Rapid statistical discrimination of fluorescence images of T cell receptors on immobilizing surfaces with different coating conditions

Abstract

The spatial organization of T cell receptors (TCRs) correlates with membrane-associated signal amplification, dispersion, and regulation during T cell activation. Despite its potential clinical importance, quantitative analysis of the spatial arrangement of TCRs from standard fluorescence images remains difficult. Here, we report Statistical Classification Analyses of Membrane Protein Images or SCAMPI as a technique capable of analyzing the spatial arrangement of TCRs on the plasma membrane of T cells. We leveraged medical image analysis techniques that utilize pixel-based values. We transformed grayscale pixel values from fluorescence images of TCRs into estimated model parameters of partial differential equations. The estimated model parameters enabled an accurate classification using linear discrimination techniques, including Fisher Linear Discriminant (FLD) and Logistic Regression (LR). In a proof-of-principle study, we modeled and discriminated images of fluorescently tagged TCRs from Jurkat T cells on uncoated cover glass surfaces (Null) or coated cover glass surfaces with either positively charged poly-L-lysine (PLL) or TCR cross-linking anti-CD3 antibodies (OKT3). Using 80 training images and 20 test images per class, our statistical technique achieved 85% discrimination accuracy for both OKT3 versus PLL and OKT3 versus Null conditions. The run time of image data download, model construction, and image discrimination was 21.89 s on a laptop computer, comprised of 20.43 s for image data download, 1.30 s on the FLD-SCAMPI analysis, and 0.16 s on the LR-SCAMPI analysis. SCAMPI represents an alternative approach to morphology-based qualifications for discriminating complex patterns of membrane proteins conditioned on a small sample size and fast runtime. The technique paves pathways to characterize various physiological and pathological conditions using the spatial organization of TCRs from patient T cells.

Synthesis of mesoporous SiO2 coating containing chlorine phenol–formaldehyde resin (Cl–PFR) composites for effective fingerprint detection

“…[27][28][29][30] For example, red-emissive conjugated oligomer/silica hybrid NPs prepared by Yang's [31,32] team improved the fluorescence quantum yield and enhanced affinity for the residual fingerprint components due to the combination with silica NPs, which showed a high affinity for fingerprint secretions and produced fluorescent images with high resolution and uniquely detailed features that have received much attention. [33,34] Ultrabright fluorescent silica nanoparticles embedded with conjugated oligomers prepared by Zhang's [35,36] group also showed good photostability under UV light irradiation after being doped with SiO 2 nanospheres, which had excellent resistance to a wide range of pH values, temperatures, and solvents, therefore providing protection from external disturbances. The resulting SiO 2 nanoparticles were found to be effective reagents for optical/fluorescence detection of LFPs.…”