Stepwise Procedures under Unknown Variances for Toxicological Evaluation

Toxicological study is of practical importance in modern drug development. Proper statistical methodologies for toxicological evaluation of new developed drugs are undoubtedly necessary. In toxicological studies, it is practically desirable for a method to not declare the safety of a developed drug at a higher dosage prior to the declaration of the safety at lower dosages. Hsu and Berger 's stepwise confidence interval method was recently proposed for this purpose. Unfortunately, their procedure necessitates the homogeneity of variances among dosages, which is seldom satisfied in practice. In this article, via the application of the Stein 's two‐stage sampling method, we propose a stepwise confidence interval procedure for the same task without the homoscedasticity restriction. In addition, our procedure is shown to control its family‐wise type I error rate at the pre‐chosen nominal level. A simulation study will be conducted to compare our method, Hsu and Berger 's stepwise confidence interval method, and a single stage stepwise testing procedure based on Welch 's approximation. Our procedure is empirically shown to outperform Hsu and Berger 's procedure under heteroscedasticity and perform similarly with Welch 's procedure. An example will be used to illustrate our method.     

A Revisit on Comparing the Asymptotic Interval Estimators of Odds Ratio in a Single 2 × 2 Table

It is well known that Cornfield 's confidence interval of the odds ratio with the continuity correction can mimic the performance of the exact method. Furthermore, because the calculation procedure of using the former is much simpler than that of using the latter, Cornfield 's confidence interval with the continuity correction is highly recommended by many publications. However, all these papers that draw this conclusion are on the basis of examining the coverage probability exclusively. The efficiency of the resulting confidence intervals is completely ignored. This paper calculates and compares the coverage probability and the average length for Woolf s logit interval estimator, Gart 's logit interval estimator of adding 0.50, Cornfield 's interval estimator with the continuity correction, and Cornfield 's interval estimator without the continuity correction in a variety of situations. This paper notes that Cornfield 's interval estimator with the continuity correction is too conservative, while Cornfield 's method without the continuity correction can improve efficiency without sacrificing the accuracy of the coverage probability. This paper further notes that when the sample size is small (say, 20 or 30 per group) and the probability of exposure in the control group is small (say, 0.10) or large (say, 0.90), using Cornfield 's method without the continuity correction is likely preferable to all the other estimators considered here. When the sample size is large (say, 100 per group) or when the probability of exposure in the control group is moderate (say, 0.50), Gart 's logit interval estimator is probably the best.     

Berkson's paradox and weighted distributions: An application to Alzheimer's disease

One reason for observing in practice a false positive or negative correlation between two random variables, which are either not correlated or correlated with a different direction, is the overrepresentation in the sample of individuals satisfying specific properties. In 1946, Berkson first illustrated the presence of a false correlation due to this last reason, which is known as Berkson's paradox and is one of the most famous paradox in probability and statistics. In this paper, the concept of weighted distributions is utilized to describe Berskon's paradox. Moreover, a proper procedure is suggested to make inference for the population given a biased sample which possesses all the characteristics of Berkson's paradox. A real data application for patients with dementia due to Alzheimer's disease demonstrates that the proposed method reveals characteristics of the population that are masked by the sampling procedure.     

Protein interaction network for Alzheimer's disease using computational approach

Alzheimer''s disease (AD) is the most common form of dementia. It is the sixth leading cause of death in old age people. Despite recent advances in the field of drug design, the medical treatment for the disease is purely symptomatic and hardly effective. Thus there is a need to understand the molecular mechanism behind the disease in order to improve the drug aspects of the disease. We provided two contributions in the field of proteomics in drug design. First, we have constructed a protein-protein interaction network for Alzheimer''s disease reviewed proteins with 1412 interactions predicted among 969 proteins. Second, the disease proteins were given confidence scores to prioritize and then analyzed for their homology nature with respect to paralogs and homologs. The homology persisted with the mouse giving a basis for drug design phase. The method will create a new drug design technique in the field of bioinformatics by linking drug design process with protein-protein interactions via signal pathways. This method can be improvised for other diseases in future.     

Joint Confidence Sets in Multiple Dilution Assays

Let {Q₁, …, Q_k} be the potencies of k substances relative to a standard in a multiple dilution assay. Joint confidence bounds for these are given with confidence coefficient at least 1-α. These bounds are easily interpreted; they appeal to available tables; they improve Scheffe's bounds; they are based on applicable probability inequalities together with extensions of Fieller's theorem; and they are genuinely nonparametric. The procedures are illustrated using data from parallel-line and slope-ratio assays.     

Scheffy's Confidence Intervals in the Models of Analysis of Covariance

Scheffe's confidence intervals for linear functions of some subvectors of a vector of parameters are presented. The considered subvectors are such that covariance matrices of their estimators are known non-negative definite matrices multiplied by unknown positive constants. This property is characteristic of the least squares estimators of vectors of main and interaction effects in the analysis of covariance models of the following experimental designs: split-block, split-plot, completely randomized two-factor design and randomized complete block design. The formulas for confidence intervals for linear functions of vectors of main or interaction effects in the designs mentioned above are given in the paper. The practical example is given as an illustration.     

Morphological variations in a widely distributed Eastern Asian passerine cannot be consistently explained by ecogeographic rules

Ecogeographic rules that describe quantitative relationships between morphologies and climate might help us predict how morphometrics of animals was shaped by local temperature or humidity. Although the ecogeographic rules had been widely tested in animals of Europe and North America, they had not been fully validated for species in regions that are less studied. Here, we investigate the morphometric variation of a widely distributed East Asian passerine, the vinous‐throated parrotbill (Sinosuthora webbiana), to test whether its morphological variation conforms to the prediction of Bergmann''s rule, Allen''s rules, and Gloger''s rule. We at first described the climatic niche of S. webbiana from occurrence records (n = 7838) and specimen records (n = 290). The results of analysis of covariance (ANCOVA) suggested that the plumage coloration of these parrotbills was darker in wetter/warmer environments following Gloger''s rule. However, their appendage size (culmen length, beak volume, tarsi length) was larger in colder environments, the opposite of the predictions of Allen''s rule. Similarly, their body size (wing length) was larger in warmer environments, the opposite of the predictions of Bergmann''s rule. Such disconformity to both Bergmann''s rule and Allen''s rule suggests that the evolution of morphological variations is likely governed by multiple selection forces rather than dominated by thermoregulation. Our results suggest that these ecogeographic rules should be validated prior to forecasting biological responses to climate change especially for species in less‐studied regions.     

On the Comparison of Two Observed Frequencies

A significance measure essentially due to Liebermeister and dating back to 1877 may be preferable to Fisher's Exact Test, a conservative but commonly applied test when the sample sizes are small. We show that Liebermeister's measure is less conservative than Fisher's P‐value and just as easy to calculate, while retaining the important features of a significance measure. We also compare Liebermeister's measure with Lancaster's mid‐P, which has gained increasing acceptance as a replacement for Fisher's P‐value. Application is made to a recent striking medical study on appendicitis symptoms for which the Fisher test does not give significance.     

A Comparative Statistical Analysis of Genetic Distances. II–Confidence Intervals and Tests of Comparison

We present methods for constructing the confidence intervals of the estimations of absolute genetic distance and Nei's minimum and standard genetic distances. Two different estimators of the standard distance are considered: jack-knife and corrected. A Monte-Carlo simulation analysis permitted to choose the best adapted confidence interval type for each distance estimator and for each size of the samples of loci and of gametes, taking into account the magnitude of the estimation value. Simulated true confidence levels showed that the best results are obtained using abolute genetic distance. We also give rules for testing the significance of the difference of two distance estimations. Monte-Carlo simulations were performed in order to obtain the distributions of the difference of two distance estimations under the null hypothesis and consequently the true type I errors of tests. Test powers, obtained by simulation under the alternative hypothesis, also showed the superiority of absolute genetic distance.     

Confidence Intervals of the Simple Difference between the Proportions of a Primary Infection and a Secondary Infection,Given the Primary Infection

This paper discusses interval estimation of the simple difference (SD) between the proportions of the primary infection and the secondary infection, given the primary infection, by developing three asymptotic interval estimators using Wald's test statistic, the likelihood‐ratio test, and the basic principle of Fieller's theorem. This paper further evaluates and compares the performance of these interval estimators with respect to the coverage probability and the expected length of the resulting confidence intervals. This paper finds that the asymptotic confidence interval using the likelihood ratio test consistently performs well in all situations considered here. When the underlying SD is within 0.10 and the total number of subjects is not large (say, 50), this paper further finds that the interval estimators using Fieller's theorem would be preferable to the estimator using the Wald's test statistic if the primary infection probability were moderate (say, 0.30), but the latter is preferable to the former if this probability were large (say, 0.80). When the total number of subjects is large (say, ≥200), all the three interval estimators perform well in almost all situations considered in this paper. In these cases, for simplicity, we may apply either of the two interval estimators using Wald's test statistic or Fieller's theorem without losing much accuracy and efficiency as compared with the interval estimator using the asymptotic likelihood ratio test.     

A remark on a paper by misra

MISRA (1978) sets confidence intervals for a double linear compound of multivariate normal regression coefficients by using ROY'S maximum root test criterion. The exact test statistic to be used is STUDENT'S t. The t statistic gives narrower confidence bounds than those given by ROY's maximum root statistic. A result given by MORRISON (1975, p. 18, equation 10) for profile analysis is also obtained by using the STUDENT'S t test.     

Hirschsprung's disease prevalence in Europe: A register based study

Background: Hirschsprung's disease is a congenital gut motility disorder, characterised by the absence of the enteric ganglion cells along the distal gut. The aim of this study was to describe the epidemiology of Hirschsprung's disease, including additional congenital anomalies, total prevalence, trends, and association with maternal age. Methods: Cases of Hirschsprung's disease delivered during 1980 to 2009 notified to 31 European Surveillance of Congenital Anomaly registers formed the population‐based case‐series. Prevalence rates and 95% confidence intervals were calculated as the number of cases per 10,000 births. Multilevel Poisson regression was performed to investigate trends in prevalence, geographical variation and the association with maternal age. Results: There were 1,322 cases of Hirschsprung's disease among 12,146,210 births. The total prevalence was 1.09 (95% confidence interval, 1.03–1.15) per 10,000 births and there was a small but significant increase in prevalence over time (relative risk = 1.01; 95% credible interval, 1.00–1.02; p = 0.004). There was evidence of geographical heterogeneity in prevalence (p < 0.001). Excluding 146 (11.0%) cases with chromosomal anomalies or genetic syndromes, there were 1,176 cases (prevalence = 0.97; 95% confidence interval, 0.91–1.03 per 10,000 births), of which 137 (11.6%) had major structural anomalies. There was no evidence of a significant increased risk of Hirschsprung's disease in cases born to women aged ≥35 years compared with those aged 25 to 29 (relative risk = 1.09; 95% credible interval, 0.91–1.31; p = 0.355). Conclusion: This large population‐based study found evidence of a small increasing trend in Hirschsprung's disease and differences in prevalence by geographic location. There was also no evidence of an association with maternal age. Birth Defects Research (Part A), 100:695–702, 2014. © 2014 Wiley Periodicals, Inc.     

Morgan's Canon: Is it still a useful rule of thumb?

For over 100 years, Morgan's Canon has served as the criterion for distinguishing what appears to be complex cognitive processes shown by animals from simpler associative learning processes (Pavlovian and instrumental conditioning). Morgan's ( 1894 ) canon states “In no case is an animal activity to be interpreted in terms of higher psychological processes if it can be fairly interpreted in terms of processes which stand lower in the scale of psychological evolution and development.” In the present article, several examples are provided in which complex human‐like processes are proposed to have been demonstrated but the judicious use of Morgan's Canon suggests that simpler mechanisms may be sufficient to account for the behavior. The use of Morgan's Canon is not meant to reduce behavior to its lowest common denominator but rather to challenge investigators to develop procedures that can distinguish between simple behavioral principles and the more complex processes that cannot be explained in terms of genetics or simple conditioning. Whatever the results of these experiments, they should help identify the underlying processes and mechanisms involved.     

NAD/NADP及其介导氧化应激在神经退行性疾病中的作用

神经退行性疾病如阿尔茨海默病、帕金森病、亨廷顿病等疾病的发生与氧化应激紧密相关。NAD和NADP是维持氧化系统和抗氧化系统平衡的两个关键物质。NAD和NADP的生物合成和降解有多种途径,参与其生物途径的物质如NAMPT、NADK、PARP1、SIRT1、CD38等,均报道在神经退行性疾病发挥一定的作用。因此,本文分别从NAD和NADP的合成和降解途径中的一些关键物质出发,结合氧化应激总结并探讨它们在神经退行性疾病的作用,以期为临床治疗神经退行性疾病提供新思路。     

Interrelations of global macroecological patterns in wing and thorax size,sexual size dimorphism,and range size of the Drosophilidae

Support for macroecological rules in insects is mixed, with potential confounding interrelations between patterns rarely studied. We here investigate global patterns in body and wing size, sexual size dimorphism and range size in common fruit flies (Diptera: Drosophilidae) and explore potential interrelations and the predictive power of Allen's, Bergmann's, Rensch's and Rapoport's rules. We found that thorax length (r² = 0.05) and wing size (r² = 0.09) increased with latitude, supporting Bergmann's rule. Contrary to patterns often found in endothermic vertebrates, relative wing size increased towards the poles (r² = 0.12), a pattern against Allen's rule, which we attribute to selection for increased flight capacity in the cold. Sexual size dimorphism decreased with size, evincing Rensch's rule across the family (r² = 0.14). Yet, this pattern was largely driven by the virilis–repleta radiation. Finally, range size did not correlate with latitude, although a positive relationship was present in a subset of the species investigated, providing no convincing evidence for Rapoport's rule. We further found little support for confounding interrelations between body size, wing loading and range size in this taxon. Nevertheless, we demonstrate that studying several traits simultaneously at minimum permits better interpretation in case of multiple, potentially conflicting trends or hypotheses concerning the macroecology of insects.     

On Testing for Non-Additivity in Factorial Experiments

In analysis of variance the assumption of non-additivity has more serious consequences on the interpretation of results than the assumptions of non-normality or non-homogeneity of variances. Tukey (1949, 1955) suggested a procedure for separating out a single degree of freedom for non-additivity for two factor and multi-factor experiments, respectively. In multifactor experiments Tukey's procedure does not indicate which combinations of the factors contribute to non-additivity. In this paper a procedure is proposed which separates out a sum of squares with a single degree of freedom from each of the 2^P?P?1 interactions in a P-factor experiment.     

Phase response and entrainment: Model computations on their relation using Wever's oscillator model

Abstract

Enright's theory, which explains entrainment as periodically repeated phase response, is applied to Wever's self‐sustained oscillation model of are circadian rhythm and tested by computer simulation. Ranges of phase response and entrainment are compared and the oscillatory behaviour is shown in the phase diagram for the cases of phase response and entrainment. It is shown that Enright's theory is not valid for self‐sustained oscillations in general, but it need not necessarily fail in case of the biological circadian rhythm.     

Catheter Ablation of Hemodynamically Unstable Ventricular Tachycardia in a Patient with Dextro - Transposition of the Great Arteries and Mustard's Repair

Introduction

A patient with D-TGA and surgical repair (Mustard''s procedure) presented with appropriate ICD shocks due to monomorphic ventricular tachycardia, refractory to antiarrhythmic medications.

Methods and Results

The patient underwent an electrophysiological study and catheter ablation for the VT. Substrate and pace mapping techniques, with the help of an electroanatomical mapping system, was used to localize and ablate the tachycardia successfully.

Conclusions

In patients with D-TGA and Mustard''s repair, scar tissue resulting from VSD repair can act as a substrate for recurrent VT. Catheter ablation of VT is useful in management of VT that occurs despite antiarrhythmic therapy and/or when it is unstable.