Phenotype Switching and Mutations in Random Environments

Cell populations can benefit from changing phenotype when the environment changes. One mechanism for generating these changes is stochastic phenotype switching, whereby cells switch stochastically from one phenotype to another according to genetically determined rates, irrespective of the current environment, with the matching of phenotype to environment then determined by selective pressure. This mechanism has been observed in numerous contexts, but identifying the precise connection between switching rates and environmental changes remains an open problem. Here, we introduce a simple model to study the evolution of phenotype switching in a finite population subject to random environmental shocks. We compare the successes of competing genotypes with different switching rates, and analyze how the optimal switching rates depend on the frequency of environmental changes. If environmental changes are as rare as mutations, then the optimal switching rates mimic the rates of environmental changes. If the environment changes more frequently, then the optimal genotype either maximally favors fitness in the more common environment or has the maximal switching rate to each phenotype. Our results also explain why the optimum is relatively insensitive to fitness in each environment.     

Analysis of Counts involving Random Effects with Applications in Experimental Biology

This paper is concerned with the analysis of count data with special reference to experimental biology and agricultural research. The model considered in this paper is obtained by extending a generalized linear model by introducing random effects with associated variance components on the scale of the linear predictor. Maximum likelihood estimation is discussed and compared with a method which uses a simplified version of the likelihood equations. Two practical applications are used to illustrate the methods.     

Phenotype of patients with gynecomastia

INTRODUCTION: Gynecomastia, a benign enlargement of the breast glandular tissue in men. The aim of the study was to evaluate the phenotype of patients with gynecomastia, in particular antropometric assessment, breast ultrasound examination and hormonal testing, as well as to estimate possible causes of gynecomastia in studied population. MATERIAL AND METHODS: Two hundred-twenty men were enrolled in the study: 126 patients with gynecomastia and 94 healthy volunteers as a control group. Detailed medical examination, breast ultrasound and hormonal assays for T, E2, LH, FSH, SHBG, S-DHEA, PRL and TSH were performed. Calculation of free testosterone concentration was done. RESULTS: The results of clinical and hormonal evaluation enabled to divide the cases into three groups: patients with idiopathic gynecomastia (58 subjects, 46%), with hypogonadism (34 subjects, 27%) and drug-induced or associated with other disorders gynecomastia (34 subjects, 27%). We found that men with gynecomastia, particularly associated with hypogonadism, had significantly higher BMI compared with control group. Ultrasound examination revealed the positive correlation between breast tissue volume and BMI, duration of gynecomastia and estradiol level, while negative correlation with testosterone level. We demonstrated significant differences in LH, T, SHBG, fT and S-DHEA levels between cases and controls. There were no differences in PRL, FSH and TSH levels among groups. Significant elevation of SHBG concentration in all groups of patients, including idiopathic gynecomastia cases, compared with controls, was remarkable. CONCLUSION: Clinical evaluation and hormonal profile can help to classify patient with gynecomastia into one of three groups: idiopathic gynecomastia, associated with hypogonadism, and drug-induced or associated with other diseases. Idiopathic gynecomastia - of unknown etiology is diagnosed in almost half of all cases (46%). We showed that apart from well known hormonal disturbances leading to gynecomastia, like hypogonadism or hyperestrogenism, also subtle hormonal alterations, such as sex hormone binding globuline (SHBG) level elevation may contribute to breast enlargement.     

Population-Based Resequencing of APOA1 in 10,330 Individuals: Spectrum of Genetic Variation,Phenotype, and Comparison with Extreme Phenotype Approach

Rare genetic variants, identified by in-detail resequencing of loci, may contribute to complex traits. We used the apolipoprotein A-I gene (APOA1), a major high-density lipoprotein (HDL) gene, and population-based resequencing to determine the spectrum of genetic variants, the phenotypic characteristics of these variants, and how these results compared with results based on resequencing only the extremes of the apolipoprotein A-I (apoA-I) distribution. First, we resequenced APOA1 in 10,330 population-based participants in the Copenhagen City Heart Study. The spectrum and distribution of genetic variants was determined as a function of the number of individuals resequenced. Second, apoA-I and HDL cholesterol phenotypes were determined for nonsynonymous (NS) and synonymous (S) variants and were validated in the Copenhagen General Population Study (n = 45,239). Third, observed phenotypes were compared with those predicted using an extreme phenotype approach based on the apoA-I distribution. Our results are as follows: First, population-based resequencing of APOA1 identified 40 variants of which only 7 (18%) had minor allele frequencies >1%, and most were exceedingly rare. Second, 0.27% of individuals in the general population were heterozygous for NS variants which were associated with substantial reductions in apoA-I (up to 39 mg/dL) and/or HDL cholesterol (up to 0.9 mmol/L) and, surprisingly, 0.41% were heterozygous for variants predisposing to amyloidosis. NS variants associated with a hazard ratio of 1.72 (1.09–2.70) for myocardial infarction (MI), largely driven by A164S, a variant not associated with apoA-I or HDL cholesterol levels. Third, using the extreme apoA-I phenotype approach, NS variants correctly predicted the apoA-I phenotype observed in the population-based resequencing. However, using the extreme approach, between 79% (screening 0–1^st percentile) and 21% (screening 0–20^th percentile) of all variants were not identified; among these were variants previously associated with amyloidosis. Population-based resequencing of APOA1 identified a majority of rare NS variants associated with reduced apoA-1 and HDL cholesterol levels and/or predisposing to amyloidosis. In addition, NS variants associated with increased risk of MI.     

Lot-Sizing for Substitutable, Production-to-Order Parts with Random Functionality Yields

A variety of manufacturing processes produce parts that have multiple functionalities or uses, that require different degrees of conformity to standards, and with the degree of conformity of an individual part revealed only after it is produced and inspected. If orders for different product grades need to be met in full but demands are upwardly substitutable, we are faced with a complex multiple-lot-sizing problem. We formulate such a decision model and apply it to some structured numerical examples. The implications of inspections and the computation of their expected costs also are discussed.     

Correlations between Planar Random Structures,with an Ecological Application

This paper suggests some characteristics which may help to detect and quantify “correlations” between planar geometrical structures such as point patterns/point processes, fibre systems/fibre processes and region patterns/random sets. Typical examples of “correlations” are mutual attraction or inhibition. Some of the characteristics are related to moment-measures, the definition of the others is similar to that of quantities in the mathematical morphology of MATHERON and SERRA . For all quantities unbiased estimators are given. Also the detection of orientations in random structures is discussed. An ecological example demonstrates the application of the characteristics.     

R-藻红蛋白的结构、功能及其应用

R-藻红蛋白是最重要类型的藻红蛋白,为许多藻类的前级捕光色素蛋白,在光的激发下,能发出桔红色荧光。现对R-藻红蛋白的三维结构与功能的关系、R-藻红蛋白离体的光学活性在肿瘤光动力学治疗(PDT)中作为光敏剂和荧光免疫检测等领域作为荧光探针分子的应用进行综述。     

腈水解酶的来源、结构、作用机制及其应用

综合报道了腈水解酶的来源、结构、作用机制及其工业应用。     

Random Stride Intervals with Memory

The stride interval in normal human gait is not strictly constant, butfluctuates from step to step in a random manner. Herein we show thatcontrary to the traditional assumption of uncorrelated random errors,these fluctuations have long-time memory. However, rather than being amonofractal process as found earlier, there exists a multiplicative timescale that characterizes the process in addition to the fractal dimension.Further, these long-time correlations are interpreted in terms of anallometric control process.     

Crossover Designs with Random Periods

Crossover experiments usually are modelled with fixed treatment, carryover, and period effects while the effects of subjects are assumed to be random. In actual realisations of crossover experiments however periods are quite arbitrary intervals of time, depending on administrative affairs for instance and possibly they are even varying from subject to subject. Modelling these arbitrary periods as random effects either globally for all subjects or individually for each one seems to be more adequate than the assumption of fixed period effects. This paper is concerned with the two treatments, two periods crossover design. It is described that—in spite of the somewhat involved covariance structure—the estimators and tests developed for models with fixed period effects remain valid for models with random effects for periods provided that no treatment X period interaction exists.     

The Method of Random Skewers

Ecological and evolutionary studies are often concerned with the properties of covariance matrices. The method of random skewers (RS method) has been used compare a matrix to an a priori vector or to compare two matrices. The method involves multiplying a matrix by many random vectors drawn from a uniform distribution over all possible vector directions. The comparisons are usually made using the average angle (or cosine) of the response vectors to an a priori vector or to the response vectors corresponding from another matrix. Angles are usually constrained to the interval 0°–90° because the distribution of response vectors is bipolar bimodal. The size of the average angle or cosine depends strongly on the relative sizes of the eigenvalues (especially the first). The distribution of angles between pairs of response vectors from two covariance matrices is more complicated because it depends on the differences in orientation of the eigenvectors and the relative sizes of the eigenvalues of the both matrices. The average absolute value of the angles between these pairs of response vectors depends on the relative sizes of the eigenvalues of the matrices making it difficult to interpret its meaning without knowledge of the eigenvalues and eigenvectors of the two matrices. Thus, it is simpler to just directly compare matrices in terms of these quantities.