The squeeze film effect on micro-electromechanical resonators

The air squeeze film damping effect on the dynamic responses of clamped micro- electromechanical resonators is investigated in this study. A dynamic model for a clamped micro-electromechanical resonator with the damping consideration is derived using Lagrange’s equation. The corresponding resonator eigen solutions are formulated and solved by employing the assumed-mode method. The effect of different parameters; i.e. the resonator size, ambient temperature and pressure on the squeeze film damping characteristics were simulated and investigated. The results indicate that the squeeze film damping effect may significantly affect the dynamic responses of micro-scale electromechanical resonator

Transcriptome profiling of the fifth-stage larvae of Angiostrongylus cantonensis by next-generation sequencing

Angiostrongylus cantonensis is an important zoonotic nematode. It is the causative agent of eosinophilic meningitis and eosinophilic meningoencephalitis in humans. However, information of this parasite at the genomic level is very limited. In the present study, the transcriptomic profiles of the fifth-stage larvae (L5) of A. cantonensis were investigated by next-generation sequencing (NGS). In the NGS database established from the larvae isolated from the brain of Sprague–Dawley rats, 31,487 unique genes with a mean length of 617 nucleotides were assembled. These genes were found to have a 46.08 % significant similarity to Caenorhabditis elegans by BLASTx. They were then compared with the expressed sequence tags of 18 other nematodes, and significant matches of 36.09–59.12 % were found. Among these genes, 3,338 were found to participate in 124 Kyoto Encyclopedia of Genes and Genomes pathways. These pathways included 1,514 metabolisms, 846 genetic information processing, 358 environmental information processing, 264 cellular processes, and 91 organismal systems. Analysis of 30,816 sequences with the gene ontology database indicated that their annotations included 5,656 biological processes (3,364 cellular processes, 3,061 developmental processes, and 3,191 multicellular organismal processes), 7,218 molecular functions (4,597 binding and 3,084 catalytic activities), and 4,719 cellular components (4,459 cell parts and 4,466 cells). Moreover, stress-related genes (112 heat stress and 33 oxidation stress) and genes for proteases (159) were not uncommon. This study is the first NGS-based study to set up a transcriptomic database of A. cantonensis L5. The results provide new insights into the survival, development, and host–parasite interactions of this blood-feeding nematode. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00436-013-3495-z) contains supplementary material, which is available to authorized users

Resonance in modulation instability from non-instantaneous nonlinearities

To explore resonance phenomena in the nonlinear region, we show by experimental measurements and theoretical analyses that resonance happens in modulation instability (MI) from non-instantaneous nonlinearities in photorefractive crystals. With a temporally periodic modulation in the external bias voltage, corresponding to a modulation in the nonlinear strength, an enhancement in the visibility of MI at resonant frequency is reported through spontaneous optical pattern formations. Modeled by such temporally periodic nonlinear driving force to the system, theoretical curves obtained from a nonlinear non-instantaneous Schr\"{o}dinger equation give good agreement to experimental data. As MI is a universal signature of symmetry-breaking phenomena, our observation on the resonance in MI may provide a control on chaotic, solitary, and turbulence waves.Comment: 5 pages, 4 figure

Extracting density-density correlations from in situ images of atomic quantum gases

We present a complete recipe to extract the density-density correlations and the static structure factor of a two-dimensional (2D) atomic quantum gas from in situ imaging. Using images of non-interacting thermal gases, we characterize and remove the systematic contributions of imaging aberrations to the measured density-density correlations of atomic samples. We determine the static structure factor and report results on weakly interacting 2D Bose gases, as well as strongly interacting gases in a 2D optical lattice. In the strongly interacting regime, we observe a strong suppression of the static structure factor at long wavelengths.Comment: 15 pages, 5 figure

Selection of DDX5 as a novel internal control for Q-RT-PCR from microarray data using a block bootstrap re-sampling scheme

<p>Abstract</p> <p>Background</p> <p>The development of microarrays permits us to monitor transcriptomes on a genome-wide scale. To validate microarray measurements, quantitative-real time-reverse transcription PCR (Q-RT-PCR) is one of the most robust and commonly used approaches. The new challenge in gene quantification analysis is how to explicitly incorporate statistical estimation in such studies. In the realm of statistical analysis, the various available methods of the probe level normalization for microarray analysis may result in distinctly different target selections and variation in the scores for the correlation between microarray and Q-RT-PCR. Moreover, it remains a major challenge to identify a proper internal control for Q-RT-PCR when confirming microarray measurements.</p> <p>Results</p> <p>Sixty-six Affymetrix microarray slides using lung adenocarcinoma tissue RNAs were analyzed by a statistical re-sampling method in order to detect genes with minimal variation in gene expression. By this approach, we identified <it>DDX5 </it>as a novel internal control for Q-RT-PCR. Twenty-three genes, which were differentially expressed between adjacent normal and tumor samples, were selected and analyzed using 24 paired lung adenocarcinoma samples by Q-RT-PCR using two internal controls, <it>DDX5 </it>and <it>GAPDH</it>. The percentage correlation between Q-RT-PCR and microarray were 70% and 48% by using <it>DDX5 </it>and <it>GAPDH </it>as internal controls, respectively.</p> <p>Conclusion</p> <p>Together, these quantification strategies for Q-RT-PCR data processing procedure, which focused on minimal variation, ought to significantly facilitate internal control evaluation and selection for Q-RT-PCR when corroborating microarray data.</p

Mutations in the Salmonella enterica serovar Choleraesuis cAMP-receptor protein gene lead to functional defects in the SPI-1 Type III secretion system

Salmonella enterica serovar Choleraesuis (Salmonella Choleraesuis) causes a lethal systemic infection (salmonellosis) in swine. Live attenuated Salmonella Choleraesuis vaccines are effective in preventing the disease, and isolates of Salmonella Choleraesuis with mutations in the cAMP-receptor protein (CRP) gene (Salmonella Choleraesuis ∆crp) are the most widely used, although the basis of the attenuation remains unclear. The objective of this study was to determine if the attenuated phenotype of Salmonella Choleraesuis ∆crp was due to alterations in susceptibility to gastrointestinal factors such as pH and bile salts, ability to colonize or invade the intestine, or cytotoxicity for macrophages. Compared with the parental strain, the survival rate of Salmonella Choleraesuis ∆crp at low pH or in the presence of bile salts was higher, while the ability of the mutant to invade intestinal epithelia was significantly decreased. In examining the role of CRP on the secretory function of the Salmonella pathogenicity island 1 (SPI-1) encoded type III secretion system (T3SS), it was shown that Salmonella Choleraesuis ∆crp was unable to secrete the SPI-1 T3SS effector proteins, SopB and SipB, which play a role in Salmonella intestinal invasiveness and macrophage cytotoxicity, respectively. In addition, caspase-1 dependent cytotoxicity for macrophages was significantly reduced in Salmonella Choleraesuis ∆crp. Collectively, this study demonstrates that the CRP affects the secretory function of SPI-1 T3SS and the resulting ability to invade the host intestinal epithelium, which is a critical element in the pathogenesis of Salmonella Choleraesuis

Gene expression profiling of breast cancer survivability by pooled cDNA microarray analysis using logistic regression, artificial neural networks and decision trees

BACKGROUND: Microarray technology can acquire information about thousands of genes simultaneously. We analyzed published breast cancer microarray databases to predict five-year recurrence and compared the performance of three data mining algorithms of artificial neural networks (ANN), decision trees (DT) and logistic regression (LR) and two composite models of DT-ANN and DT-LR. The collection of microarray datasets from the Gene Expression Omnibus, four breast cancer datasets were pooled for predicting five-year breast cancer relapse. After data compilation, 757 subjects, 5 clinical variables and 13,452 genetic variables were aggregated. The bootstrap method, Mann–Whitney U test and 20-fold cross-validation were performed to investigate candidate genes with 100 most-significant p-values. The predictive powers of DT, LR and ANN models were assessed using accuracy and the area under ROC curve. The associated genes were evaluated using Cox regression. RESULTS: The DT models exhibited the lowest predictive power and the poorest extrapolation when applied to the test samples. The ANN models displayed the best predictive power and showed the best extrapolation. The 21 most-associated genes, as determined by integration of each model, were analyzed using Cox regression with a 3.53-fold (95% CI: 2.24-5.58) increased risk of breast cancer five-year recurrence… CONCLUSIONS: The 21 selected genes can predict breast cancer recurrence. Among these genes, CCNB1, PLK1 and TOP2A are in the cell cycle G2/M DNA damage checkpoint pathway. Oncologists can offer the genetic information for patients when understanding the gene expression profiles on breast cancer recurrence