A predictive model for freshwater bioassessment (Mondego River,Portugal)

We sampled macroinvertebrates at 75 locations in the Mondego river catchment, Central Portugal, and developed a predictive model for water quality assessment of this basin, based on the Reference Condition Approach. Sampling was done from June to September 2001. Fifty-five sites were identified as “Reference sites” and 20 sites were used as “Test sites” to test the model. At each site we also measured 40 habitat variables to characterize water physics and chemistry, habitat type, land use, stream hydrology and geographic location. Macroinvertebrates were generally identified to species or genus level; a total of 207 taxa were found. By Unweighted Pair Group Method with Arithmetic mean (UPGMA) clustering and analysis of species contribution to similarities percentage (SIMPER), two groups of reference sites were established. Using Discriminant Analysis (stepwise forward), four variables correctly predicted 78% of the reference sites to the appropriate group: stream order, pool quality, substrate quality and current velocity. Test sites’ environmental quality was established from their relative distance to reference sites, in MDS ordination space, using a series of bands (BEAST methodology). The model performed well at upstream sites, but at downstream sites it was compromised by the lack of reference sites. As with the English RIVPACS predictive model, the Mondego model should be continually improved with the addition of new reference sites. The adaptation of the Mondego model methodology to the Water Framework Directive is possible and would consist mainly of the integration of the WFD typology and increasing the number of ellipses that define quality bands. Handling editor: K. Martens     

Method to estimate genotype probabilities at individual loci in farm livestock

Summary A Bayesian method to estimate genotype probabilities at a single locus using information on the individual and all its relatives and their mates has been developed. The method uses data over several generations, can deal with large numbers of individuals in large livestock families and allows for missing information. It can be extended to multiple alleles and can be used for autosomal or sex-linked loci. The allele frequencies and the form of expression (dominance, penetrance) must be specified. An algorithm using the method and involving an iterative procedure has been developed to calculate the genotype probabilities for practical use in livestock breeding. The method and algorithm were used to determine the accuracy of estimating genotype probabilities of sires for a female sex-limited trait, such as genetic variants of milk proteins. Data were similated and genotype probabilities estimated for 100 sires (20 replicates) with 3, 6 and 12 female offspring per sire, for different population frequencies, for additive and dominance gene action and for variable genotypic expression. Such simulation is useful in the design of testing systems for the use of information on specific genetic loci in selection.Prepared during a leave at Centre for Genetic Improvement of Livestock, Guelph, Canada     

Bias of heritability estimates from twin data in presence of errors of zygosity determination

Simple heritability estimators of continuous as well as discrete traits from twin data are known to overestimate the degree of genetic determination of the measured traits for several reasons. Errors of zygosity determination will, however, underestimate the true heritability. The bias due to wrong assignment of dizygous twin pairs into monozygous type is evaluated here, and the results indicate that this negative bias has a compensatory effect on the estimate of the degree of genetic determination when other factors of similarity between twin pairs are taken into account. It is shown that when an estimate of zygosity error is available, the bias due to this factor can be evaluated quantitatively, and hence the adjustment for zygosity error can be incorporated in the estimation of the degree of genetic determination of a trait. Although this theory is explicitly developed here for twin studies, the general principle also applies for other types of errors of determining the degree of biological relationships for estimation of heritability, in which case this type of error may be more important than the simple zygosity error.     

Temperature as a determinative factor in the evolution of genetic systems

Summary Heat induces a number of premutational lesions (for example, the deamination of cytosine to uracil) in DNA and RNA. These kinds of errors occur in resting as well as replicating polynucleotides. However, an increase in temperature also raises the probability of copying error occurring in nucleic acids because of increased thermal noise in the replicative machinery. In most modern genetic systems, the majority of heat-induced lesions are efficiently repaired. It follows that the importance of heat-induced error increases as the effectiveness of repair declines. We show in this paper that the error rate of enzymatic polynucleotide copying is expected to increase monotonically with temperature. We also explore the effects of temperature variations on the early evolution of biological information transmission mechanisms.     

Full and reduced models for yield trials

Summary Empirical results routinely demonstrate that the reduced Additive Main effects and Multiplicative Interaction (AMMI) model achieves better predictive accuracy for yield trials than does the full treatment means model. It may seem mysterious that treatment means are not the most accurate estimates, but rather that the AMMI model is often more accurate than its data. The statistical explanation involves the Stein effect, whereby a small sacrifice in bias can produce a large gain in accuracy. The corresponding agricultural explanation is somewhat complex, beginning with a yield trial's design and ending with its research purposes and applications. In essence, AMMI selectively recovers pattern related to the treatment design in its model, while selectively relegating noise related to the experimental design in its discarded residual. For estimating the yield of a particular genotype in a particular environment, the AMMI model uses the entire yield trial, rather than only the several replications of this particular trial, as in the treatment means model. This use of more information is the source of AMMI's gain in accuracy.This research was supported by the Rhizobotany Project of the USDA-ARS     

The nature and frequency of agonism in free-ranging and semi-free-ranging brown lemurs,Eulemur fulvus

Agonistic behaviour was studied in three groups each of free-ranging and semi-free-ranging brown lemurs (Eulemur fulvus) at Berenty, Madagascar and the Duke University Primate Center (DUPC) respectively. The purpose of the study was to answer questions arising from the work of other researchers regarding the frequency and intensity of agonism in this species. Authors of field studies generally concluded that agonism was rare and mild, whereas those who had studied semi-free-ranging or captive animals at the DUPC reported intense agonism during the peaks of the mating and birth seasons, with sometimes fatal wounding occurring among captive animals. I recorded 30 agonistic behaviours or “signals” which I grouped into seven general categories — cuffs, other physical contact, threats, chases, third party intervention, unprovoked submissive signals, and reciprocal aggression. The seven categories represent the types of signals which initiated or otherwise defined agonistic interactions, regardless of whether or not there was a submissive response to aggression. The relative percentages of all agonism constituted by the seven categories were not found to be significantly different between study sites. Agonistic signals were also classified as either subtle or obvious, a classification which crosscut the seven categories. At both study sites, the majority of agonistic signals initiating or defining interactions were subtle. Rates of agonism for the Berenty groups, studied during the birth season only, were significantly lower than those for the DUPC groups during the birth season, possibly due to (1) easier observation conditions at the DUPC, and (2) the impossibility of successful emigration at the DUPC, which might have resulted in social stresses translating into higher rates of agonism. In only one DUPC group was there significant variation in rates of agonism between seasons. I found agonistic behaviour to be mild, at both study sites, in the senses of subtlety of both aggressive and submissive signals, unlikelihood of response to aggression, and virtual absence of wounding; and I noted that serious wounding during other studies at the DUPC involved animals captive in caged runs. Comparing rates of the study groups with rates reported in other research for brown lemurs, other lemuriform species, and some New and Old World anthropoid species, I concluded thatE. fulvus agonism was in fact not rare except in comparison to baboons and macaques.     

Best Linear Unbiased Prediction (BLUP) for regional yield trials: a comparison to additive main effects and multiplicative interaction (AMMI) analysis

Multilocation trials are often used to analyse the adaptability of genotypes in different environments and to find for each environment the genotype that is best adapted; i.e. that is highest yielding in that environment. For this purpose, it is of interest to obtain a reliable estimate of the mean yield of a cultivar in a given environment. This article compares two different statistical estimation procedures for this task: the Additive Main Effects and Multiplicative Interaction (AMMI) analysis and Best Linear Unbiased Prediction (BLUP). A modification of a cross validation procedure commonly used with AMMI is suggested for trials that are laid out as a randomized complete block design. The use of these procedure is exemplified using five faba bean datasets from German registration trails. BLUP was found to outperform AMMI in four of five faba bean datasets.     

A real-time database/models base/expert system in predictive microbiology

Summary This paper describes the development and operation of a database/models base/expert system funded by the Ministry of Agriculture, Fisheries and Food in the UK. As part of an on-going coordinated program on predictive microbiology, the system being established involves storage of data and models relevant to changes in populations of food-borne pathogens under given conditions. The system is due to be completed by March 1994.     

Development and use of probability models: The industry perspective

Summary In the processed meat industry, food safety and microbiological shelf life issues lend themselves to the use of probability modeling. Our research concentrated on predicting the effectiveness of sodium lactate as an antibotulinal agent in vacuum packaged, uncured and cured turkey breast model systems. In uncured turkey breast containing 1.4% NaCl, 0.3% Na phosphate, and 0–3% Na lactate, the antibotulinal effect of sodium lactate can be predicted using the following model: Days to toxicity = 3.13+0.39(Na lactate)². Using cured turkey breast with 0.3% Na phosphate, 0.2% sucrose, 0–3% Na lactate, the time to toxicity can be predicted from the following model: Days to toxicity = 1.69+4.88(NaCl)–11.16(Na lactate)+7.23(Na lactate)². Probability models have also been developed to predict the refrigerated shelf life of specific processed meat products. The usefulness of the predictive modeling for food safety and quality in the food industry will also be discussed.This paper was presented at The International Conference on the Application of Predictive Microbiology and Computer Modeling Techniques to the Food Industry, April 12–15 1992, Hyatt Regency Hotel, Tampa, FL, USA.     

尿铜蓝蛋白、肾损伤因子1与糖尿病肾病患者肾功能的关系及对预后不良的预测价值研究

摘要 目的：探讨尿铜蓝蛋白（CP）、肾损伤因子1（KIM-1）与糖尿病肾病（DKD）患者肾功能的关系及对预后不良的预测价值。方法：回顾性分析2017年1月～2019年1月陆军第八十二集团军医院肾内科收治的160例DKD患者（DKD组）的临床资料,随访3年,根据是否发展为终末期肾脏疾病（ESRD）分为预后不良组42例和预后良好组118例,另选取同期56例单纯2型糖尿病（T2DM）患者作为T2DM组和47例体检健康者作为对照组。采用微量法和酶联免疫吸附试验法检测尿CP、KIM-1水平,并计算尿白蛋白/肌酐比值（UACR）和估算肾小球滤过率（eGFR）。通过Spearman相关性分析DKD患者尿CP、KIM-1与UACR、eGFR的相关性,单因素和多因素Logistic回归分析DKD患者预后不良的影响因素,受试者工作特征（ROC）曲线分析尿CP、KIM-1对DKD患者预后不良的预测价值。结果：随访3年,160例DKD患者有42例发展为ESRD,预后不良发生率为26.25％（42/160）。DKD组尿CP、KIM-1、UACR高于T2DM组、对照组,eGFR低于T2DM组、对照组（P＜0.05）;T2DM组尿CP、KIM-1、UACR高于对照组,eGFR低于对照组（P＜0.05）。Spearman相关性分析显示,DKD患者尿CP、KIM-1与UACR呈正相关（P均＜0.001）,与eGFR呈负相关（P均＜0.001）。多因素Logistic回归分析显示,高血压、DKD分期4期和糖化血红蛋白（HbA1c）（较高）、低密度脂蛋白胆固醇（LDL-C）（较高）、UACR（较高）、尿CP（较高）、尿KIM-1（较高）为DKD患者预后不良的独立危险因素（P＜0.05）,eGFR（较高）为独立保护因素（P＜0.05）。ROC曲线分析显示,尿CP、KIM-1联合预测DKD患者预后不良的曲线下面积大于各指标单独预测。结论：DKD患者尿CP、KIM-1升高与肾功能降低和预后不良密切相关,尿CP、KIM-1联合预测DKD患者预后不良的价值较高。