Fatigue behavior of dissimilar friction stir welds between cast and wrought aluminum alloys

Cast aluminum alloy, AC4CH-T6, and wrought aluminum alloy, A6061-T6, werejoined by means of friction stir welding (FSW) technique. The effect of microstructure and post heat treatment on fatigue behavior of the dissimilar joints was investigated. Near the weld centre, Vickers hardness was lower than in the parent metals and the hardness minima were observed along the trace route ofFSW tool’s shoulder edge. Tensilefracture tookplace on A6061 side where the hardness was minimal, resulting in the lower static strength of the dissimilar joints than AC4CH or A6061. Fatigue fracture occurred on AC4CH side due to casting defects and the fatigue strength of the dissimilarjoints was similar to that of AC4CH, but lower than that of A6061. Friction stirprocess (FSP) andpost heat treatment successfully improved thefatigue strength of the dissimilarjoints up to that of the parent metal, A6061.Испытания на круговой изгиб для оценки сопротивления усталости проводили на воз­духе и в дистиллированной воде на трех экструзивных магниевых сплавах AZ80, AZ61 и AM60 различного химического сос­тава. На воздухе сопротивление усталости при высоких уровнях напряжений было при­ мерно одинаковым для всех сплавов, по­скольку трещины зарождались у интерме­таллических соединений Al-Mn, тогда как AZ80 с наибольшим содержанием Al имел наибольшее сопротивление усталости при низких уровнях напряжений, что объясня­ется зарождением трещин вследствие циклической деформации скольжения в микро­структуре матрицы. В дистиллированной воде сопротивление усталости значительно снижалось за счет образования коррозион­ных язв во всех сплавах, а различие в сопротивлении усталости при низких уров­ нях напряжений отсутствовало, указывая на то, что добавка Al, улучшавшая сопротив­ление усталости на воздухе, оказывала отрицательное воздействие на коррозион­ную усталость

SNP analysis of the inter-alpha-trypsin inhibitor family heavy chain-related protein (IHRP) gene by a fluorescence-adapted SSCP method

BACKGROUND: Single-nucleotide polymorphisms (SNPs) are considered to be useful polymorphic markers for genetic studies of polygenic traits. Single-stranded conformational polymorphism (SSCP) analysis has been widely applied to detect SNPs, including point mutations in cancer and congenital diseases. In this study, we describe an application of the fluorescent labeling of PCR fragments using a fluorescent-adapted primer for SSCP analysis as a novel method. METHODS: Single-nucleotide polymorphisms (SNPs) of the inter-alpha-trypsin inhibitor family heavy chain-related protein (IHRP) gene were analyzed using a fluorescence-adapted SSCP method. The method was constructed from two procedures: 1) a fluorescent labeling reaction of PCR fragments using fluorescence-adapted primers in a single tube, and 2) electrophoresis on a non-denaturing polyacrylamide gel. RESULTS: This method was more economical and convenient than the single-stranded conformational polymorphism (SSCP) methods previously reported in the detection of the labeled fragments obtained. In this study, eight SNPs of the IHRP gene were detected by the fluorescence-adapted SSCP. One of the SNPs was a new SNP resulting in an amino acid substitution, while the other SNPs have already been reported in the public databases. Six SNPs of the IHRP were associated with two haplotypes. CONCLUSIONS: The fluorescence-adapted SSCP was useful for detecting and genotyping SNPs

First step to facilitate long term and multi centre studies of shear wave elastography in solid breast lesions using a computer assisted algorithm

Purpose: Shear wave elastography (SWE) visualises the elasticity of tissue. As malignant tissue is generally stiffer than benign tissue, SWE is helpful to diagnose solid breast lesions. Until now, quantitative measurements of elasticity parameters have been possible only, while the images were still saved on the ultrasound imaging device. This work aims to overcome this issue and introduces an algorithm allowing fast offline evaluation of SWE images. Methods: The algorithm was applied to a commercial phantom comprising three lesions of various elasticities and 207 in vivo solid breast lesions. All images were saved in DICOM, JPG and QDE (quantitative data export; for research only) format and evaluated according to our clinical routine using a computer-aided diagnosis algorithm. The results were compared to the manual evaluation (experienced radiologist and trained engineer) regarding their numerical discrepancies and their diagnostic performance using ROC and ICC analysis. Results: ICCs of the elasticity parameters in all formats were nearly perfect (0.861–0.990). AUC for all formats was nearly identical for ${E}_{\mathrm{max}}$ and ${E}_{\mathrm{mean}}$ (0.863–0.888). The diagnostic performance of SD using DICOM or JPG estimations was lower than the manual or QDE estimation (AUC 0.673 vs. 0.844). Conclusions: The algorithm introduced in this study is suitable for the estimation of the elasticity parameters offline from the ultrasound system to include images taken at different times and sites. This facilitates the performance of long-term and multi-centre studies

Lack of association between estrogen receptor β dinucleotide repeat polymorphism and autoimmune thyroid diseases in Japanese patients

BACKGROUND: The autoimmune thyroid diseases (AITDs), such as Graves' disease (GD) and Hashimoto's thyroiditis (HT), appear to develop as a result of complex interactions between predisposing genes and environmental triggers. Susceptibility to AITDs is conferred by genes in the human leukocyte antigen (HLA) and genes unlinked to HLA, including the CTLA-4 gene. Recently, estrogen receptor (ER) β, located at human chromosome 14q23-24.1, was identifed. We analyzed a dinucleotide (CA)n repeat polymorphism located in the flanking region of ERβ gene in patients with AITDs and in normal subjects. High heterozygosity makes this polymorphism a useful marker in the genetic study of disorders affecting female endocrine systems. We also correlated a ERβ gene microsatellite polymorphism with bone mineral density (BMD) in the distal radius and biochemical markers of bone turnover in patients with GD in remission. RESULTS: Fourteen different alleles were found in 133 patients with GD, 114 patients with HT, and 179 controls subjects. The various alleles were designated as allele(*)1 through allele(*)14 according to the number of the repeats, from 18 to 30. There was no significant difference in the distributions of ERβ alleles between patient groups and controls. Although recent study demonstrated a significant relation between a allele(*)9 in the ERβ gene and BMD in postmenopausal Japanese women, there were no statistically significant interaction between this allele and BMD in the distal radius, nor biochemical markers in patients with GD in remission. CONCLUSIONS: The present results do not support an association between the ERβ microsatellite marker and AITD in the Japanese population. We also suggest that the ERβ microsatellite polymorphism has at most a minor pathogenic importance in predicting the risk of osteoporosis as a complication of GD

Selection of diagnostic features on breast MRI to differentiate between malignant and benign lesions using computer-aided diagnosis: differences in lesions presenting as mass and non-mass-like enhancement

Purpose: To investigate methods developed for the characterisation of the morphology and enhancement kinetic features of both mass and non-mass lesions, and to determine their diagnostic performance to differentiate between malignant and benign lesions that present as mass versus non-mass types. Methods: Quantitative analysis of morphological features and enhancement kinetic parameters of breast lesions were used to differentiate among four groups of lesions: 88 malignant (43 mass, 45 non-mass) and 28 benign (19 mass, 9 non-mass). The enhancement kinetics was measured and analysed to obtain transfer constant (Ktrans) and rate constant (kep). For each mass eight shape/margin parameters and 10 enhancement texture features were obtained. For the lesions presenting as nonmass-like enhancement, only the texture parameters were obtained. An artificial neural network (ANN) was used to build the diagnostic model. Results: For lesions presenting as mass, the four selected morphological features could reach an area under the ROC curve (AUC) of 0.87 in differentiating between malignant and benign lesions. The kinetic parameter (kep) analysed from the hot spot of the tumour reached a comparable AUC of 0.88. The combined morphological and kinetic features improved the AUC to 0.93, with a sensitivity of 0.97 and a specificity of 0.80. For lesions presenting as non-mass-like enhancement, four texture features were selected by the ANN and achieved an AUC of 0.76. The kinetic parameter kepfrom the hot spot only achieved an AUC of 0.59, with a low added diagnostic value. Conclusion: The results suggest that the quantitative diagnostic features can be used for developing automated breast CAD (computer-aided diagnosis) for mass lesions to achieve a high diagnostic performance, but more advanced algorithms are needed for diagnosis of lesions presenting as non-mass-like enhancement. © The Author(s) 2009

NetMets: software for quantifying and visualizing errors in biological network segmentation

One of the major goals in biomedical image processing is accurate segmentation of networks embedded in volumetric data sets. Biological networks are composed of a meshwork of thin filaments that span large volumes of tissue. Examples of these structures include neurons and microvasculature, which can take the form of both hierarchical trees and fully connected networks, depending on the imaging modality and resolution. Network function depends on both the geometric structure and connectivity. Therefore, there is considerable demand for algorithms that segment biological networks embedded in three-dimensional data. While a large number of tracking and segmentation algorithms have been published, most of these do not generalize well across data sets. One of the major reasons for the lack of general-purpose algorithms is the limited availability of metrics that can be used to quantitatively compare their effectiveness against a pre-constructed ground-truth. In this paper, we propose a robust metric for measuring and visualizing the differences between network models. Our algorithm takes into account both geometry and connectivity to measure network similarity. These metrics are then mapped back onto an explicit model for visualization

Modification of neuropathic pain sensation through microglial ATP receptors

Neuropathic pain that typically develops when peripheral nerves are damaged through surgery, bone compression in cancer, diabetes, or infection is a major factor causing impaired quality of life in millions of people worldwide. Recently, there has been a rapidly growing body of evidence indicating that spinal glia play a critical role in the pathogenesis of neuropathic pain. Accumulating findings also indicate that nucleotides play an important role in neuron-glia communication through P2 purinoceptors. Damaged neurons release or leak nucleotides including ATP and UTP to stimulate microglia through P2 purinoceptors expressing on microglia. It was shown in an animal model of neuropathic pain that microglial P2X4 and P2X7 receptors are crucial in pain signaling after peripheral nerve lesion. In this review, we describe the modification of neuropathic pain sensation through microglial P2X4 and P2X7, with the possibility of P2Y6 and P2Y12 involvement