Semi-supervised linear spectral unmixing using a hierarchical Bayesian model for hyperspectral imagery

This paper proposes a hierarchical Bayesian model that can be used for semi-supervised hyperspectral image unmixing. The model assumes that the pixel reflectances result from linear combinations of pure component spectra contaminated by an additive Gaussian noise. The abundance parameters appearing in this model satisfy positivity and additivity constraints. These constraints are naturally expressed in a Bayesian context by using appropriate abundance prior distributions. The posterior distributions of the unknown model parameters are then derived. A Gibbs sampler allows one to draw samples distributed according to the posteriors of interest and to estimate the unknown abundances. An extension of the algorithm is finally studied for mixtures with unknown numbers of spectral components belonging to a know library. The performance of the different unmixing strategies is evaluated via simulations conducted on synthetic and real data

Inactivation of the particulate methane monooxygenase (pMMO) in Methylococcus capsulatus (Bath) by acetylene

Acetylene (HCCH) has a long history as a mechanism-based enzyme inhibitor and is considered an active-site probe of the particulate methane monooxygenase (pMMO). Here, we report how HCCH inactivates pMMO in Methylococcus capsulatus (Bath) by using high-resolution mass spectrometry and computational simulation. High-resolution MALDI-TOF MS of intact pMMO complexes has allowed us to confirm that the enzyme oxidizes HCCH to the ketene (C_2H_2O) intermediate, which then forms an acetylation adduct with the transmembrane PmoC subunit. LC-MS/MS analysis of the peptides derived from in-gel proteolytic digestion of the protein subunit identifies K196 of PmoC as the site of acetylation. No evidence is obtained for chemical modification of the PmoA or PmoB subunit. The inactivation of pMMO by a single adduct in the transmembrane PmoC domain is intriguing given the complexity of the structural fold of this large membrane-protein complex as well as the complicated roles played by the various metal cofactors in the enzyme catalysis. Computational studies suggest that the entry of hydrophobic substrates to, and migration of products from, the catalytic site of pMMO is controlled tightly within the transmembrane domain. Support of these conclusions is provided by parallel experiments with two related alkynes: propyne (CH3CCH) and trifluoropropyne (CF_3CCH). Finally, we discuss the implication of these findings to the location of the catalytic site in pMMO

Specific, sensitive and rapid detection of human plasmodium knowlesi infection by loop-mediated isothermal amplification (LAMP) in blood samples

<p>Abstract</p> <p>Background</p> <p>The emergence of <it>Plasmodium knowlesi </it>in humans, which is in many cases misdiagnosed by microscopy as <it>Plasmodium malariae </it>due to the morphological similarity has contributed to the needs of detection and differentiation of malaria parasites. At present, nested PCR targeted on <it>Plasmodium </it>ssrRNA genes has been described as the most sensitive and specific method for Plasmodium detection. However, this method is costly and requires trained personnel for its implementation. Loop-mediated isothermal amplification (LAMP), a novel nucleic acid amplification method was developed for the clinical detection of <it>P. knowlesi</it>. The sensitivity and specificity of LAMP was evaluated in comparison to the results obtained via microscopic examination and nested PCR.</p> <p>Methods</p> <p>LAMP assay was developed based on <it>P. knowlesi </it>genetic material targeting the apical membrane antigen-1 (AMA-1) gene. The method uses six primers that recognize eight regions of the target DNA and it amplifies DNA within an hour under isothermal conditions (65°C) in a water-bath.</p> <p>Results</p> <p>LAMP is highly sensitive with the detection limit as low as ten copies for AMA-1. LAMP detected malaria parasites in all confirm cases (n = 13) of <it>P. knowlesi </it>infection (sensitivity, 100%) and none of the negative samples (specificity, 100%) within an hour. LAMP demonstrated higher sensitivity compared to nested PCR by successfully detecting a sample with very low parasitaemia (< 0.01%).</p> <p>Conclusion</p> <p>With continuous efforts in the optimization of this assay, LAMP may provide a simple and reliable test for detecting <it>P. knowlesi </it>malaria parasites in areas where malaria is prevalent.</p

Asian-Pacific consensus statement on the management of chronic hepatitis B: a 2008 update

Large amounts of new data on the natural history and treatment of chronic hepatitis B virus (HBV) infection have become available since 2005. These include long-term follow-up studies in large community-based cohorts or asymptomatic subjects with chronic HBV infection, further studies on the role of HBV genotype/naturally occurring HBV mutations, treatment of drug resistance and new therapies. In addition, Pegylated interferon α2a, entecavir and telbivudine have been approved globally. To update HBV management guidelines, relevant new data were reviewed and assessed by experts from the region, and the significance of the reported findings were discussed and debated. The earlier “Asian-Pacific consensus statement on the management of chronic hepatitis B” was revised accordingly. The key terms used in the statement were also defined. The new guidelines include general management, special indications for liver biopsy in patients with persistently normal alanine aminotransferase, time to start or stop drug therapy, choice of drug to initiate therapy, when and how to monitor the patients during and after stopping drug therapy. Recommendations on the therapy of patients in special circumstances, including women in childbearing age, patients with antiviral drug resistance, concurrent viral infection, hepatic decompensation, patients receiving immune-suppressive medications or chemotherapy and patients in the setting of liver transplantation, are also included

Real-time recursive hyperspectral sample and band processing: algorithm architecture and implementation

This book explores recursive architectures in designing progressive hyperspectral imaging algorithms. In particular, it makes progressive imaging algorithms recursive by introducing the concept of Kalman filtering in algorithm design so that hyperspectral imagery can be processed not only progressively sample by sample or band by band but also recursively via recursive equations. This book can be considered a companion book of author’s books, Real-Time Progressive Hyperspectral Image Processing, published by Springer in 2016. Explores recursive structures in algorithm architecture Implements algorithmic recursive architecture in conjunction with progressive sample and band processing Derives Recursive Hyperspectral Sample Processing (RHSP) techniques according to Band-Interleaved Sample/Pixel (BIS/BIP) acquisition format Develops Recursive Hyperspectral Band Processing (RHBP) techniques according to Band SeQuential (BSQ) acquisition format for hyperspectral data

Real-time progressive hyperspectral image processing: endmember finding and anomaly detection

The book covers the most crucial parts of real-time hyperspectral image processing: causality and real-time capability. Recently, two new concepts of real time hyperspectral image processing, Progressive Hyperspectral Imaging (PHSI) and Recursive Hyperspectral Imaging (RHSI). Both of these can be used to design algorithms and also form an integral part of real time hyperpsectral image processing. This book focuses on progressive nature in algorithms on their real-time and causal processing implementation in two major applications, endmember finding and anomaly detection, both of which are fundamental tasks in hyperspectral imaging but generally not encountered in multispectral imaging. This book is written to particularly address PHSI in real time processing, while a book, Recursive Hyperspectral Sample and Band Processing: Algorithm Architecture and Implementation (Springer 2016) can be considered as its companion book. Includes preliminary background which is essential to those who work in hyperspectral imaging area Develops sequential and progressive algorithms for finding endmembers as they relate to real time hyperspectral image processing Designs algorithms for anomaly detection from causality and real time perspectives and investigates the effects of causality and real-time processing in anomaly detection

Hyperspectral data exploitation: theory and applications

Authored by a panel of experts in the field, this book focuses on hyperspectral image analysis, systems, and applications. With discussion of application-based projects and case studies, this professional reference will bring you up-to-date on this pervasive technology, wether you are working in the military and defense fields, or in remote sensing technology, geoscience, or agriculture

Editorial for Special Issue “Hyperspectral Imaging and Applications”

Due to advent of sensor technology, hyperspectral imaging has become an emerging technology in remote sensing. Many problems, which cannot be resolved by multispectral imaging, can now be solved by hyperspectral imaging. The aim of this Special Issue &ldquo;Hyperspectral Imaging and Applications&rdquo; is to publish new ideas and technologies to facilitate the utility of hyperspectral imaging in data exploitation and to further explore its potential in different applications. This Special Issue has accepted and published 25 papers in various areas, which can be organized into 7 categories, Data Unmixing, Spectral variability, Target Detection, Hyperspectral Image Classification, Band Selection, Data Fusion, Applications