Dynamic response of multiple coplanar interface cracks between two dissimilar piezoelectric materials

The linear piezoelectricity theory is applied to investigate the dynamic response of coplanar interface cracks between two dissimilar piezoelectric materials subjected to the mechanical and electrical impacts. The number of cracks is arbitrary, and the interface cracks are assumed to be permeable for electric field. Integral transforms and dislocation density function are employed to reduce the problem to Cauchy singular integral equations. Numerical examples are given to show the effects of crack relative position and material property parameters on the variations of dynamic energy release rate.postprin

Promoter hypermethylation and histone hypoacetylation contribute to pancreatic-duodenal homeobox 1 silencing in gastric cancer

Background and Aims: The expression of pancreatic-duodenal homeobox 1 (PDX1) in gastric cancer is aberrantly reduced. The aim of this study was to elucidate the regulation of DNA methylation and histone acetylation at the promoter for PDX1 silencing in gastric cancer. Methods: PDX1 expression in response to demethylation and acetylation was detected in human gastric cancer cell lines by reverse transcription-polymerase chain reaction (PCR) and western blot. Four CpG islands within the 5#-flanking region of PDX1 gene were analyzed with their transcription activities being detected by dual luciferase assay. Promoter hypermethylation was identified in gastric cancer cell lines and cancer tissues by methylation-specific PCR or bisulfite DNA sequencing PCR analysis. Histone acetylation was determined by chromatin immunoprecipitation (ChIP) assay. Results: Demethylation by 5′-aza-2′-deoxycytidine (5′-aza-dC) and/or acetylation by trichostatin A (TSA) restored PDX1 expression in gastric cancer cells. Hypermethylation was found in four CpG islands in six of seven cancer cell lines. However, only the distal CpG island located in the promoter fragment of PDX1, F383 (c.22063 to 21681 nt upstream of the ATG start codon) displayed significant transcriptional activity that could be suppressed by SssI methylase and increased by 5′-aza-dC and TSA. More than 70% of the single CpG sites in F383 were methylated with hypermethylation of F383 fragment more common in gastric cancerous tissues compared with the paired normal tissues (P < 0.05). ChIP assay showed F383 was also associated with low hypoacetylation level of the histones. Conclusion: Promoter hypermethylation and histone hypoacetylation contribute to PDX1 silencing in gastric cancer. © The Author 2010. Published by Oxford University Press. All rights reserved.postprin

Selection of tuning parameters in bridge regression models via Bayesian information criterion

We consider the bridge linear regression modeling, which can produce a sparse or non-sparse model. A crucial point in the model building process is the selection of adjusted parameters including a regularization parameter and a tuning parameter in bridge regression models. The choice of the adjusted parameters can be viewed as a model selection and evaluation problem. We propose a model selection criterion for evaluating bridge regression models in terms of Bayesian approach. This selection criterion enables us to select the adjusted parameters objectively. We investigate the effectiveness of our proposed modeling strategy through some numerical examples.Comment: 20 pages, 5 figure

Finding related sentence pairs in MEDLINE

We explore the feasibility of automatically identifying sentences in different MEDLINE abstracts that are related in meaning. We compared traditional vector space models with machine learning methods for detecting relatedness, and found that machine learning was superior. The Huber method, a variant of Support Vector Machines which minimizes the modified Huber loss function, achieves 73% precision when the score cutoff is set high enough to identify about one related sentence per abstract on average. We illustrate how an abstract viewed in PubMed might be modified to present the related sentences found in other abstracts by this automatic procedure

Recipes for sparse LDA of horizontal data

Many important modern applications require analyzing data with more variables than observations, called for short horizontal. In such situation the classical Fisher’s linear discriminant analysis (LDA) does not possess solution because the within-group scatter matrix is singular. Moreover, the number of the variables is usually huge and the classical type of solutions (discriminant functions) are difficult to interpret as they involve all available variables. Nowadays, the aim is to develop fast and reliable algorithms for sparse LDA of horizontal data. The resulting discriminant functions depend on very few original variables, which facilitates their interpretation. The main theoretical and numerical challenge is how to cope with the singularity of the within-group scatter matrix. This work aims at classifying the existing approaches according to the way they tackle this singularity issue, and suggest new ones

oA novel nonparametric approach for estimating cut-offs in continuous risk indicators with application to diabetes epidemiology

<p>Abstract</p> <p>Background</p> <p>Epidemiological and clinical studies, often including anthropometric measures, have established obesity as a major risk factor for the development of type 2 diabetes. Appropriate cut-off values for anthropometric parameters are necessary for prediction or decision purposes. The cut-off corresponding to the Youden-Index is often applied in epidemiology and biomedical literature for dichotomizing a continuous risk indicator.</p> <p>Methods</p> <p>Using data from a representative large multistage longitudinal epidemiological study in a primary care setting in Germany, this paper explores a novel approach for estimating optimal cut-offs of anthropomorphic parameters for predicting type 2 diabetes based on a discontinuity of a regression function in a nonparametric regression framework.</p> <p>Results</p> <p>The resulting cut-off corresponded to values obtained by the Youden Index (maximum of the sum of sensitivity and specificity, minus one), often considered the optimal cut-off in epidemiological and biomedical research. The nonparametric regression based estimator was compared to results obtained by the established methods of the Receiver Operating Characteristic plot in various simulation scenarios and based on bias and root mean square error, yielded excellent finite sample properties.</p> <p>Conclusion</p> <p>It is thus recommended that this nonparametric regression approach be considered as valuable alternative when a continuous indicator has to be dichotomized at the Youden Index for prediction or decision purposes.</p

NADPH oxidase and reactive oxygen species contribute to alcohol-induced microglial activation and neurodegeneration

<p>Abstract</p> <p>Background</p> <p>Activation of microglia causes the production of proinflammatory factors and upregulation of NADPH oxidase (NOX) that form reactive oxygen species (ROS) that lead to neurodegeneration. Previously, we reported that 10 daily doses of ethanol treatment induced innate immune genes in brain. In the present study, we investigate the effects of chronic ethanol on activation of NOX and release of ROS, and their contribution to ethanol neurotoxicity.</p> <p>Methods</p> <p>Male C57BL/6 and NF-κB enhanced GFP mice were treated intragastrically with water or ethanol (5 g/kg, i.g., 25% ethanol w/v) daily for 10 days. The effects of chronic ethanol on cell death markers (activated caspase-3 and Fluoro-Jade B), microglial morphology, NOX, ROS and NF-κB were examined using real-time PCR, immunohistochemistry and hydroethidine histochemistry. Also, Fluoro-Jade B staining and NOX gp91^phoximmunohistochemistry were performed in the orbitofrontal cortex (OFC) of human postmortem alcoholic brain and human moderate drinking control brain.</p> <p>Results</p> <p>Ethanol treatment of C57BL/6 mice showed increased markers of neuronal death: activated caspase-3 and Fluoro-Jade B positive staining with Neu-N (a neuronal marker) labeling in cortex and dentate gyrus. The OFC of human post-mortem alcoholic brain also showed significantly more Fluoro-Jade B positive cells colocalized with Neu-N, a neuronal marker, compared to the OFC of human moderate drinking control brain, suggesting increased neuronal death in the OFC of human alcoholic brain. Iba1 and GFAP immunohistochemistry showed activated morphology of microglia and astrocytes in ethanol-treated mouse brain. Ethanol treatment increased NF-κB transcription and increased NOX gp91^phoxat 24 hr after the last ethanol treatment that remained elevated at 1 week. The OFC of human postmortem alcoholic brain also had significant increases in the number of gp91^phox+ immunoreactive (IR) cells that are colocalized with neuronal, microglial and astrocyte markers. In mouse brain ethanol increased gp91^phoxexpression coincided with increased production of O₂^-and O₂^-- derived oxidants. Diphenyleneiodonium (DPI), a NOX inhibitor, reduced markers of neurodegeneration, ROS and microglial activation.</p> <p>Conclusions</p> <p>Ethanol activation of microglia and astrocytes, induction of NOX and production of ROS contribute to chronic ethanol-induced neurotoxicity. NOX-ROS and NF-κB signaling pathways play important roles in chronic ethanol-induced neuroinflammation and neurodegeneration.</p

The projection score - an evaluation criterion for variable subset selection in PCA visualization

<p>Abstract</p> <p>Background</p> <p>In many scientific domains, it is becoming increasingly common to collect high-dimensional data sets, often with an exploratory aim, to generate new and relevant hypotheses. The exploratory perspective often makes statistically guided visualization methods, such as Principal Component Analysis (PCA), the methods of choice. However, the clarity of the obtained visualizations, and thereby the potential to use them to formulate relevant hypotheses, may be confounded by the presence of the many non-informative variables. For microarray data, more easily interpretable visualizations are often obtained by filtering the variable set, for example by removing the variables with the smallest variances or by only including the variables most highly related to a specific response. The resulting visualization may depend heavily on the inclusion criterion, that is, effectively the number of retained variables. To our knowledge, there exists no objective method for determining the optimal inclusion criterion in the context of visualization.</p> <p>Results</p> <p>We present the projection score, which is a straightforward, intuitively appealing measure of the informativeness of a variable subset with respect to PCA visualization. This measure can be universally applied to find suitable inclusion criteria for any type of variable filtering. We apply the presented measure to find optimal variable subsets for different filtering methods in both microarray data sets and synthetic data sets. We note also that the projection score can be applied in general contexts, to compare the informativeness of any variable subsets with respect to visualization by PCA.</p> <p>Conclusions</p> <p>We conclude that the projection score provides an easily interpretable and universally applicable measure of the informativeness of a variable subset with respect to visualization by PCA, that can be used to systematically find the most interpretable PCA visualization in practical exploratory analysis.</p

Increased osteoclastic activity in acute Charcot’s osteoarthopathy: the role of receptor activator of nuclear factor-kappaB ligand

Aims/hypothesis: Our aims were to compare osteoclastic activity between patients with acute Charcot's osteoarthropathy and diabetic and healthy controls, and to determine the effect of the receptor activator of nuclear factor-kappaB ligand (RANKL) and its decoy receptor osteoprotegerin (OPG). Methods: Peripheral blood monocytes isolated from nine diabetic Charcot patients, eight diabetic control and eight healthy control participants were cultured in the presence of macrophage-colony stimulating factor (M-CSF) alone, M-CSF and RANKL, and also M-CSF and RANKL with excess concentrations of OPG. Osteoclast formation was assessed by expression of tartrate-resistant acid phosphatase on glass coverslips and resorption on dentine slices. Results: In cultures with M-CSF, there was a significant increase in osteoclast formation in Charcot patients compared with healthy and diabetic control participants (p=0.008). A significant increase in bone resorption was also seen in the former, compared with healthy and diabetic control participants (p&lt;0.0001). The addition of RANKL to the cultures with M-CSF led to marked increase in osteoclastic resorption in Charcot (from 0.264±0.06% to 41.6±8.1%, p&lt;0.0001) and diabetic control (0.000±0.00% to 14.2±16.5%, p&lt;0.0001) patients, and also in healthy control participants (0.004±0.01% to 10.5±1.9%, p0.0001). Although the addition of OPG to cultures with M-CSF and RANKL led to a marked reduction of resorption in Charcot patients (41.6±8.1% to 5.9±2.4%, p=0.001), this suppression was not as complete as in diabetic control patients (14.2±16.5% to 0.45±0.31%, p=0.001) and in healthy control participants (from 10.5±1/9% to 0.00±0.00%, p&lt;0.0001). Conclusions/interpretation: These results indicate that RANKL-mediated osteoclastic resorption occurs in acute Charcot's osteoarthropathy. However, the incomplete inhibition of RANKL after addition of OPG also suggests the existence of a RANKL-independent pathway