Effects of long-term dietary restriction on body temperature are modified with increasing age

Effects of long-term dietary restriction on body temperature and its circadian changes were investigated in 3.5- and 14.5-month-old male Long-Evans rats. Animals were either fed and libitum or kept on a restricted diet for 8 weeks. Purina Lab Chow was constantly available to the ad libitum-fed groups, while half portions of their daily food consumption were given to age-matched diet-restricted groups every day. A highly significant lowering of body temperature in middle-aged diet-restricted (MR) rats was not observed until their food intake had been restricted for 5 weeks compared with that of the middle-aged ad libitum-fed (MA) group as well as that of the young diet-restricted (YR) rats. Eight weeks after diet restriction, both the circadian pattern of body temperature and its diurnal peak-trough difference remained almost unchanged in all four groups, while the average body temperature of MR rats was greatly lower than that of the YR group and that of MA animals. No significant difference in average body temperature was found between the young ad libitum-fed (YA) rats and the MA group. These data suggest that the average body temperature and its circadian changes in ad libitum-fed rats, at least before the age of 14.5 months, is not age-related, while the effect of dietary restriction on body temperature may be modified with increasing age.     

Optimal data collection for correlated mutation analysis

The main objective of correlated mutation analysis (CMA) is to predict intraprotein residue-residue interactions from sequence alone. Despite considerable progress in algorithms and computer capabilities, the performance of CMA methods remains quite low. Here we examine whether, and to what extent, the quality of CMA methods depends on the sequences that are included in the multiple sequence alignment (MSA). The results revealed a strong correlation between the number of homologs in an MSA and CMA prediction strength. Furthermore, many of the current methods include only orthologs in the MSA, we found that it is beneficial to include both orthologs and paralogs in the MSA. Remarkably, even remote homologs contribute to the improved accuracy. Based on our findings we put forward an automated data collection procedure, with a minimal coverage of 50% between the query protein and its orthologs and paralogs. This procedure improves accuracy even in the absence of manual curation. In this era of massive sequencing and exploding sequence data, our results suggest that correlated mutation-based methods have not reached their inherent performance limitations and that the role of CMA in structural biology is far from being fulfilled.     

植物根呼吸对升温的响应

植物根呼吸碳释放量高达18Pg／a,约为全球化石燃料燃烧碳排放量（6．5Pg／a）的2．8倍。了解根呼吸对升温的响应对于构建陆地生态系统碳动态模型、评价地下碳库碳收支具有重要作用。短期升温能明显提高根呼吸速率,但在近乎恒定的温度梯度下,根呼吸速率可能逐渐恢复到温度变化前的水平。根呼吸的温度敏感性与植物种和测定的温度范围有关,其Q10值介于1．1～10之间。在野外条件下,根呼吸的温度敏感性还会受到土壤湿度、养分状况、呼吸底物有效性、太阳辐射、光合产物的地下分配模式和天气状况等影响。通常根呼吸的温度敏感性比土壤微生物呼吸的温度敏感性高,但室内控制温度下和野外环割（girdling）实验中并未观测到类似现象。根呼吸是否具有温度适应性仍是一个尚未解决的重大科学问题。有关根呼吸对升温的适应机理仍不清楚,可能是碳循环研究存在不确定性的重要来源。今后的研究方向应集中在以下几方面：（1）深入探讨根呼吸的温度适应性;（2）扩大对成年植物种的研究;（3）扩大对环境因子交互影响和模拟研究;（4）扩大对植物根呼吸测定和升温新技术的研究。     

Daily patterns of nest visits are correlated with ambient temperature in the Northern Wheatear

The diurnal pattern of foraging behaviour in birds is commonly linked to the risk of starvation and predation. During the breeding season, when offspring place additional demands on the quantity of food adults need to collect, diurnal foraging patterns may be influenced to a greater extent by food availability because adults need to balance starvation–predation risks not only for themselves but also their offspring. We used data-loggers to measure diurnal variation in rates of nest visits to 7- to 10-day-old nestlings of the insectivorous Northern Wheatear Oenanthe oenanthe in Swedish farmland habitat. Adults provisioned the nestlings with food for an average 19.5 h each day (n = 11 pairs), with visitation rates sharply increasing during the morning, remaining relatively stable between 0800 and 1700 hours, and then declining in the evening. This pattern is similar to daily temperature fluctuations and is consistent with the hypothesis that nest visit rates are a function of temperature-dependent prey availability. Higher rates of nest visits on warm days support this correlation between temperature and offspring feeding. However, without data on the rate of self-feeding by adults it is difficult to distinguish between patterns of nest visits being driven by food availability, or starvation–predation constraints being imposed on the parents; thus, future studies of patterns of offspring feeding should collect data on the self-feeding behaviour of the adults.     

Marginal analysis of correlated failure time data with informative cluster sizes

We consider modeling correlated survival data when cluster sizes may be informative to the outcome of interest based on a within-cluster resampling (WCR) approach and a weighted score function (WSF) method. We derive the large sample properties for the WCR estimators under the Cox proportional hazards model. We establish consistency and asymptotic normality of the regression coefficient estimators, and the weak convergence property of the estimated baseline cumulative hazard function. The WSF method is to incorporate the inverse of cluster sizes as weights in the score function. We conduct simulation studies to assess and compare the finite-sample behaviors of the estimators and apply the proposed methods to a dental study as an illustration.     

Competing risks analysis of correlated failure time data

Summary .   We develop methods for competing risks analysis when individual event times are correlated within clusters. Clustering arises naturally in clinical genetic studies and other settings. We develop a nonparametric estimator of cumulative incidence, and obtain robust pointwise standard errors that account for within-cluster correlation. We modify the two-sample Gray and Pepe–Mori tests for correlated competing risks data, and propose a simple two-sample test of the difference in cumulative incidence at a landmark time. In simulation studies, our estimators are asymptotically unbiased, and the modified test statistics control the type I error. The power of the respective two-sample tests is differentially sensitive to the degree of correlation; the optimal test depends on the alternative hypothesis of interest and the within-cluster correlation. For purposes of illustration, we apply our methods to a family-based prospective cohort study of hereditary breast/ovarian cancer families. For women with BRCA1 mutations, we estimate the cumulative incidence of breast cancer in the presence of competing mortality from ovarian cancer, accounting for significant within-family correlation.     

Bayesian hierarchical spatially correlated functional data analysis with application to colon carcinogenesis

Summary .   In this article, we present new methods to analyze data from an experiment using rodent models to investigate the role of p27, an important cell-cycle mediator, in early colon carcinogenesis. The responses modeled here are essentially functions nested within a two-stage hierarchy. Standard functional data analysis literature focuses on a single stage of hierarchy and conditionally independent functions with near white noise. However, in our experiment, there is substantial biological motivation for the existence of spatial correlation among the functions, which arise from the locations of biological structures called colonic crypts: this possible functional correlation is a phenomenon we term crypt signaling . Thus, as a point of general methodology, we require an analysis that allows for functions to be correlated at the deepest level of the hierarchy. Our approach is fully Bayesian and uses Markov chain Monte Carlo methods for inference and estimation. Analysis of this data set gives new insights into the structure of p27 expression in early colon carcinogenesis and suggests the existence of significant crypt signaling. Our methodology uses regression splines, and because of the hierarchical nature of the data, dimension reduction of the covariance matrix of the spline coefficients is important: we suggest simple methods for overcoming this problem.     

Specific peroxidase isoenzymes are correlated with organogenesis

We have examined isoperoxidase patterns obtained from buffer-, salt-, and enzyme-extractable fractions and correlated them with histological changes in tobacco (Nicotiana tabacum L., cv Wisc. 38) `epidermal' explants induced to produce either callus, vegetative buds, or floral buds. By utilizing a combination of extraction and electrophoretic procedures different from any hitherto used for this kind of investigation, we were able to resolve 47 isoperoxidases distributed between the three types of fractions. The majority of these isoperoxidases were common to all explants regardless of their developmental fate. Correspondingly, a number of histological changes were observed in all explants (e.g. the initiation of cell division by day 2, lignin deposition by day 4, and the formation of clustered tracheary elements by day 8). We have made correlations between 25 isoperoxidases and specific developmental events based on the time when certain isoperoxidases were detected relative to observed histological changes: 3 were correlated with desuppressed/sustained cell division, 3 to 6 with lignification/tracheary element maturation, 7 with callus formation, 1 with localized suppression of growth, 3 with determinate axial organization, 4 with leaf development, and 1 with stamen development. These results suggest that a continued investigation using this system could lead to a better understanding of the role of specific isoperoxidases in different developmental processes.     

Joint regression analysis of correlated data using Gaussian copulas

Summary .  This article concerns a new joint modeling approach for correlated data analysis. Utilizing Gaussian copulas, we present a unified and flexible machinery to integrate separate one-dimensional generalized linear models (GLMs) into a joint regression analysis of continuous, discrete, and mixed correlated outcomes. This essentially leads to a multivariate analogue of the univariate GLM theory and hence an efficiency gain in the estimation of regression coefficients. The availability of joint probability models enables us to develop a full maximum likelihood inference. Numerical illustrations are focused on regression models for discrete correlated data, including multidimensional logistic regression models and a joint model for mixed normal and binary outcomes. In the simulation studies, the proposed copula-based joint model is compared to the popular generalized estimating equations, which is a moment-based estimating equation method to join univariate GLMs. Two real-world data examples are used in the illustration.     

Rates of climatic niche evolution are correlated with species richness in a large and ecologically diverse radiation of songbirds

By employing a recently inferred phylogeny and museum occurrence records, we examine the relationship of ecological niche evolution to diversification in the largest family of songbirds, the tanagers (Thraupidae). We test whether differences in species numbers in the major clades of tanagers can be explained by differences in rate of climatic niche evolution. We develop a methodological pipeline to process and filter occurrence records. We find that, of the ecological variables examined, clade richness is higher in clades with higher climatic niche rate, and that this rate is also greater for clades that occupy a greater extent of climatic space. Additionally, we find that more speciose clades contain species with narrower niche breadths, suggesting that clades in which species are more successful at diversifying across climatic gradients have greater potential for speciation or are more buffered from the risk of extinction.     

Deconvolution of single photon counting data with a reference method and global analysis

A method based on quenched references and global analysis was used to deconvolute timeresolved single photon counting data. The results from both computer simulated data and real experiments showed that highly accurate and reliable deconvolutions were possible. Fluorescence lifetimes and Stern-Volmer quenching constants for quenching with NaI were determined for the reference substances para-terphenyl, PPO (2,5-diphenyloxazol), POPOP (1,4-bis-(5-phenyl-2-oxazolyl)-benzene), and dimethyl-POPOP, all in ethanol. The fluorescence from a mixture of POPOP, anthracene, and diphenylanthracene in ethanol at different wavelengths was successfully resolved into the known relative contributions from the species at each wavelength. Fluorescence intensity decays of tryptophan in solution were studied at different wavelengths and globally analyzed with the method. Also, fluorescence anisotropy described by isotropic and anisotropic rotations in homogeneous and heterogeneous emitting systems were simulated and successfully deconvoluted. The method was applied to real fluorescence anisotropy data of diphenylanthracene and POPOP in paraffin oil, as well as to data from experiments on the blue copper-containing protein stellacyanin and its apo-form. In these cases, the method both corrected for errors due to, for example, the wavelength-dependent transit-times in the photomultiplier, and realized global deconvolutions of the total, parallel, and perpendicular components of the fluorescence. General algorithms for arbitrary fluorescence impulse responses are given.A preliminary account of this work was presented at the NATO ASI in Acireale, Italy (Löfroth 1985a, in press)     

Direct analysis of quantal radiation response data

A direct analysis is proposed for quantal (all-or-nothing) responses to fractionated radiation and endpoint-dilution assays of cell survival. As opposed to two-step methods such as the reciprocal-dose technique, in which ED50 values are first estimated for different fractionation schemes and then fit (as reciprocals) against dose per fraction, all raw data are included in a single maximum-likelihood treatment. The method accommodates variations such as short-interval fractionation regimens designed to determine tissue repair kinetics, tissue response to continuous exposures, and data obtained using endpoint-dilution assays of cell survival after fractionated doses. Monte-Carlo techniques were used to compare the direct and reciprocal-dose methods for analysis of small-scale and large-scale studies of response to fractionated doses. Both methods tended toward biased estimates in the analysis of the small-scale (3 fraction numbers) studies. The alpha/beta ratios showed less scatter when estimated by the direct method. Most important, the 95 per cent confidence intervals determined by the direct method were more appropriate than those determined by reciprocal-dose analysis, for which 18 per cent (small-scale study) or 8 per cent (large-scale study) of the confidence intervals did not include the 'true' value of alpha/beta.     

Estimation with correlated censored survival data with missing covariates

Incomplete covariate data are a common occurrence in studies in which the outcome is survival time. Further, studies in the health sciences often give rise to correlated, possibly censored, survival data. With no missing covariate data, if the marginal distributions of the correlated survival times follow a given parametric model, then the estimates using the maximum likelihood estimating equations, naively treating the correlated survival times as independent, give consistent estimates of the relative risk parameters Lipsitz et al. 1994 50, 842-846. Now, suppose that some observations within a cluster have some missing covariates. We show in this paper that if one naively treats observations within a cluster as independent, that one can still use the maximum likelihood estimating equations to obtain consistent estimates of the relative risk parameters. This method requires the estimation of the parameters of the distribution of the covariates. We present results from a clinical trial Lipsitz and Ibrahim (1996b) 2, 5-14 with five covariates, four of which have some missing values. In the trial, the clusters are the hospitals in which the patients were treated.     

Long-lived mutagenic radicals induced in mammalian cells by ionizing radiation are mainly localized to proteins

We have provided evidence that long-lived radicals, produced by ionizing radiation, are highly mutagenic and transforming in mammalian cells. Long-lived radicals are scavenged effectively by vitamin C or by epigallocatechin-3-O-gallate (EGCG). Long-lived radicals are not involved in lethality or in the induction of chromosome aberrations. We now report the results of experiments that define the relative amounts of long-lived radicals in DNA and proteins and identify the major protein radicals as sulfinyl radicals (R-CH2-S-O*). To make these assignments, yields of long-lived radicals in gamma-irradiated salmon sperm DNA and albumin were compared by ESR. ESR spectra of long-lived radicals produced in irradiated Syrian hamster embryo (SHE) cells were analyzed precisely and compared with ESR parameters obtained by density functional theory calculations. Long-lived radicals yields of 99.8% were produced in proteins. We also identified a new type of long-lived radical as H-added phenylalanine radicals. While our evidence does not rule out the possibility of important biological consequences of the low-level long-lived radicals created by radiation, it implicates radicals in proteins as playing a key role in genetic effects of ionizing radiation. We suggest that these novel radicals, wherever they reside, need to be considered in explanations of biological sequela of radiation.