Many-particle entanglement with Bose--Einstein condensates

We propose a method to produce entangled states of several particles starting from a Bose-Einstein condensate. In the proposal, a single fast $\pi/2$ pulse is applied to the atoms and due to the collisional interaction, the subsequent free time evolution creates an entangled state involving all atoms in the condensate. The created entangled state is a spin-squeezed state which could be used to improve the sensitivity of atomic clocks.Comment: 4 pages. Minor modification

Correlation between nucleotide composition and folding energy of coding sequences with special attention to wobble bases

Background: The secondary structure and complexity of mRNA influences its accessibility to regulatory molecules (proteins, micro-RNAs), its stability and its level of expression. The mobile elements of the RNA sequence, the wobble bases, are expected to regulate the formation of structures encompassing coding sequences. Results: The sequence/folding energy (FE) relationship was studied by statistical, bioinformatic methods in 90 CDS containing 26,370 codons. I found that the FE (dG) associated with coding sequences is significant and negative (407 kcal/1000 bases, mean +/- S.E.M.) indicating that these sequences are able to form structures. However, the FE has only a small free component, less than 10% of the total. The contribution of the 1st and 3rd codon bases to the FE is larger than the contribution of the 2nd (central) bases. It is possible to achieve a ~ 4-fold change in FE by altering the wobble bases in synonymous codons. The sequence/FE relationship can be described with a simple algorithm, and the total FE can be predicted solely from the sequence composition of the nucleic acid. The contributions of different synonymous codons to the FE are additive and one codon cannot replace another. The accumulated contributions of synonymous codons of an amino acid to the total folding energy of an mRNA is strongly correlated to the relative amount of that amino acid in the translated protein. Conclusion: Synonymous codons are not interchangable with regard to their role in determining the mRNA FE and the relative amounts of amino acids in the translated protein, even if they are indistinguishable in respect of amino acid coding.Comment: 14 pages including 6 figures and 1 tabl

Semi-supervised discovery of differential genes

BACKGROUND: Various statistical scores have been proposed for evaluating the significance of genes that may exhibit differential expression between two or more controlled conditions. However, in many clinical studies to detect clinical marker genes for example, the conditions have not necessarily been controlled well, thus condition labels are sometimes hard to obtain due to physical, financial, and time costs. In such a situation, we can consider an unsupervised case where labels are not available or a semi-supervised case where labels are available for a part of the whole sample set, rather than a well-studied supervised case where all samples have their labels. RESULTS: We assume a latent variable model for the expression of active genes and apply the optimal discovery procedure (ODP) proposed by Storey (2005) to the model. Our latent variable model allows gene significance scores to be applied to unsupervised and semi-supervised cases. The ODP framework improves detectability by sharing the estimated parameters of null and alternative models of multiple tests over multiple genes. A theoretical consideration leads to two different interpretations of the latent variable, i.e., it only implicitly affects the alternative model through the model parameters, or it is explicitly included in the alternative model, so that the interpretations correspond to two different implementations of ODP. By comparing the two implementations through experiments with simulation data, we have found that sharing the latent variable estimation is effective for increasing the detectability of truly active genes. We also show that the unsupervised and semi-supervised rating of genes, which takes into account the samples without condition labels, can improve detection of active genes in real gene discovery problems. CONCLUSION: The experimental results indicate that the ODP framework is effective for hypotheses including latent variables and is further improved by sharing the estimations of hidden variables over multiple tests

EBV-Encoded LMP1 Upregulates Igκ 3′Enhancer Activity and Igκ Expression in Nasopharyngeal Cancer Cells by Activating the Ets-1 through ERKs Signaling

Accumulating evidence indicates that epithelial cancer cells, including nasopharyngeal carcinoma (NPC) cells, express immunoglobulins (Igs). We previously found that the expression of the kappa light chain protein in NPC cells can be upregulated by the EBV-encoded latent membrane protein 1 (LMP1). In the present study, we used NPC cell lines as models and found that LMP1-augmented kappa production corresponds with elevations in ERKs phosphorylation. PD98059 attenuates LMP1-induced ERKs phosphorylation resulting in decreased expression of the kappa light chain. ERK-specific small interfering RNA blunts LMP1-induced kappa light chain gene expression. Luciferase reporter assays demonstrate that immunoglobulin κ 3′ enhancer (3′Eκ) is active in Igκ-expressing NPC cells and LMP1 upregulates the activity of 3′Eκ in NPC cells. Moreover, mutation analysis of the PU binding site in 3′Eκ and inhibition of the MEK/ERKs pathway by PD98059 indicate that the PU site is functional and LMP1-enhanced 3′Eκ activity is partly regulated by this site. PD98059 treatment also leads to a concentration-dependent inhibition of LMP1-induced Ets-1 expression and phosphorylation, which corresponds with a dose-dependent attenuation of LMP1-induced ERK phosphorylation and kappa light chain expression. Suppression of endogenous Ets-1 by small interfering RNA is accompanied by a decrease of Ig kappa light chain expression. Gel shift assays using nuclear extracts of NPC cells indicate that the transcription factor Ets-1 is recruited by LMP1 to the PU motif within 3′Eκ in vitro. ChIP assays further demonstrate Ets-1 binding to the PU motif of 3′Eκ in cells. These results suggest that LMP1 upregulates 3′Eκ activity and kappa gene expression by activating the Ets-1 transcription factor through the ERKs signaling pathway. Our studies provide evidence for a novel regulatory mechanism of kappa expression, by which virus-encoded proteins activate the kappa 3′ enhancer through activating transcription factors in non-B epithelial cancer cells

In situ–Directed Growth of Organic Nanofibers and Nanoflakes: Electrical and Morphological Properties

Organic nanostructures made from organic molecules such as para-hexaphenylene (p-6P) could form nanoscale components in future electronic and optoelectronic devices. However, the integration of such fragile nanostructures with the necessary interface circuitry such as metal electrodes for electrical connection continues to be a significant hindrance toward their large-scale implementation. Here, we demonstrate in situ–directed growth of such organic nanostructures between pre-fabricated contacts, which are source–drain gold electrodes on a transistor platform (bottom-gate) on silicon dioxide patterned by a combination of optical lithography and electron beam lithography. The dimensions of the gold electrodes strongly influence the morphology of the resulting structures leading to notably different electrical properties. The ability to control such nanofiber or nanoflake growth opens the possibility for large-scale optoelectronic device fabrication

Classification of behaviour in housed dairy cows using an accelerometer-based activity monitoring system

Background Advances in bio-telemetry technology have made it possible to automatically monitor and classify behavioural activities in many animals, including domesticated species such as dairy cows. Automated behavioural classification has the potential to improve health and welfare monitoring processes as part of a Precision Livestock Farming approach. Recent studies have used accelerometers and pedometers to classify behavioural activities in dairy cows, but such approaches often cannot discriminate accurately between biologically important behaviours such as feeding, lying and standing or transition events between lying and standing. In this study we develop a decision-tree algorithm that uses tri-axial accelerometer data from a neck-mounted sensor to both classify biologically important behaviour in dairy cows and to detect transition events between lying and standing. Results Data were collected from six dairy cows that were monitored continuously for 36 h. Direct visual observations of each cow were used to validate the algorithm. Results show that the decision-tree algorithm is able to accurately classify three types of biologically relevant behaviours: lying (77.42 % sensitivity, 98.63 % precision), standing (88.00 % sensitivity, 55.00 % precision), and feeding (98.78 % sensitivity, 93.10 % precision). Transitions between standing and lying were also detected accurately with an average sensitivity of 96.45 % and an average precision of 87.50 %. The sensitivity and precision of the decision-tree algorithm matches the performance of more computationally intensive algorithms such as hidden Markov models and support vector machines. Conclusions Biologically important behavioural activities in housed dairy cows can be classified accurately using a simple decision-tree algorithm applied to data collected from a neck-mounted tri-axial accelerometer. The algorithm could form part of a real-time behavioural monitoring system in order to automatically detect dairy cow health and welfare status

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Core module biomarker identification with network exploration for breast cancer metastasis

<p>Abstract</p> <p>Background</p> <p>In a complex disease, the expression of many genes can be significantly altered, leading to the appearance of a differentially expressed "disease module". Some of these genes directly correspond to the disease phenotype, (i.e. "driver" genes), while others represent closely-related first-degree neighbours in gene interaction space. The remaining genes consist of further removed "passenger" genes, which are often not directly related to the original cause of the disease. For prognostic and diagnostic purposes, it is crucial to be able to separate the group of "driver" genes and their first-degree neighbours, (i.e. "core module") from the general "disease module".</p> <p>Results</p> <p>We have developed COMBINER: COre Module Biomarker Identification with Network ExploRation. COMBINER is a novel pathway-based approach for selecting highly reproducible discriminative biomarkers. We applied COMBINER to three benchmark breast cancer datasets for identifying prognostic biomarkers. COMBINER-derived biomarkers exhibited 10-fold higher reproducibility than other methods, with up to 30-fold greater enrichment for known cancer-related genes, and 4-fold enrichment for known breast cancer susceptible genes. More than 50% and 40% of the resulting biomarkers were cancer and breast cancer specific, respectively. The identified modules were overlaid onto a map of intracellular pathways that comprehensively highlighted the hallmarks of cancer. Furthermore, we constructed a global regulatory network intertwining several functional clusters and uncovered 13 confident "driver" genes of breast cancer metastasis.</p> <p>Conclusions</p> <p>COMBINER can efficiently and robustly identify disease core module genes and construct their associated regulatory network. In the same way, it is potentially applicable in the characterization of any disease that can be probed with microarrays.</p

Post-natal cardiomyocytes can generate iPS cells with an enhanced capacity toward cardiomyogenic re-differentation

Adult mammalian cells can be reprogrammed to a pluripotent state by forcing the expression of a few embryonic transcription factors. The resulting induced pluripotent stem (iPS) cells can differentiate into cells of all three germ layers. It is well known that post-natal cardiomyocytes (CMs) lack the capacity to proliferate. Here, we report that neonatal CMs can be reprogrammed to generate iPS cells that express embryonic-specific markers and feature gene-expression profiles similar to those of mouse embryonic stem (mES) cell and cardiac fibroblast (CF)-derived iPS cell populations. CM-derived iPS cells are able to generate chimeric mice and, moreover, re-differentiate toward CMs more efficiently then either CF-derived iPS cells or mES cells. The increased differentiation capacity is possibly related to CM-derived iPS cells retaining an epigenetic memory of the phenotype of their founder cell. CM-derived iPS cells may thus lead to new information on differentiation processes underlying cardiac differentiation and proliferation