Michael Handler

MALDI-MS tissue imaging identification of biliverdin reductase B overexpression in prostate cancer

UNLABELLEDnNew biomarkers are needed to improve the specificity of prostate cancer detection and characterisation of individual tumors. In a proteomics profiling approach using MALDI-MS tissue imaging on frozen tissue sections, we identified discriminating masses. Imaging analysis of cancer, non-malignant benign epithelium and stromal areas of 15 prostatectomy specimens in a test and 10 in a validation set identified characteristic m/z peaks for each tissue type, e.g. m/z 10775 for benign epithelial, m/z 6284 and m/z 6657.5 for cancer and m/z 4965 for stromal tissue. A 10-fold cross-validation analysis showed highest discriminatory ability to separate tissue types for m/z 6284 and m/z 6657.5, both overexpressed in cancer, and a multicomponent mass peak cluster at m/z 10775-10797.4 overexpressed in benign epithelial tissue. ROC AUC values for these three masses ranged from 0.85 to 0.95 in the discrimination of malignant and non-malignant tissue. To identify the underlying proteins, prostate whole tissue extract was separated by nano-HPLC and subjected to MALDI TOF/TOF analysis. Proteins in fractions containing discriminatory m/z masses were identified by MS/MS analysis and candidate marker proteins subsequently validated by immunohistochemistry (IHC). Biliverdin reductase B (BLVRB) turned out to be overexpressed in PCa tissue.nnnBIOLOGICAL SIGNIFICANCEnIn this study on cryosections of radical prostatectomies of prostate cancer patients, we performed a MALDI-MS tissue imaging analysis and a consecutive protein identification of significant m/z masses by nano-HPLC, MALDI TOF/TOF and MS/MS analysis. We identified BLVRB as a potential biomarker in the discrimination of PCa and benign tissue, also suggesting BVR as a feasible therapeutic target.

Profiling the human response to physical exercise: a computational strategy for the identification and kinetic analysis of metabolic biomarkers

BackgroundIn metabolomics, biomarker discovery is a highly data driven process and requires sophisticated computational methods for the search and prioritization of novel and unforeseen biomarkers in data, typically gathered in preclinical or clinical studies. In particular, the discovery of biomarker candidates from longitudinal cohort studies is crucial for kinetic analysis to better understand complex metabolic processes in the organism during physical activity.FindingsIn this work we introduce a novel computational strategy that allows to identify and study kinetic changes of putative biomarkers using targeted MS/MS profiling data from time series cohort studies or other cross-over designs. We propose a prioritization model with the objective of classifying biomarker candidates according to their discriminatory ability and couple this discovery step with a novel network-based approach to visualize, review and interpret key metabolites and their dynamic interactions within the network. The application of our method on longitudinal stress test data revealed a panel of metabolic signatures, i.e., lactate, alanine, glycine and the short-chain fatty acids C2 and C3 in trained and physically fit persons during bicycle exercise.ConclusionsWe propose a new computational method for the discovery of new signatures in dynamic metabolic profiling data which revealed known and unexpected candidate biomarkers in physical activity. Many of them could be verified and confirmed by literature. Our computational approach is freely available as R package termed BiomarkeR under LGPL via CRAN http://cran.r-project.org/web/packages/BiomarkeR/.

A Cellular Automaton Framework for Infectious Disease Spread Simulation

In this paper, a cellular automaton framework for processing the spatiotemporal spread of infectious diseases is presented. The developed environment simulates and visualizes how infectious diseases might spread, and hence provides a powerful instrument for health care organizations to generate disease prevention and contingency plans. In this study, the outbreak of an avian flu like virus was modeled in the state of Tyrol, and various scenarios such as quarantine, effect of different medications on viral spread and changes of social behavior were simulated. The proposed framework is implemented using the programming language Java. The set up of the simulation environment requires specification of the disease parameters and the geographical information using a population density colored map, enriched with demographic data. The results of the numerical simulations and the analysis of the computed parameters will be used to get a deeper understanding of how the disease spreading mechanisms work, and how to protect the population from contracting the disease. Strategies for optimization of medical treatment and vaccination regimens will also be investigated using our cellular automaton framework. In this study, six different scenarios were simulated. It showed that geographical barriers may help to slow down the spread of an infectious disease, however, when an aggressive and deadly communicable disease spreads, only quarantine and controlled medical treatment are able to stop the outbreak, if at all.

Alterations of field potentials in isotropic cardiomyocyte cell layers induced by multiple endogenous pacemakers under normal and hypothermal conditions.

The use of autonomous contracting randomly grown cardiomyocyte monolayers cultivated on microelectrode arrays (MEAs) represents an accepted experimental setting for preclinical experimental research in the field of cardiac electrophysiology. A dominant pacemaker forces a monolayer to adhere to a regular and synchronized contraction. Randomly distributed multiple pacemakers interfere with this dominant center, resulting in more or less frequent changes of propagation direction. This study aims to characterize the impact of changing propagation directions at single electrodes of the MEA on the four intrinsic parameters of registered field potentials (FPs) FPrise, FPMIN, FPpre, and FPdur and conduction velocity (CV) under normal and hypothermal conditions. Primary cultures of chicken cardiomyocytes (n = 18) were plated directly onto MEAs and FPs were recorded in a temperature range between 37 and 29°C. The number and spatiotemporal distribution of biological and artificial pacemakers of each cell layer inside and outside of the MEA registration area were evaluated using an algorithm developed in-house. In almost every second myocardial cell layer, interfering autonomous pacemakers were detected at stable temperatures, showing random spatial distributions with similar beating rates. Additionally, a temperature-dependent change of the dominant pacemaker center was observed in n = 16 experiments. A significant spread-direction-dependent variation of CV, FPrise, FPMIN, and FPpre up to 14% could be measured between different endogenous pacemakers. In conclusion, based on our results, disregarding the spatial origin of excitation may lead to misinterpretations and erroneous conclusions of FP parameters in the verification of research hypotheses in cellular electrocardiology.

Analysis of Vestibular Labyrinthine Geometry and Variation in the Human Temporal Bone

Stable posture and body movement in humans is dictated by the precise functioning of the ampulla organs in the semi-circular canals. Statistical analysis of the interrelationship between bony and membranous compartments within the semi-circular canals is dependent on the visualization of soft tissue structures. Thirty-one human inner ears were prepared, post-fixed with osmium tetroxide and decalcified for soft tissue contrast enhancement. High resolution X-ray microtomography images at 15 μm voxel-size were manually segmented. This data served as templates for centerline generation and cross-sectional area extraction. Our estimates demonstrate the variability of individual specimens from averaged centerlines of both bony and membranous labyrinth. Centerline lengths and cross-sectional areas along these lines were identified from segmented data. Using centerlines weighted by the inverse squares of the cross-sectional areas, plane angles could be quantified. The fit planes indicate that the bony labyrinth resembles a Cartesian coordinate system more closely than the membranous labyrinth. A widening in the membranous labyrinth of the lateral semi-circular canal was observed in some of the specimens. Likewise, the cross-sectional areas in the perilymphatic spaces of the lateral canal differed from the other canals. For the first time we could precisely describe the geometry of the human membranous labyrinth based on a large sample size. Awareness of the variations in the canal geometry of the membranous and bony labyrinth would be a helpful reference in designing electrodes for future vestibular prosthesis and simulating fluid dynamics more precisely.

Achieving elongated lesions employing cardiac cryoablation: a preclinical evaluation study

Cardiac cryoablation applied for treating cardiac arrhythmias has shown promising results after intervention, particularly for the creation of elongated lesions. A model for simulating and assessing cryoablation interventions was developed, evaluated and validated with animal experiments. We employed two simulations of different freezing outlet settings for a loop shaped cryocatheter, applying Pennes heat equation for cardiac tissue. Our experiments demonstrated that an equidistantly spaced freezing outlet distribution of 5mm led to an improved formation of lesions, i.e., elongated lesions were observed throughout the transmural cardiac volume and on the epicardial structure. A complete transmural frozen lesion was not achieved with a freezing outlet distance of 10mm. These simulation results could be experimentally verified by morphological and histological examinations. Using our simulation model we were able to optimize the intervention procedure by predicting and assessing the freezing process. This should further increase the success rate of cardiac cryoablation in clinical interventions.

Model-based Vestibular Afferent Stimulation: Modular Workflow for Analyzing Stimulation Scenarios in Patient Specific and Statistical Vestibular Anatomy

Our sense of balance and spatial orientation strongly depends on the correct functionality of our vestibular system. Vestibular dysfunction can lead to blurred vision and impaired balance and spatial orientation, causing a significant decrease in quality of life. Recent studies have shown that vestibular implants offer a possible treatment for patients with vestibular dysfunction. The close proximity of the vestibular nerve bundles, the facial nerve and the cochlear nerve poses a major challenge to targeted stimulation of the vestibular system. Modeling the electrical stimulation of the vestibular system allows for an efficient analysis of stimulation scenarios previous to time and cost intensive in vivo experiments. Current models are based on animal data or CAD models of human anatomy. In this work, a (semi-)automatic modular workflow is presented for the stepwise transformation of segmented vestibular anatomy data of human vestibular specimens to an electrical model and subsequently analyzed. The steps of this workflow include (i) the transformation of labeled datasets to a tetrahedra mesh, (ii) nerve fiber anisotropy and fiber computation as a basis for neuron models, (iii) inclusion of arbitrary electrode designs, (iv) simulation of quasistationary potential distributions, and (v) analysis of stimulus waveforms on the stimulation outcome. Results obtained by the workflow based on human datasets and the average shape of a statistical model revealed a high qualitative agreement and a quantitatively comparable range compared to data from literature, respectively. Based on our workflow, a detailed analysis of intra- and extra-labyrinthine electrode configurations with various stimulation waveforms and electrode designs can be performed on patient specific anatomy, making this framework a valuable tool for current optimization questions concerning vestibular implants in humans.

Simulation and evaluation of freeze-thaw cryoablation scenarios for the treatment of cardiac arrhythmias

BackgroundCardiac cryoablation is a minimally invasive procedure to treat cardiac arrhythmias by cooling cardiac tissues responsible for the cardiac arrhythmia to freezing temperatures. Although cardiac cryoablation offers a gentler treatment than radiofrequency ablation, longer interventions and higher recurrence rates reduce the clinical acceptance of this technique. Computer models of ablation scenarios allow for a closer examination of temperature distributions in the myocardium and evaluation of specific effects of applied freeze-thaw protocols in a controlled environment.MethodsIn this work multiple intervention scenarios with two freeze-thaw cycles were simulated with varying durations and starting times of the interim thawing phase using a finite element model verified by in-vivo measurements and data from literature. To evaluate the effects of different protocols, transmural temperature distributions and iceball dimensions were compared over time. Cryoadhesion durations of the applicator were estimated in the interim thawing phase with varying thawing phase starting times. In addition, the increase of cooling rates was compared between the freezing phases, and the thawing rates of interim thawing phases were analyzed over transmural depth.ResultsIt could be shown that the increase of cooling rate, the regions undergoing additional phase changes and depths of selected temperatures depend on the chosen ablation protocol. Only small differences of the estimated cryoadhesion duration were found for ablation scenarios with interim thawing phase start after 90 s freezing.ConclusionsBy the presented model a quantification of effects responsible for cell death is possible, allowing for the analysis and optimization of cryoablation scenarios which contribute to a higher clinical acceptance of cardiac cryoablation.

[KD 3 ] A workflow-based application for exploration of biomedical data sets

Based on the biotechnological revolution in the past years, molecular biology has become increasingly data-driven. Knowledge Discovery in Databases, a well-known process in the field of bioinformatics, is supporting the biological research process from data integration, knowledge mining to data interpretation. n nThis work proposes a new software suite, termed Knowledge Discovery inDatabases Designer (KD3), covering the completeKnowledge Discovery in Databases process using a workflow-oriented architecture. Three different application-oriented modules are implemented in KD3: First, the Designer for designing specific workflows. These workflows can be used by the Interpreter, which allows to load and parameterize existing workflows. The Launcher encapsulates one dedicated workflow into an independent application to answer one specific biomedical question. KD3 offers a variety of implemented methods, which can be easily extended with new customized components using functional objects. All components can be connected to workflows, which may contain elements of other applications.

A workflow for preprocessing and proteomic biomarker identification on mass-spectrometry data

A core technology in proteomics is mass spectroscopy (MS) that permits the measurement of thousands of proteins/peptides simultanously. Sophisticated data mining methods are necessary to identify highly predictive proteomic biomarker candidates in generated MS spectra that are specific to a certain disease. However, before analysis can be started the preprocessing of raw mass spectra is an essential task, mainly due to the presence of background signals in the spectra such as electrical and chemical noise. In this work we present a new data mining workflow for the identification of proteomic biomarker candidates using mass spectrometry data. The workflow includes two major steps: 1) the preprocessing of raw spectra, and 2) the identification of highly discriminating candidate masses using a 3-step feature selection approach by combining the advantages of efficient filter and effective wrapper techniques. With the proposed workflow we were able to identify putative candidate biomarkers in a lifethreatening human disease using matrix-assisted laser desorption/ionization imaging MS (MALDI-IMS).