Methods to assess an exercise intervention trial based on 3-level functional data.

Motivated by data recording the effects of an exercise intervention on subjects' physical activity over time, we develop a model to assess the effects of a treatment when the data are functional with 3 levels (subjects, weeks and days in our application) and possibly incomplete. We develop a model with 3-level mean structure effects, all stratified by treatment and subject random effects, including a general subject effect and nested effects for the 3 levels. The mean and random structures are specified as smooth curves measured at various time points. The association structure of the 3-level data is induced through the random curves, which are summarized using a few important principal components. We use penalized splines to model the mean curves and the principal component curves, and cast the proposed model into a mixed effects model framework for model fitting, prediction and inference. We develop an algorithm to fit the model iteratively with the Expectation/Conditional Maximization Either (ECME) version of the EM algorithm and eigenvalue decompositions. Selection of the number of principal components and handling incomplete data issues are incorporated into the algorithm. The performance of the Wald-type hypothesis test is also discussed. The method is applied to the physical activity data and evaluated empirically by a simulation study.

Metabolomic analysis of plasma and liver from surplus arginine fed Atlantic salmon.

The aim of this study was to determine the metabolic effect of surplus arginine (36.1 g/kg dry matter) compared to a control diet with required arginine (21.1 g/kg dry matter) in adult Atlantic salmon (Salmo salar L.). Although the feeding trial had no significant effect on growth, there were significant differences in the metabolite profile in both plasma and liver in experimental group as compared to the control group. There was increased concentrations of biliverdin, PGF-2 alpha, oxidized glutathione, selenocysteine, two monoacylglycerols and a tripeptide in the liver as well as decreased concentrations of valine and a vitamin D3 metabolite in plasma of arginine supplemented fish. These results indicate that while surplus arginine does not affect growth or body weight, it induces metabolic changes in Atlantic salmon.

Beneficial roles of dietary oleum cinnamomi in alleviating intestinal injury.

Cinnamon is a traditional herb used for treatment of many human diseases. The most important chemical compounds of the essential oil are cinnamaldehyde and eugenol. Oleum cinnamomi (OCM, cinnamon oil) is increasingly used as a feed additive to animal diets. Beneficial effects of OCM in protecting tissues from inflammation and injury by endogenous and exogenous agents (such as hydrogen peroxide and lipopolysaccharide (LPS)) may result, in part, from its action on regulating amino acid metabolism in cells to favor the synthesis of glutathione (a major low-molecular-weight antioxidant) from cysteine, glycine and glutamate. In support of this notion, results of recent studies indicate that supplementing OCM (50 mg/kg diet) to a corn- and soybean meal-based diet for piglets weaned at 21 days of age enhances intestinal anti-oxidative capacity and reduces the incidence of diarrhea. Additionally, dietary supplementation with OCM ameliorates LPS-induced mucosal barrier dysfunction and mucosal damage in the small intestine. OCM holds great promise for protecting the gut from injury under conditions of inflammation, infections, and oxidative stress.

Rapid publication-ready MS-Word tables for two-way ANOVA.

BACKGROUND: Statistical tables are an essential component of scientific papers and reports in biomedical and agricultural sciences. Measurements in these tables are summarized as mean ± SEM for each treatment group. Results from pairwise-comparison tests are often included using letter displays, in which treatment means that are not significantly different, are followed by a common letter. However, the traditional manual processes for computation and presentation of statistically significant outcomes in MS Word tables using a letter-based algorithm are tedious and prone to errors. RESULTS: Using the R package 'Shiny', we present a web-based program freely available online, at https://houssein-assaad.shinyapps.io/TwoWayANOVA/. No download is required. The program is capable of rapidly generating publication-ready tables containing two-way analysis of variance (ANOVA) results. Additionally, the software can perform multiple comparisons of means using the Duncan, Student-Newman-Keuls, Tukey Kramer, Westfall, and Fisher's least significant difference (LSD) tests. If the LSD test is selected, multiple methods (e.g., Bonferroni and Holm) are available for adjusting p-values. Significance statements resulting from all pairwise comparisons are included in the table using the popular letter display algorithm. With the application of our software, the procedures of ANOVA can be completed within seconds using a web-browser, preferably Mozilla Firefox or Google Chrome, and a few mouse clicks. To our awareness, none of the currently available commercial (e.g., Stata, SPSS and SAS) or open-source software (e.g., R and Python) can perform such a rapid task without advanced knowledge of the corresponding programming language. CONCLUSIONS: The new and user-friendly program described in this paper should help scientists perform statistical analysis and rapidly generate publication-ready MS-Word tables for two-way ANOVA. Our software is expected to facilitate research in agriculture, biomedicine, and other fields of life sciences.

Rapid publication-ready MS-Word tables for one-way ANOVA.

BACKGROUND: Statistical tables are an important component of data analysis and reports in biological sciences. However, the traditional manual processes for computation and presentation of statistically significant results using a letter-based algorithm are tedious and prone to errors. RESULTS: Based on the R language, we present two web-based software for individual and summary data, freely available online, at http://shiny.stat.tamu.edu:3838/hassaad/Table_report1/ and http://shiny.stat.tamu.edu:3838/hassaad/SumAOV1/, respectively. The software are capable of rapidly generating publication-ready tables containing one-way analysis of variance (ANOVA) results. No download is required. Additionally, the software can perform multiple comparisons of means using the Duncan, Student-Newman-Keuls, Tukey Kramer, and Fisher's least significant difference (LSD) tests. If the LSD test is selected, multiple methods (e.g., Bonferroni and Holm) are available for adjusting p-values. Using the software, the procedures of ANOVA can be completed within seconds using a web-browser, preferably Mozilla Firefox or Google Chrome, and a few mouse clicks. Furthermore, the software can handle one-way ANOVA for summary data (i.e. sample size, mean, and SD or SEM per treatment group) with post-hoc multiple comparisons among treatment means. To our awareness, none of the currently available commercial (e.g., SPSS and SAS) or open-source software (e.g., R and Python) can perform such a rapid task without advanced knowledge of the corresponding programming language. CONCLUSIONS: Our new and user-friendly software to perform statistical analysis and generate publication-ready MS-Word tables for one-way ANOVA are expected to facilitate research in agriculture, biomedicine, and other fields of life sciences.

Chlorogenic acid decreases intestinal permeability and increases expression of intestinal tight junction proteins in weaned rats challenged with LPS.

Chlorogenic acid, a natural phenolic acid present in fruits and plants, provides beneficial effects for human health. The objectives of this study were to investigate whether chlorogenic acid (CHA) could improve the intestinal barrier integrity for weaned rats with lipopolysaccharide (LPS) challenge. Thirty-two weaned male Sprague Dawley rats (21 ± 1 d of age; 62.26 ± 2.73 g) were selected and randomly allotted to four treatments, including weaned rat control, LPS-challenged and chlorogenic acid (CHA) supplemented group (orally 20 mg/kg and 50 mg/kg body). Dietary supplementation with CHA decreased (P<0.05) the concentrations of urea and albumin in the serum, compared to the LPS-challenged group. The levels of IFN-γ and TNF-α were lower (P<0.05) in the jejunal and colon of weaned rats receiving CHA supplementation, in comparison with the control group. CHA supplementation increased (P<0.05) villus height and the ratio of villus height to crypt depth in the jejunal and ileal mucosae under condictions of LPS challenge. CHA supplementation decreased (P<0.05) intestinal permeability, which was indicated by the ratio of lactulose to mannitol and serum DAO activity, when compared to weaned rats with LPS challenge. Immunohistochemical analysis of tight junction proteins revealed that ZO-1 and occludin protein abundances in the jejunum and colon were increased (P<0.05) by CHA supplementation. Additionally, results of immunoblot analysis revealed that the amount of occludin in the colon was also increased (P<0.05) in CHA-supplemented rats. In conclusion, CHA decreases intestinal permeability and increases intestinal expression of tight junction proteins in weaned rats challenged with LPS.

Analysis of energy expenditure in diet-induced obese rats.

Development of obesity in animals is affected by energy intake, dietary composition, and metabolism. Useful models for studying this metabolic problem are Sprague-Dawley rats fed low-fat (LF) or high-fat (HF) diets beginning at 28 days of age. Through experimental design, their dietary intakes of energy, protein, vitamins, and minerals per kg body weight (BW) do not differ in order to eliminate confounding factors in data interpretation. The 24-h energy expenditure of rats is measured using indirect calorimetry. A regression model is constructed to accurately predict BW gain based on diet, initial BW gain, and the principal component scores of respiratory quotient and heat production. Time-course data on metabolism (including energy expenditure) are analyzed using a mixed effect model that fits both fixed and random effects. Cluster analysis is employed to classify rats as normal-weight or obese. HF-fed rats are heavier than LF-fed rats, but rates of their heat production per kg non-fat mass do not differ. We conclude that metabolic conversion of dietary lipids into body fat primarily contributes to obesity in HF-fed rats.

Metabolomic analysis of amino acid and energy metabolism in rats supplemented with chlorogenic acid.

This study was conducted to investigate effects of chlorogenic acid (CGA) supplementation on serum and hepatic metabolomes in rats. Rats received daily intragastric administration of either CGA (60 mg/kg body weight) or distilled water (control) for 4 weeks. Growth performance, serum biochemical profiles, and hepatic morphology were measured. Additionally, serum and liver tissue extracts were analyzed for metabolomes by high-resolution (1)H nuclear magnetic resonance-based metabolomics and multivariate statistics. CGA did not affect rat growth performance, serum biochemical profiles, or hepatic morphology. However, supplementation with CGA decreased serum concentrations of lactate, pyruvate, succinate, citrate, ß-hydroxybutyrate and acetoacetate, while increasing serum concentrations of glycine and hepatic concentrations of glutathione. These results suggest that CGA supplementation results in perturbation of energy and amino acid metabolism in rats. We suggest that glycine and glutathione in serum may be useful biomarkers for biological properties of CGA on nitrogen metabolism in vivo.

L-statistics for Repeated Measurements Data With Application to Trimmed Means, Quantiles and Tolerance Intervals.

The L-statistics form an important class of estimators in nonparametric statistics. Its members include trimmed means and sample quantiles and functions thereof. This article is devoted to theory and applications of L-statistics for repeated measurements data, wherein the measurements on the same subject are dependent and the measurements from different subjects are independent. This article has three main goals: (a) Show that the L-statistics are asymptotically normal for repeated measurements data. (b) Present three statistical applications of this result, namely, location estimation using trimmed means, quantile estimation and construction of tolerance intervals. (c) Obtain a Bahadur representation for sample quantiles. These results are generalizations of similar results for independently and identically distributed data. The practical usefulness of these results is illustrated by analyzing a real data set involving measurement of systolic blood pressure. The properties of the proposed point and interval estimators are examined via simulation.