ArticleSoft matter2011
Influence of Red Blood Cells on Nanoparticle Targeted Delivery in Microcirculation.
Article in Soft matter, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
55 citing papers in PubMed, 196 citations in OpenAlex.
- A ciliated intravascular soft millirobot for multimodal in-flow collective manipulation.Science advances · 2026Article
- Artificial intelligence-driven design and optimization of mitochondria-targeted nanocarriers for chronic heart failure.Frontiers in bioengineering and biotechnology · 2026Review
- Red Blood Cell-Induced Bacterial Margination Improves Microbial Hemoadsorption on Engineered Cell-Depleted Thrombi, Restoring Severe Bacteremia in Rats.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- The pathways for nanoparticle transport across tumour endothelium.Nature nanotechnology · 2025Article
- Navigating the brain: Harnessing endogenous cellular hitchhiking for targeting neoplastic and neuroinflammatory diseases.Asian journal of pharmaceutical sciences · 2025Review
- Design of nanoparticle-based systems for the systemic delivery of chemotherapeutics: Alternative potential routes via sublingual and buccal administration for systemic drug delivery.Drug delivery and translational research · 2024Review
- In situ cellular hitchhiking of nanoparticles for drug delivery.Advanced drug delivery reviews · 2024Review
- The flow of anisotropic nanoparticles in solution and in blood.Exploration (Beijing, China) · 2023Review
- Review
- Modeling of Red Blood Cells in Capillary Flow Using Fluid-Structure Interaction and Gas Diffusion.Cells · 2022Article
- Models of Shear-Induced Platelet Activation and Numerical Implementation With Computational Fluid Dynamics Approaches.Journal of biomechanical engineering · 2022Article
- A numerical study on drug deliveryNanoscale · 2021Article
- A Molecular Communications System for the Detection of Inflammatory Levels Related to COVID-19 Disease.IEEE transactions on molecular, biological, and multi-scale communications · 2021Article
- Elucidating the rheological implications of adding particles in blood.Rheologica acta · 2021Article
- Multiscale modeling of protein membrane interactions for nanoparticle targeting in drug delivery.Current opinion in structural biology · 2020Review
- Prediction of mechanical hemolysis in medical devices via a Lagrangian strain-based multiscale model.Artificial organs · 2020Article
- Endothelial Cell Targeting by cRGD-Functionalized Polymeric Nanoparticles under Static and Flow Conditions.Nanomaterials (Basel, Switzerland) · 2020Article
- Targeting Dysfunctional Vascular Endothelial Cells Using Immunoliposomes Under Flow Conditions.Cellular and molecular bioengineering · 2020Article
- Multiscale modeling of hemolysis during microfiltration.Microfluidics and nanofluidics · 2020Article
- A mathematical model to predict nanomedicine pharmacokinetics and tumor delivery.Computational and structural biotechnology journal · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Multifunctional nanomedicine holds considerable promise as the next generation of medicine that allows for targeted therapy with minimal toxicity. Most current studies on Nanoparticle (NP) drug delivery consider a Newtonian fluid with suspending NPs. However, blood is a complex biological fluid composed of deformable cells, proteins, platelets, and plasma. For blood flow in capillaries, arterioles and venules, the particulate nature of the blood needs to be considered in the delivery process. The existence of the cell-free-layer and NP-cell interaction will largely influence both the dispersion and binding rates, thus impact targeted delivery efficacy. In this paper, a particle-cell hybrid model is developed to model NP transport, dispersion, and binding dynamics in blood suspension. The motion and deformation of red blood cells is captured through the Immersed Finite Element Method. The motion and adhesion of individual NPs are tracked through Brownian adhesion dynamics. A mapping algorithm and an interaction potential function are introduced to consider the cell-particle collision. NP dispersion and binding rates are derived from the developed model under various rheology conditions. The influence of red blood cells, vascular flow rate, and particle size on NP distribution and delivery efficacy is characterized. A non-uniform NP distribution profile with higher particle concentration near the vessel wall is observed. Such distribution leads to over 50% higher particle binding rate compared to the case without RBC considered. The tumbling motion of RBCs in the core region of the capillary is found to enhance NP dispersion, with dispersion rate increases as shear rate increases. Results from this study contribute to the fundamental understanding and knowledge on how the particulate nature of blood influences NP delivery, which will provide mechanistic insights on the nanomedicine design for targeted drug delivery applications.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.