Does using stepwise variable selection to build sequential path analysis models make sense?

Causal inference methods - mainly path analysis and structural equation modeling - offer plant physiologists information about cause-and-effect relationships among plant traits. Recently, an unusual approach to causal inference through stepwise variable selection has been proposed and used in various works on plant physiology. The approach should not be considered correct from a biological point of view. Here, it is explained why stepwise variable selection should not be used for causal inference, and shown what strange conclusions can be drawn based upon the former analysis when one aims to interpret cause-and-effect relationships among plant traits.

Random regression models to estimate test-day milk yield genetic parameters Holstein cows in Southeastern Brazil

A total of 152,145 weekly test-day milk yield records from 7317 first lactations of Holstein cows distributed in 93 herds in southeastern Brazil were analyzed. Test-day milk yields were classified into 44 weekly classes of DIM. The contemporary groups were defined as herd-year-week of test-day. The model included direct additive genetic, permanent environmental and residual effects as random and fixed effects of contemporary group and age of cow at calving as covariable, linear and quadratic effects. Mean trends were modeled by a cubic regression on orthogonal polynomials of DIM. Additive genetic and permanent environmental random effects were estimated by random regression on orthogonal Legendre polynomials. Residual variances were modeled using third to seventh-order variance functions or a step function with 1, 6,13,17 and 44 variance classes. Results from Akaike`s and Schwarz`s Bayesian information criterion suggested that a model considering a 7th-order Legendre polynomial for additive effect, a 12th-order polynomial for permanent environment effect and a step function with 6 classes for residual variances, fitted best. However, a parsimonious model, with a 6th-order Legendre polynomial for additive effects and a 7th-order polynomial for permanent environmental effects, yielded very similar genetic parameter estimates. (C) 2008 Elsevier B.V. All rights reserved.

Vegetative and fruit characteristics of papaya trees obtained by mass selection

The present work had as purpose to evaluate some characteristics of papaya trees (Carica papaya L.), Golden cultivar, obtained trough plant mass selection, regarding plant and fruit quality in the first months of production. The samples were evaluated in a commercial crop at: 0, 20, 40, 70, 130, 180, 230, 260, 280, 310 and 340 days after the planting (DAP) and the first fruits were harvested at 230 DAP. The results showed the low height (199cm in 340 DAP) and low first flowering`s heigth (71cm), which is important to facilitate the harvest process. The plants presented good yield with high number of leafs (allowing a great area of fruit cover) and about 60 fruits per plant. The fruits kept similar features to cv. Golden. The fruit`s fresh weight ranged from 302.4 to 467.5g, which is in the range of the Brazilian market. The pulp thickness was 2.35cm, which is a feature of great economic interest. The pulp thickness showed close relation with climatic factors, and great variations of temperature and precipitation accelerated the pulp loss of thickness.

Geographic variation and positive selection on M7 lysin, an acrosomal sperm protein in mussels (Mytilus spp.)

Successful fertilization in free-spawning marine organisms depends on the interactions between genes expressed on the surfaces of eggs and sperm. Positive selection frequently characterizes the molecular evolution of such genes, raising the possibility that some common deterministic process drives the evolution of gamete recognition genes and may even be important for understanding the evolution of prezygotic isolation and speciation in the marine realm. One hypothesis is that gamete recognition genes are subject to selection for prezygotic isolation, namely reinforcement. In a previous study, positive selection on the gene coding for the acrosomal sperm protein M7 lysin was demonstrated among allopatric populations of mussels in the Mytilus edulis species group (M. edulis, M. galloprovincialis, and M. trossulus). Here, we expand sampling to include M7 lysin haplotypes from populations where mussel species are sympatric and hybridize to determine whether there is a pattern of reproductive character displacement, which would be consistent with reinforcement driving selection on this gene. We do not detect a strong pattern of reproductive character displacement; there are no unique haplotypes in sympatry nor is there consistently greater population structure in comparisons involving sympatric populations. One distinct group of haplotypes, however, is strongly affected by natural selection and this group of haplotypes is found within M. galloprovincialis populations throughout the Northern Hemisphere concurrent with haplotypes common to M. galloprovincialis and M. edulis. We suggest that balancing selection, perhaps resulting from sexual conflicts between sperm and eggs, maintains old allelic diversity within M. galloprovincialis.

A hybrid probabilistic criterion for market-based transmission expansion planning

Market-based transmission expansion planning gives information to investors on where is the most cost efficient place to invest and brings benefits to those who invest in this grid. However, both market issue and power system adequacy problems are system planers’ concern. In this paper, a hybrid probabilistic criterion of Expected Economical Loss (EEL) is proposed as an index to evaluate the systems’ overall expected economical losses during system operation in a competitive market. It stands on both investors’ and planner’s point of view and will further improves the traditional reliability cost. By applying EEL, it is possible for system planners to obtain a clear idea regarding the transmission network’s bottleneck and the amount of losses arises from this weak point. Sequentially, it enables planners to assess the worth of providing reliable services. Also, the EEL will contain valuable information for moneymen to undertake their investment. This index could truly reflect the random behaviors of power systems and uncertainties from electricity market. The performance of the EEL index is enhanced by applying Normalized Coefficient of Probability (NCP), so it can be utilized in large real power systems. A numerical example is carried out on IEEE Reliability Test System (RTS), which will show how the EEL can predict the current system bottleneck under future operational conditions and how to use EEL as one of planning objectives to determine future optimal plans. A well-known simulation method, Monte Carlo simulation, is employed to achieve the probabilistic characteristic of electricity market and Genetic Algorithms (GAs) is used as a multi-objective optimization tool.

Weibull model selection for reliability modelling

A large number of models have been derived from the two-parameter Weibull distribution and are referred to as Weibull models. They exhibit a wide range of shapes for the density and hazard functions, which makes them suitable for modelling complex failure data sets. The WPP and IWPP plot allows one to determine in a systematic manner if one or more of these models are suitable for modelling a given data set. This paper deals with this topic.

Positive selection on an acrosomal sperm protein, M7 lysin, in three species of the mussel genus Mytilus

Marine invertebrate sperm proteins are particularly interesting because they are characterized by positive selection and are likely to be involved in prezyogotic isolation and, thus, speciation. Here, we present the first survey of inter and intraspecific variation of a bivalve sperm protein among a group of species that regularly hybridize in nature. M7 lysin is found in sperm acrosomes of mussels and dissolves the egg vitelline coat, permitting fertilization. We sequenced multiple alleles of the mature protein-coding region of M7 lysin from allopatric populations of mussels in the Mytilus edulis species group (M. edulis, M. galloprovincialis, and M. trossulus). A significant McDonald-Kreitman test showed an excess of fixed amino acid replacing substitutions between species, consistent with positive selection. In addition, Kolmogorov-Smirnov tests showed significant heterogeneity in polymorphism to divergence ratios for both synonymous variation and combined synonymous and non-synonymous variation within M. galloprovincialis. These results indicate that there has been adaptive evolution at M7 lysin and, furthermore, shows that positive selection on sperm proteins can occur even when post-zygotic reproductive isolation is incomplete.

Selection bias in gene extraction on the basis of microarray gene-expression data

In the context of cancer diagnosis and treatment, we consider the problem of constructing an accurate prediction rule on the basis of a relatively small number of tumor tissue samples of known type containing the expression data on very many (possibly thousands) genes. Recently, results have been presented in the literature suggesting that it is possible to construct a prediction rule from only a few genes such that it has a negligible prediction error rate. However, in these results the test error or the leave-one-out cross-validated error is calculated without allowance for the selection bias. There is no allowance because the rule is either tested on tissue samples that were used in the first instance to select the genes being used in the rule or because the cross-validation of the rule is not external to the selection process; that is, gene selection is not performed in training the rule at each stage of the cross-validation process. We describe how in practice the selection bias can be assessed and corrected for by either performing a cross-validation or applying the bootstrap external to the selection process. We recommend using 10-fold rather than leave-one-out cross-validation, and concerning the bootstrap, we suggest using the so-called. 632+ bootstrap error estimate designed to handle overfitted prediction rules. Using two published data sets, we demonstrate that when correction is made for the selection bias, the cross-validated error is no longer zero for a subset of only a few genes.

A novel method for selection of chymotrypsin inhibitors from a phage peptide library

A novel screening strategy has been developed for the identification of alpha-chymotrypsin inhibitors from a phage peptide library. In this strategy, the standard affinity selection protocol was modified by adding a proteolytic cleavage period to avoid recovery of alpha-chymotrypsin substrates. After four cycles of selection and further activity assay, a group of related peptides were identified by DNA sequencing. These peptides share a consensus sequence motif as (S/T)RVPR(R/H). Then, a corresponding short peptide (Ac-ASRVPRRG-NH2) was synthesized chemically and proved to be an inhibitor of alpha-chymotrypsin. The present work provides a useful way for searching proteinase inhibitors without detailed knowledge of the molecular structure.

Selection of a strain of Aspergillus for the production of citric acid from pineapple waste in solid-state fermentation

Aspergillus foetidus ACR I 3996 (=FRR 3558) and three strains of Aspergillus niger ACM 4992 (=ATCC 9142), ACM 4993 (=ATCC 10577), ACM 4994 (=ATCC 12846) were compared for the production of citric acid from pineapple peel in solid-state fermentation. A. niger ACM 4992 produced the highest amount of citric acid, with a yield of 19.4 g of citric acid per 100 g of dry fermented pineapple waste under optimum conditions, representing a yield of 0.74 g citric acid/g sugar consumed. Optimal conditions were 65% (w/w) initial moisture content, 3% (v/w) methanol, 30 degrees C, an unadjusted initial pH of 3.4, a particle size of 2 mm and 5 ppm Fe2+. Citric acid production was best in flasks, with lower yields being obtained in tray and rotating drum bioreactors.

Anthropometric-based selection and sprint kayak training in children

A 12 week kayak training programme was evaluated in children who either had or did not have the anthropometric characteristics identified as being unique to senior elite sprint kayakers. Altogether, 234 male and female school children were screened to select 10 children with and 10 children without the identified key anthropometric characteristics. Before and after training, the children completed an all-out 2 min kayak ergometer simulation test; measures of oxygen consumption, plasma lactate and total work accomplished were recorded. In addition, a 500 m time trial was performed at weeks 3 and 12. The coaches were unaware which 20 children possessed those anthropometric characteristics deemed to favour development of kayak ability. All children improved in both the 2 min ergometer simulation test and 500 m time trial. However, boys who were selected according to favourable anthropometric characteristics showed greater improvement than those without such characteristics in the 2 min ergometer test only. In summary, in a small group of children selected according to anthropometric data unique to elite adult kayakers, 12 weeks of intensive kayak training did not influence the rate of improvement of on-water sprint kayak performance.

Effects of egg load on the host-selection behaviour of Helicoverpa armigera (Hubner) (Lepidoptera : Noctuidae)

We examined the effect of age-specific fecundity, mated status, and egg load on host-plant selection, by Helicoverpa armigera under laboratory conditions. The physiological state of a female moth (number of mature eggs produced) greatly influences her host-plant specificity and propensity to oviposit (oviposition motivation). Female moths were less discriminating against cowpea (a low-ranked host) relative to maize (a high-ranked host) as egg load increased. Similarly, increased egg load led to a greater propensity to oviposit on both cowpea and maize. Distribution of oviposition with age of mated females peaked shortly after mating and declined steadily thereafter until death. Most mated females (88%) carried only a single spermatophore, a few females (12%) contained two. The significance of these findings in relation to host-plant selection by H. armigera, and its management, are discussed.

Effects of data characteristics on the results of reserve selection algorithms

We tested the effects of four data characteristics on the results of reserve selection algorithms. The data characteristics were nestedness of features (land types in this case), rarity of features, size variation of sites (potential reserves) and size of data sets (numbers of sites and features). We manipulated data sets to produce three levels, with replication, of each of these data characteristics while holding the other three characteristics constant. We then used an optimizing algorithm and three heuristic algorithms to select sites to solve several reservation problems. We measured efficiency as the number or total area of selected sites, indicating the relative cost of a reserve system. Higher nestedness increased the efficiency of all algorithms (reduced the total cost of new reserves). Higher rarity reduced the efficiency of all algorithms (increased the total cost of new reserves). More variation in site size increased the efficiency of all algorithms expressed in terms of total area of selected sites. We measured the suboptimality of heuristic algorithms as the percentage increase of their results over optimal (minimum possible) results. Suboptimality is a measure of the reliability of heuristics as indicative costing analyses. Higher rarity reduced the suboptimality of heuristics (increased their reliability) and there is some evidence that more size variation did the same for the total area of selected sites. We discuss the implications of these results for the use of reserve selection algorithms as indicative and real-world planning tools.