Isolated Phosphate-Solubilizing Soil Bacteria Promotes In vitro Growth of Solanum tuberosum L.

The capacity of four bacterial strains isolated from productive soil potato fields to solubilize tricalcium phosphate on Pikovskaya agar or in a liquid medium was evaluated. A bacterial strain was selected to evaluate in vitro capacity of plant-growth promotion on Solanum tuberosum L. culture. Bacterial strain A3 showed the highest value of phosphate solubilization, reaching a 20 mm-diameter halo and a concentration of 350 mg/l on agar and in a liquid medium, respectively. Bacterial strain A3 was identified by 16S rDNA analysis as Bacillus pumilus with 98% identity; therefore, it is the first report for Bacillus pumilus as phosphate solubilizer. Plant-growth promotion assayed by in vitro culture of potato microplants showed that the addition of bacterial strain A3 increased root and stems length after 28 days. It significantly increased stem length by 79.3%, and duplicated the fresh weight of control microplants. In this paper, results reported regarding phosphorus solubilization and growth promotion under in vitro conditions represent a step forward in the use of innocuous bacterial strain biofertilizer on potato field cultures.Key words: Bacillus sp., phosphorus soluble, Pikovskaya agar, potato rhizosphere, plant growth promoting rhizobacteria     

First molecular identification of the vertebrate hosts of Culicoides imicola in Europe and a review of its blood‐feeding patterns worldwide: implications for the transmission of bluetongue disease and African horse sickness

Culicoides (Diptera: Ceratopogonidae) are vectors of pathogens that affect wildlife, livestock and, occasionally, humans. Culicoides imicola (Kieffer, 1913) is considered to be the main vector of the pathogens that cause bluetongue disease (BT) and African horse sickness (AHS) in southern Europe. The study of blood‐feeding patterns in Culicoides is an essential step towards understanding the epidemiology of these pathogens. Molecular tools that increase the accuracy and sensitivity of traditional methods have been developed to identify the hosts of potential insect vectors. However, to the present group's knowledge, molecular studies that identify the hosts of C. imicola in Europe are lacking. The present study genetically characterizes the barcoding region of C. imicola trapped on farms in southern Spain and identifies its vertebrate hosts in the area. The report also reviews available information on the blood‐feeding patterns of C. imicola worldwide. Culicoides imicola from Spain feed on blood of six mammals that include species known to be hosts of the BT and AHS viruses. This study provides evidence of the importance of livestock as sources of bloodmeals for C. imicola and the relevance of this species in the transmission of BT and AHS viruses in Europe.     

Marine polyprenylated hydroquinones, quinones, and chromenols with inhibitory effects on leukotriene formation

A series of polyprenylated hydroquinones, quinones, and chromenols were isolated from the extracts of the marine sponge Ircinia spinosula and the brown alga Taonia atomaria, which gave rise to the constituents 1-4 and 5-8, respectively. Compounds 1, 2, 6, and 7 are new natural products, which were fully characterized. Their anti-inflammatory activities in terms of leukotriene formation were evaluated in an in vitro assay with pork leukocytes. The new hydroxylated compound, 2'-[28-hydroxy]heptaprenyl-1',4'-hydroquinone (= 2-[(2E,6E,10E,14E,18Z,22E)-19-(hydroxymethyl)-3,7,11,15,23,27-hexamethyloctacosa-2,6,10,14,18,22,26-heptaen-1-yl]benzene-1,4-diol; 1), the known tetraprenyl benzoquinone sargaquinone (5), and the known polyprenyl chromenols 3 and 4 exhibited the highest anti-inflammatory activities, with IC50 values of 1.9-9.4 microM (Table 3). Potential structure-activity relationships (SAR) are discussed.     

Semiparametric mixed-scale models using shared Bayesian forests

This paper demonstrates the advantages of sharing information about unknown features of covariates across multiple model components in various nonparametric regression problems including multivariate, heteroscedastic, and semicontinuous responses. In this paper, we present a methodology which allows for information to be shared nonparametrically across various model components using Bayesian sum-of-tree models. Our simulation results demonstrate that sharing of information across related model components is often very beneficial, particularly in sparse high-dimensional problems in which variable selection must be conducted. We illustrate our methodology by analyzing medical expenditure data from the Medical Expenditure Panel Survey (MEPS). To facilitate the Bayesian nonparametric regression analysis, we develop two novel models for analyzing the MEPS data using Bayesian additive regression trees—a heteroskedastic log-normal hurdle model with a “shrink-toward-homoskedasticity” prior and a gamma hurdle model.