PubRunner: a light-weight framework for updating text mining results

Biomedical text mining promises to assist biologists in quickly navigating the combined knowledge in their domain. This would allow improved understanding of the complex interactions within biological systems and faster hypothesis generation. New biomedical research articles are published daily and text mining tools are only as good as the corpus from which they work. Many text mining tools are underused because their results are static and do not reflect the constantly expanding knowledge in the field. In order for biomedical text mining to become an indispensable tool used by researchers, this problem must be addressed. To this end, we present PubRunner, a framework for regularly running text mining tools on the latest publications. PubRunner is lightweight, simple to use, and can be integrated with an existing text mining tool. The workflow involves downloading the latest abstracts from PubMed, executing a user-defined tool, pushing the resulting data to a public FTP or Zenodo dataset, and publicizing the location of these results on the public PubRunner website. We illustrate the use of this tool by re-running the commonly used word2vec tool on the latest PubMed abstracts to generate up-to-date word vector representations for the biomedical domain. This shows a proof of concept that we hope will encourage text mining developers to build tools that truly will aid biologists in exploring the latest publications

Targeting sorghum improvement in drought-prone environments: Approaches and progress

Grain sorghum is grown in environments of highly variable water supply, both within and between seasons. This variability, coupled with associated genotype-by-environment (GxE) interactions, results in unclear definition of both target environment(s) and traits that may be used as selection criteria, causing slow progress in breeding for drought resistance. This paper reviews new approaches to characterize environments in terms of the incidence of water deficits and to assess the value of traits for improvement of drought resistance. Sorghum simulation models are powerful tools to characterize types of environmental challenges and their frequency of occurrence at different locations. Models also are being used to assess hypotheses about trait action and their value, and to develop optimal combinations of traits for different environmental challenges. Further research involving physiologists, agronomists, and plant breeders using integrated systems analysis will realize the potential of these approaches and improve the efficiency of selection in drought-prone environments

Application of the Hybrid-Maize model for limits to maize productivity analysis in a semiarid environment

Effects of meteorological variables on crop production can be evaluated using various models. We have evaluated the ability of the Hybrid-Maize model to simulate growth, development and grain yield of maize (Zea mays L.) cultivated on the Loess Plateau, China, and applied it to assess effects of meteorological variations on the performance of maize under rain-fed and irrigated conditions. The model was calibrated and evaluated with data obtained from field experiments performed in 2007 and 2008, then applied to yield determinants using daily weather data for 2005-2009, in simulations under both rain-fed and irrigated conditions. The model accurately simulated Leaf Area Index , biomass, and soil water data from the field experiments in both years, with normalized percentage root mean square errors < 25 %. Gr.Y and yield components were also accurately simulated, with prediction deviations ranging from -2.3 % to 22.0 % for both years. According to the simulations, the maize potential productivity averaged 9.7 t ha-1 under rain-fed conditions and 11.53 t ha-1 under irrigated conditions, and the average rain-fed yield was 1.83 t ha-1 less than the average potential yield with irrigation. Soil moisture status analysis demonstrated that substantial potential yield may have been lost due to water stress under rain-fed conditions

BMP-2 Dependent Increase of Soft Tissue Density in Arthrofibrotic TKA

Arthrofibrosis after total knee arthroplasty (TKA) is difficult to treat, as its aetiology remains unclear. In a previous study, we established a connection between the BMP-2 concentration in the synovial fluid and arthrofibrosis after TKA. The hypothesis of the present study was, therefore, that the limited range of motion in arthrofibrosis is caused by BMP-2 induced heterotopic ossifications, the quantity of which is dependent on the BMP-2 concentration in the synovial fluid

Lablab purpureus—A Crop Lost for Africa?

In recent years, so-called ‘lost crops’ have been appraised in a number of reviews, among them Lablab purpureus in the context of African vegetable species. This crop cannot truly be considered ‘lost’ because worldwide more than 150 common names are applied to it. Based on a comprehensive literature review, this paper aims to put forward four theses, (i) Lablab is one of the most diverse domesticated legume species and has multiple uses. Although its largest agro-morphological diversity occurs in South Asia, its origin appears to be Africa. (ii) Crop improvement in South Asia is based on limited genetic diversity. (iii) The restricted research and development performed in Africa focuses either on improving forage or soil properties mostly through one popular cultivar, Rongai, while the available diversity of lablab in Africa might be under threat of genetic erosion. (iv) Lablab is better adapted to drought than common beans (Phaseolus vulgaris) or cowpea (Vigna unguiculata), both of which have been preferred to lablab in African agricultural production systems. Lablab might offer comparable opportunities for African agriculture in the view of global change. Its wide potential for adaptation throughout eastern and southern Africa is shown with a GIS (geographic information systems) approach

Effect of water availability pattern on yield of pearl millet in semi-arid tropical environments

Throughout much of the semi-arid tropics, fluctuations in grain yield can largely be attributed to differences in timing and intensity of drought stress. Since seasonal rainfall in these environments is often poorly related to grain yield, the aim of this paper was to establish a relationship between water availability and grain yield for pearl millet (Pennisetum glaucum (L.) R. Br.), grown across 24 semi-arid tropical environments in India. We used a simple soil water budget to calculate a water satisfaction index (WSI) throughout the season. The cumulative WSI at maturity explained 76% of the variance in grain yield. This was three times as much as explained by actual rainfall, because WSI accounted for differences in water losses and pan evaporation. A classification of environments into four groups of water availability patterns explained 75% of the environmental sum of squares for grain yield. For a subset of 13 environments, environmental differences in grain number could also be explained by water availability patterns, whereas differences in grain mass were related to both water availability and temperature. Our results indicate that cumulative WSI, which is an integrated measure of plant-available water, can provide an adequate estimation of the environmental potential for yield in environments where grain yield is mainly limited by variable availability of water