’s Boston, Boston, MA, United StatesDepartment of Plastic, Reconstructive and Aesthetic Surgery, CHU Rennes, University of Rennes, Rennes, FranceVascularized Composite Allotransplantation Laboratory, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United StatesDivision of Plastic and Reconstructive Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United StatesFaculty of Medicine and Health Sciences, University of Antwerp, Wilrijk, BelgiumGynaecological Oncology Unit, Department of Obstetrics and Gynaecology, Multidisciplinary Breast Clinic, Antwerp University Hospital, University of Antwerp, Antwerp, BelgiumDepartment of Plastic, Reconstructive and Aesthetic Surgery, Multidisciplinary Breast Clinic, Antwerp University Hospital, Antwerp, BelgiumDepartment of Plastic, Reconstructive and Aesthetic Surgery, Ziekenhuis Netwerk Antwerpen, Antwerp, BelgiumVascularized Composite Allotransplantation Laboratory, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United StatesDivision of Plastic and Reconstructive Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United StatesShriners Children’s Boston, Boston, MA, United States0Division of Plastic and Reconstructive Surgery, Cedars Sinai Medical Center, Los Angeles, CA, United StatesCenter for Engineering in Medicine and Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United StatesShriners Children’s Boston, Boston, MA, United StatesVascularized Composite Allotransplantation Laboratory, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United StatesDivision of Plastic and Reconstructive Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United StatesShriners Children’s Boston, Boston, MA, United States0Division of Plastic and Reconstructive Surgery, Cedars Sinai Medical Center, Los Angeles, CA, United States1Unité Mixte de Recherche UMR 1236 Suivi Immunologique des Thérapeutiques Innovantes, INSERM and University of Rennes, Rennes, France2Unité Mixte de Recherche UMR-S 1140 Innovative Therapies in Haemostais, INSERM and University of Paris, Paris, FranceIntroductionMagnetic nanoparticles (MNPs), particularly iron oxide nanoparticles (IONPs), are renowned for their superparamagnetic behavior, allowing precise control under external magnetic fields. This characteristic makes them ideal for biomedical applications, including diagnostics and drug delivery. Superparamagnetic IONPs, which exhibit magnetization only in the presence of an external field, can be functionalized with ligands for targeted affinity diagnostics. This study presents a computational model to explore the induced voltage in a search coil when MNPs pass through a simulated blood vessel, aiming to improve non-invasive diagnostic methods for disease detection and monitoring.MethodsA finite element model was constructed using COMSOL Multiphysics to simulate the behavior of IONPs within a dynamic blood vessel environment. Governing equations such as Ampère’s law and Faraday’s law of induction were incorporated to simulate the induced voltage in a copper coil as MNPs of various sizes flowed through the vessel. Rheological parameters, including blood viscosity and flow rates, were factored into the model using a non-Newtonian fluid approach.ResultsThe amount of MNPs required for detection varies significantly based on the sensitivity of the detection equipment and the size of the nanoparticles themselves. For highly sensitive devices like a SQUID voltmeter, with a coil sensitivity approximately 10−12 V, very low MNP concentrations—approximately 10−4 μg/mL—are sufficient for detection, staying well within the safe range. As coil sensitivity decreases, such as with standard voltmeters at 10−8 V or 10−6 V, the MNP concentration required for detection rises, approaching or even exceeding potentially toxic levels. Additionally, the physical size of MNPs plays a role; larger nanoparticles (e.g., 50 nm radius) require fewer total particles for detection at the same sensitivity than smaller particles like those with a 2.5 nm radius. For instance, at a coil sensitivity of 10−10 V, a 2.5 nm particle requires approximately 1012 particles, whereas a 50-nm particle only needs 108. This highlights the importance of optimizing both detection sensitivity and particle size to balance effective detection with safety.ConclusionThis computational model demonstrates the feasibility of using superparamagnetic nanoparticles in real-time, non-invasive diagnostic systems.https://www.frontiersin.org/articles/10.3389/fbioe.2024.1500756/fullcoilCOMSOLdiagnosticiron oxidemagnetic nanoparticlessuperparamagnetism |
| spellingShingle | Loïc Van Dieren Loïc Van Dieren Loïc Van Dieren Loïc Van Dieren Loïc Van Dieren Vlad Tereshenko Haïzam Oubari Haïzam Oubari Haïzam Oubari Yanis Berkane Yanis Berkane Jonathan Cornacchini Jonathan Cornacchini Filip Thiessen EF Filip Thiessen EF Filip Thiessen EF Filip Thiessen EF Curtis L. Cetrulo Curtis L. Cetrulo Curtis L. Cetrulo Curtis L. Cetrulo Korkut Uygun Korkut Uygun Alexandre G. Lellouch Alexandre G. Lellouch Alexandre G. Lellouch Alexandre G. Lellouch Alexandre G. Lellouch Alexandre G. Lellouch Computational modeling of superparamagnetic nanoparticle-based (affinity) diagnostics Frontiers in Bioengineering and Biotechnology coil COMSOL diagnostic iron oxide magnetic nanoparticles superparamagnetism |
| title | Computational modeling of superparamagnetic nanoparticle-based (affinity) diagnostics |
| title_full | Computational modeling of superparamagnetic nanoparticle-based (affinity) diagnostics |
| title_fullStr | Computational modeling of superparamagnetic nanoparticle-based (affinity) diagnostics |
| title_full_unstemmed | Computational modeling of superparamagnetic nanoparticle-based (affinity) diagnostics |
| title_short | Computational modeling of superparamagnetic nanoparticle-based (affinity) diagnostics |
| title_sort | computational modeling of superparamagnetic nanoparticle based affinity diagnostics |
| topic | coil COMSOL diagnostic iron oxide magnetic nanoparticles superparamagnetism |
| url | https://www.frontiersin.org/articles/10.3389/fbioe.2024.1500756/full |
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