Strength Characteristics of Weathered Granite

Weathered granite, which widely distributed in Japan, was tested by a triaxial testing apparatus to investigate its mechanical properties in the consolidated-undrained condition. This rock, classified as a soft rock, causes much trouble in the construction of civil engineering structures. However, its mechanical behavior has not been studied enough to understand the strength characteristics. In this paper, it was found that the general behavior of the weathered granite was very similar to that of clay. The comparison between these materials has been discussed. The strength parameters were obtained from yield points which were defined by two different methods. The physical meanings of these yield points were also discussed

Creep Deformation Characteristics of Weathered Granite

Creep deformation characteristics of weathered granite were studied. While displacement of a structure on foundation rock is the main concern of foundation designers, the mechanical and especially the time dependent properties of weathered granite, which is being used recently as a foundation rock in Japan, have not been investigated so much. The test results show that the behavior of soft rock is very similar to that of soil. The time dependent deformation in soft rock can be predicted by a simple stress-strain-time function or rheological models. The time to failure under a sustained creep load was also discussed in relation to the strength of weathered granite

Oral Tolerance Induced by Transfer of Food Antigens via Breast Milk of Allergic Mothers Prevents Offspring from Developing Allergic Symptoms in a Mouse Food Allergy Model

We examined whether maternal exposure to food antigens during lactation and maternal allergic status would affect the development of food allergy in offspring. OVA-sensitized or OVA-nonsensitized BALB/c female mice were exposed or unexposed to OVA during lactation. After weaning, their offspring were systemically sensitized twice with OVA and repeatedly given OVA by oral intubation. While 97.1% of the mice breastfed by OVA-nonsensitized and OVA-unexposed mothers developed allergic diarrhea, 59.7% of the mice breastfed by OVA-exposed nonallergic mothers during lactation and 24.6% of the mice breastfed by OVA-exposed allergic mothers during lactation developed food allergy. Furthermore, OVA was detected in breast-milk from OVA-exposed nonallergic mothers during lactation (4.6 ± 0.5 μg/mL). In addition, OVA-specific IgG1 titers were markedly increased in breast milk from allergic mothers (OVA-sensitized and OVA-unexposed mother: 11.0 ± 0.5, OVA-sensitized and OVA-exposed mother: 12.3 ± 0.3). Our results suggest that oral tolerance induced by breast milk-mediated transfer of dietary antigens along with their specific immunoglobulins to offspring leads to antigen-specific protection from food allergy

Discriminative application of string similarity methods to chemical and non-chemical names for biomedical abbreviation clustering

BACKGROUND: Various computational methods are presently available to classify whether a protein variation is disease-associated or not. However data derived from recent technological advancements make it feasible to extend the annotation of disease-associated variations in order to include specific phenotypes. Here we tackle the problem of distinguishing between genetic variations associated to cancer and variations associated to other genetic diseases. RESULTS: We implement a new method based on Support Vector Machines that takes as input the protein variant and the protein function, as described by its associated Gene Ontology terms. Our approach succeeds in discriminating between germline variants that are likely to be cancer-associated from those that are related to other genetic disorders. The method performs with values of 90% accuracy and 0.61 Matthews correlation coefficient on a set comprising 6478 germline variations (16% are cancer-associated) in 592 proteins. The sensitivity and the specificity on the cancer class are 69% and 66%, respectively. Furthermore the method is capable of correctly excluding some 96% of 3392 somatic cancer-associated variations in 1983 proteins not included in the training/testing set. CONCLUSIONS: Here we prove feasible that a large set of cancer associated germline protein variations can be successfully discriminated from those associated to other genetic disorders. This is a step further in the process of protein variant annotation. Scoring largely improves when protein function as encoded by Gene Ontology terms is considered, corroborating the role of protein function as a key feature for a correct annotation of its variations

The aim of the measurement of Epstein‐Barr virus DNA in hydroa vacciniforme and hypersensitivity to mosquito bites

Epstein‐Barr virus (EBV) DNA load in the blood increases in posttransplant lymphoproliferative disorders and chronic active EBV infection. In this report, we analyzed the EBV DNA load in the peripheral blood mononuclear cells (PBMCs) and plasma of patients with hydroa vacciniforme (HV) and/or hypersensitivity to mosquito bites (HMB) to understand the clinical significance of EBV DNA load. All 30 patients showed high DNA loads in the PBMCs over the cut‐off level. Of 16 plasma samples, extremely high in two samples obtained from patients with hemophagocytic lymphohistiocytosis (HLH). The amount of cell‐free DNA in plasma was correlated to the serum levels of lactate dehydrogenase and inversely correlated to platelet counts. These results indicate that the EBV DNA load in PBMCs can provide one of the diagnostic indicators for HV and HMB and marked elevation of cell‐free EBV DNA in plasma might be related to cytolysis such as that observed in HLH

Reliable outlier detection by spectral clustering on Riemannian manifold of EEG covariance matrix

International audienceIntroduction: Automatically identifying and rejecting artifact-contaminated trials is a key problem to design robust BCIs. Here, we propose a novel outlier detection method based on Riemannian Geometry (RG), a promising approach for BCI classification [1]. With RG, EEG signals are represented and processed as Sample Covariance Matrix (SCM), which is also known to reduce EEG artifacts influence. State-of-the-art outlier detection methods in RG include Riemannian Potato (RP) [2] and Median-Based Trimming (MBT) [3]. However, both suffer from the need of a threshold to determine outliers, and both always reject some samples as outliers, even when there is none. Thus, we propose Riemannian Spectral Clustering (RiSC), to detect outliers by clustering SCMs into non-outliers and outliers by similarity, without thresholds. Material, Methods and Results: First, RiSC computes the graph of SCMs similarities using the Riemannian distance between SCMs. Then, the graph nodes are clustered using spectral clustering [4], and all clusters except the most numerous one are rejected as outliers. We compared the classification accuracy of a Minimum Distance to Mean classifier [1] without outlier rejection (baseline) and after rejecting outliers from each class training data using RP, MBT and RiSC. We used EEG signals from 78 subjects from [5, 6], who performed right or left-hand motor imagery. The first two runs were used for training and the remaining runs for testing. Results showed no significant differences between methods (repeated measure ANOVA, p = 0.093). Mean classification accuracy (%) was 59.5±10.2, 59.8±10.1, 59.4±9.99 and 59.5±10.1 for the baseline, RiSC, RP and MBT respectively. Discussion: RiSC did not detect any outlier for most (68 out of 78) subjects. However, when it removed outliers, this increased accuracy for all but one subject (mean gain: 2.39 ± 2.24 %). On the other hand, RP and MBT detected outliers in all subjects, but this decreased accuracy for 46 and 34 out of 78 subjects respectively. Discussion: RiSC did not detect outlier for most subjects, which may suggest EEG contamination was already reduced using SCM. Thus, RiSC might be useful on more contaminated data. Contrary to RP and MBT, RiSC did not inadvertently reduce accuracy by rejecting clean data as outliers. Significance: Describing EEG as SCMs and detecting their outliers by spectral clustering seem to be a robust method that usually does not lead to inadvertent decrease in classification accuracy

Soluble Siglec-9 suppresses arthritis in a collagen-induced arthritis mouse model and inhibits M1 activation of RAW264.7 macrophages

Background: The aim of this study was to assess the effects of soluble sialic acid-binding immunoglobulin-type lectin (sSiglec)-9 on joint inflammation and destruction in a murine collagen-induced arthritis (CIA) model and in monolayer cultures of murine macrophages (RAW264.7 cells and peritoneal macrophages) and fibroblast-like synoviocytes (FLS) derived from patients with rheumatoid arthritis. Methods: DBA/1J mice were immunized with type II collagen. Effects of sSiglec-9 were evaluated using a physiologic arthritis score, histological analysis, serum tumor necrosis factor (TNF)-α concentration, and the proportion of forkhead box P3 (Foxp3)-positive regulatory T (Treg) cells. In vivo biofluorescence imaging was used to assess the distribution of sSiglec-9. Levels of M1 (TNF-α, interleukin [IL]-6, and inducible nitric oxide synthase) and M2 (CD206, Arginase-1, and IL-10) macrophage markers and phosphorylation of intracellular signaling molecules were examined in macrophages, and levels of matrix metalloproteinase (MMP)-1, MMP-3, and MMP-13 were examined in FLS. Results: sSiglec-9 significantly suppressed the clinical and histological incidence and severity of arthritis. The proportion of Foxp3-positive Treg cells significantly improved and serum TNF-α concentration decreased in vivo. Although sSiglec-9 reduced the expression of M1 markers in macrophages, it did not affect the expression of M2 markers and MMPs in FLS. Nuclear factor (NF)-kB p65 phosphorylation was attenuated by sSiglec-9, and chemical blockade of the NF-kB pathway reduced M1 marker expression in RAW264.7 cells. Conclusions: In this study, we have demonstrated the therapeutic effects of sSiglec-9 in a murine CIA model. The mechanism underlying these effects involves the suppression of M1 proinflammatory macrophages by inhibiting the NF-kB pathway. sSiglec-9 may provide a novel therapeutic option for patients with rheumatoid arthritis refractory to currently available drugs