A social network analysis of primate groups

Primate social systems are difficult to characterize, and existing classification schemes have been criticized for being overly simplifying, formulated only on a verbal level or partly inconsistent. Social network analysis comprises a collection of analytical tools rooted in the framework of graph theory that were developed to study human social interaction patterns. More recently these techniques have been successfully applied to examine animal societies. Primate social systems differ from those of humans in both size and density, requiring an approach that puts more emphasis on the quality of relationships. Here, we discuss a set of network measures that are useful to describe primate social organization and we present the results of a network analysis of 70 groups from 30 different species. For this purpose we concentrated on structural measures on the group level, describing the distribution of interaction patterns, centrality, and group structuring. We found considerable variability in those measures, reflecting the high degree of diversity of primate social organizations. By characterizing primate groups in terms of their network metrics we can draw a much finer picture of their internal structure that might be useful for species comparisons as well as the interpretation of social behavior.     

Addressing cancer disparities via community network mobilization and intersectoral partnerships: a social network analysis

Community mobilization and collaboration among diverse partners are vital components of the effort to reduce and eliminate cancer disparities in the United States. We studied the development and impact of intersectoral connections among the members of the Massachusetts Community Network for Cancer Education, Research, and Training (MassCONECT). As one of the Community Network Program sites funded by the National Cancer Institute, this infrastructure-building initiative utilized principles of Community-based Participatory Research (CBPR) to unite community coalitions, researchers, policymakers, and other important stakeholders to address cancer disparities in three Massachusetts communities: Boston, Lawrence, and Worcester. We conducted a cross-sectional, sociometric network analysis four years after the network was formed. A total of 38 of 55 members participated in the study (69% response rate). Over four years of collaboration, the number of intersectoral connections reported by members (intersectoral out-degree) increased, as did the extent to which such connections were reported reciprocally (intersectoral reciprocity). We assessed relationships between these markers of intersectoral collaboration and three intermediate outcomes in the effort to reduce and eliminate cancer disparities: delivery of community activities, policy engagement, and grants/publications. We found a positive and statistically significant relationship between intersectoral out-degree and community activities and policy engagement (the relationship was borderline significant for grants/publications). We found a positive and statistically significant relationship between intersectoral reciprocity and community activities and grants/publications (the relationship was borderline significant for policy engagement). The study suggests that intersectoral connections may be important drivers of diverse intermediate outcomes in the effort to reduce and eliminate cancer disparities. The findings support investment in infrastructure-building and intersectoral mobilization in addressing disparities and highlight the benefits of using CBPR approaches for such work.     

Environment damage assessment: A literature review using social network analysis

Rapid development of environment science and ecology has witnessed the emerging of economical tools applying to environmental issues, especially environment damage assessment. This study applied bibliometrics tools to the environment damage assessment methods based on on-line SCI-E and SSCI from 2007 to 2016, and described the bibliometric characteristics including publications number, journals, and disciplines. Moreover, the concept of social network was introduced into bibliometrics analysis, and the collaboration relationship network of countries, authors, and institutions are generated. Furthermore, frequency analysis of keywords revealed five most widely used methods in environment damage assessment, including market valuation, contingent valuation method, choice experiment method, travel cost method, and hedonic price method, which are specifically reviewed on developing trend, economic basis, and operating process.     

Breast cancer at bone metastatic sites: recent discoveries and treatment targets

Breast carcinoma is the most common cancer of women. Bones are often involved with breast carcinoma metastases with the resulting morbidity and reduced quality of life. Breast cancer cells arriving at bone tissues mount supportive microenvironment by recruiting and modulating the activity of several host tissue cell types including the specialized bone cells osteoblasts and osteoclasts. Pathologically activated osteoclasts produce osteolytic lesions associated with bone pain, pathological fractures, cord compression and other complications of metastatic breast carcinoma at bone. Over the last decade there has been enormous growth of knowledge in the field of osteoclasts biology both in the physiological state and in the tumor microenvironment. This knowledge allowed the development and implementation of several targeted therapeutics that expanded the armamentarium of the oncologists dealing with the metastases-associated osteolytic disease. While the interactions of cancer cells with resident bone cells at the established metastatic gross lesions are well-studied, the preclinical events that underlie the progression of disseminated tumor cells into micrometastases and then into clinically-overt macrometastases are just starting to be uncovered. In this review, we discuss the established information and the most recent discoveries in the pathogenesis of osteolytic metastases of breast cancer, as well as the corresponding investigational drugs that have been introduced into clinical development.     

A comparative social network analysis of wasp colonies and classrooms: Linking network structure to functioning

A major question in current network science is how to understand the relationship between structure and functioning of real networks. Here we present a comparative network analysis of 48 wasp and 36 human social networks. We have compared the centralisation and small world character of these interaction networks and have studied how these properties change over time. We compared the interaction networks of (1) two congeneric wasp species (Ropalidia marginata and Ropalidia cyathiformis), (2) the queen-right (with the queen) and queen-less (without the queen) networks of wasps, (3) the four network types obtained by combining (1) and (2) above, and (4) wasp networks with the social networks of children in 36 classrooms. We have found perfect (100%) centralisation in a queen-less wasp colony and nearly perfect centralisation in several other queen-less wasp colonies. Note that the perfectly centralised interaction network is quite unique in the literature of real-world networks. Differences between the interaction networks of the two wasp species are smaller than differences between the networks describing their different colony conditions. Also, the differences between different colony conditions are larger than the differences between wasp and children networks. For example, the structure of queen-right R. marginata colonies is more similar to children social networks than to that of their queen-less colonies. We conclude that network architecture depends more on the functioning of the particular community than on taxonomic differences (either between two wasp species or between wasps and humans).     

A guide to choosing and implementing reference models for social network analysis

Analysing social networks is challenging. Key features of relational data require the use of non-standard statistical methods such as developing system-specific null, or reference, models that randomize one or more components of the observed data. Here we review a variety of randomization procedures that generate reference models for social network analysis. Reference models provide an expectation for hypothesis testing when analysing network data. We outline the key stages in producing an effective reference model and detail four approaches for generating reference distributions: permutation, resampling, sampling from a distribution, and generative models. We highlight when each type of approach would be appropriate and note potential pitfalls for researchers to avoid. Throughout, we illustrate our points with examples from a simulated social system. Our aim is to provide social network researchers with a deeper understanding of analytical approaches to enhance their confidence when tailoring reference models to specific research questions.     

降水稳定同位素研究的历史与现状——基于文献计量学及网络分析方法

降水稳定同位素可以揭示降水的不同水汽来源和水汽的季节转换。通过建立降水稳定同位素与不同气象要素的关系,可为区域水资源管理甚至可为生态修复中的植被恢复状态的研究提供重要的背景数据。为揭示降水稳定同位素研究的发展现状,基于文献计量学以及网络分析方法运用Citespace软件对1990—2017年Web of Science核心数据库中降水稳定同位素的相关文献进行可视化统计分析。发现降水稳定同位素相关的文献数量在呈逐年上升趋势,主要分布在地质、气象与大气科学、海洋学、湖泊沼泽学、古生物学等相关学科,美国、中国、德国、加拿大等国家以及中国科学院、美国地质调查局等研究机构文章数量较多,表现出较强的科研实力。利用Citespace软件绘制了降水稳定同位素研究相关文献的共被引、研究作者的共被引等知识图谱,对该研究领域知识基础及核心作者的影响力进行了探讨。图谱显示,2007年以来,Yao T、Risi C、Tian L等对降水稳定同位素的研究的推进起到了重要的推动作用。最后对该研究领域的关键词与词频等进行分析,绘制出降水稳定同位素研究领域的研究热点演进脉络,并确定leaf water、Tibetan Plateau、cellulose、environmental change、tree ring、atmospheric circulation、groundwater recharge、hydrograph separation等即将成为研究的新热点。近几年来,虽然研究的文章数量在逐年增加,但是核心作者及代表作品较少,与社会的实际生产应用结合度不足。在未来研究中在注重方法的更新的同时可考虑与社会生产实际相结合。     

Applying DNA computation to intractable problems in social network analysis

From ancient times to the present day, social networks have played an important role in the formation of various organizations for a range of social behaviors. As such, social networks inherently describe the complicated relationships between elements around the world. Based on mathematical graph theory, social network analysis (SNA) has been developed in and applied to various fields such as Web 2.0 for Web applications and product developments in industries, etc. However, some definitions of SNA, such as finding a clique, N-clique, N-clan, N-club and K-plex, are NP-complete problems, which are not easily solved via traditional computer architecture. These challenges have restricted the uses of SNA. This paper provides DNA-computing-based approaches with inherently high information density and massive parallelism. Using these approaches, we aim to solve the three primary problems of social networks: N-clique, N-clan, and N-club. Their accuracy and feasible time complexities discussed in the paper will demonstrate that DNA computing can be used to facilitate the development of SNA.     

A decade of discoveries in cardiac biology

The heart is the first organ to form in the embryo, and all subsequent events in the life of the organism depend on its function. Inherited mutations in cardiac regulatory genes give rise to congenital heart disease, the most common form of human birth defects, and abnormalities of the adult heart represent the most prevalent cause of morbidity and mortality in the industrialized world. The past decade has marked a transition from physiological and functional studies of the heart toward a deeper understanding of cardiac function (and dysfunction) at genetic and molecular levels. These discoveries have provided new therapeutic approaches for prevention and palliation of cardiac disease and have raised new questions, challenges and opportunities for the future.     

一个新现象发现的故事——我的科学人生和趣事

金国章教授是我国著名的药理学家,中国科学院院士。他致力于中药延胡索的研究,从其有效成分、构效关系的研究,直至新型药理学作用机制的发现,以及创新性假设的提出,形成了自己完整的科研思路与研究体系。他几十年如一日,针对一种中药,不遗余力地进行科学研究,最终取得原始创新性成果。他的科研故事告诉我们:成功来自于"汗水、理念、机遇",且这一切则取决于自身的努力,用自己的智慧抓住良机。青年人多梦想,常为人所鼓励。能否梦想成真,决定于两个因素:一是自己的努力,二是客观所赋予的机遇。机遇总是垂青有准备之人。有青年人的梦想,才有本文要介绍的故事。这故事的全过程记录在国家自然科学基金研究专著《中药延胡索研究中的新发现》中(2001),该书总结了四氢原小檗碱同类物(THPBs)作用在脑内多巴胺(DA)受体的神经药理作用,使它在中国土地上生根、发芽、开花、结果的故事,并突出左旋千金藤啶碱(l-SPD)对DA受体独特的新型双重作用。评审专家们指出,该书是国际上第一本这方面的专著(1999),有创新性,令作者感到欣慰。     

基于社会网络分析法的生态工业园典型案例研究

以丹麦卡伦堡和广西贵港生态工业园为例,应用社会网络分析法分析典型生态工业园的组织结构和网络结构。用簇系数、平均最短距离、传递性以及核心-边缘结构来衡量其稳定性,分析其不同结构特征。卡伦堡生态工业园的簇系数为0.715,远高于贵港生态工业园的0.246,说明其聚合性较好;从最短距离长度来看,卡伦堡和贵港分别为2.110和2.236,复杂性弱;从传递性来看,两者传递性皆低于25%,节点之间联系性不够强;从核心-边缘结构来看,卡伦堡各节点之间的异质性(0.057)高于贵港(0.005),可见贵港参与主体的中心性较为均衡,而卡伦堡差异性较大。两者都以一个产业或者企业集团为网络核心;网络内其他节点联系不够紧密,长链条联结较少;网络复杂性弱。     

Comprehensive analysis of lncRNA-associated ceRNA network in colorectal cancer

Colorectal cancer (CRC) is one of the most common malignancies and morbidity and mortality are increasing rapidly. Increasing evidence showed the close correlation between aberrant expression of certain RNAs and the occurrence and development of CRC. However, comprehensive analyses of differentially expressed profiles of linRNA in CRC based on large sample size have been lacking. In the present study, based on RNA-seq data obtained from the TCGA (The Cancer Genome Atlas) database, we identified 1176 lncRNAs, 245 miRNAs and 2083 mRNAs whichaberrantly expressed in the colorectal cancer tissues compared with the adjacent non-tumorous tissues. A Kaplan-Meier curve analysis was used to study the overall survival rate of the three RNA-related CRC patients. After constructing the ceRNA network, we performed the KEGG enrichment pathway analysis on ceRNA-related differentially expressed mRNAs and found that these mRNAs were remarkably enriched in the pathways associated with CRC. Combining the differentially expressed lncRNAs with clinical pathological variables of CRC patients, we also found that LINC00400 and LINC00355 not only contribute to the regulation of ceRNA network, but also show significantchanges in its expression in multiple CRC pathological stages, indicating that LINC00400 and LINC00355 can be considered as promising therapeutic targets for CRC.     

The malignant social network: Cell-cell adhesion and communication in cancer stem cells

Tumors contain a vastly complicated cellular network that relies on local communication to execute malignant programs. The molecular cues that are involved in cell-cell adhesion orchestrate large-scale tumor behaviors such as proliferation and invasion. We have recently begun to appreciate that many tumors contain a high degree of cellular heterogeneity and are organized in a cellular hierarchy, with a cancer stem cell (CSC) population identified at the apex in multiple cancer types. CSCs reside in unique microenvironments or niches that are responsible for directing their behavior through cellular interactions between CSCs and stromal cells, generating a malignant social network. Identifying cell-cell adhesion mechanisms in this network has implications for the basic understanding of tumorigenesis and the development of more effective therapies. In this review, we will discuss our current understanding of cell-cell adhesion mechanisms used by CSCs and how these local interactions have global consequences for tumor biology.     

Evidence for social role in a dolphin social network

Social animals have to take into consideration the behaviour of conspecifics when making decisions to go by their daily lives. These decisions affect their fitness and there is therefore an evolutionary pressure to try making the right choices. In many instances individuals will make their own choices and the behaviour of the group will be a democratic integration of everyone’s decision. However, in some instances it can be advantageous to follow the choice of a few individuals in the group if they have more information regarding the situation that has arisen. Here I provide early evidence that decisions about shifts in activity states in a population of bottlenose dolphin follow such a decision-making process. This unshared consensus is mediated by a non-vocal signal, which can be communicated globally within the dolphin school. These signals are emitted by individuals that tend to have more information about the behaviour of potential competitors because of their position in the social network. I hypothesise that this decision-making process emerged from the social structure of the population and the need to maintain mixed-sex schools.