Stop-app: Using the Behaviour Change Wheel to develop an app to increase uptake and attendance at NHS Stop Smoking Services.

Smokers who attend NHS Stop Smoking Services (SSS) are four times more likely to stop smoking; however, uptake has been in decline. We report the development of an intervention designed to increase uptake of SSS, from a more motivated self-selected sample of smokers. In Phase 1 we collected data to explore the barriers and facilitators to people using SSS. In Phase 2, data from extant literature and Phase 1 were subject to behavioural analysis, as outlined by the Behaviour Change Wheel (BCW) framework. Relevant Behaviour Change Techniques (BCTs) were identified in order to address these, informing the content of the StopApp intervention. In Phase 3 we assessed the acceptability of the StopApp. Smokers and ex-smokers identified a number of barriers to attending SSS, including a lack of knowledge about what happens at SSS (Capability); the belief that SSS is not easy to access (Opportunity); that there would be ’scare tactics’ or ‘nagging’; and not knowing anyone who had been and successfully quit (Motivation). The ‘StopApp’ is in development and will link in with the commissioned SSS booking system. Examples of the content and functionality of the app are outlined. The next phase will involve a full trial to test effectiveness

Characteristics associated with willingness to participate in a randomized controlled behavioral clinical trial using home-based personal computers and a webcam

Abstract Background Trials aimed at preventing cognitive decline through cognitive stimulation among those with normal cognition or mild cognitive impairment are of significant importance in delaying the onset of dementia and reducing dementia prevalence. One challenge in these prevention trials is sample recruitment bias. Those willing to volunteer for these trials could be socially active, in relatively good health, and have high educational levels and cognitive function. These participants’ characteristics could reduce the generalizability of study results and, more importantly, mask trial effects. We developed a randomized controlled trial to examine whether conversation-based cognitive stimulation delivered through personal computers, a webcam and the internet would have a positive effect on cognitive function among older adults with normal cognition or mild cognitive impairment. To examine the selectivity of samples, we conducted a mass mail-in survey distribution among community-dwelling older adults, assessing factors associated with a willingness to participate in the trial. Methods Two thousand mail-in surveys were distributed to retirement communities in order to collect data on demographics, the nature and frequency of social activities, personal computer use and additional health-related variables, and interest in the prevention study. We also asked for their contact information if they were interested in being contacted as potential participants in the trial. Results Of 1,102 surveys returned (55.1% response rate), 983 surveys had complete data for all the variables of interest. Among them, 309 showed interest in the study and provided their contact information (operationally defined as the committed with interest group), 74 provided contact information without interest in the study (committed without interest group), 66 showed interest, but provided no contact information (interest only group), and 534 showed no interest and provided no contact information (no interest group). Compared with the no interest group, the committed with interest group were more likely to be personal computer users (odds ratio (OR) = 2.78), physically active (OR = 1.03) and had higher levels of loneliness (OR = 1.16). Conclusion Increasing potential participants’ familiarity with a personal computer and the internet before trial recruitment could increase participation rates and improve the generalizability of future studies of this type. Trial registration The trial was registered on 29 March 2012 at ClinicalTirals.gov (ID number NCT01571427 ).http://deepblue.lib.umich.edu/bitstream/2027.42/111291/1/13063_2013_Article_2385.pd

Characteristics Associated with Willingness to Participate in a Randomized Controlled Behavioral Clinical Trial Using Home-Based Personal Computers and a Webcam

BACKGROUND: Trials aimed at preventing cognitive decline through cognitive stimulation among those with normal cognition or mild cognitive impairment are of significant importance in delaying the onset of dementia and reducing dementia prevalence. One challenge in these prevention trials is sample recruitment bias. Those willing to volunteer for these trials could be socially active, in relatively good health, and have high educational levels and cognitive function. These participants\u27 characteristics could reduce the generalizability of study results and, more importantly, mask trial effects. We developed a randomized controlled trial to examine whether conversation-based cognitive stimulation delivered through personal computers, a webcam and the internet would have a positive effect on cognitive function among older adults with normal cognition or mild cognitive impairment. To examine the selectivity of samples, we conducted a mass mail-in survey distribution among community-dwelling older adults, assessing factors associated with a willingness to participate in the trial. METHODS: Two thousand mail-in surveys were distributed to retirement communities in order to collect data on demographics, the nature and frequency of social activities, personal computer use and additional health-related variables, and interest in the prevention study. We also asked for their contact information if they were interested in being contacted as potential participants in the trial. RESULTS: Of 1,102 surveys returned (55.1% response rate), 983 surveys had complete data for all the variables of interest. Among them, 309 showed interest in the study and provided their contact information (operationally defined as the committed with interest group), 74 provided contact information without interest in the study (committed without interest group), 66 showed interest, but provided no contact information (interest only group), and 534 showed no interest and provided no contact information (no interest group). Compared with the no interest group, the committed with interest group were more likely to be personal computer users (odds ratio (OR) = 2.78), physically active (OR = 1.03) and had higher levels of loneliness (OR = 1.16). CONCLUSION: Increasing potential participants\u27 familiarity with a personal computer and the internet before trial recruitment could increase participation rates and improve the generalizability of future studies of this type. TRIAL REGISTRATION: The trial was registered on 29 March 2012 at ClinicalTirals.gov (ID number NCT01571427)

Nonparametric Bayesian inference for perturbed and orthologous gene regulatory networks

Motivation: The generation of time series transcriptomic datasets collected under multiple experimental conditions has proven to be a powerful approach for disentangling complex biological processes, allowing for the reverse engineering of gene regulatory networks (GRNs). Most methods for reverse engineering GRNs from multiple datasets assume that each of the time series were generated from networks with identical topology. In this study, we outline a hierarchical, non-parametric Bayesian approach for reverse engineering GRNs using multiple time series that can be applied in a number of novel situations including: (i) where different, but overlapping sets of transcription factors are expected to bind in the different experimental conditions; that is, where switching events could potentially arise under the different treatments and (ii) for inference in evolutionary related species in which orthologous GRNs exist. More generally, the method can be used to identify context-specific regulation by leveraging time series gene expression data alongside methods that can identify putative lists of transcription factors or transcription factor targets. Results: The hierarchical inference outperforms related (but non-hierarchical) approaches when the networks used to generate the data were identical, and performs comparably even when the networks used to generate data were independent. The method was subsequently used alongside yeast one hybrid and microarray time series data to infer potential transcriptional switches in Arabidopsis thaliana response to stress. The results confirm previous biological studies and allow for additional insights into gene regulation under various abiotic stresses. Availability: The methods outlined in this article have been implemented in Matlab and are available on request

Weekly observations of online survey metadata obtained through home computer use allow for detection of changes in everyday cognition before transition to mild cognitive impairment

IntroductionSubtle changes in instrumental activities of daily living often accompany the onset of mild cognitive impairment (MCI) but are difficult to measure using conventional tests.MethodsWeekly online survey metadata metrics, annual neuropsychological tests, and an instrumental activity of daily living questionnaire were examined in 110 healthy older adults with intact cognition (mean age = 85 years) followed up for up to 3.6 years; 29 transitioned to MCI during study follow‐up.ResultsIn the baseline period, incident MCI participants completed their weekly surveys 1.4 hours later in the day than stable cognitively intact participants, P = .03, d = 0.47. Significant associations were found between earlier survey start time of day and higher memory (r = −0.34; P < .001) and visuospatial test scores (r = −0.37; P < .0001). Longitudinally, incident MCI participants showed an increase in survey completion time by 3 seconds per month for more than the year before diagnosis compared with stable cognitively intact participants (β = 0.12, SE = 0.04, t = 2.8; P = .006).DiscussionWeekly online survey metadata allowed for detection of changes in everyday cognition before transition to MCI.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/152601/1/alzjjalz201707756.pd

Public Perceptions of Wildlife-Associated Disease: Risk Communication Matters

Wildlife professionals working at the interface where conflicts arise between people and wild animals have an exceptional responsibility in the long-term interest of sustaining society’s support for wildlife and its conservation by resolving human–wildlife conflicts so that people continue to view wildlife as a valued resource. The challenge of understanding and responding to people’s concerns about wildlife is particularly acute in situations involving wildlife-associated disease and may be addressed through One Health communication. Two important questions arise in this work: (1) how will people react to the message that human health and wildlife health are linked?; and (2) will wildlife-associated disease foster negative attitudes about wildlife as reservoirs, vectors, or carriers of disease harmful to humans? The answers to these questions will depend in part on whether wildlife professionals successfully manage wildlife disease and communicate the associated risks in a way that promotes societal advocacy for healthy wildlife rather than calls for eliminating wildlife because they are viewed as disease-carrying pests. This work requires great care in both formal and informal communication. We focus on risk perception, and we briefly discuss guidance available for risk communication, including formation of key messages and the importance of word choices. We conclude that the risk perception and communication research available is helpful but inadequate, and that thoughtful practice with respect to message and word choice is needed

Toward a Continuous Intravascular Glucose Monitoring System

Proof-of-concept studies that display the potential of using a glucose-sensitive hydrogel as a continuous glucose sensor are presented. The swelling ratio, porosity, and diffusivity of the hydrogel increased with glucose concentration. In glucose solutions of 50, 100, 200, and 300 mg/dL, the hydrogel swelling ratios were 4.9, 12.3, 15.9, and 21.7, respectively, and the swelling was reversible. The impedance across the hydrogel depended solely on the thickness and had an average increase of 47 Ω/mm. The hydrogels exposed to a hyperglycemic solution were more porous than the hydrogels exposed to a normal glycemic solution. The diffusivity of 390 Da MW fluorescein isothiocyanate in hydrogels exposed to normal and hyperglycemic solutions was examined using fluorescence recovery after photobleaching and was found to be 9.3 × 10−14 and 41.4 × 10−14 m2/s, respectively, compared to 6.2 × 10−10 m2/s in glucose solution. There was no significant difference between the permeability of hydrogels in normal and hyperglycemic glucose solutions with averages being 5.26 × 10−17 m2 and 5.80 × 10−17 m2, respectively, which resembles 2–4% agarose gels. A prototype design is presented for continuous intravascular glucose monitoring by attaching a glucose sensor to an FDA-approved stent

High-resolution temporal profiling of transcripts during Arabidopsis leaf senescence reveals a distinct chronology of processes and regulation

Leaf senescence is an essential developmental process that impacts dramatically on crop yields and involves altered regulation of thousands of genes and many metabolic and signaling pathways, resulting in major changes in the leaf. The regulation of senescence is complex, and although senescence regulatory genes have been characterized, there is little information on how these function in the global control of the process. We used microarray analysis to obtain a highresolution time-course profile of gene expression during development of a single leaf over a 3-week period to senescence. A complex experimental design approach and a combination of methods were used to extract high-quality replicated data and to identify differentially expressed genes. The multiple time points enable the use of highly informative clustering to reveal distinct time points at which signaling and metabolic pathways change. Analysis of motif enrichment, as well as comparison of transcription factor (TF) families showing altered expression over the time course, identify clear groups of TFs active at different stages of leaf development and senescence. These data enable connection of metabolic processes, signaling pathways, and specific TF activity, which will underpin the development of network models to elucidate the process of senescence

Bringing numerous methods for expression and promoter analysis to a public cloud computing service

Every year, a large number of novel algorithms are introduced to the scientific community for a myriad of applications, but using these across different research groups is often troublesome, due to suboptimal implementations and specific dependency requirements. This does not have to be the case, as public cloud computing services can easily house tractable implementations within self-contained dependency environments, making the methods easily accessible to a wider public. We have taken 14 popular methods, the majority related to expression data or promoter analysis, developed these up to a good implementation standard and housed the tools in isolated Docker containers which we integrated into the CyVerse Discovery Environment, making these easily usable for a wide community as part of the CyVerse UK project

Cohort profile : the Scottish Diabetes Research Network national diabetes cohort - a population-based cohort of people with diabetes in Scotland

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