Pain management skills of regional nurses caring for older people with dementia: a needs analysis

An exploratory survey of the pain management education needs of 197 nurses working with older people with dementia was undertaken in a regional area of Queensland, Australia. The analysis indicated that nurses in this setting might not have the knowledge base to manage pain effectively; and that respondents have essentially negative perceptions of the availability and appropriateness of current pain management education programs. Consistent with non-metropolitan nurses generally, respondents expressed a preference for pain management education that had a significant face-to-face component allied with ongoing mentorship and support on completion of the program. The obstacles to attending such programs were also typical of the problems facing regional and rural nurses throughout Australia. These were identified as inability to pay for courses; lack of information on what is available; distance to travel to education; and a perceived lack of employer support due to an inability to replace those staff attending education. Positive aspects include the degree to which participants were responsive and interested in dementia pain management and their access to, and acceptance of, non-medical pain therapies. The findings suggest a definite need for a dementia pain management program for aged care nurses, specifically tailored to their needs and to the constraints of the regional practice setting

Towards reproducible MSMS data preprocessing, quality control and quantification

The development of MSnbase aims at providing researchers dealing with labelled quantitative proteomics data with a transparent, portable, extensible and open-source collaborative framework to easily manipulate and analyse MS2-level raw tandem mass spectrometry data. The implementation in R gives users and developers a great variety of powerful tools to be used in a controlled and reproducible way. Furthermore, MSnbase has been developed following an object-oriented programming paradigm: all information that is manipulated by the user is encapsulated in ad hoc data containers to hide it's underlying complexity. We illustrate the usage and achievements of our software using a published spiked-in data set in which varying quantities of test proteins have been labelled with four different iTRAQ tags. In addition to providing raw MSMS data, MSnbase also stores meta-data and logs processing steps in the data object itself for optimal traceability. We provide graphics on how to inspect precursor data for quality control and how individual or merged MSMS spectra can subsequently be processed, plotted and extracted using a variety of methods. We also demonstrate how reporter ions (or any peaks of interest defined by the user) can easily be quantified and normalised using several build-in alternative strategies and how the effect of each transformation can be recorded, examined and reproduced. MSnbase constitutes a unique versatile working and development environment to process labelled MSMS data and provides in turn important feedback for data acquisition optimisation. We conclude by presenting future extensions of MSnbase and highlight its usage in reproducible proteomics research

Density of 33-critical signed graphs

We say that a signed graph is $k$-critical if it is not $k$-colorable but every one of its proper subgraphs is $k$-colorable. Using the definition of colorability due to Naserasr, Wang, and Zhu that extends the notion of circular colorability, we prove that every $3$-critical signed graph on $n$ vertices has at least $\frac{3n-1}{2}$ edges, and that this bound is asymptotically tight. It follows that every signed planar or projective-planar graph of girth at least $6$ is (circular) $3$-colorable, and for the projective-planar case, this girth condition is best possible. To prove our main result, we reformulate it in terms of the existence of a homomorphism to the signed graph $C_{3}^*$, which is the positive triangle augmented with a negative loop on each vertex.Comment: 27 pages, 12 figure

Real-time electrochemical LAMP: a rational comparative study of different DNA intercalating and non-intercalating redox probes

International audienceWe present a comparative study of ten redox-active probes for use in real-time electrochemical loop-mediated isothermal amplification (LAMP). Our main objectives were to establish the criteria that need to be fulfilled for minimizing some of the current limitations of the technique and to provide future guidelines in the search for ideal redox reporters. To ensure a reliable comparative study, each redox probe was tested under similar conditions using the same LAMP reaction and the same entirely automatized custom-made real-time electrochemical device (designed for electrochemically monitoring in real-time and in parallel up to 48 LAMP samples). Electrochemical melt curve analyses were recorded immediately at the end of each LAMP reaction. Our results show that there are a number of intercalating and non-intercalating redox compounds suitable for real-time electrochemical LAMP and that the best candidates are those able to intercalate strongly into ds-DNA but not too much to avoid inhibition of the LAMP reaction. The strongest intercalating redox probes were finally shown to provide higher LAMP sensitivity, speed, greater signal amplitude, and cleaner-cut DNA melting curves than the non-intercalating molecules

Effects of Traveling Wave Ion Mobility Separation on Data Independent Acquisition in Proteomics Studies

qTOF mass spectrometry and traveling wave ion mobility separation (TWIMS) hybrid instruments (q- TWIMS-TOF) have recently become commercially available. Ion mobility separation allows an additional dimension of precursor separation inside the instrument, without incurring an increase in instrument time. We comprehensively investigated the effects of TWIMS on data-independent acquisition on a Synapt G2 instrument. We observed that if fragmentation is performed post TWIMS, more accurate assignment of fragment ions to precursors is possible in data independent acquisition. This allows up to 60% higher proteome coverage and higher confidence of protein and peptide identifications. Moreover, the majority of peptides and proteins identified upon application of TWIMS span the lower intensity range of the proteome. It has also been demonstrated in several studies that employing IMS results in higher peak capacity of separation and consequently more accurate and precise quantitation of lower intensity precursor ions. We observe that employing TWIMS results in an attenuation of the detected ion current. We postulate that this effect is binary; sensitivity is reduced due to ion scattering during transfer into a high pressure “IMS zone”, sensitivity is reduced due to the saturation of detector digitizer as a result of the IMS concentration effect. This latter effect limits the useful linear range of quantitation, compromising quantitation accuracy of high intensity peptides. We demonstrate that the signal loss from detector saturation and transmission loss can be deconvoluted by investigation of the peptide isotopic envelope. We discuss the origin and extent of signal loss and suggest methods to minimize these effects on q-TWIMS-TOF instrument in the light of different experimental designs and other IMS/MS platforms described previously

A Bayesian mixture modelling approach for spatial proteomics.

Analysis of the spatial sub-cellular distribution of proteins is of vital importance to fully understand context specific protein function. Some proteins can be found with a single location within a cell, but up to half of proteins may reside in multiple locations, can dynamically re-localise, or reside within an unknown functional compartment. These considerations lead to uncertainty in associating a protein to a single location. Currently, mass spectrometry (MS) based spatial proteomics relies on supervised machine learning algorithms to assign proteins to sub-cellular locations based on common gradient profiles. However, such methods fail to quantify uncertainty associated with sub-cellular class assignment. Here we reformulate the framework on which we perform statistical analysis. We propose a Bayesian generative classifier based on Gaussian mixture models to assign proteins probabilistically to sub-cellular niches, thus proteins have a probability distribution over sub-cellular locations, with Bayesian computation performed using the expectation-maximisation (EM) algorithm, as well as Markov-chain Monte-Carlo (MCMC). Our methodology allows proteome-wide uncertainty quantification, thus adding a further layer to the analysis of spatial proteomics. Our framework is flexible, allowing many different systems to be analysed and reveals new modelling opportunities for spatial proteomics. We find our methods perform competitively with current state-of-the art machine learning methods, whilst simultaneously providing more information. We highlight several examples where classification based on the support vector machine is unable to make any conclusions, while uncertainty quantification using our approach provides biologically intriguing results. To our knowledge this is the first Bayesian model of MS-based spatial proteomics data.LG was supported by the BBSRC Strategic Longer and Larger grant (Award BB/L002817/1) and the Wellcome Trust Senior Investigator Award 110170/Z/15/Z awarded to KSL. PDWK was supported by the MRC (project reference MC_UP_0801/1). CMM was supported by a Wellcome Trust Technology Development Grant (Grant number 108467/Z/15/Z). OMC is a Wellcome Trust Mathematical Genomics and Medicine student supported financially by the School of Clinical Medicine, University of Cambridge. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

A Near-Infrared Survey of the Inner Galactic Plane for Wolf-Rayet Stars I. Methods and First Results: 41 New WR Stars

The discovery of new Wolf-Rayet (WR) stars in our Galaxy via large-scale narrowband optical surveys has been severely limited by dust extinction. Recent improvements in infrared technology have made narrowband-broadband imaging surveys viable again. We report a new J, K and narrow-band imaging survey of 300 square degrees of the plane of the Galaxy, spanning 150 degrees in Galactic longitude and reaching 1 degree above and below the Galactic plane. The survey has a useful limiting magnitude of K = 15 over most of the observed Galactic plane, and K = 14 within a few degrees of the Galactic center. Thousands of emission line candidates have been detected. In spectrographic follow-ups of 173 WR star candidates we have discovered 41 new WR stars, 15 of type WN and 26 of type WC. Star subtype assignments have been confirmed with K band spectra, and distances approximated using the method of spectroscopic parallax. A few of the new WR stars are amongst the most distant known in our Galaxy. The distribution of these new WR stars is seen to follow that of previously known WR stars along the spiral arms of the Galaxy. Tentative radial velocities were also measured for most of the new WR stars.Comment: 55 pages, 23 figures, 7 tables, accepted to Astronomical Journa