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Updated: Apr 23, 2026

Methods for Quantitative Detection of Antibody-induced Complement Activation on Red Blood Cells

Methods for Quantitative Detection of Antibody-induced Complement Activation on Red Blood Cells

Published on: January 29, 2014

Physicochemical signatures of nanoparticle-dependent complement activation.

Dennis G Thomas¹, Satish Chikkagoudar¹, Alejandro Heredia-Langer²

¹Knowledge Discovery and Informatics, Pacific Northwest National Laboratory, Richland, WA 99352, USA.

Computational Science & Discovery

|September 26, 2014

Summary

This summary is machine-generated.

Physicochemical properties of nanoparticles predict complement activation. This finding aids in designing safer nanoparticles for therapeutic and imaging applications by understanding their immune response.

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Last Updated: Apr 23, 2026

Methods for Quantitative Detection of Antibody-induced Complement Activation on Red Blood Cells

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Published on: January 29, 2014

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Advanced Compositional Analysis of Nanoparticle-polymer Composites Using Direct Fluorescence Imaging

Advanced Compositional Analysis of Nanoparticle-polymer Composites Using Direct Fluorescence Imaging

Published on: July 19, 2016

Area of Science:

Biomaterials Science
Immunology
Nanotechnology

Background:

Nanoparticles offer therapeutic and imaging potential but can trigger adverse immune responses via complement activation.
Understanding nanoparticle-complement interactions is crucial for safe clinical translation.

Purpose of the Study:

To develop a predictive model for nanoparticle-dependent complement activation.
To identify key nanoparticle physicochemical properties influencing complement response.

Main Methods:

Utilized an in vitro hemolysis assay to measure serum complement activity of perfluorocarbon nanoparticles.
Applied a decision tree learning algorithm to analyze assay data and derive predictive rules.

Main Results:

Identified nanoparticle size, polydispersity index, zeta potential, and surface ligand density as key predictors.
The decision tree model effectively estimated nanoparticle-dependent complement activation based on these properties.

Conclusions:

Physicochemical properties are reliable descriptors for predicting nanoparticle-induced complement activation.
This predictive framework can guide the rational design of safer nanoparticles for biomedical applications.