Quantum feedback control of a superconducting qubit: Persistent Rabi oscillations

The act of measurement bridges the quantum and classical worlds by projecting a superposition of possible states into a single, albeit probabilistic, outcome. The time-scale of this "instantaneous" process can be stretched using weak measurements so that it takes the form of a gradual random walk towards a final state. Remarkably, the interim measurement record is sufficient to continuously track and steer the quantum state using feedback. We monitor the dynamics of a resonantly driven quantum two-level system -- a superconducting quantum bit --using a near-noiseless parametric amplifier. The high-fidelity measurement output is used to actively stabilize the phase of Rabi oscillations, enabling them to persist indefinitely. This new functionality shows promise for fighting decoherence and defines a path for continuous quantum error correction.Comment: Manuscript: 5 Pages and 3 figures ; Supplementary Information: 9 pages and 3 figure

Antifungal Activity of Microbial Secondary Metabolites

Secondary metabolites are well known for their ability to impede other microorganisms. Reanalysis of a screen of natural products using the Caenorhabditis elegans-Candida albicans infection model identified twelve microbial secondary metabolites capable of conferring an increase in survival to infected nematodes. In this screen, the two compound treatments conferring the highest survival rates were members of the epipolythiodioxopiperazine (ETP) family of fungal secondary metabolites, acetylgliotoxin and a derivative of hyalodendrin. The abundance of fungal secondary metabolites indentified in this screen prompted further studies investigating the interaction between opportunistic pathogenic fungi and Aspergillus fumigatus, because of the ability of the fungus to produce a plethora of secondary metabolites, including the well studied ETP gliotoxin. We found that cell-free supernatant of A. fumigatus was able to inhibit the growth of Candida albicans through the production of a secreted product. Comparative studies between a wild-type and an A. fumigatus ΔgliP strain unable to synthesize gliotoxin demonstrate that this secondary metabolite is the major factor responsible for the inhibition. Although toxic to organisms, gliotoxin conferred an increase in survival to C. albicans-infected C. elegans in a dose dependent manner. As A. fumigatus produces gliotoxin in vivo, we propose that in addition to being a virulence factor, gliotoxin may also provide an advantage to A. fumigatus when infecting a host that harbors other opportunistic fungi

Intelligent OS X malware threat detection with code inspection

With the increasing market share of Mac OS X operating system, there is a corresponding increase in the number of malicious programs (malware) designed to exploit vulnerabilities on Mac OS X platforms. However, existing manual and heuristic OS X malware detection techniques are not capable of coping with such a high rate of malware. While machine learning techniques offer promising results in automated detection of Windows and Android malware, there have been limited efforts in extending them to OS X malware detection. In this paper, we propose a supervised machine learning model. The model applies kernel base Support Vector Machine (SVM) and a novel weighting measure based on application library calls to detect OS X malware. For training and evaluating the model, a dataset with a combination of 152 malware and 450 benign were is created. Using common supervised Machine Learning algorithm on the dataset, we obtain over 91% detection accuracy with 3.9% false alarm rate. We also utilize Synthetic Minority Over-sampling Technique (SMOTE) to create three synthetic datasets with different distributions based on the refined version of collected dataset to investigate impact of different sample sizes on accuracy of malware detection. Using SMOTE datasets we could achieve over 96% detection accuracy and false alarm of less than 4%. All malware classification experiments are tested using cross validation technique. Our results reflect that increasing sample size in synthetic datasets has direct positive effect on detection accuracy while increases false alarm rate in compare to the original dataset

Features of mammalian microRNA promoters emerge from polymerase II chromatin immunoprecipitation data

Background: MicroRNAs (miRNAs) are short, non-coding RNA regulators of protein coding genes. miRNAs play a very important role in diverse biological processes and various diseases. Many algorithms are able to predict miRNA genes and their targets, but their transcription regulation is still under investigation. It is generally believed that intragenic miRNAs (located in introns or exons of protein coding genes) are co-transcribed with their host genes and most intergenic miRNAs transcribed from their own RNA polymerase II (Pol II) promoter. However, the length of the primary transcripts and promoter organization is currently unknown. Methodology: We performed Pol II chromatin immunoprecipitation (ChIP)-chip using a custom array surrounding regions of known miRNA genes. To identify the true core transcription start sites of the miRNA genes we developed a new tool (CPPP). We showed that miRNA genes can be transcribed from promoters located several kilobases away and that their promoters share the same general features as those of protein coding genes. Finally, we found evidence that as many as 26% of the intragenic miRNAs may be transcribed from their own unique promoters. Conclusion: miRNA promoters have similar features to those of protein coding genes, but miRNA transcript organization is more complex. © 2009 Corcoran et al

Modelling Canopy Flows over Complex Terrain

Recent studies of flow over forested hills have been motivated by a number of important applications including understanding CO22 and other gaseous fluxes over forests in complex terrain, predicting wind damage to trees, and modelling wind energy potential at forested sites. Current modelling studies have focussed almost exclusively on highly idealized, and usually fully forested, hills. Here, we present model results for a site on the Isle of Arran, Scotland with complex terrain and heterogeneous forest canopy. The model uses an explicit representation of the canopy and a 1.5-order turbulence closure for flow within and above the canopy. The validity of the closure scheme is assessed using turbulence data from a field experiment before comparing predictions of the full model with field observations. For near-neutral stability, the results compare well with the observations, showing that such a relatively simple canopy model can accurately reproduce the flow patterns observed over complex terrain and realistic, variable forest cover, while at the same time remaining computationally feasible for real case studies. The model allows closer examination of the flow separation observed over complex forested terrain. Comparisons with model simulations using a roughness length parametrization show significant differences, particularly with respect to flow separation, highlighting the need to explicitly model the forest canopy if detailed predictions of near-surface flow around forests are required

Assessment of clusters of transcription factor binding sites in relationship to human promoter, CpG islands and gene expression

BACKGROUND: Gene expression is regulated mainly by transcription factors (TFs) that interact with regulatory cis-elements on DNA sequences. To identify functional regulatory elements, computer searching can predict TF binding sites (TFBS) using position weight matrices (PWMs) that represent positional base frequencies of collected experimentally determined TFBS. A disadvantage of this approach is the large output of results for genomic DNA. One strategy to identify genuine TFBS is to utilize local concentrations of predicted TFBS. It is unclear whether there is a general tendency for TFBS to cluster at promoter regions, although this is the case for certain TFBS. Also unclear is the identification of TFs that have TFBS concentrated in promoters and to what level this occurs. This study hopes to answer some of these questions. RESULTS: We developed the cluster score measure to evaluate the correlation between predicted TFBS clusters and promoter sequences for each PWM. Non-promoter sequences were used as a control. Using the cluster score, we identified a PWM group called PWM-PCP, in which TFBS clusters positively correlate with promoters, and another PWM group called PWM-NCP, in which TFBS clusters negatively correlate with promoters. The PWM-PCP group comprises 47% of the 199 vertebrate PWMs, while the PWM-NCP group occupied 11 percent. After reducing the effect of CpG islands (CGI) against the clusters using partial correlation coefficients among three properties (promoter, CGI and predicted TFBS cluster), we identified two PWM groups including those strongly correlated with CGI and those not correlated with CGI. CONCLUSION: Not all PWMs predict TFBS correlated with human promoter sequences. Two main PWM groups were identified: (1) those that show TFBS clustered in promoters associated with CGI, and (2) those that show TFBS clustered in promoters independent of CGI. Assessment of PWM matches will allow more positive interpretation of TFBS in regulatory regions

GPVI and GPIbα Mediate Staphylococcal Superantigen-Like Protein 5 (SSL5) Induced Platelet Activation and Direct toward Glycans as Potential Inhibitors

Background Staphylococcus aureus (S. aureus) is a common pathogen capable of causing life-threatening infections. Staphylococcal superantigen-like protein 5 (SSL5) has recently been shown to bind to platelet glycoproteins and induce platelet activation. This study investigates further the interaction between SSL5 and platelet glycoproteins. Moreover, using a glycan discovery approach, we aim to identify potential glycans to therapeutically target this interaction and prevent SSL5-induced effects. Methodology/Principal Findings In addition to platelet activation experiments, flow cytometry, immunoprecipitation, surface plasmon resonance and a glycan binding array, were used to identify specific SSL5 binding regions and mediators. We independently confirm SSL5 to interact with platelets via GPIbα and identify the sulphated-tyrosine residues as an important region for SSL5 binding. We also identify the novel direct interaction between SSL5 and the platelet collagen receptor GPVI. Together, these receptors offer one mechanistic explanation for the unique functional influences SSL5 exerts on platelets. A role for specific families of platelet glycans in mediating SSL5-platelet interactions was also discovered and used to identify and demonstrate effectiveness of potential glycan based inhibitors in vitro. Conclusions/Significance These findings further elucidate the functional interactions between SSL5 and platelets, including the novel finding of a role for the GPVI receptor. We demonstrate efficacy of possible glycan-based approaches to inhibit the SSL5-induced platelet activation. Our data warrant further work to prove SSL5-platelet effects in viv

Effects of Local and Landscape Factors on Population Dynamics of a Cotton Pest

BACKGROUND: Many polyphagous pests sequentially use crops and uncultivated habitats in landscapes dominated by annual crops. As these habitats may contribute in increasing or decreasing pest density in fields of a specific crop, understanding the scale and temporal variability of source and sink effects is critical for managing landscapes to enhance pest control. METHODOLOGY/PRINCIPAL FINDINGS: We evaluated how local and landscape characteristics affect population density of the western tarnished plant bug, Lygus hesperus (Knight), in cotton fields of the San Joaquin Valley in California. During two periods covering the main window of cotton vulnerability to Lygus attack over three years, we examined the associations between abundance of six common Lygus crops, uncultivated habitats and Lygus population density in these cotton fields. We also investigated impacts of insecticide applications in cotton fields and cotton flowering date. Consistent associations observed across periods and years involved abundances of cotton and uncultivated habitats that were negatively associated with Lygus density, and abundance of seed alfalfa and cotton flowering date that were positively associated with Lygus density. Safflower and forage alfalfa had variable effects, possibly reflecting among-year variation in crop management practices, and tomato, sugar beet and insecticide applications were rarely associated with Lygus density. Using data from the first two years, a multiple regression model including the four consistent factors successfully predicted Lygus density across cotton fields in the last year of the study. CONCLUSIONS/SIGNIFICANCE: Our results show that the approach developed here is appropriate to characterize and test the source and sink effects of various habitats on pest dynamics and improve the design of landscape-level pest management strategies

The power of comparative and developmental studies for mouse models of Down syndrome

Since the genetic basis for Down syndrome (DS) was described, understanding the causative relationship between genes at dosage imbalance and phenotypes associated with DS has been a principal goal of researchers studying trisomy 21 (Ts21). Though inferences to the gene-phenotype relationship in humans have been made, evidence linking a specific gene or region to a particular congenital phenotype has been limited. To further understand the genetic basis for DS phenotypes, mouse models with three copies of human chromosome 21 (Hsa21) orthologs have been developed. Mouse models offer access to every tissue at each stage of development, opportunity to manipulate genetic content, and ability to precisely quantify phenotypes. Numerous approaches to recreate trisomic composition and analyze phenotypes similar to DS have resulted in diverse trisomic mouse models. A murine intraspecies comparative analysis of different genetic models of Ts21 and specific DS phenotypes reveals the complexity of trisomy and important considerations to understand the etiology of and strategies for amelioration or prevention of trisomic phenotypes. By analyzing individual phenotypes in different mouse models throughout development, such as neurologic, craniofacial, and cardiovascular abnormalities, greater insight into the gene-phenotype relationship has been demonstrated. In this review we discuss how phenotype-based comparisons between DS mouse models have been useful in analyzing the relationship of trisomy and DS phenotypes

Prostaglandin E2 Signals Through PTGER2 to Regulate Sclerostin Expression

The Wnt signaling pathway is a robust regulator of skeletal homeostasis. Gain-of-function mutations promote high bone mass, whereas loss of Lrp5 or Lrp6 co-receptors decrease bone mass. Similarly, mutations in antagonists of Wnt signaling influence skeletal integrity, in an inverse relation to Lrp receptor mutations. Loss of the Wnt antagonist Sclerostin (Sost) produces the generalized skeletal hyperostotic condition of sclerosteosis, which is characterized by increased bone mass and density due to hyperactive osteoblast function. Here we demonstrate that prostaglandin E2 (PGE2), a paracrine factor with pleiotropic effects on osteoblasts and osteoclasts, decreases Sclerostin expression in osteoblastic UMR106.01 cells. Decreased Sost expression correlates with increased expression of Wnt/TCF target genes Axin2 and Tcf3. We also show that the suppressive effect of PGE2 is mediated through a cyclic AMP/PKA pathway. Furthermore, selective agonists for the PGE2 receptor EP2 mimic the effect of PGE2 upon Sost, and siRNA reduction in Ptger2 prevents PGE2-induced Sost repression. These results indicate a functional relationship between prostaglandins and the Wnt/β-catenin signaling pathway in bone