Energy Expenditure Overestimation Bias in Elliptical Trainer Machine

Elliptical trainers are a common mode of aerobic exercise in recreationally active populations. Those with a weight loss goal might rely upon the energy expenditure (EE) estimation that many elliptical brands provide to keep track of calories (kcals) burned and make nutritional decisions. For this reason, it is important to evaluate the accuracy of the algorithms used by elliptical trainers to estimate EE. The purpose of this study was to compare EE estimates by a common brand of elliptical trainer to that measured using open circuit spirometry, at different combinations of resistance and pedal speed. Twenty subjects (10 male, 10 female; 34 ± 12 yr; 175.3 ± 10.7 cm; 77.1 ± 14.1 kg) consented to participate. Each completed three 15-min bouts of elliptical exercise on the same elliptical trainer, with at least 24 hr between exercise bouts. Pedal rates were held constant throughout each bout at 50, 60, or 70 RPM, and resistance was increased incrementally every 5 min from level 5 to 10 to 15. The different cadences were completed in a randomized order between participants. Expired gases were collected continuously throughout the 15 min. Heart rate, distance (mi), and EE from the elliptical readout were recorded every 1 min. RPE was collected twice per resistance level. A two-tailed paired samples t-test was used to compare elliptical EE to measured EE. A linear regression model was used to evaluate the ability of the elliptical EE to predict measured EE. Significance for all statistical measures was held at an alpha level of 0.05. The difference between EE estimates from the elliptical and measured VO2 was significant (p Measured EE = 0.95*(Elliptical EE) – 3.161 In conclusion, the elliptical trainer used for this study demonstrated a bias to overestimate EE. This should be taken into account by health/fitness professionals using these estimations to program for clients. There may be some variation in the EE correction regression depending on elliptical model, and proper machine calibration should be ensured

“MULTIRACIAL AND MULTIETHNIC IDENTITY DEVELOPMENT: SHOULD THE QUESTION REALLY BE ‘IS THE GLASS HALF FULL OR HALF EMPTY?’”

The purpose of this symposium is to challenge and expand the work in identity development beyond simplistic, single identity developmental frameworks by examining the inherent complexities of multiple identity development and group affiliations

A communal catalogue reveals Earth's multiscale microbial diversity

Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth's microbial diversity.Peer reviewe

A communal catalogue reveals Earth’s multiscale microbial diversity

Our growing awareness of the microbial world’s importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth’s microbial diversity

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

EU/US/CTAD Task Force: Lessons Learned from Recent and Current Alzheimer's Prevention Trials

At a meeting of the EU/US/Clinical Trials in Alzheimer’s Disease (CTAD) Task Force in December 2016, an international group of investigators from industry, academia, and regulatory agencies reviewed lessons learned from ongoing and planned prevention trials, which will help guide future clinical trials of AD treatments, particularly in the pre-clinical space. The Task Force discussed challenges that need to be addressed across all aspects of clinical trials, calling for innovation in recruitment and retention, infrastructure development, and the selection of outcome measures. While cognitive change provides a marker of disease progression across the disease continuum, there remains a need to identify the optimal assessment tools that provide clinically meaningful endpoints. Patient- and informant-reported assessments of cognition and function may be useful but present additional challenges. Imaging and other biomarkers are also essential to maximize the efficiency of and the information learned from clinical trials

Development of the attributions for scholastic outcomes scale--Latino (ASO-L)

textThis study supports the development of the Attributions for Scholastic Outcomes Scale--Latino (ASO-L). Previous research has shown that people believe that it is important to close the achievement gaps that exist between racial/ethnic minorities and Whites (Rose & Gallup, 2004). Despite the fact that the general public has taken an interest in this area, there are currently no instruments for measuring how people reason about these issues. Consequently, there is little knowledge as to why people continue to support policies that have been unsuccessful in bringing racial/ethnic minority academic performance up to the level of Whites. This study takes steps in that direction by providing educators and school reform advocates with a useful instrument for understanding how people reason about the causes for the Latino-White achievement gap. The ASO-L measures the extent to which people believe in two different explanations for the Latino-White achievement gap. I have termed the explanation that I believe is most pervasive in US society "culture-blaming." It is consistent with the dominant racial story about Latino underachievement, which focuses primarily on the presumed limitations of Latino families and Latino culture. I refer to what I believe to be the second most common explanation as "structure-blaming." It challenges the dominant racial story because it places blame on schools and the schooling system rather than the limitations of Latinos. Confirmatory factor analyses provide evidence for the factorial validity of the ASO-L. In addition, structural equation modeling performed on sample data indicates that the two primary explanations--culture-blaming and structure-blaming--are meaningfully related to attitudes towards resource redistribution, English-only initiatives, parent education, and standardized testing above and beyond what can be accounted for by measures of attributional complexity (G. Fletcher, Danilovics, Fernandez, Peterson, & Reeder, 1986) and political orientation (Kerlinger, 1984). Finally, a comparison of latent means revealed that Latinos are more likely than Whites to endorse structure-blaming attributions, but no less likely to endorse culture-blaming attributions. Recommendations for further research and academic activism are included.Educational Psycholog