automated force volume image processing for biological samples自动化的体积力生物样本图像处理.pdf

Automated Force Volume Image Processing for Biological Samples 1. 2. 2 ´ ˆ 3 2 ´ Pavel Polyakov , Charles Soussen , Junbo Duan , Jerome F. L. Duval , David Brie *, Gregory Francius1* ´ ` 1 Laboratoire de Chimie Physique et Microbiologie pour l’Environnement, LCPME, UMR 7564, Nancy-Universite, CNRS, Vandoeuvre les Nancy, France, 2 Centre de ´ ` ´ Recherche en Automatique de Nancy, CRAN, UMR 7039, Nancy-Universite, CNRS, Vandoeuvre les Nancy, France, 3 Laboratoire Environnement et Mineralurgie, LEM, UMR ´ ` 7569, Nancy-Universite, CNRS, Vandoeuvre les Nancy, France Abstract Atomic force microscopy (AFM) has now become a powerful technique for investigating on a molecular level, surface forces, nanomechanical properties of deformable particles, biomolecular interactions, kinetics, and dynamic processes. This paper specifically focuses on the analysis of AFM force curves collected on biological systems, in particular, bacteria. The goal is to provide fully automated tools to achieve theoretical interpretation of force curves on the basis of adequate, available physical models. In this respect, we propose two algorithms, one for the processing of approach force curves and another for the quantitative analysis of retraction force curves. In the former, electrostatic interactions prior to contact between AFM probe and bacterium are accounted for and mechanical interactions operating after