Gibberellins and Growth Inhibitors in Spring Bleeding Sap, Roots and Branches of Juglans regia L.

The main gibberellin found in the spring bleeding sap of thewalnut tree was identified as GA₁₉ and quantified by gas chromatography-selectedion monitoring (817 pg/ml). The second minor gibberellin (12pg GA₃-equiv./ml) was chromatographically similar to GA₅₃. Bothgibberellins occur in their free forms and as neutral ester-likeconjugates. In the roots, these free gibberellins and an additionalgibberellin glucoside-like component were found in late winter. In the bleeding sap, branches and roots, abscisic acid was identifiedby gas chromatography and mass spectrometry. In the sap, itsamount was determined to be 34 ng/ml. ABA was not found in aconjugated form, but the branches contained a neutral ester-likeconjugate of 4'-dihydrophaseic acid, an ABA metabolite, whichafter hydrolysis was identified by combined gas chromatography-massspectrometry. (Received March 28, 1981; Accepted November 16, 1981)     

A glia-derived neurite promoting factor with protease inhibitory activity belongs to the protease nexins

A glia-derived neurite promoting factor (GdNPF) has serine protease inhibitory activity and in addition regulates the migration of neuronal cells. cDNA cloning of GdNPF is necessary for studying the physiological relevance and the mode of action of this protein and similar cell-derived protease inhibitors. Xenopus oocytes injected with rat glioma cells mRNA release this inhibitor. A rat cDNA clone coding for the previously purified glia-derived neurite promoting factor (GdNPF) was isolated upon hybridization-selected translation, followed by immunoprecipitation. The correct identity of this cDNA is proven by the presence of a sequence coding for a tryptic fragment from pure GdNPF. Northern analysis indicates that GdNPF mRNA is found almost exclusively in brain tissue and could be developmentally regulated. The same cDNA clone has been used to isolate full-length rat and human GdNPF cDNA. The deduced human GdNPF amino acid sequence indicates that the protein is a member of a family of cell-derived protease inhibitors named protease nexins.     

Factors Influencing Algae–Clay Aggregation

The dumping of bauxite tailings on a clear-water Amazonian lake caused a significant decrease in phytoplankton densities. The influence of these suspended clay particles on algal sinking, through algae–clay aggregation, was investigated under laboratory conditions, by measuring fluctuations in algal population densities over time, with different suspended clay concentrations. The population densities of the four algal species tested, Phormidium amoenum, Mougeotia sp., Staurodesmus convergens and Chlorella sp., were decreased by the algae–clay aggregation. The extent of this process was dependent on algal morphological characteristics such as size and shape, as well as on the concentration of suspended clay particles.     

Cloudgene: A graphical execution platform for MapReduce programs on private and public clouds

ABSTRACT: BACKGROUND: The MapReduce framework enables a scalable processing and analyzing of large datasets by distributing the computational load on connected computer nodes, referred to as a cluster. In Bioinformatics, MapReduce has already been adopted to various case scenarios such as mapping next generation sequencing data to a reference genome, finding SNPs from short read data or matching strings in genotype files. Nevertheless, tasks like installing and maintaining MapReduce on a cluster system, importing data into its distributed file system or executing MapReduce programs require advanced knowledge in computer science and could thus prevent scientists from usage of currently available and useful software solutions. RESULTS: Here we present Cloudgene, a freely available platform to improve the usability of MapReduce programs in Bioinformatics by providing a graphical user interface for the execution, the import and export of data and the reproducibility of workflows on in-house (private clouds) and rented clusters (public clouds). The aim of Cloudgene is to build a standardized graphical execution environment for currently available and future MapReduce programs, which can all be integrated by using its plug-in interface. Since Cloudgene can be executed on private clusters, sensitive datasets can be kept in house at all time and data transfer times are therefore minimized. CONCLUSIONS: Our results show that MapReduce programs can be integrated into Cloudgene with little effort and without adding any computational overhead to existing programs. This platform gives developers the opportunity to focus on the actual implementation task and provides scientists a platform with the aim to hide the complexity of MapReduce. In addition to MapReduce programs, Cloudgene can also be used to launch predefined systems (e.g. Cloud BioLinux, RStudio) in public clouds. Currently, five different bioinformatic programs using MapReduce and two systems are integrated and have been successfully deployed. Cloudgene is freely available at http://cloudgene.uibk.ac.at.     

Photoperiod influences the development and the expression of personality traits and social behaviour in wild cavies (Cavia aperea)

Seasonality influences behaviour, physiology and life history of organisms, and photoperiod is a reliable and influential cue gearing individual adaptation to seasonal changes in the environment. Plastic phenotypic adjustments according to the prevailing season are a widespread, well-studied phenomenon. Less well known are effects on developmental trajectories of animals born into different seasons. By manipulating the photoperiod during pregnancy and lactation independent of food availability and temperature, we studied if maternal behaviour in the precocial wild cavy (Cavia aperea) responds to this seasonal cue and if maternal behaviour and photoperiod shape offspring development and behaviour. We repeatedly observed mothers before and after birth. We investigated if pups differ in risk-taking behaviours directly after birth (indicating direct prenatal effects) or only after gaining independence of the mother (indicating delayed prenatal or postnatal effects due to own cue sampling). Furthermore, we tested if different simulated seasons of birth affect social and aggressive behaviour of adult animals. While theoretical predictions according to risk-taking are quite clear, they are contradictory for social behaviours that are much less well studied. We predicted that animals born into spring photoperiods would be aggressive because of a need to gather enough resources for early reproduction and successfully establishing a territory at least in males. Spring-born males were more aggressive than autumn-borns, while females did not differ with respect to season. Spring-born females, however, lost more body mass when they had to integrate into an established group and autumn-born females initiated more aggressive interactions. Our data demonstrate flexible and long-term stable seasonal effects on behaviours that likely affect fitness outcomes under natural conditions.     

Proposed follow up programme after curative resection for lower third oesophageal cancer

Cyclins are indispensable elements of the cell cycle and derangement of their function can lead to cancer formation. Recent studies have also revealed more mechanisms through which cyclins can express their oncogenic potential. This review focuses on the aberrant expression of G1/S cyclins and especially cyclin D and cyclin E; the pathways through which they lead to tumour formation and their involvement in different types of cancer. These elements indicate the mechanisms that could act as targets for cancer therapy.     

Uncertainty in life cycle costing for long-range infrastructure. Part II: guidance and suitability of applied methods to address uncertainty

Life cycle costing (LCC) is the state-of-the-art method to economically evaluate long-term projects over their life spans. However, uncertainty in long-range planning raises concerns about LCC results. In Part I of this series, we developed a holistic framework of the different types of uncertainty in infrastructure LCCs. We also collected methods to address these uncertainties. The aim of Part II is to evaluate the suitability of methods to cope with uncertainty in LCC. Part I addressed two research gaps. It presented a systematic collection of uncertainties and methods in LCC and, furthermore, provided a holistic categorization of both. However, Part I also raised new issues. First, a combined analysis of sources and methods is still outstanding. Such an investigation would reveal the suitability of different methods to address a certain type of uncertainty. Second, what has not been assessed so far is what types of uncertainty are insufficiently addressed in LCC. This would be a feature to improve accuracy of LCC results within LCC, by suggesting options to better cope with uncertainty. To address these research gaps, we conducted a systematic literature review. Part II analyzed the suitability of methods to address uncertainties. The suitability depends on data availability, type of data (tangible, intangible, random, non-random), screened hotspots, and tested modeling specifications. We identified types of uncertainties and methods that have been insufficiently addressed. The methods include probabilistic modeling such as design of experiment or subset simulation and evolutionary algorithm and Bayesian modeling such as the Bayesian latent Markov decision process. Subsequently, we evaluated learning potential from other life cycle assessment (LCA) and life cycle sustainability assessment (LCSA). This analysis revealed 28 possible applications that have not yet been used in LCC. Lastly, we developed best practices for LCC practitioners. This systematic review complements prior research on uncertainty in LCC for infrastructure, as laid out in Part I. Part II concludes that all relevant methods to address uncertainty are currently applied in LCC. Yet, the level of application is different. Moreover, not all methods are equally suited to address different categories of uncertainty. This review offers guidance on what to do for each source and type of uncertainty. It illustrates how methods can address both based on current practice in LCC, LCA, and LCSA. The findings of Part II encourage a dialog between practitioners of LCC, LCA, and LCSA to advance research and practice in uncertainty analysis.