Radio variability of 1st 3-months Fermi blazars at 5 GHz: affected by interstellar scintillation?

Blazars from the first-three-months Fermi-AGN list were observed with the Urumqi 25m radio telescope at 5GHz in IDV (Intra-Day Variability) mode and inter-month observation mode. A significant correlation between the flux density at 5GHz and the gamma-ray intensity for the Fermi-LAT detected blazars is seen. There is a higher IDV detection rate in Fermi detected blazars than those reported for other samples. Stronger variability appears at lower Galactic latitudes; IDV appears to be stronger in weaker sources, indicating that the variability is affected by interstellar scintillation.Comment: 4 pages, 4 figures, in proceedings of 'Multiwavelength Variability of Blazars' in Guangzhou Uni. of China, 22-24, Sep. 2010, to appear in JA

Development of Photonic Crystal Fiber Based Gas/ Chemical Sensors

The development of highly-sensitive and miniaturized sensors that capable of real-time analytes detection is highly desirable. Nowadays, toxic or colorless gas detection, air pollution monitoring, harmful chemical, pressure, strain, humidity, and temperature sensors based on photonic crystal fiber (PCF) are increasing rapidly due to its compact structure, fast response and efficient light controlling capabilities. The propagating light through the PCF can be controlled by varying the structural parameters and core-cladding materials, as a result, evanescent field can be enhanced significantly which is the main component of the PCF based gas/chemical sensors. The aim of this chapter is to (1) describe the principle operation of PCF based gas/ chemical sensors, (2) discuss the important PCF properties for optical sensors, (3) extensively discuss the different types of microstructured optical fiber based gas/ chemical sensors, (4) study the effects of different core-cladding shapes, and fiber background materials on sensing performance, and (5) highlight the main challenges of PCF based gas/ chemical sensors and possible solutions

Quantum nondemolition measurement of mechanical motion quanta

The fields of opto- and electromechanics have facilitated numerous advances in the areas of precision measurement and sensing, ultimately driving the studies of mechanical systems into the quantum regime. To date, however, the quantization of the mechanical motion and the associated quantum jumps between phonon states remains elusive. For optomechanical systems, the coupling to the environment was shown to preclude the detection of the mechanical mode occupation, unless strong single photon optomechanical coupling is achieved. Here, we propose and analyse an electromechanical setup, which allows to overcome this limitation and resolve the energy levels of a mechanical oscillator. We find that the heating of the membrane, caused by the interaction with the environment and unwanted couplings, can be suppressed for carefully designed electromechanical systems. The results suggest that phonon number measurement is within reach for modern electromechanical setups.Comment: 8 pages, 5 figures plus 24 pages, 11 figures supplemental materia

Identification of disease-causing genes using microarray data mining and gene ontology

Background: One of the best and most accurate methods for identifying disease-causing genes is monitoring gene expression values in different samples using microarray technology. One of the shortcomings of microarray data is that they provide a small quantity of samples with respect to the number of genes. This problem reduces the classification accuracy of the methods, so gene selection is essential to improve the predictive accuracy and to identify potential marker genes for a disease. Among numerous existing methods for gene selection, support vector machine-based recursive feature elimination (SVMRFE) has become one of the leading methods, but its performance can be reduced because of the small sample size, noisy data and the fact that the method does not remove redundant genes. Methods: We propose a novel framework for gene selection which uses the advantageous features of conventional methods and addresses their weaknesses. In fact, we have combined the Fisher method and SVMRFE to utilize the advantages of a filtering method as well as an embedded method. Furthermore, we have added a redundancy reduction stage to address the weakness of the Fisher method and SVMRFE. In addition to gene expression values, the proposed method uses Gene Ontology which is a reliable source of information on genes. The use of Gene Ontology can compensate, in part, for the limitations of microarrays, such as having a small number of samples and erroneous measurement results. Results: The proposed method has been applied to colon, Diffuse Large B-Cell Lymphoma (DLBCL) and prostate cancer datasets. The empirical results show that our method has improved classification performance in terms of accuracy, sensitivity and specificity. In addition, the study of the molecular function of selected genes strengthened the hypothesis that these genes are involved in the process of cancer growth. Conclusions: The proposed method addresses the weakness of conventional methods by adding a redundancy reduction stage and utilizing Gene Ontology information. It predicts marker genes for colon, DLBCL and prostate cancer with a high accuracy. The predictions made in this study can serve as a list of candidates for subsequent wet-lab verification and might help in the search for a cure for cancers

International Veterinary Epilepsy Task Force recommendations for a veterinary epilepsy-specific MRI protocol

Epilepsy is one of the most common chronic neurological diseases in veterinary practice. Magnetic resonance imaging (MRI) is regarded as an important diagnostic test to reach the diagnosis of idiopathic epilepsy. However, given that the diagnosis requires the exclusion of other differentials for seizures, the parameters for MRI examination should allow the detection of subtle lesions which may not be obvious with existing techniques. In addition, there are several differentials for idiopathic epilepsy in humans, for example some focal cortical dysplasias, which may only apparent with special sequences, imaging planes and/or particular techniques used in performing the MRI scan. As a result, there is a need to standardize MRI examination in veterinary patients with techniques that reliably diagnose subtle lesions, identify post-seizure changes, and which will allow for future identification of underlying causes of seizures not yet apparent in the veterinary literature. There is a need for a standardized veterinary epilepsy-specific MRI protocol which will facilitate more detailed examination of areas susceptible to generating and perpetuating seizures, is cost efficient, simple to perform and can be adapted for both low and high field scanners. Standardisation of imaging will improve clinical communication and uniformity of case definition between research studies. A 6–7 sequence epilepsy-specific MRI protocol for veterinary patients is proposed and further advanced MR and functional imaging is reviewed

Characterizing genomic alterations in cancer by complementary functional associations.

Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment. We used REVEALER to uncover complementary genomic alterations associated with the transcriptional activation of β-catenin and NRF2, MEK-inhibitor sensitivity, and KRAS dependency. REVEALER successfully identified both known and new associations, demonstrating the power of combining functional profiles with extensive characterization of genomic alterations in cancer genomes

Klebsiella pneumoniae is able to trigger epithelial-mesenchymal transition process in cultured airway epithelial cells

The ability of some bacterial pathogens to activate Epithelial-Mesenchymal Transition normally is a consequence of the persistence of a local chronic inflammatory response or depends on a direct interaction of the pathogens with the host epithelial cells. In this study we monitored the abilities of the K. pneumoniae to activate the expression of genes related to EMT-like processes and the occurrence of phenotypic changes in airway epithelial cells during the early steps of cell infection. We describe changes in the production of intracellular reactive oxygen species and increased HIF-1α mRNA expression in cells exposed to K. pneumoniae infection. We also describe the upregulation of a set of transcription factors implicated in the EMT processes, such as Twist, Snail and ZEB, indicating that the morphological changes of epithelial cells already appreciable after few hours from the K. pneumoniae infection are tightly regulated by the activation of transcriptional pathways, driving epithelial cells to EMT. These effects appear to be effectively counteracted by resveratrol, an antioxidant that is able to exert a sustained scavenging of the intracellular ROS. This is the first report indicating that strains of K. pneumoniae may promote EMT-like programs through direct interaction with epithelial cells without the involvement of inflammatory cells

Normalizing single-cell RNA sequencing data: challenges and opportunities

Single-cell transcriptomics is becoming an important component of the molecular biologist's toolkit. A critical step when analyzing data generated using this technology is normalization. However, normalization is typically performed using methods developed for bulk RNA sequencing or even microarray data, and the suitability of these methods for single-cell transcriptomics has not been assessed. We here discuss commonly used normalization approaches and illustrate how these can produce misleading results. Finally, we present alternative approaches and provide recommendations for single-cell RNA sequencing users

Observation of Spontaneous Brillouin Cooling

While radiation-pressure cooling is well known, the Brillouin scattering of light from sound is considered an acousto-optical amplification-only process. It was suggested that cooling could be possible in multi-resonance Brillouin systems when phonons experience lower damping than light. However, this regime was not accessible in traditional Brillouin systems since backscattering enforces high acoustical frequencies associated with high mechanical damping. Recently, forward Brillouin scattering in microcavities has allowed access to low-frequency acoustical modes where mechanical dissipation is lower than optical dissipation, in accordance with the requirements for cooling. Here we experimentally demonstrate cooling via such a forward Brillouin process in a microresonator. We show two regimes of operation for the Brillouin process: acoustical amplification as is traditional, but also for the first time, a Brillouin cooling regime. Cooling is mediated by an optical pump, and scattered light, that beat and electrostrictively attenuate the Brownian motion of the mechanical mode.Comment: Supplementary material include

Identification of plasma lipid biomarkers for prostate cancer by lipidomics and bioinformatics

Background: Lipids have critical functions in cellular energy storage, structure and signaling. Many individual lipid molecules have been associated with the evolution of prostate cancer; however, none of them has been approved to be used as a biomarker. The aim of this study is to identify lipid molecules from hundreds plasma apparent lipid species as biomarkers for diagnosis of prostate cancer. Methodology/Principal Findings: Using lipidomics, lipid profiling of 390 individual apparent lipid species was performed on 141 plasma samples from 105 patients with prostate cancer and 36 male controls. High throughput data generated from lipidomics were analyzed using bioinformatic and statistical methods. From 390 apparent lipid species, 35 species were demonstrated to have potential in differentiation of prostate cancer. Within the 35 species, 12 were identified as individual plasma lipid biomarkers for diagnosis of prostate cancer with a sensitivity above 80%, specificity above 50% and accuracy above 80%. Using top 15 of 35 potential biomarkers together increased predictive power dramatically in diagnosis of prostate cancer with a sensitivity of 93.6%, specificity of 90.1% and accuracy of 97.3%. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) demonstrated that patient and control populations were visually separated by identified lipid biomarkers. RandomForest and 10-fold cross validation analyses demonstrated that the identified lipid biomarkers were able to predict unknown populations accurately, and this was not influenced by patient's age and race. Three out of 13 lipid classes, phosphatidylethanolamine (PE), ether-linked phosphatidylethanolamine (ePE) and ether-linked phosphatidylcholine (ePC) could be considered as biomarkers in diagnosis of prostate cancer. Conclusions/Significance: Using lipidomics and bioinformatic and statistical methods, we have identified a few out of hundreds plasma apparent lipid molecular species as biomarkers for diagnosis of prostate cancer with a high sensitivity, specificity and accuracy