R. Mitchell Parry

Desorption electrospray ionization mass spectrometry reveals surface-mediated antifungal chemical defense of a tropical seaweed

Organism surfaces represent signaling sites for attraction of allies and defense against enemies. However, our understanding of these signals has been impeded by methodological limitations that have precluded direct fine-scale evaluation of compounds on native surfaces. Here, we asked whether natural products from the red macroalga Callophycus serratus act in surface-mediated defense against pathogenic microbes. Bromophycolides and callophycoic acids from algal extracts inhibited growth of Lindra thalassiae, a marine fungal pathogen, and represent the largest group of algal antifungal chemical defenses reported to date. Desorption electrospray ionization mass spectrometry (DESI-MS) imaging revealed that surface-associated bromophycolides were found exclusively in association with distinct surface patches at concentrations sufficient for fungal inhibition; DESI-MS also indicated the presence of bromophycolides within internal algal tissue. This is among the first examples of natural product imaging on biological surfaces, suggesting the importance of secondary metabolites in localized ecological interactions, and illustrating the potential of DESI-MS in understanding chemically-mediated biological processes.

OmniSpect: An Open MATLAB-Based Tool for Visualization and Analysis of Matrix-Assisted Laser Desorption/Ionization and Desorption Electrospray Ionization Mass Spectrometry Images

AbstractWe present omniSpect, an open source web- and MATLAB-based software tool for both desorption electrospray ionization (DESI) and matrix-assisted laser desorption ionization (MALDI) mass spectrometry imaging (MSI) that performs computationally intensive functions on a remote server. These functions include converting data from a variety of file formats into a common format easily manipulated in MATLAB, transforming time-series mass spectra into mass spectrometry images based on a probe spatial raster path, and multivariate analysis. OmniSpect provides an extensible suite of tools to meet the computational requirements needed for visualizing open and proprietary format MSI data.

Seaweed Allelopathy Against Coral: Surface Distribution of a Seaweed Secondary Metabolite by Imaging Mass Spectrometry

Coral reefs are in global decline, with seaweeds increasing as corals decrease. Although seaweeds inhibit coral growth, recruitment, and survivorship, the mechanism of these interactions is poorly understood. Here, we used field experiments to show that contact with four common seaweeds induces bleaching on natural colonies of Porites rus. Controls in contact with inert, plastic mimics of seaweeds did not bleach, suggesting seaweed effects resulted from allelopathy rather than shading, abrasion, or physical contact. Bioassay-guided fractionation of the hydrophobic extract from the red alga Phacelocarpus neurymenioides revealed a previously characterized antibacterial metabolite, neurymenolide A, as the main allelopathic agent. For allelopathy of lipid-soluble metabolites to be effective, the compounds would need to be deployed on algal surfaces where they could transfer to corals on contact. We used desorption electrospray ionization mass spectrometry (DESI-MS) to visualize and quantify neurymenolide A on the surface of P. neurymenioides, and we found the molecule on all surfaces analyzed, with highest concentrations on basal portions of blades.

Estimating the spatial position of spectral components in audio

One way of separating sources from a single mixture recording is by extracting spectral components and then combining them to form estimates of the sources. The grouping process remains a difficult problem. We propose, for instances when multiple mixture signals are available, clustering the components based on their relative contribution to each mixture (i.e., their spatial position). We introduce novel factorizations of magnitude spectrograms from multiple recordings and derive update rules that extend independent subspace analysis and non-negative matrix factorization to concurrently estimate the spectral shape, time envelope and spatial position of each component. We show that estimated component positions are near the position of their corresponding source, and that multichannel non-negative matrix factorization can distinguish three pianos by their position in the mixture.

Musical interactions with a perceptual robotic percussionist

We present our approach for human-robot musical interaction using a perceptual and socially-oriented robotic percussionist. Our robot, named Haile, listens to live players, analyzes perceptual musical aspects in real-time, and uses the product of this analysis to playback in an acoustically rich manner, forming musical collaborations with human players. We conclude by proposing guidelines for pedagogy and an educational environment for learning music, math, acoustics, and programming through interaction with Haile.

Phase-aware non-negative spectrogram factorization

Non-negative spectrogram factorization has been proposed for single-channel source separation tasks. These methods operate on the magnitude or power spectrogram of the input mixture and estimate the magnitude or power spectrogram of source components. The usual assumption is that the mixture spectrogram is well approximated by the sum of source components. However, this relationship additionally depends on the unknown phase of the sources. Using a probabilistic representation of phase, we derive a cost function that incorporates this uncertainty. We compare this cost function against four standard approaches for a variety of spectrogram sizes, numbers of components, and component distributions. This phase-aware cost function reduces the estimation error but is more affected by detection errors.

Acquisition and display of real-time atmospheric data on terrain

This paper investigates the integrated acquisition, organization, and display of data from disparate sources, including the display of data acquired in real-time. In this case real-time acquisition and display refers to the capture and visualization of data as they are being produced. The particular application investigated is 3D dynamic atmospheric data on terrain, but key elements presented here are applicable more generally to other types of real-time data. 3D Doppler radar data are acquired and visualized with global, high resolution terrain. This is the first time such data have been displayed together in a real-time environment and provides the potential for new vistas in forecasting and analysis. Associated data such as buildings and maps are displayed along with the weather data and the terrain. A global hierarchical structure makes these disparate data available for integrated visualization in real-time. Requirements for effective 3D visualization for decision-making are identified, and it is shown that the applications presented meet most of these requirements.

Simple quantification of multiplexed Quantum Dot staining in clinical tissue samples

In this paper, we present a simple method for the processing and quantification of multiplexed Quantum Dot (QD) labeled images of clinical cancer tissue samples. QDs provide several features which make them ideal for reliable quantification, including long-term signal stability, high signal-to-noise ratios, as well as narrow emission bandwidths. Deconvolution of QD spectra is accomplished in a batch mode in which unmixing parameters are preserved across samples to allow for quantitative and reproducible comparisons. After unmixing the QD images, we segment each one to exclude acellular regions. We use a simple average intensity to quantify the level of QD staining for each image. We illustrate the viability of this approach by testing it on 28 tissue samples using a tissue microarray. We show that using as few as two QD protein targets (MDM-2, and B-actin), the Renal Cell Carcinoma (RCC) samples are distinguishable from adjacent normal tissue samples. A simple linear discriminant results in 100% classification of 25 RCC samples and 3 normal samples. This suggests that multiplexed QDs can be used to properly diagnose RCC from otherwise healthy tissue. We expect to apply this work to larger panels of more robust QD biomarker targets to aid in clinical decision-making for the diagnosis and prognosis of diseases, such as cancer.

caCORRECT2: Improving the accuracy and reliability of microarray data in the presence of artifacts

BackgroundIn previous work, we reported the development of caCORRECT, a novel microarray quality control system built to identify and correct spatial artifacts commonly found on Affymetrix arrays. We have made recent improvements to caCORRECT, including the development of a model-based data-replacement strategy and integration with typical microarray workflows via caCORRECTs web portal and caBIG grid services. In this report, we demonstrate that caCORRECT improves the reproducibility and reliability of experimental results across several common Affymetrix microarray platforms. caCORRECT represents an advance over state-of-art quality control methods such as Harshlighting, and acts to improve gene expression calculation techniques such as PLIER, RMA and MAS5.0, because it incorporates spatial information into outlier detection as well as outlier information into probe normalization. The ability of caCORRECT to recover accurate gene expressions from low quality probe intensity data is assessed using a combination of real and synthetic artifacts with PCR follow-up confirmation and the affycomp spike in data. The caCORRECT tool can be accessed at the website: http://cacorrect.bme.gatech.edu.ResultsWe demonstrate that (1) caCORRECTs artifact-aware normalization avoids the undesirable global data warping that happens when any damaged chips are processed without caCORRECT; (2) When used upstream of RMA, PLIER, or MAS5.0, the data imputation of caCORRECT generally improves the accuracy of microarray gene expression in the presence of artifacts more than using Harshlighting or not using any quality control; (3) Biomarkers selected from artifactual microarray data which have undergone the quality control procedures of caCORRECT are more likely to be reliable, as shown by both spike in and PCR validation experiments. Finally, we present a case study of the use of caCORRECT to reliably identify biomarkers for renal cell carcinoma, yielding two diagnostic biomarkers with potential clinical utility, PRKAB1 and NNMT.ConclusionscaCORRECT is shown to improve the accuracy of gene expression, and the reproducibility of experimental results in clinical application. This study suggests that caCORRECT will be useful to clean up possible artifacts in new as well as archived microarray data.

An analysis of scale and rotation invariance in the bag-of-features method for histopathological image classification

The bag-of-features method has emerged as a useful and flexible tool that can capture medically relevant image characteristics. In this paper, we study the effect of scale and rotation invariance in the bag-of-features framework for Renal Cell Carcinoma subtype classification. We estimated the performance of different features by linear support vector machine over 10 iterations of 3-fold cross validation. For a very heterogeneous dataset labeled by an expert pathologist, we achieve a classification accuracy of 88% with four subtypes. Our study shows that rotation invariance is more important than scale invariance but combining both properties gives better classification performance.