Screening of 42 Bacillus isolates for ability to ferment soybeans into dawadawa

Forty-two cultures of Bacillus species isolated from soybean dawadawa were screened for their proteolytic activity on Skim Milk Agar, amylolytic activity on Starch Agar, and ability to grow on Soybean Agar. Distinct differences were observed between the cultures for all the criteria. Eleven isolates were selected for laboratory fermentation trials and each produced soybean dawadawa which was found acceptable by a taste panel. The pH of the samples, which increased from 6.37-6.58 to 8.22-8.85 during fermentation, were significantly different at P< or =0.05 for the different cultures. In the fermented samples, Bacillus counts exceeded 10(9) cfu/g, with the population of only one sample being significantly different at P< or =0.05. A market focus group familiar with soybean dawadawa selected Bacillus subtilis 24BP(2) and B. subtilis FpdP(2) as the best potential starter cultures. A taste panel found no significant differences in overall acceptance between soybean dawadawa either fermented spontaneously or with B. subtilis 24BP(2) and also between soybean dawadawa fermented with either B. subtilis 24BP(2) or B. subtilis FpdP(2).     

“Arbequina” Olive Oil Composition Is Affected by the Application of Regulated Deficit Irrigation during Pit Hardening Stage

Three new regulated deficit irrigation (RDI) treatments were applied to “Arbequina” olive orchards during pit hardening. Oil quality was determined by measuring analytical parameters for olive oil grading, antioxidant activity, total phenol content, fatty acid profile, volatile compounds profile, and sensory analysis. Oils from RDI were classified as “extra virgin olive oil” and their quality was improved due to their higher antioxidant potential (ABTS⁺ [increased ~75%] and DPPH^˙ [increased ~25%] assays) and phenols (increased ~53%) than control. Concentration of total volatile compounds decreased (~27%) but RDI olive oils showed a more balanced profile (alcohols, aldehydes, and esters). Monounsaturated fatty acid content increased (~5%) and atherogenic and thrombogenic indexes decreased (~8.5%) in RDI olive oil. Regarding sensory analysis, RDI provided more balanced oils with higher fruit aroma than control. Other benefits of RDI olive oil, when compared with oil from full irrigated orchards are reduced use of water and improved functional and sensory quality.     

Lactobacillus casei strains isolated from cheese reduce biogenic amine accumulation in an experimental model

Tyramine and histamine are the biogenic amines (BAs) most commonly found in cheese, in which they appear as a result of the microbial enzymatic decarboxylation of tyrosine and histidine respectively. Given their toxic effects, their presence in high concentrations in foods should be avoided. In this work, samples of three cheeses (Zamorano, Cabrales and Emmental) with long ripening periods, and that often have high BA concentrations, were screened for the presence of BA-degrading lactic acid bacteria (LAB). Seventeen isolates were found that were able to degrade tyramine and histamine in broth culture. All 17 isolates were identified by 16S rRNA sequencing as belonging to Lactobacillus casei. They were typed by plasmid S1-PFGE and genomic macrorestriction-PFGE analysis. Two strains (L. casei 4a and 5b) associated with high degradation rates for both BAs were selected to test how this ability might affect histamine and tyramine accumulation in a Cabrales-like mini-cheese manufacturing model. The quantification of BAs and the monitoring of the strains' growth over ripening were undertaken by RP-HPLC and qPCR respectively. Both strains were found to reduce histamine and tyramine accumulation. These two strains might be suitable for use as adjunct cultures for reducing the presence of BAs in cheese.     

Evaluation of a screening method for classifying virgin and recycled paper and board samples

This paper deals with the study of volatile compounds released by recycled paper and board. The aim of the study was to demonstrate the feasibility of headspace procedure coupled to gas chromatography/mass spectrometry (GC/MS) applied to complex paper‐based samples together with a chemometric procedure as a powerful method for screening potential volatile contaminants released by the recycled and virgin paper samples. Using this procedure, the identification of virgin or recycled paper could be achieved based on the identification on specific markers of the recycled pulp. Fifteen different samples within virgin and recycled paper were studied. After equilibration, the vapour phase of the samples was analysed by automatic headspace coupled online to GC/MS. The analytical approach for volatile compounds, their identification and the selection of some compounds as markers for recycled pulp are shown and discussed. A discriminate analysis applied to the set of results obtained allows classification of the samples into four different groups according to the content of recycled pulp (0, 10–30 and > 80% of recycled pulp), the surface treatment of the paper (no surface treatment, clay coating and plastic coating), the grammage (from < 100 to > 300 g/m²) and the sample thickness (from < 300 to > 600 µm). The matrix effect on the volatilization of some compounds from the paper samples and the analytical behaviour are also discussed. Copyright © 2009 John Wiley & Sons, Ltd.     

Bootstrap prediction intervals in state–space models

Abstract.  Prediction intervals in state–space models can be obtained by assuming Gaussian innovations and using the prediction equations of the Kalman filter, with the true parameters substituted by consistent estimates. This approach has two limitations. First, it does not incorporate the uncertainty caused by parameter estimation. Second, the Gaussianity of future innovations assumption may be inaccurate. To overcome these drawbacks, Wall and Stoffer [ Journal of Time Series Analysis (2002) Vol. 23, pp. 733–751] propose a bootstrap procedure for evaluating conditional forecast errors that requires the backward representation of the model. Obtaining this representation increases the complexity of the procedure and limits its implementation to models for which it exists. In this article, we propose a bootstrap procedure for constructing prediction intervals directly for the observations, which does not need the backward representation of the model. Consequently, its application is much simpler, without losing the good behaviour of bootstrap prediction intervals. We study its finite-sample properties and compare them with those of the standard and the Wall and Stoffer procedures for the local level model. Finally, we illustrate the results by implementing the new procedure to obtain prediction intervals for future values of a real time series.     

Prediction of botanical composition in grassland herbage samples by near infrared reflectance spectroscopy

Near infrared reflectance spectroscopy (NIRS) was evaluated as a method to predict the botanical composition of seminatural grassland in ‘dehesa’ systems. Samples of herbaceous biomass were harvested over four consecutive years, determining in each—by manual separation—the proportion by weight of the following taxonomic groups: grasses, legumes and the rest of the families in a single block (‘others’). After reconstructing the natural samples they were analysed by NIRS. One set of samples (calibration set) was selected for the development of the equations, assaying different mathematical treatments (log l/R, first derivative and second derivative). The ranges of coefficients of multiple determination and standard errors of calibration, respectively, for the various components were: grasses, 0.86 to 0.92 and 6.66 to 9.14; legumes, 0.77 to 0.81 and 6.82 to 7.43; and ‘others’, 0.85 to 0.88 and 8.17 to 9.54. The remaining samples not included in the development of the NIRS equations (prediction set) were used for the purposes of validating the best equations. Standard errors of performance were: grasses, 6.12; legumes, 7.56 and ‘others’, 7.70.     

Risk factors for cognitive impairment in epilepsy.

The literature suggests that seizure disorders are associated with an increased likelihood of intellectual problems, prompting researchers to investigate risk factors of cognitive impairment in epileptic patients. This study examined the contribution of certain variables (age of seizure onset, duration, etiology, seizure location and laterality, sex, handedness, and cerebral speech pattern) to cognitive outcome in patients with medically refractory seizures. Seizure location (temporal or extratemporal), age of onset of seizures, and handedness proved to be the best indicators of general intellectual ability. There was a relatively diverse pattern of relationships when neuropsychological tests of language, visuospatial ability, and memory were considered individually. However, a factor analytic approach revealed a simpler pattern in which location of dysfunction, age at seizure onset, hand preference, cerebral speech dominance, and gender were relevant and independent indicators of verbal and nonverbal ability. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Analysis of extractables from one euphorbia

Chemical analyses have been made of the heptane extractable material ofEuphorbia lathyris, a plant which has been proposed as an “energy farm” candidate. The heptane extract is 4–5% of the dry plant weight and has a heat value of ≈18×10³ BTU/Ib. This reduced photosynthetic material consists almost entirely of polycyclic triterpenoids.     

Grid Data Management: Open Problems and New Issues

Initially developed for the scientific community, Grid computing is now gaining much interest in important areas such as enterprise information systems. This makes data management critical since the techniques must scale up while addressing the autonomy, dynamicity and heterogeneity of the data sources. In this paper, we discuss the main open problems and new issues related to Grid data management. We first recall the main principles behind data management in distributed systems and the basic techniques. Then we make precise the requirements for Grid data management. Finally, we introduce the main techniques needed to address these requirements. This implies revisiting distributed database techniques in major ways, in particular, using P2P techniques. Work partially funded by ARA “Massive Data” of the French ministry of research (project Respire), the European Strep Grid4All project, the CAPES–COFECUB Daad project and the CNPq–INRIA Gridata project.     

The Role of Circulating Biomarkers in Peripheral Arterial Disease

Peripheral arterial disease (PAD) of the lower extremities is a chronic illness predominantly of atherosclerotic aetiology, associated to traditional cardiovascular (CV) risk factors. It is one of the most prevalent CV conditions worldwide in subjects >65 years, estimated to increase greatly with the aging of the population, becoming a severe socioeconomic problem in the future. The narrowing and thrombotic occlusion of the lower limb arteries impairs the walking function as the disease progresses, increasing the risk of CV events (myocardial infarction and stroke), amputation and death. Despite its poor prognosis, PAD patients are scarcely identified until the disease is advanced, highlighting the need for reliable biomarkers for PAD patient stratification, that might also contribute to define more personalized medical treatments. In this review, we will discuss the usefulness of inflammatory molecules, matrix metalloproteinases (MMPs), and cardiac damage markers, as well as novel components of the liquid biopsy, extracellular vesicles (EVs), and non-coding RNAs for lower limb PAD identification, stratification, and outcome assessment. We will also explore the potential of machine learning methods to build prediction models to refine PAD assessment. In this line, the usefulness of multimarker approaches to evaluate this complex multifactorial disease will be also discussed.