A nondestructive method for the measurement of radioactive 14CO2 in blood

A method for estimation of 14CO2 present in blood and tissular samples is described. It is basically based on the introduction of large amounts of a gas mixture (95% O2, 5% CO2) in the samples which serves to remove the CO2 label by gas dilution. The gas phase is later captured in scintillation vials containing an organic-soluble base that retains the carbon label. The results obtained by means of this methodology show much better recoveries for blood samples than those obtained when the classic acid-diffusion method is used. In addition, it is a very fast procedure which does not alter the pH or protein integrity of the biological sample.     

Finite Sample Properties of the Maximum Likelihood Estimator and of Likelihood Ratio Tests in Hidden Markov Models

Hidden Markov models were successfully applied in various fields of time series analysis, especially for analyzing ion channel recordings. The maximum likelihood estimator (MLE) has recently been proven to be asymptotically normally distributed. Here, we investigate finite sample properties of the MLE and of different types of likelihood ratio tests (LRTs) by means of simulation studies. The MLE is shown to reach the asymptotic behavior within sample sizes that are common for various applications. Thus, reliable estimates and confidence intervals can be obtained. We give an approximative scaling function for the estimation error for finite samples, and investigate the power of different LRTs suitable for applications to ion channels, including tests for superimposed hidden Markov processes. Our results are applied to physiological sodium channel data.     

Empirical Bayes estimation of gene-specific effects in micro-array research

Micro-array technology allows investigators the opportunity to measure expression levels of thousands of genes simultaneously. However, investigators are also faced with the challenge of simultaneous estimation of gene expression differences for thousands of genes with very small sample sizes. Traditional estimators of differences between treatment means (ordinary least squares estimators or OLS) are not the best estimators if interest is in estimation of gene expression differences for an ensemble of genes. In the case that gene expression differences are regarded as exchangeable samples from a common population, estimators are available that result in much smaller average mean-square error across the population of gene expression difference estimates. We have simulated the application of such an estimator, namely an empirical Bayes (EB) estimator of random effects in a hierarchical linear model (normal-normal). Simulation results revealed mean-square error as low as 0.05 times the mean-square error of OLS estimators (i.e., the difference between treatment means). We applied the analysis to an example dataset as a demonstration of the shrinkage of EB estimators and of the reduction in mean-square error, i.e., increase in precision, associated with EB estimators in this analysis. The method described here is available in software that is available at .     

A nonparametric mean estimator for judgment poststratified data

Summary .   MacEachern, Stasny, and Wolfe (2004, Biometrics 60 , 207–215) introduced a data collection method, called judgment poststratification (JPS), based on ideas similar to those in ranked set sampling, and proposed methods for mean estimation from JPS samples. In this article, we propose an improvement to their methods, which exploits the fact that the distributions of the judgment poststrata are often stochastically ordered, so as to form a mean estimator using isotonized sample means of the poststrata. This new estimator is strongly consistent with similar asymptotic properties to those in MacEachern et al. (2004) . It is shown to be more efficient for small sample sizes, which appears to be attractive in applications requiring cost efficiency. Further, we extend our method to JPS samples with imprecise ranking or multiple rankers. The performance of the proposed estimators is examined on three data examples through simulation.     

Estimation of total water and fatness from weight and height: inaccurate for lean women

Mellits and Cheek have provided a regression equation which predicts total water, and by extension, fat, from weight and height of women. The equation has been used by many researchers as a convenient means to estimate fat when more complicated body composition estimation techniques are not possible. It is an essential component of evidence provide by Frisch for the critical fat hypothesis. The equation has not been validated on another sample, however, and has a large standard error. I test the Mellits and Cheek equation on five samples of young women, two of which show a normal range of heights and weights. The other three are athletic samples composed of lean women. In the normal samples mean fat percent determined by density (from underwater weighing) is closely approximated by the weight and height equation but not in the lean samples. When measured fat is regressed on estimated fat, correlations are low, and standard errors are high, suggesting that the Mellits and Cheek equation predicts poorly the body fat percentage of individual females. In summary, the Mellits and Cheek equation is moderately useful for the prediction of group means for body composition on samples with normal ranges of height and weight. It does not produce acceptable results on groups selected for extreme leanness or obesity. It is not recommended for fat prediction of individuals.     

生物群落多样性的测度方法VI：与多样性测度中有关的统计问题

物种多样性测度是(群落的)总体参数,它们常常是未知的,需要通过抽样将它们估计出来,因此,必须了解估计量的抽样性质。本文对与一些多样性测度的均值、方差的估计和假设检验以及大、小样本分布等有关的问题作了综述。可以看出大多数多样性测度的抽样性质还不清楚,有些甚至根本就没有研究过。Pielou的合并样方法和刀切法是两个比较通用的方法,用它们可以解决其中的一些问题。但相比之下,刀切法更实用。     

Minimum sampling effort for reliable non-invasive estimations of excretion abundance of Elaphostrongylus cervi L1 in red deer (Cervus elaphus) populations

Faecal surveys are commonly used as non-invasive means to evaluate population abundance of animals as well as comparable indexes of prevalence and intensity of diseases between populations, especially macroparasites. While faecal surveys are among one of the simplest means to perform these evaluations, they are time consuming and labour intensive. The present study evaluated 80 red deer (Cervus elaphus) faecal samples collected in two study sites for the presence and abundance of first-stage larvae of the nematode Elaphostrongylus cervi and established pools of samples for epidemiological analysis. The analysis of 20-30 individual samples would produce a reliable estimate of the 'true' prevalence, and the error of the smaller sample size only doubled that of the 80 reference samples. The analysis of 5 pools of 5 pellet groups each, or of 4 pools of 10 pellet groups each, provided a reliable estimation of the 'true' excretion abundance estimated by the analysis of all 80 samples. These pools comprise a cost-effective and dependable alternative for measuring and obtaining comparable abundances of parasitic faecal excretion stages in red deer populations, which is very valuable for epidemiological and ecological research as well as for management purposes.     

A radio-gas chromatographic method for the determination of 11-oxotestosterone in fish plasma: its use in confirming estimations by radioimmunoassay

A radio-gas chromatographic method has been devised for the estimation of 11-oxotestosterone (17beta-hydroxyandrost-4-ene-3, 11-dione) in fish plasma samples which provides an independent means of validating the radioimmunoassay described earlier. Estimates of the concentration of 11-oxotestosterone in a sample of male rainbow trout plasma by radio-gas chromatography using peak height and peak weight measurements were 6.9 microgram/100 ml and 7.4 microgram/100 ml respectively, in good agreement with that of 7.1 microgram/100 ml determined by radioimmunoassay.     

Graphical exploration of covariate effects on survival data through nonparametric quantile curves

Kaplan-Meier curves provide an effective means of presenting the distributional pattern in a sample of survival data. However, in order to assess the effect of a covariate, a standard scatterplot is often difficult to interpret because of the presence of censored observations. Several authors have proposed a running median as an effective way of indicating the effect of a covariate. This article proposes a form of kernel estimation, employing double smoothing, that can be applied in a simple and efficient manner to construct an estimator of a percentile of the survival distribution as a function of one or two covariates. Permutations and bootstrap samples can be used to construct reference bands that help identify whether particular features of the estimates indicate real features of the underlying curve or whether this may be due simply to random variation. The techniques are illustrated on data from a study of kidney transplant patients.     

Assessing microbial diversity using recent lake sediments and estimations of spatio‐temporal diversity

Aim Recent papers have used large palaeolimnological datasets to reveal the biodiversity patterns of aquatic microorganisms. However, scant attention has been paid to the influence of time on these patterns. Where lake surficial sediment samples are used as integrals of diversity, the time interval of each sample varies according to differences in sediment accumulation rates. This paper aims to test the reliability of using lake surface sediments to measure and to compare microbial diversity when the potential influences of the species–time relationships are taken into account. Location Alpine lakes in Europe. Methods We analysed microorganism (siliceous microalgae) assemblages in three European Alpine lakes using short sediment cores (²¹⁰Pb‐dated) and annual sediment trap samples from 12 UK lakes. The same number of individuals was pooled for each sample 500 times to avoid sampling effort effects and to standardize species diversity estimation. The influence of time on the diversity score was assessed by simulating an increase of time span for surface sediment samples by cumulatively adding in successive sediment core samples (from the most recent to the oldest). We used species richness (S) and the exponential of the bias‐corrected Shannon entropy index (exp(H_b‐c)) to estimate diversity. Results Increasing the time interval represented by a surficial sediment sample did not affect the diversity results. The estimation of diversity was similar for cumulative and non‐cumulative samples. Diversity estimation was only altered in lakes experiencing high community turnover due to strong environmental forcing during the time period spanned by the cumulative sample. Main conclusions The use of surface lake sediments is suitable for estimating the average site diversity of free‐living microorganisms. Diversity is integrated in a single sample and species assemblage composition is derived from microbial communities living in distinct lake microhabitats. Species remains, accumulated in a single sample over several years of environmental variability, represent a diversity integral that captures a spatio‐temporal component equivalent to the γ‐diversity measure.     

模拟计算平行样对流域生物信息流估算的影响

流域生物信息流是流域生态学研究中的重要内容,是流域生态系统中的物质输移和能量输移过程的信息标记,是用eDNA技术调查评估河流水体中物种组成空间特征的基础。估算流域生物信息流是流域生态系统过程研究和eDNA技术调查评估河流水体中物种组成空间特征的关键。在有限的调查采样中,平行样的数量如何影响流域生物信息流的估算,尚待解答。基于随机抽样调查的基本原理,提出假设--采样数量不影响流域生物信息流估算结果的准确度,但会影响其精密度,然后通过问题简化转化和模拟计算,对该假设进行了检验。模拟计算结果显示,随着样点生物信息检出度(平行样数量)的增大,流域生物信息流估算结果会从偏小逐渐靠近流域生物信息流实际值,同时其99.9%置信区间也逐渐集中于流域生物信息流实际值。即样点生物信息检出度(平行样数量)对流域生物信息流估算的准确度和精密度均有影响。在实际调查研究过程中,建议先在所研究区域对平行样数量和样点生物信息检出度的关系进行预评估,然后基于流域生物信息流估算可信度目标在正式实施方案中经济有效地设置平行样,基于多平行样调查结果估算流域生物信息流,再根据各样点生物信息检出状况对流域生物信息流估算结果进行后验评估。     

A Comparison of Robust Estimators in the Presence of Arbitrarily Right Censored Data

Robust estimation of a location parameter is considered when the data from an unknown symmetric population are subject to arbitrary right-censorship. Comparisons are made between various M-estimators, several L-estimators (trimmed means), and the Kaplan-Meier median. Ten sampling distributions, two uniform censoring distributions, and three sample sizes are examined. A Cauchy censoring distribution is also considered when the sample size is equal to twenty for each of the ten sampling distributions. Performance is based on the estimated mean square error.     

Testing the quality of nonadult Bayesian dental age assessment methods to juvenile skeletal remains: the Lisbon collection children and secular trend effects

Age estimation of nonadult skeletons from archaeological or forensic contexts has relied heavily on modern schedules of dental formation developed on samples of children of affluent populations. Although genetic factors have been considered to have had the greatest influence on population differences in dental development, increased interest has been placed on the role of environmental influences, such as differences in socioeconomic status and secular trends. This study evaluates the quality (i.e., accuracy and reliability) of two Bayesian dental age estimation methods to a sample of identified child skeletons from the Lisbon collection (20th century Portugal). The two Bayesian methods are developed on a reference sample of modern children from France, Ivory Coast, Iran, and Morocco. The test sample from Lisbon, compared to the reference sample, is separated by over 50 years of secular trends and comprises a lower socioeconomic segment. The two Bayesian methods show that the Lisbon children are consistently 1-year behind in dental age compared to the modern children of the reference sample. Environmental factors largely explain the differences between dental and chronological age in historic samples of nonadults.     

Effect of sampling scale on the assessment of epiphytic bacterial populations

Bacterial populations on above-ground plant surfaces were estimated at three different biological scales, including leaflet disks, entire leaflets, and whole plants. The influence of sample scale on the estimation of mean bacterial population size per unit and per gram and on the variability among sampling units was quantified at each scale. Populations were highly variable among sampling units at every scale examined, suggesting that there is no optimal scale at which sample variance is reduced. The distribution of population sizes among sample units was sometimes, but not consistently, described by the lognormal. Regardless of the sampling scale, expression of population sizes on a per gram basis may not reduce variance, because population size was not generally a function of sample unit weight within any single sampling scale. In addition, the data show that scaling populations on a per gram basis does not provide a useful means of comparing population estimates from samples taken at different scales. The implications of these results for designing sampling strategies to address specific issues in microbial ecology are discussed. Correspondence to: L.L. Kinkel     

Hematopoietic chimerism monitoring based on STRs: quantitative platform performance on sequential samples.

Hematopoietic stem cell transplantation (HSCT) creates a donor-recipient cellular chimerism in the patient, which is quantitatively assayed from peripheral blood based on STR-DNA. Since chimerism values often vary across a patient's samples, it is important to determine to what extent this variability reflects technical aspects of platform performance. This issue is systematically assessed in the current study for the first time. Using the SGM Plus multiplex PCR kit and ABI platform, the longitudinal performance of STR markers was quantitatively evaluated in two chimeric models with true values, and in patient samples (n >500 marker loci). Computation of percent chimerism for each marker, and mean (sample) percent chimerism, standard deviation, and coefficient of variance was performed by our ChimerTrack utility. In chimeric models with known values, individual markers exhibited an accuracy (observed/true) of 88-98%; replication precision was 92-100% true, with a mean error of 2%. Fragment size calling was greater than 99% accurate and precise. Patient results were comparable for markers, relaive to sample means. One source of technical variability in chimerism estimation was allelic differential amplification efficiency. The latter was influenced by signal amplitude, dye label, marker size, and allelic size interval. It can be concluded that long-term chimeric tracking is routinely feasible using this platform in conjunction with ChimerTrack software. Importantly, mean percent chimerism, for any sample, should closely approximate the true chimeric status, with a technical accuracy of 98%. Guidelines are presented for selecting an optimized marker profile.     

Estimating misclassification error with small samples via bootstrap cross-validation

MOTIVATION: Estimation of misclassification error has received increasing attention in clinical diagnosis and bioinformatics studies, especially in small sample studies with microarray data. Current error estimation methods are not satisfactory because they either have large variability (such as leave-one-out cross-validation) or large bias (such as resubstitution and leave-one-out bootstrap). While small sample size remains one of the key features of costly clinical investigations or of microarray studies that have limited resources in funding, time and tissue materials, accurate and easy-to-implement error estimation methods for small samples are desirable and will be beneficial. RESULTS: A bootstrap cross-validation method is studied. It achieves accurate error estimation through a simple procedure with bootstrap resampling and only costs computer CPU time. Simulation studies and applications to microarray data demonstrate that it performs consistently better than its competitors. This method possesses several attractive properties: (1) it is implemented through a simple procedure; (2) it performs well for small samples with sample size, as small as 16; (3) it is not restricted to any particular classification rules and thus applies to many parametric or non-parametric methods.     

Cementum annulations,age estimation,and demographic dynamics in Mid-Holocene foragers of North India

One of the principal problems facing palaeodemography is age estimation in adult skeletons and the centrist tendency that affects many age estimation methods by artificially increasing the proportion of individuals in the 30–45-year age category. Several recent publications have indicated that cementum annulations are significantly correlated with known age of extraction or death. This study addresses the question of how demographic dynamics are altered for an archaeological sample when cementum-based age estimates are used as opposed to those obtained via conventional macroscopic methods. Age pyramids were constructed and demographic profiles were compared for the early Holocene skeletal population from Damdama (India). The results demonstrate that the use of cementum annulations for age estimation in only a subset of the skeletal sample has a significant impact on the demographic profile with regard to specific parameters such as mean age at death and life expectancy at birth. This confirms the importance of using cementum annulations to refine age estimates in archaeological samples, which, when combined with a fertility-centred approach to demography, can provide new insights into population dynamics in the past.     

A multistep protein lysate array quantification method and its statistical properties

The protein lysate array is an emerging technology for quantifying the protein concentration ratios in multiple biological samples. Statistical inference for a parametric quantification procedure has been inadequately addressed in the literature, mainly because the appropriate asymptotic theory involves a problem with the number of parameters increasing with the number of observations. In this article, we develop a multistep procedure for the Sigmoidal models, ensuring consistent estimation of the concentration levels with full asymptotic efficiency. The results obtained in the article justify inferential procedures based on large sample approximations. Simulation studies and real data analysis are used in the article to illustrate the performance of the proposed method in finite samples. The multistep procedure is convenient to work with asymptotically, and is recommended for its statistical efficiency in protein concentration estimation and improved numerical stability by focusing on optimization of lower-dimensional objective functions.     

利用定量杂交方法对几个人工和环境微生物样品的分析研究

利用真细菌和真核生物两个域特异性探针,初步建立起16SrRNA定量杂交的方法,并对几个人工RNA样品（由提取自S.cerevisiae和P.fluorescens纯培养细胞的RNA按一定比例混合而成）和一个提取自垃圾填埋场渗滤液的RNA样品进行了初步的定量分析。结果表明该方法能从域的水平上对这些样品的组成作较精确的分析,从而在微生物生态学领域具有广泛的应用前景。