An MLSA-based online scheme for the rapid identification of Stenotrophomonas isolates

An online scheme to assign Stenotrophomonas isolates to genomic groups was developed using the multilocus sequence analysis (MLSA), which is based on the DNA sequencing of selected fragments of the housekeeping genes ATP synthase alpha subunit (atpA), the recombination repair protein (recA), the RNA polymerase alpha subunit (rpoA) and the excision repair beta subunit (uvrB). This MLSA-based scheme was validated using eight of the 10 Stenotrophomonas species that have been previously described. The environmental and nosocomial Stenotrophomonas strains were characterised using MLSA, 16S rRNA sequencing and DNA-DNA hybridisation (DDH) analyses. Strains of the same species were found to have greater than 95% concatenated sequence similarity and specific strains formed cohesive readily recognisable phylogenetic groups. Therefore, MLSA appeared to be an effective alternative methodology to amplified fragment length polymorphism fingerprint and DDH techniques. Strains of Stenotrophomonas can be readily assigned through the open database resource that was developed in the current study (www.steno.lncc.br/)

A numerical and analytical study of two holes doped into the 2D t--J model

Exact diagonalization numerical results are presented for a 32-site square cluster, with two holes propagating in an antiferromagnetic background described by the t-J model. We characterize the wave function of the lowest energy bound state found in this calculation, which has d_{x^2-y^2} symmetry. Analytical work is presented, based on a Lang-Firsov-type canonical transformation derived quasiparticle Hamiltonian, that accurately agrees with numerically determined values for the electron momentum distribution function and the pair correlation function. We interpret this agreement as strong support for the validity of this description of the hole quasiparticles.Comment: 3 pages, REVTeX, to appear in the proceedings of the Fifth International Conference on Spectroscopies in Novel Superconductors, September 14-18, 1997, Cape Cod, Massachusett

Consciousness Regained: Disentangling Mechanisms, Brain Systems, and Behavioral Responses

How consciousness (experience) arises from and relates to material brain processes (the "mind-body problem") has been pondered by thinkers for centuries, and is regarded as among the deepest unsolved problems in science, with wide-ranging theoretical, clinical, and ethical implications. Until the last few decades, this was largely seen as a philosophical topic, but not widely accepted in mainstream neuroscience. Since the 1980s, however, novel methods and theoretical advances have yielded remarkable results, opening up the field for scientific and clinical progress. Since a seminal paper by Crick and Koch (1998) claimed that a science of consciousness should first search for its neural correlates (NCC), a variety of correlates have been suggested, including both content-specific NCCs, determining particular phenomenal components within an experience, and the full NCC, the neural substrates supporting entire conscious experiences. In this review, we present recent progress on theoretical, experimental, and clinical issues. Specifically, we (1) review methodological advances that are important for dissociating conscious experience from related enabling and executive functions, (2) suggest how critically reconsidering the role of the frontal cortex may further delineate NCCs, (3) advocate the need for general, objective, brain-based measures of the capacity for consciousness that are independent of sensory processing and executive functions, and (4) show how animal studies can reveal population and network phenomena of relevance for understanding mechanisms of consciousness.European Union's Horizon 2020 Research and Innovation ProgrammeHermann and Lilly Schilling FoundationGerman Research FoundationCenter for Nanoscale Microscopy and Molecular Physiology of the BrainNational Institutes of Health/National Institute of Neurological Disorders and StrokeSao Paulo Research FoundationJames S. McDonnell Foundation Scholar AwardEU Grant H2020-FETOPENCanadian Institute for Advanced ResearchAzrieli Program in Brain, Mind and ConsciousnessFLAG-ERA JTC project CANONNorwegian Research CouncilNetherlands Organization for Scientific ResearchUniv Oslo, Inst Basal Med Sci, Div Physiol, Dept Mol Med, POB 1103 Blindern, N-0317 Oslo, NorwayUniv Wisconsin, Dept Neurol, Madison, WI 53705 USAUniv Wisconsin, Dept Psychiat, Madison, WI 53719 USAUniv Fed Sao Paulo, Inst Sci & Technol, BR-12231280 Sao Jose Dos Campos, SP, BrazilUniv Milan, Dept Biomed & Clin Sci Luigi Sacco, I-20157 Milan, ItalyFdn Don Carlo Gnocchi ONLUS, Ist Ricovero & Cura Carattere Sci, I-20162 Milan, ItalyUniv Amsterdam, Swammerdam Inst Life Sci, Cognit & Syst Neurosci Grp, NL-1098 XH Amsterdam, NetherlandsUniv Amsterdam, Res Prior Program Brain & Cognit, NL-1098 XH Amsterdam, NetherlandsUniv Med Goettingen, Dept Cognit Neurol, D-37075 Gottingen, GermanyLeibniz Inst Primate Res, German Primate Ctr, D-37077 Gottingen, GermanyLeibniz Sci Campus Primate Cognit, D-37077 Gottingen, GermanyUniv Fed Sao Paulo, Inst Sci & Technol, BR-12231280 Sao Jose Dos Campos, SP, BrazilEuropean Union's Horizon 2020 Research and Innovation Programme: 720270German Research Foundation: WI 4046/1-1National Institutes of Health/National Institute of Neurological Disorders and Stroke: 1R03NS096379FAPESP: 2016/08263-9EU Grant H2020-FETOPEN: RIA 686764Web of Scienc

Evaluation of Ca-Based Sorbents for Gaseous HCl Emissions Adsorption

The problem of acid gas exhaust emissions treatment has not been fully resolved at present. Dry adsorption of acid gases with alkaline sorbents is currently being investigated, to improve solid sorbents. In this study, 5 types of hydrated lime were characterised and tested. The sorption capacities were measured by means of a system consisting of a feed line (HCl/N2), a thermostatic reactor and a water absorber. The physical characteristics of sorbent samples were also compared. Analyses conducted with scanning electronic microscopy revealed that sample C1 showed uniform particle distribution. Samples C2 and C3 showed the co-presence of fine and coarse particles. Sample C4 showed very fine particles with agglomeration phenomena. In sample C5, fibrous elements were found. Energy dispersive spectrometry (EDS) analyses showed a similar composition of the samples, with the exception of the presence of Mg in some of them. After 30 min of testing, the following differences in sorption capacities with respect to C1 (3.59 mg g−1) were found: C2, −20%; C3, −13%; C4, −17%; C5, −3%. Higher sorption capacities were associated with more uniform particle size distributions. Conversely, agglomeration of fine particles may have adversely affected the performance of sorbents

Data Publication with the Structural Biology Data Grid Supports Live Analysis

Access to experimental X-ray diffraction image data is fundamental for validation and reproduction of macromolecular models and indispensable for development of structural biology processing methods. Here, we established a diffraction data publication and dissemination system, Structural Biology Data Grid (SBDG; data.sbgrid.org), to preserve primary experimental data sets that support scientific publications. Data sets are accessible to researchers through a community driven data grid, which facilitates global data access. Our analysis of a pilot collection of crystallographic data sets demonstrates that the information archived by SBDG is sufficient to reprocess data to statistics that meet or exceed the quality of the original published structures. SBDG has extended its services to the entire community and is used to develop support for other types of biomedical data sets. It is anticipated that access to the experimental data sets will enhance the paradigm shift in the community towards a much more dynamic body of continuously improving data analysis

Data publication with the structural biology data grid supports live analysis

Access to experimental X-ray diffraction image data is fundamental for validation and reproduction of macromolecular models and indispensable for development of structural biology processing methods. Here, we established a diffraction data publication and dissemination system, Structural Biology Data Grid (SBDG; data. sbgrid. org), to preserve primary experimental data sets that support scientific publications. Data sets are accessible to researchers through a community driven data grid, which facilitates global data access. Our analysis of a pilot collection of crystallographic data sets demonstrates that the information archived by SBDG is sufficient to reprocess data to statistics that meet or exceed the quality of the original published structures. SBDG has extended its services to the entire community and is used to develop support for other types of biomedical data sets. It is anticipated that access to the experimental data sets will enhance the paradigm shift in the community towards a much more dynamic body of continuously improving data analysis

Hierarchical ResNeXt Models for Breast Cancer Histology Image Classification

Microscopic histology image analysis is a cornerstone in early detection of breast cancer. However these images are very large and manual analysis is error prone and very time consuming. Thus automating this process is in high demand. We proposed a hierarchical system of convolutional neural networks (CNN) that classifies automatically patches of these images into four pathologies: normal, benign, in situ carcinoma and invasive carcinoma. We evaluated our system on the BACH challenge dataset of image-wise classification and a small dataset that we used to extend it. Using a train/test split of 75%/25%, we achieved an accuracy rate of 0.99 on the test split for the BACH dataset and 0.96 on that of the extension. On the test of the BACH challenge, we've reached an accuracy of 0.81 which rank us to the 8th out of 51 teams

Data Publication with the Structural Biology Data Grid Supports Live Analysis

Access to experimental X-ray diffraction image data is fundamental for validation and reproduction of macromolecular models and indispensable for development of structural biology processing methods. Here, we established a diffraction data publication and dissemination system, Structural Biology Data Grid (SBDG; data.sbgrid.org), to preserve primary experimental data sets that support scientific publications. Data sets are accessible to researchers through a community driven data grid, which facilitates global data access. Our analysis of a pilot collection of crystallographic data sets demonstrates that the information archived by SBDG is sufficient to reprocess data to statistics that meet or exceed the quality of the original published structures. SBDG has extended its services to the entire community and is used to develop support for other types of biomedical data sets. It is anticipated that access to the experimental data sets will enhance the paradigm shift in the community towards a much more dynamic body of continuously improving data analysis