UNM NIH Investigator Policy Knowledge and Attitudes Survey

Survey instrument used to assess UNM NIH-funded investigators\u27 knowledge, acceptance and perceived barriers to compliance with the NIH Enhanced Public Access Policy

How effective is the Forestry Commission Scotland's woodland improvement programme--'Woods In and Around Towns' (WIAT)--at improving psychological well-being in deprived urban communities? A quasi-experimental study

Introduction: There is a growing body of evidence that suggests that green spaces may positively influence psychological well-being. This project is designed to take advantage of a natural experiment where planned physical and social interventions to enhance access to natural environments in deprived communities provide an opportunity to prospectively assess impacts on perceived stress and mental well-being.<p></p> Study design and methods: A controlled, prospective study comprising a repeat cross-sectional survey of residents living within 1.5 km of intervention and comparison sites. Three waves of data will be collected: prephysical environment intervention (2013); postphysical environment intervention (2014) and postwoodland promotion social intervention (2015). The primary outcome will be a measure of perceived stress (Perceived Stress Scale) preintervention and postintervention. Secondary, self-report outcomes include: mental well-being (Short Warwick-Edinburgh Mental Well-being Scale), changes in physical activity (IPAQ-short form), health (EuroQoL EQ-5D), perception and use of the woodlands, connectedness to nature (Inclusion of Nature in Self Scale), social cohesion and social capital. An environmental audit will complement the study by evaluating the physical changes in the environment over time and recording any other contextual changes over time. A process evaluation will assess the implementation of the programme. A health economics analysis will assess the cost consequences of each stage of the intervention in relation to the primary and secondary outcomes of the study.<p></p> Ethics and dissemination: Ethical approval has been given by the University of Edinburgh, Edinburgh College of Art Research, Ethics and Knowledge Exchange Committee (ref. 19/06/2012). Findings will be disseminated through peer-reviewed publications, national and international conferences and, at the final stage of the project, through a workshop for those interested in implementing environmental interventions.<p></p&gt

Amortised resource analysis with separation logic

Type-based amortised resource analysis following Hofmann and Jost—where resources are associated with individual elements of data structures and doled out to the programmer under a linear typing discipline—have been successful in providing concrete resource bounds for functional programs, with good support for inference. In this work we translate the idea of amortised resource analysis to imperative languages by embedding a logic of resources, based on Bunched Implications, within Separation Logic. The Separation Logic component allows us to assert the presence and shape of mutable data structures on the heap, while the resource component allows us to state the resources associated with each member of the structure. We present the logic on a small imperative language with procedures and mutable heap, based on Java bytecode. We have formalised the logic within the Coq proof assistant and extracted a certified verification condition generator. We demonstrate the logic on some examples, including proving termination of in-place list reversal on lists with cyclic tails

A phase II, randomized, open-label, 52-week study of seladelpar in patients with primary biliary cholangitis

Background & aims: We examined the efficacy and safety of seladelpar, a selective peroxisome proliferator-activated receptor-delta agonist, in adults with primary biliary cholangitis (PBC) at risk of disease progression (alkaline phosphatase [ALP] ≥1.67xupper limit of normal [ULN]) who were receiving or intolerant to ursodeoxycholic acid. Methods: In this 52-week, phase II, dose-ranging, open-label study, patients were randomized (1:1) to seladelpar 5 mg/day (n = 53) or 10 mg/day (n = 55) or assigned to 2 mg/day (n = 11; United Kingdom sites after interim analysis) for 12 weeks. Doses could then be uptitrated to 10 mg/day. The primary efficacy endpoint was ALP change from baseline to Week 8. Results: Mean baseline ALP was 300, 345, and 295 U/L in the 2 mg, 5 mg, and 10 mg cohorts, respectively. Twenty-one percent of patients had cirrhosis, 71% had pruritus. At Week 8, mean ± standard error ALP reductions from baseline were 26 ± 2.8%, 33 ± 2.6%, and 41 ± 1.8% in the 2 mg (n = 11), 5 mg (n = 49), and 10 mg (n = 52) cohorts (all p ≤0.005), respectively. Responses were maintained or improved at Week 52, after dose escalation in 91% and 80% of the 2 mg and 5 mg cohorts, respectively. At Week 52, composite response (ALP <1.67xULN, ≥15% ALP decrease, and normal total bilirubin) rates were 64%, 53%, and 67%, and ALP normalization rates were 9%, 13%, and 33% in the 2 mg, 5 mg, and 10 mg cohorts, respectively. Pruritus visual analog scale score was decreased in the 5 mg and 10 mg cohorts. There were no treatment-related serious adverse events, and 4 patients discontinued due to adverse events. Conclusions: Seladelpar demonstrated robust, dose-dependent, clinically significant, and durable improvements in biochemical markers of cholestasis and inflammation in patients with PBC at risk of disease progression. Seladelpar appeared safe and well tolerated and was not associated with any increase in pruritus. Gov number: NCT02955602 CLINICALTRIALSREGISTER. Eu number: 2016-002996-91 LAY SUMMARY: Current treatment options for patients living with primary biliary cholangitis (PBC) are not optimal due to inadequate effectiveness or undesirable side effects. Patients with PBC who took seladelpar, a new treatment being developed for PBC, at increasing doses (2, 5, or 10 mg/day) for 1 year had clinically significant, dose-dependent improvements in key liver tests. Treatment appeared safe and was not associated with any worsening in patient self-reported itch scores. Keywords: Clinical study; Primary biliary cholangitis; Seladelpa

Understanding causality and uncertainty in volcanic observations: an example of forecasting eruptive activity on Soufrière Hills Volcano, Montserrat

Following a cessation in eruptive activity it is important to understand how a volcano will behave in the future and when it may next erupt. Such an assessment can be based on the volcano's long-term pattern of behaviour and insights into its current state via monitoring observations. We present a Bayesian network that integrates these two strands of evidence to forecast future eruptive scenarios using expert elicitation. The Bayesian approach provides a framework to quantify the magmatic causes in terms of volcanic effects (i.e., eruption and unrest). In October 2013, an expert elicitation was performed to populate a Bayesian network designed to help forecast future eruptive (in-)activity at Soufrière Hills Volcano. The Bayesian network was devised to assess the state of the shallow magmatic system, as a means to forecast the future eruptive activity in the context of the long-term behaviour at similar dome-building volcanoes. The findings highlight coherence amongst experts when interpreting the current behaviour of the volcano, but reveal considerable ambiguity when relating this to longer patterns of volcanism at dome-building volcanoes, as a class. By asking questions in terms of magmatic causes, the Bayesian approach highlights the importance of using short-term unrest indicators from monitoring data as evidence in long-term forecasts at volcanoes. Furthermore, it highlights potential biases in the judgements of volcanologists and identifies sources of uncertainty in terms of magmatic causes rather than scenario-based outcomes

Expression of the androgen receptor and an androgen-responsive protein, apolipoprotein D, in human breast cancer.

Little is known regarding the activity and function of the androgen receptor (AR) in human breast cancer. In the present study AR was evaluated in untreated primary breast cancers using antisera to the amino- and carboxy-termini of the receptor and quantitated using colour video image analysis. A strong correlation between tissue concentration and percentage AR-positive cells was observed for each antiserum. However, comparison of percentage positive cells using the amino- and carboxy-terminal AR antisera in individual breast cancer specimens revealed a subset of tumours with discordantly increased staining for the carboxy terminus. These findings suggest the presence of amino-terminal-truncated AR in a proportion of breast cancer cells or presence of AR mutations or associated protein alterations that affect binding of the amino-terminal AR antiserum. Immunohistochemical expression of the androgen-regulated glycoprotein, apolipoprotein D (apo-D), was also evaluated in the breast cancer specimens. Focal positivity of apo-D staining, which did not always co-localise with AR-positive cells, was observed within breast tumours. Furthermore, no correlation was evident between percentage positive cells stained for AR and apo-D in breast cancer specimens. These findings indicate that, although apo-D expression is androgen regulated in human breast cancer cell lines in vitro, its expression in primary breast cancers may be regulated by other factors. The expression of AR in primary breast cancers also suggests that the receptor may be involved in tumour responsiveness or in abnormal responses to endocrine therapies

Automatic Inference of Upper Bounds for Recurrence Relations in Cost Analysis

The classical approach to automatic cost analysis consists of two phases. Given a program and some measure of cost, we first produce recurrence relations (RRs) which capture the cost of our program in terms of the size of its input data. Second, we convert such RRs into closed form (i.e., without recurrences). Whereas the first phase has received considerable attention, with a number of cost analyses available for a variety of programming languages, the second phase has received comparatively little attention. In this paper we first study the features of RRs generated by automatic cost analysis and discuss why existing computer algebra systems are not appropriate for automatically obtaining closed form solutions nor upper bounds of them. Then we present, to our knowledge, the first practical framework for the fully automatic generation of reasonably accurate upper bounds of RRs originating from cost analysis of a wide range of programs. It is based on the inference of ranking functions and loop invariants and on partial evaluation