Rapid activation of Mac-1(CD11b/CD18) molecules on macrophages by a new chemotactic factor 'Gasserokine' produced by Lactobacillus gasseri JCM1131T

The chemoattractant activity of a new chemotactic factor, 'Gasserokine' produced by Lactobacillus gasseri JCM1131^T, has been proposed as a novel immunological function of probiotic lactic acid bacteria. The focus of the present study was to understand the mechanism of the chemotaxis induced by Gasserokine, using activation of an adhesion molecule, Mac-1 (CD11b/CD18) on macrophages. The macrophage chemotaxis to Gasserokine was abolished by preincubation of macrophages with the anti-Mac-1 mAb. Gasserokine induced rapid serine phosphorylation of CD18 molecules within 1 min of stimulation, but the effect was short-lived. Substantial tyrosine phosphorylation was observed in CD18-associated protein of macrophages stimulated by Gasserokine. The tyrosine phosphorylation was confirmed in macrophages stimulated with Gasserokine and also serine/threonine phosphorylation was detected on CD18 molecules by laser microscopy using a double immunostaining method. These results suggest that selective activation of intracellular signaling cascades, such as the mitogen-activated protein kinase pathway, are related to the macrophage chemotaxis induced by Gasserokine.     

Software development for estimating the concentration of radioactive cesium in the skeletal muscles of cattle from blood samples

The 2011 earthquake severely damaged the Fukushima Daiichi Nuclear Power Plant (FNPP), resulting in the release of large quantities of radioactive material into the environment. The deposition of these radionuclides in rice straw as livestock feed led to the circulation of contaminated beef in the market. Based on the safety concern of the consumers, a reliable method for estimating concentrations of radioactive cesium in muscle tissue is needed. In this study, we analyzed the concentrations of radioactive cesium in the blood and skeletal muscle of 88 cattle, and detected a linear correlation between them. We then developed software that can be used to estimate radioactive cesium concentrations in muscle tissue from blood samples. Distribution of this software to the livestock production field would allow us to easily identify high‐risk cattle, which would be beyond the safety regulation, before shipping out to the market. This software is planned to be released as freeware. This software would contribute to food safety, and aid the recovery of the livestock industry from the damage creacted by the 2011 Tohoku earthquake and tsunami.     

Kinetics of endotoxin concentration and tumor necrosis factor-alpha,interleukin-1beta,and interleukin-6 activities in the systemic and portal circulation during small intestinal ischemia and reperfusion in dogs

OBJECTIVE: To determine whether small intestinal ischemia and reperfusion induces bacterial translocation and proinflammatory cytokine response in either the systemic or portal circulation in dogs. ANIMALS: 17 healthy adult Beagles. PROCEDURE: The superior mesenteric artery (SMA) was occluded for 0 (group-3 dogs), 30 (group-1 dogs), or 60 (group-2 dogs) minutes, followed by reperfusion for 180 minutes; serum lactate and endotoxin concentrations and tumor necrosis factor-alpha (TNF-alpha), interleukin-1beta (IL-1beta), and IL-6 activities in the systemic and portal circulation and intramucosal pH were measured at various time points. RESULTS: In group-2 dogs, TNFalpha activity was found to be significantly increased in the portal circulation, peaking at 60 minutes of reperfusion; TNF-alpha activity, in the systemic circulation, gradually increased from 60 minutes of reperfusion to the end of the experiment; however, the increase was not significant. In group-1 and -2 dogs, IL-6 activities significantly and gradually increased in the systemic and portal circulation during the reperfusion phase, and the magnitude of these increases was dependent on the duration of the ischemic phase. There were no significant changes in IL-1beta activity or endotoxin concentration in any dog group. CONCLUSIONS AND CLINICAL RELEVANCE: Results of the our study indicate that intestinal ischemia and reperfusion leads to significant increases of the circulating TNF-alpha and IL-6 activities, depending on the duration of the ischemia phase, in the absence of detectable endotoxin in the circulation. This finding suggests that intestinal ischemia and reperfusion induces a systemic proinflammatory cytokine response in dogs.     

A 39 kDa protein mediates adhesion of avian Pasteurella multocida to chicken embryo fibroblast cells

To clarify the role of avian Pasteurella multocida capsule in pathogenesis, adhesion of capsulated strains P-1059, X-73 and Pm-18, and noncapsulated strains P-1059B, Pm-1 and Pm-3 to chicken embryo fibroblast (CEF) cells was compared. Number of adherent organisms of the capsulated strains to CEF cells were approximately three times as much as noncapsulated strains indicating that adhesive properties were enhanced by the presence of bacterial capsule. Pretreatments of the bacterial cells with heat, trypsin, or with antiserum caused a marked decrease in adhesion of capsulated strain P-1059 and its noncapsulated variant P-1059B. However, depolymerization of capsular hyaluronic acid with high dose of hyaluronidase enhanced adhesion of these strains. Combined treatments of the bacterial cells with both hyaluronidase and trypsin significantly (P < 0.05) inhibited the adherence of strain P-1059 as compared to the treatment only with trypsin, but strain P-1059B was not affected. SDS-PAGE profiles of crude capsular extract (CCE) prepared from capsulated strain P-1059 and its noncapsulated variant P-1059B grown on dextrose starch agar (DSA) plates by heating at 56 degrees C in a 2.5% NaCl solution demonstrated eight protein bands of 28, 34, 36, 39, 52, 56, 63 and 93 kDa. The 28, 34 and 36 kDa proteins were commonly major for both strains, and the 39 kDa protein was major only for strain P-1059 but poor in strain P-1059B. Outer membrane protein (OMP) profiles were identical with a major protein at 34 kDa and four minor proteins between the two strains. The adhesion of strain P-1059 and strain P-1059B to CEF cells was inhibited significantly (P < 0.01) by treatment with rabbit antisera against P-1059, P-1059B, CCE or 39 kDa protein of strain P-1059 as compared to the treatment with either PBS or with normal rabbit serum. These results indicated that an antigenic 39 kDa protein in the capsule may be responsible for adhesion of avian P. multocida type A strains to CEF cells as a virulence factor.     

Comparison of Salmonella enterica serovar Abortusequi isolates of equine origin by pulsed-field gel electrophoresis and fluorescent amplified-fragment length polymorphism fingerprinting

Equine paratyphoid is caused by Salmonella enterica serovar Abortusequi, and manifests mainly as abortion in the mare. We compared S. Abortusequi strains isolated in Japan and other countries using pulsed-field gel electrophoresis (PFGE) and fluorescent amplified-fragment length polymorphism (FAFLP) analysis. PFGE analysis of S. Abortusequi strains gave 21-27 fragments ranging in size from 33 to 602kb. Although two PFGE profiles were observed among the 20 S. Abortusequi isolates in Japan, the restriction fragments originating from the chromosome were common between the two profiles. The similarity index of the two profiles was 90.9%, while those between Japanese and five other S. Abortusequi strains were 29.8-37.5%. On the other hand, FAFLP analysis of S. Abortusequi strains generated 64-67 amplified fragments ranging in size from 100 to 400bp. One polymorphic fragment was observed among the 20 S. Abortusequi isolates in Japan. These data indicate the close relation of this agent in Japan. S. Abortusequi strains sharing a common ancestry might have been conserved in Japan.     

Dairy cattle behavior classifications based on decision tree learning using 3‐axis neck‐mounted accelerometers

Demand has been increasing recently for an automated monitoring system of animal behavior as a tool for the management of livestock animals. This study investigated the association between the behavior of dairy cattle and the acceleration data collected using three‐axis neck‐mounted accelerometers, as well as the feasibility of improving the precision of behavior classifications through machine learning. In total 38 Holstein dairy cows were used, and kept in four different farms. A logger was mounted to each collar to obtain acceleration data for calculating the activity level and variations. At the same time the behavior of the cattle was observed visually. Characteristic acceleration waves were recorded for eating, rumination, and lying, respectively; and the activity level and variations were significantly different among these behaviors (p < 0.01). Decision tree learning was performed on the data set from Farm A and validated its precision; which proved to be 99.2% in cross‐validation, and 100% in test data sets from Farms B to D. This study showed that highly precise classifications for eating, rumination, and lying is possible by using decision tree learning to calculate the activity level and variations of cattle based on the data obtained by three‐axis accelerometers mounted to a collar.     

The smell and odorous components of dried shiitake mushroom, <Emphasis Type="Italic">Lentinula edodes</Emphasis> I: relationship between sensory evaluations and amounts of odorous components

The smell of food is one of the most important factors in assessing its quality. Concerning the smell of dried shiitake mushrooms [Lentinula edodes (Berk.) Pegler], 1,2,3,5,6-pentathiepane, commonly known as lenthionine, has been reported as a key compound. However, other compounds have not been studied sufficiently in connection with smell. From the results of sensory intensity studies and sensory evaluations of dried shiitake mushrooms, a positive significant correlation at 1% risk was observed between sensory intensity and sulfur perception. This showed that the smell of dried shiitake mushrooms was characterized by a sulfurous smell. Also, comparing the sensory intensity with the amounts of volatile components showed positive significant correlations at 1% risk between sensory intensity and three compounds: 1,2,4-trithiolane, 1,2,4,6-tetrathiepane, and lenthionine. Furthermore, significant correlations at 5% risk were obtained between the amounts of these three compounds and sensory intensity by multiple regression analysis. This showed that the smell of dried shiitake mushrooms depended on these compounds. The partial regression coefficient of 1,2,4-trithiolane was larger than those of the others, and so it was proposed that 1,2,4-trithiolane could serve as an indicator to estimate the smell of dried shiitake mushroom.     

Verification for generalizability and accuracy of a thinning-trees selection model with the ensemble learning algorithm and the cross-validation method

For the purpose of making a highly effective model in relation to the selection of trees for thinning for various forestry goals, the author examined the generalizability and accuracy of models using various ensemble learning algorithms and the m-fold cross-validation method. These techniques make it possible to improve discrimination accuracy by combining or integrating multiple learning results whose accuracies are not very high. WEKA, which is a machine learning tool for data mining programmed in Java machine language, was used to verify the results of the simulation models. The number of samples was 503. Pattern-recognition algorithms in this study used five classification-type models and one function-type model. It was found that: (1) without cross validation, two pattern-recognition algorithms can be classified as having comparatively high discrimination accuracy; (2) with cross validation, discrimination accuracy decreased as a whole, but was not very different from that without cross validation, and (3) from the viewpoint of generalizability, we constructed a model at around 70% discrimination accuracy. In order to construct more effective models, we need to design the model to utilize certain algorithms or to build in re-sampling methods such as ensemble learning and cross validation. Additionally, in the case of small sample datasets, ensemble learning is an effective method for constructing efficient models. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.