Analysis of peptides from known proteins: Clusterization in sequence space

A combinatorial sequence space (CSS) model was introduced to represent sequences as a set of overlapping k-tuples of some fixed length which correspond to points in the CSS. The aim was to analyze clusterization of protein sequences in the CSS and to test various hypotheses about the possible evolutionary basis of this clusterization. The authors developed an easy-to-use technique which can reveal and analyze such a clusterization in a multidimensional CSS. Application of the technique led to an unexpectedly high clusterization of points in the CSS corresponding to k-tuples from known proteins. The clusterization could not be inferred from nonuniform amino acid frequencies or be explained by the influence of homologous data. None of the tested possible evolutionary and structural factors could explain the clusterization observed either. It looked as if certain protein sequence variations occurred and were fixed in the early course of evolution. Subsequent evolution (predominantly neutral) allowed only a limited number of changes and permitted new variants which led to preservation of certain k-tuples during the course of evolution. This was consistent with the theory of exon shuffling and protein block structure evolution. Possible applications of sequence space features found were also discussed.Correspondence to: H.A. Lim     

Stem cell competition driven by the Axin2-p53 axis controls brain size during murine development

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A review of methods to trace material flows into final products in dynamic material flow analysis: From industry shipments in physical units to monetary input–output tables,Part 1

Dynamic material flow analysis (dMFA) is widely used to model stock-flow dynamics. To appropriately represent material lifetimes, recycling potentials, and service provision, dMFA requires data about the allocation of economy-wide material consumption to different end-use products or sectors, that is, the different product stocks, in which material consumption accumulates. Previous estimates of this allocation only cover few years, countries, and product groups. Recently, several new methods for estimating end-use product allocation in dMFA were proposed, which so far lack systematic comparison. We review and systematize five methods for tracing material consumption into end-use products in inflow-driven dMFA and discuss their strengths and limitations. Widely used data on industry shipments in physical units have low spatio-temporal coverage, which limits their applicability across countries and years. Monetary input–output tables (MIOTs) are widely available and their economy-wide coverage makes them a valuable source to approximate material end-uses. We find four distinct MIOT-based methods: consumption-based, waste input–output MFA (WIO-MFA), Ghosh absorbing Markov chain, and partial Ghosh. We show that when applied to a given MIOT, the methods’ underlying input–output models yield the same results, with the exception of the partial Ghosh method, which involves simplifications. For practical applications, the MIOT system boundary must be aligned to those of dMFA, which involves the removal of service flows, sector (dis)aggregation, and re-defining specific intermediate outputs as final demand. Theoretically, WIO-MFA, applied to a modified MIOT, produces the most accurate results as it excludes massless and waste transactions. In part 2 of this work, we compare methods empirically and suggest improvements for aligning MIOT-dMFA system boundaries.     

番木瓜proteinase omega基因启动子的克隆及功能初步研究

采用PCR技术从番木瓜基因组中克隆了proteinase omega基因的部分序列及其5′侧翼序列。序列分析表明,克隆到的基因序列与GenBank中的序列同源性为96%,长1039bp的5′端侧翼序列在GenBank数据库中没有同源片段。预测5′端侧翼序列有两处基础启动子区域,转录起始位点(TSS)分别为是A,T。在基础启动子区域都存在TATA-box,上游发现多处CAAT-box,G-box,I-box等顺式作用元件和AT富含区。构建了植物表达载体并用基因枪轰击番木瓜的叶组织,GUS基因瞬间表达结果表明,该长1039bp的5′端侧翼序列具有驱动GUS基因在乳管中表达的功能。该启动子的发现对进一步研究启动子的功能和开发番木瓜作为生物反应器具有重要意义。     

Meta-analysis in applied ecology

This overview examines research synthesis in applied ecology and conservation. Vote counting and pooling unweighted averages are widespread despite the superiority of syntheses based on weighted combination of effects. Such analyses allow exploration of methodological uncertainty in addition to consistency of effects across species, space and time, but exploring heterogeneity remains controversial. Meta-analyses are required to generalize in ecology, and to inform evidence-based decision-making, but the more sophisticated statistical techniques and registers of research used in other disciplines must be employed in ecology to fully realize their benefits.     

Profiles of trace elements in toenails of Arab-Americans in the Detroit area, Michigan

Exposure to environmental contaminants is complicated by factors related to socioeconomic status, diet, and other culturally conditioned risk behaviors. Determination of a trace element profile in toenails can be used as a tool in biomonitoring the exposure history or assessing the deficiency of a particular element in a study population, which can lead to a better understanding of environmental and disease risks. Toenail clippings from 259 Arab Americans (163 adults, 96 children) residing in a highly industrialized area were analyzed for Al, V, Cr, Mn, Co, Ni, Cu, As, Se, Mo, Cd, Ba, Tl, and Pb using an inductively coupled plasma-mass spectrometer. Mean concentrations were compared with published values, and the influence of age, gender, and other demographic factors were explored. Elevated levels of Ni in this population warrant further investigation. Significant differences in the mean concentration of Al, V, Cr, Mn, Cd, Pb, and Se exist between toenails of adults and children. Pearson correlation coefficients reveal strong significant associations among Cd, Cr, and Tl (p<0.05), in addition to other elements. These investigations provide insight into exposures and factors influencing exposures in this population while adding to the growing fund of knowledge surrounding use of toenails as a marker of exposure.     

Proteomic identification of the TRAF6 regulation of vacuolar ATPase for osteoclast function

Osteoclasts are cells specialized for bone resorption. For osteoclast activation, tumor necrosis factor receptor-associated factor 6 (TRAF6) plays a pivotal role. To find new molecules that bind TRAF6 and have a function in osteoclast activation, we employed a proteomic approach. TRAF6-binding proteins were purified from osteoclast cell lysates by affinity chromatography and their identity was disclosed by MS. The identified proteins included several heat shock proteins, actin and actin-binding proteins, and vacuolar ATPase (V-ATPase). V-ATPase, documented for a great increase in expression during osteoclast differentiation, is an important enzyme for osteoclast function; it transports proton to resorption lacunae for hydroxyapatite dissolution. The binding of V-ATPase with TRAF6 was confirmed both in vitro by GST pull-down assays and in osteoclasts by co-immunoprecipitation and confocal microscopy experiments. In addition, the V-ATPase activity associated with TRAF6 increased in osteoclasts stimulated with receptor activator of nuclear factor kappaB ligand (RANKL). Furthermore, a dominant-negative form of TRAF6 abrogated the RANKL stimulation of V-ATPase activity. Our study identified V-ATPase as a TRAF6-binding protein using a proteomics strategy and proved a direct link between these two important molecules for osteoclast function.     

Phylogeography of island canary (Serinus canaria) populations

Island canaries (Serinus canaria) are characterised as a species living exclusively on North Atlantic islands, mainly on the Azores, Madeira and Canary Islands. Although they are very common in their habitats, their behaviour and breeding system has only recently been studied systematically. To advance the understanding of their ecology and to see if the rather isolated archipelagos are already promoting a genetic differentiation, we investigated their phylogeographic relationship as revealed by mtDNA sequences of the cytochrome b gene and investigated whether this measure corresponds to morphological characteristics within the islands. Genetic distances were very low throughout the distribution range of the species. Although the variation of genetic distances within the population of Pico (Azores) was larger than that on Madeira and Canary Islands, the genetic distances between island populations were very low throughout which prevented a clear phylogeographic differentiation. Moreover, morphological measurements did not reveal a consistent pattern to reliably separate the populations, although the measures of beak length and body weight revealed a clear island-specific differentiation. These data lead to the assumption that the colonisation of the Atlantic islands by the canaries occurred very recently, while there is no persisting gene flow between the populations.     

Multikink quantile regression for longitudinal data with application to progesterone data analysis

Motivated by investigating the relationship between progesterone and the days in a menstrual cycle in a longitudinal study, we propose a multikink quantile regression model for longitudinal data analysis. It relaxes the linearity condition and assumes different regression forms in different regions of the domain of the threshold covariate. In this paper, we first propose a multikink quantile regression for longitudinal data. Two estimation procedures are proposed to estimate the regression coefficients and the kink points locations: one is a computationally efficient profile estimator under the working independence framework while the other one considers the within-subject correlations by using the unbiased generalized estimation equation approach. The selection consistency of the number of kink points and the asymptotic normality of two proposed estimators are established. Second, we construct a rank score test based on partial subgradients for the existence of the kink effect in longitudinal studies. Both the null distribution and the local alternative distribution of the test statistic have been derived. Simulation studies show that the proposed methods have excellent finite sample performance. In the application to the longitudinal progesterone data, we identify two kink points in the progesterone curves over different quantiles and observe that the progesterone level remains stable before the day of ovulation, then increases quickly in 5 to 6 days after ovulation and then changes to stable again or drops slightly.