In silico detection of control signals: mRNA 3′-end-processing sequences in diverse species

We have investigated mRNA 3′-end-processing signals in each of six eukaryotic species (yeast, rice, arabidopsis, fruitfly, mouse, and human) through the analysis of more than 20,000 3′-expressed sequence tags. The use and conservation of the canonical AAUAAA element vary widely among the six species and are especially weak in plants and yeast. Even in the animal species, the AAUAAA signal does not appear to be as universal as indicated by previous studies. The abundance of single-base variants of AAUAAA correlates with their measured processing efficiencies. As found previously, the plant polyadenylation signals are more similar to those of yeast than to those of animals, with both common content and arrangement of the signal elements. In all species examined, the complete polyadenylation signal appears to consist of an aggregate of multiple elements. In light of these and previous results, we present a broadened concept of 3′-end-processing signals in which no single exact sequence element is universally required for processing. Rather, the total efficiency is a function of all elements and, importantly, an inefficient word in one element can be compensated for by strong words in other elements. These complex patterns indicate that effective tools to identify 3′-end-processing signals will require more than consensus sequence identification.

Detection of neuritic plaques in Alzheimer’s disease by magnetic resonance microscopy

Magnetic resonance microscopy (MRM) theoretically provides the spatial resolution and signal-to-noise ratio needed to resolve neuritic plaques, the neuropathological hallmark of Alzheimer’s disease (AD). Two previously unexplored MR contrast parameters, T2* and diffusion, are tested for plaque-specific contrast to noise. Autopsy specimens from nondemented controls (n = 3) and patients with AD (n = 5) were used. Three-dimensional T2* and diffusion MR images with voxel sizes ranging from 3 × 10−3 mm3 to 5.9 × 10−5 mm3 were acquired. After imaging, specimens were cut and stained with a microwave king silver stain to demonstrate neuritic plaques. From controls, the alveus, fimbria, pyramidal cell layer, hippocampal sulcus, and granule cell layer were detected by either T2* or diffusion contrast. These structures were used as landmarks when correlating MRMs with histological sections. At a voxel resolution of 5.9 × 10−5 mm3, neuritic plaques could be detected by T2*. The neuritic plaques emerged as black, spherical elements on T2* MRMs and could be distinguished from vessels only in cross-section when presented in three dimension. Here we provide MR images of neuritic plaques in vitro. The MRM results reported provide a new direction for applying this technology in vivo. Clearly, the ability to detect and follow the early progression of amyloid-positive brain lesions will greatly aid and simplify the many possibilities to intervene pharmacologically in AD.

Detection of Transient In Vivo Interactions between Substrate and Transporter during Protein Translocation into the Endoplasmic Reticulum

The split-ubiquitin technique was used to detect transient protein interactions in living cells. Nub, the N-terminal half of ubiquitin (Ub), was fused to Sec62p, a component of the protein translocation machinery in the endoplasmic reticulum of Saccharomyces cerevisiae. Cub, the C-terminal half of Ub, was fused to the C terminus of a signal sequence. The reconstitution of a quasi-native Ub structure from the two halves of Ub, and the resulting cleavage by Ub-specific proteases at the C terminus of Cub, serve as a gauge of proximity between the two test proteins linked to Nub and Cub. Using this assay, we show that Sec62p is spatially close to the signal sequence of the prepro-α-factor in vivo. This proximity is confined to the nascent polypeptide chain immediately following the signal sequence. In addition, the extent of proximity depends on the nature of the signal sequence. Cub fusions that bore the signal sequence of invertase resulted in a much lower Ub reconstitution with Nub-Sec62p than otherwise identical test proteins bearing the signal sequence of prepro-α-factor. An inactive derivative of Sec62p failed to interact with signal sequences in this assay. These in vivo findings are consistent with Sec62p being part of a signal sequence-binding complex.

Ultrasensitive detection of pathological prion protein aggregates by dual-color scanning for intensely fluorescent targets

A definite diagnosis of prion diseases such as Creutzfeldt–Jakob disease (CJD) relies on the detection of pathological prion protein (PrPSc). However, no test for PrPSc in cerebrospinal fluid (CSF) has been available thus far. Based on a setup for confocal dual-color fluorescence correlation spectroscopy, a technique suitable for single molecule detection, we developed a highly sensitive detection method for PrPSc. Pathological prion protein aggregates were labeled by specific antibody probes tagged with fluorescent dyes, resulting in intensely fluorescent targets, which were measured by dual-color fluorescence intensity distribution analysis in a confocal scanning setup. In a diagnostic model system, PrPSc aggregates were detected down to a concentration of 2 pM PrPSc, corresponding to an aggregate concentration of approximately 2 fM, which was more than one order of magnitude more sensitive than Western blot analysis. A PrPSc-specific signal could also be detected in a number of CSF samples from patients with CJD but not in control samples, providing the basis for a rapid and specific test for CJD and other prion diseases. Furthermore, this method could be adapted to the sensitive detection of other disease-associated amyloid aggregates such as in Alzheimer's disease.

Immunoassays with rolling circle DNA amplification: A versatile platform for ultrasensitive antigen detection

We describe an adaptation of the rolling circle amplification (RCA) reporter system for the detection of protein Ags, termed “immunoRCA.” In immunoRCA, an oligonucleotide primer is covalently attached to an Ab; thus, in the presence of circular DNA, DNA polymerase, and nucleotides, amplification results in a long DNA molecule containing hundreds of copies of the circular DNA sequence that remain attached to the Ab and that can be detected in a variety of ways. Using immunoRCA, analytes were detected at sensitivities exceeding those of conventional enzyme immunoassays in ELISA and microparticle formats. The signal amplification afforded by immunoRCA also enabled immunoassays to be carried out in microspot and microarray formats with exquisite sensitivity. When Ags are present at concentrations down to fM levels, specifically bound Abs can be scored by counting discrete fluorescent signals arising from individual Ag–Ab complexes. Multiplex immunoRCA also was demonstrated by accurately quantifying Ags mixed in different ratios in a two-color, single-molecule-counting assay on a glass slide. ImmunoRCA thus combines high sensitivity and a very wide dynamic range with an unprecedented capability for single molecule detection. This Ag-detection method is of general applicability and is extendable to multiplexed immunoassays that employ a battery of different Abs, each labeled with a unique oligonucleotide primer, that can be discriminated by a color-coded visualization system. ImmunoRCA-profiling based on the simultaneous quantitation of multiple Ags should expand the power of immunoassays by exploiting the increased information content of ratio-based expression analysis.

Magnetic resonance imaging (MRI) detection of the murine brain response to light: temporal differentiation and negative functional MRI changes.

Using a 9.4 T MRI instrument, we have obtained images of the mouse brain response to photic stimulation during a period between deep anesthesia and the early stages of arousal. The large image enhancements we observe (often >30%) are consistent with literature results extrapolated to 9.4 T. However, there are also two unusual aspects to our findings. (i) The visual area of the brain responds only to changes in stimulus intensity, suggesting that we directly detect operations of the M visual system pathway. Such a channel has been observed in mice by invasive electrophysiology, and described in detail for primates. (ii) Along with the typical positive response in the area of the occipital portion of the brain containing the visual cortex, another area displays decreased signal intensity upon stimulation.

Real-time detection of DNA hybridization and melting on oligonucleotide arrays by using optical wave guides.

The challenge of the Human Genome Project is to increase the rate of DNA sequence acquisition by two orders of magnitude to complete sequencing of the human genome by the year 2000. The present work describes a rapid detection method using a two-dimensional optical wave guide that allows measurement of real-time binding or melting of a light-scattering label on a DNA array. A particulate label on the target DNA acts as a light-scattering source when illuminated by the evanescent wave of the wave guide and only the label bound to the surface generates a signal. Imaging/visual examination of the scattered light permits interrogation of the entire array simultaneously. Hybridization specificity is equivalent to that obtained with a conventional system using autoradiography. Wave guide melting curves are consistent with those obtained in the liquid phase and single-base discrimination is facile. Dilution experiments showed an apparent lower limit of detection at 0.4 nM oligonucleotide. This performance is comparable to the best currently known fluorescence-based systems. In addition, wave guide detection allows manipulation of hybridization stringency during detection and thereby reduces DNA chip complexity. It is anticipated that this methodology will provide a powerful tool for diagnostic applications that require rapid cost-effective detection of variations from known sequences.

Human Motion Analysis Based on Sequential Modeling of Radar Signal and Stereo Image Features

Falls are one of the greatest threats to elderly health in their daily living routines and activities. Therefore, it is very important to detect falls of an elderly in a timely and accurate manner, so that immediate response and proper care can be provided, by sending fall alarms to caregivers. Radar is an effective non-intrusive sensing modality which is well suited for this purpose, which can detect human motions in all types of environments, penetrate walls and fabrics, preserve privacy, and is insensitive to lighting conditions. Micro-Doppler features are utilized in radar signal corresponding to human body motions and gait to detect falls using a narrowband pulse-Doppler radar. Human motions cause time-varying Doppler signatures, which are analyzed using time-frequency representations and matching pursuit decomposition (MPD) for feature extraction and fall detection. The extracted features include MPD features and the principal components of the time-frequency signal representations. To analyze the sequential characteristics of typical falls, the extracted features are used for training and testing hidden Markov models (HMM) in different falling scenarios. Experimental results demonstrate that the proposed algorithm and method achieve fast and accurate fall detections. The risk of falls increases sharply when the elderly or patients try to exit beds. Thus, if a bed exit can be detected at an early stage of this motion, the related injuries can be prevented with a high probability. To detect bed exit for fall prevention, the trajectory of head movements is used for recognize such human motion. A head detector is trained using the histogram of oriented gradient (HOG) features of the head and shoulder areas from recorded bed exit images. A data association algorithm is applied on the head detection results to eliminate head detection false alarms. Then the three dimensional (3D) head trajectories are constructed by matching scale-invariant feature transform (SIFT) keypoints in the detected head areas from both the left and right stereo images. The extracted 3D head trajectories are used for training and testing an HMM based classifier for recognizing bed exit activities. The results of the classifier are presented and discussed in the thesis, which demonstrates the effectiveness of the proposed stereo vision based bed exit detection approach.

Near Real-Time Detection Of Pipe Bursts in Water Distribution Systems

The research work presented in the thesis describes a new methodology for the automated near real-time detection of pipe bursts in Water Distribution Systems (WDSs). The methodology analyses the pressure/flow data gathered by means of SCADA systems in order to extract useful informations that go beyond the simple and usual monitoring type activities and/or regulatory reporting , enabling the water company to proactively manage the WDSs sections. The work has an interdisciplinary nature covering AI techniques and WDSs management processes such as data collection, manipulation and analysis for event detection. Indeed, the methodology makes use of (i) Artificial Neural Network (ANN) for the short-term forecasting of future pressure/flow signal values and (ii) Rule-based Model for bursts detection at sensor and district level. The results of applying the new methodology to a District Metered Area in Emilia- Romagna’s region, Italy have also been reported in the thesis. The results gathered illustrate how the methodology is capable to detect the aforementioned failure events in fast and reliable manner. The methodology guarantees the water companies to save water, energy, money and therefore enhance them to achieve higher levels of operational efficiency, a compliance with the current regulations and, last but not least, an improvement of customer service.

Non-invasive Detection of Cortical Control Signals for Brain-Computer Interfaces

Thesis (Ph.D.)--University of Washington, 2016-05

Marine mammal species detection and classification

Thesis (Ph.D.)--University of Washington, 2016-04

Optimized Decoding for Auditory Attention Detection

Thesis (Master's)--University of Washington, 2016-06

Ultra-wideband multistatic SAR for the detection and location of landmines

Techniques for improving the signal to clutter ratio of an. ultra-wideband SAR designed to detect small mine-like objects in the surface of the ground were investigated. In particular, images were collected using different bistatic antenna configurations in an attempt to decorrelate the clutter with respect to the targets. The images were converted to a reference depression angle, summed, and then converted to ground coordinates. The resulting target strengths were then compared with the amplitude distribution of the ground clutter to show the improvement obtained. While some improvement was demonstrated, this was for the relatively easy scenario of targets on the surface partially obscured by grass. Detection based on thresholding the raw RF signal (the bipolar response) rather than the envelope (baseband I-2 + Q(2)) was also considered to further enhance target-to-clutter ratios.

Fourier-domain optical coherence tomography: optimization of signal-to-noise ratio in full space

Optical coherence tomography (OCT) is an emerging coherence-domain technique capable of in vivo imaging of sub-surface structures at millimeter-scale depth. Its steady progress over the last decade has been galvanized by a breakthrough detection concept, termed spectral-domain OCT, which has resulted in a dramatic improvement of the OCT signal-to-noise ratio of 150 times demonstrated for weakly scattering objects at video-frame-rates. As we have realized, however, an important OCT sub-system remains sub-optimal: the sample arm traditionally operates serially, i.e. in flying-spot mode. To realize the full-field image acquisition, a Fourier holography system illuminated with a swept-source is employed instead of a Michelson interferometer commonly used in OCT. The proposed technique, termed Fourier-domain OCT, offers a new leap in signal-to-noise ratio improvement, as compared to flying-spot OCT systems, and represents the main thrust of this paper. Fourier-domain OCT is described, and its basic theoretical aspects, including the reconstruction algorithm, are discussed. (C) 2004 Elsevier B.V. All rights reserved.

Blind detection of PAM and QAM in fading channels

This correspondence considers block detection for blind wireless digital transmission. At high signal-to-noise ratio (SNR), block detection errors are primarily due to the received sequence having multiple possible decoded sequences with the same likelihood. We derive analytic expressions for the probability of detection ambiguity written in terms of a Dedekind zeta function, in the zero noise case with large constellations. Expressions are also provided for finite constellations, which can be evaluated efficiently, independent of the block length. Simulations demonstrate that the analytically derived error floors exist at high SNR.