The first CCD photometric study of the open cluster NGC 2126

We present the first CCD photometric observations of the northern open cluster NGC 2126. Data were taken on eight nights in February and December 2002 with a total time span of ~57 hours. Almost 1000 individual V-band frames were examined to find short-period variable stars. We discovered six new variable stars, of which one is a promising candidate for an eclipsing binary with a pulsating component. Two stars were classified as delta Scuti stars and one as Algol-type eclipsing binary. Two stars are slow variables with ambiguous classification. From absolute VRI photometry we have estimated the main characteristics of the cluster: m-M=11.0+/-0.5, E(V-I)=0.4+/-0.1, E(V-R)=0.08+/-0.06 (E(B-V)=0.2+/-0.15) and d=1.3+/-0.6 kpc. Cluster membership is suggested for three variable stars from their positions on the colour-magnitude diagram.Comment: 7 pages, 10 figures, accepted for publication in A&

Seatbelt use and risk of major injuries sustained by vehicle occupants during motor-vehicle crashes: A systematic review and meta-analysis of cohort studies

BackgroundIn 2004, a World Health Report on road safety called for enforcement of measures such as seatbelt use, effective at minimizing morbidity and mortality caused by road traffic accidents. However, injuries caused by seatbelt use have also been described. Over a decade after publication of the World Health Report on road safety, this study sought to investigate the relationship between seatbelt use and major injuries in belted compared to unbelted passengers.MethodsCohort studies published in English language from 2005 to 2018 were retrieved from seven databases. Critical appraisal of studies was carried out using the Scottish Intercollegiate Guidelines Network (SIGN) checklist. Pooled risk of major injuries was assessed using the random effects meta-analytic model. Heterogeneity was quantified using I-squared and Tau-squared statistics. Funnel plots and Egger's test were used to investigate publication bias. This review is registered in PROSPERO (CRD42015020309).ResultsEleven studies, all carried out in developed countries were included. Overall, the risk of any major injury was significantly lower in belted passengers compared to unbelted passengers (RR 0.47; 95%CI, 0.29 to 0.80; I-2=99.7; P=0.000). When analysed by crash types, belt use significantly reduced the risk of any injury (RR 0.35; 95%CI, 0.24 to 0.52). Seatbelt use reduces the risk of facial injuries (RR=0.56, 95% CI=0.37 to 0.84), abdominal injuries (RR=0.87; 95% CI=0.78 to 0.98) and, spinal injuries (RR=0.56, 95% CI=0.37 to 0.84). However, we found no statistically significant difference in risk of head injuries (RR=0.49; 95% CI=0.22 to 1.08), neck injuries (RR=0.69: 95%CI 0.07 to 6.44), thoracic injuries (RR 0.96, 95%CI, 0.74 to 1.24), upper limb injuries (RR=1.05, 95%CI 0.83 to 1.34) and lower limb injuries (RR=0.77, 95%CI 0.58 to 1.04) between belted and non-belted passengers.ConclusionIn sum, the risk of most major road traffic injuries is lower in seatbelt users. Findings were inconclusive regarding seatbelt use and susceptibility to thoracic, head and neck injuries during road traffic accidents. Awareness should be raised about the dangers of inadequate seatbelt use. Future research should aim to assess the effects of seatbelt use on major injuries by crash type

Hybridization in parasites: consequences for adaptive evolution, pathogenesis and public health in a changing world

[No abstract available

Signatures of arithmetic simplicity in metabolic network architecture

Metabolic networks perform some of the most fundamental functions in living cells, including energy transduction and building block biosynthesis. While these are the best characterized networks in living systems, understanding their evolutionary history and complex wiring constitutes one of the most fascinating open questions in biology, intimately related to the enigma of life's origin itself. Is the evolution of metabolism subject to general principles, beyond the unpredictable accumulation of multiple historical accidents? Here we search for such principles by applying to an artificial chemical universe some of the methodologies developed for the study of genome scale models of cellular metabolism. In particular, we use metabolic flux constraint-based models to exhaustively search for artificial chemistry pathways that can optimally perform an array of elementary metabolic functions. Despite the simplicity of the model employed, we find that the ensuing pathways display a surprisingly rich set of properties, including the existence of autocatalytic cycles and hierarchical modules, the appearance of universally preferable metabolites and reactions, and a logarithmic trend of pathway length as a function of input/output molecule size. Some of these properties can be derived analytically, borrowing methods previously used in cryptography. In addition, by mapping biochemical networks onto a simplified carbon atom reaction backbone, we find that several of the properties predicted by the artificial chemistry model hold for real metabolic networks. These findings suggest that optimality principles and arithmetic simplicity might lie beneath some aspects of biochemical complexity

Convective self-aggregation in numerical simulations: a review

Organized convection in the Tropics occurs across a range of spatial and temporal scales and strongly influences cloud cover and humidity. One mode of organization found is “self-aggregation”, in which moist convection spontaneously organizes into one or several isolated clusters despite spatially homogeneous boundary conditions and forcing. Self-aggregation is driven by interactions between clouds, moisture, radiation, surface fluxes, and circulation, and occurs in a wide variety of idealized simulations of radiative-convective equilibrium. Here we provide a review of convective self-aggregation in numerical simulations, including its character, causes, and effects. We describe the evolution of self-aggregation including its time and length scales and the physical mechanisms leading to its triggering and maintenance, and we also discuss possible links to climate and climate change

Optimal flux spaces of genome-scale stoichiometric models are determined by a few subnetworks

The metabolism of organisms can be studied with comprehensive stoichiometric models of their metabolic networks. Flux balance analysis (FBA) calculates optimal metabolic performance of stoichiometric models. However, detailed biological interpretation of FBA is limited because, in general, a huge number of flux patterns give rise to the same optimal performance. The complete description of the resulting optimal solution spaces was thus far a computationally intractable problem. Here we present CoPE-FBA: Comprehensive Polyhedra Enumeration Flux Balance Analysis, a computational method that solves this problem. CoPE-FBA indicates that the thousands to millions of optimal flux patterns result from a combinatorial explosion of flux patterns in just a few metabolic sub-networks. The entire optimal solution space can now be compactly described in terms of the topology of these sub-networks. CoPE-FBA simplifies the biological interpretation of stoichiometric models of metabolism, and provides a profound understanding of metabolic flexibility in optimal states

Assessment of the proliferative, apoptotic and cellular renovation indices of the human mammary epithelium during the follicular and luteal phases of the menstrual cycle

Introduction During the menstrual cycle, the mammary gland goes through sequential waves of proliferation and apoptosis. in mammary epithelial cells, hormonal and non-hormonal factors regulate apoptosis. To determine the cyclical effects of gonadal steroids on breast homeostasis, we evaluated the apoptotic index ( AI) determined by terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling ( TUNEL) staining in human mammary epithelial cells during the spontaneous menstrual cycle and correlated it with cellular proliferation as determined by the expression of Ki-67 during the same period.Methods Normal breast tissue samples were obtained from 42 randomly selected patients in the proliferative ( n = 21) and luteal ( n = 21) phases. Menstrual cycle phase characterization was based on the date of the last and subsequent menses, and on progesterone serum levels obtained at the time of biopsy.Results the proliferation index ( PI), defined as the number of Ki-67-positive nuclei per 1,000 epithelial cells, was significantly larger in the luteal phase (30.46) than in the follicular phase (13.45; P = 0.0033). the AI was defined as the number of TUNEL-positive cells per 1,000 epithelial cells. the average AI values in both phases of the menstrual cycle were not statistically significant ( P = 0.21). However, the cell renewal index ( CRI = PI/AI) was significantly higher in the luteal phase ( P = 0.033). A significant cyclical variation of PI, AI and CRI was observed. PI and AI peaks occurred on about the 24th day of the menstrual cycle, whereas the CRI reached higher values on the 28th day.Conclusions We conclude that proliferative activity is dependent mainly on hormonal fluctuations, whereas apoptotic activity is probably regulated by hormonal and non-hormonal factors.Universidade Federal de São Paulo, Dept Gyneol, Mastol Div, São Paulo, BrazilStanford Univ, Sch Med, Dept Neurosurg, Stanford, CA 94305 USAAPC Pathol, São Paulo, BrazilUniversidade Federal de São Paulo, Dept Gyneol, Mastol Div, São Paulo, BrazilWeb of Scienc

Meneco, a Topology-Based Gap-Filling Tool Applicable to Degraded Genome-Wide Metabolic Networks

International audienceIncreasing amounts of sequence data are becoming available for a wide range of non-model organisms. Investigating and modelling the metabolic behaviour of those organisms is highly relevant to understand their biology and ecology. As sequences are often incomplete and poorly annotated, draft networks of their metabolism largely suffer from incompleteness. Appropriate gap-filling methods to identify and add missing reactions are therefore required to address this issue. However, current tools rely on phenotypic or taxonomic information, or are very sensitive to the stoichiometric balance of metabolic reactions, especially concerning the co-factors. This type of information is often not available or at least prone to errors for newly-explored organisms. Here we introduce Meneco, a tool dedicated to the topological gap-filling of genome-scale draft metabolic networks. Meneco reformulates gap-filling as a qualitative combinatorial optimization problem, omitting constraints raised by the stoichiometry of a metabolic network considered in other methods, and solves this problem using Answer Set Programming. Run on several artificial test sets gathering 10,800 degraded Escherichia coli networks Meneco was able to efficiently identify essential reactions missing in networks at high degradation rates, outperforming the stoichiometry-based tools in scalability. To demonstrate the utility of Meneco we applied it to two case studies. Its application to recent metabolic networks reconstructed for the brown algal model Ectocarpus siliculosus and an associated bacterium Candidatus Phaeomarinobacter ectocarpi revealed several candidate metabolic pathways for algal-bacterial interactions. Then Meneco was used to reconstruct, from transcriptomic and metabolomic data, the first metabolic network for the microalga Euglena mutabilis. These two case studies show that Meneco is a versatile tool to complete draft genome-scale metabolic networks produced from heterogeneous data, and to suggest relevant reactions that explain the metabolic capacity of a biological system

A sociological dilemma: race, segregation, and US sociology

US sociology has been historically segregated in that, at least until the 1960s, there were two distinct institutionally organized traditions of sociological thought – one black and one white. For the most part, however, dominant historiographies have been silent on that segregation and, at best, reproduce it when addressing the US sociological tradition. This is evident in the rarity with which scholars such as WEB Du Bois, E Franklin Frazier, Oliver Cromwell Cox, or other ‘African American Pioneers of Sociology’, as Saint-Arnaud calls them, are presented as core sociological voices within histories of the discipline. This article addresses the absence of African American sociologists from the US sociological canon and, further, discusses the implications of this absence for our understanding of core sociological concepts. With regard to the latter, the article focuses in particular on the debates around equality and emancipation and discusses the ways in which our understanding of these concepts could be extended by taking into account the work of African American sociologists and their different interpretations of core themes

The Caenorhabditis elegans Gene mfap-1 Encodes a Nuclear Protein That Affects Alternative Splicing

RNA splicing is a major regulatory mechanism for controlling eukaryotic gene expression. By generating various splice isoforms from a single pre–mRNA, alternative splicing plays a key role in promoting the evolving complexity of metazoans. Numerous splicing factors have been identified. However, the in vivo functions of many splicing factors remain to be understood. In vivo studies are essential for understanding the molecular mechanisms of RNA splicing and the biology of numerous RNA splicing-related diseases. We previously isolated a Caenorhabditis elegans mutant defective in an essential gene from a genetic screen for suppressors of the rubberband Unc phenotype of unc-93(e1500) animals. This mutant contains missense mutations in two adjacent codons of the C. elegans microfibrillar-associated protein 1 gene mfap-1. mfap-1(n4564 n5214) suppresses the Unc phenotypes of different rubberband Unc mutants in a pattern similar to that of mutations in the splicing factor genes uaf-1 (the C. elegans U2AF large subunit gene) and sfa-1 (the C. elegans SF1/BBP gene). We used the endogenous gene tos-1 as a reporter for splicing and detected increased intron 1 retention and exon 3 skipping of tos-1 transcripts in mfap-1(n4564 n5214) animals. Using a yeast two-hybrid screen, we isolated splicing factors as potential MFAP-1 interactors. Our studies indicate that C. elegans mfap-1 encodes a splicing factor that can affect alternative splicing.National Natural Science Foundation (China) (Grant 30971639)United States. National Institutes of Health (Grant GM24663