Seasonal and spatial variations of heavy metalsin surface sediments collected from the BaoxiangRiver in the Dianchi Watershed, China

To explore potential ecological hazards due to heavy metals in the Dianchi Lake Watershed, a three-stage European Community Bureau of Reference (BCR) sequential extraction procedure was applied to examine the spatial distributions and relative speciation ratios of Zn, Cu, Ni, Pb, and Cr in Baoxiang River sediments during wet and dry seasons. The metal species have similar spatial variations during different seasons. In the upstream reaches of the Baoxiang River, heavy metals reside primarily in the non-extractable residual fraction (72&ndash;90%). In the midstream, the residual fraction (35&ndash;89%) remains dominant, but the extractable fraction increases, featuring especially notable increases in the reducible fraction (5&ndash;40%). Downstream, the Cu, Ni, Pb, and Cr residual fractions remain high (46&ndash;80%) and the extractable fractions increase rapidly; the Zn extractable fraction is quite high (65.5%). Anthropogenic sources drive changes in heavy metal speciation. Changes in the river environment, such as pH and oxidation-reduction potential, also affect speciation. The reducible fraction of heavy metals in Baoxiang River sediments is most sensitive to pH. Potential ecological risk assessments for these five elements indicate that risks from Zn and Pb are mild to moderate in the middle and lower reaches of the river.<br style="line-height: normal; text-align: -webkit-auto; text-size-adjust: auto;" /

A general model for collaboration networks

In this paper, we propose a general model for collaboration networks. Depending on a single free parameter "{\bf preferential exponent}", this model interpolates between networks with a scale-free and an exponential degree distribution. The degree distribution in the present networks can be roughly classified into four patterns, all of which are observed in empirical data. And this model exhibits small-world effect, which means the corresponding networks are of very short average distance and highly large clustering coefficient. More interesting, we find a peak distribution of act-size from empirical data which has not been emphasized before of some collaboration networks. Our model can produce the peak act-size distribution naturally that agrees with the empirical data well.Comment: 10 pages, 10 figure

MEKK2 mediates aberrant ERK activation in neurofibromatosis type I

Neurofibromatosis type I (NF1) is characterized by prominent skeletal manifestations caused by NF1 loss. While inhibitors of the ERK activating kinases MEK1/2 are promising as a means to treat NF1, the broad blockade of the ERK pathway produced by this strategy is potentially associated with therapy limiting toxicities. Here, we have sought targets offering a more narrow inhibition of ERK activation downstream of NF1 loss in the skeleton, finding that MEKK2 is a novel component of a noncanonical ERK pathway in osteoblasts that mediates aberrant ERK activation after NF1 loss. Accordingly, despite mice with conditional deletion of Nf1 in mature osteoblasts (Nf1(fl/fl);Dmp1-Cre) and Mekk2(-/-) each displaying skeletal defects, Nf1(fl/fl);Mekk2(-/-);Dmp1-Cre mice show an amelioration of NF1-associated phenotypes. We also provide proof-of-principle that FDA-approved inhibitors with activity against MEKK2 can ameliorate NF1 skeletal pathology. Thus, MEKK2 functions as a MAP3K in the ERK pathway in osteoblasts, offering a potential new therapeutic strategy for the treatment of NF1

Multicolor Photometric Observation of Lightning from Space: Comparison with Radio Measurements

This study evaluates the effectiveness of spectrophotometric measurements from space in revealing properties of lightning flash. The multicolor optical waveform data obtained by FORMOSAT-2/Imager of Sprites and Upper Atmospheric Lightning (ISUAL) were analyzed in relation to National Lightning Detection Network (NLDN), North Alabama Lightning Mapping Array (LMA). As of July 2011, we found six lightning events which were observed by ISUAL and North Alabama LMA. In two of these events, NLDN showed clear positive cloud-to-ground (CG) discharges with peak current of +139.9 kA and +41.6 kA and, around that time, LMA showed continuous intra-cloud (IC) leader activities at 4-6 km altitudes. ISUAL also observed consistent optical waveforms of the IC and CG components and, interestingly, it was found that the blue/red spectral ratio clearly decreased by a factor of 1.5-2.5 at the time of CG discharges. Other four lightning events in which NLDN did not detect any CG discharges were also investigated, but such a feature was not found in any of these cases. These results suggest that the optical color of CG component is more reddish than that of IC component and we explain this as a result of more effective Rayleigh scattering in blue light emissions coming from lower-altitude light source. This finding suggests that spectral measurements could be a new useful technique to characterize ICs and CGs from space. In this talk, we will also present a result from lightning statistical analysis of ISUAL spectrophotometric data and ULF magnetic data

Genome-Wide Binding Map of the HIV-1 Tat Protein to the Human Genome

The HIV-1 Trans-Activator of Transcription (Tat) protein binds to multiple host cellular factors and greatly enhances the level of transcription of the HIV genome. While Tat's control of viral transcription is well-studied, much less is known about the interaction of Tat with the human genome. Here, we report the genome-wide binding map of Tat to the human genome in Jurkat T cells using chromatin immunoprecipitation combined with next-generation sequencing. Surprisingly, we found that ∼53% of the Tat target regions are within DNA repeat elements, greater than half of which are Alu sequences. The remaining target regions are located in introns and distal intergenic regions; only ∼7% of Tat-bound regions are near transcription start sites (TSS) at gene promoters. Interestingly, Tat binds to promoters of genes that, in Jurkat cells, are bound by the ETS1 transcription factor, the CBP histone acetyltransferase and/or are enriched for histone H3 lysine 4 tri-methylation (H3K4me3) and H3K27me3. Tat binding is associated with genes enriched with functions in T cell biology and immune response. Our data reveal that Tat's interaction with the host genome is more extensive than previously thought, with potentially important implications for the viral life cycle

Novel molecular approach to define pest species status and tritrophic interactions from historical Bemisia specimens

Museum specimens represent valuable genomic resources for understanding host-endosymbiont/parasitoid evolutionary relationships, resolving species complexes and nomenclatural problems. However, museum collections suffer DNA degradation, making them challenging for molecular-based studies. Here, the mitogenomes of a single 1912 Sri Lankan Bemisia emiliae cotype puparium, and of a 1942 Japanese Bemisia puparium are characterised using a Next-Generation Sequencing approach. Whiteflies are small sap-sucking insects including B. tabaci pest species complex. Bemisia emiliae’s draft mitogenome showed a high degree of homology with published B. tabaci mitogenomes, and exhibited 98–100% partial mitochondrial DNA Cytochrome Oxidase I (mtCOI) gene identity with the B. tabaci species known as Asia II-7. The partial mtCOI gene of the Japanese specimen shared 99% sequence identity with the Bemisia ‘JpL’ genetic group. Metagenomic analysis identified bacterial sequences in both Bemisia specimens, while hymenopteran sequences were also identified in the Japanese Bemisia puparium, including complete mtCOI and rRNA genes, and various partial mtDNA genes. At 88–90% mtCOI sequence identity to Aphelinidae wasps, we concluded that the 1942 Bemisia nymph was parasitized by an Eretmocerus parasitoid wasp. Our approach enables the characterisation of genomes and associated metagenomic communities of museum specimens using 1.5 ng gDNA, and to infer historical tritrophic relationships in Bemisia whiteflies.© The Author(s) 2017. This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The attached file is the published pdf

Characterization and Comparison of the Tissue-Related Modules in Human and Mouse

BACKGROUND: Due to the advances of high throughput technology and data-collection approaches, we are now in an unprecedented position to understand the evolution of organisms. Great efforts have characterized many individual genes responsible for the interspecies divergence, yet little is known about the genome-wide divergence at a higher level. Modules, serving as the building blocks and operational units of biological systems, provide more information than individual genes. Hence, the comparative analysis between species at the module level would shed more light on the mechanisms underlying the evolution of organisms than the traditional comparative genomics approaches. RESULTS: We systematically identified the tissue-related modules using the iterative signature algorithm (ISA), and we detected 52 and 65 modules in the human and mouse genomes, respectively. The gene expression patterns indicate that all of these predicted modules have a high possibility of serving as real biological modules. In addition, we defined a novel quantity, "total constraint intensity," a proxy of multiple constraints (of co-regulated genes and tissues where the co-regulation occurs) on the evolution of genes in module context. We demonstrate that the evolutionary rate of a gene is negatively correlated with its total constraint intensity. Furthermore, there are modules coding the same essential biological processes, while their gene contents have diverged extensively between human and mouse. CONCLUSIONS: Our results suggest that unlike the composition of module, which exhibits a great difference between human and mouse, the functional organization of the corresponding modules may evolve in a more conservative manner. Most importantly, our findings imply that similar biological processes can be carried out by different sets of genes from human and mouse, therefore, the functional data of individual genes from mouse may not apply to human in certain occasions

A multi-filter enhanced genetic ensemble system for gene selection and sample classification of microarray data

Background: Feature selection techniques are critical to the analysis of high dimensional datasets. This is especially true in gene selection from microarray data which are commonly with extremely high feature-to-sample ratio. In addition to the essential objectives such as to reduce data noise, to reduce data redundancy, to improve sample classification accuracy, and to improve model generalization property, feature selection also helps biologists to focus on the selected genes to further validate their biological hypotheses.Results: In this paper we describe an improved hybrid system for gene selection. It is based on a recently proposed genetic ensemble (GE) system. To enhance the generalization property of the selected genes or gene subsets and to overcome the overfitting problem of the GE system, we devised a mapping strategy to fuse the goodness information of each gene provided by multiple filtering algorithms. This information is then used for initialization and mutation operation of the genetic ensemble system.Conclusion: We used four benchmark microarray datasets (including both binary-class and multi-class classification problems) for concept proving and model evaluation. The experimental results indicate that the proposed multi-filter enhanced genetic ensemble (MF-GE) system is able to improve sample classification accuracy, generate more compact gene subset, and converge to the selection results more quickly. The MF-GE system is very flexible as various combinations of multiple filters and classifiers can be incorporated based on the data characteristics and the user preferences. <br /