Predicting <i>in situ</i> nanoparticle behavior using multiple particle tracking and artificial neural networks

Curtis, Chad; McKenna, Mike; Pontes, Hugo; Toghani, Dorsa; Choe, Alex; Nance, Elizabeth

doi:10.1039/c9nr06327g

Cited by 21 publications

(22 citation statements)

References 37 publications

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“…It is well established that simulations can be highly useful in developing novel and smart nanomedicine systems. In this regard, many efforts have been devoted to exploiting Molecular Dynamics (MD) (31)(32)(33)(34)(35), Density Functional Theory(DFT) (36), and Machine Learning (37)(38)(39) in discovering emerging and smart drug nanocarriers. Shariatinia and Mazloom-Jalali (40) perused the graphene containing chitosan as a carrier of anticancer ifosfamide drug through MD, in which, the N-doped graphene/chitosan was suggested as an effective drug carrier.…”

Section: Introductionmentioning

confidence: 99%

Engineering the pH-Sensitivity of the Graphene and Carbon Nanotube Based Nanomedicines in Smart Cancer Therapy by Grafting Trimetyl Chitosan

et al. 2020

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Purpose The aim of this study was to introduce a smart and responsive drug carrier for Doxorubicin (DOX) and Paclitaxel (PAX) for desirable therapeutic application. Method Loading and releasing of DOX and PAX from smart and pH-sensitive functionalized single-walled carbon nanotube (SWCNTs) and graphene carriers have been simulated by molecular dynamics. The influences of chitosan polymer on proposed carriers have been studied, and both carriers were functionalized with carboxyl groups to improve the loading and releasing properties of the drugs. Results The results showed that DOX could be well adsorbed on both functionalized SWCNTs and graphene. In contrast, there was a weak electrostatic and Van der Waals interaction between both these drugs and carriers at cancerous tissues, which is highly favorable for cancer therapy. Adding trimethyl chitosan (TMC) polymer to carriers facilitated DOX release at acidic tissues. Furthermore, at blood pH, the PAX loaded on the functionalized SWCNTs carrier represented the highest dispersion of the drug while the DOX-graphene showed the highest concentration of the drug at a point. In addition, the mean-square displacement (MSD) results of PAX-graphene indicated that the PAX could be adsorbed quickly and be released slowly. Finally, functionalized graphene-TMC-PAX is a smart drug system with responsive behavior and controllable drug release, which are essential in cancer therapy. Conclusion Simultaneous application of the carboxyl group and TMC can optimize the pH sensitivity of the SWCNTs and graphene to prepare a novel and smart drug carrier for cancer therapy.

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Section: Introductionmentioning

confidence: 99%

Engineering the pH-Sensitivity of the Graphene and Carbon Nanotube Based Nanomedicines in Smart Cancer Therapy by Grafting Trimetyl Chitosan

et al. 2020

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“…A total of 39 features were computed, some based on trajectory geometry (aspect ratio and straightness, for example) and some based on traditional diffusion theory (anomalous diffusion exponent and MSD ratio). The list of trajectory features was adopted from previous literature (Curtis et al, 2019a) but scaled up by introducing additional, local-averaged features (Table S2). An XGBoost classifier was then trained on a subset of the age-dependent feature dataset.…”

Section: Xgboost Classifiers Provide Predictive Models For Age-dependmentioning

confidence: 99%

“…Additionally, there exist different algorithms that can be used for multiclass classification. Artificial neural networks represent a promising alternative, as they have already displayed an ability to accurately predict both nanoparticle properties like size and surface functionality, and environmental properties like gel stiffness and in vitro cell uptake status, when trained on trajectory feature datasets (Curtis et al, 2019a). Random forests, a form of ensemble decision trees, are another promising algorithm for classifications that exist along a continuum, having recently been applied to classifying neuroimaging data from Alzheimer's Disease patients (Sarica et al, 2017).…”

Section: Recent Work By Sigal Et Al Used a Stochastic Optical Reconsmentioning

confidence: 99%

“…Following euthanasia, brains were extracted, immersed in room temperature (22°C) dissection media, and cut into hemispheres with a razor blade. 300 µm-thick coronal slices were prepared from each hemisphere using a Mcllwain tissue chopper (Ted Pella, Redding, CA) (Curtis et al, 2019a). Briefly, individual slices were plated on 30 mm cell culture inserts in non-treated 6-well plates.…”

Section: Organotypic Hemispheric Brain Slice Preparationmentioning

confidence: 99%

“…The utility of this approach is already well documented. Wagner et al demonstrated the ability to predict motion type (confined, directed, anomalous, normal) using random forest classifiers trained on trajectory feature datasets (Wagner et al, 2017), and others have employed artificial neural networks to predict agarose gel stiffness and in vitro cell uptake of nanoparticles (Curtis et al, 2019a).…”

Section: Introductionmentioning

confidence: 99%

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Multiple particle tracking detects changes in brain extracellular matrix structure and predicts neurodevelopmental age

McKenna

Shackelford

Pontes

et al. 2020

Preprint

Self Cite

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Brain extracellular matrix (ECM) structure mediates many aspects of neuronal function. Probing changes in ECM structure could provide insights into aging and neurological disease. Herein, we demonstrate the ability to characterize changes in brain ECM structure using multiple particle tracking (MPT). MPT was carried out in organotypic rat brain slices to detect induced and naturally occurring changes in ECM structure. Induced degradation of neural ECM led to a significant increase in nanoparticle diffusive ability in the brain extracellular space. For structural changes that occur naturally during development, an inverse relationship existed between age and nanoparticle diffusion. Using the age-dependent dataset, we applied extreme gradient boosting (XGBoost) to generate models capable of classifying nanoparticle trajectories.Collectively, this work demonstrates the utility of MPT combined with machine learning for measuring changes in brain ECM structure and predicting associated complex features such as developmental age.

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Mapping Extracellular Space Features of Viral Encephalitis to Evaluate the Proficiency of Anti‐Viral Drugs

Wang,

Chen,

Wang

et al. 2024

Advanced Materials

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The extracellular space (ECS) is an important barrier against viral attack on brain cells, and dynamic changes in ECS microstructure characteristics are closely related to the progression of viral encephalitis in the brain and the efficacy of antiviral drugs. However, mapping the precise morphological and rheological features of the ECS in viral encephalitis is still challenging so far. Here, we developed a robust approach using single‐particle diffusional fingerprinting (SPDF) of quantum dots combined with machine learning to map ECS features in the brain and predict the efficacy of antiviral encephalitis drugs. Our results demonstrated that this approach can characterize the microrheology and geometry of the brain ECS at different stages of viral infection and identify subtle changes induced by different drug treatments. This approach provides a potential platform for drug proficiency assessment and is expected to offer a reliable basis for clinical translation of drugs.This article is protected by copyright. All rights reserved

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Predicting in situ nanoparticle behavior using multiple particle tracking and artificial neural networks

Abstract: Diffusion data obtained from multiple particle tracking of nanotherapeutically-relevant platforms can predict nanoparticle transport in living tissue.

Cited by 21 publications

References 37 publications

Engineering the pH-Sensitivity of the Graphene and Carbon Nanotube Based Nanomedicines in Smart Cancer Therapy by Grafting Trimetyl Chitosan

Engineering the pH-Sensitivity of the Graphene and Carbon Nanotube Based Nanomedicines in Smart Cancer Therapy by Grafting Trimetyl Chitosan

Multiple particle tracking detects changes in brain extracellular matrix structure and predicts neurodevelopmental age

Mapping Extracellular Space Features of Viral Encephalitis to Evaluate the Proficiency of Anti‐Viral Drugs

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