Environmentally induced phenotypic variation in wild yellow-bellied marmots

We thank all the marmoteers who helped in data collection and 2 anonymous reviewers who helped us to clarify our message. AM-C was supported by a Fulbright Fellowship, and JGAM was supported by Fond Québécois de Recherche sur la Nature et les Technologies. KBA was supported by the National Science Foundation between 1962 and 2000. DTB was supported by the National Geographic Society, UCLA (Faculty Senate and the Division of Life Sciences), a Rocky Mountain Biological Laboratory research fellowship, and by the National Science Foundation (IDBR-0754247 and DEB-1119660 to DTB as well as DBI 0242960 and 0731346 to the Rocky Mountain Biological Laboratory).Peer reviewedPostprin

Multicore Acceleration for Priority Based Schedulers for Concurrency Bug Detection

Testing multithreaded programs is difficult as threads can interleave in a nondeterministic fashion. Untested interleavings can cause failures, but testing all interleavings is infeasible. Many interleaving exploration strategies for bug detection have been proposed, but their relative effectiveness and performance remains unclear as they often lack publicly available implementations and have not been evaluated using common benchmarks. We describe NeedlePoint, an open-source framework that allows selection and comparison of a wide range of interleaving exploration policies for bug detection proposed by prior work. Our experience with NeedlePoint indicates that priority-based probabilistic concurrency testing (the PCT algorithm) finds bugs quickly, but it runs only one thread at a time, which destroys parallelism by serializing executions. To address this problem we propose a parallel version of the PCT algorithm (PPCT).We show that the new algorithm outperforms the original by a factor of 5x when testing parallel programs on an eight-core machine. We formally prove that parallel PCT provides the same probabilistic coverage guarantees as PCT. Moreover, PPCT is the first algorithm that runs multiple threads while providing coverage guarantees

Implementing a hybrid cognitive-behavioural therapy for pain-related insomnia in primary care : lessons learnt from a mixed-methods feasibility study

Objectives: To test the feasibility of implementing a brief but intensive hybrid cognitive behavioural therapy (Hybrid CBT) for pain-related insomnia. Design: Mixed-methods, with qualitative process evaluation on a two-arm randomised controlled feasibility trial. Setting: Primary care. Participants: Twenty-five adult patients with chronic pain and insomnia. Intervention: Hybrid CBT or self-help control intervention. Primary and secondary outcome measures: Primary outcomes measures were the Insomnia Severity Index and interference scale of the Brief Pain Inventory (BPI). Secondary outcomes measures were the present pain intensity rating from the BPI, Multidimensional Fatigue Inventory, Hospital Anxiety and Depression Scale and EQ-5D-5L. Results: Fourteen participants were randomised to receive Hybrid CBT, 11 to receive the self-help control treatment. Of the 14 in the Hybrid CBT group, 9 (64%) completed all four treatment sessions (4 discontinued due to poor health; 1 due to time constraints). Adherence to the self-help control treatment was not monitored. The total number of participants completing the 12-week and 24-week follow-ups were 12 (6 in each group; Hybrid CBT: 43%; self-help: 55%) and 10 (5 in each group; Hybrid CBT: 36%; self-help: 45%). Based on the data available, candidate outcome measures appeared to be sensitive to changes associated with interventions. Thematic analysis of pre-postintervention interview data revealed satisfaction with treatment content among those who completed the Hybrid CBT, whereas those in the self-help control treatment wanted more contact hours and therapist guidance. Other practical suggestions for improvement included shortening the duration of each treatment session, reducing the amount of assessment paperwork, and minimising the burden of sleep and pain monitoring. Conclusion: Important lessons were learnt with regard to the infrastructure required to achieve better patient adherence and retention. Based on the qualitative feedback provided by a subset of treatment completers, future trials should also consider lowering the intensity of treatment and streamlining the data collection procedure. Trial registration number: ISRCTN17294365

Value of information methods to design a clinical trial in a small population to optimise a health economic utility function

Background: Most confirmatory randomised controlled clinical trials (RCTs) are designed with specified power, usually 80% or 90%, for a hypothesis test conducted at a given significance level, usually 2.5% for a one-sided test. Approval of the experimental treatment by regulatory agencies is then based on the result of such a significance test with other information to balance the risk of adverse events against the benefit of the treatment to future patients. In the setting of a rare disease, recruiting sufficient patients to achieve conventional error rates for clinically reasonable effect sizes may be infeasible, suggesting that the decision-making process should reflect the size of the target population. Methods: We considered the use of a decision-theoretic value of information (VOI) method to obtain the optimal sample size and significance level for confirmatory RCTs in a range of settings. We assume the decision maker represents society. For simplicity we assume the primary endpoint to be normally distributed with unknown mean following some normal prior distribution representing information on the anticipated effectiveness of the therapy available before the trial. The method is illustrated by an application in an RCT in haemophilia A. We explicitly specify the utility in terms of improvement in primary outcome and compare this with the costs of treating patients, both financial and in terms of potential harm, during the trial and in the future. Results: The optimal sample size for the clinical trial decreases as the size of the population decreases. For non-zero cost of treating future patients, either monetary or in terms of potential harmful effects, stronger evidence is required for approval as the population size increases, though this is not the case if the costs of treating future patients are ignored. Conclusions: Decision-theoretic VOI methods offer a flexible approach with both type I error rate and power (or equivalently trial sample size) depending on the size of the future population for whom the treatment under investigation is intended. This might be particularly suitable for small populations when there is considerable information about the patient population

Approaches to sample size calculation for clinical trials in rare diseases

We discuss 3 alternative approaches to sample size calculation: traditional sample size calculation based on power to show a statistically significant effect, sample size calculation based on assurance, and sample size based on a decision-theoretic approach. These approaches are compared head-to-head for clinical trial situations in rare diseases. Specifically, we consider 3 case studies of rare diseases (Lyell disease, adult-onset Still disease, and cystic fibrosis) with the aim to plan the sample size for an upcoming clinical trial. We outline in detail the reasonable choice of parameters for these approaches for each of the 3 case studies and calculate sample sizes. We stress that the influence of the input parameters needs to be investigated in all approaches and recommend investigating different sample size approaches before deciding finally on the trial size. Highly influencing for the sample size are choice of treatment effect parameter in all approaches and the parameter for the additional cost of the new treatment in the decision-theoretic approach. These should therefore be discussed extensively

Повышение эффективности взаимодействия проектировщиков бортовой радиоэлектронной аппаратуры космических аппаратов на базе интеграции информационных систем

Предложен подход реализации информационного взаимодействия проектировщиков бортовой радиоэлектронной аппаратуры, повышающий эффективность использования ресурсов и управление производственными процессами. Представлена концепция практической реализации предложенного подхода в среде PLM-системы Enovia SmarTeam. Разработан алгоритм сохранения данных проектов EDA-системы Altium Designer в хранилище данных PLM-системы Enovia SmarTeam. Сформирован механизм генерации конструкторских документов на базе формата хранения данных JSON

Contrasting effects of climate change on seasonal survival of a hibernating mammal

Seasonal environmental conditions shape the behavior and life history of virtually all organisms. Climate change is modifying these seasonal environmental conditions, which threatens to disrupt population dynamics. It is conceivable that climatic changes may be beneficial in one season but result in detrimental conditions in another because life-history strategies vary between these time periods. We analyzed the temporal trends in seasonal survival of yellow-bellied marmots (Marmota flaviventer) and explored the environmental drivers using a 40-y dataset from the Colorado Rocky Mountains (USA). Trends in survival revealed divergent seasonal patterns, which were similar across age-classes. Marmot survival declined during winter but generally increased during summer. Interestingly, different environmental factors appeared to drive survival trends across age-classes. Winter survival was largely driven by conditions during the preceding summer and the effect of continued climate change was likely to be mainly negative, whereas the likely outcome of continued climate change on summer survival was generally positive. This study illustrates that seasonal demographic responses need disentangling to accurately forecast the impacts of climate change on animal population dynamics

Does the low prevalence affect the sample size of interventional clinical trials of rare diseases? An analysis of data from the aggregate analysis of clinicaltrials.gov

Background Clinical trials are typically designed using the classical frequentist framework to constrain type I and II error rates. Sample sizes required in such designs typically range from hundreds to thousands of patients which can be challenging for rare diseases. It has been shown that rare disease trials have smaller sample sizes than non-rare disease trials. Indeed some orphan drugs were approved by the European Medicines Agency based on studies with as few as 12 patients. However, some studies supporting marketing authorisation included several hundred patients. In this work, we explore the relationship between disease prevalence and other factors and the size of interventional phase 2 and 3 rare disease trials conducted in the US and/or EU. We downloaded all clinical trials from Aggregate Analysis of ClinialTrials.gov (AACT) and identified rare disease trials by cross-referencing MeSH terms in AACT with the list from Orphadata. We examined the effects of prevalence and phase of study in a multiple linear regression model adjusting for other statistically significant trial characteristics. Results Of 186941 ClinicalTrials.gov trials only 1567 (0.8%) studied a single rare condition with prevalence information from Orphadata. There were 19 (1.2%) trials studying disease with prevalence <1/1,000,000, 126 (8.0%) trials with 1–9/1,000,000, 791 (50.5%) trials with 1–9/100,000 and 631 (40.3%) trials with 1–5/10,000. Of the 1567 trials, 1160 (74%) were phase 2 trials. The fitted mean sample size for the rarest disease (prevalence <1/1,000,000) in phase 2 trials was the lowest (mean, 15.7; 95% CI, 8.7–28.1) but were similar across all the other prevalence classes; mean, 26.2 (16.1–42.6), 33.8 (22.1–51.7) and 35.6 (23.3–54.3) for prevalence 1–9/1,000,000, 1–9/100,000 and 1–5/10,000, respectively. Fitted mean size of phase 3 trials of rarer diseases, <1/1,000,000 (19.2, 6.9–53.2) and 1–9/1,000,000 (33.1, 18.6–58.9), were similar to those in phase 2 but were statistically significant lower than the slightly less rare diseases, 1–9/100,000 (75.3, 48.2–117.6) and 1-5/10,000 (77.7, 49.6–121.8), trials. Conclusions We found that prevalence was associated with the size of phase 3 trials with trials of rarer diseases noticeably smaller than the less rare diseases trials where phase 3 rarer disease (prevalence <1/100,000) trials were more similar in size to those for phase 2 but were larger than those for phase 2 in the less rare disease (prevalence ≥1/100,000) trials

Do current methods of measuring the impact of chronic pain on work reflect the experience of working-age adults? : An integrated mixed methods systematic narrative review

The authors would like to acknowledge contributions to the QUICK study by members of the study advisory group: Patrice Forget, Siladitya Bhattacharya, Peter Goadsby, Cathy Price, David Coggon, Maureen McAllister, Stephen Bevan. The work presented in this manuscript was funded by the Medical Research Council (grant MR/V020676/1).Peer reviewe

Droplet Fluctuations in the Morphology and Kinetics of Martensites

We derive a coarse grained, free-energy functional which describes droplet configurations arising on nucleation of a product crystal within a parent. This involves a new `slow' vacancy mode that lives at the parent-product interface. A mode-coupling theory suggests that a {\it slow} quench from the parent phase produces an equilibrium product, while a {\it fast} quench produces a metastable martensite. In two dimensions, the martensite nuclei grow as `lens-shaped' strips having alternating twin domains, with well-defined front velocities. Several empirically known structural and kinetic relations drop out naturally from our theory.Comment: 4 pages, REVTEX, and 3 .eps figures, compressed and uuencoded, Submitted to Phys. Rev. Let