Plant-growth regulators from common starfish (<Emphasis Type="Italic">Asterias amurensis</Emphasis> Lütken) waste

Starfish waste has been shown to be an effective compost material not only in the promotion of plant growth but also in terms of having insecticidal activity. In the present study, plant growth regulation by chemicals from starfish was examined. The aqueous fraction from a hot water extract of the starfish Asterias amurensis Lütken showed plant-growth activity, while the aqueous fraction from a methanol extract inhibited growth of Brassica campestris. The lipophilic fraction from the methanol extract also exhibited a plant growth-promoting effect. The active components from each extract were identified. Asterubine from the hot water extract promoted plant growth. A ceramide from the lipophilic fraction showed root growth promoting effect, and three glucocerebrosides had promotive effects on the entire plant. Asterosaponins were identified as the main growth inhibitors in the aqueous fraction of the methanol extract. These active compounds from starfish waste could be analyzed as potential plant growth regulators in agricultural applications in the future.     

Transcriptional profiling of the nucleus pulposus: say yes to notochord

This editorial addresses the debate concerning the origin of adult nucleus pulposus cells in the light of profiling studies by Minogue and colleagues. In their report of several marker genes that distinguish nucleus pulposus cells from other related cell types, the authors provide novel insights into the notochordal nature of the former. Together with recently published work, their work lends support to the view that all cells present within the nucleus pulposus are derived from the notochord. Hence, the choice of an animal model for disc research should be based on considerations other than the cell loss and replacement by non-notochordal cells.     

Expression profiling of <Emphasis Type="Italic">Crambe abyssinica</Emphasis>under arsenate stress identifies genes and gene networks involved in arsenic metabolism and detoxification

Background  

Arsenic contamination is widespread throughout the world and this toxic metalloid is known to cause cancers of organs such as liver, kidney, skin, and lung in human. In spite of a recent surge in arsenic related studies, we are still far from a comprehensive understanding of arsenic uptake, detoxification, and sequestration in plants. Crambe abyssinica, commonly known as 'abyssinian mustard', is a non-food, high biomass oil seed crop that is naturally tolerant to heavy metals. Moreover, it accumulates significantly higher levels of arsenic as compared to other species of the Brassicaceae family. Thus, C. abyssinica has great potential to be utilized as an ideal inedible crop for phytoremediation of heavy metals and metalloids. However, the mechanism of arsenic metabolism in higher plants, including C. abyssinica, remains elusive.     

A yeast's eye view of mammalian reproduction: cross-species gene co-expression in meiotic prophase

Background  

Meiotic prophase is a critical stage in sexual reproduction. Aberrant chromosome recombination during this stage is a leading cause of human miscarriages and birth defects. However, due to the experimental intractability of mammalian gonads, only a very limited number of meiotic genes have been characterized. Here we aim to identify novel meiotic genes important in human reproduction through computational mining of cross-species and cross-sex time-series expression data from budding yeast, mouse postnatal testis, mouse embryonic ovary, and human fetal ovary.     

Calculation of accurate small angle X-ray scattering curves from coarse-grained protein models

Background  

Genome sequencing projects have expanded the gap between the amount of known protein sequences and structures. The limitations of current high resolution structure determination methods make it unlikely that this gap will disappear in the near future. Small angle X-ray scattering (SAXS) is an established low resolution method for routinely determining the structure of proteins in solution. The purpose of this study is to develop a method for the efficient calculation of accurate SAXS curves from coarse-grained protein models. Such a method can for example be used to construct a likelihood function, which is paramount for structure determination based on statistical inference.     

Bayesian Quantile Regression for Longitudinal Studies with Nonignorable Missing Data

Summary .  We study quantile regression (QR) for longitudinal measurements with nonignorable intermittent missing data and dropout. Compared to conventional mean regression, quantile regression can characterize the entire conditional distribution of the outcome variable, and is more robust to outliers and misspecification of the error distribution. We account for the within-subject correlation by introducing a   ℓ₂   penalty in the usual QR check function to shrink the subject-specific intercepts and slopes toward the common population values. The informative missing data are assumed to be related to the longitudinal outcome process through the shared latent random effects. We assess the performance of the proposed method using simulation studies, and illustrate it with data from a pediatric AIDS clinical trial.