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941.
网络分析(network analysis)可以同时分析群落中的物种多样性和种间关系, 为了解生态群落的稳定性机制提供了新的分析思路和方法。本研究从西双版纳国家级自然保护区的纳板河、勐仑和勐腊(补蚌)三个地点采集了树栖性蚂蚁及树木的种类和数量数据, 对蚂蚁-树组成的二分网络进行了分析, 探讨了3个采样点物种的多样性、网络指标以及群落指标之间的关系。我们采用零模型的方法比较了3个样点的标准化网络参数差异。结果表明: 蚂蚁和树木的物种数以及树的异质性指数(Shannon-Wiener多样性指数、Simpson多样性指数)都呈现出勐仑 > 纳板河 > 补蚌的趋势。树木-蚂蚁的灭绝曲线系数大小关系同样为勐仑 > 纳板河 > 补蚌, 灭绝曲线与树的物种数及异质性指数大小趋势一致, 而与蚂蚁的异质性指数并不吻合。根据Z值的绝对值来看, 网络参数(加权嵌套性、平均连接数、特化水平、模块性、连接度)与群落参数(灭绝曲线系数、生态位重叠)的大小趋势相同, 表现出勐仑 > 纳板河 > 补蚌的趋势。综上所述, 蚂蚁-树互作网络的稳定性(灭绝曲线系数)主要由树的数量和异质性指数决定。网络的加权嵌套性和网络中节点的平均连接数也能促进群落的稳定性。而在一个特化的(数值越大表示专性互作越多)和模块化(具有较多密切互作的节点单元)的网络中, 当低营养级物种灭绝时高营养级物种数量将迅速减少。 相似文献
942.
943.
Huiting Wu Yang Zhang Thomas L. Stubbs Yuanlin Sun 《Lethaia: An International Journal of Palaeontology and Stratigraphy》2020,53(4):515-532
Diversity indices (dominance and evenness) and ecological spatial structure (lifestyles and relative abundances) are important features of Changhsingian brachiopod communities prior to the end-Permian mass extinction (EPME) and could predict temporal and spatial extinction patterns during the EPME. In South China, Changhsingian brachiopod communities show higher diversity than other contemporaneous brachiopod communities in the world and have been reported from a variety of sedimentary environments. In this paper, brachiopods from 18 sections in South China were selected to divide communities and compare their ecological structure. Based on the results of network analysis, cluster analysis and quantitative data from the selected sections, we show that Changhsingian brachiopod communities in South China can be categorized into three assemblages along a marine depth gradient: the Neochonetes–Fusichonetes–Paryphella Assemblage from the shallow-water clastic-rock facies, Spinomarginifera–Peltichia–Oldhamina Assemblage from the shallow-water carbonate platform facies and Fusichonetes–Crurithyris Assemblage from the deep-water siliciclastic intracontinental basin facies. Compared with communities from carbonate platform facies, the communities from siliciclastic facies were characterized by high dominance, low evenness and low lifestyle diversity, which might be important biotic factors leading to earlier extinctions. After the extinction began in all environments, the whole earliest Triassic brachiopod community was first dominated by Fusichonetes and then by Crurithyris. These patterns of domination and replacement could be explained by morphological and ecological advantages. The domination of these two genera, which were already adapted to the oxygen and food-limited deep-water habitat, indicates that the cooler deep-water environment might have been a relatively less stressed habitat after the beginning of the EPME. This suggests that global warming might be the main trigger among the previously proposed synergistic environmental stresses, while anoxia might not, at least for the beginning of EPME. 相似文献
944.
Adriana R. Aguilar-Melo Sophie Calmé Braulio Pinacho-Guendulain Sandra E. Smith-Aguilar Gabriel Ramos-Fernández 《American journal of primatology》2020,82(1):e23077
Some social species exhibit high levels of fission–fusion dynamics (FFD) that improve foraging efficiency. In this study, we shed light on the way that FFD allows animal groups to cope with fluctuations in fruit availability. We explore the relative contribution of fruit availability and social factors like sex in determining association and proximity patterns in spider monkeys. We tested the influence of fruit availability and social factors on the association and proximity patterns using three-year data from a group of spider monkeys in the Yucatan Peninsula of Mexico. We identified subgroup members and estimated their Interindividual distances through instantaneous scan sampling. We evaluated fruit availability by monitoring the phenology of the 10 most important food tree species for spider monkeys in the study site. Social network analyses allowed us to evaluate association and proximity patterns in subgroups. We showed that association patterns vary between seasons, respond to changes in fruit availability, and are influenced by the sex of individuals, likely reflecting biological and behavioral differences between sexes and the interplay between ecological and social factors. In contrast, proximity patterns were minimally affected by changes in fruit availability, suggesting that social factors are more important than food availability in determining cohesion within subgroups. 相似文献
945.
Pierre Denelle Cyrille Violle DivGrass Consortium François Munoz 《Journal of Biogeography》2020,47(9):1922-1933
946.
Tanja Proctor Katrin Jensen Meinhard Kieser 《Biometrical journal. Biometrische Zeitschrift》2020,62(3):777-789
Individualized therapies for patients with biomarkers are moving more and more into the focus of research interest when developing new treatments. Hereby, the term individualized (or targeted) therapy denotes a treatment specifically developed for biomarker-positive patients. A network meta-analysis model for a binary endpoint combining the evidence for a targeted therapy from individual patient data with the evidence for a non-targeted therapy from aggregate data is presented and investigated. The biomarker status of the patients is either available at patient-level in individual patient data or at study-level in aggregate data. Both types of biomarker information have to be included. The evidence synthesis model follows a Bayesian approach and applies a meta-regression to the studies with aggregate data. In a simulation study, we address three treatment arms, one of them investigating a targeted therapy. The bias and the root-mean-square error of the treatment effect estimate for the subgroup of biomarker-positive patients based on studies with aggregate data are investigated. Thereby, the meta-regression approach is compared to approaches applying alternative solutions. The regression approach has a surprisingly small bias even in the presence of few studies. By contrast, the root-mean-square error is relatively greater. An illustrative example is provided demonstrating implementation of the presented network meta-analysis model in a clinical setting. 相似文献
947.
948.
Kecheng Lei Liwen Zhang Yijing He Hui Sun Weifang Tong Yichun Xu Lingjing Jin 《Bioscience reports》2020,40(12)
Early stage diagnosis of Parkinson’s disease (PD) is challenging without significant motor symptoms. The identification of effective molecular biomarkers as a hematological indication of PD may help improve the diagnostic timelines and accuracy. In the present paper, we analyzed and compared the blood samples of PD and control (CTR) patients to identify the disease-related changes and determine the putative biomarkers for PD diagnosis. Based on the RNA sequencing analysis, differentially expressed genes (DEGs) were identified, and the co-expression network of DEGs was constructed using the weighted gene correlation network analysis (WGCNA). The analysis leads to the identification of 87 genes that were exclusively regulated in the PD group, whereas 66 genes were significantly increased and 21 genes were significantly decreased in contrast with the control group. The results indicate that the core lncRNA–mRNA co-expression network greatly changes the immune response in PD patients. Specifically, the results showed that Prader Willi Angelman Region RNA6 (PWAR6), LINC00861, AC83843.1, IRF family, IFIT family and calcium/calmodulin-dependent protein kinase IV (CaMK4) may play important roles in the immune system of PD. Based on the findings from the present study, future research aims at identifying novel therapeutic strategies for PD. 相似文献
949.
950.
Yuan Zhang Yang Chen Chenran Wang Chun-Chao Lo Xiuwen Liu Wei Wu Jinfeng Zhang 《Proteins》2020,88(7):819-829
Designing protein sequences that fold to a given three-dimensional (3D) structure has long been a challenging problem in computational structural biology with significant theoretical and practical implications. In this study, we first formulated this problem as predicting the residue type given the 3D structural environment around the C α atom of a residue, which is repeated for each residue of a protein. We designed a nine-layer 3D deep convolutional neural network (CNN) that takes as input a gridded box with the atomic coordinates and types around a residue. Several CNN layers were designed to capture structure information at different scales, such as bond lengths, bond angles, torsion angles, and secondary structures. Trained on a very large number of protein structures, the method, called ProDCoNN (protein design with CNN), achieved state-of-the-art performance when tested on large numbers of test proteins and benchmark datasets. 相似文献