Experimental simulation of quantum graphs by microwave networks

We present the results of experimental and theoretical study of irregular, tetrahedral microwave networks consisting of coaxial cables (annular waveguides) connected by T-joints. The spectra of the networks were measured in the frequency range 0.0001-16 GHz in order to obtain their statistical properties such as the integrated nearest neighbor spacing distribution and the spectral rigidity. The comparison of our experimental and theoretical results shows that microwave networks can simulate quantum graphs with time reversal symmetry. In particular, we use the spectra of the microwave networks to study the periodic orbits of the simulated quantum graphs. We also present experimental study of directional microwave networks consisting of coaxial cables and Faraday isolators for which the time reversal symmetry is broken. In this case our experimental results indicate that spectral statistics of directional microwave networks deviate from predictions of Gaussian orthogonal ensembles (GOE) in random matrix theory approaching, especially for small eigenfrequency spacing s, results for Gaussian unitary ensembles (GUE). Experimental results are supported by the theoretical analysis of directional graphs.Comment: 16 pages, 7 figures, to be published in Phys. Rev.

Cutting Gordian Knots: Reducing Prejudice Through Attachment Security

The positive role of secure attachment in reducing intergroup biases has been suggested in prior studies. We extend this work by testing the effects of secure attachment primes on negative emotions and aggressive behaviors toward outgroup members across four experiments. Results from Studies 1A and 1B reveal that secure attachment prime, relative to neutral, can reduce negative outgroup emotions. In addition, Studies 1B and 3 results rule out positive mood increase as an alternative explanation for the observed effects. Results from Studies 2 and 3 reveal that secure attachment primes can reduce aggressive behavior toward an outgroup member. The effect of secure attachment primes on outgroup harm was found to be fully mediated by negative emotions in Studies 2 and 3. An interaction between secure attachment primes and ingroup identification in Study 2 indicated that the positive effects of secure attachment in reducing outgroup harm may be especially beneficial for highly identified ingroup members

Integrated Proteomic and Transcriptomic Investigation of the Acetaminophen Toxicity in Liver Microfluidic Biochip

Microfluidic bioartificial organs allow the reproduction of in vivo-like properties such as cell culture in a 3D dynamical micro environment. In this work, we established a method and a protocol for performing a toxicogenomic analysis of HepG2/C3A cultivated in a microfluidic biochip. Transcriptomic and proteomic analyses have shown the induction of the NRF2 pathway and the related drug metabolism pathways when the HepG2/C3A cells were cultivated in the biochip. The induction of those pathways in the biochip enhanced the metabolism of the N-acetyl-p-aminophenol drug (acetaminophen-APAP) when compared to Petri cultures. Thus, we observed 50% growth inhibition of cell proliferation at 1 mM in the biochip, which appeared similar to human plasmatic toxic concentrations reported at 2 mM. The metabolic signature of APAP toxicity in the biochip showed similar biomarkers as those reported in vivo, such as the calcium homeostasis, lipid metabolism and reorganization of the cytoskeleton, at the transcriptome and proteome levels (which was not the case in Petri dishes). These results demonstrate a specific molecular signature for acetaminophen at transcriptomic and proteomic levels closed to situations found in vivo. Interestingly, a common component of the signature of the APAP molecule was identified in Petri and biochip cultures via the perturbations of the DNA replication and cell cycle. These findings provide an important insight into the use of microfluidic biochips as new tools in biomarker research in pharmaceutical drug studies and predictive toxicity investigations

Determination of Preferred pH for Root-knot Nematode Aggregation Using Pluronic F-127 Gel

Root-knot nematodes (Meloidogyne spp.) are obligate endoparasites of a wide range of plant species. The infective stage is attracted strongly to and enters host roots at the zone of elongation, but the compounds responsible for this attraction have not been identified. We developed a simple assay to investigate nematode response to chemical gradients that uses Pluronic F-127, a synthetic block copolymer that, as a 23% aqueous solution, forms a liquid at low temperature and a gel at room temperature. Test chemicals are put into a modified pipette tip, or ‘chemical dispenser,’ and dispensers are inserted into the gel in which nematodes have been dispersed. Meloidogyne hapla is attracted to pH gradients formed by acetic acid and several other Brønsted acids and aggregates between pH 4.5 and 5.4. While this pH range was attractive to all tested root-knot nematode strains and species, the level of aggregation depended on the species/strain assessed. For actively growing roots, the pH at the root surface is most acidic at the zone of elongation. This observation is consistent with the idea that low pH is an attractant for nematodes. Root-knot nematodes have been reported to be attracted to carbon dioxide, but our experiments suggest that the observed attraction may be due to acidification of solutions by dissolved CO2 rather than to CO2 itself. These results suggest that Pluronic F-127 gel will be broadly applicable for examining responses of a range of organisms to chemical gradients or to each other

Predicting the Potential Worldwide Distribution of the Red Palm Weevil Rhynchophorus ferrugineus (Olivier) (Coleoptera: Curculionidae) using Ecological Niche Modeling

This is the publisher's version, also available electronically from http://www.bioone.org/doi/abs/10.1653/024.095.0317.The red palm weevil (RPW), Rhynchophorus ferrugineus (Olivier) (Coleoptera: Curculionidae), ranks among the most important pests of various palm species. The pest originates from South and Southeast Asia, but has expanded its range dramatically since the 1980s. We used ecological niche modeling (ENM) approaches to explore its likely geographic potential. Two techniques, the Genetic Algorithm for Rule-set Prediction (GARP) and a maximum entropy approach (MaxEnt), were used. However, MaxEnt provided more significant results, with all 5 random replicate subsamples having P < 0.002 while GARP models failed to achieve statistical significance in 3 of 5 cases, in which predictions achieved probabilities of 0.07 < P < 0.10. The MaxEnt models predicted successfully the known distribution, including the single North American occurrence point of Laguna Beach, California, and various areas where the pest has been reported in North Africa, southern Europe, Middle East and South and Southeastern Asia. In addition, areas where the pest has not been yet reported were found to be suitable for invasion by RPW in sub-Saharan Africa, southern, central and northern America, Asia, Europe, and Oceania. Highly suitable areas in the United States of America were limited mostly to coastal California and southern Florida, while all Caribbean islands were found highly suitable for establishment and spread of the pest

Sequence-based identification of interface residues by an integrative profile combining hydrophobic and evolutionary information

<p>Abstract</p> <p>Background</p> <p>Protein-protein interactions play essential roles in protein function determination and drug design. Numerous methods have been proposed to recognize their interaction sites, however, only a small proportion of protein complexes have been successfully resolved due to the high cost. Therefore, it is important to improve the performance for predicting protein interaction sites based on primary sequence alone.</p> <p>Results</p> <p>We propose a new idea to construct an integrative profile for each residue in a protein by combining its hydrophobic and evolutionary information. A support vector machine (SVM) ensemble is then developed, where SVMs train on different pairs of positive (interface sites) and negative (non-interface sites) subsets. The subsets having roughly the same sizes are grouped in the order of accessible surface area change before and after complexation. A self-organizing map (SOM) technique is applied to group similar input vectors to make more accurate the identification of interface residues. An ensemble of ten-SVMs achieves an MCC improvement by around 8% and F1 improvement by around 9% over that of three-SVMs. As expected, SVM ensembles constantly perform better than individual SVMs. In addition, the model by the integrative profiles outperforms that based on the sequence profile or the hydropathy scale alone. As our method uses a small number of features to encode the input vectors, our model is simpler, faster and more accurate than the existing methods.</p> <p>Conclusions</p> <p>The integrative profile by combining hydrophobic and evolutionary information contributes most to the protein-protein interaction prediction. Results show that evolutionary context of residue with respect to hydrophobicity makes better the identification of protein interface residues. In addition, the ensemble of SVM classifiers improves the prediction performance.</p> <p>Availability</p> <p>Datasets and software are available at <url>http://mail.ustc.edu.cn/~bigeagle/BMCBioinfo2010/index.htm</url>.</p

Evaluation of drug administration errors in a teaching hospital

<p>Abstract</p> <p>Background</p> <p>Medication errors can occur at any of the three steps of the medication use process: prescribing, dispensing and administration. We aimed to determine the incidence, type and clinical importance of drug administration errors and to identify risk factors.</p> <p>Methods</p> <p>Prospective study based on disguised observation technique in four wards in a teaching hospital in Paris, France (800 beds). A pharmacist accompanied nurses and witnessed the preparation and administration of drugs to all patients during the three drug rounds on each of six days per ward. Main outcomes were number, type and clinical importance of errors and associated risk factors. Drug administration error rate was calculated with and without wrong time errors. Relationship between the occurrence of errors and potential risk factors were investigated using logistic regression models with random effects.</p> <p>Results</p> <p>Twenty-eight nurses caring for 108 patients were observed. Among 1501 opportunities for error, 415 administrations (430 errors) with one or more errors were detected (27.6%). There were 312 wrong time errors, ten simultaneously with another type of error, resulting in an error rate without wrong time error of 7.5% (113/1501). The most frequently administered drugs were the cardiovascular drugs (425/1501, 28.3%). The highest risks of error in a drug administration were for dermatological drugs. No potentially life-threatening errors were witnessed and 6% of errors were classified as having a serious or significant impact on patients (mainly omission). In multivariate analysis, the occurrence of errors was associated with drug administration route, drug classification (ATC) and the number of patient under the nurse's care.</p> <p>Conclusion</p> <p>Medication administration errors are frequent. The identification of its determinants helps to undertake designed interventions.</p