Anti-DNA:RNA antibodies and silicon photonic microring resonators: increased sensitivity for multiplexed microRNA detection

In this paper, we present a method for the sensitive detection of microRNAs (miRNAs) utilizing an antibody that specifically recognizes DNA:RNA heteroduplexes and a silicon photonic microring resonator array transduction platform. Microring resonator arrays are covalently functionalized with DNA capture probes that are complementary to solution phase miRNA targets. Following hybridization on the sensor, the anti-DNA:RNA antibody is introduced and binds selectively to the heteroduplexes, giving a larger signal than the original miRNA hybridization due to the increased mass of the antibody, as compared to the 22-mer oligoribonucleotide. Furthermore, the secondary recognition step is performed in neat buffer solution and at relatively higher antibody concentrations, facilitating the detection of miRNAs of interest. The intrinsic sensitivity of the microring resonator platform coupled with the amplification provided by the anti-DNA:RNA antibodies allows for the detection of microRNAs at concentrations as low as 10 pM (350 amol). The simplicity and sequence generality of this amplification method position it as a promising tool for high-throughput, multiplexed miRNA analysis as well as a range of other RNA based detection applications.     

The confirmability and disconfirmability of trait concepts revisited: Does content matter?

M. Rothbart and B. Park (1986) demonstrated that, consistent with the common negativity bias, positive traits are difficult to confirm and easy to disconfirm, whereas the opposite is true for negative traits. This article extends their analysis by showing that trait (dis-)confirmability is moderated by trait content (warmth vs. competence). Study 1 identifies a trait sample representative of warmth and competence. Study 2 shows a strong negativity effect for warmth and a reduced (or absent) negativity effect for competence. Study 3 examines trait properties related to the behavioral range of the trait possessor and to the motivational goals of the perceiver as predictors of trait (dis-)confirmability. The theoretical and practical implications of the authors' findings are discussed, and avenues for future research are suggested. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Social skill deficit interventions for substance abusers.

Because substance abusers demonstrate significant cognitive and behavioral skill deficits, 2 social competency models of habilitation are proposed to increase abusers' life management skills and coping abilities. Social problem-solving training programs focus on generic cognitive problem-solving deficits, while social skills training programs address specific behavioral deficiencies. Social problem solving is a cognitive-behavioral approach that teaches people how to think, emphasizing thinking that is alternative, consequential, means-end, perspective taking, and social-causal. Social skills training may be taught using modeling, role playing, rehearsal, coaching, and feedback. Both approaches have been successful for increasing social adjustment and diminishing psychopathology among high-risk substance abusers. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

DBDigger: reorganized proteomic database identification that improves flexibility and speed

Database search identification algorithms, such as Sequest and Mascot, constitute powerful enablers for proteomic tandem mass spectrometry. We introduce DBDigger, an algorithm that reorganizes the database identification process to remove a problematic bottleneck. Typically such algorithms determine which candidate sequences can be compared to each spectrum. Instead, DBDigger determines which spectra can be compared to each candidate sequence, enabling the software to generate candidate sequences only once for each HPLC separation rather than for each spectrum. This reorganization also reduces the number of times a spectrum must be predicted for a particular candidate sequence and charge state. As a result, DBDigger can accelerate some database searches by more than an order of magnitude. In addition, the software offers features to reduce the performance degradation introduced by posttranslational modification (PTM) searching. DBDigger allows researchers to specify the sequence context in which each PTM is possible. In the case of CNBr digests, for example, modified methionine residues can be limited to occur only at the C-termini of peptides. Use of "context-dependent" PTM searching reduces the performance penalty relative to traditional PTM searching. We characterize the performance possible with DBDigger, showcasing MASPIC, a new statistical scorer. We describe the implementation of these innovations in the hope that other researchers will employ them for rapid and highly flexible proteomic database search.     

Selective ion filtering by digital thresholding: a method to unwind complex ESI-mass spectra and eliminate signals from low molecular weight chemical noise

In this work, we present a simple method by which to preferentially detect either high molecular weight or low molecular weight ions generated by electrospray ionization. This approach, termed selective ion filtering by digital thresholding (SIFdT) is demonstrated on a commercial ESI-TOF instrument that employs a fast digitizer coupled to a microchannel plate detector. The digital representation of each individual scan is digitally filtered prior to spectral coaddition. As larger, more highly charged ions induce a more intense response than low molecular weight singly charged species, a digital threshold can be set that precludes the detection of singly charged species yet permits the efficient detection of larger, more highly charged species. In this work, we demonstrate the applicability of this approach to eliminate low molecular weight chemical noise in ESI-TOF spectra of oligonucleotide and protein ions, demonstrate improved dynamic range for analyte solutions containing high levels of low MW constituents, and show that spectra acquired at different digital thresholds can be subtracted to yield spectra of low molecular weight constituents with improved mass measurement accuracies. A notional scheme is presented in which an alternative digitization approach is employed using multiple differentially thresholded data streams to allow improved internal mass calibration and higher resolution ion partitioning.     

Investigation of the 2D assumption in the image‐based inertial impact test

The image‐based inertial impact (IBII) test has shown promise for measuring properties of composites at strain rates where existing test methods become unreliable due to inertial effects (> 10² s^?1 ). Typically, the IBII tests are performed with a single camera, and therefore, to use surface measurements for material property identification, it is necessary to assume that the test is two‐dimensional. In this work, synchronised ultra‐high‐speed cameras are used to quantify the relevance of this assumption when nonuniform, through‐the‐thickness loading is applied to interlaminar samples. Initial experiments revealed that an angular misalignment of approximately 1° between the impact faces of the waveguide and projectile created a bending wave that propagated along the sample behind the axial pulse. Even under these conditions, consistent measurements of stiffness were made by assuming a linear distribution of the behaviour through‐the‐thickness. When the misalignment was reduced to 0.2°, the effects on single‐sided measurements were significantly reduced. The two alignment cases were compared to show that three‐dimensional loading had a small effect on stiffness identification (approximately 5% bias) relative to failure stress (approximately 30% bias). This study highlights the importance of impact alignment for reliable characterisation of the interlaminar failure stress and was used to establish guidelines for diagnosing loading issues from single‐sided measurements.     

Interior Penalties for Summation-by-Parts Discretizations of Linear Second-Order Differential Equations

This work focuses on simultaneous approximation terms (SATs) for multidimensional summation-by-parts (SBP) discretizations of linear second-order partial differential equations with variable coefficients. Through the analysis of adjoint consistency and stability, we present several conditions on the SAT penalties for general operators, including those operators that do not have nodes on their boundary or do not correspond with a collocation discontinuous Galerkin method. Based on these conditions, we generalize the modified scheme of Bassi and Rebay and the symmetric interior penalty Galerkin method to SBP-SAT discretizations. Numerical experiments are carried out on unstructured grids with triangular elements to verify the theoretical results.