The effects of patient characteristics on ADHD diagnosis and treatment: a factorial study of family physicians

<p>Abstract</p> <p>Background</p> <p>Attention Deficit Hyperactivity Disorder (ADHD) is a costly and prevalent disorder in the U.S., especially among youth. However, significant disparities in diagnosis and treatment appear to be predicted by the race and insurance status of patients.</p> <p>Methods</p> <p>This study employed a web-based factorial survey with four ADHD cases derived from an ADHD clinic, two diagnosed with ADHD in actual evaluation, and two not. Randomized measures included race and insurance status of the patients. Participants N = (187) included clinician members of regional and national practice-based research networks and the U.S. clinical membership of the Society of Teachers of Family Medicine. The main outcomes were decisions to 1) diagnose and 2) treat the cases, based upon the information presented, analyzed via binary logistic regression of the randomized factors and case indicators on diagnosis and treatment.</p> <p>Results</p> <p>ADHD-positive cases were 8 times more likely to be diagnosed and 12 times more likely to be treated, and the male ADHD positive case was more likely to be diagnosed and treated than the female ADHD positive case. Uninsured cases were significantly more likely to be treated overall, but male cases that were uninsured were about half as likely to be diagnosed and treated with ADHD. Additionally, African-American race appears to increase the likelihood of medicinal treatment for ADHD and being both African-American and uninsured appears to cut the odds of medicinal treatment in half, but not significantly.</p> <p>Conclusions</p> <p>Family physicians were competent at discerning between near-threshold ADHD-negative and ADHD positive cases. However, insurance status and race, as well as gender, appear to affect the likelihood of diagnosis and treatment for ADHD in Family Medicine settings.</p

Comparative study of unsupervised dimension reduction techniques for the visualization of microarray gene expression data

<p>Abstract</p> <p>Background</p> <p>Visualization of DNA microarray data in two or three dimensional spaces is an important exploratory analysis step in order to detect quality issues or to generate new hypotheses. Principal Component Analysis (PCA) is a widely used linear method to define the mapping between the high-dimensional data and its low-dimensional representation. During the last decade, many new nonlinear methods for dimension reduction have been proposed, but it is still unclear how well these methods capture the underlying structure of microarray gene expression data. In this study, we assessed the performance of the PCA approach and of six nonlinear dimension reduction methods, namely Kernel PCA, Locally Linear Embedding, Isomap, Diffusion Maps, Laplacian Eigenmaps and Maximum Variance Unfolding, in terms of visualization of microarray data.</p> <p>Results</p> <p>A systematic benchmark, consisting of Support Vector Machine classification, cluster validation and noise evaluations was applied to ten microarray and several simulated datasets. Significant differences between PCA and most of the nonlinear methods were observed in two and three dimensional target spaces. With an increasing number of dimensions and an increasing number of differentially expressed genes, all methods showed similar performance. PCA and Diffusion Maps responded less sensitive to noise than the other nonlinear methods.</p> <p>Conclusions</p> <p>Locally Linear Embedding and Isomap showed a superior performance on all datasets. In very low-dimensional representations and with few differentially expressed genes, these two methods preserve more of the underlying structure of the data than PCA, and thus are favorable alternatives for the visualization of microarray data.</p

Nothing a Hot Bath Won't Cure: Infection Rates of Amphibian Chytrid Fungus Correlate Negatively with Water Temperature under Natural Field Settings

Dramatic declines and extinctions of amphibian populations throughout the world have been associated with chytridiomycosis, an infectious disease caused by the pathogenic chytrid fungus Batrachochytrium dendrobatidis (Bd). Previous studies indicated that Bd prevalence correlates with cooler temperatures in the field, and laboratory experiments have demonstrated that Bd ceases growth at temperatures above 28°C. Here we investigate how small-scale variations in water temperature correlate with Bd prevalence in the wild. We sampled 221 amphibians, including 201 lowland leopard frogs (Rana [Lithobates] yavapaiensis), from 12 sites in Arizona, USA, and tested them for Bd. Amphibians were encountered in microhabitats that exhibited a wide range of water temperatures (10–50°C), including several geothermal water sources. There was a strong inverse correlation between the water temperature in which lowland leopard frogs were captured and Bd prevalence, even after taking into account the influence of year, season, and host size. In locations where Bd was known to be present, the prevalence of Bd infections dropped from 75–100% in water <15°C, to less than 10% in water >30°C. A strong inverse correlation between Bd infection status and water temperature was also observed within sites. Our findings suggest that microhabitats where water temperatures exceed 30°C provide lowland leopard frogs with significant protection from Bd, which could have important implications for disease dynamics, as well as management applications

Pathogenic variants in glutamyl-tRNAGln amidotransferase subunits cause a lethal mitochondrial cardiomyopathy disorder.

Mitochondrial protein synthesis requires charging mt-tRNAs with their cognate amino acids by mitochondrial aminoacyl-tRNA synthetases, with the exception of glutaminyl mt-tRNA (mt-tRNAGln). mt-tRNAGln is indirectly charged by a transamidation reaction involving the GatCAB aminoacyl-tRNA amidotransferase complex. Defects involving the mitochondrial protein synthesis machinery cause a broad spectrum of disorders, with often fatal outcome. Here, we describe nine patients from five families with genetic defects in a GatCAB complex subunit, including QRSL1, GATB, and GATC, each showing a lethal metabolic cardiomyopathy syndrome. Functional studies reveal combined respiratory chain enzyme deficiencies and mitochondrial dysfunction. Aminoacylation of mt-tRNAGln and mitochondrial protein translation are deficient in patients' fibroblasts cultured in the absence of glutamine but restore in high glutamine. Lentiviral rescue experiments and modeling in S. cerevisiae homologs confirm pathogenicity. Our study completes a decade of investigations on mitochondrial aminoacylation disorders, starting with DARS2 and ending with the GatCAB complex