Free-energy landscape of a chameleon sequence in explicit water and its inherent alpha/beta bifacial property

A sequence in yeast MATalpha2/MCM1/DNA complex that folds into alpha-helix or beta-hairpin depending on the surroundings has been known as "chameleon" sequence. We obtained the free-energy landscape of this sequence by using a generalized-ensemble method, multicanonical molecular dynamics simulation, to sample the conformational space. The system was expressed with an all-atom model in explicit water, and the initial conformation for the simulation was a random one. The free-energy landscape demonstrated that this sequence inherently has an ability to form either alpha or beta structure: The conformational distribution in the landscape consisted of two alpha-helical clusters with different packing patterns of hydrophobic residues, and four beta-hairpin clusters with different strand-strand interaction patterns. Narrow pathways connecting the clusters were found, and analysis on the pathways showed that a compact structure formed at the N-terminal root of the chameleon sequence controls the cluster-cluster transitions. The free-energy landscape indicates that a small conditional change induces alpha-beta transitions. Additional unfolding simulations done with replacing amino acids showed that the chameleon sequence has an advantage to form an alpha-helix. Current study may be useful to understand the mechanism of diseases resulting from abnormal chain folding, such as amyloid disease.     

北京城市公园湿地休憩功能的利用及其社会人口学因素

城市公园湿地是城市重要的生态基础设施,是城市居民休闲游憩的重要场所,具有重要的生态、社会文化服务功能。以北京地区20个典型的公园湿地为研究对象,采用问卷调查方法,将定性指标和定量指标相结合,用统计学方法分析了休憩者对公园湿地的使用情况,并采用Logistic回归方法揭示了影响城市公园湿地利用的社会人口学因素。结果表明:(1)休憩者到访公园湿地的距离与使用频率密切相关,43.4%的休憩者到达公园湿地的行程时间<1 h,这其中34.1%的休憩者使用公园湿地的频率每年在12次以上;仅有17.4%的休憩者每年使用各公园湿地频率为12次以上,这其中85%到达各公园湿地的行程时间<1h;(2)影响休憩者对公园湿地使用频率为每年12次以上的因素依次为行程时间、个人月收入、有无私家车、文化程度、职业、年龄。另外,性别与年龄的交互作用也有一定的影响;(3)愉悦身心是休憩者使用各公园湿地的最主要原因。研究旨在为城市公园湿地的合理优化与配置、城市绿地系统规划及城市的可持续发展提供科学依据。     

可描述横向电场中外周神经兴奋的电缆方程

传统的电缆方程只能用于描述纵向电场中外周神经的兴奋,无法描述外周神经在横向电场作用下的兴奋,其于两阶段过程模型,提出一种改进的电缆方程,可以描述外周神经在横向电场中的兴奋,其结果和Struijk的离体实验数据相吻合。此改进的电缆方程可用于描述任意电场中外周神经的兴奋。     

Laser-induced hyperthermia of nanoshell mediated vascularized tissue – A numerical study

Laser-induced hyperthermia treatment of tumor in a 2-D axisymmetric tissue embedded with moderate size (100–150 µm) blood vessels is studied. Laser absorption is enhanced by embedding gold–silica nanoshells in the tumor. Heat transfer in the tissue is modeled using Weinbaum–Jiji bioheat transfer equation. With laser irradiation, the volumetric radiation is accounted in the governing bioheat equation. Radiative information needed in the bioheat equation is calculated using the discrete ordinate method, and the coupled bioheat-radiation equation is solved using the finite volume method. Effects of power density, laser exposure time, beam radius, diameter of blood vessel and volume fractions of nanoshells on temperature spread in the tissue are analyzed.     

Enantiomerization of Allylic Trifluoromethyl Sulfoxides Studied by HPLC Analysis and DFT Calculations

Enantiomerization of allylic trifluoromethyl sulfoxides occurs spontaneously at room temperature through the corresponding allylic trifluoromethanesulfenates via a [2,3]‐sigmatropic rearrangement. Dynamic enantioselective high‐performance liquid chromatography (HPLC) analysis revealed the stereodynamics of these sulfoxides ranging from chromatographic resolution to peak coalescence at temperatures between 5 and 53 °C. The rate constant of enantiomerization and activation parameters were determined and compared with Density Functional Theory (DFT) calculations. Chirality 28:136–142, 2016. © 2015 Wiley Periodicals, Inc.     

Models for contact-mediated pattern formation: cells that form parallel arrays

Kinetic continuum models are derived for cells that crawl over a 2D substrate, undergo random reorientation, and turn in response to contact with a neighbor. The integro-partial differential equations account for changes in the distribution of orientations in the population. It is found that behavior depends on parameters such as total mass, random motility, adherence, and sloughing rates, as well as on broad aspects of the contact response. Linear stability analysis, and numerical, and cellular automata simulations reveal that as parameters are varied, a bifurcation leads to loss of stability of a uniform (isotropic) steady state, in favor of an (anisotropic) patterned state in which cells are aligned in parallel arrays.     

从中指骨长度推算身高的研究

作者对近年在华南地区收集的,已知生前身高的汉族成年男性骨骼的中指骨近节、中节进行了测量。用直线回归方程、多元回归方程对从中指骨长度推算身高进行了研究。并用50例国人骨骼标本对这些推算身高的方法作了检验。结果表明,中指骨与四肢大型长骨,以及从中指骨长度推算身高的直线回归方程与多元回归方程,对推算身高的价值都是相同的。     

Spatial autocorrelation and red herrings in geographical ecology

Aim Spatial autocorrelation in ecological data can inflate Type I errors in statistical analyses. There has also been a recent claim that spatial autocorrelation generates ‘red herrings’, such that virtually all past analyses are flawed. We consider the origins of this phenomenon, the implications of spatial autocorrelation for macro‐scale patterns of species diversity and set out a clarification of the statistical problems generated by its presence. Location To illustrate the issues involved, we analyse the species richness of the birds of western/central Europe, north Africa and the Middle East. Methods Spatial correlograms for richness and five environmental variables were generated using Moran's I coefficients. Multiple regression, using both ordinary least‐squares (OLS) and generalized least squares (GLS) assuming a spatial structure in the residuals, were used to identify the strongest predictors of richness. Autocorrelation analyses of the residuals obtained after stepwise OLS regression were undertaken, and the ranks of variables in the full OLS and GLS models were compared. Results Bird richness is characterized by a quadratic north–south gradient. Spatial correlograms usually had positive autocorrelation up to c. 1600 km. Including the environmental variables successively in the OLS model reduced spatial autocorrelation in the residuals to non‐detectable levels, indicating that the variables explained all spatial structure in the data. In principle, if residuals are not autocorrelated then OLS is a special case of GLS. However, our comparison between OLS and GLS models including all environmental variables revealed that GLS de‐emphasized predictors with strong autocorrelation and long‐distance clinal structures, giving more importance to variables acting at smaller geographical scales. Conclusion Although spatial autocorrelation should always be investigated, it does not necessarily generate bias. Rather, it can be a useful tool to investigate mechanisms operating on richness at different spatial scales. Claims that analyses that do not take into account spatial autocorrelation are flawed are without foundation.     

Analysing the representativeness of local‐scale palaeodiversity measurements: a case from the Lower Cretaceous plant assemblage of Hautrage (Mons Basin,Belgium)

Two plant fossil‐bearing beds from the middle Barremian of Belgium were analysed to ascertain how experimental designs affect conclusions regarding palaeodiversity at a local scale. We analysed eight lateral samples per bed taken regularly every 3 m using an exhaustive sub‐sampling method. The Clench equation was used to evaluate the completeness of the taxonomic inventory of the samples and the sampling effort needed to obtain a reliable representation of diversity. The number of replicates needed to obtain the same representation of diversity from different nearby lateral samples of the same bed ranged from 5 to 19. Richness (S), Evenness (J) and the number of equiprobable taxa (2^H’) greatly varied between samples from the same bed, even over short distances. Only one of the studied samples was representative of the taxonomic inventory of its bed. Our study shows that 1) the selection bias of the sampling area is reduced by increasing the number of lateral samples taken in a bed, enabling more reliable conclusions about local‐scale diversity; 2) intense sub‐sampling methods are needed to account for statistically independent observations of detailed lateral variation; and 3) sampling methods in palaeodiversity analyses must look for a similar degree of representativeness in samples rather than a homogeneous sample size. Using a sampling effort analysis provides evidence for the completeness of the data set, adjusting the amount of work required. Implementing the Clench equation in palaeodiversity analyses improves the performance of data acquisition in palaeoecological studies and provides a quality test of the data sets derived from them.     

A machine‐learning approach for extending classical wildlife resource selection analyses

Resource selection functions (RSFs) are tremendously valuable for ecologists and resource managers because they quantify spatial patterns in resource utilization by wildlife, thereby facilitating identification of critical habitat areas and characterizing specific habitat features that are selected or avoided. RSFs discriminate between known‐use resource units (e.g., telemetry locations) and available (or randomly selected) resource units based on an array of environmental features, and in their standard form are performed using logistic regression. As generalized linear models, standard RSFs have some notable limitations, such as difficulties in accommodating nonlinear (e.g., humped or threshold) relationships and complex interactions. Increasingly, ecologists are using flexible machine‐learning methods (e.g., random forests, neural networks) to overcome these limitations. Herein, we investigate the seasonal resource selection patterns of mule deer (Odocoileus hemionus) by comparing a logistic regression framework with random forest (RF), a popular machine‐learning algorithm. Random forest (RF) models detected nonlinear relationships (e.g., optimal ranges for slope and elevation) and complex interactions which would have been very challenging to discover and characterize using standard model‐based approaches. Compared with standard RSF models, RF models exhibited improved predictive skill, provided novel insights about resource selection patterns of mule deer, and, when projected across a relevant geographic space, manifested notable differences in predicted habitat suitability. We recommend that wildlife researchers harness the strengths of machine‐learning tools like RF in addition to “classical” tools (e.g., mixed‐effects logistic regression) for evaluating resource selection, especially in cases where extensive telemetry data sets are available.