结直肠癌血清肿瘤标记物液相芯片制备条件的优化及在CEA抗原检测中的初步应用

液相芯片技术由于其高通量,灵敏度高,信噪比高,液相条件下反应,操作简便,耗时短等优点,已被美国FDA批准成为临床的检测手段。本文主要介绍了结直肠癌血清肿瘤标记物液相芯片制备条件的优化及其在CEA抗原检测中的初步应用。本研究首先将CEA抗原的捕获抗体与微球载体进行偶联,制备液相芯片,然后对影响反应的微球与抗原的反应时间,生物素化检测抗体的浓度及avidin-PE荧光染料的反应浓度等因素进行正交设计,确定出最优的反应条件;用该液相芯片反应体系检测55例临床样本,与ELISA试剂盒检测结果相比：在同样的样本浓度范围内,两者的检测结果基本一致,但液相芯片检测的浓度范围更大而且液相芯片可将多种肿瘤标记物在一个反应进行检测,节省检测的时间和人力。     

宁乡猪数量性状遗传规律的研究

数量性状遗传参数有其相对稳定的一面, 但可因样本含量不同及估测方法不同而有很大 差异。表型参数也可受环境条件、样本含量等 因素影响而有变化。本文根据扩大了的样本含 量和改进了的方法,对宁乡猪生长发育性状的 遗传规律进行了研究。     

宁乡猪数量性状遗传规律的研究 Ⅲ.生长发育性状

数量性状遗传参数有其相对稳定的一面,但可因样本含量不同及估测方法不同而有很大差异。表型参数也可受环境条件、样本含量等因素影响而有变化。本文根据扩大了的样本含量和改进了的方法,对宁乡猪生长发育性状的遗传规律进行了研究。     

水杨酸对大叶黄杨茎抗寒性和电阻抗图谱参数的影响

在抗寒锻炼前,对当年生大叶黄杨(Euonymus japonicus)扦插苗喷施不同浓度水杨酸,用电阻抗图谱(EIS)法和电导(EL)法估测茎的抗寒性,以探明抗寒锻炼期间水杨酸对大叶黄杨抗寒性和电阻抗图谱参数的影响,找到适合不经冷冻处理估测大叶黄杨茎抗寒性和经冷冻处理后测定其抗寒性的EIS参数。结果表明,水杨酸处理能够提高大叶黄杨茎的抗寒性,最适浓度为5.0mmol.L-1;不经冷冻处理茎的EIS参数电阻率r和r1、胞外电阻率re、胞内电阻率ri、弛豫时间τ、弛豫时间分布系数ψ与EL法测定的抗寒性有较高的相关性(r=0.70~0.87),说明不经冷冻处理样本用以上参数估测大叶黄杨茎抗寒性是可行的,r1为最佳参数;冷冻处理后茎的re、τ、ri求得的抗寒性与EL法测定的抗寒性有较高的相关性(r=0.85~0.94),说明冷冻处理后re、τ、ri可以作为测定大叶黄杨茎抗寒性的参数,re为最佳参数。     

影响数量性状遗传参数估测的两个因素

以家蚕试验数据为例,讨论了基因型与环境的互作效应以及小样本数据对数量性状遗传参数的影响。结果指出,对于存在基因型与环境互作效应的性状,应采用多五限竟的试验设计来估测遗传参数,对于遗传力较低的性状,应采用较大的样本来估测遗传参数,这样才能得到准确的结论。     

用空间直观模型是否足以从斑块占据性资料中推断集合种群的动态过程?

在集合种群的研究中,经常要根据空间占据性数据应用斑块模型来推断种群的动态过程,在保护生物学应用中,斑块占据性模型的参数估测对于阐释集合种群动态和预测种群对生境破坏的反应极为重要。我们探讨了一种广泛应用的空间直观模型——率函数模型(Incidence function model)中参数估测的不确定性问题,通过构建由50个斑块组成的网络和两个假想的已知参数的集合种群,应用模拟模型产生集合种群随时间变化的斑块占据性数据系列：即快照(snapshot)。然后,根据这些快照,应用率函数模型和最大似然法估测种群动态参数。此外,我们还给出了传统的率函数模型的一个变形,这个变形包含了目标区效应(Target area effect)：即一个斑块的占据概率不但取决于空间隔离度,也取决于斑块本身面积的大小。结果表明：根据同一个集合种群不同的快照所估测的参数可以有很大差异,一个快照得出的参数提示的是占据性强但存活率低的集合种群,而另一个快照可能反映的是一个占据性弱但存活率高的集合种群。应用传统的率函数模型于一个包含了目标区效应的集合种群,导致斑块大小相关的灭绝率参数估测的正偏差。因此,仅根据一个快照的空间占据性数据来推测集合种群的过程有很大的不确定性[动物学报49(6)：787～794,2003]。     

捕食性昆虫的功能反应方程及其参数的估算

昆虫的功能反应是指每头捕食者在一定时间内的捕食量对猎物密度变化的反应。该文介绍描述这种功能反应的圆盘方程 (Ⅱ型 )的由来及其参数的估测方法 ,简要讨论了影响昆虫功能反应测定的主要因素。     

基于支持向量回归的棉铃虫蛹发育历期估测

温度与发育速率关系模拟是昆虫学研究的一个重要内容, 传统基于经验风险最小的非线性参数模型(Logan模型、Lactin模型和王氏模型)存在诸多弊端。本文基于结构风险最小的改进支持向量回归（SVR）研究温度与棉铃虫Helicoverpa armigera蛹发育历期关系。结果表明: 与传统非线性模型相比, SVR模型性能优异; 基于全部92个样本, SVR模型拟合和留一法预测的决定系数R²分别为0.998和0.996, 估测的蛹期三基点温度更可信。从全部样本中依温度均匀选取部分样本实施独立预测, 当训练集为20个样本时, SVR模型独立预测的R²为0.981, 优于传统非线性模型中独立预测最佳的Lactin模型（R²=0.958）; 当训练集进一步减少到12个样本时, SVR模型的R²仅降低到0.964, 而传统非线性模型均已不适用。结果提示SVR模型在小样本情况下较传统非线性模型优势明显, 在昆虫发育历期估测建模中有应用前景。     

成都白鸡某些性状遗传力的几种估测方法的比较

性状遗传力是进行选种、育种工作不可缺 少的遗传参数。有关鸡的经济行状遗传力,国 外已有许多研究,而国内这方面的报道较少。由 于不同品种同一性状的遗传力不尽相同,因而 国外估测的有关性状遗传力只能供我们参考。 为使成都白鸡今后的选育工作更为科学可靠, 有必要正确估测成都白鸡某些主要经济性状的 遗传力。关于估测性状遗传力的方法,许多学 者作了介绍。这些方法大体可归纳为相关分析 和方差分析两类。相关分析是度量亲缘间的相 似性。方差分析是估测遗传方差在总的表型方 差中所占的比分。度量同胞间的组内相关分析 方法实际上也是一种方差分析。本研究的目的 在于估测成都白鸡某些经济性状的遗传力,比 较使用子亲相关、子亲回归、半同胞相关、全同 胞相关和实际选择反应估测这些性状遗传力的 差别,讨论估测这些性状遗传力的可行方法。     

两种萝芙木生物量分配与估测模型研究

采用样本全收获法测量催吐萝芙木（Rauvolfia vomitoria）和萝芙木（Rauvolfia verticillata）的生物量,比较它们的生长特性及生物量分配,同时以基径（d）和株高（h）的组合d^2h为变量与各器官以及单株总生物量进行估测模型的建立。结果表明,两个种生物量间差异非常大,前者明显高于后者。在各自生物量构成中,茎所占的比例最高,为60％左右;而主要药用部位根只占27％左右。所建立的模型中除萝芙木叶以外,其余的判定系数R^2都较高,模型具有一定的适用性,所建立的估测模型可应用于这两个萝芙木种的幼龄植株生物量估测。     

The Influence of Mark-Recapture Sampling Effort on Estimates of Rock Lobster Survival

Five annual capture-mark-recapture surveys on Jasus edwardsii were used to evaluate the effect of sample size and fishing effort on the precision of estimated survival probability. Datasets of different numbers of individual lobsters (ranging from 200 to 1,000 lobsters) were created by random subsampling from each annual survey. This process of random subsampling was also used to create 12 datasets of different levels of effort based on three levels of the number of traps (15, 30 and 50 traps per day) and four levels of the number of sampling-days (2, 4, 6 and 7 days). The most parsimonious Cormack-Jolly-Seber (CJS) model for estimating survival probability shifted from a constant model towards sex-dependent models with increasing sample size and effort. A sample of 500 lobsters or 50 traps used on four consecutive sampling-days was required for obtaining precise survival estimations for males and females, separately. Reduced sampling effort of 30 traps over four sampling days was sufficient if a survival estimate for both sexes combined was sufficient for management of the fishery.     

Using Inverse Probability Bootstrap Sampling to Eliminate Sample Induced Bias in Model Based Analysis of Unequal Probability Samples

In ecology, as in other research fields, efficient sampling for population estimation often drives sample designs toward unequal probability sampling, such as in stratified sampling. Design based statistical analysis tools are appropriate for seamless integration of sample design into the statistical analysis. However, it is also common and necessary, after a sampling design has been implemented, to use datasets to address questions that, in many cases, were not considered during the sampling design phase. Questions may arise requiring the use of model based statistical tools such as multiple regression, quantile regression, or regression tree analysis. However, such model based tools may require, for ensuring unbiased estimation, data from simple random samples, which can be problematic when analyzing data from unequal probability designs. Despite numerous method specific tools available to properly account for sampling design, too often in the analysis of ecological data, sample design is ignored and consequences are not properly considered. We demonstrate here that violation of this assumption can lead to biased parameter estimates in ecological research. In addition, to the set of tools available for researchers to properly account for sampling design in model based analysis, we introduce inverse probability bootstrapping (IPB). Inverse probability bootstrapping is an easily implemented method for obtaining equal probability re-samples from a probability sample, from which unbiased model based estimates can be made. We demonstrate the potential for bias in model-based analyses that ignore sample inclusion probabilities, and the effectiveness of IPB sampling in eliminating this bias, using both simulated and actual ecological data. For illustration, we considered three model based analysis tools—linear regression, quantile regression, and boosted regression tree analysis. In all models, using both simulated and actual ecological data, we found inferences to be biased, sometimes severely, when sample inclusion probabilities were ignored, while IPB sampling effectively produced unbiased parameter estimates.     

Estimating multiple time‐fixed treatment effects using a semi‐Bayes semiparametric marginal structural Cox proportional hazards regression model

Marginal structural models for time‐fixed treatments fit using inverse‐probability weighted estimating equations are increasingly popular. Nonetheless, the resulting effect estimates are subject to finite‐sample bias when data are sparse, as is typical for large‐sample procedures. Here we propose a semi‐Bayes estimation approach which penalizes or shrinks the estimated model parameters to improve finite‐sample performance. This approach uses simple symmetric data‐augmentation priors. Limited simulation experiments indicate that the proposed approach reduces finite‐sample bias and improves confidence‐interval coverage when the true values lie within the central “hill” of the prior distribution. We illustrate the approach with data from a nonexperimental study of HIV treatments.     

A self-similarity model for the occupancy frequency distribution

The shapes of interspecific range-size distributions at scales finer than the geographic range are highly variable. However, no numerical model has been developed as a basis for understanding this variation. Using self-similarity conditions, we present an occupancy probability transition (OPT) model to investigate the effect of sampling scale (i.e. sample grain) and species saturation (strongly positively correlated with the fractal dimension) on the shape of occupancy frequency distributions (fine scale expression of range-size distributions). In accordance with empirical observations, the model showed that core-modes are likely to be rare in occupancy frequency distributions. The modal occupancy shifted from core to satellite with an increase in sample grain (from coarse scale to fine scale) at a linear rate after log-transformation of occupancy. Saturation coefficients above a particular threshold generated multimodality. Bimodal distributions arose from a combination of different occupancy probability distributions (OPDs), with species-specific saturation coefficients generating occupancy frequency distributions of the shape commonly observed empirically, i.e. bimodal with a dominant satellite mode. This is a consequence of the statistical properties of the OPD, and is also largely insensitive to species richness. The OPT model thus provides a null model for the shape of occupancy frequency distributions. Furthermore, it demonstrates that the sample grain of a study, sampling adequacy (based on a linear sampling assumption) and the distribution of species saturation coefficients in a community are together largely able to explain the patterns observed in empirical occupancy frequency distributions.     

Computer-assisted pattern recognition model for the identification of slowly growing mycobacteria including Mycobacterium tuberculosis.

We present a computerized pattern recognition model used to speciate mycobacteria based on their restriction fragment length polymorphism (RFLP) banding patterns. DNA fragment migration distances were normalized to minimize lane-to-lane variability of band location both within and among gels through the inclusion of two internal size standards in each sample. The computer model used a library of normalized RFLP patterns derived from samples of known origin to create a probability matrix which was then used to classify the RFLP patterns from samples of unknown origin. The probability matrix contained the proportion of bands that fell within defined migration distance windows for each species in the library of reference samples. These proportions were then used to compute the likelihood that the banding pattern of an unknown sample corresponded to that of each species represented in the probability matrix. As a test of this process, we developed an automated, computer-assisted model for the identification of Mycobacterium species based on their normalized RFLP banding patterns. The probability matrix contained values for the M. tuberculosis complex, M. avium, M. intracellulare, M. kansasii and M. gordonae species. Thirty-nine independent strains of known origin, not included in the probability matrix, were used to test the accuracy of the method in classifying unknowns: 37 of 39 (94.9%) were classified correctly. An additional set of 16 strains of known origin representing species not included in the model were tested to gauge the robustness of the probability matrix. Every sample was correctly identified as an outlier, i.e. a member of a species not included in the original matrix.(ABSTRACT TRUNCATED AT 250 WORDS)     

The combined effect of incubation temperature, pH and sorbic acid on the probability of growth of non-proteolytic, type B Clostridium botulinum

It has been reported that non-proteolytic strains of Clostridium botulinum will grow at 3.3 degrees C, and they are therefore of concern in relation to certain chilled foods. The effects of combinations of inhibitory factors may be used to reduce the risk of growth of these bacteria in foods. The combined effect of pH values between 4.8 and 7.0, temperatures between 6 degrees and 30 degrees C, and sorbic acid concentrations up to 2270 mg/l on the probability of growth from a single spore of non-proteolytic, type B strains in a culture medium has been determined. A mathematical model has been developed that enables the effect of varying combinations of these factors on the probability of growth of non-proteolytic, type B Cl. botulinum to be predicted.     

Allele frequencies after a bottleneck

The effect that a recent change in population size (a “bottleneck”) has on the genetic composition of a random sample of genes is studied. The population is assumed to evolve as in the Wright-Fisher model with infinitely many neutral alleles. Simple analytic formulas are found for such quantities as the probability distribution and moments of the total number of alleles, the allelic “frequency spectrum,” and the homozygosity, in the sample. Numerical examples are given which compare these results with those obtained previously by a variety of other methods.     

Size is not everything: a meta‐analysis of geographic variation in microscopic eukaryotes

Aim To analyse how important body size is for geographic variation in microscopic organisms in the marine environment and thereby determine the validity of the ‘everything is everywhere’ hypothesis. Location Marine environments, globally. Methods Studies on geographic variation in all marine eukaryotes smaller than 1 mm and all marine copepods were compiled from the literature and incorporated in multiple binomial regressions to analyse the effect of body size, lifestyle, environmental isolation and taxonomic affinity on the probability of different regions being reciprocally monophyletic. Sample size was also analysed, because a negative relationship between sample size and probability of being reciprocally monophyletic would indicate biases due to undersampling in the original studies. Separate analyses were performed for three potential types of barriers to gene flow for marine organisms (the water barrier of the middle of the oceans, the temperature barrier of the equator, and the land barrier of the continents). Results Environmental isolation was the only variable in the best‐fitting model for the probability of populations from each side of an ocean being reciprocally monophyletic. The estimated importance of body size was quite large and the lack of this variable in the best‐fitting model may be a power issue due to the small sample size (n= 40). Both environmental isolation and body size were important for the probability of monophyletic populations in different hemispheres. The analysis of isolation between different oceans did not produce clear results. The relationship between sample intensity and probability of being reciprocally monophyletic was positive for the isolation between different oceans and non‐existent for the two other analyses. Main conclusions The results showed that body size was an important factor governing the potential for geographic variation but not the only important factor by far. These results clearly weaken the ‘everything is everywhere’ hypothesis as they showed that microscopic organisms may have geographic variation, albeit to a lesser degree than larger organisms.     

The in vitro effect of gossypol and its interaction with salts on conidial germination and viability of Fusarium oxysporum sp. vasinfectum isolates

AIMS: To assess the effect of different concentrations of gossypol (0, 2, 4, 10 and 20 mg l(-1)) in combination with NaCl and Na(2)SO(4) (20 mS cm(-1)) on the conidial germination and viability of Fusarium oxysporum f.sp. vasinfectum (Fov). METHODS AND RESULTS: A multinomial logistic model was developed to estimate the germination probability of Fov. The inhibitory effect was markedly evident at the two highest concentrations of gossypol; it varied among the isolates tested and with time, and it was attenuated by the presence of sodium salts. The inhibition was temporary as the germination probability increased after 8 h. Fluorescent staining revealed that gossypol either killed the conidia or retarded the elongation of the germ tubes. CONCLUSION: Fov showed the ability to overcome gossypol inhibition over time, and the inhibitory effect is reduced under saline conditions. Differential responses among Fov isolates to the presence of gossypol suggest that gossypol tolerance is genetically determined in the pathogen. SIGNIFICANCE AND IMPACT OF THE STUDY: This study suggests that selecting for high plant gossypol cultivars would have minimal effect on the overall Fov resistance of cotton. A new statistical model was developed to explore the statistical significance of plant-pathogen interactions.