Development of the Motivational Interviewing Supervision and Training Scale

The movement to use empirically supported treatments has increased the need for researchers and supervisors to evaluate therapists’ adherence to and the quality with which they implement those interventions. Few empirically supported approaches exist for providing these types of evaluations. This is also true for motivational interviewing, an empirically supported intervention important in the addictions field. This study describes the development and psychometric evaluation of the Motivational Interviewing Supervision and Training Scale (MISTS), a measure intended for use in training and supervising therapists implementing motivational interviewing. Satisfactory interrater reliability was found (generalizability coefficient p2 = .79), and evidence was found supporting the convergent and discriminant validity of the MISTS. Recommendations for refinement of the measure and future research are discussed

High-order noise filtering in nontrivial quantum logic gates

Treating the effects of a time-dependent classical dephasing environment during quantum logic operations poses a theoretical challenge, as the application of non-commuting control operations gives rise to both dephasing and depolarization errors that must be accounted for in order to understand total average error rates. We develop a treatment based on effective Hamiltonian theory that allows us to efficiently model the effect of classical noise on nontrivial single-bit quantum logic operations composed of arbitrary control sequences. We present a general method to calculate the ensemble-averaged entanglement fidelity to arbitrary order in terms of noise filter functions, and provide explicit expressions to fourth order in the noise strength. In the weak noise limit we derive explicit filter functions for a broad class of piecewise-constant control sequences, and use them to study the performance of dynamically corrected gates, yielding good agreement with brute-force numerics.Comment: Revised and expanded to include filter function terms beyond first order in the Magnus expansion. Related manuscripts available from http://www.physics.usyd.edu.au/~mbiercu

SOPRA: Scaffolding algorithm for paired reads via statistical optimization

<p>Abstract</p> <p>Background</p> <p>High throughput sequencing (HTS) platforms produce gigabases of short read (<100 bp) data per run. While these short reads are adequate for resequencing applications, <it>de novo </it>assembly of moderate size genomes from such reads remains a significant challenge. These limitations could be partially overcome by utilizing mate pair technology, which provides pairs of short reads separated by a known distance along the genome.</p> <p>Results</p> <p>We have developed SOPRA, a tool designed to exploit the mate pair/paired-end information for assembly of short reads. The main focus of the algorithm is selecting a sufficiently large subset of simultaneously satisfiable mate pair constraints to achieve a balance between the size and the quality of the output scaffolds. Scaffold assembly is presented as an optimization problem for variables associated with vertices and with edges of the contig connectivity graph. Vertices of this graph are individual contigs with edges drawn between contigs connected by mate pairs. Similar graph problems have been invoked in the context of shotgun sequencing and scaffold building for previous generation of sequencing projects. However, given the error-prone nature of HTS data and the fundamental limitations from the shortness of the reads, the ad hoc greedy algorithms used in the earlier studies are likely to lead to poor quality results in the current context. SOPRA circumvents this problem by treating all the constraints on equal footing for solving the optimization problem, the solution itself indicating the problematic constraints (chimeric/repetitive contigs, etc.) to be removed. The process of solving and removing of constraints is iterated till one reaches a core set of consistent constraints. For SOLiD sequencer data, SOPRA uses a dynamic programming approach to robustly translate the color-space assembly to base-space. For assessing the quality of an assembly, we report the no-match/mismatch error rate as well as the rates of various rearrangement errors.</p> <p>Conclusions</p> <p>Applying SOPRA to real data from bacterial genomes, we were able to assemble contigs into scaffolds of significant length (N50 up to 200 Kb) with very few errors introduced in the process. In general, the methodology presented here will allow better scaffold assemblies of any type of mate pair sequencing data.</p

Kinetochore Attachments Require an Interaction between Unstructured Tails on Microtubules and Ndc80Hec1

SummaryKinetochore attachments to microtubules are tight enough to move chromosomes, yet the microtubules' plus ends must remain dynamic and reposition within the attachment pocket during depolymerization-coupled movement. Kinetochores are unable to bind microtubules after any of the four subunits of the Ndc80 complex are knocked down [2, 4]; however, because the Ndc80 complex has important structural roles [1–3], it is unclear whether it directly mediates kinetochore-microtubule attachments. The Ndc80Hec1 subunit (Hec1) has a microtubule-binding site composed of both an unstructured N-terminal tail and a calponin homology domain [5–7]. Here, we show that, surprisingly, the N-terminal tail is sufficient for microtubule-binding affinity in vitro. The interaction is salt sensitive, and the positively charged Hec1 tail cannot bind microtubules lacking negatively charged tails. We have replaced the endogenous Hec1 subunit with a mutant lacking the N-terminal tail. These cells assemble kinetochores properly but are unable to congress chromosomes, generate tension across sister kinetochores, or establish cold-stable kinetochore-microtubule attachments. Our data argue that the highest affinity interactions between kinetochores and microtubules are ionic attractions between two unstructured domains. We discuss the importance of this finding for models of repositioning of microtubules in the kinetochore during depolymerization

Modeling raccoon (Procyon lotor) habitat connectivity to identify potential corridors for rabies spread

The United States Department of Agriculture (USDA), Animal and Plant Health Inspection Service (APHIS), Wildlife Services National Rabies Management Program has conducted cooperative oral rabies vaccination (ORV) programs since 1997. Understanding the eco-epidemiology of raccoon (Procyon lotor) variant rabies (raccoon rabies) is critical to successful management. Pine (Pinus spp.)-dominated landscapes generally support low relative raccoon densities that may inhibit rabies spread. However, confounding landscape features, such as wetlands and human development, represent potentially elevated risk corridors for rabies spread, possibly imperiling enhanced rabies surveillance and ORV planning. Raccoon habitat suitability in pine-dominated landscapes in Massachusetts, Florida, and Alabama was modeled by the maximum entropy (Maxent) procedure using raccoon presence, and landscape and environmental data. Replicated (n = 100/state) bootstrapped Maxent models based on raccoon sampling locations from 2012–2014 indicated that soil type was the most influential variable in Alabama (permutation importance PI = 38.3), which, based on its relation to landcover type and resource distribution and abundance, was unsurprising. Precipitation (PI = 46.9) and temperature (PI = 52.1) were the most important variables in Massachusetts and Florida, but these possibly spurious results require further investigation. The Alabama Maxent probability surface map was ingested into Circuitscape for conductance visualizations of potential areas of habitat connectivity. Incorporating these and future results into raccoon rabies containment and elimination strategies could result in significant cost-savings for rabies management here and elsewhere