Individuals Maintain Similar Rates of Protein Synthesis Over Time on the Same Plane of Nutrition Under Controlled Environmental Conditions

Consistent individual differences in animal performance drive individual fitness under variable environmental conditions and provide the framework through which natural selection can operate. Underlying this concept is the assumption that individuals will display consistent levels of performance in fitness-related traits and interest has focused on individual variation and broad sense repeatability in a range of behavioural and physiological traits. Despite playing a central role in maintenance and growth, and with considerable inter-individual variation documented, broad sense repeatability in rates of protein synthesis has not been assessed. In this study we show for the first time that juvenile flounder Platichthys flesus reared under controlled environmental conditions on the same plane of nutrition for 46 days maintain consistent whole-animal absolute rates of protein synthesis (As). By feeding meals containing 15N-labelled protein and using a stochastic end-point model, two non-terminal measures of protein synthesis were made 32 days apart (d14 and d46). As values (mass-corrected to a standard mass of 12 g) showed 2- to 3-fold variation between individuals on d14 and d46 but individuals showed similar As values on both days with a broad sense repeatability estimate of 0.684 indicating significant consistency in physiological performance under controlled experimental conditions. The use of non-terminal methodologies in studies of animal ecophysiology to make repeat measures of physiological performance enables known individuals to be tracked across changing conditions. Adopting this approach, repeat measures of protein synthesis under controlled conditions will allow individual ontogenetic changes in protein metabolism to be assessed to better understand the ageing process and to determine individual physiological adaptive capacity, and associated energetic costs of adaptation, to global environmental change

Using Healthcare Data in Embedded Pragmatic Clinical Trials among People Living with Dementia and Their Caregivers: State of the Art

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/156003/1/jgs16617_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/156003/2/jgs16617.pd

Microenvironment temperature prediction between body and seat interface using autoregressive data-driven model

There is a need to develop a greater understanding of temperature at the skin–seat interface during prolonged seating from the perspectives of both industrial design (comfort/discomfort) and medical care (skin ulcer formation). Here we test the concept of predicting temperature at the seat surface and skin interface during prolonged sitting (such as required from wheelchair users). As caregivers are usually busy, such a method would give them warning ahead of a problem. This paper describes a data-driven model capable of predicting thermal changes and thus having the potential to provide an early warning (15- to 25-min ahead prediction) of an impending temperature that may increase the risk for potential skin damages for those subject to enforced sitting and who have little or no sensory feedback from this area. Initially, the oscillations of the original signal are suppressed using the reconstruction strategy of empirical mode decomposition (EMD). Consequentially, the autoregressive data-driven model can be used to predict future thermal trends based on a shorter period of acquisition, which reduces the possibility of introducing human errors and artefacts associated with longer duration “enforced” sitting by volunteers. In this study, the method had a maximum predictive error of <0.4 °C when used to predict the temperature at the seat and skin interface 15 min ahead, but required 45 min data prior to give this accuracy. Although the 45 min front loading of data appears large (in proportion to the 15 min prediction), a relative strength derives from the fact that the same algorithm could be used on the other 4 sitting datasets created by the same individual, suggesting that the period of 45 min required to train the algorithm is transferable to other data from the same individual. This approach might be developed (along with incorporation of other measures such as movement and humidity) into a system that can give caregivers prior warning to help avoid exacerbating the skin disorders of patients who suffer from low body insensitivity and disability requiring them to be immobile in seats for prolonged periods

Diagnosed prevalence of Alzheimer’s disease and related dementias in Medicare Advantage plans

IntroductionOne- third of Medicare beneficiaries are enrolled in Medicare Advantage (MA). Yet, little is known about MA beneficiaries diagnosed with Alzheimer’s disease (AD) and AD- related dementias (AD/ADRD).MethodsWe calculated the prevalence of AD/ADRD diagnoses in 2014 and 2016 in three MA plans. We determined the demographic characteristics of beneficiaries diagnosed with AD/ADRD, and whether they disenrolled from the MA plan for any reason within 364 days from the index date.ResultsIn 2014 and 2016, the overall prevalence of AD/ADRD diagnoses was 5.6% and 6.5%, respectively. In 2016, AD/ADRD beneficiaries were on average 82.4 (SD = 7.4) years of age, 61.8% female, and had multiple comorbidities. By 364 days post- index date, 32% of beneficiaries with AD/ADRD had disenrolled from their plan. The demographic characteristics of 2014 beneficiaries with diagnosed AD/ADRD were similar to their 2016 counterparts.DiscussionThe prevalence of AD/ADRD diagnosis in MA is lower than rates reported in Medicare fee- for- service.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156169/2/dad212048.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156169/1/dad212048_am.pd

Noise removal applied to a temperature signal from body and seat contact surface based on the EMD method

People today spend longer seated resulting from changes in demand on the workforce. As a result there is a need for a greater understanding of factors affecting pressure sore formation and comfort in general. In order to monitor the body-cushion interface temperature, we have developed a portable five-channel temperature measuring system which can be powered by a laptop. An Empirical Mode Decomposition (EMD) was used to remove noise of thermal data between body and seat contact surface. The performance of this data driven filter was compared with three other filters (medium filter, adaptive filter and wavelet filter) with the help of the goodness of fitness statistics as judgment criteria. Results showed the EMD-based filter worked better than traditional de-noising algorithms with the lowest RMSE (root-mean-square-error) and the highest R2 values

The Verifying Compiler: A Grand Challenge for Computing Research

Abstract. This contribution proposes a set of criteria that distinguish a grand challenge in science or engineering from the many other kinds of short-term or long-term research problems that engage the interest of scientists and engineers. As an example drawn from Computer Science, it revives an old challenge: the construction and application of a verifying compiler that guarantees correctness of a program before running it. Introduction. The primary purpose of the formulation and promulgation of a grand challenge is the advancement of science or engineering. A grand challenge represents a commitment by a significant section of the research community to work together towards a common goal, agreed to be valuable and achievable by a team effort within a predicted timescale. The challenge is formulated by th

Dietary metabolite profiling brings new insight into the relationship between nutrition and metabolic risk: An IMI Direct study

Background: Dietary advice remains the cornerstone of prevention and management of type 2 diabetes (T2D). However, understanding the efficacy of dietary interventions is confounded by the challenges inherent in assessing free living diet. Here we profiled dietary metabolites to investigate glycaemic deterioration and cardiometabolic risk in people at risk of or living with T2D. Methods: We analysed data from plasma collected at baseline and 18-month follow-up in individuals from the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohort 1 n=403 individuals with normal or impaired glucose regulation (prediabetic) and cohort 2 n=458 individuals with new onset of T2D. A dietary metabolite profile model (Tpred) was constructed using multivariate regression of 113 plasma metabolites obtained from targeted metabolomics assays. The continuous Tpred score was used to explore the relationships between diet, glycaemic deterioration and cardio-metabolic risk via multiple linear regression models. Findings: A higher Tpred was associated with healthier diets high in wholegrain (β=0.004 g, p=0.02 and β=0.003 g, p=0.03) and lower energy intake (β=-0.0002 kcal, p=0.04 and β=-0.0002 kcal, p=0.003), and saturated fat (β=-0.03 g, p<.0001 and β=-0.03 g, p<.0001), respectively for cohort 1 and 2. In both cohorts a higher Tpred score was also associated with lower total body adiposity and improved lipid profiles HDL-cholesterol (β=0.07 mmol/L, p<.0001), (β=0.08 mmol/L, p=0.0002), and triglycerides (β=-0.1 mmol/L, p=0.003), (β=-0.2 mmol/L, p=0.0002), respectively for cohort 1 and 2. In cohort 2, the Tpred score was negatively associated with liver fat content (β=-0.74 %, p<.0001), and lower fasting concentrations of HbA1c (β=-0.9mmol/mol, p=0.02), glucose (β=-0.2 mmol/L, p=0.01) and insulin (β=-11.0 pmol/mol, p=0.01). Longitudinal analysis showed at 18-month follow up a higher Tpred score was also associated lower total body adiposity in both cohorts and lower fasting glucose (β=-0.2 mmol/L, p=0.03) and insulin (β=-9.2 pmol/mol, p=0.04) concentrations in cohort 2. Interpretation: Plasma dietary metabolite profiling provides objective measures of diet intake, showing a relationship to glycaemic deterioration and cardiometabolic health

Green function techniques in the treatment of quantum transport at the molecular scale

The theoretical investigation of charge (and spin) transport at nanometer length scales requires the use of advanced and powerful techniques able to deal with the dynamical properties of the relevant physical systems, to explicitly include out-of-equilibrium situations typical for electrical/heat transport as well as to take into account interaction effects in a systematic way. Equilibrium Green function techniques and their extension to non-equilibrium situations via the Keldysh formalism build one of the pillars of current state-of-the-art approaches to quantum transport which have been implemented in both model Hamiltonian formulations and first-principle methodologies. We offer a tutorial overview of the applications of Green functions to deal with some fundamental aspects of charge transport at the nanoscale, mainly focusing on applications to model Hamiltonian formulations.Comment: Tutorial review, LaTeX, 129 pages, 41 figures, 300 references, submitted to Springer series "Lecture Notes in Physics

Measurement of the p-pbar -> Wgamma + X cross section at sqrt(s) = 1.96 TeV and WWgamma anomalous coupling limits

The WWgamma triple gauge boson coupling parameters are studied using p-pbar -> l nu gamma + X (l = e,mu) events at sqrt(s) = 1.96 TeV. The data were collected with the DO detector from an integrated luminosity of 162 pb^{-1} delivered by the Fermilab Tevatron Collider. The cross section times branching fraction for p-pbar -> W(gamma) + X -> l nu gamma + X with E_T^{gamma} > 8 GeV and Delta R_{l gamma} > 0.7 is 14.8 +/- 1.6 (stat) +/- 1.0 (syst) +/- 1.0 (lum) pb. The one-dimensional 95% confidence level limits on anomalous couplings are -0.88 < Delta kappa_{gamma} < 0.96 and -0.20 < lambda_{gamma} < 0.20.Comment: Submitted to Phys. Rev. D Rapid Communication

Measurement of the ttbar Production Cross Section in ppbar Collisions at sqrt{s} = 1.96 TeV using Kinematic Characteristics of Lepton + Jets Events

We present a measurement of the top quark pair ttbar production cross section in ppbar collisions at a center-of-mass energy of 1.96 TeV using 230 pb**{-1} of data collected by the DO detector at the Fermilab Tevatron Collider. We select events with one charged lepton (electron or muon), large missing transverse energy, and at least four jets, and extract the ttbar content of the sample based on the kinematic characteristics of the events. For a top quark mass of 175 GeV, we measure sigma(ttbar) = 6.7 {+1.4-1.3} (stat) {+1.6- 1.1} (syst) +/-0.4 (lumi) pb, in good agreement with the standard model prediction.Comment: submitted to Phys.Rev.Let