Unbalanced ranked set sampling for estimating a population proportion

The application of ranked set sampling (RSS) techniques to data from a dichotomous population is currently an active research topic, and it has been shown that balanced RSS leads to improvement in precision over simple random sampling (SRS) for estimation of a population proportion. Balanced RSS, however, is not in general optimal in terms of variance reduction for this setting. The objective of this article is to investigate the application of unbalanced RSS in estimation of a population proportion under perfect ranking, where the probabilities of success for the order statistics are functions of the underlying population proportion. In particular, the Neyman allocation, which assigns sample units for each order statistic proportionally to its standard deviation, is shown to be optimal in the sense that it leads to minimum variance within the class of RSS estimators that are simple averages of the means of the order statistics. We also use a substantial data set, the National Health and Nutrition Examination Survey III (NHANES III) data, to demonstrate the feasibility and benefits of Neyman allocation in RSS for binary variables.     

Low-rank scale-invariant tensor product smooths for generalized additive mixed models

A general method for constructing low-rank tensor product smooths for use as components of generalized additive models or generalized additive mixed models is presented. A penalized regression approach is adopted in which tensor product smooths of several variables are constructed from smooths of each variable separately, these "marginal" smooths being represented using a low-rank basis with an associated quadratic wiggliness penalty. The smooths offer several advantages: (i) they have one wiggliness penalty per covariate and are hence invariant to linear rescaling of covariates, making them useful when there is no "natural" way to scale covariates relative to each other; (ii) they have a useful tuneable range of smoothness, unlike single-penalty tensor product smooths that are scale invariant; (iii) the relatively low rank of the smooths means that they are computationally efficient; (iv) the penalties on the smooths are easily interpretable in terms of function shape; (v) the smooths can be generated completely automatically from any marginal smoothing bases and associated quadratic penalties, giving the modeler considerable flexibility to choose the basis penalty combination most appropriate to each modeling task; and (vi) the smooths can easily be written as components of a standard linear or generalized linear mixed model, allowing them to be used as components of the rich family of such models implemented in standard software, and to take advantage of the efficient and stable computational methods that have been developed for such models. A small simulation study shows that the methods can compare favorably with recently developed smoothing spline ANOVA methods.     

Variable Rate Application of Nematicides on Cotton Fields: A Promising Site-Specific Management Strategy

Field tests were conducted to determine if differences in response to nematicide application (i.e., root-knot nematode (RKN) populations, cotton yield, and profitability) occurred among RKN management zones (MZ). The MZ were delineated using fuzzy clustering of five terrain (TR) and edaphic (ED) field features related to soil texture: apparent soil electrical conductivity shallow (EC_a-shallow) and deep (EC_a-deep), elevation (EL), slope (SL), and changes in bare soil reflectance. Zones with lowest mean values of EC_{a- shallow}, EC_{a- deep}, NDVI, and SL were designated as at greater risk for high RKN levels. Nematicide-treated plots (4 rows wide and 30 m long) were established in a randomized complete block design within each zone, but the number of replications in each zone varied from four to six depending on the size of the zone.The nematicides aldicarb (Temik 15 G) and 1,3-dichloropropene (1,3-D,Telone II) were applied at two rates (0.51 and 1.0 kg a.i./ha for aldicarb, and 33.1 and 66.2 kg a.i./ha for 1,3-D) to RKN MZ in commercial fields between 2007 and 2009. A consolidated analysis over the entire season showed that regardless of the zone, there were not differences between aldicarb rates and 1,3-D rates. The result across zones showed that 1,3-D provided better RKN control than did aldicarb in zones with low EC_a values (high RKN risk zones exhibiting more coarse-textured sandy soils). In contrast, in low risk zones with relatively higher EC_a values (heavier textured soil), the effects of 1,3-D and aldicarb were equal and application of any of the treatments provided sufficient control. In low RKN risk zones, a farmer would often have lost money if a high rate of 1,3-D was applied. This study showed that the effect of nematicide type and rate on RKN control and cotton yield varied across management zones (MZ) with the most expensive treatment likely to provide economic benefit only in zones with coarser soil texture. This study demonstrates the value of site specific application of nematicides based on management zones, although this approach might not be economically beneficial in fields with little variability in soil texture.     

Identification of differentially expressed salt-responsive proteins in roots of two perennial grass species contrasting in salinity tolerance

This study was designed to identify physiological responses and differential proteomic responses to salinity stress in roots of a salt-tolerant grass species, seashore paspalum (Paspalum vaginatum), and a salt-sensitive grass species, centipedegrass (Eremochloa ophiuroides). Plants of both species were exposed to salinity stress by watering the soil with 300 mM NaCl solution for 20 d in a growth chamber. The 2-DE analysis revealed that the abundance of 8 protein spots significantly increased and 14 significantly decreased in seashore paspalum, while 19 and 16 protein spots exhibited increase and decrease in abundance in centipedegrass, respectively. Eight protein spots that exhibited enhanced abundance in seashore paspalum under salinity stress were subjected to mass spectrometry analysis. Seven protein spots were successfully identified, they are peroxidase (POD, 2.36-fold), cytoplasmic malate dehydrogenase (cMDH, 5.84-fold), asorbate peroxidase (APX, 4.03-fold), two mitochondrial ATPSδ chain (2.26-fold and 4.78-fold), hypothetical protein LOC100274119 (5.01-fold) and flavoprotein wrbA (2.20-fold), respectively. Immunblotting analysis indicated that POD and ATPSδ chain were significantly up-regulated in seashore paspalum at 20 d of salinity treatment while almost no expression in both control and salt treatment of centipedegrass. These results indicated that the superior salinity tolerance in seashore paspalum, compared to centipedegrass, could be associated with a high abundance of proteins involved in ROS detoxification and energy metabolism.     

Multiple loci mapping via model-free variable selection

Despite recent flourish of proposals on variable selection, genome-wide multiple loci mapping remains to be challenging. The majority of existing variable selection methods impose a model, and often the homoscedastic linear model, prior to selection. However, the true association between the phenotypical trait and the genetic markers is rarely known a priori, and the presence of epistatic interactions makes the association more complex than a linear relation. Model-free variable selection offers a useful alternative in this context, but the fact that the number of markers p often far exceeds the number of experimental units n renders all the existing model-free solutions that require n > p inapplicable. In this article, we examine a number of model-free variable selection methods for small-n-large-p regressions in the context of genome-wide multiple loci mapping. We propose and advocate a multivariate group-wise adaptive penalization solution, which requires no model prespecification and thus works for complex trait-marker association, and handles one variable at a time so that works for n < p. Effectiveness of the new method is demonstrated through both intensive simulations and a comprehensive real data analysis across 6100 gene expression traits.     

秸秆降解菌剂对秸秆还田土壤中细菌种群数量的影响

要研究秸秆降解菌剂施用后1个生长季秸秆中细菌的数量和纤维素酶活力,了解其动态变化,为进一步研究分析土壤中微生物结构变化规律提供可靠的理论依据.利用分子生物学方法,对秸秆降解菌剂施用后不同生长阶段耕层中细菌基因组DNA纯化后PCR扩增其16S rDNA V3可变区,对扩增产物进行DGGE电泳,并对结果进行分析.初步分析表明,菌落数量呈现前期上升、中期最高、后期逐渐降低的趋势.     

Predicting the effect of a point mutation on a protein fold: the villin and advillin headpieces and their Pro62Ala mutants

Homology modeling of unknown proteins is based on the assumption that highly similar sequences are likely to share the same fold. However, this does not provide any information on the stability of a given fold, which is ultimately determined by the subtle interplay of enthalpic and entropic contributions. Herein it is shown that ab initio atomistic simulations can be used to predict the effect of point mutations on the stability of a protein fold. The calculations indicate that the fold stabilities of two proteins of similar sequence and identical fold, the villin and advillin C-terminal headpiece fragments, are different and that the same P62A point mutation has a dramatic effect on the fold of villin but a minor one on that of advillin. These predictions were subsequently validated by NMR and CD experiments.     

An scFv intrabody against the nonamyloid component of alpha-synuclein reduces intracellular aggregation and toxicity

Prevention of abnormal misfolding and aggregation of α synuclein (syn) protein in vulnerable neurons should be viable therapeutic strategies for reducing pathogenesis in Parkinson's disease. The nonamyloid component (NAC) region of α-syn shows strong tendencies to form β-sheet structures, and deletion of this region has been shown to reduce aggregation and toxicity in vitro and in vivo. The binding of a molecular species to this region may mimic the effects of such deletions. Single-chain variable fragment (scFv) antibodies retain the binding specificity of antibodies and, when genetically manipulated to create high-diversity libraries, allow in vitro selection against peptides. Accordingly, we used a yeast surface display library of an entire naïve repertoire of human scFv antibodies to select for binding to a NAC peptide. Candidate scFv antibodies (after transfer to mammalian expression vectors) were screened for viability in a neuronal cell line by transient cotransfection with A53T mutant α-syn. This provided a ranking of the protective efficacies of the initial panel of intracellular antibodies (intrabodies). High steady-state expression levels and apparent conformational epitope binding appeared more important than in vitro affinity in these assays. None of the scFv antibodies selected matched the sequences of previously reported anti-α-syn scFv antibodies. A stable cell line expressing the most effective intrabody, NAC32, showed highly significant reductions in abnormal aggregation in two separate models. Recently, intrabodies have shown promising antiaggregation and neuroprotective effects against misfolded mutant huntingtin protein. The NAC32 study extends such work significantly by utilizing information about the pathogenic capacity of a specific α-syn region to offer a new generation of in vitro-derived antibody fragments, both for further engineering as direct therapeutics and as a tool for rational drug design for Parkinson's disease.