Real-time maximum a-posteriori image reconstruction for fluorescence microscopy

Rapid reconstruction of multidimensional image is crucial for enabling real-time 3D fluorescence imaging. This becomes a key factor for imaging rapidly occurring events in the cellular environment. To facilitate real-time imaging, we have developed a graphics processing unit (GPU) based real-time maximum a-posteriori (MAP) image reconstruction system. The parallel processing capability of GPU device that consists of a large number of tiny processing cores and the adaptability of image reconstruction algorithm to parallel processing (that employ multiple independent computing modules called threads) results in high temporal resolution. Moreover, the proposed quadratic potential based MAP algorithm effectively deconvolves the images as well as suppresses the noise. The multi-node multi-threaded GPU and the Compute Unified Device Architecture (CUDA) efficiently execute the iterative image reconstruction algorithm that is similar to 200-fold faster (for large dataset) when compared to existing CPU based systems. (C) 2015 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.

Directional bilateral filters for smoothing fluorescence microscopy images

Images obtained through fluorescence microscopy at low numerical aperture (NA) are noisy and have poor resolution. Images of specimens such as F-actin filaments obtained using confocal or widefield fluorescence microscopes contain directional information and it is important that an image smoothing or filtering technique preserve the directionality. F-actin filaments are widely studied in pathology because the abnormalities in actin dynamics play a key role in diagnosis of cancer, cardiac diseases, vascular diseases, myofibrillar myopathies, neurological disorders, etc. We develop the directional bilateral filter as a means of filtering out the noise in the image without significantly altering the directionality of the F-actin filaments. The bilateral filter is anisotropic to start with, but we add an additional degree of anisotropy by employing an oriented domain kernel for smoothing. The orientation is locally adapted using a structure tensor and the parameters of the bilateral filter are optimized for within the framework of statistical risk minimization. We show that the directional bilateral filter has better denoising performance than the traditional Gaussian bilateral filter and other denoising techniques such as SURE-LET, non-local means, and guided image filtering at various noise levels in terms of peak signal-to-noise ratio (PSNR). We also show quantitative improvements in low NA images of F-actin filaments. (C) 2015 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.

QUANTITATIVE OH PLANAR LASER INDUCED FLUORESCENCE DIAGNOSTICS OF SYNGAS AND METHANE COMBUSTION IN A CAVITY COMBUSTOR

The current work reports quantitative OH species concentration in the cavity of a trapped vortex combustor (TVC) in the context of mixing and flame stabilization studies using both syngas and methane fuels. Planar laser induced fluorescence (PLIF) measurements of OH radical obtained using a Nd: YAG pumped dye laser are quantified using a flat flame McKenna burner. The momentum flux ratio (MFR), defined as the ratio of the cavity fuel jet momentum to that of the guide vane air stream, is observed to be a key governing parameter. At high MFRs similar to 4.5, the flame front is observed to form at the interface of the fuel jet and the air jet stream. This is substantiated by velocity vector field measurements. For syngas, as the MFR is lowered to similar to 0.3, the fuel-air mixing increases and a flame front is formed at the bottom and downstream edge of the cavity where a stratified charge is present. This trend is observed for different velocities at similar equivalence ratios. In case of methane combustion in the cavity, where the MFRs employed are extremely low at similar to 0.01, a different mechanism is observed. A fuel-rich mixture is now observed at the center of the cavity and this mixture undergoes combustion. On further increase of the cavity equivalence ratio, the rich mixture exceeds the flammability limit and forms a thin reaction zone at the interface with air stream. As a consequence, a shear layer flame at the top of the cavity interface with the mainstream is also observed. The equivalence ratio in the cavity also determines the combustion characteristics in the case of fuel-air mixtures that are formed as a result of the mixing. Overall, flame stabilization mechanisms have been proposed, which account for the wide range of MFRs and premixing in the mainstream as well.

A Mitigation Technique for Harmonic Downconversion in Wideband Spectrum Sensors

The down conversion of radio frequency components around the harmonics of the local oscillator (LO), and its impact on the accuracy of white space detection using integrated spectrum sensors, is studied. We propose an algorithm to mitigate the impact of harmonic downconversion by utilizing multiple parallel downconverters in the system architecture. The proposed algorithm is validated on a test-board using commercially available integrated circuits and a test-chip implemented in a 130-nm CMOS technology. The measured data show that the impact of the harmonic downconversion is closely related to the LO characteristics, and that much of it can be mitigated by the proposed technique.

Near-Optimal Detection Thresholds for Bayesian Spectrum Sensing Under Fading

This paper considers the problem of energy-based, Bayesian spectrum sensing in cognitive radios under various fading environments. Under the well-known central limit theorem based model for energy detection, we derive analytically tractable expressions for near-optimal detection thresholds that minimize the probability of error under lognormal, Nakagami-m, and Weibull fading. For the Suzuki fading case, a generalized gamma approximation is provided, which saves on the computation of an integral. In each case, the accuracy of the theoretical expressions as compared to the optimal thresholds are illustrated through simulations.

Multi-dimensional Goodness-of-Fit Tests for Spectrum Sensing Based on Stochastic Distances

In this paper, we study two multi-dimensional Goodness-of-Fit tests for spectrum sensing in cognitive radios. The multi-dimensional scenario refers to multiple CR nodes, each with multiple antennas, that record multiple observations from multiple primary users for spectrum sensing. These tests, viz., the Interpoint Distance (ID) based test and the h, f distance based tests are constructed based on the properties of stochastic distances. The ID test is studied in detail for a single CR node case, and a possible extension to handle multiple nodes is discussed. On the other hand, the h, f test is applicable in a multi-node setup. A robustness feature of the KL distance based test is discussed, which has connections with Middleton's class A model. Through Monte-Carlo simulations, the proposed tests are shown to outperform the existing techniques such as the eigenvalue ratio based test, John's test, and the sphericity test, in several scenarios.

Ultrafast Chemical Dynamics in Time Domain Through Fluorescence Spectroscopy

While absorption and emission spectroscopy have always been used to detect and characterize molecules and molecular complexes, the availability of ultrashort laser pulses and associated computer-aided optical detection techniques allowed study of chemical processes directly in the time domain at unprecedented time scales, through appearance and disappearance of fluorescence from participating chemical species. Application of such techniques to chemical dynamics in liquids, where many processes occur with picosecond and femtosecond time scales lead to the discovery of a host of new phenomena that in turn led to the development of many new theories. Experiment and theory together provided new and valuable insight into many fundamental chemical processes, like isomerization dynamics, electron and proton transfer reactions, vibrational energy and phase relaxation, photosynthesis, to name just a few. In this article, we shall review a few of such discoveries in attempt to provide a glimpse of the fascinating research employing fluorescence spectroscopy that changed the field of chemical dynamics forever.

Chemical Shifts to Metabolic Pathways: Identifying Metabolic Pathways Directly from a Single 2D NMR Spectrum

Identifying cellular processes in terms of metabolic pathways is one of the avowed goals of metabolomics studies. Currently, this is done after relevant metabolites are identified to allow their mapping onto specific pathways. This task is daunting due to the complex nature of cellular processes and the difficulty in establishing the identity of individual metabolites. We propose here a new method: ChemSMP (Chemical Shifts to Metabolic Pathways), which facilitates rapid analysis by identifying the active metabolic pathways directly from chemical shifts obtained from a single two-dimensional (2D) C-13-H-1] correlation NMR spectrum without the need for identification and assignment of individual metabolites. ChemSMP uses a novel indexing and scoring system comprised of a ``uniqueness score'' and a ``coverage score''. Our method is demonstrated on metabolic pathways data from the Small Molecule Pathway Database (SMPDB) and chemical shifts from the Human Metabolome Database (HMDB). Benchmarks show that ChemSMP has a positive prediction rate of >90% in the presence of deduttered data and can sustain the same at 60-70% even in the presence of noise, such as deletions of peaks and chemical shift deviations. The method tested on NMR data acquired for a mixture of 20 amino acids shows a success rate of 93% in correct recovery of pathways. When used on data obtained from the cell lysate of an unexplored oncogenic cell line, it revealed active metabolic pathways responsible for regulating energy homeostasis of cancer cells. Our unique tool is thus expected to significantly enhance analysis of NMIR-based metabolomics data by reducing existing impediments.

Error exponent analysis of energy-based Bayesian decentralized spectrum sensing under fading

This paper considers decentralized spectrum sensing, i.e., detection of occupancy of the primary users' spectrum by a set of Cognitive Radio (CR) nodes, under a Bayesian set-up. The nodes use energy detection to make their individual decisions, which are combined at a Fusion Center (FC) using the K-out-of-N fusion rule. The channel from the primary transmitter to the CR nodes is assumed to undergo fading, while that from the nodes to the FC is assumed to be error-free. In this scenario, a novel concept termed as the Error Exponent with a Confidence Level (EECL) is introduced to evaluate and compare the performance of different detection schemes. Expressions for the EECL under general fading conditions are derived. As a special case, it is shown that the conventional error exponent both at individual sensors, and at the FC is zero. Further, closed-form lower bounds on the EECL are derived under Rayleigh fading and lognormal shadowing. As an example application, it answers the question of whether to use pilot-signal based narrowband sensing, where the signal undergoes Rayleigh fading, or to sense over the entire bandwidth of a wideband signal, where the signal undergoes lognormal shadowing. Theoretical results are validated using Monte Carlo simulations. (C) 2015 Elsevier B.V. All rights reserved.

Design and implementation of spectrum sensing for cognitive radios with a frequency-hopping primary system

In this work, spectrum sensing for cognitive radios is considered in the presence of multiple Primary Users (PU) using frequency-hopping communication over a set of frequency bands. The detection performance of the Fast Fourier Transform (FFT) Average Ratio (FAR) algorithm is obtained in closed-form, for a given FFT size and number of PUs. The effective throughput of the Secondary Users (SU) is formulated as an optimization problem with a constraint on the maximum allowable interference on the primary network. Given the hopping period of the PUs, the sensing duration that maximizes the SU throughput is derived. The results are validated using Monte Carlo simulations. Further, an implementation of the FAR algorithm on the Lyrtech (now, Nutaq) small form factor software defined radio development platform is presented, and the performance recorded through the hardware is observed to corroborate well with that obtained through simulations, allowing for implementation losses. (C) 2015 Elsevier B.V. All rights reserved.

Limited-view light sheet fluorescence microscopy for three dimensional volume imaging

We propose and demonstrate a limited-view light sheet microscopy (LV-LSM) for three dimensional (3D) volume imaging. Realizing that longer and frequent image acquisition results in significant photo-bleaching, we have taken limited angular views (18 views) of the macroscopic specimen and integrated with maximum likelihood (ML) technique for reconstructing high quality 3D volume images. Existing variants of light-sheet microscopy require both rotation and translation with a total of approximately 10-fold more views to render a 3D volume image. Comparatively, LV-LSM technique reduces data acquisition time and consequently minimizes light-exposure by many-folds. Since ML is a post-processing technique and highly parallelizable, this does not cost precious imaging time. Results show noise-free and high contrast volume images when compared to the state-of-the-art selective plane illumination microscopy. (C) 2015 AIP Publishing LLC.

Potency and pharmacokinetics of broad spectrum and isoform-specific p110 gamma and delta inhibitors in cancers

Emerging data on cancer suggesting that target-based therapy is promising strategy in cancer treatment. PI3K-AKT pathway is extensively studied in many cancers; several inhibitors target this pathway in different levels. Recent finding on this pathway uncovered the therapeutic applications of PI3K-specific inhibitors; PI3K, AKT, and mTORC broad spectrum inhibitors. Noticeably, class I PI3K isoforms, p110 and p110 catalytic subunits have rational therapeutic application than other isoforms. Therefore, three classes of inhibitors: isoform-specific, dual-specific and broad spectrum were selected for molecular docking and dynamics. First, p110 structure was modelled; active site was analyzed. Then, molecular docking of each class of inhibitors were studied; the docked complexes were further used in 1.2ns molecular dynamics simulation to report the potency of each class of inhibitor. Remarkably, both the studies retained the similar kind of protein ligand interactions. GDC-0941, XL-147 (broad spectrum); TG100-115 (dual-specific); and AS-252424, PIK-294 (isoform-specific) were found to be potential inhibitors of p110 and p110, respectively. In addition to that pharmacokinetic properties are within recommended ranges. Finally, molecular phylogeny revealed that p110 and p110 are evolutionarily divergent; they probably need separate strategies for drug development.

Enhancement Mechanism of Fluorescence Intensity in Presence of Plasmonic Nanoparticles

The emission intensity of fluorophore molecule may change in presence of strong plasmon field induced by nanoparticles. The enhancement intensity is optimized through selective clustering or functionalization of nanoparticles in closed vicinity of fluorophore. Our study is aimed at understanding the enhancement mechanism of fluorescence intensity in presence of gold nanoparticles to utilize it in molecular sensing and in situ imaging in the microfluidic lab-on-chip device. Related phenomena are studied in situ in a microfluidic channel via fluorescence imaging. Detailed analysis is carried out to understand the possible mechanism of enhancement of fluorescence due to nanoparticles. In the present experimental study we show that SYTO9 fluorescence intensity increased in presence of Au nanoparticles of similar to 20 nm diameter. The fluorescence intensity is 20 time more compared to that in absence of Au nanoparticles. The enhancement of fluorescence intensity is attributed to the plasmonic resonance of Au nanoparticle at around the fluorescence emission wavelength. Underlying fundamental mechanism via dipole interaction model is explored for quantitative correlation of plasmonic enhancement properties.

Elucidating the cancer-specific genetic alteration spectrum of glioblastoma derived cell lines from whole exome and RNA sequencing

Cell lines derived from tumor tissues have been used as a valuable system to study gene regulation and cancer development. Comprehensive characterization of the genetic background of cell lines could provide clues on novel genes responsible for carcinogenesis and help in choosing cell lines for particular studies. Here, we have carried out whole exome and RNA sequencing of commonly used glioblastoma (GBM) cell lines (U87, T98G, LN229, U343, U373 and LN18) to unearth single nucleotide variations (SNVs), indels, differential gene expression, gene fusions and RNA editing events. We obtained an average of 41,071 SNVs out of which 1,594 (3.88%) were potentially cancer-specific. The cell lines showed frequent SNVs and indels in some of the genes that are known to be altered in GBM-EGFR, TP53, PTEN, SPTA1 and NF1. Chromatin modifying genes-ATRX, MLL3, MLL4, SETD2 and SRCAP also showed alterations. While no cell line carried IDH1 mutations, five cell lines showed hTERT promoter activating mutations with a concomitant increase in hTERT transcript levels. Five significant gene fusions were found of which NUP93-CYB5B was validated. An average of 18,949 RNA editing events was also obtained. Thus we have generated a comprehensive catalogue of genetic alterations for six GBM cell lines.