The use and misuse of regression models in landscape genetic analyses

The field of landscape genetics has been rapidly evolving, adopting and adapting analytical frameworks to address research questions. Current studies are increasingly using regression‐based frameworks to infer the individual contributions of landscape and habitat variables on genetic differentiation. This paper outlines appropriate and inappropriate uses of multiple regression for these purposes, and demonstrates through simulation the limitations of different analytical frameworks for making correct inference. Of particular concern are recent studies seeking to explain genetic differences by fitting regression models with effective distance variables calculated independently on separate landscape resistance surfaces. When moving across the landscape, organisms cannot respond independently and uniquely to habitat and landscape features. Analyses seeking to understand how landscape features affect gene flow should model a single conductance or resistance surface as a parameterized function of relevant spatial covariates, and estimate the values of these parameters by linking a single set of resistance distances to observed genetic dissimilarity via a loss function. While this loss function may involve a regression‐like step, the associated nuisance parameters are not interpretable in terms of organismal movement and should not be conflated with what is actually of interest: the mapping between spatial covariates and conductance/resistance. The growth and evolution of landscape genetics as a field has been rapid and exciting. It is the goal of this paper to highlight past missteps and demonstrate limitations of current approaches to ensure that future use of regression models will appropriately consider the process being modeled, which will provide clarity to model interpretation.     

基于增强回归树与区域增温敏感性指数的城市升温效应空间分异

热岛效应已成为城市化进程中备受关注的城市生态环境问题。有关城市热岛效应的研究对区域在地表升温过程中的空间分异关注尚不足。通过设计区域增温敏感性指数,借助增强回归树（boosted regression tree,BRT）机器学习算法,量化城市不同区域在地表升温过程中的敏感性差异。结果表明：（1）上海市各辖区增温敏感性从高至低依次是：黄浦区、杨浦区、虹口区、静安区、普陀区、徐汇区、长宁区、宝山区、闵行区、浦东新区、嘉定区、奉贤区、松江区、青浦区、金山区、崇明区;（2）区域增温敏感性在不同的温度梯度下具有明显差异,在高温梯度下区域间指数值的差异最大;（3）地表覆被的增温敏感性存在明显的区域分异特性;（4）基于BRT的增温敏感性指数具有较好的指示意义和较高的灵敏度。在城市热环境持续恶化背景下,探讨城市异质空间中地表温度变化的敏感性可为城市热环境调控提供科学依据。     

中老铁路经济廊带生态质量及其与人类活动的关系

区域生态质量很大程度上受人类活动强度影响,制约着区域经济可持续发展。以中老铁路经济廊带为对象,重点研究区内人类活动强度对区域生态环境的影响。选取1999、2009、2019年遥感影像计算遥感生态指数(RSEI),采用空间自相关及局域G统计量探测研究区生态质量的时空演变规律,并结合同期人口密度构建地理加权回归模型,定量分析区内人类活动强度引起的生态效应。研究表明: 1999—2019年,区内生态质量经历了先升后降的变化,RSEI均值由1999年的0.645升为2009年的0.738,随后又降为2019年的0.721,中部地区生态质量波动较大;基于地理加权回归模型(GWR)拟合人口密度与生态质量的效果明显好于最小二乘法,基于GWR的不同时期R²均高于0.7且拟合效果稳定,2019年拟合度最好(R²为0.785),1999、2009年R²分别为0.726、0.754;中老铁路沿线南部万象一带的生态质量对人类活动较敏感,以中度敏感区为主。对高、中、低度敏感区而言,人口密度每增长10、100、1000倍将相应导致RSEI均值降低0.2、0.4、0.6。经济廊带发展会导致人口密度增加,在规划布局过程中应控制人类活动,防止潜在敏感区及现有敏感区生态质量进一步恶化。     

黄丘区特色治理开发小流域土壤侵蚀变化对景观格局演变的响应

研究土壤侵蚀与景观格局变化的关系对小流域的治理开发具有重要的指导意义。本研究以实施退耕还林草、生态农业、生态旅游及科技示范的黄土高原安塞南沟特色治理小流域为研究对象,基于GIS平台和通用土壤流失方程,分析小流域1981—2018年景观格局和土壤侵蚀量的时空演化特征,并利用主成分回归法,从斑块类型水平和景观水平两个尺度分析土壤侵蚀模数与3类9个景观格局指标的关系。结果表明: 研究期间,在5种景观类型中,耕地和林地面积的时空变化主导了南沟小流域景观格局的演化,并且影响整个小流域的聚集分散程度;南沟小流域的土壤侵蚀量逐年减少,1981—2018年土壤侵蚀面积减少29.7%,侵蚀模数减少61.2%,且有73.4%的区域土壤侵蚀强度减轻;耕地和林地面积的变化决定了整个小流域土壤侵蚀模数的变化,其景观格局指数的变化方向与该景观类型土壤侵蚀的变化方向一致;退耕还林草工程是流域景观格局变化、土壤侵蚀减轻的主要原因,特色开发治理可以减弱局部地区土壤侵蚀强度。景观类型的合理化配置能有效地防治小流域土壤侵蚀,将其与特色治理开发相结合有助于实现小流域可持续高质量发展。     

Epidemiological Characteristics of Influenza A and B in Macau, 2010–2018

Virologica Sinica - Influenza is one of the major respiratory diseases in humans. Macau is a tourist city with high density of population and special population mobility. The study on the...     

医学生学习激情现状及影响因素的研究

目的:测量医学生学习激情现状,探索相关人口学变量差异及影响因素作用机制。方法:通过网络问卷对1793名在校医学生进行问卷调查,回收有效问卷1218份,应用SPSS22.0软件对数据进行统计处理。结果:测量对象的学习激情处于中等偏上水平(4.37±0.91);学习激情平均得分在性别(F=9.097,P<0.05)、生源地(F=14.850,P<0.05)、独生子女情况(F=5.470,P<0.05)方面的差异有统计学意义;成绩水平(β=0.094,P<0.01)、发展规划(β=0.105,P<0.01)、生活满意度(β=0.213,P<0.01)和活力(β=0.253,P<0.01)对医学生学习激情的影响有统计学意义。结论:医学生学习激情水平在性别、生源地、独生与否方面存在显著差异;成绩水平、发展规划、生活满意度、活力是影响医学生学习激情的因素。     

Oxaliplatin induces immunogenic cells death and enhances therapeutic efficacy of checkpoint inhibitor in a model of murine lung carcinoma

Abstract

Background: Platinum compounds are commonly used for lung cancer treatment. However, the severe side effects and relatively poor prognosis limit their therapeutic effect. Therefore, developing novel platinum derivative and treatment strategy are critical for current lung cancer therapy.

Methods: Flow cytometry, HMGB1 and ATP release, and immunoblotting were performed to evaluate the Oxaliplatin-induced immunogenic cell death (ICD) in two lung carcinoma cells. Vaccination approach and subcutaneous tumor models were created to analyze the tumor regression effect of Oxaliplatin. PD-L1 mRNA and protein levels were detected in LLC (Lewis lung carcinoma). Enhanced therapeutic efficacy of LLC was assessed by co-administration Oxaliplatin and aPD-L1 in murine lung tumor model.

Results: Oxaliplatin induced robust ICD in LLC cells, activated dendritic cells (DCs, CD80⁺CD86⁺) and enhanced cytotoxic T cells (CD8⁺) in LLC tumor tissues, which resulted in tumor regression. Co-administration of Oxaliplatin and checkpoint inhibitor, aPD-L1, could enhance the therapeutic efficacy of LLC in murine lung carcinoma.

Conclusion: This study reveals Oxaliplatin can induce robust ICD in tumor tissues and suppress tumor growth by activating DCs and enhancing T-cell infiltration. Notably, the Oxaliplatin-induced ICD provides an immunogenic microenvironment, which enhances the checkpoint inhibitor therapeutic efficacy of LLC.     

The past,present and future of thermophilous Cyperus polystachyos Rottb. (Cyperaceae) on the island of Ischia (southern Italy)

Cyperus polystachyos is a hygrophilous, thermophilous and heliophilous plant with a punctiform distribution in southern Italy, where it is almost exclusively found on Ischia, an island in the Bay of Naples characterized by widespread volcanic hydrothermal activity. This species is a native of tropical and subtropical areas and there is evidence for ancient isolation events in the creation of its current distribution pattern. We have studied the historical literature available for this plant since 1800 and collected temporal and spatial presence data of this species in order to develop a habitat suitability map based on a GIS approach and using a multiple linear regression model. Moreover, we have used univariate and multivariate statistical analysis. The results show the importance of the environmental mosaic around fumaroles to preserve the species; urbanization and geothermal energy use of fumaroles in the past and the combination of abandonment of the typical agricultural system and the natural occurrence of reforestation in the present are the main causes of the decline in the number of populations.     

Mantel test in population genetics

The comparison of genetic divergence or genetic distances, estimated by pairwise F_ST and related statistics, with geographical distances by Mantel test is one of the most popular approaches to evaluate spatial processes driving population structure. There have been, however, recent criticisms and discussions on the statistical performance of the Mantel test. Simultaneously, alternative frameworks for data analyses are being proposed. Here, we review the Mantel test and its variations, including Mantel correlograms and partial correlations and regressions. For illustrative purposes, we studied spatial genetic divergence among 25 populations of Dipteryx alata (“Baru”), a tree species endemic to the Cerrado, the Brazilian savannas, based on 8 microsatellite loci. We also applied alternative methods to analyze spatial patterns in this dataset, especially a multivariate generalization of Spatial Eigenfunction Analysis based on redundancy analysis. The different approaches resulted in similar estimates of the magnitude of spatial structure in the genetic data. Furthermore, the results were expected based on previous knowledge of the ecological and evolutionary processes underlying genetic variation in this species. Our review shows that a careful application and interpretation of Mantel tests, especially Mantel correlograms, can overcome some potential statistical problems and provide a simple and useful tool for multivariate analysis of spatial patterns of genetic divergence.