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     

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     

Evidence for deviations from uniform changes in a Portuguese watershed illustrated by CORINE maps: An Intensity Analysis approach

We apply a method to evaluate the strength of the evidence for deviations from uniform land change in a coastal area, in the context of Intensity Analysis. The errors in the CORINE maps at 1990 and 2006 can influence the apparent change, but the errors are unknown because error assessment of the 1990 map has never been released, while the error of the 2006 map has been checked for only some countries. The 1990 and the 2006 maps of a coastal watershed in Portugal served as the data to compute the intensities of changes among eight categories. We evaluate the sizes and types of errors that could explain deviations from uniform intensities. Errors in 2.0% of the 2006 map can explain all apparent deviations from uniform gains. Errors in 1.5% of the 1990 map can explain all apparent deviations from uniform losses. Errors in less than 0.7% of the 1990 map can explain all apparent deviations from uniform transitions to each gaining category. We analyse the strength of the evidence for deviations from uniform intensities in light of historical processes of change. Historical processes can explain some transitions that the data show, while the hypothesised errors in the data are the explanation for other transitions that are not consistent with known processes. Inconsistent transitions are an indication of the misclassification errors that could propagate to other land cover change applications, as in the assessment of hydrological processes.     

Detailed evaluation of Mobius3D dose calculation accuracy for volumetric-modulated arc therapy

PurposeTo perform a detailed evaluation of dose calculation accuracy and clinical feasibility of Mobius3D. Of particular importance, multileaf collimator (MLC) modeling accuracy in the Mobius3D dose calculation algorithm was investigated.MethodsMobius3D was fully commissioned by following the vendor-suggested procedures, including dosimetric leaf gap (DLG) optimization. The DLG optimization determined an optimal DLG correction factor which minimized the average difference between calculated and measured doses for 13 patient volumetric-modulated arc therapy (VMAT) plans. Two sets of step-and-shoot plans were created to examine MLC and off-axis open fields modeling accuracy of the Mobius3D dose calculation algorithm: MLC test set and off-axis open field test set. The test plans were delivered to MapCHECK for the MLC tests and an ionization chamber for the off-axis open field test, and these measured doses were compared to Mobius3D-calculated doses.ResultsThe mean difference between the calculated and measured doses across the 13 VMAT plans was 0.6% with an optimal DLG correction factor of 1.0. The mean percentage of pixels passing gamma from a 3%/1 mm gamma analysis for the MLC test set was 43.5% across the MLC tests. For the off-axis open field tests, the Mobius3D-calculated dose for 1.5 cm square field was −4.6% lower than the chamber-measured dose.ConclusionsIt was demonstrated that Mobius3D has dose calculation uncertainties for small fields and MLC tongue-and-groove design is not adequately taken into consideration in Mobius3D. Careful consideration of DLG correction factor, which affects the resulting dose distributions, is required when commissioning Mobius3D for patient-specific QA.     

A simple and accurate protocol for absolute polar metabolite quantification in cell cultures using quantitative nuclear magnetic resonance

Absolute analyte quantification by nuclear magnetic resonance (NMR) spectroscopy is rarely pursued in metabolomics, even though this would allow researchers to compare results obtained using different techniques. Here we report on a new protocol that permits, after pH-controlled serum protein removal, the sensitive quantification (limit of detection [LOD] = 5−25 μM) of hydrophilic nutrients and metabolites in the extracellular medium of cells in cultures. The method does not require the use of databases and uses PULCON (pulse length-based concentration determination) quantitative NMR to obtain results that are significantly more accurate and reproducible than those obtained by CPMG (Carr–Purcell–Meiboom–Gill) sequence or post-processing filtering approaches. Three practical applications of the method highlight its flexibility under different cell culture conditions. We identified and quantified (i) metabolic differences between genetically engineered human cell lines, (ii) alterations in cellular metabolism induced by differentiation of mouse myoblasts into myotubes, and (iii) metabolic changes caused by activation of neurotransmitter receptors in mouse myoblasts. Thus, the new protocol offers an easily implementable, efficient, and versatile tool for the investigation of cellular metabolism and signal transduction.     

蛋白质二级结构在线服务器预测评估

蛋白质二级结构的预测,对于研究蛋白质的功能和人类生命科学意义非凡。1951年开始提出预测蛋白质二级结构,1983年对于二级结构的预测只有50%的准确率。经过多年的发展,预测方式不断的改进和完善,到如今准确率已经超过80%。但目前预测在线服务器繁多,连续自动模型评估(CAMEO)也只给出服务器三级结构的预测评估,二级结构评估还未实现。针对上述问题,选取了以下6个服务器:PSRSM、MUFOLD、SPIDER、RAPTORX、JPRED和PSIPRED,对其预测的二级结构进行评估。并且为保证测试集不在训练集内,实验数据选取蛋白质结构数据库(Protein Data Bank,PDB)最新发布的蛋白质。在基于蛋白质同源性30%、50%和70%的实验中,PSRSM取得Q3的准确率分别为91.44%、88.12%和90.17%,比其他预测服务器中最高的MUFOLD分别高出3.19%、1.33%和2.19%,证明在同一类同源性数据中PSRSM比其他服务器有更好的预测效果。除此之外实验也得到其预测的Sov准确度也比其他服务器要高。比较各类服务器的方法与结果,得出今后蛋白质二级结构预测应当重点从大数据、模板和深度学习的角度进行研究。     

钼靶和超声检查在乳腺癌临床诊断的准确性的比较分析

摘要 目的：比较与分析钼靶和超声检查在乳腺癌临床诊断的准确性。方法：2018年8月到2021年1月选择在本院进行诊治的乳腺肿瘤患者110例作为研究对象,所有患者都给予钼靶和超声检查,记录影像学特征并判断诊断价值。结果：在110例患者中,病理诊断为乳腺良性肿瘤76例、乳腺癌34例。恶性组钼靶的分叶征、钙化、大角征、毛刺征等比例高于良性组,病灶大小也高于良性组(P<0.05)。恶性组超声的形态不规则、边缘不光整、高回声晕、回声衰减、微钙化等比例高于良性组(P<0.05)。钼靶乳腺影像报告及数据系统(Breast imaging report and data system,BI-RADS)判断为乳腺良性肿瘤72例,乳腺癌38例;超声BI-RADS判断为乳腺良性肿瘤75例,乳腺癌35例,钼靶鉴别诊断乳腺癌的敏感性为93.4%,特异性为97.1%,准确性为94.5%;超声鉴别诊断乳腺癌的敏感性为98.7%,特异性为100.0%,准确性为99.1%。多因素logistic回归分析显示病灶大小、分叶征、回声衰减、毛刺征为导致误诊的重要因素(P<0.05)。结论：乳腺癌在钼靶和超声检查中都有明显的征象特征,超声诊断的准确性更高,病灶大小、分叶征、回声衰减、毛刺征为影响诊断效果的很重要因素。     

The Effect of Recombination on the Accuracy of Phylogeny Estimation

Phylogenetic studies based on DNA sequences typically ignore the potential occurrence of recombination, which may produce different alignment regions with different evolutionary histories. Traditional phylogenetic methods assume that a single history underlies the data. If recombination is present, can we expect the inferred phylogeny to represent any of the underlying evolutionary histories? We examined this question by applying traditional phylogenetic reconstruction methods to simulated recombinant sequence alignments. The effect of recombination on phylogeny estimation depended on the relatedness of the sequences involved in the recombinational event and on the extent of the different regions with different phylogenetic histories. Given the topologies examined here, when the recombinational event was ancient, or when recombination occurred between closely related taxa, one of the two phylogenies underlying the data was generally inferred. In this scenario, the evolutionary history corresponding to the majority of the positions in the alignment was generally recovered. Very different results were obtained when recombination occurred recently among divergent taxa. In this case, when the recombinational breakpoint divided the alignment in two regions of similar length, a phylogeny that was different from any of the true phylogenies underlying the data was inferred.     

Large-sliding contact elements accurately predict levels of bone-implant micromotion relevant to osseointegration

Primary stability is recognised as an important determinant in the aseptic loosening failure process of cementless implants. An accurate evaluation of the bone–implant relative micromotion is becoming important both in pre-clinical and clinical studies. If the biological threshold for micro-movements is in the range 100–200 μm then, in order to be discriminative, any method used to evaluate the primary stability should have an accuracy of 10–20 μm or better. Additionally, such method should also be able to report the relative micromotion at each point of the interface. None of the available experimental methods satisfies both requirements. Aim of the present study is to verify if any of the current finite element modelling techniques is sufficiently accurate in predicting the primary stability of a cementless prosthesis to be used to decide whether the micromotion may or may not jeopardise the implant osseointegration. The primary stability of an anatomic cementless stem, as measured in vitro, was used as a benchmark problem to comparatively evaluate different contact modelling techniques. Frictionless contact, frictional contact and press-fitted frictional contact conditions were modelled using alternatively node-to-node, node-to-face and face-to-face contact elements. The model based on face-to-face contact elements accounting for frictional contact and initial press-fit was able to predict the micromotion measured experimentally with an average (RMS) error of 10 μm and a peak error of 14 μm. All the other models presented errors higher than 20 μm assumed in the present study as an accuracy threshold.