Formulation Optimization of an Indomethacin-Containing Photocrosslinked Polyacrylic Acid Hydrogel as an Anti-inflammatory Patch

Photocrosslinked polyacrylic acid hydrogel, made from polyacrylic acid (PAA) modified with 2-hydroxyethyl methacrylate (HEMA), is a promising candidate adhesive for dermatological patches. In this study, we investigated the further availability of hydrogel as an adhesive for dermatological patches using a hydrogel containing indomethacin (IDM) as a model anti-inflammatory patch. From an orthogonal experimental study, we clarified the relationships between formulation factors and characteristics of model formulation. Formulations with a lower degree of swelling were prepared by increasing the degree of HEMA modification and the addition of Tween 80. Apparent permeation rate was increased by addition of l-menthol and Tween 80. A tendency for higher HEMA modification to be accompanied by the prolongation of the lag time of IDM was observed. To obtain an applicable anti-inflammatory patch, we conducted a formulation optimization study using a novel optimization method, a response-surface method incorporating multivariate spline interpolation (RSM-S). Consequently, a highly functional anti-inflammatory patch in terms of its adhesive properties and bioavailability was successfully obtained. Since a wide range of functions can be fully controlled by manipulating the formulation factors, photocrosslinked polyacrylic acid hydrogel is an attractive candidate adhesive for dermatological patches.     

Reducing variability of crossvalidation for smoothing-parameter choice

One of the attractions of crossvalidation, as a tool for smoothing-parameterchoice, is its applicability to a wide variety of estimatortypes and contexts. However, its detractors comment adverselyon the relatively high variance of crossvalidatory smoothingparameters, noting that this compromises the performance ofthe estimators in which those parameters are used. We show thatthe variability can be reduced simply, significantly and reliablyby employing bootstrap aggregation or bagging. We establishthat in theory, when bagging is implemented using an adaptivelychosen resample size, the variability of crossvalidation canbe reduced by an order of magnitude. However, it is arguablymore attractive to use a simpler approach, based for exampleon half-sample bagging, which can reduce variability by approximately50%.     

The effects of interpolation error and location quality on animal track reconstruction

The Global Positioning System (GPS) gives precise estimates of location. However, the investigation of animal movement and behavior often requires interpolation to examine events between such fixes. We obtained 6,288 GPS locations from an electronic tag deployed for 170 d on an adult male gray seal ( Halichoerus grypus ) that ranged freely off the east coast of Scotland, and interpolated between subsamples of these data to investigate the growth of uncertainty within the intervals between observations. Average uncertainty over the path increased linearly as the interval between interpolating locations increased, reaching 12 km in longitude and 6 km in latitude at 2-d separation. The decrease in precision caused by duty-cycling, only collecting data in part of the day, was demonstrated. Adding noise to the GPS locations to simulate data from the ARGOS satellite system had little effect on the total errors for observations separated by more than 12 h. While the rate of growth in interpolation error is likely to vary between species, these results suggest that frequent, and preferably evenly spaced, location fixes are required to take full advantage of the precision of GPS data in the reconstruction of animal tracks.     

Advances in Geometric Morphometrics

Geometric morphometrics is the statistical analysis of form based on Cartesian landmark coordinates. After separating shape from overall size, position, and orientation of the landmark configurations, the resulting Procrustes shape coordinates can be used for statistical analysis. Kendall shape space, the mathematical space induced by the shape coordinates, is a metric space that can be approximated locally by a Euclidean tangent space. Thus, notions of distance (similarity) between shapes or of the length and direction of developmental and evolutionary trajectories can be meaningfully assessed in this space. Results of statistical techniques that preserve these convenient properties—such as principal component analysis, multivariate regression, or partial least squares analysis—can be visualized as actual shapes or shape deformations. The Procrustes distance between a shape and its relabeled reflection is a measure of bilateral asymmetry. Shape space can be extended to form space by augmenting the shape coordinates with the natural logarithm of Centroid Size, a measure of size in geometric morphometrics that is uncorrelated with shape for small isotropic landmark variation. The thin-plate spline interpolation function is the standard tool to compute deformation grids and 3D visualizations. It is also central to the estimation of missing landmarks and to the semilandmark algorithm, which permits to include outlines and surfaces in geometric morphometric analysis. The powerful visualization tools of geometric morphometrics and the typically large amount of shape variables give rise to a specific exploratory style of analysis, allowing the identification and quantification of previously unknown shape features.     

全球陆地保护地60年增长情况分析和趋势预测

保护地建设已成为全球生物多样性保护的第一道防线。掌握其在不同尺度上的发展状况和变化趋势对保护地规划和建设有重要意义。针对已有研究在时间跨度、空间尺度以及结果对比方面的不足, 本文基于世界保护地数据库(World Database of Protected Areas, http://www.protectedplanet.net), 对全球、洲际、地区及国家尺度1950-2013年陆地保护地的增长情况进行描述和短期预测。结果发现: (1)全球保护地增长速率不断加快, 特别是在20世纪90年代以后。(2)洲际和地区保护地发展大致呈现3种增长趋势: 在美洲及大洋洲, 多数地区的保护地增长速率一直在加快; 在亚洲和欧洲, 多数地区的发展高峰出现在20世纪80、90年代; 在非洲, 多数地区的发展高峰为20世纪70年代及21世纪前10年。(3)各国保护地建设存在不平衡性, 仍有近一半国家的陆地保护地比例小于10%, 但这种差距随时间的推移有缩小的趋势。(4)绝大部分保护地增速均匀性低的国家分布在非洲。(5)虽然全球的《爱知生物多样性目标》在2020年预计不能完成, 但包括中国在内的22个国家有望如期达到目标。本文结果为未来保护地规划和建设工作的开展提供了参考依据。     

Bayesian semiparametric intensity estimation for inhomogeneous spatial point processes

In this work we propose a fully Bayesian semiparametric method to estimate the intensity of an inhomogeneous spatial point process. The basic idea is to first convert intensity estimation into a Poisson regression setting via binning data points on a regular grid, and then model the log intensity semiparametrically using an adaptive version of Gaussian Markov random fields to smooth the corresponding counts. The inference is carried by an efficient Markov chain Monte Carlo simulation algorithm. Compared to existing methods for intensity estimation, for example, parametric modeling and kernel smoothing, the proposed estimator not only provides inference regarding the dependence of the intensity function on possible covariates, but also uses information from the data to adaptively determine the amount of smoothing at the local level. The effectiveness of using our method is demonstrated through simulation studies and an application to a rainforest dataset.     

A new semiparametric estimation method for accelerated hazard model

The accelerated hazard model has been proposed for more than a decade. However, its application is still very limited, partly due to the complexity of the existing semiparametric estimation method. We propose a new semiparametric estimation method based on a kernel-smoothed approximation to the limit of a profile likelihood function of the model. The method leads to smooth estimating equations and is easy to use. The estimates from the method are proved to be consistent and asymptotically normal. Our numerical study shows that the new method is more efficient than the existing method. The proposed method is employed to reanalyze the data from a brain tumor treatment study.     

Smoothing spline ANOVA frailty model for recurrent event data

Gap time hazard estimation is of particular interest in recurrent event data. This article proposes a fully nonparametric approach for estimating the gap time hazard. Smoothing spline analysis of variance (ANOVA) decompositions are used to model the log gap time hazard as a joint function of gap time and covariates, and general frailty is introduced to account for between-subject heterogeneity and within-subject correlation. We estimate the nonparametric gap time hazard function and parameters in the frailty distribution using a combination of the Newton-Raphson procedure, the stochastic approximation algorithm (SAA), and the Markov chain Monte Carlo (MCMC) method. The convergence of the algorithm is guaranteed by decreasing the step size of parameter update and/or increasing the MCMC sample size along iterations. Model selection procedure is also developed to identify negligible components in a functional ANOVA decomposition of the log gap time hazard. We evaluate the proposed methods with simulation studies and illustrate its use through the analysis of bladder tumor data.     

采用三次样条拟合胎儿体格发育指标百分位数参考值

目的:生长发育评价标准的最佳形式是年龄别百分位数,然而,目前我国缺乏胎儿的孕周别体格发育指标百分位数评价标准,影响了胎儿宫内生长发育水平的准确评价,本研究拟建立陕西省正常单胎妊娠孕妇胎儿体格发育指标百分位数参考标准。方法:以陕西省西安、汉中、延安5所大型综合医院超声科或妇产科超声室为数据采集点,选择2010-01-01到2010-12-31间进行常规孕期检查的正常单胎妊娠胎儿的超声测量数据,随机抽取一次测量结果,共收集到6832个单胎正常妊娠胎儿的超声测量数据。采用三次样条法对陕西省孕16-41周正常单胎妊娠胎儿的双顶径、腹围、股骨长百分位数进行拟合。结果:三次样条拟合胎儿的双顶径、腹围、股骨长百分位数,各百分位数的决定系数均在0.95以上,均方差均在各指标重复测量的容许误差内,拟合结果满意。计算出了胎儿的孕周别双顶径、腹围、股骨长的P3、P10、P25、P50、P75、P90、P97百分位数。结论:三次样条兼顾了曲线拟合中的拟合优度和光滑度,能更好的实现曲线拟合的目的。所建立的孕周别胎儿体格发育指标百分位数符合胎儿宫内生长发育规律,为胎儿宫内生长发育的准确评价提供了科学、准确的评价工具,可用于产科临床和研究工作中。     

使用线性微分方程构建初步的乳腺癌转移相关基因网络模型

随着基因芯片的技术的推广,越来越多的表达数据需要被处理和分析．利用这些表达数据提取基因调控矩阵从而构建基因网络是一个重要的问题．通过线性微分方程模型可以初步构建基因网络,了解网络结构,提取最显著的信息．然而由于分子生物学的条件限制或者数据来源的限制,导致实验数据不充分,使方程组无解．本文使用三次样条方法,对26例临床、病理资料完备的具有淋巴结转移的乳腺癌基因表达数据进行插值处理,使表达数据满秩,从而使用最小二乘法解出加权矩阵,构建初步的表达基因调控网络．通过对构建的基因网络的初步分析表明:乳腺癌转移的形成是由多基因异常引起多条传导通路异常,致使细胞恶性转化的结果,这与生物学上公认的看法是相一致的．因此,利用此线性模型方法对基因表达谱进行分析兵有一定可行性,在认识乳腺癌转移机制,乳腺癌诊断和治疗方面具有一定的理论和应用价值．