Improved accuracy in DFS pattern interpretation using a novel HEp-2 ELITE system.

INTRODUCTION/OBJECTIVES: Accurate interpretation of DFS70 (dense fine speckled 70) and mixed antinuclear antibodies (ANAs) patterns can be challenging using conventional HEp-2 immunofluorescence (IIF) method. We evaluated a novel HEp-2 IIF substrate (HEp-2 ELITE/DFS70-KO) composed of a mixture of engineered HEp-2 devoid of the DFS70 autoantigen and conventional HEp-2 cells. The study assessed the utility of the new substrate in ANA screening and its advantages. METHOD: One thousand and five consecutive routine samples sent for ANA screening were tested on both standard HEp-2 and the HEp-2 ELITE DFS70 KO substrates (ImmuGlo ANA HEp-2 and HEp-2 ELITE/DFS70-KO, Trinity Biotech, Buffalo, NY). Anti-DFS70 antibody specificity was additionally determined by immunoblot (IB). Clinical and serological data were included in the analysis of the overall impact of the novel HEp-2 substrate on DFS pattern interpretation. RESULTS: Of the 22 cases suspected as positive for DFS pattern alone or in combination with homogeneous or speckled patterns on conventional HEp-2 cells, 17 were interpreted with a higher accuracy using the new HEp-2 ELITE method as positive for DFS70 (monospecific DFS70 (10), mixed DFS70 (7)), speckled (3), and DFS (2) patterns. CONCLUSIONS: The new substrate was not only useful in deciphering unclear mixed ANA patterns but also highly sensitive in detecting DFS70 pattern in comparison to the DFS70 positivity obtained using IB.

Automated matching of genomic structures in microscopic images of living cells using an information theoretic approach.

Advances in microscopic imaging technology have revolutionized biology in recent years by enabling the study of dynamic processes inside living cells. Time-lapse microscopy produces large numbers of sequential images of living cells taken over time. In this paper we describe the novel approaches we have developed to automate and introduce high accuracy to the process of identifying genomic structures in living cells and matching them between consecutive time-points. We derive control points from landmarks within the structures and use the Kulback-Leibler divergence as an information-theoretic approach to correctly resolve potential close matches within the iterative closest point (ICP) algorithm. We also describe the steps needed to extend our techniques to analyze three dimensional voxel images. The approaches we describe are widely applicable in the analysis of timelapse microscopy data.

Fractal analysis of replication site images of the human cell nucleus.

Epi-fluorescent microscopic images of the mammalian cell nucleus taken during the early, mid and late S (synthetic) phase of the cell cycle suggest that the mass of replicating DNA that belong to the cell nucleus can be characterized as a space filling fractal curve. We reason from a biological standpoint and our understanding of naturally occurring fractals that our microscopic images reveal portions of the spatially complex DNA molecule and present methods for computing the fractal dimensions of the images. Results presented here suggest that our methodology based on fractal properties can distinguish replication of DNA occurring in early versus mid or late S-phase.