641 research outputs found

    The day-to-day reliability of resting metabolic rate

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    This purpose of this study was to determine the day-to-day reliability of resting metabolic rate. 18 college students, (mean age 22 +/- 3.6 yrs, height 65.78 +/- 22.0 in., body mass 68.05 +/- 10.34 kg, percent body fat 23 +/- 6.5%) gave informed consent to participate in the study. RMR was measured on four separate days over a period of 14 days. Height, weight, and resting heart rate were also recorded on each testing day. Body composition was assessed on the first day. Energy intake, energy expenditure, and caffeine intake were controlled between days. Each test was done between 7 and 9 AM each morning, and RMR was measured by open circuit spirometry over a 35-minute period. Reliability was assessed using an Intraclass Correlation Coefficient. The reliability across days was R = 0.97. The overall mean VO2 was 3.35 +/- .77 ml/kg/min. The mean VO2 was 3.34 +/- .35 ml/kg/min on day one, 3.29 +/- .29 ml kg-1&dotbelow; min-1 on day two, 3.36 +/- .37 ml kg-1&dotbelow; min-1 on day three, and 3.37 +/- .50 ml kg-1&dotbelow; min -1 on day four. This study demonstrates that under controlled conditions, resting metabolic rate is a very stable measurement. Therefore, under these conditions, a single RMR measurement can be considered an estimate of the individual\u27s true RMR, and confidence can be placed in that measurement

    Skunk River Review 2016-2018

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    https://openspace.dmacc.edu/skunkriver/1025/thumbnail.jp

    Weight Gain Trajectories Associated With Elevated C‐Reactive Protein Levels in Chinese Adults

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    BACKGROUND: Recent longitudinal work suggests that weight change is an important risk factor for inflammation across the full range of BMI. However, few studies have examined whether the risk of inflammation differs by patterns of weight gain over time. Using latent class trajectory analysis, we test whether patterns of weight gain are associated with elevated high-sensitivity C-reactive protein (hs-CRP 2-10 mg/L). METHODS AND RESULTS: Data come from China Health and Nutrition Survey (CHNS) participants (n=5536), aged 18 at baseline to 66 years in 2009, with measured weight over 18 years. Latent class trajectory analysis was used to identify weight-change trajectories in 6 age and sex strata. Multivariable general linear mixed-effects models fit with a logit link were used to assess the risk of elevated hs-CRP across weight trajectory classes. Models were fit within age and sex strata, controlling for baseline weight, adult height, and smoking, and included random intercepts to account for community-level correlation. Steeper weight-gain trajectories were associated with greater risk of elevated hs-CRP compared to more moderate weight-gain trajectories in men and women. Initially high weight gain followed by weight loss was associated with lower risk of elevated hs-CRP in women aged 18 to 40. CONCLUSIONS: Latent class trajectory analysis identified heterogeneity in adult weight change associated with differential risk of inflammation independently of baseline weight and smoking. These results suggest that trajectories of weight gain are an important clinical concern and may identify those at risk for inflammation and the development of cardiometabolic disease

    Aqueous Processes and Microbial Habitability of Gale Crater Sediments from the Blunts Point to the Glenn Torridon Clay Unit

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    A driving factor for sending the Mars Science Laboratory, Curiosity rover to Gale Crater was the orbital detection of clay minerals in the Glen Torridon (GT) clay unit. Clay mineral detections in GT suggested a past aqueous environment that was habitable, and could contain organic evidence of past microbiology. The mission of the Sample Analysis at Mars (SAM) instrument onboard Curiosity was to detect organic evidence of past microbiology and to detect volatile bearing mineralogy that can inform on whether past geochemical conditions would have supported microbiological activity. The objective of this work was to 1) evaluate the depositional/alteration conditions of Blunts Point (BP) to GT sediments 2) search for evidence of organics, and 3) evaluate microbial habitability in the BP, Vera Rubin Ridge (VRR), and GT sedimentary rock

    Comparison of Marker-based Pairwise Relatedness Estimators on a Pedigreed Plant Population

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    Several estimators have been proposed that use molecular marker data to infer the degree of relatedness for pairs of individuals. The objective of this study was to evaluate the performance of seven estimators when applied to marker data of a set of 33 key individuals from a large complex apple pedigree. The evaluation considered different scenarios of allele frequencies and different numbers of marker loci. The method of moments estimators were Similarity, Queller-Goodknight, Lynch-Ritland and Wang. The maximum likelihood estimators were Thompson, Anderson-Weir and Jacquard. The pedigree-based coancestry coefficients were taken as the point of reference in calculating correlations and root mean square error (RMSE). The marker data comprised 86 multi-allelic SSR markers on 17 linkage groups, covering 11 Morgans. Additionally, we simulated 10 datasets conditional on the real pedigree to support the results on the real dataset. None of the estimators outperformed the others. Knowledge of allele frequencies appeared to be the most influential, i.e., the highest correlations and lowest RMSE were found when frequencies from the founder population were available. When equal allele frequencies were used, all estimators resulted in very similar, but on average lower, correlations. The use of allele frequencies estimated from the set of 33 individuals gave, on average, the poorest results. The maximum likelihood estimators and the Lynch-Ritland estimator were the most sensitive to allele frequencies. The results from the simulation study fully supported the trends in results of the real dataset. This study indicated that high correlations (up to 0.90) and small RMSE (below 0.03), may be obtained when population allelic frequencies are available. In this scenario, the performances of the various estimators were similar, but seemed to favor the maximum likelihood estimators. In the absence of reliable allele frequencies the method of moments estimators were shown to be more robust. The number of marker loci influenced the average performance of the estimators; however, the ranking was not affected. Correlations up to 0.80 were obtained when two markers per chromosome and appropriate allele frequencies were available. Adding more markers to the current dataset may lead to marginal improvements

    Care team and practice-level implementation strategies to optimize pediatric collaborative care: Study protocol for a cluster-randomized hybrid type III trial

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    BACKGROUND: Implementation facilitation is an effective strategy to support the implementation of evidence-based practices (EBPs), but our understanding of multilevel strategies and the mechanisms of change within the black box of implementation facilitation is limited. This implementation trial seeks to disentangle and evaluate the effects of facilitation strategies that separately target the care team and leadership levels on implementation of a collaborative care model in pediatric primary care. Strategies targeting the provider care team (TEAM) should engage team-level mechanisms, and strategies targeting leaders (LEAD) should engage organizational mechanisms. METHODS: We will conduct a hybrid type 3 effectiveness-implementation trial in a 2 × 2 factorial design to evaluate the main and interactive effects of TEAM and LEAD and test for mediation and moderation of effects. Twenty-four pediatric primary care practices will receive standard REP training to implement Doctor-Office Collaborative Care (DOCC) and then be randomized to (1) Standard REP only, (2) TEAM, (3) LEAD, or (4) TEAM + LEAD. Implementation outcomes are DOCC service delivery and change in practice-level care management competencies. Clinical outcomes are child symptom severity and quality of life. DISCUSSION: This statewide trial is one of the first to test the unique and synergistic effects of implementation strategies targeting care teams and practice leadership. It will advance our knowledge of effective care team and practice-level implementation strategies and mechanisms of change. Findings will support efforts to improve common child behavioral health conditions by optimizing scale-up and sustainment of CCMs in a pediatric patient-centered medical home. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04946253 . Registered June 30, 2021

    Eighteen year weight trajectories and metabolic markers of diabetes in modernising China: which timescale is most relevant? Reply to Vistisen D and Færch K [letter]

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    Aims/HypothesisAlthough obesity is a major risk factor for diabetes, little is known about weight gain trajectories across adulthood, and whether they are differentially associated with metabolic markers of diabetes.MethodsWe used fasting blood samples and longitudinal weight data for 5,436 adults (5,734 observations, aged 18–66years) from the China Health and Nutrition Survey (1991–2009). Using latent class trajectory analysis, we identified different weight gain trajectories in six age and sex strata, and used multivariable general linear mixed effects models to assess elevated metabolic markers of diabetes (fasting glucose, HbA1c, HOMA-IR, insulin) across weight trajectory classes. Models were fitted within age and sex strata, and controlled for baseline weight (or baseline weight by weight trajectory interaction terms), height, and smoking habit, with random intercepts to control for community-level correlations.ResultsCompared with weight gain, classes with weight maintenance, weight loss, or a switch from weight gain to loss had lower values for metabolic markers of diabetes. These associations were stronger among younger women (aged 18–29 and 30–39years) and men (18–29years) than in older (40–66years) men and women. An exception was HOMA-IR, which showed class differences across all ages (at least p < 0.004).ConclusionTrajectory analysis identified heterogeneity in adult weight gain associated with diabetes-related metabolic markers, independent of baseline weight. Our findings suggest that variation in metabolic markers of diabetes across patterns of weight gain is masked by a homogeneous classification of weight gain.Electronic supplementary materialThe online version of this article (doi:10.1007/s00125-014-3284-y) contains peer-reviewed but unedited supplementary material, which is available to authorised users

    Overview of CAPICE-Childhood and Adolescence Psychopathology:unravelling the complex etiology by a large Interdisciplinary Collaboration in Europe-an EU Marie Skłodowska-Curie International Training Network

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    Abstract The Roadmap for Mental Health and Wellbeing Research in Europe (ROAMER) identified child and adolescent mental illness as a priority area for research. CAPICE (Childhood and Adolescence Psychopathology: unravelling the complex etiology by a large Interdisciplinary Collaboration in Europe) is a European Union (EU) funded training network aimed at investigating the causes of individual differences in common childhood and adolescent psychopathology, especially depression, anxiety, and attention deficit hyperactivity disorder. CAPICE brings together eight birth and childhood cohorts as well as other cohorts from the EArly Genetics and Life course Epidemiology (EAGLE) consortium, including twin cohorts, with unique longitudinal data on environmental exposures and mental health problems, and genetic data on participants. Here we describe the objectives, summarize the methodological approaches and initial results, and present the dissemination strategy of the CAPICE network. Besides identifying genetic and epigenetic variants associated with these phenotypes, analyses have been performed to shed light on the role of genetic factors and the interplay with the environment in influencing the persistence of symptoms across the lifespan. Data harmonization and building an advanced data catalogue are also part of the work plan. Findings will be disseminated to non-academic parties, in close collaboration with the Global Alliance of Mental Illness Advocacy Networks-Europe (GAMIAN-Europe)

    Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

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    Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts
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