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Background A comprehensive study of the effect of supramaximal exercise in lipid homeostasis of Thoroughbreds provides the basis for future research on the role of lipids on energy metabolism in racehorses. Objective To compare the plasma lipidome of Thoroughbreds before and after supramaximal exercise using an untargeted lipidomics approach. Study design Pilot experimental study. Methods Four Thoroughbred horses were used. The maximal oxygen consumption (VO2 max ) was calculated for each horse. Horses then underwent treadmill exercise at the speed for which the oxygen requirements had been calculated to be 115% VO2 max . Plasma samples were obtained before (T0) and immediately (T1), 15 (T2) and 30 (T3) minutes post-exercise, and evaluated using liquid chromatography/mass spectrometry. Data analysis consisted of principal component analysis and one-way repeated measures analysis of variance. Results A total of 933 plasma lipids were detected. Supramaximal exercise-induced significant changes in the signal intensity of 13 lipids; all ubiquitous in the organism as major components of biological membranes or energy substrates. Main limitations A treadmill was used to replicate track conditions. Also, sample size involved only four horses and the statistical analyses failed to achieve the desired power of 80%. Conclusions The findings in this pilot study suggest that supramaximal exercise induces changes in specific plasma lipids in Thoroughbred racehorses. While the biological significance of these findings remains to be determined, these results provide baseline information for future studies in lipidomics applied to equine exercise physiology. Further research is warranted to better understand the role of lipids on energy metabolism in Thoroughbred racehorses.

We evaluate the estimation performance of the Binary Dynamic Logit model for correlated ordinal variables (BDLCO model), and compare it to GEE and Ordinal Logistic Regression performance in terms of bias and Mean Absolute Percentage Error (MAPE) via Monte Carlo simulation. Our results indicate that when the proportional-odds assumption does not hold, the proposed BDLCO method is superior to existing models in estimating correlated ordinal data. Moreover, this method is flexible in terms of modeling dependence and allows unequal slopes for each category, and can be used to estimate an apple bloom data set where the proportional-odds assumption is violated. We also provide a function in R to implement BDLCO.

BACKGROUND Many foals that develop thoracic ultrasonographic lesions as a result of Rhodococcus equi infection heal on their own. However, most of these foals receive antimicrobials because foals at risk of developing clinical pneumonia cannot be identified. Untargeted lipidomics is useful to identify candidate biomarkers. OBJECTIVES (a) To describe the changes that occur in foal lipidomics as a result of ageing (birth to 8 weeks) and (b) To compare these results with those observed in foals after experimental infection with R. equi. STUDY DESIGN Experimental study. METHODS Healthy newborn foals (n = 9) were challenged with R. equi intratracheally the first week of life. Foals were treated with antimicrobials if they developed clinical pneumonia (n = 4, "clinical group") or were closely monitored if they showed no signs of disease (n = 5 "subclinical group"). An unchallenged group (n = 4) was also included. All foals were free of disease (transtracheal wash fluid evaluation and culture as well as thoracic ultrasonography) by 8 weeks of life. Plasma lipidomics was determined by LC-MS weekly for the study duration (8 weeks). RESULTS Both ageing and experimental infection altered the foal's plasma lipidome as demonstrated by multivariate statistical analysis. The intensities of 31 lipids were altered by ageing and 12 by infection (P

This study was designed to determine the efficacy of canker excision (CE) followed by a subsequent application of cauterization (CAU) and/or fungicide treatment to the excised area for the management of anthracnose canker (caused by Neofabraea malicorticis) on cider apple (Malus ×domestica) trees. Three experiments were conducted from 2015 to 2017, with one experiment each year, in an experimental cider apple orchard in western Washington where trees were naturally infested with N. malicorticis. Treatments were applied once in December and data were collected January through March. Treatments in the 2015 experiment were CE + CAU, CE + CAU + copper hydroxide, CE + 0.5% sodium hypochlorite, Bordeaux mixture (BM) only, and CE + copper hydroxide (control). The 2016 experiment included the same treatments as in 2015 plus one additional treatment, CE + BM. In 2017, one additional treatment was added, CE only, and CAU treatments were removed as they caused significant injury to the trees. Canker size was measured pretreatment, and the treated canker or excised area was measured posttreatment every 2 weeks for 13–15 weeks. Compared with pretreatment, cankers treated with BM did not increase in size, while the excised area treated with CAU increased 28-fold in size on average, and the excised area treated with 0.5% sodium hypochlorite or copper hydroxide increased up to 4-fold in size. Each year new cankers developed in all treatments 13–15 weeks after treatment application, at a time of year when there should not be any spores present to cause new infections. Dark brown streaking, indicative of the disease, was observed in the tissue below the intact or excised cankers 15 months after treatment application all years. Although N. malicorticis was not isolated from symptomatic tissue, symptoms were observed in all treatments including where cankers had not been excised and there was no wounding of the cambium tissue. Findings from this study indicate that of the treatments evaluated, the application of copper hydroxide after CE was the most effective for limiting the number of new cankers, but it did not limit expansion of the excised area. Additional physical and fungicidal strategies need to be tested for effective management of anthracnose canker.

// Matthew M. Yeh 1 , Sarag Boukhar 1 , Benjamin Roberts 2 , Nairanjana Dasgupta 3 and Sayed S. Daoud 4 1 Department of Pathology, University of Washington School of Medicine, Seattle, WA 98195, USA 2 The Liver Center, University of Kansas Medical Center, Kansas City, KS 66160, USA 3 Department of Mathematics and Statistics, Washington State University, Pullman, WA 99164, USA 4 Department of Pharmaceutical Sciences, Washington State University Health Sciences, Spokane, WA 99210, USA Correspondence to: Sayed S. Daoud, email: daoud@wsu.edu Keywords: hepatitis C, racial disparity, genomic variants, hepatocellular carcinoma, alternative splicing Received: November 30, 2016 Accepted: July 03, 2017 Published: August 01, 2017 ABSTRACT Chronic liver diseases are one of the major public health issues in United States, and there are substantial racial disparities in liver cancer-related mortality. We previously identified racially distinct alterations in the expression of transcripts and proteins of hepatitis C (HCV)-induced hepatocellular carcinoma (HCC) between Caucasian (CA) and African American (AA) subgroups. Here, we performed a comparative genome-wide analysis of normal vs . HCV+ (cirrhotic state), and normal adjacent tissues (HCCN) vs . HCV+HCC (tumor state) of CA at the gene and alternative splicing levels using Affymetrix Human Transcriptome Array (HTA2.0). Many genes and splice variants were abnormally expressed in HCV+ more than in HCV+HCC state compared with normal tissues. Known biological pathways related to cell cycle regulations were altered in HCV+HCC, whereas acute phase reactants were deregulated in HCV+ state. We confirmed by quantitative RT-PCR that SAA1 , PCNA-AS1 , DAB2 , and IFI30 are differentially deregulated, especially in AA compared with CA samples. Likewise, IHC staining analysis revealed altered expression patterns of SAA1 and HNF4α isoforms in HCV+ liver samples of AA compared with CA. These results demonstrate that several splice variants are primarily deregulated in normal vs . HCV+ stage, which is certainly in line with the recent observations showing that the pre-mRNA splicing machinery may be profoundly remodeled during disease progression, and may, therefore, play a major role in HCV racial disparity. The confirmation that certain genes are deregulated in AA compared to CA tissues also suggests that there is a biological basis for the observed racial disparities.

Fruit growth of an individual apples starts after petal and is affected by different environmental factors and orchard and tree management. Prediction of fruit size is critical for management and to prepare for postharvest processing and the logistics. The objective of this study was to develop a model to predict growth of an individual apple fruit as a function of the physiological time using cumulative degree days (GDD). The cultivars 'Cripps Pink', 'Gala', and 'Red Delicious' were monitored twice weekly during four growing seasons for eleven different locations in the main apple growing regions of eastern Washington. Thirty fruits were selected and the equatorial diameter was monitored and registered weekly. Daily temperature data came from the closest automated weather station of AgWeatherNet to the orchard where the samples were collected. The model was based on the accumulation of GDD starting after the stage of full bloom. To determine GDD, the base temperature, i.e. 7.22°C, was subtracted from the average temperature for 'Cripps Pink', 5.55°C for 'Gala' and 6.11°C for 'Red Delicious' respectively. The Bon Verthalanfy statistical model was used to determine the base temperature and other model parameters and to derive growth rate of the apple using the equation δD/δt, where D is the adjusted function and t is time in days. To determine the diameter of an apple on a daily basis, the Euler integration method was used. The observed data showed differences in fruit size among years and locations. The cultivar 'Gala' was harvested earlier than the cultivars 'Cripps Pink' and 'Red Delicious' resulting in differences in base temperatures. The relative error between predicted and observed fruit diameter was in general less than 3%, but varied due to the location and year. The model will be implemented as a prototype on the AgWeatherNet portal (www.weather.wsu.edu) to help predict fruit size as a function of local temperature for locations where an automated weather station is available.

Detailed information about apple phenology allows a grower to manage the orchard efficiently and to decide how many fruits per tree harvest. In general, eight stages have been identified for apple development starting with green tip until petal fall. Mathematical models can be developed to predict crop phenological stages. The objective of this study was to model apple phenology as a function of the physiological time using cumulative degree days (GDD). The cultivars 'Cripps Pink', 'Gala', and 'Red Delicious' were monitored twice weekly during four growing seasons for eleven different locations in the main apple growing regions of eastern Washington. Thirty buds were selected and the number of buds at a particular stage was registered. Daily temperature data came from the closest automated weather station of AgWeatherNet to the orchard where the samples were collected. The field observations showed that the stages were not mutually exclusive with at least two stages overlapping during apple development. The approach for the model was based on the duration or accumulation of GDDs for each individual stage from the first to the last observation of each stage. To determine GDD, the base temperature, i.e. 6.11°C was subtracted from the average temperature. For each stage, the lower and upper limits for the duration were calculated as the average of the minimum and the maximum GDDs for each stage. A comparison of the stage distribution among seasons, cultivars, locations and their interactions was conducted using GLIMMIX SAS procedure. There was significant effect of the factors and their interactions, indicating the complexity of apple development. The duration of each phenological stage was similar for all of the cultivars however cultivar 'Gala' started later than the other two cultivars for each stage. The model performance was good. A prototype of the model will be implemented on the AgWeatherNet portal (www.weather.wsu.edu).

Material properties of implants such as volume porosity and nanoscale surface modification have been shown to enhance cell-material interactions in vitro and osseointegration in vivo. Porous tantalum (Ta) and titanium (Ti) coatings are widely used for non-cemented implants, which are fabricated using different processing routes. In recent years, some of those implants are being manufactured using additive manufacturing. However, limited knowledge is available on direct comparison of additively manufactured porous Ta and Ti structures towards early stage osseointegration. In this study, we have fabricated porous Ta and Ti6Al4V (Ti64) implants using laser engineered net shaping (LENS™) with similar volume fraction porosity to compare the influence of surface characteristics and material chemistry on in vivo response using a rat distal femur model for 5 and 12 weeks. We have also assessed whether surface modification on Ti64 can elicit similar in vivo response as porous Ta in a rat distal femur model for 5 and 12 weeks. The harvested implants were histologically analyzed for osteoid surface per bone surface. Field emission scanning electron microscopy (FESEM) was done to assess the bone-implant interface. The results presented here indicate comparable performance of porous Ta and surface modified porous Ti64 implants towards early stage osseointegration at 5 weeks post implantation through seamless bone-material interlocking. However, a continued and extended efficacy of porous Ta is found in terms of higher osteoid formation at 12 weeks post-surgery.

Multiplicity in large scale studies using, for example, microarray genomic data and functional neuroimaging data, has been an extensively researched topic in recent years. One option often used by researchers in practice is a “top r-table”, which involves ranking the hypotheses in some order (p-values or test statistics) and reporting the top r results. This has immediate practical applications as what we have is a list of “interesting” results that are worth following up, irrespective of the actual p-value (adjusted or not). In this manuscript we take another look at multiplicity using top-tables. Our approach is intended to be a compromise between theory and practice. We look at the relationship between the probability of correct classification, which we call r-power (the units picked in the top-r table do indeed come from the alternative), and the value of r. We analytically define r-power in terms of order statistics and quantify the probability of correct classification. We use numerical integration to calculate r-power as a function of effect size, δ; the number of hypotheses tested, N; the number of hypotheses coming from the null, k; and r. Our results indicate that r-power is positively related to effect size, and negatively related to k/N. The relationship to r depends upon whether r

When a nominal categorical response along with a multidimensional covariate are repeatedly collected over a small period of time from a large number of independent individuals, it is standard to use the so-called multinomial logits to model the marginal means or probabilities of such responses in terms of time dependent covariates. However, because of the difficulties in modeling the correlations of the repeated multinomial responses, some researchers over the last two decades have analyzed this type of repeated multinomial data by using certain ‘working’ odds ratio, or ‘working’ correlation structures. But, in the context of longitudinal binary data analysis, these ‘working’ correlations based approaches were shown to produce inefficient regression estimates as compared to simpler moment and/or quasi-likelihood approaches. The situation can be worse for longitudinal nominal multinomial/categorical data. In this paper, following the recent correlation models proposed by Sutradhar (Longitudinal Categorical Data Analysis. Springer, New York, 2014, Chap. 3) for the stationary nominal and ordinal categorical data, we discuss similar correlation models but for non-stationary ordinal categorical data. More specifically we exploit the multinomial dynamic logits (MDL) in two different ways to develop correlation models for ordinal categorical data. Under model 1, the ordinal responses are first treated to be nominal and a multinominal dynamic logits model is written for correlations between repeated nominal categorical responses. The regression and correlation parameters involved in the dynamic logits are, however, computed from an updated cumulative dynamic logits model which accommodates the actual ordinal nature of the data. Under model 2, a direct dynamic logits relationship is developed linking the cumulative multinomial responses over time. A lag 1 conditional likelihood is then exploited to estimate the desired regression and correlation parameters. Some asymptotic properties of the estimators under both models are also discussed.

Motivated by an example we discuss the problem of comparison to control in a scenario where we have repeated binary data from a large number independent individuals under each comparison group. We use the generalized quasi-likelihood (GQL) estimators for the comparison group effects including the effect of the control group to define a single step and step-down method for performing many-to-one comparisons. We discuss the asymptotic properties of our method and provide ways of computing the critical values. We follow up with simulations for Type I error and marginal power and show that our proposed method performs well in practice.

In this article, we are interested in comparing growth curves for the Red Delicious apple in several locations to that of a reference site. Although such multiple comparisons are common for linear models, statistical techniques for nonlinear models are not prolific. We theoretically derive a test statistic, considering the issues of sample size and design points. Under equal sample sizes and same design points, our test statistic is based on the maximum of an equi-correlated multivariate chi-square distribution. Under unequal sample sizes and design points, we derive a general correlation structure, and then utilize the multivariate normal distribution to numerically compute critical points for the maximum of the multivariate chi-square. We apply this statistical technique to compare the growth of Red Delicious apples at six locations to a reference site in the state of Washington in 2009. Finally, we perform simulations to verify the performance of our proposed procedure for Type I error and marginal pow...

In many mule deer (Odocoileus hemionus) populations, recruitment of fawns drives population dynamics. The quality of food available to females and their fawns in summer and autumn may play an important role in fawn recruitment. We examined direct links between digestible energy (DE) content of food and the DE intake of females on the nutrient concentration of milk and between the nursing behavior, DE intake, growth, and survival in captive mule deer fawns. We offered females and their fawns diets that simulated the natural decline in DE content of forage from mid-summer to late autumn in many western landscapes. Fawns fed a higher DE diet weighed 14% more at the onset of winter, had fewer unsuccessful nursing attempts, consumed milk with more protein and energy, and had higher survival than fawns fed a low DE diet. Differences between fawn performances among treatments were greatest when diet quality began decreasing earlier in the summer. Because our results indicate that summer and autumn nutri...

Recent work suggests that availability and quality of forage in late summer and early autumn, a time when female ungulates face multiple energetic demands, is critical to reproduction in wild ungulates. Therefore, we examined direct links between nutritional quality of diets, body condition, and reproduction of lactating mule deer. Using captive mule deer, we tested the hypothesis that females consuming diets with lower digestible energy (DE; kJ/g) would have lower DE intake rates (DEI; MJ/day), have less body fat and muscle, have later estrus cycles, and have lower pregnancy and twinning rates. Deer fed lower DE diets had lower DEI during summer and autumn. In turn, deer with lower DEI, regardless of diet DE, had lower body mass, body fat, and muscle thickness. When nutritional quality of diets began to decline earlier in the summer, relationships between food quality, DEI, and body condition were stronger. Although DEI did not influence estrus date for deer that became pregnant before 21 Decemb...

In this paper we consider screening experiments where m factors are to be studied using n experimental runs and where m is relatively large compared to n. In such experimental settings unreplicated fractional factorial (FF) designs are often used. Unreplicated FF designs have received a good deal of study over the past 15 years because they present problems in terms of use and analysis. One major problem with unreplicated FF design is the lack of reliable estimates for experimental error. Because of this a number of methods have been developed for identifying significant effects which include both graphical and more objective methods. However, there does not seem to be a clear winner among the methods suggested. In this paper we suggest as an alternative the use of partially replicated FF designs. The use of partial replication provides a non-model dependent estimate for pure error which allows for simpler and more standard methods for identifying significant effects through the use of F-and T-tests for lack of fit and individual contrasts. To illustrate the possibilities we focus on 16 run designs and provide some partially replicated designs for 4 ≤ m ≤ 11. We compare our proposed designs in terms of the A-optimality criterion and Estimation Capacity to regular unreplicated FF and Generalized Minimum Aberration non-regular FF designs. Our results indicate that partially replicated FF are competitive in terms of the criteria mentioned.

Summary The use of the Internet as a teaching tool continues to grow in popularity at colleges and universities. We consider, from the students’ perspective, the use of an Internet approach compared to a lecture and lab-based approach for teaching an introductory course in statistical methods. We conducted a survey of introductory statistics students. Contradictory to what was hypothesized by the authors, they favoured keeping the lecture and lab-based approach for teaching the class.

Summary The Rhadinovirus ovine herpesvirus-2 (OvHV-2) is the most common causative agent of malignant catarrhal fever (MCF) in clinically susceptible ruminants including cattle and bison. American bison (Bison bison) are highly susceptible to clinical MCF. Nevertheless, approximately 20% of bison on ranches or in feedlots become infected with the virus without developing clinical disease. Defining the genetic basis for differences in susceptibility between bison could facilitate development of improved control strategies for MCF. One genetic region that influences susceptibility to infectious diseases is the major histocompatibility complex (MHC). In this study, a Bison bison (Bibi) DRB3 oligonucleotide microarray was used to type 189 bison from 10 herds where MCF outbreaks had occurred. Binary logistic regression was used to classify DRB3 alleles as resistant (R), susceptible (S )o r neutral (N). Animals were reclassified using six DRB3 genotype categories: N/N, N/R, N/S, R/S, R/R and S/S. Analysis of homogeneity across herds showed that there was a herd effect. Consequently, a penalized logistic regression model was run with herd and genotype categories as the explanatory variables. The R/R genotype was associated with resistance to MCF (P ¼ 0.0327), while the S/S genotype was associated with clinical MCF (P ¼ 0.0069). This is the first evidence that MHC class IIa polymorphism is associated with resistance or susceptibility to OvHV-2-induced MCF.

Experiments in real life often involve comparisons of test treatments to more than one control. However, the controls may not always be of equal importance. In this paper we introduce weighted MV optimality criterion and present a detailed study using both weighted A and MV optimality criteria, of the problem of optimally comparing a set of test treatments to two controls (positive and a negative) that are of unequal importance to the experimenter.

Traditionally, comparisons to control problems dealt with comparing k test treatments to either a positive control or a negative control. However, in certain situations, it is necessary to include both types of control in the study. When comparing k test treatments to both positive and negative controls, the null hypothesis is composite and finding the least favorable configuration (LFC) under the null analytically is difficult. We propose a numerical solution for this problem. Using our method, we show that the LFC under the null is when half of the test treatment means are equal to the mean of the negative control and the other half of the test treatment means are equal to the mean of the positive control. We calculate critical points at the LFC for k=2–6. This work was motivated by real life problems that we discuss and illustrate with an example.

Life table experiments with ten Daphnia clones were conducted to assess responses to three concentrations (0.05 mg 1−1 A1, 0.30 mg 1−1 A1, and 0.50 mg 1−1 A1) of aluminum sulfate (alum), reflecting a general range that might be encountered in lake restoration treatments. Alum is frequently employed for phosphorus inactivation in lake restoration and management applications. Experimental Daphnia clones originated from a lake currently being treated with alum, from a lake treated with alum over twenty years ago, and from a pond with no prior alum additions. When exposed to laboratory alum-conditioned media, clones from the lake with ongoing alum treatment exhibited higher age-specific survivorship, higher fecundity, and faster growth rates compared with clones having less recent or no prior exposure. Our results suggest the possibility that Daphnia may exhibit adaptive strategies that heighten survivorship and fecundity when exposed to sub-lethal chemical stresses. Results also indicate that clone ...

The purpose of this study is to investigate if, or under what conditions, fires select given land cover types for burning. If fires burn unselectively then the land cover composition (the proportional area of various land cover types) of individual fires should approximate the land cover composition available in their neighborhood. In this study we test this hypothesis by performing statistical analyses of a data set consisting of paired vectors with the proportions of land cover types present in burned areas and in their respective surroundings. The statistical methods employed (a permutation technique and the Cmax statistic) are commonly used in resource selection studies where data is subject to a unit-sum constraint. The results of the analysis of 506 fires that burned in Portugal in 1991 indicate that fires are selective, with small fires exhibiting stronger land cover preferences than large fires. According to the results of a multiple comparison analysis performed for small fires, there is a marked preference for shrubland followed by other forest cover types, while agriculture is clearly avoided. A similar analysis is performed to test if fire selectivity is related to the ecological region where it occurs. The results obtained in this study contribute to the discussion on the relative importance of fuels as a drivers of fire spread.

Trans fatty acids (TFA) are found naturally in some foods (e.g., dairy products) as well as many processed foods made with partially hydrogenated vegetable oils (PHVO). Data from a growing literature suggest that some TFA decrease milk fat in lactating animals. Because the physiologic effects of TFA in lactating women are unknown, this study was designed to investigate the effects of TFA consumption on human milk fat. A randomized, crossover design (n = 12) was used to study the effect of 3 dietary treatments: high PHVO (regular margarine), low PHVO (low TFA margarine), or low PHVO but high in naturally occurring TFA (butter) on milk fat. Treatments were administered for 5 d, with 7-d washout periods. Maternal adiposity was estimated by dual-energy X-ray absorptiometry. Milk and blood were collected on d 5 of each intervention period. In general, milk and serum fatty acid concentrations mirrored those of the dietary treatments. There were significant interactions between treatment and maternal adiposity on milk fat and infant milk consumption, as well as on serum glucose and nonesterified fatty acid (NEFA) concentrations. Consumption of regular margarine, compared with low TFA margarine, resulted in lower milk fat in leaner, but not in more obese women. Consumption of either regular or low TFA margarine, compared with butter, elevated serum NEFA concentrations in the more obese women. In summary, consumption of regular margarine, compared with low TFA margarine, decreased milk fat in lean women. Further studies are required to determine whether infant milk consumption might compensate for this potentially important change in milk composition.

Isomers of conjugated linoleic acid (CLA) decreased milk fat, altered immunity, and reduced the risk for cardiovascular disease (CVD) in some animals. The major form of CLA in the human diet is c9,t11-18:2 (rumenic acid; RA). We studied the effects of high RA consumption on plasma and milk RA concentration, milk composition, immunity, and CVD risk factors in lactating women (n = 36) assigned to 1 of 3 treatments: control, low CLA cheese (LCLA; 160 mg RA/d), or high CLA cheese (HCLA; 346 mg RA/d). The increase in plasma RA concentration between baseline and 8 wk in women consuming HCLA cheese was significantly greater than that of controls. At study completion (8 wk), milk RA concentration among women consuming HCLA cheese was greater (P < 0.05) than that of controls (0.37 vs. 0.26% of fatty acids). Treatment did not affect milk fat, protein, or lactose concentrations, immune indices (e.g., plasma T-helper cells and interleukin-2), or measured risk factors for CVD (e.g., plasma triacylglyceride and cholesterol). In summary, consumption of a RA-enriched cheese modestly increased plasma and milk RA concentrations without affecting total milk fat, plasma and milk indices of immunity, or selected risk factors for CVD.

The effects of tuber depth, soil type, and soil moisture on potato tuber infection due to Phytophthora infestans were assessed under greenhouse conditions in soil contained in large pots. Healthy tubers were used to assess infection and were either hand buried in soil at specific depths or naturally formed from potato plants growing in the soil. A spore suspension of P. infestans was chilled to induce zoospore formation and a suspension of resulting zoospores and sporangia were applied to the soil. Soil depth at which tubers became infected was used to determine the extent of spore movement in the soils. Tuber infection significantly decreased with increasing soil depth. Most infected tubers were found at the surface of soil; infection was rare on tubers at 5 cm or deeper in the soil. Amount of tuber infection varied among soil types. Significantly less tuber infection occurred in a Shano silt loam than in medium and fine sands. Only tubers on the soil surface were infected in the Shano silt loam. Depth in soil at which tubers became infected did not differ significantly among Quincy fine sand, Quincy loamy fine sand, and Quincy medium sand. Increased soil moisture did not significantly increase the soil depth at which tuber infection occurred, regardless of the soil type.

Resource selection by wildlife is often studied by observing if a particular resource category is used or not, or by observing and comparing quantitative at tributes of used and unused plots. That is, plots may be described as used or not used, as belonging to a particular resource category, and through an array of quantitative characteristics thought to be related to their use status. Of interest is the situation where different resource categories have experienced differing treatments, and one category is considered the control. A method of comparing selection of treatment categories to selection of the control is presented here when several quantitative characteristics are concurrently measured on each plot. The method is used to investigate the effect of grazing and vegetative characteristics on use of plots by pygmy rabbits.

CLA refers to isomers of octadecadienoic acid with conjugated double bonds. The most abundant form of CLA (rumenic acid (RA): c9,t11-18:2) is found in milk and beef fat. Further, CLA supplements containing RA and t10,c12-18:2 are now available. Consumption of commercially produced CLA has been shown to decrease adipose accretion in growing laboratory and production animals and cause milk fat depression in cows. We tested the hypothesis that CLA supplementation would increase milk CLA concentration and decrease milk fat content in humans. Breastfeeding women (n = 9) participated in this double-blind, placebo-controlled, crossover study divided into three periods: intervention I (5 d), washout (7 d), and intervention II (5 d). Women were randomized to treatment order. During each intervention period, women consumed 1.5 g of CLA supplement or placebo (olive oil) daily; during the washout period, no supplements were consumed. Milk was collected by complete breast expression on the final day of each period; milk output was estimated by 24-h weighing on the penultimate day of each intervention period. Milk RA and t10,c12-18:2 concentrations were greater (P < 0.05) during the CLA treatment period as compared to the placebo period. Milk fat content was significantly lower during the CLA treatment, as compared to the placebo treatment (P < 0.05). Data indicate no effect of treatment on milk output. Therefore, it would be prudent that lactating women not consume commercially available CLA supplements at this time.

For comparing several logistic regression slopes to that of a control for small sample sizes, Dasgupta et al. (2001) proposed an "asymptotic" small-sample test and a "pivoted" version of that test statistic. Their results show both methods perform well in terms of Type I error control and marginal power when the response is related to the explanatory variable via a logistic regression model. This study finds, via Monte Carlo simulations, that when the underlying relationship is probit, complementary log-log, linear, or even non-monotonic, the "asymptotic" and the "pivoted" small-sample methods perform fairly well in terms of Type I error control and marginal power. Unlike their large sample competitors, they are generally robust to departures from the logistic regression model.

Background: The mechanisms regulating postpartum anovulation (PPA) are not well understood, although poor nutritional status and “intense” breastfeeding behaviors are associated with longer durations. Objectives: This study was designed primarily to investigate the hypothesis that higher body fat and leptin concentrations are related to shorter PPA in healthy, lactating US women. Nutrient intake, breastfeeding behaviors, prolactin, and insulin levels were also evaluated. Methods: Fasting serum was collected during the third trimester of pregnancy, at 2 and 4 weeks postpartum, and every 4 weeks until the occurrence of the first postpartum menses. Body composition and breastfeeding behaviors were assessed at the same times postpartum. Women (n = 13) were categorized based on initial percentage body fat and timing of first postpartum menses. Results: There were no consistent relationships between body composition, leptin, or breastfeeding behaviors and duration of PPA. However, there was an interaction ( P = .005) between ovulation group and time on adiposity; earlier ovulating women had less percentage body fat in early lactation than did later ovulating women. There was also an interaction ( P = .1) between ovulation group and time postpartum on leptin, such that leptin concentrations tended to be greater in later than earlier ovulating groups beginning at 12 weeks postpartum. Conclusion: In summary, although baseline percentage body fat and leptin were not related to duration of PPA, fertility returned earlier in women who lost greater percentage body fat during the early postpartum period.

In experiments from the life sciences, application of logistic regression techniques is common. Often it is imperative to compare the slopes of several of logistic regressions to that of a standard. In this article we define a test statistic based on the difference of minimal sufficient statistics and we represent two techniques for dealing with this problem for small samples. In the first approach we use the distribution function of the statistic and propose a pivoted small-sample procedure. In the second approach we use step-down permutation test. We compare these methods with existing asymptotic methods and show that the proposed methods outperform their competitors in terms of both Type I error and marginal power. The research is motivated by a problem in plant pathology which we include as our data example.

Conjugated linoleic acids (CLA) are conjugated isomers of linoleic acid, which may promote health with regard to cancer, heart disease, diabetes, bone formation, growth modulation and immunity. The c9,t11 isomer of CLA, rumenic acid (RA), is the major isomer present in the diet. However, dietary intakes of CLA and RA by humans have not been examined rigorously, nor has the relationship between dietary CLA or RA and health (e.g., body composition). Three-day dietary records (DR) were collected from adult men (n = 46) and women (n = 47) and analyzed using a nutrient database modified to contain total CLA and RA. Simultaneously, 3-d food duplicates (FD) were collected to determine analytically individual fatty acid intakes, including those of total CLA and RA. Chronic total CLA and RA intakes were estimated using a semiquantitative food-frequency questionnaire (FFQ). Body composition was estimated using body mass index and percentage of body fat. Total CLA intake was estimated from FD to be 212 +/- 14 and 151 +/- 14 mg/d (mean +/- SEM) for men and women, respectively; RA intake was estimated to be 193 +/- 13 and 140 +/- 14 mg/d for men and women, respectively. In general, CLA and RA intakes estimated by DR and FFQ were significantly lower than those estimated by FD. Body composition was not significantly related to dietary total CLA or RA intake. In conclusion, results suggest that DR and FFQ methodologies are not reliable estimators of individual total CLA and RA intakes and may underestimate total CLA and RA intakes of groups. Intake of total CLA and RA was found to be significantly lower than that suggested previously by others.

We are interested in comparing logistic regressions for several test treatments or populations with a logistic regression for a standard treatment or population. The research was motivated by some real life problems, which are discussed as data examples. We propose a step-down likelihood ratio method for declaring differences between the test treatments or populations and the standard treatment or population. Competitors based on the sequentially rejective Bonferroni Wald statistic, sequentially rejective exact Wald statistic and Reiers⊘l's statistic are also discussed. It is shown that the proposed method asymptotically controls the probability of type I error. A Monte Carlo simulation shows that the proposed method performs well for relatively small sample sizes, outperforming its competitors.

Coronary artery calcium is a marker of coronary artery disease and measures the progression of atherosclerosis. It is measured by electron beam computed tomography, and the measured amount of coronary artery calcium is highly skewed to the right and left censored. The distribution of coronary artery calcium appears to be Weibull. We propose a Weibull regression model and we analyze the data using these techniques. Our analysis is based on data from the Spokane Heart Study, which is a cohort of about a thousand subjects that are assessed every two years for coronary artery calcium and risk factors of coronary artery disease. The major focus of the heart study is to determine the natural history of atherosclerosis in its early phase, and we analyze the data as a cross-sectional study with 859 subjects. We would also like to highlight the use of Weibull regression techniques in situations like this, where we have extreme right skewed data. Our main emphasis will be on examining the effect of the traditional ...

A multivariate generation of Bose's ( 1935) bivariate chi-square distribution is presented. This multivariate family arises for some problems involving the comparison of k>I experimental treatments to a control when the limiting distribution of the twosample statistic is chi-square. 1nference for these comparison with control problems is based on the null distribut~on dfthe maximum component. A computation algorithm and tables for probability points are presented for the distribution of the maximum component. Two applications are discussed.

There is little research evaluating flavor preferences among wheat varieties. We previously demonstrated that mice exert very strong preferences when given binary mixtures of wheat varieties. We plan to utilize mice to identify wheat genes associated with flavor, and then relate this back to human preferences. Here we explore the effects of experimental design including the number of days (from 1 to 4) and number of mice (from 2 to 15) in order to identify designs that provide significant statistical inferences while minimizing requirements for labor and animals. When mice expressed a significant preference between 2 wheat varieties, increasing the number of days (for a given number of mice) increased the significance level (decreased P-values) for their preference, as expected, but with diminishing benefit as more days were added. However, increasing the number of mice (for a given number of days) provided a more dramatic log-linear decrease in P-values and thus increased statistical power. In conclusion, when evaluating mouse feeding preferences in binary mixtures of grain, an efficient experimental design would emphasize fewer days rather than fewer animals thus shortening the experiment duration and reducing the overall requirement for labor and animals.

The c9,t11–18:2 isomer of conjugated linoleic acid (c9,t11-CLA) represents the main dietary CLA form with putative health benefits. Whereas CLA intake influences the tissue CLA concentration, little is known about the association between dietary CLA and the CLA content of plasma lipid fractions. This study was designed to document fasting and nonfasting plasma c9,t11-CLA concentrations in a population of free-living adults (n = 94) and relate these concentrations to c9,t11CLA intake. We also determined the c9,t11-CLA content of the primary plasma lipid fractions in a subset (n = 50) of our participants, related these to c9,t11-CLA intake, and determined whether c9,t11-CLA intake or plasma c9,t11-CLA was correlated with plasma cholesterol. Mean fasting plasma c9,t11-CLA concentrations were 0.46 6 0.01 and 0.54 6 0.01% (wt:wt) of total fatty acids for men and women, respectively (P < 0.05); nonfasting concentrations were 0.28 6 0.01 and 0.38 6 0.01% of total fatty acids, respectively (P < 0.001). All major esterified plasma lipid fractions contained c9,t11-CLA; TG had the highest percentages. In men, c9,t11-CLA intake correlated (r = 0.47; P < 0.05) with TG c9,t11-CLA content, suggesting that TG c9,t11-CLA may serve as a biomarker for c9,t11-CLA intake. In females, there were no correlations between c9,t11-CLA intake and the c9,t11-CLA content of any esterified plasma lipid fraction. In neither sex was there a relation between dietary c9,t11-CLA or plasma c9,t11-CLA concentration and circulating lipoprotein cholesterol concentration. The influence of sex on circulating c9,t11-CLA content and further validation of biomarkers of c9,t11CLA intake warrant further investigation. J. Nutr. doi: 10.3945/jn.111.156794.

With more older adults and people with cognitive disorders preferring to stay independently at home, prompting systems that assist with Activities of Daily Living (ADLs) are in demand. In this paper, with the introduction of “The PUCK”, we take the very first approach to automate a prompting system without any predefined rule set or user feedback. We statistically analyze realistic prompting data and devise a classifier from statistical outlier detection methods. Further, we devise a sampling technique to help with skewed and scanty data sets. We empirically find a class distribution that would be suitable for our work and validate our claims with the help of three classical machine learning algorithms.