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Sepsis in patients on extracorporeal membrane oxygenation (ECMO) remains a serious complication. Its presence is a poor prognostic marker and increases overall mortality. Adult patients with prolonged duration on ECMO are at high risk of developing sepsis. Ventilator-associated pneumonia and bloodstream infections are the main sources of infection these patients. A strong early suspicion, drawing adequate volume for blood cultures, and early and timely administration of empirical antibiotics can help control the infection and decrease the morbidity and mortality. The diagnostic and the treatment are both challenging. Cardiac patients have increased risk of nosocomial infection while on ECMO, which may be in part due to longer cannulation times, as well as increased likelihood of undergoing major procedures or having an open chest.

BackgroundThe blue whale, Balaenoptera musculus , is the largest animal known to have ever existed. Body size is tightly coupled to cell metabolism and environmental adaptations. A high-quality genome assembly of this magnificent animal will aid our understanding of body size regulation and related biological processes.ResultsWe report a reference-quality, long read based assembly of the blue whale genome. We sequenced genomic DNA using PacBio long-read, Illumina short-read, and 10X Genomics synthetic long-read technologies. We also obtained long-range mapping information using Bionano optical mapping and Dovetail Hi-C. Additionally, we sequenced the transcriptome of blue whale fibroblasts using Illumina RNA-seq and PacBio Iso-seq technologies. We also measured genome size using a flow cytometry technique. We report on: (1) comparison of alternative long-read and short-read-based assemblies; (2) segmental duplications within the blue whale genome, which have resulted in dramatic amplifications of several genes; (3) sites in IGF1 gene correlated to body size in cetaceans; and (4) heterozygosity and historical demography of Pacific and Atlantic blue whale populations.ConclusionsThis is one of the first high-quality reference genomes of a cetacean and the first baleen whale sequenced using a long-read technology. A high quality, annotated blue whale genome will serve as an important resource for biology, evolution, and conservation research.

Transcatheter aortic valve implantation has emerged as a therapeutic option for patients with symptomatic severe aortic stenosis who are inoperable, or at very high risk of open-heart surgery. Recently, we encountered a patient with aortic stenosis and Larsen syndrome, who had short stature, obesity, kyphoscoliosis, multiple musculoskeletal deformities, and severe restrictive lung disease. An open-heart surgery in such a patient involves substantial peri-operative risk. A successful transcaval aortic valve implantation was done under general anesthesia.

Protein 3D structure prediction has advanced significantly in recent years due to improving contact prediction accuracy. This improvement has been largely due to deep learning approaches that predict inter-residue contacts and, more recently, distances using multiple sequence alignments (MSAs). In this work we present AttentiveDist, a novel approach that uses different MSAs generated with different E-values in a single model to increase the co-evolutionary information provided to the model. To determine the importance of each MSA’s feature at the inter-residue level, we added an attention layer to the deep neural network. The model is trained in a multi-task fashion to also predict backbone and orientation angles further improving the inter-residue distance prediction. We show that AttentiveDist outperforms the top methods for contact prediction in the CASP13 structure prediction competition. To aid in structure modeling we also developed two new deep learning-based sidechain center distance and peptide-bond nitrogen-oxygen distance prediction models. Together these led to a 12% increase in TM-score from the best server method in CASP13 for structure prediction.

Motivation Protein structure prediction remains as one of the most important problems in computational biology and biophysics. In the past few years, protein residue–residue contact prediction has undergone substantial improvement, which has made it a critical driving force for successful protein structure prediction. Boosting the accuracy of contact predictions has, therefore, become the forefront of protein structure prediction. Results We show a novel contact map refinement method, ContactGAN, which uses Generative Adversarial Networks (GAN). ContactGAN was able to make a significant improvement over predictions made by recent contact prediction methods when tested on three datasets including protein structure modeling targets in CASP13 and CASP14. We show improvement of precision in contact prediction, which translated into improvement in the accuracy of protein tertiary structure models. On the other hand, observed improvement over trRosetta was relatively small, reasons for which are discussed. ContactGAN will be a valuable addition in the structure prediction pipeline to achieve an extra gain in contact prediction accuracy. Availability and implementation https://github.com/kiharalab/ContactGAN. Supplementary information Supplementary data are available at Bioinformatics online.

Protein residue-residue contact prediction from protein sequence information has undergone substantial improvement in the past few years, which has made it a critical driving force for building correct protein tertiary structure models. Improving accuracy of contact predictions has, therefore, become the forefront of protein structure prediction. Here, we show a novel contact map denoising method, ContactGAN, which uses Generative Adversarial Networks (GAN) to refine predicted protein contact maps. ContactGAN was able to make a consistent and significant improvement over predictions made by recent contact prediction methods when tested on two datasets including protein structure modeling targets in CASP13. ContactGAN will be a valuable addition in the structure prediction pipeline to achieve an extra gain in contact prediction accuracy.

A 60-year-old man presented to the authors’ institution and underwent simultaneous surgery for severe aortic stenosis and left renal mass. Potential benefits of a combined cardiac and noncardiac procedure are discussed. The literature, however, is scarce on standards of management of patients with two coexisting life-threatening conditions.

BACKGROUND ST elevation myocardial infarction is an acute emergency, more than 50% of deaths due to STEMI occur within first 1 hour, mainly due to various arrhythmias. Various arrhythmia can complicate the course of STEMI. This study was done to access the incidence and pattern of arrhythmias complicating STEMI and the prognostic implications of these arrhythmias. MATERIALS AND METHODS 100 patients were included in the study that fulfilled the required criteria. They underwent detailed history taking and systemic examination. Patients were monitored through cardiac monitor and serial ECG recording were taken specially if any rhythm disturbances were observed and data was entered in a pretested proforma. RESULTS Among 100 patients, 60 were male and 40 were female. Commonest arrhythmias noticed in this study were sinus tachycardia (31%), followed by bundle branch block (30%), ventricular arrhythmia (25%) AV blocks (20%) sinus bradycardia (18%), supraventricular arrhythmia (4%) and AIVR in 1%. Mortality was more in patients with ventricular tachycardia and complete heart block. Majority of arrhythmias (76%) occur during first hour of hospitalization. CONCLUSION The commonest arrhythmia encountered were sinus tachycardia followed by bundle branch block (BBB), AV block and sinus bradycardia, AV block and sinus bradycardia were common with IWMI and ventricular arrhythmia and bundle branch block were common with AWMI.

With advancements in synthetic biology, the cost and the time needed for designing and synthesizing customized gene products have been steadily decreasing. Many research laboratories in academia as well as industry routinely create genetically engineered proteins as a part of their research activities. However, manipulation of protein sequences could result in unintentional production of toxic proteins. Therefore, being able to identify the toxicity of a protein before the synthesis would reduce the risk of potential hazards. Existing methods are too specific, which limits their application. Here, we extended general function prediction methods for predicting the toxicity of proteins. Protein function prediction methods have been actively studied in the bioinformatics community and have shown significant improvement over the last decade. We have previously developed successful function prediction methods, which were shown to be among top-performing methods in the community-wide functional annotation experiment, CAFA. Based on our function prediction method, we developed a neural network model, named NNTox, which uses predicted GO terms for a target protein to further predict the possibility of the protein being toxic. We have also developed a multi-label model, which can predict the specific toxicity type of the query sequence. Together, this work analyses the relationship between GO terms and protein toxicity and builds predictor models of protein toxicity.

The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Here we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility (P. aureginosa only). We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory. We conclude that, while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. We finally report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bioontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.

Additional file 1 Additional figures and tables referenced in the article.

Tosatto, Silvio/0000-0003-4525-7793; Zhang, Feng/0000-0003-3447-897X; Gonzalez, Jose Maria Fernandez/0000-0002-4806-5140; Devignes, Marie-Dominique/0000-0002-0399-8713; Wass, Mark/0000-0001-5428-6479; Falda, Marco/0000-0003-2642-519X; Thurlby, Natalie/0000-0002-1007-0286; Zosa, Elaine/0000-0003-2482-0663; Dessimoz, Christophe/0000-0002-2170-853X; Yunes, Jeffrey/0000-0003-1869-3231; Hamid, Md Nafiz/0000-0001-8681-6526; Hoehndorf, Robert/0000-0001-8149-5890; Dogan, Tunca/0000-0002-1298-9763; NOTARO, MARCO/0000-0003-4309-2200; Cozzetto, Domenico/0000-0001-6752-5432; Lewis, Kimberley/0000-0003-3010-8453; Roche, Daniel/0000-0002-9204-1840; Martin, Maria-Jesus/0000-0001-5454-2815; Tress, Michael/0000-0001-9046-6370; Tolvanen, Martti/0000-0003-3434-7646; Cheng, Jianlin/0000-0003-0305-2853; Rose, Peter/0000-0001-9981-9750; Renaux, Alexandre/0000-0002-4339-2791; Kacsoh, Balint/0000-0001-9171-0611; O'Donovan, Claire/0000-0001-8051-7429; Kulmanov, Maxat/0000-0003-1710-1820; Friedberg, Iddo/0000-0002-1789-8000; Zhou, Naihui/0000-0001-6268-6149, WOS: 000498615000001, PubMed ID: 31744546, Background The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory. Conclusion We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens., National Science FoundationNational Science Foundation (NSF) [DBI1564756, DBI-1458359, DBI-1458390, DMS1614777, CMMI1825941, NSF 1458390]; Gordon and Betty Moore FoundationGordon and Betty Moore Foundation [GBMF 4552]; National Institutes of Health NIGMSUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of General Medical Sciences (NIGMS) [P20 GM113132]; Cystic Fibrosis Foundation [CFRDP STANTO19R0]; BBSRCBiotechnology and Biological Sciences Research Council (BBSRC) [BB/K004131/1, BB/F00964X/1, BB/M025047/1, BB/M015009/1]; Consejo Nacional de Ciencia y Tecnologia Paraguay (CONACyT)Consejo Nacional de Ciencia y Tecnologia (CONACyT) [14-INV-088, PINV15-315]; NSFNational Science Foundation (NSF) [1660648, DBI 1759934, IIS1763246, DBI-1458477, 0965768, DMR-1420073, DBI-1458443]; NIHUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [R01GM093123, DP1MH110234, UL1 TR002319, U24 TR002306]; Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy-EXC 2155 "RESIST"German Research Foundation (DFG) [39087428]; National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [R01GM123055, R01GM60595, R15GM120650, GM083107, GM116960, AI134678, NIH R35-GM128637, R00-GM097033]; ERCEuropean Research Council (ERC) [StG 757700]; Spanish Ministry of Science, Innovation and Universities [BFU2017-89833-P]; Severo Ochoa award; Centre of Excellence project "BioProspecting of Adriatic Sea"; Croatian Government; European Regional Development FundEuropean Union (EU) [KK.01.1.1.01.0002]; ATT Tieto kayttoon grant; Academy of FinlandAcademy of Finland; University of Turku; CSC-IT Center for Science Ltd.; University of Miami; National Cancer Institute of the National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Cancer Institute (NCI) [U01CA198942]; Helsinki Institute for Life Sciences; Academy of FinlandAcademy of Finland [292589]; National Natural Science Foundation of ChinaNational Natural Science Foundation of China [31671367, 31471245, 91631301, 61872094, 61572139]; National Key Research and Development Program of China [2016YFC1000505, 2017YFC0908402]; Italian Ministry of Education, University and Research (MIUR) PRIN 2017 projectMinistry of Education, Universities and Research (MIUR) [2017483NH8]; Shanghai Municipal Science and Technology Major Project [2017SHZDZX01, 2018SHZDZX01]; UK Biotechnology and Biological Sciences Research CouncilBiotechnology and Biological Sciences Research Council (BBSRC) [BB/N019431/1, BB/L020505/1, BB/L002817/1]; Elsevier; Extreme Science and Engineering Discovery Environment (XSEDE) award [MCB160101, MCB160124]; Ministry of Education, Science and Technological Development of the Republic of Serbia [173001]; Taiwan Ministry of Science and Technology [106-2221-E-004-011-MY2]; Montana State University; Bavarian Ministry for Education; Simons Foundation; NIH NINDSUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of Neurological Disorders & Stroke (NINDS) [1R21NS103831-01]; University of Illinois at Chicago (UIC) Cancer Center award; UIC College of Liberal Arts and Sciences Faculty Award; UIC International Development Award; Yad Hanadiv [9660/2019]; National Institute of General Medical Science of the National Institute of Health [GM066099, GM079656]; Research Supporting Plan (PSR) of University of Milan [PSR2018-DIP-010-MFRAS]; Swiss National Science FoundationSwiss National Science Foundation (SNSF) [150654]; EMBL-European Bioinformatics Institute core funds; CAFA BBSRC [BB/N004876/1]; European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grantEuropean Union (EU) [778247]; COST ActionEuropean Cooperation in Science and Technology (COST) [BM1405]; NIH/NIGMSUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of General Medical Sciences (NIGMS) [R01 GM071749]; National Human Genome Research Institute of the National of Health [U41 HG007234]; INB Grant (ISCIII-SGEFI/ERDF) [PT17/0009/0001]; TUBITAKTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [EEEAG-116E930]; KanSil [2016K121540]; Universita degli Studi di Milano; 111 ProjectMinistry of Education, China - 111 Project [B18015]; key project of Shanghai Science Technology [16JC1420402]; ZJLab; project Ribes Network POR-FESR 3S4H [TOPP-ALFREVE18-01]; PRID/SID of University of Padova [TOPP-SID19-01]; NIGMSUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of General Medical Sciences (NIGMS) [R15GM120650]; King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) [URF/1/3454-01-01, URF/1/3790-01-01]; "the Human Project from Mind, Brain and Learning" of the NCCU Higher Education Sprout Project by the Taiwan Ministry of Education; National Center for High-performance ComputingIstanbul Technical University, The work of IF was funded, in part, by the National Science Foundation award DBI-1458359. The work of CSG and AJL was funded, in part, by the National Science Foundation award DBI-1458390 and GBMF 4552 from the Gordon and Betty Moore Foundation. The work of DAH and KAL was funded, in part, by the National Science Foundation award DBI-1458390, National Institutes of Health NIGMS P20 GM113132, and the Cystic Fibrosis Foundation CFRDP STANTO19R0. The work of AP, HY, AR, and MT was funded by BBSRC grants BB/K004131/1, BB/F00964X/1 and BB/M025047/1, Consejo Nacional de Ciencia y Tecnologia Paraguay (CONACyT) grants 14-INV-088 and PINV15-315, and NSF Advances in BioInformatics grant 1660648. The work of JC was partially supported by an NIH grant (R01GM093123) and two NSF grants (DBI 1759934 and IIS1763246). ACM acknowledges the support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy -EXC 2155 "RESIST" - Project ID 39087428. DK acknowledges the support from the National Institutes of Health (R01GM123055) and the National Science Foundation (DMS1614777, CMMI1825941). PB acknowledges the support from the National Institutes of Health (R01GM60595). GB and BZK acknowledge the support from the National Science Foundation (NSF 1458390) and NIH DP1MH110234. FS was funded by the ERC StG 757700 "HYPER-INSIGHT" and by the Spanish Ministry of Science, Innovation and Universities grant BFU2017-89833-P. FS further acknowledges the funding from the Severo Ochoa award to the IRB Barcelona. TS was funded by the Centre of Excellence project "BioProspecting of Adriatic Sea", co-financed by the Croatian Government and the European Regional Development Fund (KK.01.1.1.01.0002). The work of SK was funded by ATT Tieto kayttoon grant and Academy of Finland. JB and HM acknowledge the support of the University of Turku, the Academy of Finland and CSC -IT Center for Science Ltd. TB and SM were funded by the NIH awards UL1 TR002319 and U24 TR002306. The work of CZ and ZW was funded by the National Institutes of Health R15GM120650 to ZW and start-up funding from the University of Miami to ZW. The work of PWR was supported by the National Cancer Institute of the National Institutes of Health under Award Number U01CA198942. PR acknowledges NSF grant DBI-1458477. PT acknowledges the support from Helsinki Institute for Life Sciences. The work of AJM was funded by the Academy of Finland (No. 292589). The work of FZ and WT was funded by the National Natural Science Foundation of China (31671367, 31471245, 91631301) and the National Key Research and Development Program of China (2016YFC1000505, 2017YFC0908402]. CS acknowledges the support by the Italian Ministry of Education, University and Research (MIUR) PRIN 2017 project 2017483NH8. SZ is supported by the National Natural Science Foundation of China (No. 61872094 and No. 61572139) and Shanghai Municipal Science and Technology Major Project (No. 2017SHZDZX01). PLF and RLH were supported by the National Institutes of Health NIH R35-GM128637 and R00-GM097033. JG, DTJ, CW, DC, and RF were supported by the UK Biotechnology and Biological Sciences Research Council (BB/N019431/1, BB/L020505/1, and BB/L002817/1) and Elsevier. The work of YZ and CZ was funded in part by the National Institutes of Health award GM083107, GM116960, and AI134678; the National Science Foundation award DBI1564756; and the Extreme Science and Engineering Discovery Environment (XSEDE) award MCB160101 and MCB160124.; The work of BG, VP, RD, NS, and NV was funded by the Ministry of Education, Science and Technological Development of the Republic of Serbia, Project No. 173001. The work of YWL, WHL, and JMC was funded by the Taiwan Ministry of Science and Technology (106-2221-E-004-011-MY2). YWL, WHL, and JMC further acknowledge the support from "the Human Project from Mind, Brain and Learning" of the NCCU Higher Education Sprout Project by the Taiwan Ministry of Education and the National Center for High-performance Computing for computer time and facilities. The work of IK and AB was funded by Montana State University and NSF Advances in Biological Informatics program through grant number 0965768. BR, TG, and JR are supported by the Bavarian Ministry for Education through funding to the TUM. The work of RB, VG, MB, and DCEK was supported by the Simons Foundation, NIH NINDS grant number 1R21NS103831-01 and NSF award number DMR-1420073. CJJ acknowledges the funding from a University of Illinois at Chicago (UIC) Cancer Center award, a UIC College of Liberal Arts and Sciences Faculty Award, and a UIC International Development Award. The work of ML was funded by Yad Hanadiv (grant number 9660/2019). The work of OL and IN was funded by the National Institute of General Medical Science of the National Institute of Health through GM066099 and GM079656. Research Supporting Plan (PSR) of University of Milan number PSR2018-DIP-010-MFRAS. AWV acknowledges the funding from the BBSRC (CASE studentship BB/M015009/1). CD acknowledges the support from the Swiss National Science Foundation (150654). CO and MJM are supported by the EMBL-European Bioinformatics Institute core funds and the CAFA BBSRC BB/N004876/1. GG is supported by CAFA BBSRC BB/N004876/1. SCET acknowledges funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 778247 (IDPfun) and from COST Action BM1405 (NGP-net). SEB was supported by NIH/NIGMS grant R01 GM071749. The work of MLT, JMR, and JMF was supported by the National Human Genome Research Institute of the National of Health, grant numbers U41 HG007234. The work of JMF and JMR was also supported by INB Grant (PT17/0009/0001 - ISCIII-SGEFI/ERDF). VA acknowledges the funding from TUBITAK EEEAG-116E930. RCA acknowledges the funding from KanSil 2016K121540. GV acknowledges the funding from Universita degli Studi di Milano - Project "Discovering Patterns in Multi-Dimensional Data" and Project "Machine Learning and Big Data Analysis for Bioinformatics". SZ is supported by the National Natural Science Foundation of China (No. 61872094 and No. 61572139) and Shanghai Municipal Science and Technology Major Project (No. 2017SHZDZX01). RY and SY are supported by the 111 Project (NO. B18015), the key project of Shanghai Science & Technology (No. 16JC1420402), Shanghai Municipal Science and Technology Major Project (No. 2018SHZDZX01), and ZJLab. ST was supported by project Ribes Network POR-FESR 3S4H (No. TOPP-ALFREVE18-01) and PRID/SID of University of Padova (No. TOPP-SID19-01). CZ and ZW were supported by the NIGMS grant R15GM120650 to ZW and start-up funding from the University of Miami to ZW. The work of MK and RH was supported by the funding from King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No. URF/1/3454-01-01 and URF/1/3790-01-01. The work of SDM is funded, in part, by NSF award DBI-1458443.

Moonlighting proteins is an emerging concept for considering protein functions, which indicate proteins with two or more independent and distinct functions. An increasing number of moonlighting proteins have been reported in the past years; however, a systematic study of the topic has been hindered because the secondary functions of proteins are usually found serendipitously by experiments. Toward systematic identification and study of moonlighting proteins, we have developed computational methods for identifying moonlighting proteins from several different information sources, database entries, literature, and large-scale omics data. In this work, we overview a pipeline for finding moonlighting proteins we have developed. Then, we apply the literature-mining method, DextMP, to find new moonlighting proteins in three genomes, Arabidopsis thaliana, Caenorhabditis elegans, and Drosophila melanogaster. Potential moonlighting proteins identified by DextMP were further examined by a two-step manual literature checking procedure, which finally yielded thirteen new moonlighting proteins. Identified moonlighting proteins were categorized into two classes based on the clarity of the distinctness of two functions of the proteins. A few cases of the identified moonlighting proteins are described in detail. Further direction for improving the DextMP algorithm is also discussed.

Motivation Function annotation of proteins is fundamental in contemporary biology across fields including genomics, molecular biology, biochemistry, systems biology and bioinformatics. Function prediction is indispensable in providing clues for interpreting omics-scale data as well as in assisting biologists to build hypotheses for designing experiments. As sequencing genomes is now routine due to the rapid advancement of sequencing technologies, computational protein function prediction methods have become increasingly important. A conventional method of annotating a protein sequence is to transfer functions from top hits of a homology search; however, this approach has substantial short comings including a low coverage in genome annotation. Results Here we have developed Phylo-PFP, a new sequence-based protein function prediction method, which mines functional information from a broad range of similar sequences, including those with a low sequence similarity identified by a PSI-BLAST search. To evaluate functional similarity between identified sequences and the query protein more accurately, Phylo-PFP reranks retrieved sequences by considering their phylogenetic distance. Compared to the Phylo-PFP’s predecessor, PFP, which was among the top ranked methods in the second round of the Critical Assessment of Functional Annotation (CAFA2), Phylo-PFP demonstrated substantial improvement in prediction accuracy. Phylo-PFP was further shown to outperform prediction programs to date that were ranked top in CAFA2. Availability and implementation Phylo-PFP web server is available for at http://kiharalab.org/phylo_pfp.php. Supplementary information Supplementary data are available at Bioinformatics online.

If a semiflexible polymer confined to a narrow channel bends around by 180 degrees, the polymer is said to exhibit a hairpin. The equilibrium extension statistics of the confined polymer are well understood when hairpins are vanishingly rare or when they are plentiful. Here we analyze the extension statistics in the intermediate situation via experiments with DNA coated by the protein RecA, which enhances the stiffness of the DNA molecule by approximately one order of magnitude. We find that the extension distribution is highly non-Gaussian, in good agreement with Monte Carlo simulations of confined discrete wormlike chains. We develop a simple model that qualitatively explains the form of the extension distribution. The model shows that the tail of the distribution at short extensions is determined by conformations with one hairpin., Comment: Revised version. 22 pages, 7 figures, 2 tables, supplementary material

Modeling the dynamics of a confined, semi exible polymer is a challenging problem, owing to the complicated interplay between the configurations of the chain, which are strongly affected by the length scale for the confinement relative to the persistence length of the chain, and the polymer-wall hydrodynamic interactions. At the same time, understanding these dynamics are crucial to the advancement of emerging genomic technologies that use confinement to stretch out DNA and "read" a genomic signature. In this mini-review, we begin by considering what is known experimentally and theoretically about the friction of a wormlike chain such as DNA confined in a slit or a channel. We then discuss how to estimate the friction coefficient of such a chain, either with dynamic simulations or via Monte Carlo sampling and the Kirk-wood pre-averaging approximation. We then review our recent work on computing the diffusivity of DNA in nanoslits and nanochannels, and conclude with some promising avenues for future work and caveats about our approach.

Background: Pediatric surgery performed in a daycare unit has become the norm in the last few years. Children need special care in terms of psychological stress during the perioperative period 1 . There are many ways to reduce stress in children scheduled for surgery, including preoperative sedative premedication, induction of anesthesia in a familiar environment and “steal” induction in the mother’s arms 2,3 . It is important to consider parental satisfaction while delivering a healthcare service to children. Objective: To assess the overall parental satisfaction throughout the patient’s journey, including the preoperative, intraoperative and the postoperative periods. Setting: Daycare Unit, Department of Anesthesia, King Hamad University Hospital, Bahrain. Design: A Prospective Study. Method: Fifty parents were consented for the questionnaire-based study. Children of these parents were posted for different types of daycare surgery. The parents were asked to fill a form either in Arabic or English, before their children were discharged from the daycare ward. The parents were given an 11-point questionnaire 4 . Scoring these questions was based on their choice of 5 options including: (1) strongly agree, (2) agree, (3) neutral, (4) disagree and (5) strongly disagree. Fifty parents had been included in the study. Patient’s CPR numbers and telephone numbers of the parents were recorded. Questions 7 and 11 demanded individual answers rather than box-ticking. Result: “Strongly agree” and “agree” were taken as positive responses. The majority of parents answered positively to the questions asked. “Strongly disagree” and “disagree” were taken as negative responses. Neutral response was taken as a parent’s wish not to comment either positively or negatively. Conclusion: The majority of the parents were in positive agreement with the questions asked. The majority of the parents were satisfied that the PAC clinic gave them enough information about the anesthetic. The majority of parents were also satisfied with the amount of pain relief given in the recovery room and in the day-care ward. ______________________________________________________________________________ * Senior Registrar ** Director of Intensive Care and Consultant Anesthetist Associate Professor of Physiology and Critical Care, RCSI-MUB *** Senior Registrar Department of Anesthesia and ICU King Hamad University Hospital Kingdom of Bahrain Email: eamon.tierney@khuh.org.bh; aashishjain29@gmail.com INTRODUCTION In a questionnaire-based study conducted in the Royal Berkshire Hospital, it was concluded that parental satisfaction is an important outcome of quality of care delivered in the pediatric daycare unit 5 . The study also concluded that the nurses play a key role in maintaining a quality service and should therefore be involved in monitoring that service. Daycare surgery is increasingly popular because it reduces the length of stay in the hospital by facilitating admission and discharge on the same day. At least 70% of procedures in the pediatric age group are performed as day cases 6 . The increase in daycare surgery has become possible as a result of the availability of shorter-acting anesthetic agents and analgesics. In addition, the use of nerve blocks such as penile blocks and caudal blocks per-operatively has become more commonplace for pain management. Proper selection of patients is of the utmost importance for daycare surgery and one of the important categories of the patients in daycare surgeries is the pediatric age group. These patients are commonly posted for tonsillectomy, adenotonsillectomy, circumcision, undescended testes, inguinal herniotomy and other similar short duration surgeries with minimal blood loss. Children are vulnerable to separation anxiety and associated perioperative stress. In our hospital, we have a policy of child-friendly and parent-friendly management of the pediatric patient coming to theatre for surgery. The parent stays with the child until the child falls asleep. Anesthesia is always induced by inhalation to avoid placing a needle into a conscious child. When the child is transferred from theatre to the recovery room after surgery, the parent is called as quickly as possible to the recovery room to be with the child. In this manner, the child is awake without the presence of a parent for a minimum period of time. In addition, we place a large emphasis on good peri-operative analgesia in pediatric patients, with good intra-operative analgesia and with a rapid response to any complaint of pain expressed by the child in the recovery room. The aim of this study is to assess the overall parental satisfaction throughout the patient’s journey including the preoperative, intraoperative and the postoperative periods. METHOD The parents of 50 patients below 10 years of age posted for daycare surgery were included in the study. The children were anesthetized by anesthetic gas inhalation in the presence of one parent. The parent left the induction room immediately when the child fell asleep. At the end of surgery, the child was transferred to the recovery room. The parent was called to the recovery room as soon as the anesthetist and recovery nurse were satisfied that the child had recovered from the anesthetic. An eleven-point questionnaire was filled out by the parents just before their children were discharged from the daycare ward, see table 1. The questionnaire included the preoperative, intraoperative and postoperative periods. In response to each question, parents were requested to select one of the options on five-point score; the options were:  strongly agree  agree  neutral  disagree  strongly disagree Identifying data on the questionnaire forms were the patient’s Central Population Registration (CPR) number and the telephone number of their parents. RESULT Table 1: Parents’ Responses Numbers and Percentages Question Number Strongly Agree Agree Neutral Disagree Strongly Disagree Not Attempted 1 Was your visit to the pre admission Clinic helpful? 31 16 0 1 1 1 2 Are you satisfied that the doctor/anesthetist gave you enough information about the anesthetic for your child? 34 10 3 2 1 0 3 Did the doctor or anesthetist answer all your questions? 37 10 2 0 0 1 4 Did the doctor/anesthetist explain enough details about the anesthetic procedure? 31 13 2 3 0 1 5 Was it helpful for you to go to operating room with your child? 42 6 2 0 0 6 If yes, was it helpful for your child? 39 9 1 0 0 1 7 Why was it helpful for your child? Discussed below 8 Were you called early enough to be with the child as he/she woke up in the recovery room? 39 9 0 0 1 1 9 Were you satisfied with the 40 8 1 0 0 1 amount of pain relief given to your child in the recovery room? 10 Were you satisfied with the amount of pain relief given to your child in the ward? 42 7 0 0 0 1 11 Do you have any suggestions as to how we can improve the anesthetic and Pain relief services for children? Discussed below

We have developed a multi-scale model describing the dynamics of internal segments of DNA in nanochannels used for genome mapping. In addition to the channel geometry, the model takes as its inputs the DNA properties in free solution (persistence length, effective width, molecular weight, and segmental hydrodynamic radius) and buffer properties (temperature and viscosity). Using pruned-enriched Rosenbluth simulations of a discrete wormlike chain model with circa 10 base pair resolution and a numerical solution for the hydrodynamic interactions in confinement, we convert these experimentally available inputs into the necessary parameters for a one-dimensional, Rouse-like model of the confined chain. The resulting coarse-grained model resolves the DNA at a length scale of approximately 6 kilobase pairs in the absence of any global hairpin folds, and is readily studied using a normal-mode analysis or Brownian dynamics simulations. The Rouse-like model successfully reproduces both the trends and order of magnitude of the relaxation time of the distance between labeled segments of DNA obtained in experiments. The model also provides insights that are not readily accessible from experiments, such as the role of the molecular weight of the DNA and location of the labeled segments that impact the statistical models used to construct genome maps from data acquired in nanochannels. The multi-scale approach used here, while focused towards a technologically relevant scenario, is readily adapted to other channel sizes and polymers.

The linear stability of gravity-driven annular liquid film flow outside wires and inside tubes is analyzed when the rigid surface is replaced by a deformable (neo-Hookean) solid wall. On a rigid surface, an annular liquid thread becomes unstable due to a Rayleigh-type capillary instability even in the absence of flow. In the presence of flow, the annular liquid film becomes unstable due to a flow-driven, free-surface instability, which occurs over and above the curvature-induced capillary instability. In this paper, a low-wavenumber perturbation analysis is first used to elucidate the effect of wall deformability on the free-surface instability. It is shown that the free-surface instability is completely stabilized in the low-wavenumber limit when the wall is made sufficiently deformable. A numerical method is subsequently used to determine the stability of the system at arbitrary wavenumbers. Results from the numerical solution reveal that the prediction of instability suppression at low wavenumbers extends to finite wavenumbers as well. However, as the solid wall is made deformable even further, the free surface is destabilized at finite wavenumbers by the deformability; in addition, the liquid-solid interface could also become unstable when the solid deformability becomes high. It is demonstrated, however, that there is a sufficient range of shear modulus of the solid where the annular flow is stable at all wavenumbers. The results of this study have implications in wire-coating operations, as well as in biological settings such as closure of lung airways.

AIM AND OBJECTIVE: The aim of this study was to determine the effectiveness and results of repair of Organic Tricuspid Valve disease. INTRODUCTION : since tricuspid valve disease most often found in association with other valve disease. Isolated tricuspid valve disease is ra re. Pattern of involvement of tricuspid valve disease shows functional (75%) and primary (organic) in (25%). Surgical repair of organic tricuspid valve disease often fails because of abnormal valve. This usually leads to limited options. This study examine s our experience of tricuspid valve repair with autologous pericardium for organic tricuspid valve disease. MATERIAL AND METHODS : From Jan 2014 to May 2015, 22 patients underwent repairs for organic tricuspid valve disease. The patient aged 15 to 65 years and all were in New York Heart Association (NYHA) class of III or IV. All patients presented with severe tricuspid disease coexisting with other cardiac pathology, usually left - sided heart valve disease. Repair techniques included Commisurotomy, division o f secondary chordae, Glutaraldehyde treated autologous pericardial patch augmentation of tricuspid valve leaflets, anterior papillary muscle advancement etc with or without ring/suture annuloplasty. Follow - up duration was 3 to 18 months. RESULTS : No deaths or late reoperations occurred. All patients demonstrated clinical improvements on follow up. Echocardiographic studies before hospital discharge showed less than mild tricuspid regurgitation in all patients except one. CONCLUSIONS : Large majorit y of organic tricuspid valve regurgitation is repairable with acceptable early results. Tricuspid stenosis and mixed tricuspid valve disease are more challenging. In the latter group, it is a judgment call whether to accept a suboptimal result or replace t he valve

We use Brownian dynamics with hydrodynamic interactions to calculate both the Kirkwood (short-time) diffusivity and the long-time diffusivity of DNA chains from free solution down to channel confinement in the de Gennes regime. The Kirkwood diffusivity in confinement is always higher than the diffusivity obtained from the mean-squared displacement of the center-of-mass, as is the case in free solution. Moreover, the divergence of the local diffusion tensor, which is non-zero in confinement, makes a negligible contribution to the latter diffusivity in confinement. The maximum error in the Kirkwood approximation in our simulations is about 2% for experimentally relevant simulation times. The error decreases with increasing confinement, consistent with arguments from blob theory and the molecular-weight dependence of the error in free solution. In light of the typical experimental errors in measuring the properties of channel-confined DNA, our results suggest that the Kirkwood approximation is sufficiently accurate to model experimental data.

Periodic boundary conditions for planar mixed flows are implemented in the context of a multi-chain Brownian dynamics simulation algorithm. The effect of shear rate $\dot{\gamma}$, and extension rate $\dot{\epsilon}$, on the size of polymer chains, $\left$, and on the polymer contribution to viscosity, $\eta$, is examined for solutions of FENE dumbbells at finite concentrations, with excluded volume interactions between the beads taken into account. The influence of the mixedness parameter, $\chi$, and flow strength, $\dot{\Gamma}$, on $\left$ and $\eta$, is also examined, where $\chi \rightarrow 0$ corresponds to pure shear flow, and $\chi \rightarrow 1$ corresponds to pure extensional flow. It is shown that there exists a critical value, $\chi_\text{c}$, such that the flow is shear dominated for $\chi < \chi_\text{c}$, and extension dominated for $\chi > \chi_\text{c}$., Comment: 18 pages, 12 figures, to appear in Chemical Engineering Science

Genome mapping involves the confinement of long DNA molecules, in excess of 150 kilobase pairs, in nanochannels near the circa 50 nm persistence length of DNA. The fidelity of the map relies on the assumption that the DNA is linearized by channel confinement, which assumes the absence of knots. We have computed the probability of forming different knot types and the size of these knots for long chains (approximately 164 kilobase pairs) via pruned-enriched Rosenbluth method simulations of a discrete wormlike chain model of DNA in channel sizes ranging from 35 nm to 60 nm. Compared to prior simulations of short DNA in similar confinement, these long molecules exhibit both complex knots, with up to seven crossings, and multiple knots per chain. The knotting probability is a very strong function of channel size, ranging from 0.3% to 60%, and rationalized in the context of Odijk's theory for confined semiflexible chains. Overall, the knotting probability and knot size obtained from these equilibrium measurements are not consistent with experimental measurements of the properties of anomalously bright regions along the DNA backbone during genome mapping experiments. This result suggests that these events in experiments are either knots formed during the processing of the DNA prior to injection into the nanochannel or regions of locally high DNA concentration without a topological constraint. If so, knots during genome mapping are not an intrinsic problem for genome mapping technology.

The crossover region in the phase diagram of polymer solutions, in the regime above the overlap concentration, is explored by Brownian Dynamics simulations, to map out the universal crossover scaling functions for the gyration radius and the single-chain diffusion constant. Scaling considerations, our simulation results, and recently reported data on the polymer contribution to the viscosity obtained from rheological measurements on DNA systems, support the assumption that there are simple relations between these functions, such that they can be inferred from one another., Comment: 4 pages, 6 figures, 1 Table. Revised version to appear in Physical Review Letters. Includes supplemental materials

Simulating the static and dynamic properties of semidilute polymer solutions with Brownian dynamics (BD) requires the computation of a large system of polymer chains coupled to one another through excluded-volume and hydrodynamic interactions. In the presence of periodic boundary conditions, long-ranged hydrodynamic interactions are frequently summed with the Ewald summation technique. By performing detailed simulations that shed light on the influence of several tuning parameters involved both in the Ewald summation method, and in the efficient treatment of Brownian forces, we develop a BD algorithm in which the computational cost scales as O(N^{1.8}), where N is the number of monomers in the simulation box. We show that Beenakker's original implementation of the Ewald sum, which is only valid for systems without bead overlap, can be modified so that \theta-solutions can be simulated by switching off excluded-volume interactions. A comparison of the predictions of the radius of gyration, the end-to-end vector, and the self-diffusion coefficient by BD, at a range of concentrations, with the hybrid Lattice Boltzmann/Molecular Dynamics (LB/MD) method shows excellent agreement between the two methods. In contrast to the situation for dilute solutions, the LB/MD method is shown to be significantly more computationally efficient than the current implementation of BD for simulating semidilute solutions. We argue however that further optimisations should be possible., Comment: 17 pages, 8 figures, revised version to appear in Physical Review E (2012)

The linear stability of viscoelastic (Oldroyd-B) film flow down an inclined plane lined with a deformable (neo-Hookean) solid layer is analyzed using low-wave-number asymptotic analysis and the Chebyshev-Tau spectral numerical method. The free surface of film flows of viscoelastic liquids, unlike that of their Newtonian counterparts, becomes unstable in flow down a rigid inclined surface even in the absence of fluid inertia, due to the elastic nature of the liquids. For film flow past a deformable solid, our low-wave-number asymptotic analysis reveals that the solid deformability has a stabilizing effect on the free-surface instability, and, remarkably, this prediction is insensitive to rheology of the liquid film, be it viscoelastic or Newtonian. Using the spectral numerical method, we demonstrate that the free-surface instability can be completely suppressed at all wave numbers when the solid becomes sufficiently deformable. For the case of pure polymeric liquids without any solvent, when the solid layer is made further deformable, both the free surface and the liquid-solid interface are destabilized at finite wave numbers. We also demonstrate a type of mode exchange phenomenon between the modes corresponding to the two interfaces. Importantly, our numerical results show that there is a sufficient range of shear modulus of the solid where both the modes are stable at all wave numbers. For polymer solutions described by the Oldroyd-B model, while the free-surface instability is suppressed by the deformable solid, a host of new unstable modes appear at finite Reynolds number and wave number because of the coupling between liquid flow and free shear waves in the solid. Our study thus demonstrates that the elastohydrodynamic coupling between liquid flow and solid deformation can be exploited either to suppress the free-surface instability (present otherwise in rigid inclines) in viscoelastic film flows, or to induce new instabilities that are absent in flow adjacent to rigid surfaces.