205 research outputs found

    MyAirCoach: The use of home-monitoring and mHealth systems to predict deterioration in asthma control and the occurrence of asthma exacerbations; Study protocol of an observational study

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    © Published by the BMJ Publishing Group Limited. Introduction Asthma is a variable lung condition whereby patients experience periods of controlled and uncontrolled asthma symptoms. Patients who experience prolonged periods of uncontrolled asthma have a higher incidence of exacerbations and increased morbidity and mortality rates. The ability to determine and to predict levels of asthma control and the occurrence of exacerbations is crucial in asthma management. Therefore, we aimed to determine to what extent physiological, behavioural and environmental data, obtained by mobile healthcare (mHealth) and home-monitoring sensors, as well as patient characteristics, can be used to predict episodes of uncontrolled asthma and the onset of asthma exacerbations. Methods and analysis In an 1-year observational study, patients will be provided with mHealth and home-monitoring systems to record daily measurements for the first-month (phase I) and weekly measurements during a follow-up period of 11 months (phase II). Our study population consists of 150 patients, aged ≄18 years, with a clinician's diagnosis of asthma, currently on controller medication, with uncontrolled asthma and/or minimally one exacerbation in the past 12 months. They will be enrolled over three participating centres, including Leiden, London and Manchester. Our main outcomes are the association between physiological, behavioural and environmental data and (1) the loss of asthma control and (2) the occurrence of asthma exacerbations. Ethics This study was approved by the Medical Ethics Committee of the Leiden University Medical Center in the Netherlands and by the NHS ethics service in the UK. Trial registration number NCT02774772

    An Empirical Assessment of Corporate Environmental Crime-Control Strategies

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    Corporate illegality is often attributed to greed by corporate managers and insufficient legal safeguards. Underlying this argument is an explicit critique of corporate crime regulatory systems. Yet there is little systematic investigation of the relative merits of different types or components of crime-control strategies; research comparing more punitive command-and-control strategies with self-regulatory approaches is particularly lacking. In this Article, we assess these crime prevention-and-control mechanisms in the context of individual and situational risk factors that may increase the likelihood of illegal behavior in the environmental arena. We use data drawn from two groups of business managers who participated in a factorial survey (using vignettes) measuring their intentions to participate in two types of environmental offenses. Generally, results show that the most effective regulatory levers are (1) credible legal sanctions and (2) the certainty and severity of informal discovery by significant others in the firm. We conclude by discussing the implications of our findings for regulatory policy and strategy, and for efforts to account for the role of social norms in corporate environmental compliance

    Corporate Crime Deterrence: A Systematic Review

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    Corporate crime is a poorly understood problem with little known about effective strategies to prevent and control it. Competing definitions of corporate crime affect how the phenomenon is studied and implications for reducing it. Therefore, in this review, we use John Braithwaite’s definition (1984: 6) which specifies that corporate crime is “the conduct of a corporation, or of employees acting on behalf of a corporation, which is proscribed and punishable by law.” Consistent with this approach, this review focuses on various legal strategies aimed at companies and their officials/managers to curtail corporate crime. Interventions may be punitive or cooperative, but the goal is to prevent offending and increase levels of corporate compliance. Our overall objective is to identify and synthesize published and unpublished studies on formal legal and administrative prevention and control strategies—i.e., the actions and programs of government law enforcement agencies, legislative bodies, and regulatory agencies on corporate crime. We then assess the impact of these strategies on individual and company offending. Included are legal and administrative interventions such as new laws or changes in laws, inspections by regulatory agencies, punitive sanctions and non-punitive interventions aimed at deterring or controlling illegal behaviors

    Identification of a Novel “Almost Neutral” Mu Opioid Receptor Antagonist in CHO Cells Expressing the Cloned Human Mu Opioid Receptor

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    The basal (constitutive) activity of G protein-coupled receptors allows for the measurement of inverse agonist activity. Some competitive antagonists turn into inverse agonists under conditions where receptors are constitutively active. In contrast, neutral antagonists have no inverse agonist activity, and they block both agonist and inverse agonist activity. The mu opioid receptor (MOR) demonstrates detectable constitutive activity only after a state of dependence is produced by chronic treatment with a MOR agonist. We therefore sought to identify novel MOR inverse agonists, and novel neutral MOR antagonists in both untreated and agonist-treated MOR cells. CHO cells expressing the cloned human mu receptor (hMOR-CHO cells) were incubated for 20 hr with medium (control) or 10 ÎŒM (2S,4aR,6aR,7R,9S,10aS,10bR)-9-(benzoyloxy)-2-(3-furanyl)dodecahydro-6a,10b-dimethyl-4,10-dioxo-2H-naphtho-[2,1-c]pyran-7-carboxylic acid methyl ester (herkinorin, HERK). HERK-treatment generates a high degree of basal signaling and enhances the ability to detect inverse agonists. [35S]-GTP-Îł-S assays were conducted using established methods. We screened 21 MOR “antagonists” using membranes prepared from HERK-treated hMOR-CHO cells. All antagonists, including CTAP and 6ÎČ-naltrexol, were inverse agonists. However, LTC-2 7 4 ( (-)-3-cyclopropylmethyl-2,3,4,4aα,5,6,7,7aα-octahydro-1H-benzofuro[3,2-e]isoquinolin-9-ol)) showed the lowest efficacy as an inverse agonist, and, at concentrations less than 5 nM, had minimal effects on basal [35S]-GTP-Îł-S binding. Other efforts in this study identified KC-2-009 ((+)-3-((1R,5S)-2-((Z)-3-Phenylallyl)-2-azabicyclo[3.3.1]nonan-5-yl)phenol hydrochloride) as an inverse agonist at untreated MOR cells. In HERK-treated cells, KC-2-009 had the highest efficacy as an inverse agonist. In summary, we identified a novel and selective MOR inverse agonist (KC-2-009), and a novel MOR antagonist (LTC-274) that shows the least inverse agonist activity among 21 MOR antagonists. LTC-274 is a promising lead compound for developing a true MOR neutral antagonist

    Association of latent class analysis-derived multimorbidity clusters with adverse health outcomes in patients with multiple long-term conditions: Comparative results across three UK cohorts

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    Background It remains unclear how to meaningfully classify people living with multimorbidity (multiple long-term conditions (MLTCs)), beyond counting the number of conditions. This paper aims to identify clusters of MLTCs in different age groups and associated risks of adverse health outcomes and service use. Methods Latent class analysis was used to identify MLTCs clusters in different age groups in three cohorts: Secure Anonymised Information Linkage Databank (SAIL) (n = 1,825,289), UK Biobank (n = 502,363), and the UK Household Longitudinal Study (UKHLS) (n = 49,186). Incidence rate ratios (IRR) for MLTC clusters were computed for: all-cause mortality, hospitalisations, and general practice (GP) use over 10 years, using <2 MLTCs as reference. Information on health outcomes and service use were extracted for a ten year follow up period (between 01st Jan 2010 and 31st Dec 2019 for UK Biobank and UKHLS, and between 01st Jan 2011 and 31st Dec 2020 for SAIL). Findings Clustering MLTCs produced largely similar results across different age groups and cohorts. MLTC clusters had distinct associations with health outcomes and service use after accounting for LTC counts, in fully adjusted models. The largest associations with mortality, hospitalisations and GP use in SAIL were observed for the “Pain+” cluster in the age-group 18–36 years (mortality IRR = 4.47, hospitalisation IRR = 1.84; GP use IRR = 2.87) and the “Hypertension, Diabetes & Heart disease” cluster in the age-group 37–54 years (mortality IRR = 4.52, hospitalisation IRR = 1.53, GP use IRR = 2.36). In UK Biobank, the “Cancer, Thyroid disease & Rheumatoid arthritis” cluster in the age group 37–54 years had the largest association with mortality (IRR = 2.47). Cardiometabolic clusters across all age groups, pain/mental health clusters in younger groups, and cancer and pulmonary related clusters in older age groups had higher risk for all outcomes. In UKHLS, MLTC clusters were not significantly associated with higher risk of adverse outcomes, except for the hospitalisation in the age-group 18–36 years. Interpretation Personalising care around MLTC clusters that have higher risk of adverse outcomes may have important implications for practice (in relation to secondary prevention), policy (with allocation of health care resources), and research (intervention development and targeting), for people living with MLTCs. Funding This study was funded by the National Institute for Health and Care Research (NIHR; Personalised Exercise-Rehabilitation FOR people with Multiple long-term conditions (multimorbidity)—NIHR202020)

    Associations of quantity and quality of carbohydrate sources with subjective appetite sensations during 3-year weight-loss maintenance : Results from the PREVIEW intervention study

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    Publisher Copyright: © 2021 The Author(s)Background & aims: The association of quantity and quality of carbohydrate sources with appetite during long-term weight-loss maintenance (WLM) after intentional weight loss (WL) is unclear. We aimed to investigate longitudinal associations of quantity and quality of carbohydrate sources with changes in subjective appetite sensations during WLM. Methods: This secondary analysis evaluated longitudinal data from the 3-year WLM phase of the PREVIEW study, a 2 × 2 factorial (diet–physical activity arms), multi-center, randomized trial. 1279 individuals with overweight or obesity and prediabetes (25–70 years; BMI≄25 kg m−2) were included. Individuals were merged into 1 group to assess longitudinal associations of yearly changes in appetite sensations. Quantity and quality of carbohydrate sources including total carbohydrate, glycemic index (GI), glycemic load (GL), and total dietary fiber were assessed via 4-day food diaries at 4 timepoints (26, 52, 104, and 156 weeks) during WLM. Visual analog scales were used to assess appetite sensations in the previous week. Results: During WLM, participants consumed on average 160.6 (25th, 75th percentiles 131.1, 195.8) g·day−1 of total carbohydrate, with GI 53.8 (48.7, 58.8) and GL 85.3 (67.2, 108.9) g day−1, and 22.3 (17.6, 27.3) g·day−1 of dietary fiber. In the available-case analysis, multivariable-adjusted linear mixed models with repeated measures showed that each 30-g increment in total carbohydrate was associated with increases in hunger (1.36 mm year−1, 95% CI 0.77, 1.95, P < 0.001), desire to eat (1.10 mm year−1, 0.59, 1.60, P < 0.001), desire to eat something sweet (0.99 mm year−1, 0.30, 1.68, P = 0.005), and weight regain (0.20%·year−1, 0.03, 0.36, P = 0.022). Increasing GI was associated with weight regain, but not associated with increases in appetite sensations. Each 20-unit increment in GL was associated with increases in hunger (0.92 mm year−1, 0.33, 1.51, P = 0.002), desire to eat (1.12 mm year−1, 0.62, 1.62, P < 0.001), desire to eat something sweet (1.13 mm year−1, 0.44, 1.81, P < 0.001), and weight regain (0.35%·year−1, 0.18, 0.52, P < 0.001). Surprisingly, dietary fiber was also associated with increases in desire to eat, after adjustment for carbohydrate or GL. Conclusions: In participants with moderate carbohydrate and dietary fiber intake, and low to moderate GI, we found that higher total carbohydrate, GL, and total fiber, but not GI, were associated with increases in subjective desire to eat or hunger over 3 years. This study was registered as ClinicalTrials.gov, NCT01777893.Peer reviewe
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