Performance analysis of low-flux least-squares single-pixel imaging

A single-pixel camera is able to computationally form spatially resolved images using one photodetector and a spatial light modulator. The images it produces in low-light-level operation are imperfect, even when the number of measurements exceeds the number of pixels, because its photodetection measurements are corrupted by Poisson noise. Conventional performance analysis for single-pixel imaging generates estimates of mean-square error (MSE) from Monte Carlo simulations, which require long computational times. In this letter, we use random matrix theory to develop a closed-form approximation to the MSE of the widely used least-squares inversion method for Poisson noise-limited single-pixel imaging. We present numerical experiments that validate our approximation and a motivating example showing how our framework can be used to answer practical optical design questions for a single-pixel camera.This work was supported in part by the Samsung Scholarship and in part by the US National Science Foundation under Grant 1422034. (Samsung Scholarship; 1422034 - US National Science Foundation)Accepted manuscrip

Smartphone microendoscopy for high resolution fluorescence imaging

High resolution optical endoscopes are increasingly used in diagnosis of various medical conditions of internal organs, such as the gastrointestinal tracts, but they are too expensive for use in resource-poor settings. On the other hand, smartphones with high resolution cameras and Internet access have become more affordable, enabling them to diffuse into most rural areas and developing countries in the past decade. In this letter we describe a smartphone microendoscope that can take fluorescence images with a spatial resolution of 3.1 {\mu}m. Images collected from ex vivo, in vitro and in vivo samples using the device are also presented. The compact and cost-effective smartphone microendoscope may be envisaged as a powerful tool for detecting pre-cancerous lesions of internal organs in low and middle income countries.Comment: 4 pages, 4 figure

Photon-Efficient Computational 3D and Reflectivity Imaging with Single-Photon Detectors

Capturing depth and reflectivity images at low light levels from active illumination of a scene has wide-ranging applications. Conventionally, even with single-photon detectors, hundreds of photon detections are needed at each pixel to mitigate Poisson noise. We develop a robust method for estimating depth and reflectivity using on the order of 1 detected photon per pixel averaged over the scene. Our computational imager combines physically accurate single-photon counting statistics with exploitation of the spatial correlations present in real-world reflectivity and 3D structure. Experiments conducted in the presence of strong background light demonstrate that our computational imager is able to accurately recover scene depth and reflectivity, while traditional maximum-likelihood based imaging methods lead to estimates that are highly noisy. Our framework increases photon efficiency 100-fold over traditional processing and also improves, somewhat, upon first-photon imaging under a total acquisition time constraint in raster-scanned operation. Thus our new imager will be useful for rapid, low-power, and noise-tolerant active optical imaging, and its fixed dwell time will facilitate parallelization through use of a detector array.Comment: 11 pages, 8 figure

Computational multi-depth single-photon imaging

We present an imaging framework that is able to accurately reconstruct multiple depths at individual pixels from single-photon observations. Our active imaging method models the single-photon detection statistics from multiple reflectors within a pixel, and it also exploits the fact that a multi-depth profile at each pixel can be expressed as a sparse signal. We interpret the multi-depth reconstruction problem as a sparse deconvolution problem using single-photon observations, create a convex problem through discretization and relaxation, and use a modified iterative shrinkage-thresholding algorithm to efficiently solve for the optimal multi-depth solution. We experimentally demonstrate that the proposed framework is able to accurately reconstruct the depth features of an object that is behind a partially-reflecting scatterer and 4 m away from the imager with root mean-square error of 11 cm, using only 19 signal photon detections per pixel in the presence of moderate background light. In terms of root mean-square error, this is a factor of 4.2 improvement over the conventional method of Gaussian-mixture fitting for multi-depth recovery.This material is based upon work supported in part by a Samsung Scholarship, the US National Science Foundation under Grant No. 1422034, and the MIT Lincoln Laboratory Advanced Concepts Committee. We thank Dheera Venkatraman for his assistance with the experiments. (Samsung Scholarship; 1422034 - US National Science Foundation; MIT Lincoln Laboratory Advanced Concepts Committee)Accepted manuscrip

Single-Photon Depth Imaging Using a Union-of-Subspaces Model

Light detection and ranging systems reconstruct scene depth from time-of-flight measurements. For low light-level depth imaging applications, such as remote sensing and robot vision, these systems use single-photon detectors that resolve individual photon arrivals. Even so, they must detect a large number of photons to mitigate Poisson shot noise and reject anomalous photon detections from background light. We introduce a novel framework for accurate depth imaging using a small number of detected photons in the presence of an unknown amount of background light that may vary spatially. It employs a Poisson observation model for the photon detections plus a union-of-subspaces constraint on the discrete-time flux from the scene at any single pixel. Together, they enable a greedy signal-pursuit algorithm to rapidly and simultaneously converge on accurate estimates of scene depth and background flux, without any assumptions on spatial correlations of the depth or background flux. Using experimental single-photon data, we demonstrate that our proposed framework recovers depth features with 1.7 cm absolute error, using 15 photons per image pixel and an illumination pulse with 6.7-cm scaled root-mean-square length. We also show that our framework outperforms the conventional pixelwise log-matched filtering, which is a computationally-efficient approximation to the maximum-likelihood solution, by a factor of 6.1 in absolute depth error.Samsung (Firm) (Scholarship)National Science Foundation (U.S.) (Grant 1422034)Lincoln Laboratory. Advanced Concepts Committe

PURIFICATION AND BIOCHEMICAL CHARACTERIZATION OF L-AMINO ACID OXIDASE FROM WESTERN REGION INDIAN COBRA (NAJA NAJA) VENOM

Objective: Purification and biochemical characterization of LAAO from western region Indian Cobra (Naja naja) venom.Methods: LAAO was purified from Indian cobra (Naja naja) venom using sequential chromatography on Sephadex G-75 gel filtration followed by Ion exchange on CM-Sephadex C-25 column. Biochemical characterization viz., pH, Temperature, Km and Vmax were determined. Molecular weight of LAAO was determined by electrophoresis. Inhibition of LAAO from cold water extracts of Curcuma zedoria, Curcuma ceasia, Curcuma aromatic, Curcuma longa, Curcuma amada, Cucumis sativus and Benincasa hispida was done.Results: Purified LAAO showed the single band on non reducing SDS-PAGE with approximate molecular weight of 65 kDa. Further biochemical characterization revealed that, LAAO from Naja naja (western region) has an optimum pH of 7.0 and is stable at room Temperature upto 37 °C and showed an optimum enzyme concentration of 4µg/ml and Km 134.1µM and Vmax is 21.87 U/min. Cold water extract of Curcuma ceasia, Curcuma aromatic and Benincasa hispida showed comparatively significant inhibition of LAAO.Conclusion: LAAO has promising therapeutic prospects because of its effects on various biological functions. Variation in snake species and their geographical distribution also contributes to the venom properties such as composition, toxicity level, pharmacological and biological activities. The significant difference in protein profiling leads to substantial lethality among different geographical regions. Thus in this study Indian Cobra (Naja naja) venom from the western region of India was subjected to purification of LAAO and biochemical characterization. Â

Molecular epidemiology of canine parvovirus in southern India

Aim: The present study was conducted to isolate and characterize canine parvovirus circulating in Southern India by genetic analysis of VP2 capsid protein gene.Materials and Methods: In this study, 128 samples were collected from nine different locations covering five Southern Indian states (Pondicherry, Tamil Nadu, Kerala, Andhra Pradesh and Karnataka) . Out of 128 samples, 69 samples were found to be positive by PCR assay. Out of 69 positive samples, 36 were randomly selected and processed for virus isolation. Twenty viruses could be isolated successfully and 18 randomly selected isolate were subjected to VP2 gene sequence analysis along with 6 random clinical samples.Result: Seventeen isolates and 5 clinical samples were characterized as New CPV-2a (CPV2a with 297-Ser→Ala). But one isolate and one clinical sample had amino acids variations which were characteristics of New CPV-2b. The phylogenetic analysis revealed that one of the field isolates was found to be phylogenetically closely related to New CPV-2b strains of India; rest other sequences was found to share ancestral origins with New CPV-2a reference strains of Japan, China, Thailand and India.Conclusion: The present study revealed that the predominant CPV strain circulating in Southern India is New CPV-2a. There is also enough indication of New CPV-2b strain from different states of Southern India

Targeting of Histone Acetyltransferase p300 by Cyclopentenone Prostaglandin Δ12-PGJ2 through Covalent Binding to Cys1438

This document is the Accepted Manuscript version of a Published Work that appeared in final form in Chemical Research in Toxicology, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see http://pubs.acs.org/doi/abs/10.1021/tx200383cInhibitors of histone acetyltransferases (HATs) are perceived to treat diseases like cancer, neurodegeneration, and AIDS. On the basis of previous studies, we hypothesized that Cys1438 in the substrate binding site could be targeted by Δ12-prostaglandin J2 (Δ12-PGJ2), a cyclopentenone prostaglandin (CyPG) derived from PGD2. We demonstrate here the ability of CyPGs to inhibit p300 HAT-dependent acetylation of histone H3. A cell-based assay system clearly showed that the α,β-unsaturation in the cyclopentenone ring of Δ12-PGJ2 was crucial for the inhibitory activity, while the 9,10-dihydro-15-deoxy- Δ12,14-PGJ2, which lacks the electrophilic carbon (at carbon 9), was ineffective. Molecular docking studies suggested that Δ12-PGJ2 places the electrophilic carbon in the cyclopentenone ring well within the vicinity of Cys1438 of p300 to form a covalent Michael adduct. Site-directed mutagenesis of the p300 HAT domain, peptide competition assay involving p300 wild type and mutant peptides, followed by mass spectrometric analysis confirmed the covalent interaction of Δ12-PGJ2 with Cys1438. Using biotinylated derivatives of Δ12-PGJ2 and 9,10-dihydro-15-deoxy- Δ12,14-PGJ2, we demonstrate the covalent interaction of Δ12-PGJ2 with the p300 HAT domain, but not the latter. In agreement with the in vitro filter binding assay, CyPGs were also found to inhibit H3 histone acetylation in cell-based assays. In addition, Δ12-PGJ2 also inhibited the acetylation of the HIV-1 Tat by recombinant p300 in in vitro assays. This study demonstrates, for the first time, that Δ12-PGJ2 inhibits p300 through Michael addition, where α,β-unsaturated carbonyl function is absolutely required for the inhibitory activity