Gerlind Herberich

Measuring the regulation of keratin filament network dynamics

The organization of the keratin intermediate filament cytoskeleton is closely linked to epithelial function. To study keratin network plasticity and its regulation at different levels, tools are needed to localize and measure local network dynamics. In this paper, we present image analysis methods designed to determine the speed and direction of keratin filament motion and to identify locations of keratin filament polymerization and depolymerization at subcellular resolution. Using these methods, we have analyzed time-lapse fluorescence recordings of fluorescent keratin 13 in human vulva carcinoma-derived A431 cells. The fluorescent keratins integrated into the endogenous keratin cytoskeleton, and thereby served as reliable markers of keratin dynamics. We found that increased times after seeding correlated with down-regulation of inward-directed keratin filament movement. Bulk flow analyses further revealed that keratin filament polymerization in the cell periphery and keratin depolymerization in the more central cytoplasm were both reduced. Treating these cells and other human keratinocyte-derived cells with EGF reversed all these processes within a few minutes, coinciding with increased keratin phosphorylation. These results highlight the value of the newly developed tools for identifying modulators of keratin filament network dynamics and characterizing their mode of action, which, in turn, contributes to understanding the close link between keratin filament network plasticity and epithelial physiology.

Analysis of length and orientation of microtubules in wide-field fluorescence microscopy

In this paper we present a novel approach for the analysis of microtubules in wide-field fluorescence microscopy. Microtubules are flexible elongated structures and part of the cytoskeleton, a cytoplasmic scaffolding responsible for cell stability and motility. The method allows for precise measurements of microtubule length and orientation under different conditions despite a high variability of image data and in the presence of artefacts. Application of the proposed method to demonstrate the effect of the protein GAR22 on the rate of polymerisation of microtubules illustrates the potential of our approach.

Segmentation and Detection of Nuclei in Silver Stained Cell Specimens for Early Cancer Diagnosis

For successful cure, cancer has to be detected as early as possible. Since cancer starts from a single cell, this can best be done using cytopathological methods. One important diagnostically relevant measure is the proliferation rate of the cells, which can be estimated from segmented silver stained nuclei. However, the microscopy images of silver stained specimens vary strongly in intensity and contrast and are furthermore compromised by an overall texture. We show that a precise segmentation of the nuclei is possible using a two-step approach. First, an oversegmentation with the mean shift algorithm is obtained. In a second step, these regions are merged to objects, guided by a suitable shape model, viz an ellipse, but simultaneously allowing deviations from this shape model. The segmentation results are compared to a gold standard of 8617 nuclei from 23 specimens of the thyroid gland, achieving a mean areal segmentation error of DeltaA macrnucleus = 12mum2 per nucleus.

Signal and noise modeling in confocal laser scanning fluorescence microscopy

Fluorescence confocal laser scanning microscopy (CLSM) has revolutionized imaging of subcellular structures in biomedical research by enabling the acquisition of 3D time-series of fluorescently-tagged proteins in living cells, hence forming the basis for an automated quantification of their morphological and dynamic characteristics. Due to the inherently weak fluorescence, CLSM images exhibit a low SNR. We present a novel model for the transfer of signal and noise in CLSM that is both theoretically sound as well as corroborated by a rigorous analysis of the pixel intensity statistics via measurement of the 3D noise power spectra, signal-dependence and distribution. Our model provides a better fit to the data than previously proposed models. Further, it forms the basis for (i) the simulation of the CLSM imaging process indispensable for the quantitative evaluation of CLSM image analysis algorithms, (ii) the application of Poisson denoising algorithms and (iii) the reconstruction of the fluorescence signal.

Fluorescence microscopic imaging and image analysis of the cytoskeleton

Cell stability and motility depends on a complex dynamic cytoplasmic scaffolding called the cytoskeleton. It is composed of actin filaments, intermediate filaments and microtubules, and interacts with neighbouring cells and the extracellular matrix via specialized adhesion sites - multimolecular complexes responsible for the transmission of mechanical force and regulatory signals. The dynamic behaviour of these subcellular structures in living cells can be analysed by fluorescence microscopy yielding series of 2D or 3D images. Towards a quantitative analysis, we present methods for the segmentation and motion estimation of cytoskeletal filaments as well as for the tracking of adhesion sites, allowing the quantification of cytoskeletal dynamics under different conditions.

Proving Correctness of an Efficient Abstraction for Interrupt Handling

This paper presents an approach to the efficient abstraction of interrupt handling in microcontroller systems. Such systems usually operate in uncertain environments, giving rise to a high degree of nondeterminism in the corresponding formal models, which in turn aggravates the state explosion problem. Careful handling of nondeterminism is therefore crucial for obtaining efficient model checking tools. Here, we support this goal by developing a formal computation model and an abstraction method, called interrupt nondeterminism, which instantiates nondeterministic values only if and when this is required by the application code. It is shown how this symbolic technique can be integrated into our explicit CTL model checking tool [mc]square by introducing lazy states. A lazy state consists of explicit and symbolic parts and therefore, represents several concrete states. With regard to interrupt handling, we also give a simulation relation between the concrete and the abstract state space, thus establishing the correctness of our technique. Furthermore, a case study is presented in which three different programs are used to demonstrate the effectiveness of our method.

3D motion analysis of keratin filaments in living cells

We present a novel and efficient approach for 3D motion estimation of keratin intermediate filaments in vitro. Keratin filaments are elastic cables forming a complex scaffolding within epithelial cells. To understand the mechanisms of filament formation and network organisation under physiological and pathological conditions, quantitative measurements of dynamic network alterations are essential. Therefore we acquired time-lapse series of 3D images using a confocal laser scanning microscope. Based on these image series, we show that a dense vector field can be computed such that the displacements from one frame to the next can be determined. Our method is based on a two-step registration process: First, a rigid pre-registration is applied in order to compensate for possible global cell movement. This step enables the subsequent nonrigid registration to capture only the sought local deformations of the filaments. As the transformation model of the deformable registration algorithm is based on Free Form Deformations, it is well suited for modeling filament network dynamics. The optimization is performed using efficient linear programming techniques such that the huge amount of image data of a time series can be efficiently processed. The evaluation of our results illustrates the potential of our approach.

Chromatinmuster-basierte Zellklassifizierung für die DNS-Bildzytometrie an Mundschleimhaut-Abstrichen

Mit zytopathologischen Methoden kann Krebs sehr fruh schon anhand geringfugiger Normabweichungen in einzelnen Zellen erkannt werden. Nachteil ist oft der derzeit benotigte Zeitaufwand eines Zytopathologen, der insbesondere einen Einsatz als Screening-Verfahren ausschliesst. Eine wichtige zytologische Diagnosemethode ist die DNS-Bildzytometrie. Um deren Zeitaufwand zu reduzieren, mussen fur die Messung relevante Zellen automatisch detektiert werden. Fur Epithelien der Mundschleimhaut vergleichen wir daher verschiedene Varianten des k-Nachste-Nachbarn-Klassifikators (kNN), um zwischen sicher gesunden und krebsverdachtigen Zellbildern zu unterscheiden. Geeignete Merkmalskombinationen wurden durch das Floating-Search-Verfahren ausgewahlt.