Irregular Shaped Small Nodule Detection Using a Robust Scan Statistic

Statistics in Biosciences - The spatial scan statistics based on the Poisson and binomial models are the most common methods to detect spatial clusters in disease surveillance. These models rely on...     

Identifying Signatures of Natural Selection in Tibetan and Andean Populations Using Dense Genome Scan Data

High-altitude hypoxia (reduced inspired oxygen tension due to decreased barometric pressure) exerts severe physiological stress on the human body. Two high-altitude regions where humans have lived for millennia are the Andean Altiplano and the Tibetan Plateau. Populations living in these regions exhibit unique circulatory, respiratory, and hematological adaptations to life at high altitude. Although these responses have been well characterized physiologically, their underlying genetic basis remains unknown. We performed a genome scan to identify genes showing evidence of adaptation to hypoxia. We looked across each chromosome to identify genomic regions with previously unknown function with respect to altitude phenotypes. In addition, groups of genes functioning in oxygen metabolism and sensing were examined to test the hypothesis that particular pathways have been involved in genetic adaptation to altitude. Applying four population genetic statistics commonly used for detecting signatures of natural selection, we identified selection-nominated candidate genes and gene regions in these two populations (Andeans and Tibetans) separately. The Tibetan and Andean patterns of genetic adaptation are largely distinct from one another, with both populations showing evidence of positive natural selection in different genes or gene regions. Interestingly, one gene previously known to be important in cellular oxygen sensing, EGLN1 (also known as PHD2), shows evidence of positive selection in both Tibetans and Andeans. However, the pattern of variation for this gene differs between the two populations. Our results indicate that several key HIF-regulatory and targeted genes are responsible for adaptation to high altitude in Andeans and Tibetans, and several different chromosomal regions are implicated in the putative response to selection. These data suggest a genetic role in high-altitude adaption and provide a basis for future genotype/phenotype association studies necessary to confirm the role of selection-nominated candidate genes and gene regions in adaptation to altitude.     

A Scan Statistic for Binary Outcome Based on Hypergeometric Probability Model,with an Application to Detecting Spatial Clusters of Japanese Encephalitis

As a useful tool for geographical cluster detection of events, the spatial scan statistic is widely applied in many fields and plays an increasingly important role. The classic version of the spatial scan statistic for the binary outcome is developed by Kulldorff, based on the Bernoulli or the Poisson probability model. In this paper, we apply the Hypergeometric probability model to construct the likelihood function under the null hypothesis. Compared with existing methods, the likelihood function under the null hypothesis is an alternative and indirect method to identify the potential cluster, and the test statistic is the extreme value of the likelihood function. Similar with Kulldorff’s methods, we adopt Monte Carlo test for the test of significance. Both methods are applied for detecting spatial clusters of Japanese encephalitis in Sichuan province, China, in 2009, and the detected clusters are identical. Through a simulation to independent benchmark data, it is indicated that the test statistic based on the Hypergeometric model outweighs Kulldorff’s statistics for clusters of high population density or large size; otherwise Kulldorff’s statistics are superior.     

Spatial Mode Selection by the Phase Modulation of Subwavelength Plasmonic Grating

The extraordinary transmission of the subwavelength gold grating has been investigated by the rigorous coupled-wave analysis and verified by the metal–insulator–metal plasmonic waveguide method. The physical mechanisms of the extraordinary transmission are characterized as the excitation of the surface plasmon polariton modes. The subwavelength grating integrated with the distributed Bragg reflector is proposed to modulate the phase to realize spatial mode selection, which is prospected to be applied for transverse mode selection in the vertical cavity surface-emitting laser.     

Effective Size of Populations under Selection

Equations to approximate the effective size (N(e)) of populations under continued selection are obtained that include the possibility of partial full-sib mating and other systems such as assortative mating. The general equation for the case of equal number of sexes and constant number of breeding individuals (N) is N(e) = 4N/[2(1 - α(I)) + (S(k)(2) + 4Q(2)C(2)) (1 + α(I) + 2α(O))], where S(k)(2) is the variance of family size due to sampling without selection, C(2) is the variance of selective advantages among families (the squared coefficient of variation of the expected number of offspring per family), α(I) is the deviation from Hardy-Weinberg proportions, α(O) is the correlation between genes of male and female parents, and Q(2) is the term accounting for the cumulative effect of selection on an inherited trait. This is obtained as Q = 2/[2 - G(1 + r)], where G is the remaining proportion of genetic variance in selected individuals and r is the correlation of the expected selective values of male and female parents. The method is also extended to the general case of different numbers of male and female parents. The predictive value of the formulae is tested under a model of truncation selection with the infinitesimal model of gene effects, where C(2) and G are a function of the selection intensity, the heritability and the intraclass correlation of sibs. Under random mating r = α(I) = -1/(N - 1) and α(O) = 0. Under partial full-sib mating with an average proportion β of full-sib matings per generation, r & β and α(O) & α(I) & β/ (4 - 3β). The prediction equation is compared to other approximations based on the long-term contributions of ancestors to descendants. Finally, based on the approach followed, a system of mating (compensatory mating) is proposed to reduce rates of inbreeding without loss of response in selection programs in which selected individuals from the largest families are mated to those from the smallest families.     

Generic Scan Using AFLP Markers as a Means to Assess the Role of Directional Selection in the Divergence of Sympatric Whitefish Ecotypes

DOI:10.1093/molbev/msh153 David Campbell and     

Using a Phylogenetic Framework to Assess the Role of Fruit Size in Food Selection by the Andean Night Monkey (Aotus lemurinus)

International Journal of Primatology - The study of diet and food selection is foundational to understanding how primates interact with their environment. Due to the potential evolutionary...     

Racial Differences in Selection of Ideal Body Size by Adolescent Females

Cultural differences may partially account for the fact that more black women than white women are overweight in the United States. This study measured perceptions of ideal body size among 93 black and 80 white females, 14–17 years old, who were randomly selected from three public high schools in a southeastern state. The subjects' height and weight were measured along with their estimates of their mother's body size, weight control attitudes, and demographic variables . Blacks preferred a significantly larger body sue than whites when asked to select ideal body size (p=0.045). Subjects who estimated their mother's size to be larger, also selected a larger ideal body size (p=.047). Those who perceived themselves as too fat were more likely to skip meals to help control their weight, compared with those who perceived themselves as normal or too thin (p=.003). Approximately 30% of the sample was overweight or obese. There were not significant racial differences in weight or BMI . These results suggest that overweight is more acceptable among black females than among white females and may help explain why more black females are obese .     

Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data

Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the Bayesian Maximum Entropy (BME) algorithm, using soil temperature as auxiliary information, to study the spatial distribution of soil respiration. The BME algorithm used the soft data (auxiliary information) effectively to improve the estimation accuracy of the spatiotemporal distribution of soil respiration. Based on the functional relationship between soil temperature and soil respiration, the BME algorithm satisfactorily integrated soil temperature data into said spatial distribution. As a means of comparison, we also applied the Ordinary Kriging (OK) and Co-Kriging (Co-OK) methods. The results indicated that the root mean squared errors (RMSEs) and absolute values of bias for both Day 1 and Day 2 were the lowest for the BME method, thus demonstrating its higher estimation accuracy. Further, we compared the performance of the BME algorithm coupled with auxiliary information, namely soil temperature data, and the OK method without auxiliary information in the same study area for 9, 21, and 37 sampled points. The results showed that the RMSEs for the BME algorithm (0.972 and 1.193) were less than those for the OK method (1.146 and 1.539) when the number of sampled points was 9 and 37, respectively. This indicates that the former method using auxiliary information could reduce the required number of sampling points for studying spatial distribution of soil respiration. Thus, the BME algorithm, coupled with soil temperature data, can not only improve the accuracy of soil respiration spatial interpolation but can also reduce the number of sampling points.     

应用资源选择函数对褐马鸡冬季夜栖地选择的研究

2006年11月至2007年1月,在陕西黄龙山腹地的北寺山林区,对褐马鸡Crossoptilon mantchuricum冬季夜栖地的选择进行了研究。共记录到34个夜宿地,以夜宿树为中心各做一个10m×10m样方,测定夜栖地海拔、坡向、坡度、坡位、夜栖树高度和胸径、乔木层盖度、乔木数量、灌木层盖度、草本盖度、离最近水源距离、离林间道路的距离、离最近林缘的距离、离最近居民点距离等参数;对照样方采用随机抽样法,在研究区域内设置同样数目的对照样方,测定同样指标。结果表明,褐马鸡冬季夜栖地选择的资源选择函数为:logit(p)=-11.537 2.245×坡度 3.452×乔木盖度 2.001×乔木数量-2.903×与最近居民点的距离。根据拟合出的资源选择函数,褐马鸡冬季对夜栖地的选择概率为P=elogit(p)/(1 elogit(p)),模型的正确预测率可达到93.8%。模型表明,冬季褐马鸡夜栖地的选择概率与坡度、乔木盖度和栖树数量呈正相关,与距居民点距离呈负相关。     

Spatial Clustering of the Curlin Secretion Lipoprotein Requires Curli Fiber Assembly

Gram-negative bacteria assemble functional amyloid surface fibers called curli. CsgB nucleates the major curli subunit protein, CsgA, into a self-propagating amyloid fiber on the cell surface. The CsgG lipoprotein is sufficient for curlin transport across the outer membrane and is hypothesized to be the central molecule of the curli fiber secretion and assembly complex. We tested the hypothesis that the curli secretion protein, CsgG, was restricted to certain areas of the cell to promote the interaction of CsgA and CsgB during curli assembly. Here, electron microscopic analysis of curli-producing strains showed that relatively few cells in the population contacted curli fibers and that curli emanated from spatially discrete points on the cell surface. Microscopic analysis revealed that CsgG was surface exposed and spatially clustered around curli fibers. CsgG localization to the outer membrane and exposure of the surface domain were not dependent on any other csg-encoded protein, but the clustering of CsgG required the csg-encoded proteins CsgE, CsgF, CsgA, and CsgB. CsgG formed stable oligomers in all the csg mutant strains, but these oligomers were distinct from the CsgG complexes assembled in wild-type cells. Finally, we found that efficient fiber assembly was required for the spatial clustering of CsgG. These results suggest a new model where curli fiber formation is spatially coordinated with the CsgG assembly apparatus.     

Spatial Mark-Recapture Method in the Estimation of Crayfish Population Size

The mark-recapture method is considered for estimation of population size of slowly moving animals like crayfish. The Petersen type estimator for closed population is generalized for situations where recaptures are spatially dependent between the capture sites, and its variance approximation is derived using point processes as models for the population. The method of quadratic forms is suggested to be used as variance estimator. Finally, a trapping design is proposed where one trap at recapture is replaced by four adjacent traps. A simulation experiment is performed to explain the robusticity of the new trapping design against movements of animals.     

Women's Preferences for Penis Size: A New Research Method Using Selection among 3D Models

Women’s preferences for penis size may affect men’s comfort with their own bodies and may have implications for sexual health. Studies of women’s penis size preferences typically have relied on their abstract ratings or selecting amongst 2D, flaccid images. This study used haptic stimuli to allow assessment of women’s size recall accuracy for the first time, as well as examine their preferences for erect penis sizes in different relationship contexts. Women (N = 75) selected amongst 33, 3D models. Women recalled model size accurately using this method, although they made more errors with respect to penis length than circumference. Women preferred a penis of slightly larger circumference and length for one-time (length = 6.4 inches/16.3 cm, circumference = 5.0 inches/12.7 cm) versus long-term (length = 6.3 inches/16.0 cm, circumference = 4.8 inches/12.2 cm) sexual partners. These first estimates of erect penis size preferences using 3D models suggest women accurately recall size and prefer penises only slightly larger than average.     

Combining Experiments and Simulations Using the Maximum Entropy Principle

A key component of computational biology is to compare the results of computer modelling with experimental measurements. Despite substantial progress in the models and algorithms used in many areas of computational biology, such comparisons sometimes reveal that the computations are not in quantitative agreement with experimental data. The principle of maximum entropy is a general procedure for constructing probability distributions in the light of new data, making it a natural tool in cases when an initial model provides results that are at odds with experiments. The number of maximum entropy applications in our field has grown steadily in recent years, in areas as diverse as sequence analysis, structural modelling, and neurobiology. In this Perspectives article, we give a broad introduction to the method, in an attempt to encourage its further adoption. The general procedure is explained in the context of a simple example, after which we proceed with a real-world application in the field of molecular simulations, where the maximum entropy procedure has recently provided new insight. Given the limited accuracy of force fields, macromolecular simulations sometimes produce results that are at not in complete and quantitative accordance with experiments. A common solution to this problem is to explicitly ensure agreement between the two by perturbing the potential energy function towards the experimental data. So far, a general consensus for how such perturbations should be implemented has been lacking. Three very recent papers have explored this problem using the maximum entropy approach, providing both new theoretical and practical insights to the problem. We highlight each of these contributions in turn and conclude with a discussion on remaining challenges.     

Size Matters: Metastatic Cluster Size and Stromal Recruitment in the Establishment of Successful Prostate Cancer to Bone Metastases

Prostate cancer (PCa) impacts over 180,000 men every year in the USA alone, with 26,000 patients expected to succumb to the disease (cancer.gov). The primary cause of death is metastasis, with secondary lesions most commonly occurring in the skeleton. Prostate cancer to bone metastasis is an important, yet poorly understood, process that is difficult to explore with experimental techniques alone. To this end we have utilized a hybrid (discrete–continuum) cellular automaton model of normal bone matrix homeostasis that allowed us to investigate how metastatic PCa can disrupt the bone microenvironment. Our previously published results showed that PCa cells can recruit mesenchymal stem cells (MSCs) that give rise to bone-building osteoblasts. MSCs are also thought to be complicit in the establishment of successful bone metastases (Lu, in Mol Cancer Res 4(4):221–233, 2006). Here we have explored the aspects of early metastatic colonization and shown that the size of PCa clusters needs to be within a specific range to become successfully established: sufficiently large to maximize success, but not too large to risk failure through competition among cancer and stromal cells for scarce resources. Furthermore, we show that MSC recruitment can promote the establishment of a metastasis and compensate for relatively low numbers of PCa cells seeding the bone microenvironment. Combined, our results highlight the utility of biologically driven computational models that capture the complex and dynamic dialogue between cells during the initiation of active metastases.     

Spatial and Temporal Clustering of Chikungunya Virus Transmission in Dominica

Using geo-referenced case data, we present spatial and spatio-temporal cluster analyses of the early spread of the 2013–2015 chikungunya virus (CHIKV) in Dominica, an island in the Caribbean. Spatial coordinates of the locations of the first 417 reported cases observed between December 15^th, 2013 and March 11^th, 2014, were captured using the Global Positioning System (GPS). We observed a preponderance of female cases, which has been reported for CHIKV outbreaks in other regions. We also noted statistically significant spatial and spatio-temporal clusters in highly populated areas and observed major clusters prior to implementation of intensive vector control programs suggesting early vector control measures, and education had an impact on the spread of the CHIKV epidemic in Dominica. A dynamical identification of clusters can lead to local assessment of risk and provide opportunities for targeted control efforts for nations experiencing CHIKV outbreaks.     

Spatial Autocorrelation Analysis of Migration and Selection

We test various assumptions necessary for the interpretation of spatial autocorrelation analysis of gene frequency surfaces, using simulations of Wright's isolation-by-distance model with migration or selection superimposed. Increasing neighborhood size enhances spatial autocorrelation, which is reduced again for the largest neighborhood sizes. Spatial correlograms are independent of the mean gene frequency of the surface. Migration affects surfaces and correlograms when immigrant gene frequency differentials are substantial. Multiple directions of migration are reflected in the correlograms. Selection gradients yield clinal correlograms; other selection patterns are less clearly reflected in their correlograms. Sequential migration from different directions and at different gene frequencies can be disaggregated into component migration vectors by means of principal components analysis. This encourages analysis by such methods of gene frequency surfaces in nature. The empirical results of these findings lend support to the inference structure developed earlier for spatial autocorrelation analysis.     

Spatial Autocorrelation of Genotypes under Directional Selection

The spatial distributions of genetic variation under selection-mutation equilibrium within populations that have limited dispersal are investigated. The results show that directional selection with moderate strength rapidly reduces the amount of genetic structure and spatial autocorrelations far below that predicted for selectively neutral loci. For the latter, homozygotes are spatially clustered into separate areas or patches, each consisting of several hundred homozygotes. When selection is added the patches of the deleterious homozygotes are much smaller, in the range of 25 to 50 individuals. Selection also reduces temporal correlations. Also investigated are the effects of random replacement processes, such as mutation, immigration, and long-distance migration, on spatial and temporal correlations. The detection of natural selection through spatial pattern analysis is discussed, and applied to data from populations of the morning glory, Ipomoea purpurea.     

Sensing Size through Clustering in Non-Equilibrium Membranes and the Control of Membrane-Bound Enzymatic Reactions

The formation of dynamical clusters of proteins is ubiquitous in cellular membranes and is in part regulated by the recycling of membrane components. We show, using stochastic simulations and analytic modeling, that the out-of-equilibrium cluster size distribution of membrane components undergoing continuous recycling is strongly influenced by lateral confinement. This result has significant implications for the clustering of plasma membrane proteins whose mobility is hindered by cytoskeletal “corrals” and for protein clustering in cellular organelles of limited size that generically support material fluxes. We show how the confinement size can be sensed through its effect on the size distribution of clusters of membrane heterogeneities and propose that this could be regulated to control the efficiency of membrane-bound reactions. To illustrate this, we study a chain of enzymatic reactions sensitive to membrane protein clustering. The reaction efficiency is found to be a non-monotonic function of the system size, and can be optimal for sizes comparable to those of cellular organelles.