Observations below multiple lower limits of quantification: How to estimate the mean and variance

Multiple lower limits of quantification (MLOQs) result if various laboratories are involved in the analysis of concentration data and some observations are too low to be quantified. For normally distributed data under MLOQs there exists only the multiple regression method of Helsel to estimate the mean and variance. We propose a simple imputation method and two new maximum likelihood estimation methods: the multiple truncated sample method and the multiple censored sample method. A simulation study is conducted to compare the performances of the newly introduced methods to Helsel's via the criteria root mean squared error (RMSE) and bias of the parameter estimates. Two and four lower limits of quantification (LLOQs), various amounts of unquantifiable observations and two sample sizes are studied. Furthermore, the robustness is investigated under model misspecification. The methods perform with decreasing accuracy for increasing rates of unquantified observations. Increasing sample sizes lead to smaller bias. There is almost no change in the performance between two and four LLOQs. The magnitude of the variance impairs the performance of all methods. For a smaller variance, the multiple censored sample method leads to superior estimates regarding the RMSE and bias, whereas Helsel's method is superior regarding the bias for a larger variance. Under model misspecification, Helsel's method was inferior to the other methods. Estimating the mean, the multiple censored sample method performed better, whereas the multiple truncated sample method performs best in estimating the variance. Summarizing, for a large sample size and normally distributed data we recommend to use Helsel's method. Otherwise, the multiple censored sample method should be used to obtain estimates of the mean and variance of data including MLOQs.     

Stochastic search variable selection based on two mixture components and continuous‐scale weighting

Stochastic search variable selection (SSVS) is a Bayesian variable selection method that employs covariate‐specific discrete indicator variables to select which covariates (e.g., molecular markers) are included in or excluded from the model. We present a new variant of SSVS where, instead of discrete indicator variables, we use continuous‐scale weighting variables (which take also values between zero and one) to select covariates into the model. The improved model performance is shown and compared to standard SSVS using simulated and real quantitative trait locus mapping datasets. The decision making to decide phenotype‐genotype associations in our SSVS variant is based on median of posterior distribution or using Bayes factors. We also show here that by using continuous‐scale weighting variables it is possible to improve mixing properties of Markov chain Monte Carlo sampling substantially compared to standard SSVS. Also, the separation of association signals and nonsignals (control of noise level) seems to be more efficient compared to the standard SSVS. Thus, the novel method provides efficient new framework for SSVS analysis that additionally provides whole posterior distribution for pseudo‐indicators which means more information and may help in decision making.     

Phylogeography of lethal male fighting in a social spider mite

When males fight for access to females, such conflict rarely escalates into lethal fight because the risks and costs involved, that is, severe injury or death, are too high. The social spider mite, Stigmaeopsis miscanthi, does exhibit lethal male fights, and this male–male aggressiveness varies among populations. To understand the evolution of lethal fighting, we investigated aggressiveness in 42 populations and phylogenetic relationships in 47 populations along the Japanese archipelago. By analysis of the male weapon morph, a proxy for aggressiveness, we confirmed the existence of a mildly aggressive (ML) form, besides the low aggression (LW) and high aggression (HG) forms reported earlier. To evaluate demographic history of these three forms, we employed the approximate Bayesian computation approach using mtCOI sequences and taking into consideration the postlast glacial expansion history of the host plant, Miscanthus sinensis. As results, hierarchical split models are more likely to explain the observed genetic pattern than admixture models, and the ML form in the subtropical region was considered the ancestral group. The inferred demographic history was consistent with the one reconstructed for the host plant in a previous study. The LW form was split from the ML form during the last glacial period (20,000–40,000 years BP), and subsequently, the HG form was split from the ML form at the end of or after the last glacial period (5,494–10,988 years BP). The results also suggest that the mite invaded Japan more than once, resulting in the present parapatric distribution of LW and HG forms in eastern Japan.     

Spatial patterns and interspecific associations among trees at different stand development stages in the natural secondary forests on the Loess Plateau,China

Quercus wutaishansea populations on the Loess Plateau are currently becoming more dominant in natural secondary forests, whereas Pinus tabulaeformis is declining. In the present paper, the diameter class (instead of age) was used to classify the different growth stages as juvenile, subadult, or adult, and the univariate function g(r) was used to analyze the dynamic changes in spatial patterns and interspecific associations in three 1‐ha tree permanent plots on the Loess Plateau, NW China. Our results suggested that the niche breadth changed with the development stage. The diameter distribution curve was consistent with the inverted “J” type, indicating that natural regeneration was common in all three plots. There was a close relationship between the spatial pattern and scale, which showed significant aggregation at small distances, and became more random as distance increased, but in the Pinus + Quercus mixed forests, the whole species were aggregated at distances up to 50 m. The degree of spatial clumping decreased from juvenile to subadult and from subadult to adult. The spatial pattern also differed at different growth stages, likely due to strong intraspecific competition. Associations among different growth stages were positively correlated at small scales. Our study is important to the understanding of the development of the Q. wutaishansea forests; thus, the spatial dynamic change features should be received greater attention when planning forest management and developing restoration strategies on the Loess Plateau.     

Leaf wax n‐alkane patterns of six tropical montane tree species show species‐specific environmental response

It remains poorly understood how the composition of leaf wax n‐alkanes reflects the local environment. This knowledge gap inhibits the interpretation of plant responses to the environment at the community level and, by extension, inhibits the applicability of n‐alkane patterns as a proxy for past environments. Here, we studied the n‐alkane patterns of five Miconia species and one Guarea species, in the Ecuadorian Andes (653–3,507 m a.s.l.). We tested for species‐specific responses in the average chain length (ACL), the C₃₁/(C₃₁ + C₂₉) ratio (ratio), and individual odd n‐alkane chain lengths across an altitudinally driven environmental gradient (mean annual temperature, mean annual relative air humidity, and mean annual precipitation). We found significant correlations between the environmental gradients and species‐specific ACL and ratio, but with varying magnitude and direction. We found that the n‐alkane patterns are species‐specific at the individual chain length level, which could explain the high variance in metrics like ACL and ratio. Although we find species‐specific sensitivity and responses in leaf n‐alkanes, we also find a general decrease in “shorter” (<C₂₉) and an increase in “longer” (>C₃₁) chain lengths with the environmental gradients, most strongly with temperature, suggesting n‐alkanes are useful for reconstructing past environments.     

Tree species identity determines wood decomposition via microclimatic effects

Empirical evidence suggests that the rich set of ecosystem functions and nature's contributions to people provided by forests depends on tree diversity. Biodiversity–ecosystem functioning research revealed that not only species richness per se but also other facets of tree diversity, such as tree identity, have to be considered to understand the underlying mechanisms. One important ecosystem function in forests is the decomposition of deadwood that plays a vital role in carbon and nutrient cycling and is assumed to be determined by above‐ and belowground interactions. However, the actual influence of tree diversity on wood decay in forests remains inconclusive. Recent studies suggest an important role of microclimate and advocate a systematical consideration of small‐scale environmental conditions. We studied the influence of tree species richness, tree species identity, and microclimatic conditions on wood decomposition in a 12‐year‐old tree diversity experiment in Germany, containing six native species within a tree species richness gradient. We assessed wood mass loss, soil microbial properties, and soil surface temperature in high temporal resolution. Our study shows a significant influence of tree species identity on all three variables. The presence of Scots pine strongly increased wood mass loss, while the presence of Norway spruce decreased it. This could be attributed to structural differences in the litter layer that were modifying the capability of plots to hold the soil surface temperature at night, consequently leading to enhanced decomposition rates in plots with higher nighttime surface temperatures. Therefore, our study confirmed the critical role of microclimate for wood decomposition in forests and showed that soil microbial properties alone were not sufficient to predict wood decay. We conclude that tree diversity effects on ecosystem functions may include different biodiversity facets, such as tree identity, tree traits, and functional and structural diversity, in influencing the abiotic and biotic soil properties.     

Overexpression of RYBP inhibits proliferation,invasion, and chemoresistance to cisplatin in anaplastic thyroid cancer cells via the EGFR pathway

Ring1 and YY1 binding protein (RYBP), a new member of the polycomb group protein family, has been reported to play an important role in various biological processes. Recently, more and more studies have demonstrated an implication of RYBP in cancer development. However, the specific role of RYBP in anaplastic thyroid cancer (ATC) remains unknown. In this study, we investigated for the first time the expression pattern and biological functions of RYBP in ATC. We showed that RYBP was lowly expressed in ATC tissues and cell lines. We also found that overexpression of RYBP inhibited ATC cell proliferation, invasion, and cisplatin resistance. Furthermore, we observed that upregulation of RYBP decreased the phosphorylation of EGFR and ERK1/2 in ATC cells. Taken together, our data indicated that RYBP might be considered as a promising therapeutic target for the treatment of ATC.     

Clopidogrel reduces lipopolysaccharide‐induced inflammation and neutrophil‐platelet aggregates in an experimental endotoxemic model

Platelet activation contributes to organs failure in inflammation and plays an important role in endotoxemia. Clopidogrel inhibits platelet aggregation and activation. However, the role of clopidogrel in modulating inflammatory progression of endotoxemia remains largely unexplored. Therefore, we investigated the role of clopidogrel on the activation of platelet and leukocytes in lipopolysaccharide (LPS)‐induced inflammation in mice. Animals were treated with clopidogrel or vehicle before LPS induction. The expression of neutrophil‐platelet aggregates and platelet activation and tissue factor was determined. Immunofluorescence was used to analyze platelet‐leukocyte interactions and tissue factor (TF) expression on leukocytes. Clopidogrel pretreatment markedly decreased lung damage, inhibited platelet‐neutrophil aggregates and TF expression. In addition, clopidogrel reduced thrombocytopenia and affected the number of circulating white blood cell in endotoxemia mice. Moreover, clopidogrel also reduced platelet shedding of CD40L and CD62P in endotoxemic mice. Taken together, clopidogrel played an important role through reducing platelet activation and inflammatory process in endotoxemia.     

Rapid identification and interpretation of gene–environment associations using the new R.SamBada landscape genomics pipeline

sam βada is a genome–environment association software, designed to search for signatures of local adaptation. However, pre‐ and postprocessing of data can be labour‐intensive, preventing wider uptake of the method. We have now developed R.SamBada, an r ‐package providing a pipeline for landscape genomic analysis based on sam βada , spanning from the retrieval of environmental conditions at sampling locations to gene annotation using the Ensembl genome browser. As a result, R.SamBada standardizes the landscape genomics pipeline and eases the search for candidate genes of local adaptation, enhancing reproducibility of landscape genomic studies. The efficiency and power of the pipeline is illustrated using two examples: sheep populations from Morocco with no evident population structure and Lidia cattle from Spain displaying population substructuring. In both cases, R.SamBada enabled rapid identification and interpretation of candidate genes, which are further discussed in the light of local adaptation. The package is available in the r CRAN package repository and on GitHub (github.com/SolangeD/R.SamBada).