Reyk Hillert

Design and evaluation of steganography for voice-over-IP

According to former results from (Dittmann et al., 2005) in this paper we summarize the design principles from the general approach and introduce extended experimental test results of a voice-over-IP (VoIP) framework including a steganographic channel based on (Dittmann et al., 2005), (Dittmann and Hesse, 2004), (Kraetzer et al., 2006) and (Vogel et al., 2006). We show that using this framework it is largely secure to transmit hidden messages during a VoIP session and demonstrate results with respect to perceptibility for music and speech data

Steganography and steganalysis in voice-over IP scenarios: operational aspects and first experiences with a new steganalysis tool set

Based on the knowledge and experiences from existing image steganalysis techniques, the overall objective of the paper is to evaluate existing audio steganography with a special focus on attacks in ad-hoc end-to-end media communications on the example of Voice over IP (VoIP) scenarios. One aspect is to understand operational requirements of recent steganographic techniques for VoIP applications. The other aspect is to elaborate possible steganalysis approaches applied to speech data. In particular we have examined existing VoIP applications with respect to their extensibility to steganographic algorithms. We have also paid attention to the part of steganalysis in PCM audio data which allows us to detect hidden communication while a running VoIP communication with the usage of the PCM codec. In our impelementation we use Joris Voice over IP library by Jori Liesenborgs (JVOIPLIB) that provides primitives for a voice over IP communication. Finally we show first results of our prototypic implementation which extents the common VoIP scenario by the new feature of steganography. We also show the results for our PCM steganalyzer framework that is able to detect this kind of hidden communication by using a set of 13 first and second order statistics.

Next-generation biomarkers based on 100-parameter functional super-resolution microscopy TIS.

Functional super-resolution (fSR) microscopy is based on the automated toponome imaging system (TIS). fSR-TIS provides insight into the myriad of different cellular functionalities by direct imaging of large subcellular protein networks in morphologically intact cells and tissues, referred to as the toponome. By cyclical fluorescence imaging of at least 100 molecular cell components, fSR-TIS overcomes the spectral limitations of fluorescence microscopy, which is the essential condition for the detection of protein network structures in situ/in vivo. The resulting data sets precisely discriminate between cell types, subcellular structures, cell states and diseases (fSR). With up to 16 bits per protein, the power of combinatorial molecular discrimination (PCMD) is at least 2(100) per subcellular data point. It provides the dimensionality necessary to uncover thousands of distinct protein clusters including their subcellular hierarchies controlling protein network topology and function in the one cell or tissue section. Here we review the technology and findings showing that functional protein networks of the cell surface in different cancers encompass the same hierarchical and spatial coding principle, but express cancer-specific toponome codes within that scheme (referred to as TIS codes). Findings suggest that TIS codes, extracted from large-scale toponome data, have the potential to be next-generation biomarkers because of their cell type and disease specificity. This is functionally substantiated by the observation that blocking toponome-specific lead proteins results in disassembly of molecular networks and loss of function.

Interlocking transcriptomics, proteomics and toponomics technologies for brain tissue analysis in murine hippocampus

We have correlated transcriptomics, proteomics and toponomics analyses of hippocampus tissue of inbred C57BL/6 mice to analyse the interrelationship of expressed genes and proteins at different levels of organization. We find that transcriptome and proteome levels of function as well as the topological organization of synaptic protein clusters, detected by toponomics at physiological sites of hippocampus CA3 region, are all largely conserved between different mice. While the number of different synaptic states, characterized by distinct synaptic protein clusters, is enormous (>155 000), these states together form synaptic networks defining distinct and mutually exclusive territories in the hippocampus tissue. The findings provide insight in the systems biology of gene expression on transcriptome, proteome and toponome levels of function in the same brain subregion. The approach will lay the ground for designing studies of neurodegeneration in mouse models and human brains.

Toponome imaging system in situ protein network mapping in normal and cancerous colon from the same patient reveals more than five-thousand cancer specific protein clusters and their subcellular annotation by using a three symbol code

In a proof of principle study, we have applied an automated fluorescence toponome imaging system (TIS) to examine whether TIS can find protein network structures, distinguishing cancerous from normal colon tissue present in a surgical sample from the same patient. By using a three symbol code and a power of combinatorial molecular discrimination (PCMD) of 2(21) per subcellular data point in one single tissue section, we demonstrate an in situ protein network structure, visualized as a mosaic of 6813 protein clusters (combinatorial molecular phenotype or CMPs), in the cancerous part of the colon. By contrast, in the histologically normal colon, TIS identifies nearly 5 times the number of protein clusters as compared to the cancerous part (32 009). By subcellular visualization procedures, we found that many cell surface membrane molecules were closely associated with the cell cytoskeleton as unique CMPs in the normal part of the colon, while the same molecules were disassembled in the cancerous part, suggesting the presence of dysfunctional cytoskeleton-membrane complexes. As expected, glandular and stromal cell signatures were found, but interestingly also found were potentially TIS signatures identifying a very restricted subset of cells expressing several putative stem cell markers, all restricted to the cancerous tissue. The detection of these signatures is based on the extreme searching depth, high degree of dimensionality, and subcellular resolution capacity of TIS. These findings provide the technological rationale for the feasibility of a complete colon cancer toponome to be established by massive parallel high throughput/high content TIS mapping.

Toponome mapping in prostate cancer: detection of 2000 cell surface protein clusters in a single tissue section and cell type specific annotation by using a three symbol code.

The toponome imaging technology MELC/TIS was applied to analyze prostate cancer tissue. By cyclical imaging procedures, we detected 2100 cell surface protein clusters in a single tissue section. This study provides the whole data set, a new kind of high dimensional data space, solely based on the structure-bound architecture of an in situ protein network, a putative fraction of the tissue code of prostate cancer. It is visualized as a colored mosaic composed of distinct protein clusters, together forming a motif expressed exclusively on the cell surface of neoplastic cells in prostate acini. Cell type specific expression of this motif, found in this preliminary study, suggests that high-throughput toponome analyses of a larger number of cases will provide insight into disease specific protein networks.

Toponomics and neurotoponomics: a new way to medical systems biology

The fluorescence robot imaging technology multi-epitope-ligand-cartography/toponome imaging system has revolutionized the field of proteomics/functional genomics, because it enables the investigator to locate and decipher functional protein networks, the toponome, consisting of hundreds of different proteins in a single cell or tissue section. The technology has been proven to solve key problems in biology and therapy research. It has uncovered a new cellular transdifferentiation mechanism of vascular cells giving rise to myogenic cells in situ and in vivo; a finding that has led to efficient cell therapy models of muscle disorders, and discovered a new target protein in sporadic amyotrophic lateral sclerosis by hierarchical protein network analysis, a finding that has been confirmed by a mouse knockout model. A lead target protein in tumor cells that controls cell polarization as a mechanism that is fundamental for migration and metastasis formation has also been uncovered, and new functional territories in the CNS defined by high-dimensional synaptic protein clusters have been unveiled. The technology can be effectively interlocked with genomics and proteomics to optimize time-to-market and the overall attrition rate of new drugs. This review outlines major proofs of principle with an emphasis on neurotoponomics.

Interactive, Graph-based Visual Analysis of High-dimensional, Multi-parameter Fluorescence Microscopy Data in Toponomics

In Toponomics, the function protein pattern in cells or tissue (the toponome) is imaged and analyzed for applications in toxicology, new drug development and patient-drug-interaction. The most advanced imaging technique is robot-driven multi-parameter fluorescence microscopy. This technique is capable of co-mapping hundreds of proteins and their distribution and assembly in protein clusters across a cell or tissue sample by running cycles of fluorescence tagging with monoclonal antibodies or other affinity reagents, imaging, and bleaching in situ. The imaging results in complex multi-parameter data composed of one slice or a 3D volume per affinity reagent. Biologists are particularly interested in the localization of co-occurring proteins, the frequency of co-occurrence and the distribution of co-occurring proteins across the cell. We present an interactive visual analysis approach for the evaluation of multi-parameter fluorescence microscopy data in toponomics. Multiple, linked views facilitate the definition of features by brushing multiple dimensions. The feature specification result is linked to all views establishing a focus+context visualization in 3D. In a new attribute view, we integrate techniques from graph visualization. Each node in the graph represents an affinity reagent while each edge represents two co-occurring affinity reagent bindings. The graph visualization is enhanced by glyphs which encode specific properties of the binding. The graph view is equipped with brushing facilities. By brushing in the spatial and attribute domain, the biologist achieves a better understanding of the function protein patterns of a cell. Furthermore, an interactive table view is integrated which summarizes unique fluorescence patterns. We discuss our approach with respect to a cell probe containing lymphocytes and a prostate tissue section.

Functional architecture of the cell nucleus: towards comprehensive toponome reference maps of apoptosis.

We have recently described the MELC/TIS fluorescence robot technology that is capable of colocalizing at least a hundred different molecular cell components in one cell. The technology reveals new hierarchical properties of protein network organisation, referred to as the toponome, in which topologically confined protein clusters are interlocked within the structural framework of the cell. In this study we have applied MELC/TIS to construct a three-dimensional toponome map of the cell nucleus of a single human hepatocyte undergoing apoptosis. The map reveals six different spatially separated toponome domains in the nuclear interior of one apoptotic cell. In the drive to decipher the apoptosis-specific molecular network on the single cell level, the present toponome map is a first milestone towards the construction of much larger maps addressing hundreds of molecular cell components across the stages of apoptosis.

Imaging cycler microscopy.

The article in PNAS by Gerdes et al. (1) adds to the evidence that spectral resolution limits of fluorescence microscopy can be overcome by reiterative cycles of tagging, imaging, and bleaching of fluorophores attached to ligands for target biomolecules. In fact, the robotic imaging cycler microscopes are based on this principle and have been used for decades (2⇓⇓–5). The current ready-to-use robotic Toponome Imaging System (TIS) for biomarker discovery and cell research can comap at least 100 molecules in individual cells and tissue sections and, because of its high functional resolution (<40 nm) (5), provides insights into their organization, including their supramolecular clusters.* Now Gerdes et al. offer a modified protocol using H2O …