116 research outputs found

    Apoptosis at Inflection Point in Liquid Culture of Budding Yeasts

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    Budding yeasts are highly suitable for aging studies, because the number of bud scars (stage) proportionally correlates with age. Its maximum stages are known to reach at 20–30 stages on an isolated agar medium. However, their stage dynamics in a liquid culture is virtually unknown. We investigate the population dynamics by counting scars in each cell. Here one cell division produces one new cell and one bud scar. This simple rule leads to a conservation law: “The total number of bud scars is equal to the total number of cells.” We find a large discrepancy: extremely fewer cells with over 5 scars than expected. Almost all cells with 6 or more scars disappear within a short period of time in the late log phase (corresponds to the inflection point). This discrepancy is confirmed directly by the microscopic observations of broken cells. This finding implies apoptosis in older cells (6 scars or more)

    The diversity and evolution of pollination systems in large plant clades: Apocynaceae as a case study

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    Background and Aims Large clades of angiosperms are often characterized by diverse interactions with pollinators, but how these pollination systems are structured phylogenetically and biogeographically is still uncertain for most families. Apocynaceae is a clade of >5300 species with a worldwide distribution. A database representing >10 % of species in the family was used to explore the diversity of pollinators and evolutionary shifts in pollination systems across major clades and regions. Methods The database was compiled from published and unpublished reports. Plants were categorized into broad pollination systems and then subdivided to include bimodal systems. These were mapped against the five major divisions of the family, and against the smaller clades. Finally, pollination systems were mapped onto a phylogenetic reconstruction that included those species for which sequence data are available, and transition rates between pollination systems were calculated. Key Results Most Apocynaceae are insect pollinated with few records of bird pollination. Almost three-quarters of species are pollinated by a single higher taxon (e.g. flies or moths); 7 % have bimodal pollination systems, whilst the remaining approx. 20 % are insect generalists. The less phenotypically specialized flowers of the Rauvolfioids are pollinated by a more restricted set of pollinators than are more complex flowers within the Apocynoids + Periplocoideae + Secamonoideae + Asclepiadoideae (APSA) clade. Certain combinations of bimodal pollination systems are more common than others. Some pollination systems are missing from particular regions, whilst others are over-represented. Conclusions Within Apocynaceae, interactions with pollinators are highly structured both phylogenetically and biogeographically. Variation in transition rates between pollination systems suggest constraints on their evolution, whereas regional differences point to environmental effects such as filtering of certain pollinators from habitats. This is the most extensive analysis of its type so far attempted and gives important insights into the diversity and evolution of pollination systems in large clades

    GrassPlot - a database of multi-scale plant diversity in Palaearctic grasslands

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    GrassPlot is a collaborative vegetation-plot database organised by the Eurasian Dry Grassland Group (EDGG) and listed in the Global Index of Vegetation-Plot Databases (GIVD ID EU-00-003). GrassPlot collects plot records (releves) from grasslands and other open habitats of the Palaearctic biogeographic realm. It focuses on precisely delimited plots of eight standard grain sizes (0.0001; 0.001;... 1,000 m(2)) and on nested-plot series with at least four different grain sizes. The usage of GrassPlot is regulated through Bylaws that intend to balance the interests of data contributors and data users. The current version (v. 1.00) contains data for approximately 170,000 plots of different sizes and 2,800 nested-plot series. The key components are richness data and metadata. However, most included datasets also encompass compositional data. About 14,000 plots have near-complete records of terricolous bryophytes and lichens in addition to vascular plants. At present, GrassPlot contains data from 36 countries throughout the Palaearctic, spread across elevational gradients and major grassland types. GrassPlot with its multi-scale and multi-taxon focus complements the larger international vegetationplot databases, such as the European Vegetation Archive (EVA) and the global database " sPlot". Its main aim is to facilitate studies on the scale-and taxon-dependency of biodiversity patterns and drivers along macroecological gradients. GrassPlot is a dynamic database and will expand through new data collection coordinated by the elected Governing Board. We invite researchers with suitable data to join GrassPlot. Researchers with project ideas addressable with GrassPlot data are welcome to submit proposals to the Governing Board

    Biotechnological Perspective of Reactive Oxygen Species (ROS)-Mediated Stress Tolerance in Plants

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    All environmental cues lead to develop secondary stress conditions like osmotic and oxidative stress conditions that reduces average crop yields by more than 50% every year. The univalent reduction of molecular oxygen (O2) in metabolic reactions consequently produces superoxide anions (O2‱−) and other reactive oxygen species (ROS) ubiquitously in all compartments of the cell that disturbs redox potential and causes threat to cellular organelles. The production of ROS further increases under stress conditions and especially in combination with high light intensity. Plants have evolved different strategies to minimize the accumulation of excess ROS like avoidance mechanisms such as physiological adaptation, efficient photosystems such as C4 or CAM metabolism and scavenging mechanisms through production of antioxidants and antioxidative enzymes. Ascorbate-glutathione pathway plays an important role in detoxifying excess ROS in plant cells, which includes superoxide dismutase (SOD) and ascorbate peroxidase (APX) in detoxifying O2‱−radical and hydrogen peroxide (H2O2) respectively, monodehydroascorbate reductase (MDHAR), dehydroascorbate reductase (DHAR) and glutathione reductase (GR) involved in recycling of reduced substrates such as ascorbate and glutathione. Efficient ROS management is one of the strategies used by tolerant plants to survive and perform cellular activities under stress conditions. The present chapter describes different sites of ROS generation and and their consequences under abiotic stress conditions and also described the approaches to overcome oxidative stress through genomics and genetic engineering

    Toward Understanding Molecular Mechanisms of Abiotic Stress Responses in Rice

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    Medicinal plants – prophylactic and therapeutic options for gastrointestinal and respiratory diseases in calves and piglets? A systematic review

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    Hot-gas cleanup system model development. Volume I. Final report

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    This two-volume report summarizes the state of the art in performance modeling of advanced high-temperature, high-pressure (HTHP) gas cleanup devices. Volume I contains the culmination of the research effort carried over the past 12 months and is a summary of research achievements. Volume II is the user's manual for the computer programs developed under the present research project. In this volume, Section 2 presents background information on pressurized, fluidized-bed combustion concepts, a description of the role of the advanced gas cleanup systems, and a list of advanced gas cleanup systems that are currently in development under DOE sponsorship. Section 3 describes the methodology for the software architecture that forms the basis of the well-disciplined and structured computer programs developed under the present project. Section 4 reviews the fundamental theories that are important in analyzing the cleanup performance of HTHP gas filters. Section 5 discusses the effect of alkali agents in HTHP gas cleanup. Section 6 evaluates the advanced HTHP gas cleanup models based on their mathematical integrity, availability of supporting data, and the likelihood of commercialization. As a result of the evaluation procedure detailed in Section 6, five performance models were chosen to be incorporated into the overall system simulation code, ASPEN. These five models (the electrocyclone, ceramic bag filter, moving granular bed filter, electrostatic granular bed filter, and electrostatic precipitator) are described in Section 7. The method of cost projection for these five models is discussed in Section 8. The supporting data and validation of the computer codes are presented in Section 9, and finally the conclusions and recommendations for the HTHP gas cleanup system model development are given in Section 10. 72 references, 19 figures, 25 tables

    Hot-gas cleanup system model development. Volume II. Final report

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    Under Contract to the Department of Energy (DOE) through the Morgantown Energy Technology Center (METC), Flow Industries, Inc., has developed computer models to simulate the physical performance of five hot-gas cleanup devices for pressurized, fluidized-bed combustion (PFBC), combined-cycle power plants. Separate cost models have also been developed to estimate the cost of each device. The work leading to the development of these models is described in Volume I of this report. This volume contains the user's manuals for both the physical and cost models. The manuals for the physical models are given first followed by those for the cost models. Each manual is a complete and separate document. The model names and devices and their respective subroutine names are: (1) Moving Granular Bed Filter by Combustion Power Company, USRCGB, QFCOST; (2) Ceramic Bag Filter by Acurex, USRACB, QDCOST; (3) Electrostatic Granular Bed Filter by General Electric, USRGGB, QACOST; (4) Electrostatic Precipitator by Research Cottrell, USRCEP, QECOST; and (5) Electrocyclone by General Electric, USRGCY, QBCOST
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