中国特有植物雪落樱桃潜在分布及其生态特征

为明确中国特有植物雪落樱桃(Cerasus xueluoensis)的潜在分布与居群生态特征,利用DIVA-GIS软件及其耦合的BIOCLIM模型,首次绘制了雪落樱桃适生区分布模拟图,并对影响其分布的主导气候因子进行了定性定量分析。结果表明,雪落樱桃当前潜在适生区主要分布在亚热带长江流域1 200 m以上高海拔山区,其中渝-鄂-湘三省交界的大巴山-巫山山脉可视为现代核心分布区,湘黔交界及湘南的南岭山脉可视为雪落樱桃潜在分布的南界,陕-豫-鄂交界山区的秦岭南麓可能是其潜在分布的北界。主成分分析(PCA)筛选的主导气候因子及其贡献率依次为:年降水量(bio12)最冷季降水量(bio19)最暖季降水量(bio18)最湿季降水量(bio16),累计频率曲线进一步确定其适宜范围分别为:993.00～1 870.22、500.00～680.00、430.00～669.16和500.00～680.00mm,表明降水是影响雪落樱桃当下分布格局的主导气候限制因子。Pearson相关性分析表明,雪落樱桃分布格局在区域尺度上受海拔、经、纬度影响;最小树分析和聚类分析表明,雪落樱桃7个野生居群可划分为中西部与东部两大分支;受试者工作特征曲线(ROC) AUC值达到0.751,满足模型预测精度的基本要求。这些有助于为雪落樱桃制定科学合理的资源保护与科学引种规划。     

Development of a novel,high resolution melting analysis based genotyping method for Cryptosporidium parvum

This study employed the post-real-time PCR application, high resolution melting (HRM) analysis, in order to differentiate between characterised clinical and reference Cryptosporidium parvum samples obtained from Cork University Hospital (Cork, Ireland) and the Cryptosporidium Reference Unit (Swansea, Wales). A sample set composed of 18 distinct C. parvum gp60-subtypes of the IIa gp60-subtype family (an allele family accounting for over 80% of all cryptosporidiosis cases in Ireland) was employed. HRM analysis-based interrogation of the gp60, MM5 and MS9-Mallon tandem repeat loci was found to completely differentiate between 10 of the 18 studied gp60-subtypes. The remaining eight gp60-subtypes were differentiated into three distinct groupings, with the designations within these groupings resolved to two to three potential gp60-subtypes.The current study aimed to develop a novel, reproducible, real-time PCR based multi-locus genotyping method to distinguish between C. parvum gp60-subtypes. These preliminary results support the further expansion of the multi-locus panel in order to increase the discriminatory capabilities of this novel method.     

气候和土地利用与空间结构在影响大熊猫同域分布大中型哺乳动物物种丰富度中的相对作用

气候因子和土地利用因子是影响生物多样性分布格局的两个主要驱动因素。然而,当前关于气候因子和土地利用因子对生物多样性影响的研究主要集中在物种层面上,在群落水平上对生物多样性的影响依然知之甚少。本研究以大熊猫同域分布大中型哺乳动物为研究对象,结合物种丰富度数据、气候数据、土地利用数据以及经纬度数据,构建基于不同变量组合的多元线性模型,并通过模型拟合优度比较和方差分解等方法,探讨气候因子、土地利用因子和空间结构在影响大熊猫同域分布大中型哺乳动物物种丰富度中的相对作用。结果表明：（1）四川省大熊猫分布的五大山系内的大中型哺乳动物在属数和物种数方面差异较大。其中岷山山系的属数和物种数最高,分别为25属和28种,凉山山系的属数和物种数最低,分别为19属和20种,五大山系内排名前五的优势种分别为大熊猫、羚牛、野猪、中华斑羚、中华鬣羚;（2）大熊猫同域分布大中型哺乳动物物种丰富度在空间分布上差异较大。所有10 km×10 km栅格内的物种数在1~14之间,平均值为6.199±3.475;（3）完全模型（包含所有气候变量、土地利用变量和空间结构变量的模型,CLS）的拟合优度要好于其它6类模型,且包含土地利用变量模型的拟合优度要好于没有包含的模型;（4）气候变量、土地利用变量和空间结构变量共同解释了大熊猫同域分布大中型哺乳动物物种丰富度43.0%的空间变异,其中,土地利用变量对物种丰富度的解释率最高,单独解释率为23.2%,气候变量和空间结构变量的解释率则相对较低,单独解释率分别为6.3%和9.3%。这些研究结果说明土地利用因素是影响大熊猫同域分布大中型哺乳动物物种丰富度最为关键的驱动因素。因此,提高森林覆盖率,减少人为干扰和使用,是实现对大熊猫同域分布哺乳动物综合保护的关键。     

Repeated measures random forests (RMRF): Identifying factors associated with nocturnal hypoglycemia

Nocturnal hypoglycemia is a common phenomenon among patients with diabetes and can lead to a broad range of adverse events and complications. Identifying factors associated with hypoglycemia can improve glucose control and patient care. We propose a repeated measures random forest (RMRF) algorithm that can handle nonlinear relationships and interactions and the correlated responses from patients evaluated over several nights. Simulation results show that our proposed algorithm captures the informative variable more often than naïvely assuming independence. RMRF also outperforms standard random forest and extremely randomized trees algorithms. We demonstrate scenarios where RMRF attains greater prediction accuracy than generalized linear models. We apply the RMRF algorithm to analyze a diabetes study with 2524 nights from 127 patients with type 1 diabetes. We find that nocturnal hypoglycemia is associated with HbA1c, bedtime blood glucose (BG), insulin on board, time system activated, exercise intensity, and daytime hypoglycemia. The RMRF can accurately classify nights at high risk of nocturnal hypoglycemia.     

Single-chain antibody fragments: Purification methodologies

At present, single-chain variable fragments (scFv) of antibodies are considered one of the most important tools in human therapies. Wide applications of antibodies are being exploited in different medical, pharmaceutical and research areas. These molecules maintain the same binding functionality that full length antibodies but possess several advantageous features as quickness to penetrate the tissues, easy manipulation, fast elimination of their immunocomplex and the possibility of being produced in simple expression systems like bacteria and yeast. The increasing demand in antibody based methodologies is driving advances in the production and purification of genetically engineered antibodies and antibody fragments. While advances in expression systems allow the production of high titers of antibodies, there exist some limits imposed by the downstream methodologies which are not efficient enough to ensure their industrialization.The main aim of this review is to highlight the principal characteristics of single-chain variable fragments of antibodies addressing advances and perspectives on scFv purification.     

Selection of a human butyrylcholinesterase-like antibody single-chain variable fragment resistant to AChE inhibitors from a phage library expressed in E. coli

Organophosphates are potent poisoning agents that cause severe cholinergic toxicity. Current treatment has been reported to be unsatisfactory and novel antidotes are needed. In this study, we used a single-chain variable fragment (scFv) library to select a recombinant antibody fragment (WZ1–14.2.1) with butyrylcholinesterase-like catalytic activity by using an innovative method integrating genetic selection and the bait-and-switch strategy. Ellman assay demonstrated that WZ1–14.2.1 has Michaelis-Menten kinetics in the hydrolysis of all the three substrates used, acetylthiocholine, propionylthiocholine and butyrylthiocholine. Notably, the catalytic activity was resistant to the following acetylcholinesterase inhibitors: neostigmine, iso-OMPA, chlorpyrifos oxon, dichlorvos, and paraoxon ethyl. Otherwise, the enzymatic activity of WZ1–14.2.1 was inhibited by the selective butyrylcholinesterase inhibitor, ethopropazine, and by the Ser-blocking agent phenylmethanesuphonyl fluoride. A hypothetical 3D structure of the WZ1–14.2.1 catalytic site, compatible with functional results, is proposed on the basis of a molecular modeling analysis.     

Approximation of bias and mean-squared error in two-sample Mendelian randomization analyses

Mendelian randomization (MR) is a type of instrumental variable (IV) analysis that uses genetic variants as IVs for a risk factor to study its causal effect on an outcome. Extensive investigations on the performance of IV analysis procedures, such as the one based on the two-stage least squares (2SLS) procedure, have been conducted under the one-sample scenario, where measures on IVs, the risk factor, and the outcome are assumed to be available for each study participant. Recent MR analysis usually is performed with data from two independent or partially overlapping genetic association studies (two-sample setting), with one providing information on the association between the IVs and the outcome, and the other on the association between the IVs and the risk factor. We investigate the performance of 2SLS in the two-sample–based MR when the IVs are weakly associated with the risk factor. We derive closed form formulas for the bias and mean squared error of the 2SLS estimate and verify them with numeric simulations under realistic circumstances. Using these analytic formulas, we can study the pros and cons of conducting MR analysis under one-sample and two-sample settings and assess the impact of having overlapping samples. We also propose and validate a bias-corrected estimator for the causal effect.     

Variable selection in joint frailty models of recurrent and terminal events

Recurrent event data are commonly encountered in biomedical studies. In many situations, they are subject to an informative terminal event, for example, death. Joint modeling of recurrent and terminal events has attracted substantial recent research interests. On the other hand, there may exist a large number of covariates in such data. How to conduct variable selection for joint frailty proportional hazards models has become a challenge in practical data analysis. We tackle this issue on the basis of the “minimum approximated information criterion” method. The proposed method can be conveniently implemented in SAS Proc NLMIXED for commonly used frailty distributions. Its finite-sample behavior is evaluated through simulation studies. We apply the proposed method to model recurrent opportunistic diseases in the presence of death in an AIDS study.     

Transposable elements and human cancer: A causal relationship?

Transposable elements are present in almost all genomes including that of humans. These mobile DNA sequences are capable of invading genomes and their impact on genome evolution is substantial as they contribute to the genetic diversity of organisms. The mobility of transposable elements can cause deleterious mutations, gene disruption and chromosome rearrangements that may lead to several pathologies including cancer. This mini-review aims to give a brief overview of the relationship that transposons and retrotransposons may have in the genetic cause of human cancer onset, or conversely creating protection against cancer. Finally, the cause of TE mobility may also be the cancer cell environment itself.