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1.  Heat Stress Evaluation of Two-layer Chemical Demilitarization Ensembles with a Full Face Negative Pressure Respirator 
Industrial Health  2014;52(4):304-312.
The purpose of this study was to examine the heat stress effects of three protective clothing ensembles: (1) protective apron over cloth coveralls including full face negative pressure respirator (APRON); (2) the apron over cloth coveralls with respirator plus protective pants (APRON+PANTS); and (3) protective coveralls over cloth coveralls with respirator (PROTECTIVE COVERALLS). In addition, there was a no-respirator ensemble (PROTECTIVE COVERALLS-noR), and WORK CLOTHES as a reference ensemble. Four acclimatized male participants completed a full set of five trials, and two of the participants repeated the full set. The progressive heat stress protocol was used to find the critical WBGT (WBGTcrit) and apparent total evaporative resistance (Re,T,a) at the upper limit of thermal equilibrium. The results (WBGTcrit [°C-WBGT] and Re,T,a [kPa m2 W−1]) were WORK CLOTHES (35.5, 0.0115), APRON (31.6, 0.0179), APRON+PANTS (27.7, 0.0244), PROTECTIVE COVERALLS (25.9, 0.0290), and PROTECTIVE COVERALLS-noR (26.2, 0.0296). There were significant differences among the ensembles. Supporting previous studies, there was little evidence to suggest that the respirator contributed to heat stress.
PMCID: PMC4243016  PMID: 24705801
Heat stress; Chemical protective clothing; Respirators; Clothing adjustment factors; Evaporative resistance
2.  Microbiota Present in Cystic Fibrosis Lungs as Revealed by Whole Genome Sequencing 
PLoS ONE  2014;9(3):e90934.
Determination of the precise composition and variation of microbiota in cystic fibrosis lungs is crucial since chronic inflammation due to microorganisms leads to lung damage and ultimately, death. However, this constitutes a major technical challenge. Culturing of microorganisms does not provide a complete representation of a microbiota, even when using culturomics (high-throughput culture). So far, only PCR-based metagenomics have been investigated. However, these methods are biased towards certain microbial groups, and suffer from uncertain quantification of the different microbial domains. We have explored whole genome sequencing (WGS) using the Illumina high-throughput technology applied directly to DNA extracted from sputa obtained from two cystic fibrosis patients. To detect all microorganism groups, we used four procedures for DNA extraction, each with a different lysis protocol. We avoided biases due to whole DNA amplification thanks to the high efficiency of current Illumina technology. Phylogenomic classification of the reads by three different methods produced similar results. Our results suggest that WGS provides, in a single analysis, a better qualitative and quantitative assessment of microbiota compositions than cultures and PCRs. WGS identified a high quantity of Haemophilus spp. (patient 1) or Staphylococcus spp. plus Streptococcus spp. (patient 2) together with low amounts of anaerobic (Veillonella, Prevotella, Fusobacterium) and aerobic bacteria (Gemella, Moraxella, Granulicatella). WGS suggested that fungal members represented very low proportions of the microbiota, which were detected by cultures and PCRs because of their selectivity. The future increase of reads’ sizes and decrease in cost should ensure the usefulness of WGS for the characterisation of microbiota.
PMCID: PMC3944733  PMID: 24599149
3.  Occupational Heat Stress In USA: Whither We Go? 
Industrial Health  2014;52(1):1-4.
PMCID: PMC4202768  PMID: 24531131
4. a website and repository for accessing, analysing and manipulating metabolic networks 
Bioinformatics  2013;29(6):815-816.
Summary: is a website for accessing, analysing and manipulating genome-scale metabolic networks (GSMs) as well as biochemical pathways. It consistently integrates data from various public resources and makes the data accessible in a standardized format using a common namespace. Currently, it provides access to hundreds of GSMs and pathways that can be interactively compared (two or more), analysed (e.g. detection of dead-end metabolites and reactions, flux balance analysis or simulation of reaction and gene knockouts), manipulated and exported. Users can also upload their own metabolic models, choose to automatically map them into the common namespace and subsequently make use of the website’s functionality.
Availability and implementation: is available at
PMCID: PMC3597148  PMID: 23357920
5.  Reconciliation of metabolites and biochemical reactions for metabolic networks 
Briefings in Bioinformatics  2012;15(1):123-135.
Genome-scale metabolic network reconstructions are now routinely used in the study of metabolic pathways, their evolution and design. The development of such reconstructions involves the integration of information on reactions and metabolites from the scientific literature as well as public databases and existing genome-scale metabolic models. The reconciliation of discrepancies between data from these sources generally requires significant manual curation, which constitutes a major obstacle in efforts to develop and apply genome-scale metabolic network reconstructions. In this work, we discuss some of the major difficulties encountered in the mapping and reconciliation of metabolic resources and review three recent initiatives that aim to accelerate this process, namely BKM-react, MetRxn and MNXref (presented in this article). Each of these resources provides a pre-compiled reconciliation of many of the most commonly used metabolic resources. By reducing the time required for manual curation of metabolite and reaction discrepancies, these resources aim to accelerate the development and application of high-quality genome-scale metabolic network reconstructions and models.
PMCID: PMC3896926  PMID: 23172809
data integration; data interoperability; metabolic resources; metabolic networks; cheminformatics
7.  InterPro in 2011: new developments in the family and domain prediction database 
Nucleic Acids Research  2011;40(Database issue):D306-D312.
InterPro ( is a database that integrates diverse information about protein families, domains and functional sites, and makes it freely available to the public via Web-based interfaces and services. Central to the database are diagnostic models, known as signatures, against which protein sequences can be searched to determine their potential function. InterPro has utility in the large-scale analysis of whole genomes and meta-genomes, as well as in characterizing individual protein sequences. Herein we give an overview of new developments in the database and its associated software since 2009, including updates to database content, curation processes and Web and programmatic interfaces.
PMCID: PMC3245097  PMID: 22096229
8.  The Carbohydrate-Active EnZymes database (CAZy): an expert resource for Glycogenomics 
Nucleic Acids Research  2008;37(Database issue):D233-D238.
The Carbohydrate-Active Enzyme (CAZy) database is a knowledge-based resource specialized in the enzymes that build and breakdown complex carbohydrates and glycoconjugates. As of September 2008, the database describes the present knowledge on 113 glycoside hydrolase, 91 glycosyltransferase, 19 polysaccharide lyase, 15 carbohydrate esterase and 52 carbohydrate-binding module families. These families are created based on experimentally characterized proteins and are populated by sequences from public databases with significant similarity. Protein biochemical information is continuously curated based on the available literature and structural information. Over 6400 proteins have assigned EC numbers and 700 proteins have a PDB structure. The classification (i) reflects the structural features of these enzymes better than their sole substrate specificity, (ii) helps to reveal the evolutionary relationships between these enzymes and (iii) provides a convenient framework to understand mechanistic properties. This resource has been available for over 10 years to the scientific community, contributing to information dissemination and providing a transversal nomenclature to glycobiologists. More recently, this resource has been used to improve the quality of functional predictions of a number genome projects by providing expert annotation. The CAZy resource resides at URL:
PMCID: PMC2686590  PMID: 18838391

Results 1-8 (8)