A Data-Analytic Strategy for Protein-Biomarker Discovery: Profiling of High-Dimensional Proteomic Data for Cancer Detection

With recent advances in mass spectrometry techniques, it is now possible to investigate proteins over a wide range of molecular weights in small biological specimens. This advance has generated data-analytic challenges in proteomics, similar to those created by microarray technologies in genetics, namely, discovery of "signature" protein profiles specific to each pathologic state (e.g., normal vs. cancer) or differential profiles between experimental conditions (e.g., treated by a drug of interest vs. untreated) from high-dimensional data. We propose a data analytic strategy for discovering protein biomarkers based on such high-dimensional mass-spectrometry data. A real biomarker-discovery project on prostate cancer is taken as a concrete example throughout the paper: the project aims to identify proteins in serum that distinguish cancer, benign hyperplasia, and normal states of prostate using the Surface Enhanced Laser Desorption/Ionization (SELDI) technology, a recently developed mass spectrometry technique. Our data analytic strategy takes properties of the SELDI mass-spectrometer into account: the SELDI output of a specimen contains about 48,000 (x, y) points where x is the protein mass divided by the number of charges introduced by ionization and y is the protein intensity of the corresponding mass per charge value, x, in that specimen. Given high coefficients of variation and other characteristics of protein intensity measures (y values), we reduce the measures of protein intensities to a set of binary variables that indicate peaks in the y-axis direction in the nearest neighborhoods of each mass per charge point in the x-axis direction. We then account for a shifting (measurement error) problem of the x-axis in SELDI output. After these pre-analysis processing of data, we combine the binary predictors to generate classification rules for cancer, benign hyperplasia, and normal states of prostate. Our approach is to apply the boosting algorithm to select binary predictors and construct a summary classifier. We empirically evaluate sensitivity and specificity of the resulting summary classifiers with a test dataset that is independent from the training dataset used to construct the summary classifiers. The proposed method performed nearly perfectly in distinguishing cancer and benign hyperplasia from normal. In the classification of cancer vs. benign hyperplasia, however, an appreciable proportion of the benign specimens were classified incorrectly as cancer. We discuss practical issues associated with our proposed approach to the analysis of SELDI output and its application in cancer biomarker discovery.

Digital processing and data compilation approach for using remotely sensed imagery to identify geological lineaments in hard-rock terrains : an application for groundwater explorations in Nicaragua

Sustainable yields from water wells in hard-rock aquifers are achieved when the well bore intersects fracture networks. Fracture networks are often not readily discernable at the surface. Lineament analysis using remotely sensed satellite imagery has been employed to identify surface expressions of fracturing, and a variety of image-analysis techniques have been successfully applied in “ideal” settings. An ideal setting for lineament detection is where the influences of human development, vegetation, and climatic situations are minimal and hydrogeological conditions and geologic structure are known. There is not yet a well-accepted protocol for mapping lineaments nor have different approaches been compared in non-ideal settings. A new approach for image-processing/synthesis was developed to identify successful satellite imagery types for lineament analysis in non-ideal terrain. Four satellite sensors (ASTER, Landsat7 ETM+, QuickBird, RADARSAT-1) and a digital elevation model were evaluated for lineament analysis in Boaco, Nicaragua, where the landscape is subject to varied vegetative cover, a plethora of anthropogenic features, and frequent cloud cover that limit the availability of optical satellite data. A variety of digital image processing techniques were employed and lineament interpretations were performed to obtain 12 complementary image products that were evaluated subjectively to identify lineaments. The 12 lineament interpretations were synthesized to create a raster image of lineament zone coincidence that shows the level of agreement among the 12 interpretations. A composite lineament interpretation was made using the coincidence raster to restrict lineament observations to areas where multiple interpretations (at least 4) agree. Nine of the 11 previously mapped faults were identified from the coincidence raster. An additional 26 lineaments were identified from the coincidence raster, and the locations of 10 were confirmed by field observation. Four manual pumping tests suggest that well productivity is higher for wells proximal to lineament features. Interpretations from RADARSAT-1 products were superior to interpretations from other sensor products, suggesting that quality lineament interpretation in this region requires anthropogenic features to be minimized and topographic expressions to be maximized. The approach developed in this study has the potential to improve siting wells in non-ideal regions.

Quantitative proteome analysis in cardiovascular physiology and pathology. I. Data processing

Methodological evaluation of the proteomic analysis of cardiovascular-tissue material has been performed with a special emphasis on establishing examinations that allow reliable quantitative analysis of silver-stained readouts. Reliability, reproducibility, robustness and linearity were addressed and clarified. In addition, several types of normalization procedures were evaluated and new approaches are proposed. It has been found that the silver-stained readout offers a convenient approach for quantitation if a linear range for gel loading is defined. In addition, a broad range of a 10-fold input (loading 20-200 microg per gel) fulfills the linearity criteria, although at the lowest input (20 microg) a portion of protein species will remain undetected. The method is reliable and reproducible within a range of 65-200 microg input. The normalization procedure using the sum of all spot intensities from a silver-stained 2D pattern has been shown to be less reliable than other approaches, namely, normalization through median or through involvement of interquartile range. A special refinement of the normalization through virtual segmentation of pattern, and calculation of normalization factor for each stratum provides highly satisfactory results. The presented results not only provide evidence for the usefulness of silver-stained gels for quantitative evaluation, but they are directly applicable to the research endeavor of monitoring alterations in cardiovascular pathophysiology.

Integrated data acquisition and processing to determine metabolite contents, relaxation times, and macromolecule baseline in single examinations of individual subjects

Absolute quantitation of clinical (1)H-MR spectra is virtually always incomplete for single subjects because the separate determination of spectrum, baseline, and transverse and longitudinal relaxation times in single subjects is prohibitively long. Integrated Processing and Acquisition of Data (IPAD) based on a combined 2-dimensional experimental and fitting strategy is suggested to substantially improve the information content from a given measurement time. A series of localized saturation-recovery spectra was recorded and combined with 2-dimensional prior-knowledge fitting to simultaneously determine metabolite T(1) (from analysis of the saturation-recovery time course), metabolite T(2) (from lineshape analysis based on metabolite and water peak shapes), macromolecular baseline (based on T(1) differences and analysis of the saturation-recovery time course), and metabolite concentrations (using prior knowledge fitting and conventional procedures of absolute standardization). The procedure was tested on metabolite solutions and applied in 25 subjects (15-78 years old). Metabolite content was comparable to previously found values. Interindividual variation was larger than intraindividual variation in repeated spectra for metabolite content as well as for some relaxation times. Relaxation times were different for various metabolite groups. Parts of the interindividual variation could be explained by significant age dependence of relaxation times.

Mammalian pre-mRNA 3' end processing factor CF I m 68 functions in mRNA export

Export of mRNA from the nucleus is linked to proper processing and packaging into ribonucleoprotein complexes. Although several observations indicate a coupling between mRNA 3' end formation and export, it is not known how these two processes are mechanistically connected. Here, we show that a subunit of the mammalian pre-mRNA 3' end processing complex, CF I(m)68, stimulates mRNA export. CF I(m)68 shuttles between the nucleus and the cytoplasm in a transcription-dependent manner and interacts with the mRNA export receptor NXF1/TAP. Consistent with the idea that CF I(m)68 may act as a novel adaptor for NXF1/TAP, we show that CF I(m)68 promotes the export of a reporter mRNA as well as of endogenous mRNAs, whereas silencing by RNAi results in the accumulation of mRNAs in the nucleus. Moreover, CF I(m)68 associates with 80S ribosomes but not polysomes, suggesting that it is part of the mRNP that is remodeled in the cytoplasm during the initial stages of translation. These results reveal a novel function for the pre-mRNA 3' end processing factor CF I(m)68 in mRNA export.

Digital Data Collection and Processing in Field and Lab: The Approach of Kinneret Regional Project

The paper showcases the field- and lab-documentation system developed for Kinneret Regional Project, an international archaeological expedition to the Northwestern shore of the Sea of Galilee (Israel) under the auspices of the University of Bern, the University of Helsinki, Leiden University and Wofford College. The core of the data management system is a fully relational, server-based database framework, which also includes time-based and static GIS services, stratigraphic analysis tools and fully indexed document/digital image archives. Data collection in the field is based on mobile, hand-held devices equipped with a custom-tailored stand-alone application. Comprehensive three-dimensional documentation of all finds and findings is achieved by means of total stations and/or high-precision GPS devices. All archaeological information retrieved in the field – including tachymetric data – is synched with the core system on the fly and thus immediately available for further processing in the field lab (within the local network) or for post-excavation analysis at remote institutions (via the WWW). Besides a short demonstration of the main functionalities, the paper also presents some of the key technologies used and illustrates usability aspects of the system’s individual components.

The brain’s pre-stimulus default state interacts with working memory in a load-dependent manner

Recently, multiple studies showed that spatial and temporal features of a task-negative default mode network (DMN) (Greicius et al., 2003) are important markers for psychiatric diseases (Balsters et al., 2013). Another prominent indicator of cognitive functioning, yielding information about the mental condition in health and disease, is working memory (WM) processing. In EEG and MEG studies, frontal-midline theta power has been shown to increase with load during WM retention in healthy subjects (Brookes et al., 2011). Negative correlations between DMN activity and theta amplitude have been found during resting state (Jann et al., 2010) as well as during WM (Michels et al., 2010). Likewise, WM training resulted in higher resting state theta power as well as increased small-worldness of the resting brain (Langer et al., 2013). Further, increased fMRI connectivity between nodes of the DMN correlated with better WM performance (Hampson et al., 2006). Hence, the brain’s default state might influence it’s functioning during task. We therefore hypothesized correlations between pre-stimulus DMN activity and EEG-theta power during WM maintenance, depending on the WM load. 17 healthy subjects performed a Sternberg WM task while being measured simultaneously with EEG and fMRI. Data was recorded within a multicenter-study: 12 subjects were measured in Zurich with a 64-channels MR-compatible system (Brain Products) in a 3T Philips scanner, 5 subjects with a 96-channel MR-compatible system (Brain Products) in a 3T Siemens Scanner in Bern. The DMN components was obtained by a group BOLD-ICA approach over the full task duration (figure 1). The subject-wise dynamics were obtained by back-reconstructed onto each subject’s fMRI data and normalized to percent signal change values. The single trial pre-stimulus-DMN activation was then temporally correlated with the single trial EEG-theta (3-8 Hz) spectral power during retention intervals. This so-called covariance mapping (Jann et al., 2010) yielded the spatial distribution of the theta EEG fluctuations during retention associated with the dynamics of the pre-stimulus DMN. In line with previous findings, theta power was increased at frontal-midline electrodes in high- versus low-load conditions during early WM retention (figure 2). However, correlations of DMN with theta power resulted in primarily positive correlations in low-load conditions, while during high-load conditions negative correlations of DMN activity and theta power were observed at frontal-midline electrodes. This DMN-dependent load effect reached significance in the middle of the retention period (TANOVA, p<0.05) (figure 3). Our results show a complex and load-dependent interaction of pre-stimulus DMN activity and theta power during retention, varying over time. While at a more global, load-independent view pre-stimulus DMN activity correlated positively with theta power during retention, the correlation was inversed during certain time windows in high-load trials, meaning that in trials with enhanced pre-stimulus DMN activity theta power decreases during retention. Since both WM performance and DMN activity are markers of mental health our results could be important for further investigations of psychiatric populations.

A 5'-3' exonuclease activity involved in forming the 3' products of histone pre-mRNA processing in vitro.

Histone RNA 3' processing in vitro produces one or more 5' cleavage products corresponding to the mature histone mRNA 3' end, and a group of 3' cleavage products whose 5' ends are mostly located several nucleotides downstream of the mRNA 3' end. The formation of these 3' products is coupled to the formation of 5' products and dependent on the U7 snRNP and a heat-labile processing factor. These short 3' products therefore are a true and general feature of the processing reaction. Identical 3' products are also formed from a model RNA containing all spacer nucleotides downstream of the mature mRNA 3' end, but no sequences from the mature mRNA. Again, this reaction is dependent on both the U7 snRNP and a heat-labile factor. Unlike the processing with a full-length histone pre-mRNA, this reaction produces only 3' but no 5' fragments. In addition, product formation is inhibited by addition of cap structures at the model RNA 5' end, indicating that product formation occurs by 5'-3' exonucleolytic degradation. This degradation of a model 3' product by a 5'-3' exonuclease suggests a mechanism for the release of the U7 snRNP after processing by shortening the cut-off histone spacer sequences base paired to U7 RNA.

Visualization and quantification of air embolism structure by processing postmortem MSCT data.

Venous air embolism (VAE) is an often occurring forensic finding in cases of injury to the head and neck. Whenever found, it has to be appraised in its relation to the cause of death. While visualization and quantification is difficult at traditional autopsy, Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) offer a new potential in the diagnosis of VAE. This paper reports the findings of VAE in four cases of massive head injury examined postmortem by Multislice Computed Tomography (MSCT) prior to autopsy. MSCT data of the thorax were processed using 3D air structure reconstruction software to visualize air embolism within the vascular system. Quantification of VAE was done by multiplying air containing areas on axial 2D images by their reconstruction intervals and then by summarizing the air volumes. Excellent 3D visualization of the air within the vascular system was obtained in all cases, and the intravascular gas volume was quantified.