Molecular phylogenetics of the tribeInuleae s. str.(Asteraceae), based on ITS sequences of nuclear ribosomal DNA

The sequences of the internal transcribed spacer (ITS) region of 18S–26S nrDNA for a sample of 16 taxa from theInuleae s. str. and two outgroup taxa are analysed cladistically with PAUP. A consensus tree of the four most parsimonious cladograms is presented. Three different tests of cladogram stability are conducted (Bremer support, parsimony jackknifing and bootstrapping); all tests indicate a high degree of support for the basal nodes of the tree. The ITS phylogeny of the tribe is compared with previous hypotheses based on morphological data. The position ofAnisopappus as sister group to the rest of the tribe is supported by the molecular data, but the proposed subdivision ofInuleae s. str. into a paleate grade group and an epaleate clade is not. The interpretation of the character evolution of, e.g. receptacular paleae and pappus features within the tribe is discussed.     

Upscaling leaf area index in an Arctic landscape through multiscale observations

Monitoring and understanding global change requires a detailed focus on upscaling, the process for extrapolating from the site‐specific scale to the smallest scale resolved in regional or global models or earth observing systems. Leaf area index (LAI) is one of the most sensitive determinants of plant production and can vary by an order of magnitude over short distances. The landscape distribution of LAI is generally determined by remote sensing of surface reflectance (e.g. normalized difference vegetation index, NDVI) but the mismatch in scales between ground and satellite measurements complicates LAI upscaling. Here, we describe a series of measurements to quantify the spatial distribution of LAI in a sub‐Arctic landscape and then describe the upscaling process and its associated errors. Working from a fine‐scale harvest LAI–NDVI relationship, we collected NDVI data over a 500 m × 500 m catchment in the Swedish Arctic, at resolutions from 0.2 to 9.0 m in a nested sampling design. NDVI scaled linearly, so that NDVI at any scale was a simple average of multiple NDVI measurements taken at finer scales. The LAI–NDVI relationship was scale invariant from 1.5 to 9.0 m resolution. Thus, a single exponential LAI–NDVI relationship was valid at all these scales, with similar prediction errors. Vegetation patches were of a scale of ～0.5 m and at measurement scales coarser than this, there was a sharp drop in LAI variance. Landsat NDVI data for the study catchment correlated significantly, but poorly, with ground‐based measurements. A variety of techniques were used to construct LAI maps, including interpolation by inverse distance weighting, ordinary Kriging, External Drift Kriging using Landsat data, and direct estimation from a Landsat NDVI–LAI calibration. All methods produced similar LAI estimates and overall errors. However, Kriging approaches also generated maps of LAI estimation error based on semivariograms. The spatial variability of this Arctic landscape was such that local measurements assimilated by Kriging approaches had a limited spatial influence. Over scales >50 m, interpolation error was of similar magnitude to the error in the Landsat NDVI calibration. The characterisation of LAI spatial error in this study is a key step towards developing spatio‐temporal data assimilation systems for assessing C cycling in terrestrial ecosystems by combining models with field and remotely sensed data.     

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．     

Technologies for integrating biological data

The process of building a new database relevant to some field of study in biomedicine involves transforming, integrating and cleansing multiple data sources, as well as adding new material and annotations. This paper reviews some of the requirements of a general solution to this data integration problem. Several representative technologies and approaches to data integration in biomedicine are surveyed. Then some interesting features that separate the more general data integration technologies from the more specialised ones are highlighted.     

基于GIS的浙北近海海域生态系统健康评价

在浙江省北部地区经济高速发展,科学高效利用海洋资源的同时,也不可避免的对浙北近海海域的生态系统造成一定的威胁。为了降低涉海工程对海洋生态环境可能造成的不利影响,通过分析浙江省北部海域高浊度、复杂水体等特点,利用层次分析法从水环境、沉积环境和海洋生物多样性构建了浙北近海海域生态系统评价指标体系,采用熵权法确定了相关因子的权重。在此基础上,综合GIS空间分析方法、数学模型,对2009年至2012年浙江省北部海域进行了实证研究。结果表明:(1)浙江省北部近海海域生态系统整体上处于不健康状态。含量较高的无机氮和磷酸盐及较低的海洋初级生产力是影响其环境质量的主要因素。(2)浙北近海海域生态系统主要薄弱区域与人类活动格局基本一致,由此推断,人类活动是影响浙北海域生态系统健康状态的主要因素。总体上,从2009至2012年浙北近海海域生态系统健康呈现逐年恶化的趋势。     

Fluorescence resonance energy transfer (FRET) microscopy imaging of live cell protein localizations

The current advances in fluorescence microscopy, coupled with the development of new fluorescent probes, make fluorescence resonance energy transfer (FRET) a powerful technique for studying molecular interactions inside living cells with improved spatial (angstrom) and temporal (nanosecond) resolution, distance range, and sensitivity and a broader range of biological applications.     

Detection and Structural Characterization of Ether Glycerophosphoethanolamine from Cortical Lysosomes Following Traumatic Brain Injury Using UPLC‐HDMSE

The use of ultra performance liquid chromatography coupled to data independent tandem mass spectrometry with traveling wave ion mobility for detection and structural identification of ether‐linked glycerophosphoethanolamine is described. The experimental design generates 4D data (chromatographic retention time, precursor accurate mass, drift time with associated calculated collisional cross‐section, and time‐aligned accurate mass diagnostic product ions) for each ionization mode. Confident structure identification depends on satisfying 4D data confirmation in both positive and negative ion mode. Using this methodology, a number of ether‐linked glycerophosphoethanolamine lipids are structurally elucidated from mouse brain lysosomes. It is further determined that several ether‐linked glycerophosphoethanolamine structures are differentially abundant between lysosomes isolated from mouse cortex following traumatic brain injury as compared to that of sham animals. The combined effort of aligning multi‐dimensional mass spectrometry data with a well‐defined traumatic brain injury model lays the foundation for gaining mechanistic insight in the role lysosomal membrane damage plays in neuronal cell death following brain injury.     

Extensive gaps and biases in our knowledge of a well‐known fauna: implications for integrating biological traits into macroecology

Aim Ecologists seeking to describe patterns at ever larger scales require compilations of data on the global abundance and distribution of species. Comparable compilations of biological data are needed to elucidate the mechanisms behind these patterns, but have received far less attention. We assess the availability of biological data across an entire assemblage: the well‐documented demersal marine fauna of the United Kingdom. We also test whether data availability for a species depends on its taxonomic group, maximum body size, the number of times it has been recorded in a global biogeographic database, or its commercial and conservation importance. Location Seas of the United Kingdom. Methods We defined a demersal marine fauna of 973 species from 15 phyla and 40 classes using five extensive surveys around the British Isles. We then quantified the availability of data on eight key biological traits (termed biological knowledge) for each species from online databases. Relationships between biological knowledge and our predictors were tested with generalized linear models. Results Full data on eight fundamental biological traits exist for only 9% (n= 88) of the UK demersal marine fauna, and 20% of species completely lack data. Clear trends in our knowledge exist: fish (median biological knowledge score = six traits) are much better known than invertebrates (one trait). Biological knowledge increases with biogeographic knowledge and (to a lesser extent) with body size, and is greater in species that are commercially exploited or of conservation concern. Main conclusions Our analysis reveals deep ignorance of the basic biology of a well‐studied fauna, highlighting the need for far greater efforts to compile biological trait data. Clear biases in our knowledge, relating to how well sampled or ‘important’ species are suggests that caution is required in extrapolating small subsets of biologically well‐known species to ecosystem‐level studies.     

Beyond ecosystem modeling: A roadmap to community cyberinfrastructure for ecological data‐model integration

In an era of rapid global change, our ability to understand and predict Earth's natural systems is lagging behind our ability to monitor and measure changes in the biosphere. Bottlenecks to informing models with observations have reduced our capacity to fully exploit the growing volume and variety of available data. Here, we take a critical look at the information infrastructure that connects ecosystem modeling and measurement efforts, and propose a roadmap to community cyberinfrastructure development that can reduce the divisions between empirical research and modeling and accelerate the pace of discovery. A new era of data‐model integration requires investment in accessible, scalable, and transparent tools that integrate the expertise of the whole community, including both modelers and empiricists. This roadmap focuses on five key opportunities for community tools: the underlying foundations of community cyberinfrastructure; data ingest; calibration of models to data; model‐data benchmarking; and data assimilation and ecological forecasting. This community‐driven approach is a key to meeting the pressing needs of science and society in the 21st century.