Crude oil yield and properties of rice bran oil from different varieties as affected by extraction conditions using soxhterm method

The current study was employed to investigate the effect of solvent type, extraction time and bran ratio on the rice bran oil (RBO) properties from three varieties of rice bran namely Bario, lowland and upland rice. RBO was extracted by using soxtherm extraction method using methanol solvent at different extraction time (3, 4 and 5 h) and bran ratio (10, 20 and 30 g). Free fatty acid (FFA), total phenolic content (TPC) and antioxidant properties were assessed. Solvent that has low polarity exhibited the attraction of polar component of oil with the highest yield by ethanol (16.16%), followed by methanol (15.38%). FFA contents occurred higher in lowland types of rice bran in all types of solvents at P<0.05 with ethanol (12.73%), methanol (11.96%) and hexane (11.13%), while the total phenolic content and antioxidant properties were influenced by the types of rice bran and solvents used for extracting components out of the bran. The highest phenolic content in the crude oil was extracted using ethanol in lowland (0.509 mg/ml), and the lowest was extracted by hexane in Bario (0.061 mg/ml). The highest antioxidant activity was observed in RBO extracted using methanol of lowland (73.74%) and RBO extracted using ethanol of upland (73.65%), while the lowest were observed in RBO extracted using hexane. The different types of solvent have the significant impact on the crude oil yield and properties of crude oil extracted

Nonrandom Distribution of Vector Ticks (Dermacentor variabilis) Infected by Francisella tularensis

The island of Martha's Vineyard, Massachusetts, is the site of a sustained outbreak of tularemia due to Francisella tularensis tularensis. Dog ticks, Dermacentor variabilis, appear to be critical in the perpetuation of the agent there. Tularemia has long been characterized as an agent of natural focality, stably persisting in characteristic sites of transmission, but this suggestion has never been rigorously tested. Accordingly, we sought to identify a natural focus of transmission of the agent of tularemia by mapping the distribution of PCR-positive ticks. From 2004 to 2007, questing D. variabilis were collected from 85 individual waypoints along a 1.5 km transect in a field site on Martha's Vineyard. The positions of PCR-positive ticks were then mapped using ArcGIS. Cluster analysis identified an area approximately 290 meters in diameter, 9 waypoints, that was significantly more likely to yield PCR-positive ticks (relative risk 3.3, P = 0.001) than the rest of the field site. Genotyping of F. tularensis using variable number tandem repeat (VNTR) analysis on PCR-positive ticks yielded 13 different haplotypes, the vast majority of which was one dominant haplotype. Positive ticks collected in the cluster were 3.4 times (relative risk = 3.4, P<0.0001) more likely to have an uncommon haplotype than those collected elsewhere from the transect. We conclude that we have identified a microfocus where the agent of tularemia stably perpetuates and that this area is where genetic diversity is generated

<i>Listeria monocytogenes</i>cross-contamination of cheese: risk throughout the food supply chain

SUMMARYListeria monocytogeneshas been the most common microbial cause of cheese-related recalls in both the United States and Canada in recent years. SinceL. monocytogenesis inactivated by pasteurization, the majority of these cases have been linked to environmental and cross-contamination of fresh-soft, soft-ripened, and semi-soft cheeses. Cross-contamination of foods withL. monocytogenesis a continuous risk throughout the food supply chain and presents unique challenges for subsequent illness and outbreak investigations. Reports on outbreaks of listeriosis attributed to cross-contamination downstream from primary processing help highlight the critical role of epidemiological investigation coupled with coordinated molecular subtyping and surveillance in the recognition and investigation of complex foodborne outbreaks. Despite their complexity, environmental sampling throughout the supply chain coupled with improved genotyping approaches and concomitant analysis of foodborne illness epidemiological exposure data are needed to help resolve these and similar cases more rapidly and with greater confidence.</jats:p

Novel Multiplex Single Nucleotide Polymorphism-Based Method for Identifying Epidemic Clones of Listeria monocytogenes▿

A novel primer extension-based, multiplex minisequencing assay targeting six highly informative single nucleotide polymorphisms (SNPs) in four virulence genes correctly identified and differentiated all four epidemic clones (ECs) of Listeria monocytogenes and 9 other strains initially misclassified as non-ECs. This assay allows rapid, accurate, and high-throughput screening for all known ECs of L. monocytogenes

Modeling of Spatially Referenced Environmental and Meteorological Factors Influencing the Probability of Listeria Species Isolation from Natural Environments ▿

Many pathogens have the ability to survive and multiply in abiotic environments, representing a possible reservoir and source of human and animal exposure. Our objective was to develop a methodological framework to study spatially explicit environmental and meteorological factors affecting the probability of pathogen isolation from a location. Isolation of Listeria spp. from the natural environment was used as a model system. Logistic regression and classification tree methods were applied, and their predictive performances were compared. Analyses revealed that precipitation and occurrence of alternating freezing and thawing temperatures prior to sample collection, loam soil, water storage to a soil depth of 50 cm, slope gradient, and cardinal direction to the north are key predictors for isolation of Listeria spp. from a spatial location. Different combinations of factors affected the probability of isolation of Listeria spp. from the soil, vegetation, and water layers of a location, indicating that the three layers represent different ecological niches for Listeria spp. The predictive power of classification trees was comparable to that of logistic regression. However, the former were easier to interpret, making them more appealing for field applications. Our study demonstrates how the analysis of a pathogen's spatial distribution improves understanding of the predictors of the pathogen's presence in a particular location and could be used to propose novel control strategies to reduce human and animal environmental exposure