Simulation and experimental study of rheological properties of CeO2 – water nanofluid

Open Access. This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.Metal oxide nanoparticles offer great merits over controlling rheological, thermal, chemical and physical properties of solutions. The effectiveness of a nanoparticle to modify the properties of a fluid depends on its diffusive properties with respect to the fluid. In this study, rheological properties of aqueous fluids (i.e. water) were enhanced with the addition of CeO2 nanoparticles. This study was characterized by the outcomes of simulation and experimental results of nanofluids. The movement of nanoparticles in the fluidic media was simulated by a large-scale molecular thermal dynamic program (i.e. LAMMPS). The COMPASS force field was employed with smoothed particle hydrodynamic potential (SPH) and discrete particle dynamics potential (DPD). However, this study develops the understanding of how the rheological properties are affected due to the addition of nanoparticles in a fluid and the way DPD and SPH can be used for accurately estimating the rheological properties with Brownian effect. The rheological results of the simulation were confirmed by the convergence of the stress autocorrelation function, whereas experimental properties were measured using a rheometer. These rheological values of simulation were obtained and agreed within 5 % of the experimental values; they were identified and treated with a number of iterations and experimental tests. The results of the experiment and simulation show that 10 % CeO2 nanoparticles dispersion in water has a viscosity of 2.0–3.3 mPasPeer reviewedFinal Published versio

ME3CA - Monitoring environment exercise and emotion by a cognitive assistant

The elderly population has increased dramatically in today’s society. This fact implies the need to propose new policies of attention to this group but without increasing social spending. Currently, there is a need to promote the care of elderly people in their own homes, avoiding being transferred to saturated residences. Bearing this in mind, in recent years numerous approaches have tried to offer solutions in this sense using the continuous advances in new information and communication technologies. In this way, this article proposes the employment of a personal assistant to help the elderly in the development of their daily life activities. The proposed system, called ME3CA, is a cognitive assistant that involves users in rehabilitating exercise, consisting of a sensorization platform and different integrated decision-making mechanisms. The system tries to plan and recommend activities to older people trying to improve their physical activity. In addition, in the decision making process the assistant takes into account the emotions of the user. In this way, the system is more personalized and emotionally intelligent.- (undefined

Plasmodium knowlesi Genome Sequences from Clinical Isolates Reveal Extensive Genomic Dimorphism.

Plasmodium knowlesi is a newly described zoonosis that causes malaria in the human population that can be severe and fatal. The study of P. knowlesi parasites from human clinical isolates is relatively new and, in order to obtain maximum information from patient sample collections, we explored the possibility of generating P. knowlesi genome sequences from archived clinical isolates. Our patient sample collection consisted of frozen whole blood samples that contained excessive human DNA contamination and, in that form, were not suitable for parasite genome sequencing. We developed a method to reduce the amount of human DNA in the thawed blood samples in preparation for high throughput parasite genome sequencing using Illumina HiSeq and MiSeq sequencing platforms. Seven of fifteen samples processed had sufficiently pure P. knowlesi DNA for whole genome sequencing. The reads were mapped to the P. knowlesi H strain reference genome and an average mapping of 90% was obtained. Genes with low coverage were removed leaving 4623 genes for subsequent analyses. Previously we identified a DNA sequence dimorphism on a small fragment of the P. knowlesi normocyte binding protein xa gene on chromosome 14. We used the genome data to assemble full-length Pknbpxa sequences and discovered that the dimorphism extended along the gene. An in-house algorithm was developed to detect SNP sites co-associating with the dimorphism. More than half of the P. knowlesi genome was dimorphic, involving genes on all chromosomes and suggesting that two distinct types of P. knowlesi infect the human population in Sarawak, Malaysian Borneo. We use P. knowlesi clinical samples to demonstrate that Plasmodium DNA from archived patient samples can produce high quality genome data. We show that analyses, of even small numbers of difficult clinical malaria isolates, can generate comprehensive genomic information that will improve our understanding of malaria parasite diversity and pathobiology

Quantitative model for inferring dynamic regulation of the tumour suppressor gene p53

Background: The availability of various "omics" datasets creates a prospect of performing the study of genome-wide genetic regulatory networks. However, one of the major challenges of using mathematical models to infer genetic regulation from microarray datasets is the lack of information for protein concentrations and activities. Most of the previous researches were based on an assumption that the mRNA levels of a gene are consistent with its protein activities, though it is not always the case. Therefore, a more sophisticated modelling framework together with the corresponding inference methods is needed to accurately estimate genetic regulation from "omics" datasets. Results: This work developed a novel approach, which is based on a nonlinear mathematical model, to infer genetic regulation from microarray gene expression data. By using the p53 network as a test system, we used the nonlinear model to estimate the activities of transcription factor (TF) p53 from the expression levels of its target genes, and to identify the activation/inhibition status of p53 to its target genes. The predicted top 317 putative p53 target genes were supported by DNA sequence analysis. A comparison between our prediction and the other published predictions of p53 targets suggests that most of putative p53 targets may share a common depleted or enriched sequence signal on their upstream non-coding region. Conclusions: The proposed quantitative model can not only be used to infer the regulatory relationship between TF and its down-stream genes, but also be applied to estimate the protein activities of TF from the expression levels of its target genes

iGepros: an integrated gene and protein annotation server for biological nature exploration

<p>Abstract</p> <p>Background</p> <p>In the post-genomic era, transcriptomics and proteomics provide important information to understand the genomes. With fast development of high-throughput technology, more and more transcriptomics and proteomics data are generated at an unprecedented rate. Therefore, requirement of software to annotate those omics data and explore their biological nature arises. In the past decade, some pioneer works were presented to address this issue, but limitations still exist. Fox example, some of these tools offer command line only, which is not suitable for those users with little or no experience in programming. Besides, some tools don’t support large scale gene and protein analysis.</p> <p>Results</p> <p>To overcome these limitations, an integrated gene and protein annotation server named iGepros has been developed. The server provides user-friendly interfaces and detailed on-line examples, so most researchers even those with little or no programming experience can use it smoothly. Moreover, the server provides many functionalities to compare transcriptomics and proteomics data. Especially, the server is constructed under a model-view-control framework, which makes it easy to incorporate more functions to the server in the future.</p> <p>Conclusions</p> <p>In this paper, we present a server with powerful capability not only for gene and protein functional annotation, but also for transcriptomics and proteomics data comparison. Researchers can survey biological characters behind gene and protein datasets and accelerate their investigation of transcriptome and proteome by applying the server. The server is publicly available at <url>http://www.biosino.org/iGepros/</url>.</p

Effect of Gas Atmosphere on Catalytic Behaviour of Zirconia, Ceria and Ceria Zirconia Catalysts in Valeric Acid Ketonization

[EN] Ketonization of valeric acid, which can be obtained by lignocellulosic biomass conversion, was carried out in a fixed bed flow reactor over ZrO2, 5-20 % CeO2/ZrO2 and CeO2 both under hydrogen and nitrogen stream at 628 K and atmospheric pressure. Regardless gas-carrier 10 wt% CeO2/ZrO2 was found to show higher catalytic activity compared to zirconia per se as well as other ceria modified zirconia while ceria per se exhibited very low catalytic activity. All catalysts provided higher acid conversion in H-2 than in N-2 whereas selectivity to 5-nonanone was insensitive to gas atmosphere. XRD, FTIR, UV-Vis DRS, XPS, HRTEM methods were applied to characterize catalysts in reduced and unreduced states simulating corresponding reaction conditions during acid ketonization. XRD did not reveal any changes in zirconia and ceria/zirconia lattice parameters as well as crystalline phase depending on gas atmosphere while insertion of ceria in zirconia caused notable increase in lattice parameter indicating some distortion of crystalline structure. According to XPS, FTIR and UV-Vis methods, the carrier gas was found to affect catalyst surface composition leading to alteration in Lewis acid sites ratio. Appearance of Zr3+ cations was observed on the ZrO2 surface after hydrogen pretreatment whereas only Zr4+ cations were determined using nitrogen as a gas-carrier. These changes of catalyst's surface cation composition affected corresponding activity in ketonization probably being crucial for reaction mechanism involving metal cations catalytic centers for acid adsorption and COO- stabilization at the initial step.Financial support from the Russian Foundation of Basic Research (RFBR Grant No 11-03-94001-CSIC) is gratefully acknowledged. This work was supported by the Federal Program "Scientific and Educational Cadres of Russia'' (Grant No 2012-1.5-12-000-1013-002). The authors also wish to thank Dr. Evgeniy Gerasimov, Dr. Igor Prosvirin, Dr. Demid Demidov from the Department of Physicochemical Methods at the Boreskov Institute of Catalysis for TEM and XPS measurements.Zaytseva, YA.; Panchenko, VN.; Simonov, MN.; Shutilov, AA.; Zenkovets, GA.; Renz, M.; Simakova, IL.... (2013). Effect of Gas Atmosphere on Catalytic Behaviour of Zirconia, Ceria and Ceria Zirconia Catalysts in Valeric Acid Ketonization. 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An Improvement of Shotgun Proteomics Analysis by Adding Next-Generation Sequencing Transcriptome Data in Orange

BACKGROUND: Shotgun proteomics data analysis usually relies on database search. Because commonly employed protein sequence databases of most species do not contain sufficient protein information, the application of shotgun proteomics to the research of protein sequence profile remains a big challenge, especially to the species whose genome has not been sequenced yet. METHODOLOGY/PRINCIPAL FINDINGS: In this paper, we present a workflow with integrated database to partly address this problem. First, we downloaded the homologous species database. Next, we identified the transcriptome of the sample, created a protein sequence database based on the transcriptome data, and integtrated it with homologous species database. Lastly, we developed a workflow for identifying peptides simultaneously from shotgun proteomics data. CONCLUSIONS/SIGNIFICANCE: We used datasets from orange leaves samples to demonstrate our workflow. The results showed that the integrated database had great advantage on orange shotgun proteomics data analysis compared to the homologous species database, an 18.5% increase in number of proteins identification

Transcriptome Sequencing and De Novo Analysis for Yesso Scallop (Patinopecten yessoensis) Using 454 GS FLX

BACKGROUND: Bivalves comprise 30,000 extant species, constituting the second largest group of mollusks. However, limited genetic research has focused on this group of animals so far, which is, in part, due to the lack of genomic resources. The advent of high-throughput sequencing technologies enables generation of genomic resources in a short time and at a minimal cost, and therefore provides a turning point for bivalve research. In the present study, we performed de novo transcriptome sequencing to first produce a comprehensive expressed sequence tag (EST) dataset for the Yesso scallop (Patinopecten yessoensis). RESULTS: In a single 454 sequencing run, 805,330 reads were produced and then assembled into 32,590 contigs, with about six-fold sequencing coverage. A total of 25,237 unique protein-coding genes were identified from a variety of developmental stages and adult tissues based on sequence similarities with known proteins. As determined by GO annotation and KEGG pathway mapping, functional annotation of the unigenes recovered diverse biological functions and processes. Transcripts putatively involved in growth, reproduction and stress/immune-response were identified. More than 49,000 single nucleotide polymorphisms (SNPs) and 2,700 simple sequence repeats (SSRs) were also detected. CONCLUSION: Our data provide the most comprehensive transcriptomic resource currently available for P. yessoensis. Candidate genes potentially involved in growth, reproduction, and stress/immunity-response were identified, and are worthy of further investigation. A large number of SNPs and SSRs were also identified and ready for marker development. This resource should lay an important foundation for future genetic or genomic studies on this species

A sweetpotato gene index established by de novo assembly of pyrosequencing and Sanger sequences and mining for gene-based microsatellite markers

<p>Abstract</p> <p>Background</p> <p>Sweetpotato (<it>Ipomoea batatas </it>(L.) Lam.), a hexaploid outcrossing crop, is an important staple and food security crop in developing countries in Africa and Asia. The availability of genomic resources for sweetpotato is in striking contrast to its importance for human nutrition. Previously existing sequence data were restricted to around 22,000 expressed sequence tag (EST) sequences and ~ 1,500 GenBank sequences. We have used 454 pyrosequencing to augment the available gene sequence information to enhance functional genomics and marker design for this plant species.</p> <p>Results</p> <p>Two quarter 454 pyrosequencing runs used two normalized cDNA collections from stems and leaves from drought-stressed sweetpotato clone <it>Tanzania </it>and yielded 524,209 reads, which were assembled together with 22,094 publically available expressed sequence tags into 31,685 sets of overlapping DNA segments and 34,733 unassembled sequences. Blastx comparisons with the UniRef100 database allowed annotation of 23,957 contigs and 15,342 singletons resulting in 24,657 putatively unique genes. Further, 27,119 sequences had no match to protein sequences of UniRef100database. On the basis of this gene index, we have identified 1,661 gene-based microsatellite sequences, of which 223 were selected for testing and 195 were successfully amplified in a test panel of 6 hexaploid (<it>I. batatas</it>) and 2 diploid (<it>I. trifida</it>) accessions.</p> <p>Conclusions</p> <p>The sweetpotato gene index is a useful source for functionally annotated sweetpotato gene sequences that contains three times more gene sequence information for sweetpotato than previous EST assemblies. A searchable version of the gene index, including a blastn function, is available at <url>http://www.cipotato.org/sweetpotato_gene_index</url>.</p