200 research outputs found
Improving the flexibility of ship propeller additively manufactured from HDPE/long carbon fibre composite by pre-preg-coating
A new approach for estimation of PVT properties of pure gases based on artificial neural network model
Insulin Production and Signaling in Renal Tubules of Drosophila Is under Control of Tachykinin-Related Peptide and Regulates Stress Resistance
The insulin-signaling pathway is evolutionarily conserved in animals and regulates growth, reproduction, metabolic homeostasis, stress resistance and life span. In Drosophila seven insulin-like peptides (DILP1-7) are known, some of which are produced in the brain, others in fat body or intestine. Here we show that DILP5 is expressed in principal cells of the renal tubules of Drosophila and affects survival at stress. Renal (Malpighian) tubules regulate water and ion homeostasis, but also play roles in immune responses and oxidative stress. We investigated the control of DILP5 signaling in the renal tubules by Drosophila tachykinin peptide (DTK) and its receptor DTKR during desiccative, nutritional and oxidative stress. The DILP5 levels in principal cells of the tubules are affected by stress and manipulations of DTKR expression in the same cells. Targeted knockdown of DTKR, DILP5 and the insulin receptor dInR in principal cells or mutation of Dilp5 resulted in increased survival at either stress, whereas over-expression of these components produced the opposite phenotype. Thus, stress seems to induce hormonal release of DTK that acts on the renal tubules to regulate DILP5 signaling. Manipulations of S6 kinase and superoxide dismutase (SOD2) in principal cells also affect survival at stress, suggesting that DILP5 acts locally on tubules, possibly in oxidative stress regulation. Our findings are the first to demonstrate DILP signaling originating in the renal tubules and that this signaling is under control of stress-induced release of peptide hormone
Human embryo polarization requires PLC signaling to mediate trophectoderm specification
Apico-basal polarization of cells within the embryo is critical for the segregation of distinct lineages during mammalian development. Polarized cells become the trophectoderm (TE), which forms the placenta, and apolar cells become the inner cell mass (ICM), the founding population of the fetus. The cellular and molecular mechanisms leading to polarization of the human embryo and its timing during embryogenesis have remained unknown. Here, we show that human embryo polarization occurs in two steps: it begins with the apical enrichment of F-actin and is followed by the apical accumulation of the PAR complex. This two-step polarization process leads to the formation of an apical domain at the 8–16 cell stage. Using RNA interference, we show that apical domain formation requires Phospholipase C (PLC) signaling, specifically the enzymes PLCB1 and PLCE1, from the eight-cell stage onwards. Finally, we show that although expression of the critical TE differentiation marker GATA3 can be initiated independently of embryo polarization, downregulation of PLCB1 and PLCE1 decreases GATA3 expression through a reduction in the number of polarized cells. Therefore, apical domain formation reinforces a TE fate. The results we present here demonstrate how polarization is triggered to regulate the first lineage segregation in human embryos
Integrated solar-assisted heat pumps for water heating coupled to gas burners; control criteria for dynamic operation
Effectiveness of breeding selection for grain quality in common bean.
he aims of this study were to investigate the genetic variability and the genotype × environment interaction for quality and yield traits in common bean (Phaseolus vulgaris L.), to evaluate the degree of informativeness of the evaluations of grain quality in only one environment, to estimate genetic parameters for grain quality traits, and to select lines with superior grain quality. We evaluated 81 carioca common bean lines in preliminary line trials in several environments for nutritional, technological, and commercial quality and selected the 20 superior lines, which were evaluated in validation trials in nine environments. Individual and combined ANOVAs were performed for all the traits. Correlations were estimated between Fe and Zn concentrations and yield; adaptability and phenotypic stability were analyzed; and superior genotypes were selected based on the Mulamba & Mock index. It is possible to increase the Fe, Zn, and crude protein concentrations and reduce cooking time; however, increasing crude fiber is a challenge. Preliminary evaluation of the quality traits in only one environment was effective and sufficient for selection of genotypes superior in Fe concentration, crude fiber, crude protein, and cooking time; and genetic gains can be obtained from selection for these traits. Genetic and phenotypic correlations were observed between Fe and Zn concentrations. The lines CNFC 16627, CNFC 16518, CNFC 16602, CNFC 16615, and CNFC 16520 are superior based on the selection index and are recommended for breeding for grain quality in carioca common bean
Estimating the burden of antimicrobial resistance: a systematic literature review.
Background: Accurate estimates of the burden of antimicrobial resistance (AMR) are needed to establish the magnitude of this global threat in terms of both health and cost, and to paramaterise cost-effectiveness evaluations of interventions aiming to tackle the problem. This review aimed to establish the alternative methodologies used in estimating AMR burden in order to appraise the current evidence base. Methods: MEDLINE, EMBASE, Scopus, EconLit, PubMed and grey literature were searched. English language studies evaluating the impact of AMR (from any microbe) on patient, payer/provider and economic burden published between January 2013 and December 2015 were included. Independent screening of title/abstracts followed by full texts was performed using pre-specified criteria. A study quality score (from zero to one) was derived using Newcastle-Ottawa and Philips checklists. Extracted study data were used to compare study method and resulting burden estimate, according to perspective. Monetary costs were converted into 2013 USD. Results: Out of 5187 unique retrievals, 214 studies were included. One hundred eighty-seven studies estimated patient health, 75 studies estimated payer/provider and 11 studies estimated economic burden. 64% of included studies were single centre. The majority of studies estimating patient or provider/payer burden used regression techniques. 48% of studies estimating mortality burden found a significant impact from resistance, excess healthcare system costs ranged from non-significance to 21,832 per case to over $3 trillion in GDP loss. Median quality scores (interquartile range) for patient, payer/provider and economic burden studies were 0.67 (0.56-0.67), 0.56 (0.46-0.67) and 0.53 (0.44-0.60) respectively. Conclusions: This study highlights what methodological assumptions and biases can occur dependent on chosen outcome and perspective. Currently, there is considerable variability in burden estimates, which can lead in-turn to inaccurate intervention evaluations and poor policy/investment decisions. Future research should utilise the recommendations presented in this review. Trial registration: This systematic review is registered with PROSPERO (PROSPERO CRD42016037510)
A Note on the Strength Characteristics of Small-Scale Concrete with Special Aggregates
The National Science Foundation Research Grant GK-189
Solar potential in Turkey
ARCAKLIOGLU, Erol/0000-0001-8073-5207WOS: 000225346000004Most of the locations in Turkey receive abundant solar-energy, because Turkey lies in a sunny belt between 36degrees and 42 degreesN latitudes. Average annual temperature is 18 to 20 degreesC on the south coast, falls to 14-16 degreesC on the west coat, and fluctuates between 4 and 18 degreesC in the central parts. The yearly average solar-radiation is 3.6 kWh/m(2) day, and the total yearly radiation period is similar to2610 It. In this study, a new formulation based on meteorological and geographical data was developed to determine the solar-energy potential in Turkey using artificial neural-networks (ANNs). Scaled conjugate gradient (SCG), Pola-Ribiere conjugate gradient (CGP), and Levenberg-Marquardt (LM) learning algorithms and logistic sigmoid (logsig) transfer function were used in the networks. Meteorological data for last four years (2000-2003) from 12 cities (Canakkale, Kars, Hakkari, Sakarya, Erzurum, Zonguldak, Balikesir, Artvin, Corum, Konya, Siirt, and Tekirdag) spread over Turkey were used in order to train the neural-network. Meteorological and geographical data (latitude, longitude, altitude, month, mean sunshine-duration, and mean temperature) are used in the input layer of the network. Solar-radiation is in the output layer. The maximum mean absolute percentage error was found to be less than 3.832% and R-2 values to be about 99.9738% for the selected stations. The ANN models show greater accuracy for evaluating solar-resource posibilities in regions where a network of monitoring stations has not been established in Turkey. This study confirms the ability of the ANN to predict solar-radiation values accurately. (C) 2004 Elsevier Ltd. All rights reserved
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