Rapid Generation of Optimal Generalized Monkhorst-Pack Grids

Computational modeling of the properties of crystalline materials has become an increasingly important aspect of materials research, consuming hundreds of millions of CPU-hours at scientific computing centres around the world each year, if not more. A routine operation in such calculations is the evaluation of integrals over the Brillouin zone. We have previously demonstrated that performing such integrals using generalized Monkhorst-Pack k-point grids can roughly double the speed of these calculations relative to the widely-used traditional Monkhorst-Pack grids, and such grids can be rapidly generated by querying a free, internet-accessible database of pre-generated grids. To facilitate the widespread use of generalized k-point grids, we present new algorithms that allow rapid generation of optimized generalized Monkhorst-Pack grids on the fly, an open-source library to facilitate their integration into external software packages, and an open-source implementation of the database tool that can be used offline. We also present benchmarks of the speed of our algorithms on structures randomly selected from the Inorganic Crystal Structure Database. For grids that correspond to a real-space supercell with at least 50 angstroms between lattice points, which is sufficient to converge density functional theory calculations within 1 meV/atom for nearly all materials, our algorithm finds optimized grids in an average of 0.19 seconds on a single processing core. For 100 angstroms between real-space lattice points, our algorithm finds optimal grids in less than 5 seconds on average

Learning Parsimonious Classification Rules from Gene Expression Data Using Bayesian Networks with Local Structure

The comprehensibility of good predictive models learned from high-dimensional gene expression data is attractive because it can lead to biomarker discovery. Several good classifiers provide comparable predictive performance but differ in their abilities to summarize the observed data. We extend a Bayesian Rule Learning (BRL-GSS) algorithm, previously shown to be a significantly better predictor than other classical approaches in this domain. It searches a space of Bayesian networks using a decision tree representation of its parameters with global constraints, and infers a set of IF-THEN rules. The number of parameters and therefore the number of rules are combinatorial in the number of predictor variables in the model. We relax these global constraints to learn a more expressive local structure with BRL-LSS. BRL-LSS entails a more parsimonious set of rules because it does not have to generate all combinatorial rules. The search space of local structures is much richer than the space of global structures. We design the BRL-LSS with the same worst-case time-complexity as BRL-GSS while exploring a richer and more complex model space. We measure predictive performance using Area Under the ROC curve (AUC) and Accuracy. We measure model parsimony performance by noting the average number of rules and variables needed to describe the observed data. We evaluate the predictive and parsimony performance of BRL-GSS, BRL-LSS and the state-of-the-art C4.5 decision tree algorithm, across 10-fold cross-validation using ten microarray gene-expression diagnostic datasets. In these experiments, we observe that BRL-LSS is similar to BRL-GSS in terms of predictive performance, while generating a much more parsimonious set of rules to explain the same observed data. BRL-LSS also needs fewer variables than C4.5 to explain the data with similar predictive performance. We also conduct a feasibility study to demonstrate the general applicability of our BRL methods on the newer RNA sequencing gene-expression data

P3HT-fiber-based field-effect transistor: Effects of nanostructure and annealing temperature

Poly(3-hexylthiophene) nanofibers were prepared under ambient conditions and applied in organic field-effect transistors (FETs). Top-contact FETs with spin-coated and nanofiber-based layers were fabricated to compare their transport performance. It was found that the nanofiber FET shows a higher performance than the spin-coated one. The effects of annealing on the device performance of the nanofiber FET were also investigated from room temperature to 120 °C. The key performance characteristics of the nanofiber FET, such as carrier mobility and ON/OFF ratio, were improved by low-temperature annealing up to 80 °C. However, they were degraded by high-temperature annealing at 120 °C. The modulation of the surface morphology observed by atomic force microscopy is consistent with the change in device performance. The results of the correlation analysis of the mobility, hysteresis, and OFF current indicate that the change in FET performance is due to the disappearance of nanofiber interspaces and the removal of adsorbed molecules by temperature-controlled annealing

Facet-joint injections for people with persistent non-specific low back pain (FIS) : study protocol for a randomised controlled feasibility trial

BACKGROUND: The role of injections of therapeutic substances into the back as treatment for low back pain is unclear. Facet joint injections are widely used despite the absence of evidence of sustained benefit. We hypothesise that facet joint injections might facilitate engagement with physiotherapist-led, best usual care (a combined physical and psychological programme) and is a clinically and cost-effective treatment for people with suspected low back pain of facet joint origin. METHODS/DESIGN: We present here the protocol for a randomised controlled feasibility trial for a main trial to test the above hypotheses. Patients referred to secondary care with persistent non-specific low back pain will be screened and invited to take part in the study. Those who meet the eligibility criteria will be invited for a physiotherapy assessment to confirm trial eligibility and for baseline data collection. All participants (n = 150) will be offered the best usual care package with physical and psychological components. Those randomised into the intervention arm (n = 75) will, in addition, receive intra-articular facet joint injections with local anaesthetic and steroids. Primary outcome data will be collected using daily and then weekly text messaging service for a pain score on a 0-10 scale. Questionnaire follow-up will be at 3, 6, and 12 months. Evaluation of trial processes and health economic analyses, including a value of information analysis, will be undertaken. The process evaluation will be mixed methods and will include the views of all stakeholders. DISCUSSION: Whilst this trial is a feasibility study it is currently one of the largest trials in this area. The outcomes will provide some evidence on the use of facet joint injections for patients with clinically diagnosed facet joint pain. TRIAL REGISTRATION: EudraCT identifier 2014-000682-50

Mental defeat and suicidality in chronic pain : a prospective analysis

Living with chronic pain has been identified as a significant risk factor for suicide. Qualitative and cross-sectional studies have reported an association between mental defeat and suicidal thoughts and behavior in patients with chronic pain. In this prospective cohort study, we hypothesized that higher levels of mental defeat would be associated with increased suicide risk at a 6-month follow-up. A total of 524 patients with chronic pain completed online questionnaires measuring variables related to suicide risk, mental defeat, sociodemographic, psychological, pain, activity, and health variables. At 6 months, 70.8% (n=371) of respondents completed the questionnaires again. Weighted univariate and multivariable regression models were run to predict suicide risk at 6 months. The clinical suicide risk cutoff was met by 38.55% of participants at baseline and 36.66% at 6 months. Multivariable modeling revealed that mental defeat, depression, perceived stress, head pain, and active smoking status significantly increased the odds of reporting higher suicide risk, while older age reduced the odds. Receiver operating characteristic (ROC) analysis showed that assessment of mental defeat, perceived stress, and depression is effective in discriminating between ‘low’ and ‘high’ suicide risk. Awareness of the prospective links from mental defeat, depression, perceived stress, head pain, and active smoking status to increased suicide risk in patients with chronic pain may offer a novel avenue for assessment and preventative intervention

Reducing Opioid Use for Chronic Pain With a Group-Based Intervention: A Randomized Clinical Trial

IMPORTANCE: Opioid use for chronic nonmalignant pain can be harmful. OBJECTIVE: To test whether a multicomponent, group-based, self-management intervention reduced opioid use and improved pain-related disability compared with usual care. DESIGN, SETTING, AND PARTICIPANTS: Multicentered, randomized clinical trial of 608 adults taking strong opioids (buprenorphine, dipipanone, morphine, diamorphine, fentanyl, hydromorphone, methadone, oxycodone, papaveretum, pentazocine, pethidine, tapentadol, and tramadol) to treat chronic nonmalignant pain. The study was conducted in 191 primary care centers in England between May 17, 2017, and January 30, 2019. Final follow-up occurred March 18, 2020. INTERVENTION: Participants were randomized 1:1 to either usual care or 3-day-long group sessions that emphasized skill-based learning and education, supplemented by 1-on-1 support delivered by a nurse and lay person for 12 months. MAIN OUTCOMES AND MEASURES: The 2 primary outcomes were Patient-Reported Outcomes Measurement Information System Pain Interference Short Form 8a (PROMIS-PI-SF-8a) score (T-score range, 40.7-77; 77 indicates worst pain interference; minimal clinically important difference, 3.5) and the proportion of participants who discontinued opioids at 12 months, measured by self-report. RESULTS: Of 608 participants randomized (mean age, 61 years; 362 female [60%]; median daily morphine equivalent dose, 46 mg [IQR, 25 to 79]), 440 (72%) completed 12-month follow-up. There was no statistically significant difference in PROMIS-PI-SF-8a scores between the 2 groups at 12-month follow-up (-4.1 in the intervention and -3.17 in the usual care groups; between-group difference: mean difference, -0.52 [95% CI, -1.94 to 0.89]; P = .15). At 12 months, opioid discontinuation occurred in 65 of 225 participants (29%) in the intervention group and 15 of 208 participants (7%) in the usual care group (odds ratio, 5.55 [95% CI, 2.80 to 10.99]; absolute difference, 21.7% [95% CI, 14.8% to 28.6%]; P < .001). Serious adverse events occurred in 8% (25/305) of the participants in the intervention group and 5% (16/303) of the participants in the usual care group. The most common serious adverse events were gastrointestinal (2% in the intervention group and 0% in the usual care group) and locomotor/musculoskeletal (2% in the intervention group and 1% in the usual care group). Four people (1%) in the intervention group received additional medical care for possible or probable symptoms of opioid withdrawal (shortness of breath, hot flushes, fever and pain, small intestinal bleed, and an overdose suicide attempt). CONCLUSIONS AND RELEVANCE: In people with chronic pain due to nonmalignant causes, compared with usual care, a group-based educational intervention that included group and individual support and skill-based learning significantly reduced patient-reported use of opioids, but had no effect on perceived pain interference with daily life activities. TRIAL REGISTRATION: isrctn.org Identifier: ISRCTN49470934

Protocol for an economic analysis of the randomised controlled trial of improving the wellbeing of people with opioid treated chronic pain : I-WOTCH study

Introduction: Over the last two decades, the use of opioids for the treatment of chronic pain in England has steadily increased despite lack of evidence of both long term effectiveness in pain relief and significant, well documented physical and mental adverse events. Guidelines recommend tapering when harms outweigh benefits, but the addictive nature of opioids hinders simple dose reduction strategies. Improving the Wellbeing of people with Opioid Treated CHronic pain (I WOTCH) trial tests a multicomponent self-management intervention aimed to help patients with chronic non malignant pain taper opioid doses. This paper outlines the methods to be used for the economic analysis of the I WOTCH intervention compared to the best usual care. Methods and analysis: Economic evaluation alongside the I WOTCH study, prospectively designed to identify, measure, and value key healthcare resource use and outcomes arising from the treatment strategies being compared. A within trial cost consequences analysis and a model based long-term cost effectiveness analysis will be conducted from the National Health Service and Personal Social Service perspective in England. The former will quantify key parameters to populate a Markov model designed to estimate the long-term cost and quality adjusted life years of the I-WOTCH programme against best usual care. Regression equations will be used to estimate parameters such as transition probabilities, utilities, and costs associated with the model’s states and events. Probabilistic sensitivity analysis will be used to assess the impact of parameter uncertainty onto the predicted costs and health outcomes, and the resulting value for money assessment of the I-WOTCH programme. Ethics and dissemination: Full ethics approval was granted by Yorkshire & The Humber – South Yorkshire Research Ethics Committee on September 13th, 2016 (16/YH/0325). Current protocol: version 1.7, date 31 July 2019. Findings will be disseminated in peer reviewed journals, scientific conferences, newsletters, and websites. Registration details: International Standard Randomised Controlled Trial Number: 49470934 (6 Feb 2017)

Testing a support programme for opioid reduction for people with chronic non-malignant pain: The I-WOTCH randomised controlled trial protocol

Introduction: Chronic non-malignant pain has a major impact on the wellbeing, mood and productivity of those affected. Opioids are increasingly being prescribed to manage this type of pain, but the increasing risk of other disabling symptoms, and their effectiveness for this type of pain has been questioned. This trial is designed to implement and evaluate a patient-centred intervention targeting withdrawal of strong opioids in patients with chronic pain. . Methods and analysis: A pragmatic, multi–centre, randomised controlled trial will assess the clinical and cost-effectiveness of a group-based multicomponent intervention combined with individualised clinical facilitator led support for the management of chronic non-malignant pain against the control intervention (self-help booklet and relaxation CD). An embedded process evaluation will examine fidelity of delivery and investigate experiences of the intervention. The twoprimary outcomes are activities of daily living (measured by PROMIS Pain Interference Short Form (8A)) and opioid use. The secondary outcomes are pain severity, quality of life, sleep quality, self-efficacy, adverse events, and NHS health care resource use. Participants are followed up at four, eight, and 12 months, with a primary endpoint of 12 months. Between-group differences will indicate effectiveness; we are looking for a difference of 3.5 points on our pain interference outcome (scale 40-77). We will undertake an NHS perspective cost-effectiveness analysis using Quality Adjusted Life Years. Ethics: Full approval was given by Yorkshire & The Humber - South Yorkshire Research Ethics Committee on September 13th, 2016 (16/YH/0325). Appropriate local approvals were sought for each area in which recruitment was undertaken. The current protocol version is 1.6. date 19th December 2018. Dissemination: Publication of results in peer reviewed journals, including the development and theoretical framework of the intervention, will inform the scientific and clinical community. We will disseminate results to patient participants and study facilitators in a study newsletter as well as a lay summary of results on the study website. Trial registration: This trial is registered with an International Standard Randomised Controlled Trial Number (ISRCTN) Register. ISRCTN number: 49470934 (06 Feb 2017