The Analysis of Association Between Traits When Differences Between Trait States Matter

Because of their elementary significance in almost all fields of science, measures of association between two variables or traits are abundant and multiform. One aspect of association that is of considerable interest, especially in population genetics and ecology, seems to be widely ignored. This aspect concerns association between complex traits that show variable and arbitrarily defined state differences. Among such traits are genetic characters controlled by many and potentially polyploid loci, species characteristics, and environmental variables, all of which may be mutually and asymmetrically associated. A concept of directed association of one trait with another is developed here that relies solely on difference measures between the states of a trait. Associations are considered at three levels: between individual states of two variables, between an individual state of one variable and the totality of the other variable, and between two variables. Relations to known concepts of association are identified. In particular, measures at the latter two levels turn out to be interpretable as measures of differentiation. Examples are given for areas of application (search for functional relationships, distribution of variation over populations, genomic associations, spatiogenetic structure)

The Chemistry Mechanism in the Community Earth System Model Version 2 (CESM2)

The Community Earth System Model version 2 (CESM2) includes a detailed representation of chemistry throughout the atmosphere in the Community Atmosphere Model with chemistry and Whole Atmosphere Community Climate Model configurations. These model configurations use the Model for Ozone and Related chemical Tracers (MOZART) family of chemical mechanisms, covering the troposphere, stratosphere, mesosphere, and lower thermosphere. The new MOZART tropospheric chemistry scheme (T1) has a number of updates over the previous version (MOZART‐4) in CESM, including improvements to the oxidation of isoprene and terpenes, organic nitrate speciation, and aromatic speciation and oxidation and thus improved representation of ozone and secondary organic aerosol precursors. An evaluation of the present‐day simulations of CESM2 being provided for Climate Model Intercomparison Project round 6 (CMIP6) is presented. These simulations, using the anthropogenic and biomass burning emissions from the inventories specified for CMIP6, as well as online calculation of emissions of biogenic compounds, lightning NO, dust, and sea salt, indicate an underestimate of anthropogenic emissions of a variety of compounds, including carbon monoxide and hydrocarbons. The simulation of surface ozone in the southeast United States is improved over previous model versions, largely due to the improved representation of reactive nitrogen and organic nitrate compounds resulting in a lower ozone production rate than in CESM1 but still overestimates observations in summer. The simulation of tropospheric ozone agrees well with ozonesonde observations in many parts of the globe. The comparison of NOx and PAN to aircraft observations indicates the model simulates the nitrogen budget well

Simpson's Paradox, Lord's Paradox, and Suppression Effects are the same phenomenon – the reversal paradox

This article discusses three statistical paradoxes that pervade epidemiological research: Simpson's paradox, Lord's paradox, and suppression. These paradoxes have important implications for the interpretation of evidence from observational studies. This article uses hypothetical scenarios to illustrate how the three paradoxes are different manifestations of one phenomenon – the reversal paradox – depending on whether the outcome and explanatory variables are categorical, continuous or a combination of both; this renders the issues and remedies for any one to be similar for all three. Although the three statistical paradoxes occur in different types of variables, they share the same characteristic: the association between two variables can be reversed, diminished, or enhanced when another variable is statistically controlled for. Understanding the concepts and theory behind these paradoxes provides insights into some controversial or contradictory research findings. These paradoxes show that prior knowledge and underlying causal theory play an important role in the statistical modelling of epidemiological data, where incorrect use of statistical models might produce consistent, replicable, yet erroneous results

Selecting information technology for physicians' practices: a cross-sectional study

BACKGROUND: Many physicians are transitioning from paper to electronic formats for billing, scheduling, medical charts, communications, etc. The primary objective of this research was to identify the relationship (if any) between the software selection process and the office staff's perceptions of the software's impact on practice activities. METHODS: A telephone survey was conducted with office representatives of 407 physician practices in Oregon who had purchased information technology. The respondents, usually office managers, answered scripted questions about their selection process and their perceptions of the software after implementation. RESULTS: Multiple logistic regression revealed that software type, selection steps, and certain factors influencing the purchase were related to whether the respondents felt the software improved the scheduling and financial analysis practice activities. Specifically, practices that selected electronic medical record or practice management software, that made software comparisons, or that considered prior user testimony as important were more likely to have perceived improvements in the scheduling process than were other practices. Practices that considered value important, that did not consider compatibility important, that selected managed care software, that spent less than $10,000, or that provided learning time (most dramatic increase in odds ratio, 8.2) during implementation were more likely to perceive that the software had improved the financial analysis process than were other practices. CONCLUSION: Perhaps one of the most important predictors of improvement was providing learning time during implementation, particularly when the software involves several practice activities. Despite this importance, less than half of the practices reported performing this step

Same old song and dance: An exploratory study of portrayal of physical activity in television programmes aimed at young adolescents

Abstract Objective Exposure to health-related behaviours on television has been shown to influence smoking and drinking in young people, but little research has been conducted on the portrayal physical activity. The aim of the current project was to explore the portrayal of physical activity in television programmes aimed specifically at adolescent females. Content analysis of 120 episodes of four popular adolescent television programmes was performed. Information on the type and context of physical activity, motivating factors and characters involved was recorded. Results Physical activity was portrayed 122 times, for a duration of 1 h and 31 min (3.2% of total viewing time). Physical activity was mainly portrayed as part of an informal activity as part of a group activity. Over half (53.2%) of scenes portrayed activity been carried out by teenagers. The types of activities portrayed were mostly of vigorous intensity (76.2%), for recreational purposes (78.7%) such as dancing (54.1%) and running (11.5%), and motivated by enjoyment. This study highlights that physical activity is portrayed infrequently, and often with a skewed representation of type of activity. There may be an opportunity to influence physical activity in young adolescents through the positioning of positive images of an active lifestyle in the media

Immunoblot analysis of the seroreactivity to recombinant Borrelia burgdorferi sensu lato antigens, including VlsE, in the long-term course of treated patients with Erythema migrans

Objective: We evaluated whether immunoblotting is capable of substantiating the posttreatment clinical assessment of patients with erythema migrans ( EM), the hallmark of early Lyme borreliosis. Methods: In 50 patients, seroreactivity to different antigens of Borrelia burgdorferi sensu lato was analyzed by a recombinant immunoblot test (IB) in consecutive serum samples from a minimum follow-up period of 1 year. Antigens in the IgG test were decorin- binding protein A, internal fragment of p41 (p41i), outer surface protein C (OspC), p39, variable major protein-like sequence expressed (VlsE), p58 and p100; those in the IgM test were p41i, OspC and p39. Immune responses were correlated with clinical and treatment-related parameters. Results: Positive IB results were found in 50% before, in 57% directly after therapy and in 44% by the end of the follow-up for the IgG class, and in 36, 43 and 12% for the IgM class. In acute and convalescence phase sera, VlsE was most immunogenic on IgG testing 60 and 70%), and p41i (46 and 57%) and OspC (40 and 57%) for the IgM class. By the end of the follow-up, only the anti-p41i lgM response was significantly decreased to 24%. Conclusions: No correlation was found between IB results and treatment-related parameters. Thus, immunoblotting does not add to the clinical assessment of EM patients after treatment. Copyright (c) 2008 S. Karger AG, Basel

Statistical Inference for Valued-Edge Networks: Generalized Exponential Random Graph Models

Across the sciences, the statistical analysis of networks is central to the production of knowledge on relational phenomena. Because of their ability to model the structural generation of networks, exponential random graph models are a ubiquitous means of analysis. However, they are limited by an inability to model networks with valued edges. We solve this problem by introducing a class of generalized exponential random graph models capable of modeling networks whose edges are valued, thus greatly expanding the scope of networks applied researchers can subject to statistical analysis

Fuzzy min-max neural networks for categorical data: application to missing data imputation

The fuzzy min–max neural network classifier is a supervised learning method. This classifier takes the hybrid neural networks and fuzzy systems approach. All input variables in the network are required to correspond to continuously valued variables, and this can be a significant constraint in many real-world situations where there are not only quantitative but also categorical data. The usual way of dealing with this type of variables is to replace the categorical by numerical values and treat them as if they were continuously valued. But this method, implicitly defines a possibly unsuitable metric for the categories. A number of different procedures have been proposed to tackle the problem. In this article, we present a new method. The procedure extends the fuzzy min–max neural network input to categorical variables by introducing new fuzzy sets, a new operation, and a new architecture. This provides for greater flexibility and wider application. The proposed method is then applied to missing data imputation in voting intention polls. The micro data—the set of the respondents’ individual answers to the questions—of this type of poll are especially suited for evaluating the method since they include a large number of numerical and categorical attributes

Cardiosphere-derived cells suppress allogeneic lymphocytes by production of PGE2 acting via the EP4 receptor

derived cells (CDCs) are a cardiac progenitor cell population, which have been shown to possess cardiac regenerative properties and can improve heart function in a variety of cardiac diseases. Studies in large animal models have predominantly focussed on using autologous cells for safety, however allogeneic cell banks would allow for a practical, cost-effective and efficient use in a clinical setting. The aim of this work was to determine the immunomodulatory status of these cells using CDCs and lymphocytes from 5 dogs. CDCs expressed MHC I but not MHC II molecules and in mixed lymphocyte reactions demonstrated a lack of lymphocyte proliferation in response to MHC-mismatched CDCs. Furthermore, MHC-mismatched CDCs suppressed lymphocyte proliferation and activation in response to Concanavalin A. Transwell experiments demonstrated that this was predominantly due to direct cell-cell contact in addition to soluble mediators whereby CDCs produced high levels of PGE2 under inflammatory conditions. This led to down-regulation of CD25 expression on lymphocytes via the EP4 receptor. Blocking prostaglandin synthesis restored both, proliferation and activation (measured via CD25 expression) of stimulated lymphocytes. We demonstrated for the first time in a large animal model that CDCs inhibit proliferation in allo-reactive lymphocytes and have potent immunosuppressive activity mediated via PGE2

An Evaluation of the Large‐Scale Atmospheric Circulation and Its Variability in CESM2 and Other CMIP Models

The Community Earth System Model 2 (CESM2) is the latest Earth System Model developed by the National Center for Atmospheric Research in collaboration with the university community and is significantly advanced in most components compared to its predecessor (CESM1). Here, CESM2's representation of the large‐scale atmospheric circulation and its variability is assessed. Further context is providedthrough comparison to the CESM1 large ensemble and other models from the Coupled Model Intercomparison Project (CMIP5 and CMIP6). This includes an assessment of the representation of jet streams and storm tracks, stationary waves, the global divergent circulation, the annular modes, the North Atlantic Oscillation, and blocking. Compared to CESM1, CESM2 is substantially improved in the representation of the storm tracks, Northern Hemisphere (NH) stationary waves, NH winter blocking and the global divergent circulation. It ranks within the top 10% of CMIP class models in many of these features. Some features of the Southern Hemisphere (SH) circulation have degraded, such as the SH jet strength, stationary waves, and blocking, although the SH jet stream is placed at approximately the correct location. This analysis also highlights systematic deficiencies in these features across the new CMIP6 archive, such as the continued tendency for the SH jet stream to be placed too far equatorward, the North Atlantic westerlies to be too strong over Europe, the storm tracks as measured by low‐level meridional wind variance to be too weak and a lack of blocking in the North Atlantic sector