Over‐Expression of RNA Processing,Heat Shock,and DNA Repair Proteins in Breast Tumor Compared to Normal Tissue

This study identifies the main changes in protein expression in human breast tumors compared to normal breast tissue. Malignant tumors (32) and normal breast tissue samples (23), from formaldehyde‐fixed, paraffin‐embedded specimens are subjected to discovery proteomics using liquid chromatography/tandem mass spectrometry, with spectral counts for quantitation. The dataset contains 1406 proteins. Differential expression is measured using a method that takes advantage of estimates of the percentage of tumor on a slide. This analysis shows that the major classes of proteins over‐expressed by tumors are RNA‐binding, heat shock and DNA repair proteins. RNA‐binding proteins, including heterogeneous nuclear ribonucleoproteins (HNRNPs), SR splice factors (SRSF) and elongation factors form the largest group. Comparison with results from another study demonstrates that the RNA‐binding proteins are associated specifically with malignant transformation, rather than with cell proliferation. HNRNP and SRSF proteins help define splice sites in normal cells. Their over‐expression may dysregulate splicing, which in turn has the potential to promote malignant transformation.     

土壤碳矿化潜力对沙坡头人工固沙植被演变的响应

土壤呼吸是土壤有机C矿化分解,释放无机养分的重要生物化学过程。本研究通过实验室培养的方法,分析了沙坡头地区人工固沙区不同固沙年限土壤碳矿化潜力的变化。经过103d的室内培养,土壤CO2-C的释放量表现为55龄>47龄>30龄>24龄>21龄>流动沙丘,在垂直方向上表现为0～5cm>5～10cm>10～20cm。而流沙区土壤碳矿化潜力为10～20cm土层最高。不同固沙年限土壤碳矿化潜力、全氮、有机碳、电导率有明显的差异,均表现为随植被恢复年限的延长而增加,随深度的增加而递减。相关性分析表明,土壤碳矿化潜力与土壤有机碳、总氮、C/N、pH、电导率、温度、土壤水分含量呈极显著相关,土壤各环境因子之间亦呈极显著相关。土壤养分含量随着恢复时间的延长而得到明显的改善,土壤碳矿化潜力与土壤养分状况改善程度一致。人工固沙植被的建立促进了土壤微生物活性,通过潜在的土壤呼吸得到表征。植被恢复和凋落物积累使土壤免遭风蚀,显著增加了土壤有机质的输入,因而显著作用于大气C的固存。     

Integrating multi-platform genomic data using hierarchical Bayesian relevance vector machines

Background

Recent advances in genome technologies and the subsequent collection of genomic information at various molecular resolutions hold promise to accelerate the discovery of new therapeutic targets. A critical step in achieving these goals is to develop efficient clinical prediction models that integrate these diverse sources of high-throughput data. This step is challenging due to the presence of high-dimensionality and complex interactions in the data. For predicting relevant clinical outcomes, we propose a flexible statistical machine learning approach that acknowledges and models the interaction between platform-specific measurements through nonlinear kernel machines and borrows information within and between platforms through a hierarchical Bayesian framework. Our model has parameters with direct interpretations in terms of the effects of platforms and data interactions within and across platforms. The parameter estimation algorithm in our model uses a computationally efficient variational Bayes approach that scales well to large high-throughput datasets.

Results

We apply our methods of integrating gene/mRNA expression and microRNA profiles for predicting patient survival times to The Cancer Genome Atlas (TCGA) based glioblastoma multiforme (GBM) dataset. In terms of prediction accuracy, we show that our non-linear and interaction-based integrative methods perform better than linear alternatives and non-integrative methods that do not account for interactions between the platforms. We also find several prognostic mRNAs and microRNAs that are related to tumor invasion and are known to drive tumor metastasis and severe inflammatory response in GBM. In addition, our analysis reveals several interesting mRNA and microRNA interactions that have known implications in the etiology of GBM.

Conclusions

Our approach gains its flexibility and power by modeling the non-linear interaction structures between and within the platforms. Our framework is a useful tool for biomedical researchers, since clinical prediction using multi-platform genomic information is an important step towards personalized treatment of many cancers. We have a freely available software at: http://odin.mdacc.tmc.edu/~vbaladan.

     

Applications of KAM theory to population dynamics

Computer simulations have shown that several classes of population models, including the May host-parasitoid model and the Ginzburg–Taneyhill ‘maternal-quality’ single species population model, exhibit extremely complicated orbit structures. These structures include islands-around-islands, ad infinitum, with the smaller islands containing stable periodic points of higher period. We identify the mechanism that generates this complexity and we discuss some biological implications.     

Maize orthologs of rice GS5 and their transregulator are associated with kernel development

Genome information from model species such as rice can assist in the cloning of genes in a complex genome,such as maize.Here,we identified a maize ortholog of rice GS5 that contributes to kernel development in maize.The genomewide association analysis of the expression levels of ZmGS5,and 15 of its 26 paralogs,identified a trans-regulator on chromosome 7,which was a BAKi-like gene.This gene that we named as ZmBAK1-7 could regulate the expression of ZmGS5 and three of the paralogs.Candidate-gene association analyses revealed that these five genes were associated with maize kernel development-related traits.Linkage analyses also detected that ZmGSs and ZmBAK1-7 co-localized with mapped QTLs.A transgenic analysis of ZmGS5 in Arabidopsis thaliana L.showed a significant increase in seed weight and cell number,suggesting that ZmGS5 may have a conserved function among different plant species that affects seed development.     

Spatial-temporal patterns in intra-annual gray whale foraging: Characterizing interactions between predators and prey in Clayquot Sound, British Columbia, Canada

In Clayquot Sound, British Columbia, gray whales (Eschrichtius robustus) forage primarily on mysids (Family Mysideae) and also on crab larvae (Family Porcellanidae) that are constrained to specific habitat, which relate to bathymetric depths. In this paper we characterize the interactions of gray whales and their prey by analyzing fine scale spatial‐temporal patterns in foraging gray whale distribution within a season. Kernel density estimators are applied to two seasons (1998 and 2002) of high‐resolution data on foraging by gray whales. By partitioning data from each foraging season into several time periods (12 in 1998 and 11 in 2002), using a temporal autocorrelation function, and generating kernel density estimated surfaces for each time period, it is possible to identify discrete areas of increasing and declining foraging effort. Our results indicate that gray whales forage on mysids throughout a season and opportunistically forage on crab larvae. The episodic crab larvae feeding may reduce, but not eliminate, pressure to mysid populations enabling mysids to reassemble swarms and continue to support gray whale foraging in the latter part of the season. Results suggest that when managing marine environments, gray whale populations require multiple and connected habitats for summer foraging.     

The effect of packing hydrophilization on bacterial attachment and the relationship with the performance of biotrickling filters

Many bioprocesses depend on the effective formation of a biofilm on a solid support. In the present study, three different surface treatments (sandblasting, pure‐O₂ plasma, and He–O₂ plasma treatments) were conducted on polypropylene (PP) Pall rings used as a support in biotrickling filters for air pollution control. The intent was to modify the ring surface and/or electrochemical properties in order to possibly improve cell adhesion, wetting properties, and possibly reduce the start‐up time and increase the performance of the biotrickling filters. The surface treatments were found to generally increase the hydrophilicity and the zeta potential of the surfaces. However, the startup and performance of lab‐scale biotrickling filters packed with treated Pall rings were not significantly different than the control with untreated rings. Cell and colloid deposition experiments conducted in flow cells showed that the treated surfaces and the hydrodynamic conditions were not favorable for cell deposition indicating that there could be significant opportunities for improving packings used in environmental bioprocess applications. Biotechnol. Bioeng. 2009;103: 1060–1067. © 2009 Wiley Periodicals, Inc.