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Highland, AR, United States

Lyon College is an independent, residential, co-educational, undergraduate liberal arts college affiliated with the Presbyterian Church . Founded in 1872, it is the oldest independent college in Arkansas. Wikipedia.

Rajpurohit S.,University of Nevada, Las Vegas | Rajpurohit S.,University of Pennsylvania | Oliveira C.C.,University of Arkansas | Oliveira C.C.,Lyon College | And 2 more authors.
Molecular Ecology | Year: 2013

We used whole-transcriptome microarrays to assess changes in gene expression and monitored mortality rates and epicuticular hydrocarbons (CHCs) in response to desiccation stress in four natural populations of Drosophila mojavensis from Baja California and mainland Mexico. Desiccation had the greatest effect on gene expression, followed by biogeographical variation at regional and population levels. Genes involved in environmental sensing and cuticular structure were up-regulated in dry conditions, while genes involved in transcription itself were down-regulated. Flies from Baja California had higher expression of reproductive and mitochondrial genes, suggesting that these populations have greater fecundity and higher metabolic rates. Host plant differences had a surprisingly minor effect on the transcriptome. In most cases, desiccation-caused mortality was greater in flies reared on fermenting cactus tissues than that on laboratory media. Water content of adult females and males was significantly different and was lower in Baja California males. Different groups of CHCs simultaneously increased and decreased in amounts due to desiccation exposure of 9 and 18 h and were population-specific and dependent on larval rearing substrates. Overall, we observed that changes in gene expression involved a coordinated response of behavioural, cuticular and metabolic genes. Together with differential expression of cuticular hydrocarbons, this study revealed some of the mechanisms that have allowed D. mojavensis to exploit its harsh desert conditions. Certainly, for D. mojavensis that uses different host plants, population-level understanding of responses to stressors associated with future climate change in desert regions must be evaluated across geographical and local ecological scales. © 2013 Blackwell Publishing Ltd. Source

Etges W.J.,University of Arkansas | De Oliveira C.C.,University of Arkansas | De Oliveira C.C.,Lyon College
Ecology and Evolution | Year: 2014

Analysis of sexual selection and sexual isolation in Drosophila mojavensis and its relatives has revealed a pervasive role of rearing substrates on adult courtship behavior when flies were reared on fermenting cactus in preadult stages. Here, we assessed expression of contact pheromones comprised of epicuticular hydrocarbons (CHCs) from eclosion to 28 days of age in adults from two populations reared on fermenting tissues of two host cacti over the entire life cycle. Flies were never exposed to laboratory food and showed significant reductions in average CHC amounts consistent with CHCs of wild-caught flies. Overall, total hydrocarbon amounts increased from eclosion to 14-18 days, well past age at sexual maturity, and then declined in older flies. Most flies did not survive past 4 weeks. Baja California and mainland populations showed significantly different age-specific CHC profiles where Baja adults showed far less age-specific changes in CHC expression. Adults from populations reared on the host cactus typically used in nature expressed more CHCs than on the alternate host. MANCOVA with age as the covariate for the first six CHC principal components showed extensive differences in CHC composition due to age, population, cactus, sex, and age × population, age × sex, and age × cactus interactions. Thus, understanding variation in CHC composition as adult D. mojavensis age requires information about population and host plant differences, with potential influences on patterns of mate choice, sexual selection, and sexual isolation, and ultimately how these pheromones are expressed in natural populations. Studies of drosophilid aging in the wild are badly needed. © 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. Source

Cleophas T.J.,Lyon College
American Journal of Therapeutics | Year: 2015

Robust tests are tests that can handle the inclusion into a data file of some outliers without largely changing the overall test results. Despite the risk of non-Gaussian data in clinical trials, robust tests are virtually never performed. The objective of this study was to review important robust tests and to assess whether they provide better sensitivity of testing than standard tests do. In a 33 patient study of frailty scores, no significant t value was obtained (P = 0.067). The following 4 robust tests were performed: (1) z test for medians and median absolute deviations, (2) z test for Winsorized variances, (3) Mood test, and (4) z test for M-estimators with bootstrap standard errors. They produced P values of, respectively, <0.0001, 0.043, <0.0001, and 0.005. Robust tests are wonderful for imperfect clinical data because they often produce statistically significant results, whereas standard tests do not. © 2013 Wolters Kluwer Health, Inc. Source

Cleophas T.J.,Lyon College
American Journal of Therapeutics | Year: 2016

Traditionally, nonlinear relationships like the smooth shapes of airplanes, boats, and motor cars were constructed from scale models using stretched thin wooden strips, otherwise called splines. In the past decades, mechanical spline methods have been replaced with their mathematical counterparts. The objective of the study was to study whether spline modeling can adequately assess the relationships between exposure and outcome variables in a clinical trial and also to study whether it can detect patterns in a trial that are relevant but go unobserved with simpler regression models. A clinical trial assessing the effect of quantity of care on quality of care was used as an example. Spline curves consistent of 4 or 5 cubic functions were applied. SPSS statistical software was used for analysis. The spline curves of our data outperformed the traditional curves because (1) unlike the traditional curves, they did not miss the top quality of care given in either subgroup, (2) unlike the traditional curves, they, rightly, did not produce sinusoidal patterns, and (3) unlike the traditional curves, they provided a virtually 100% match of the original values. We conclude that (1) spline modeling can adequately assess the relationships between exposure and outcome variables in a clinical trial; (2) spline modeling can detect patterns in a trial that are relevant but may go unobserved with simpler regression models; (3) in clinical research, spline modeling has great potential given the presence of many nonlinear effects in this field of research and given its sophisticated mathematical refinement to fit any nonlinear effect in the mostly accurate way; and (4) spline modeling should enable to improve making predictions from clinical research for the benefit of health decisions and health care. We hope that this brief introduction to spline modeling will stimulate clinical investigators to start using this wonderful method. © 2013 Wolters Kluwer Health, Inc. Source

Cleophas T.J.,Lyon College
American Journal of Therapeutics | Year: 2016

With large data files, outlier recognition requires a more sophisticated approach than the traditional data plots and regression lines. In addition, the number of outliers tends to rise linearly with the data's sample size. The objective of this study was to examine whether balanced iterative reducing and clustering using hierarchies (BIRCH) clustering is able to detect previously unrecognized outlier data.A simulated and a real data files were used as examples. SPSS statistical software was used for data analysis. In 50 mentally depressed persons, a regression analysis failed to detect any outliers. BIRCH analysis of these data showed in addition to 2 clusters a relevant outlier cluster consistent of 7 patients (14%) not fitting in the formed clusters. In 576 iatrogenic admissions, the number of comedications was not a significant loglinear predictor of the iatrogenic admission. In contrast, BIRCH analysis revealed an outlier cluster consistent of 174 patients (30%) with extremely many comedications. The conclusions were as follows: (1) A systematic assessment for outliers is important in therapeutic research with large data, because the lack of it can lead to catastrophic consequences. (2) Traditional data analysis, such as regression analysis, was unable to demonstrate outliers in our examples. (3) BIRCH cluster analysis of the examples produced relevant outlier clusters of patients not fitting in the data otherwise. (4) On theoretical grounds, BIRCH cluster analysis is, particularly, suitable for large datasets. © 2013 Wolters Kluwer Health, Inc. Source

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