Publications

18 Publications visible to you, out of a total of 18

Abstract (Expand)

Intestinal stem cells (ISCs) require well-defined signals from their environment in order to carry out their specific functions. Most of these signals are provided by neighboring cells that form a stem cell niche, whose shape and cellular composition self-organize. Major features of this self-organization can be studied in ISC-derived organoid culture. In this system, manipulation of essential pathways of stem cell maintenance and differentiation results in well-described growth phenotypes. We here provide an individual cell-based model of intestinal organoids that enables a mechanistic explanation of the observed growth phenotypes. In simulation studies of the 3D structure of expanding organoids, we investigate interdependences between Wnt- and Notch-signaling which control the shape of the stem cell niche and, thus, the growth pattern of the organoids. Similar to in vitro experiments, changes of pathway activities alter the cellular composition of the organoids and, thereby, affect their shape. Exogenous Wnt enforces transitions from branched into a cyst-like growth pattern; known to occur spontaneously during long term organoid expansion. Based on our simulation results, we predict that the cyst-like pattern is associated with biomechanical changes of the cells which assign them a growth advantage. The results suggest ongoing stem cell adaptation to in vitro conditions during long term expansion by stabilizing Wnt-activity. Our study exemplifies the potential of individual cell-based modeling in unraveling links between molecular stem cell regulation and 3D growth of tissues. This kind of modeling combines experimental results in the fields of stem cell biology and cell biomechanics constituting a prerequisite for a better understanding of tissue regeneration as well as developmental processes.

Authors: T. Thalheim, M. Quaas, M. Herberg, U. D. Braumann, C. Kerner, M. Loeffler, G. Aust, J. Galle

Date Published: 15th Jan 2018

Publication Type: Not specified

Human Diseases: colonic disease

Abstract (Expand)

As revealed by optical coherence tomography (OCT), the shape of the fovea may vary greatly among individuals. However, none of the hitherto available mathematical descriptions comprehensively reproduces all individual characteristics such as foveal depth, slope, naso-temporal asymmetry, and others. Here, a novel mathematical approach is presented to obtain a very accurate model of the complete 3D foveal surface of an individual, by utilizing recent developments in OCT. For this purpose, a new formula was developed serving as a simple but very flexible way to represent a given fovea. An extensive description of the used model parameters, as well as, of the complete method of reconstructing a foveal surface from OCT data, is presented. Noteworthy, the formula analytically provides characteristic foveal parameters and thus allows for extensive quantification. The present approach was verified on 432 OCT scans and has proved to be able to capture the whole range of asymmetric foveal shapes with high accuracy (i.e. a mean fit error of 1.40 mum).

Authors: P. Scheibe, A. Lazareva, U. D. Braumann, A. Reichenbach, P. Wiedemann, M. Francke, F. G. Rauscher

Date Published: 3rd Dec 2013

Publication Type: Not specified

Human Diseases: eye disease

Abstract (Expand)

Drug addiction is a chronic, relapsing disease caused by neurochemical and molecular changes in the brain. In this human autopsy study qualitative and quantitative changes of glial fibrillary acidic protein (GFAP)-positive astrocytes in the hippocampus of 26 lethally intoxicated drug addicts and 35 matched controls are described. The morphological characterization of these cells reflected alterations representative for astrogliosis. But, neither quantification of GFAP-positive cells nor the Western blot analysis indicated statistical significant differences between drug fatalities versus controls. However, by semi-quantitative scoring a significant shift towards higher numbers of activated astrocytes in the drug group was detected. To assess morphological changes quantitatively, graph-based representations of astrocyte morphology were obtained from single cell images captured by confocal laser scanning microscopy. Their underlying structures were used to quantify changes in astroglial fibers in an automated fashion. This morphometric analysis yielded significant differences between the investigated groups for four different measures of fiber characteristics (Euclidean distance, graph distance, number of graph elements, fiber skeleton distance), indicating that, e.g., astrocytes in drug addicts on average exhibit significant elongation of fiber structures as well as two-fold increase in GFAP-positive fibers as compared with those in controls. In conclusion, the present data show characteristic differences in morphology of hippocampal astrocytes in drug addicts versus controls and further supports the involvement of astrocytes in human pathophysiology of drug addiction. The automated quantification of astrocyte morphologies provides a novel, testable way to assess the fiber structures in a quantitative manner as opposed to standard, qualitative descriptions.

Authors: M. Weber, N. Scherf, T. Kahl, U. D. Braumann, P. Scheibe, J. P. Kuska, R. Bayer, A. Buttner, H. Franke

Date Published: 15th Mar 2013

Publication Type: Not specified

Human Diseases: heroin dependence

Abstract (Expand)

PURPOSE: Prostate cancer is routinely graded according to the Gleason grading scheme. This scheme is predominantly based on the textural appearance of aberrant glandular structures. Gleason grade is difficult to standardize and often leads to discussion due to interrater and intrarater disagreement. Thus, we investigated whether digital image based automated quantitative histomorphometry could be used to achieve a more standardized, reproducible classification outcome. MATERIALS AND METHODS: In a proof of principle study we developed a method to evaluate digitized histological images of single prostate cancer regions in hematoxylin and eosin stained sections. Preprocessed color images were subjected to color deconvolution, followed by the binarization of obtained hematoxylin related image channels. Highlighted neoplastic epithelial gland related objects were morphometrically assessed by a classifier based on 2 calculated quantitative and objective geometric measures, that is inverse solidity and inverse compactness. The procedure was then applied to the prostate cancer probes of 125 patients. Each probe was independently classified for Gleason grade 3, 4 or 5 by an experienced pathologist blinded to image analysis outcome. RESULTS: Together inverse compactness and inverse solidity were adequate discriminatory features for a powerful classifier that distinguished Gleason grade 3 from grade 4/5 histology. The classifier was robust on sensitivity analysis. CONCLUSIONS: Results suggest that quantitative and interpretable measures can be obtained from image based analysis, permitting algorithmic differentiation of prostate Gleason grades. The method must be validated in a large independent series of specimens.

Authors: M. Loeffler, L. Greulich, P. Scheibe, P. Kahl, Z. Shaikhibrahim, U. D. Braumann, J. P. Kuska, N. Wernert

Date Published: 20th Mar 2012

Publication Type: Not specified

Human Diseases: prostate cancer

Abstract (Expand)

AIMS: Infrared microspectroscopy (IR-MSP) has been proposed for automated histological tissue differentiation of unstained specimens based on chemical analysis of cell and extracellular constituents. This study aimed to determine the accuracy of IR-MSP-based histopathology of cervical carcinoma sections with complex tissue architecture under practically relevant testing conditions. METHODS AND RESULTS: In total, 46 regions of interest, covering an area of almost 50 mm(2) on sections derived from paraffin-embedded tissue of radical hysterectomy specimens, were analysed by IR-MSP (nominal resolution ~4.2 mum). More than 2.8 million pixel spectra that were processed using fuzzy c-means clustering followed by hierarchical cluster analysis permitted image segmentation regarding different biochemical properties. Linear image registration was applied to compare these segmentation results with manual labelling on haematoxylin and eosin-stained references (resolution ~0.7 mum). For recognition of nine tissue types, sensitivities were 42-91% and specificities were 79-100%, mostly being affected by peritumoral inflammatory responses. Algorithmic variation of the outline of dysplasia and carcinoma revealed a spatial preference of false values in tissue transition areas. CONCLUSIONS: This imaging technique has potential as a new method for tissue characterization; however, the recognition accuracy does not justify a pathologist-independent tissue analysis, and the application is only possible in combination with concomitant conventional histopathology.

Authors: J. Einenkel, U. D. Braumann, W. Steller, H. Binder, L. C. Horn

Date Published: 1st Mar 2012

Publication Type: Not specified

Human Diseases: cervical cancer

Abstract (Expand)

BACKGROUND: Analyses of the pore size distribution in 3D matrices such as the cell-hydrogel interface are very useful when studying changes and modifications produced as a result of cellular growth and proliferation within the matrix, as pore size distribution plays an important role in the signaling and microenvironment stimuli imparted to the cells. However, the majority of the methods for the assessment of the porosity in biomaterials are not suitable to give quantitative information about the textural properties of these nano-interfaces. FINDINGS: Here, we report a methodology for determining pore size distribution at the cell-hydrogel interface, and the depth of the matrix modified by cell growth by entrapped HepG(2) cells in microcapsules made of 0.8% and 1.4% w/v alginate. The method is based on the estimation of the shortest distance between two points of the fibril-like network hydrogel structures using image analysis of TEM pictures. Values of pore size distribution determined using the presented method and those obtained by nitrogen physisorption measurements were compared, showing good agreement. A combination of these methodologies and a study of the cell-hydrogel interface at various cell culture times showed that after three days of culture, HepG(2) cells growing in hydrogels composed of 0.8% w/v alginate had more coarse of pores at depths up to 40 nm inwards (a phenomenon most notable in the first 20 nm from the interface). This coarsening phenomenon was weakly observed in the case of cells cultured in hydrogels composed of 1.4% w/v alginate. CONCLUSIONS: The method purposed in this paper allows us to obtain information about the radial deformation of the hydrogel matrix due to cell growth, and the consequent modification of the pore size distribution pattern surrounding the cells, which are extremely important for a wide spectrum of biotechnological, pharmaceutical and biomedical applications.

Authors: A. Leal-Egana, U. D. Braumann, A. Diaz-Cuenca, M. Nowicki, A. Bader

Date Published: 27th May 2011

Publication Type: Not specified

Abstract (Expand)

Basal cell carcinoma (BCC) is the most common malignant skin cancer. For a deeper insight into the specific growth patterns of the tumorous tissue in BCC, we have focused on the development of a novel automated image-processing chain for 3D reconstruction of BCC using histopathological serial sections. For fully automatic delineation of the tumor within the tissue, we apply a fuzzy c-means segmentation method. We used a novel multi-grid form of the non-linear registration introduced by Braumann and Kuska in 2005 effectively suppressing registration runs into local minima (possibly caused by diffuse nature of the tumor). Our method was successfully applied in a proof-of-principle study for automated reconstruction.

Authors: P. Scheibe, U. D. Braumann, J. P. Kuska, M. Loffler, J. C. Simon, U. Paasch, T. Wetzig

Date Published: 1st Jul 2010

Publication Type: Not specified

Human Diseases: basal cell carcinoma

Powered by
(v.1.13.0-master)
Copyright © 2008 - 2021 The University of Manchester and HITS gGmbH
Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig

By continuing to use this site you agree to the use of cookies