Modelling and optimisation of the operation of a radiant warmer

This paper presents numerical calculations of the temperature field obtained for the case of a neonate placed under a radiant warmer. The results of the simulations show a very non-uniform temperature distribution on the skin of the neonate, which may cause increased evaporation leading to severe dehydration. For this reason, we propose some modifications on the geometry and operation of the radiant warmer, in order to make the temperature distribution more uniform and prevent the high temperature gradients observed on the surface of the neonate. It is concluded that placing a high conductivity blanket over the neonate and introducing additional screens along the side of the mattress, thus recovering the radiation heat escaping through the side boundaries, helped providing more uniform temperature fields.The European Union for the Marie Curie Fellowship grant awarded to the Centre for CFD, University of Leeds

Comprehensive classification of the PIN domain-like superfamily

PIN-like domains constitute a widespread superfamily of nucleases, diverse in terms of the reaction mechanism, substrate specificity, biological function and taxonomic distribution. Proteins with PIN-like domains are involved in central cellular processes, such as DNA replication and repair, mRNA degradation, transcription regulation and ncRNA maturation. In this work, we identify and classify the most complete set of PIN-like domains to provide the first comprehensive analysis of sequence–structure–function relationships within the whole PIN domain-like superfamily. Transitive sequence searches using highly sensitive methods for remote homology detection led to the identification of several new families, including representatives of Pfam (DUF1308, DUF4935) and CDD (COG2454), and 23 other families not classified in the public domain databases. Further sequence clustering revealed relationships between individual sequence clusters and showed heterogeneity within some families, suggesting a possible functional divergence. With five structural groups, 70 defined clusters, over 100,000 proteins, and broad biological functions, the PIN domain-like superfamily constitutes one of the largest and most diverse nuclease superfamilies. Detailed analyses of sequences and structures, domain architectures, and genomic contexts allowed us to predict biological function of several new families, including new toxin-antitoxin components, proteins involved in tRNA/rRNA maturation and transcription/translation regulation

Systematic classification of the His-Me finger superfamily

The His-Me finger endonucleases, also known as HNH or -metal endonucleases, form a large and diverse protein superfamily. The His-Me finger domain can be found in proteins that play an essential role in cells, including genome maintenance, intron homing, host defense and target offense. Its overall structural compactness and non-specificity make it a perfectly-tailored pathogenic module that participates on both sides of inter- and intra-organismal competition. An extremely low sequence similarity across the superfamily makes it difficult to identify and classify new His-Me fingers. Using state-of-theart distant homology detection methods, we provide an updated and systematic classification of His-Me finger proteins. In this work, we identified over 100 000 proteins and clustered them into 38 groups, of which three groups are new and cannot be found in any existing public domain database of protein families. Based on an analysis of sequences, structures, domain architectures, and genomic contexts, we provide a careful functional annotation of the poorly characterized members of this superfamily. Our results may inspire further experimental investigations that should address the predicted activity and clarify the potential substrates, to provide more detailed insights into the fundamental biological roles of these proteins

A combined study of heat and mass transfer in an infant incubator with an overhead screen

The main objective of this study is to investigate the major physical processes taking place inside an infant incubator, before and after modifications have been made to its interior chamber. The modification involves the addition of an overhead screen to decrease radiation heat losses from the infant placed inside the incubator. The present study investigates the effect of these modifications on the convective heat flux from the infant’s body to the surrounding environment inside the incubator. A combined analysis of airflow and heat transfer due to conduction, convection, radiation and evaporation has been performed, in order to calculate the temperature and velocity fields inside the incubator before and after the design modification. Due to the geometrical complexity of the model, Computer-Aided Design (CAD) applications were used to generate a computer-based model. All numerical calculations have been performed using the commercial Computational Fluid Dynamics (CFD) package FLUENT, together with in-house routines used for managing purposes and User-Defined Functions (UDFs) which extend the basic solver capabilities. Numerical calculations have been performed for three different air inlet temperatures: 32, 34 and 36ºC. The study shows a decrease of the radiative and convective heat losses when the overhead screen is present. The results obtained were numerically verified as well as compared with results available in the literature from investigations of dry heat losses from infant manikins

Evaluation of 3D-Jury on CASP7 models

<p>Abstract</p> <p>Background</p> <p>3D-Jury, the structure prediction consensus method publicly available in the Meta Server <url>http://meta.bioinfo.pl/</url>, was evaluated using models gathered in the 7^{<it>th </it>}round of the Critical Assessment of Techniques for Protein Structure Prediction (CASP7). 3D-Jury is an automated expert process that generates protein structure meta-predictions from sets of models obtained from partner servers.</p> <p>Results</p> <p>The performance of 3D-Jury was analysed for three aspects. First, we examined the correlation between the 3D-Jury score and a model quality measure: the number of correctly predicted residues. The 3D-Jury score was shown to correlate significantly with the number of correctly predicted residues, the correlation is good enough to be used for prediction. 3D-Jury was also found to improve upon the competing servers' choice of the best structure model in most cases. The value of the 3D-Jury score as a generic reliability measure was also examined. We found that the 3D-Jury score separates bad models from good models better than the reliability score of the original server in 27 cases and falls short of it in only 5 cases out of a total of 38. We report the release of a new Meta Server feature: instant 3D-Jury scoring of uploaded user models.</p> <p>Conclusion</p> <p>The 3D-Jury score continues to be a good indicator of structural model quality. It also provides a generic reliability score, especially important for models that were not assigned such by the original server. Individual structure modellers can also benefit from the 3D-Jury scoring system by testing their models in the new instant scoring feature <url>http://meta.bioinfo.pl/compare_your_model_example.pl</url> available in the Meta Server.</p

Medullary sponge kidney presenting in a neonate with distal renal tubular acidosis and failure to thrive: a case report

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Automated functional classification of experimental and predicted protein structures

BACKGROUND: Proteins that are similar in sequence or structure may perform different functions in nature. In such cases, function cannot be inferred from sequence or structural similarity. RESULTS: We analyzed experimental structures belonging to the Structural Classification of Proteins (SCOP) database and showed that about half of them belong to multi-functional fold families for which protein similarity alone is not adequate to assign function. We also analyzed predicted structures from the LiveBench and the PDB-CAFASP experiments and showed that accurate homology-based functional assignments cannot be achieved approximately one third of the time, when the protein is a member of a multi-functional fold family. We then conducted extended performance evaluation and comparisons on both experimental and predicted structures using our Functional Signatures from Structural Alignments (FSSA) algorithm that we previously developed to handle the problem of classifying proteins belonging to multi-functional fold families. CONCLUSION: The results indicate that the FSSA algorithm has better accuracy when compared to homology-based approaches for functional classification of both experimental and predicted protein structures, in part due to its use of local, as opposed to global, information for classifying function. The FSSA algorithm has also been implemented as a webserver and is available at

Classification, substrate specificity and structural features of D-2-hydroxyacid dehydrogenases: 2HADH knowledgebase

BACKGROUND: The family of D-isomer specific 2-hydroxyacid dehydrogenases (2HADHs) contains a wide range of oxidoreductases with various metabolic roles as well as biotechnological applications. Despite a vast amount of biochemical and structural data for various representatives of the family, the long and complex evolution and broad sequence diversity hinder functional annotations for uncharacterized members. RESULTS: We report an in-depth phylogenetic analysis, followed by mapping of available biochemical and structural data on the reconstructed phylogenetic tree. The analysis suggests that some subfamilies comprising enzymes with similar yet broad substrate specificity profiles diverged early in the evolution of 2HADHs. Based on the phylogenetic tree, we present a revised classification of the family that comprises 22 subfamilies, including 13 new subfamilies not studied biochemically. We summarize characteristics of the nine biochemically studied subfamilies by aggregating all available sequence, biochemical, and structural data, providing comprehensive descriptions of the active site, cofactor-binding residues, and potential roles of specific structural regions in substrate recognition. In addition, we concisely present our analysis as an online 2HADH enzymes knowledgebase. CONCLUSIONS: The knowledgebase enables navigation over the 2HADHs classification, search through collected data, and functional predictions of uncharacterized 2HADHs. Future characterization of the new subfamilies may result in discoveries of enzymes with novel metabolic roles and with properties beneficial for biotechnological applications

Comprehensive Structural and Substrate Specificity Classification of the Saccharomyces cerevisiae Methyltransferome

Methylation is one of the most common chemical modifications of biologically active molecules and it occurs in all life forms. Its functional role is very diverse and involves many essential cellular processes, such as signal transduction, transcriptional control, biosynthesis, and metabolism. Here, we provide further insight into the enzymatic methylation in S. cerevisiae by conducting a comprehensive structural and functional survey of all the methyltransferases encoded in its genome. Using distant homology detection and fold recognition, we found that the S. cerevisiae methyltransferome comprises 86 MTases (53 well-known and 33 putative with unknown substrate specificity). Structural classification of their catalytic domains shows that these enzymes may adopt nine different folds, the most common being the Rossmann-like. We also analyzed the domain architecture of these proteins and identified several new domain contexts. Interestingly, we found that the majority of MTase genes are periodically expressed during yeast metabolic cycle. This finding, together with calculated isoelectric point, fold assignment and cellular localization, was used to develop a novel approach for predicting substrate specificity. Using this approach, we predicted the general substrates for 24 of 33 putative MTases and confirmed these predictions experimentally in both cases tested. Finally, we show that, in S. cerevisiae, methylation is carried out by 34 RNA MTases, 32 protein MTases, eight small molecule MTases, three lipid MTases, and nine MTases with still unknown substrate specificity

Incorporation of Local Structural Preference Potential Improves Fold Recognition

Fold recognition, or threading, is a popular protein structure modeling approach that uses known structure templates to build structures for those of unknown. The key to the success of fold recognition methods lies in the proper integration of sequence, physiochemical and structural information. Here we introduce another type of information, local structural preference potentials of 3-residue and 9-residue fragments, for fold recognition. By combining the two local structural preference potentials with the widely used sequence profile, secondary structure information and hydrophobic score, we have developed a new threading method called FR-t5 (fold recognition by use of 5 terms). In benchmark testings, we have found the consideration of local structural preference potentials in FR-t5 not only greatly enhances the alignment accuracy and recognition sensitivity, but also significantly improves the quality of prediction models