Rhodobacteraceae on the marine brown alga Fucus spiralis are abundant and show physiological adaptation to an epiphytic lifestyle

Macroalgae harbour specific microbial communities on their surface that have functions related to host health and defence. In this study, the bacterial biofilm of the marine brown alga Fucus spiralis was investigated using 16S rRNA gene amplicon-based analysis and isolation of bacteria. Rhodobacteraceae (Alphaproteobacteria) were the predominant family constituting 23% of the epibacterial community. At the genus level, Sulfitobacter, Loktanella, Octadecabacter and a previously undescribed cluster were most abundant, and together they comprised 89% of the Rhodobacteraceae. Supported by a specific PCR approach, 23 different Rhodobacteraceae-affiliated strains were isolated from the surface of F. spiralis, which belonged to 12 established and three new genera. For seven strains, closely related sequences were detected in the 16S rRNA gene dataset. Growth experiments with substrates known to be produced by Fucus spp. showed that all of them were consumed by at least three strains, and vitamin B₁₂ was produced by 70% of the isolates. Since growth of F. spiralis depends on B₁₂ supplementation, bacteria may provide the alga with this vitamin. Most strains produced siderophores, which can enhance algal growth under iron-deficient conditions. Inhibiting properties against other bacteria were only observed when F. spiralis material was present in the medium. Thus, the physiological properties of the isolates indicated adaption to an epiphytic lifestyle.     

遥感反演植被含氮量研究进展

植被含氮量表征植被氮素状态。它作为植被生长状况的重要指标,在生态系统健康状况检测、生态系统生产估测、精准农业、生态系统干扰评估等方面均有重要意义。遥感监测植被含氮量主要基于高光谱和多光谱数据,采用的算法包括经验方法(波谱指数与回归分析)及物理方法(辐射传输模型法)。但受数据源和研究方法的局限,目前植被氮含量遥感监测局限于区域范围较小且内部植被类型与环境条件(气候、地形等)基本一致的情形,而对复杂生态系统的监测能力不足。未来的研究需针对氮沉降和人类活动的生态系统响应这一重大研究需求,发展和改进现有植被含氮量遥感反演方法。可考虑开展对不同环境条件下、不同类型植被光谱曲线进行标准化的研究,以形成普适的植被含氮量反演方法。并考虑综合运用多种数据(如微波遥感、无人机遥感),形成多尺度同步监测,以提高遥感对区域乃至全球范围内植被氮含量常规监测的能力。     

Focus: A Multifaceted Battle Against Cancer: Extracting Knowledge from Chemical Imaging Data Using Computational Algorithms for Digital Cancer Diagnosis

Fourier transform infrared (FTIR) spectroscopic imaging is an emerging microscopy modality for clinical histopathologic diagnoses as well as for biomedical research. Spectral data recorded in this modality are indicative of the underlying, spatially resolved biochemical composition but need computerized algorithms to digitally recognize and transform this information to a diagnostic tool to identify cancer or other physiologic conditions. Statistical pattern recognition forms the backbone of these recognition protocols and can be used for highly accurate results. Aided by biochemical correlations with normal and diseased states and the power of modern computer-aided pattern recognition, this approach is capable of combating many standing questions of traditional histology-based diagnosis models. For example, a simple diagnostic test can be developed to determine cell types in tissue. As a more advanced application, IR spectral data can be integrated with patient information to predict risk of cancer, providing a potential road to precision medicine and personalized care in cancer treatment. The IR imaging approach can be implemented to complement conventional diagnoses, as the samples remain unperturbed and are not destroyed. Despite high potential and utility of this approach, clinical implementation has not yet been achieved due to practical hurdles like speed of data acquisition and lack of optimized computational procedures for extracting clinically actionable information rapidly. The latter problem has been addressed by developing highly efficient ways to process IR imaging data but remains one that has considerable scope for progress. Here, we summarize the major issues and provide practical considerations in implementing a modified Bayesian classification protocol for digital molecular pathology. We hope to familiarize readers with analysis methods in IR imaging data and enable researchers to develop methods that can lead to the use of this promising technique for digital diagnosis of cancer.     

Isolation,Culture and Long-Term Maintenance of Primary Mesencephalic Dopaminergic Neurons From Embryonic Rodent Brains

Degeneration of mesencephalic dopaminergic (mesDA) neurons is the pathological hallmark of Parkinson’s diseae. Study of the biological processes involved in physiological functions and vulnerability and death of these neurons is imparative to understanding the underlying causes and unraveling the cure for this common neurodegenerative disorder. Primary cultures of mesDA neurons provide a tool for investigation of the molecular, biochemical and electrophysiological properties, in order to understand the development, long-term survival and degeneration of these neurons during the course of disease. Here we present a detailed method for the isolation, culturing and maintenance of midbrain dopaminergic neurons from E12.5 mouse (or E14.5 rat) embryos. Optimized cell culture conditions in this protocol result in presence of axonal and dendritic projections, synaptic connections and other neuronal morphological properties, which make the cultures suitable for study of the physiological, cell biological and molecular characteristics of this neuronal population.     

Plant functional types and climatic change: Introduction

Abstract. Plant functional types are a necessary device for reducing the complex and often uncharted characteristics of species diversity in function and structure when attempting to project the nature and function of species assemblages into future environments. A workshop was held to review the current methods commonly used for defining plant functional types, either globally or for particular biomes, and to compare them with the field experiences of specialists for specific biomes of the world. The methods fall into either an objective and inductive approach or a subjective and deductive approach. When the different methods were tested, it was generally found that the classification for one site or environment was not wholly applicable to a different site or environment. However, the degree of change which is necessary for adjustment between environments may not prove to be a major limitation in the use of functional types.     

Malaria-induced reduction of fecundity during the first gonotrophic cycle of Anopheles Stephensi mosquitoes

Abstract. Anopheles stephensi mosquitoes which had fed upon mice infected with Plasmodium yoelii nigeriensis malaria parasites produced significantly fewer eggs than mosquitoes fed on an uninfected mouse. Fecundity reduction was more pronounced when the bloodmeal contained malaria gametocytes and the mosquitoes developed oocysts. Egg production and haematin excretion were correlated for uninfected bloodfed mosquitoes; the presence of P.y. nigeriensis in the blood affected this relationship. Reduced fecundity was associated with a significant reduction of bloodmeal size (measured by haematin excretion) in mosquitoes which ingested gametocytaemic blood. The bloodmeal size in mosquitoes fed on parasitaemic blood without gametocytes was not significantly reduced. The use of haematin assays for determination of bloodmeal size in mosquitoes is discussed.