Phylogenetic relationships of the Fox (Forkhead) gene family in the Bilateria

The Forkhead or Fox gene family encodes putative transcription factors. There are at least four Fox genes in yeast, 16 in Drosophila melanogaster (Dm) and 42 in humans. Recently, vertebrate Fox genes have been classified into 17 groups named FoxA to FoxQ [Genes Dev. 14 (2000) 142]. Here, we extend this analysis to invertebrates, using available sequences from D. melanogaster, Anopheles gambiae (Ag), Caenorhabditis elegans (Ce), the sea squirt Ciona intestinalis (Ci) and amphioxus Branchiostoma floridae (Bf), from which we also cloned several Fox genes. Phylogenetic analyses lend support to the previous overall subclassification of vertebrate genes, but suggest that four subclasses (FoxJ, L, N and Q) could be further subdivided to reflect their relationships to invertebrate genes. We were unable to identify orthologs of Fox subclasses E, H, I, J, M and Q1 in D. melanogaster, A. gambiae or C. elegans, suggesting either considerable loss in ecdysozoans or the evolution of these subclasses in the deuterostome lineage. Our analyses suggest that the common ancestor of protostomes and deuterostomes had a minimum complement of 14 Fox genes. (C) 2003 Elsevier B.V. All rights reserved.

Cloacibacterium normanense gen. nov., sp nov., a novel bacterium in the family Flavobacteriaceae isolated from municipal wastewater

Phenotypic and phylogenetic studies were performed on three isolates of an unknown Gram-negative, facultatively anaerobic, non-motile, yellow-pigmented, rod-shaped organism isolated from raw sewage. 16S rRNA gene sequence analysis indicated that these strains were members of the Bergeyella-Chryseobacterium-Riemerella branch of the family Flavobacteriaceae. The unknown bacterium was readily distinguished from reference strains by 16S rRNA gene sequencing and biochemical tests. The organism contained menaquinone MK-6 as the predominant respiratory quinone and had a DNA G + C content of 31 mol%. A most probable number-PCR approach was developed to detect, and estimate the numbers of, this organism. Untreated wastewater from one plant yielded an estimated count of 1.4 x 10(5) cells ml(-1), and untreated wastewater from a second plant yielded an estimated count of 1.4 x 10(4) cells ml(-1). Signal was not detected from treated effluent or from human stool specimens. On the basis of the results of the study presented, it is proposed that the unknown bacterium be classified in a novel genus Cloacibacterium, as Cloacibacterium normanense gen. nov., sp. nov., which is also the type species. The type strain of Cloacibacterium normanense is strain NRS1(T) (=CCUG 46293(T)=CIP 108613(T) =ATCC BAA-825(T) = DSM 15886(T)).

Delineation and modelling of a nucleolar retention signal in the coronavirus nucleocapsid protein

Unlike nuclear localization signals, there is no obvious consensus sequence for the targeting of proteins to the nucleolus. The nucleolus is a dynamic subnuclear structure which is crucial to the normal operation of the eukaryotic cell. Studying nucleolar trafficking signals is problematic as many nucleolar retention signals (NoRSs) are part of classical nuclear localization signals (NLSs). In addition, there is no known consensus signal with which to inform a study. The avian infectious bronchitis virus (IBV), coronavirus nucleocapsid (N) protein, localizes to the cytoplasm and the nucleolus. Mutagenesis was used to delineate a novel eight amino acid motif that was necessary and sufficient for nucleolar retention of N protein and colocalize with nucleolin and fibrillarin. Additionally, a classical nuclear export signal (NES) functioned to direct N protein to the cytoplasm. Comparison of the coronavirus NoRSs with known cellular and other viral NoRSs revealed that these motifs have conserved arginine residues. Molecular modelling, using the solution structure of severe acute respiratory (SARS) coronavirus N-protein, revealed that this motif is available for interaction with cellular factors which may mediate nucleolar localization. We hypothesise that the N-protein uses these signals to traffic to and from the nucleolus and the cytoplasm.

EMG signal filtering based on Empirical Mode Decomposition

This paper introduces a procedure for filtering electromyographic (EMG) signals. Its key element is the Empirical Mode Decomposition, a novel digital signal processing technique that can decompose my time-series into a set of functions designated as intrinsic mode functions. The procedure for EMG signal filtering is compared to a related approach based on the wavelet transform. Results obtained from the analysis of synthetic and experimental EMG signals show that Our method can be Successfully and easily applied in practice to attenuation of background activity in EMG signals. (c) 2006 Elsevier Ltd. All rights reserved.

Comparison of extrasystolic ECG signal classifiers using discrete wavelet transforms

This work compares and contrasts results of classifying time-domain ECG signals with pathological conditions taken from the MITBIH arrhythmia database. Linear discriminant analysis and a multi-layer perceptron were used as classifiers. The neural network was trained by two different methods, namely back-propagation and a genetic algorithm. Converting the time-domain signal into the wavelet domain reduced the dimensionality of the problem at least 10-fold. This was achieved using wavelets from the db6 family as well as using adaptive wavelets generated using two different strategies. The wavelet transforms used in this study were limited to two decomposition levels. A neural network with evolved weights proved to be the best classifier with a maximum of 99.6% accuracy when optimised wavelet-transform ECG data wits presented to its input and 95.9% accuracy when the signals presented to its input were decomposed using db6 wavelets. The linear discriminant analysis achieved a maximum classification accuracy of 95.7% when presented with optimised and 95.5% with db6 wavelet coefficients. It is shown that the much simpler signal representation of a few wavelet coefficients obtained through an optimised discrete wavelet transform facilitates the classification of non-stationary time-variant signals task considerably. In addition, the results indicate that wavelet optimisation may improve the classification ability of a neural network. (c) 2005 Elsevier B.V. All rights reserved.

Invasive neural prosthesis for neural signal detection and nerve stimulation

This paper specifically examines the implantation of a microelectrode array into the median nerve of the left arm of a healthy male volunteer. The objective was to establish a bi-directional link between the human nervous system and a computer, via a unique interface module. This is the first time that such a device has been used with a healthy human. The aim of the study was to assess the efficacy, compatibility, and long term operability of the neural implant in allowing the subject to perceive feedback stimulation and for neural activity to be detected and processed such that the subject could interact with remote technologies. A case study demonstrating real-time control of an instrumented prosthetic hand by means of the bi-directional link is given. The implantation did not result in infection, and scanning electron microscope images of the implant post extraction have not indicated significant rejection of the implant by the body. No perceivable loss of hand sensation or motion control was experienced by the subject while the implant was in place, and further testing of the subject following the removal of the implant has not indicated any measurable long term defects. The implant was extracted after 96 days. Copyright © 2004 John Wiley & Sons, Ltd.

High signal to noise ratio THz spectroscopy with ASOPS and signal processing schemes for mapping and controlling molecular and bulk relaxation processes

Asynchronous Optical Sampling has the potential to improve signal to noise ratio in THz transient sperctrometry. The design of an inexpensive control scheme for synchronising two femtosecond pulse frequency comb generators at an offset frequency of 20 kHz is discussed. The suitability of a range of signal processing schemes adopted from the Systems Identification and Control Theory community for further processing recorded THz transients in the time and frequency domain are outlined. Finally, possibilities for femtosecond pulse shaping using genetic algorithms are mentioned.

Signal detection for distributed space-time block coding: 4 relay nodes under quasi-synchronisation

Most research on Distributed Space-Time Block Coding (D-STBC) has so far focused on the case of 2 relay nodes and assumed that the relay nodes are perfectly synchronised at the symbol level. This paper applies STBC to 4-relaynode systems under quasi-synchronisation and derives a new detector based on parallel interference cancellation, which proves to be very effective in suppressing the impact of imperfect synchronisation.

Retrievals of thick cloud optical depth from the Geoscience Laser Altimeter System (GLAS) by calibration of solar background signal

Laser beams emitted from the Geoscience Laser Altimeter System (GLAS), as well as other spaceborne laser instruments, can only penetrate clouds to a limit of a few optical depths. As a result, only optical depths of thinner clouds (< about 3 for GLAS) are retrieved from the reflected lidar signal. This paper presents a comprehensive study of possible retrievals of optical depth of thick clouds using solar background light and treating GLAS as a solar radiometer. To do so one must first calibrate the reflected solar radiation received by the photon-counting detectors of the GLAS 532-nm channel, the primary channel for atmospheric products. Solar background radiation is regarded as a noise to be subtracted in the retrieval process of the lidar products. However, once calibrated, it becomes a signal that can be used in studying the properties of optically thick clouds. In this paper, three calibration methods are presented: (i) calibration with coincident airborne and GLAS observations, (ii) calibration with coincident Geostationary Opera- tional Environmental Satellite (GOES) and GLAS observations of deep convective clouds, and (iii) cali- bration from first principles using optical depth of thin water clouds over ocean retrieved by GLAS active remote sensing. Results from the three methods agree well with each other. Cloud optical depth (COD) is retrieved from the calibrated solar background signal using a one-channel retrieval. Comparison with COD retrieved from GOES during GLAS overpasses shows that the average difference between the two retriev- als is 24%. As an example, the COD values retrieved from GLAS solar background are illustrated for a marine stratocumulus cloud field that is too thick to be penetrated by the GLAS laser. Based on this study, optical depths for thick clouds will be provided as a supplementary product to the existing operational GLAS cloud products in future GLAS data releases.

Phenotypic and phylogenetic characterization of a new Corynebacterium species from dogs: description of Corynebacterium auriscanis sp. nov.

Six strains of a previously undescribed catalase-positive coryneform bacterium isolated from clinical specimens from dogs were characterized by phenotypic and molecular genetic methods. Biochemical and chemotaxonomic studies revealed that the unknown bacterium belonged to the genus Corynebacterium sensu stricto. Comparative 16S rRNA gene sequencing showed that the six strains were genealogically highly related and constitute a new subline within the genus Corynebacterium; this subline is close to but distinct from C. falsenii, C. jeikeium, and C. urealyticum. The unknown bacterium from dogs was distinguished from all currently validated Corynebacterium species by phenotypic tests including electrophoretic analysis of whole-cell proteins. On the basis of phylogenetic and phenotypic evidence, it is proposed that the unknown bacterium be classified as a new species, Corynebacterium auriscanis. The type strain of C. auriscanis is CCUG 39938T.

Digital signal processing of optical monitoring by means of a Kalman filter

A Kalman filter algorithm has been applied to interpret the optical reflectance excursions during vacuum deposition of infrared coatings and multilayer thin-film filters. The application has been described in detail elsewhere and this paper now reports on-line experience for estimating deposition rate and thickness. The estimation proved sufficiently reliable to firstly 'navigate' regular manufacture (as controlled by a skilled operator) and to subsequently reproduce the skill without interpretation or intervention whilst maintaining exemplary product quality. Optical control by means of this Kalman filter application is therefore considered suitable as a basis for the automated manufacture of infrared coatings and multilayer thin-film filters.