Engineering the retention of coloured latex and red blood cells for paper agglutination diagnostics
Year: 2025
Type: article
Abstract: HYPOTHESIS: A key challenge in engineering high-sensitivity paper-based agglutination assays is selecting the paper substrate for efficient separation of analyte-induced aggregates from unbound bio-colloids/particles. Identification of such a paper can be done by measuring the retention efficiency of particles of different sizes; however, this requires an understanding of the filtration and interfacial mechanism(s) involved. Here, we test the hypothesis that size exclusion is the dominant mechanism for the filtration of bio-colloids/particles in diagnostic paper materials. EXPERIMENTS: We report a reproducible methodology to determine the effective pore cut-off size of paper by measuring the retention efficiency of latex particles on papers. Suspensions of latex varying in size (0.5-30 μm), along with reagent red blood cells (RRBCs), were filtered through paper under controlled conditions and their retention was quantified by image analysis. Experimental retention was correlated with DLVO interaction energy calculations between bead and paper. Retention of reagent red blood cells (RRBCs) used for blood typing was compared with 8 μm red beads. FINDINGS: The effective pore cut-off size of the designed diagnostic papers was found to be 20 μm. Size exclusion is not the dominant retention mechanism in paper filtration processes for the smaller colloids (0.5 μm) for Whatman and diagnostic papers. The retention efficiency of polystyrene beads measured on diagnostic papers increased linearly with particle size with saturation effect for the larger particles. Red blood cells (RBC) have a much lower retention efficiency than the equivalent 8 μm beads, highlighting the important effects of particle elasticity and shape.
Authors: Anuragmani Tripathi, Simon Corrie, Gil Garnier
Institution: Monash University
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,470
OpenAlex ID: W4412044448