Phytoscreening and phytoextraction of heavy metals at Danish polluted sites using willow and poplar trees

The main purpose of this study was to determine typical concentrations of heavy metals (HM) in wood from willows and poplars, in order to test the feasibility of phytoscreening and phytoextraction of HM. Samples were taken from one strongly, one moderately, and one slightly polluted site and from three reference sites. Wood from both tree species had similar background concentrations at 0.5 mg kg(−1) for cadmium (Cd), 1.6 mg kg(−1) for copper (Cu), 0.3 mg kg(−1) for nickel (Ni), and 25 mg kg(−1) for zinc (Zn). Concentrations of chromium (Cr) and lead (Pb) were below or close to detection limit. Concentrations in wood from the highly polluted site were significantly elevated, compared to references, in particular for willow. The conclusion from these results is that tree coring could be used successfully to identify strongly heavy metal-polluted soil for Cd, Cu, Ni, Zn, and that willow trees were superior to poplars, except when screening for Ni. Phytoextraction of HMs was quantified from measured concentration in wood at the most polluted site. Extraction efficiencies were best for willows and Cd, but below 0.5 % over 10 years, and below 1 ‰ in 10 years for all other HMs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11356-013-2085-z) contains supplementary material, which is available to authorized users

Insights gained from the reverse engineering of gene networks in keloid fibroblasts

<p>Abstract</p> <p>Background</p> <p>Keloids are protrusive claw-like scars that have a propensity to recur even after surgery, and its molecular etiology remains elusive. The goal of reverse engineering is to infer gene networks from observational data, thus providing insight into the inner workings of a cell. However, most attempts at modeling biological networks have been done using simulated data. This study aims to highlight some of the issues involved in working with experimental data, and at the same time gain some insights into the transcriptional regulatory mechanism present in keloid fibroblasts.</p> <p>Methods</p> <p>Microarray data from our previous study was combined with microarray data obtained from the literature as well as new microarray data generated by our group. For the physical approach, we used the fREDUCE algorithm for correlating expression values to binding motifs. For the influence approach, we compared the Bayesian algorithm BANJO with the information theoretic method ARACNE in terms of performance in recovering known influence networks obtained from the KEGG database. In addition, we also compared the performance of different normalization methods as well as different types of gene networks.</p> <p>Results</p> <p>Using the physical approach, we found consensus sequences that were active in the keloid condition, as well as some sequences that were responsive to steroids, a commonly used treatment for keloids. From the influence approach, we found that BANJO was better at recovering the gene networks compared to ARACNE and that transcriptional networks were better suited for network recovery compared to cytokine-receptor interaction networks and intracellular signaling networks. We also found that the NFKB transcriptional network that was inferred from normal fibroblast data was more accurate compared to that inferred from keloid data, suggesting a more robust network in the keloid condition.</p> <p>Conclusions</p> <p>Consensus sequences that were found from this study are possible transcription factor binding sites and could be explored for developing future keloid treatments or for improving the efficacy of current steroid treatments. We also found that the combination of the Bayesian algorithm, RMA normalization and transcriptional networks gave the best reconstruction results and this could serve as a guide for future influence approaches dealing with experimental data.</p

Pollen, biomarker and stable isotope evidence of late Quaternary environmental change at Lake McKenzie, southeast Queensland

Unravelling links between climate change and vegetation response during the Quaternary is important if the climate–environment interactions of modern systems are to be fully understood. Using a sediment core from Lake McKenzie, Fraser Island, we reconstruct changes in the lake ecosystem and surrounding vegetation over the last ca. 36.9 cal kyr. Evidence is drawn from multiple sources, including pollen, micro-charcoal, biomarker and stable isotope (C and N) analyses, and is used to gain a better understanding of the nature and timing of past ecological changes that have occurred at the site. The glacial period of the record, from ca. 36.9 to 18.3 cal kyr BP, is characterised by an increased abundance of plants of the aquatic and littoral zone, indicating lower lake water levels. High abundance of biomarkers and microfossils of the colonial green alga Botryococcus occurred at this time and included large variation in individual botryococcene d13C values. A slowing or ceasing of sediment accumulation occurred during the time period from ca. 18.3 to 14.0 cal kyr BP. By around 14.0 cal kyr BP fire activity in the area was reduced, as was abundance of littoral plants and terrestrial herbs, suggesting wetter conditions from that time. The Lake McKenzie pollen record conforms to existing records from Fraser Island by containing evidence of a period of reduced effective precipitation that commenced in the mid-Holocene

RegNetB: Predicting Relevant Regulator-Gene Relationships in Localized Prostate Tumor Samples

<p>Abstract</p> <p>Background</p> <p>A central question in cancer biology is what changes cause a healthy cell to form a tumor. Gene expression data could provide insight into this question, but it is difficult to distinguish between a gene that causes a change in gene expression from a gene that is affected by this change. Furthermore, the proteins that regulate gene expression are often themselves not regulated at the transcriptional level. Here we propose a Bayesian modeling framework we term RegNetB that uses mechanistic information about the gene regulatory network to distinguish between factors that cause a change in expression and genes that are affected by the change. We test this framework using human gene expression data describing localized prostate cancer progression.</p> <p>Results</p> <p>The top regulatory relationships identified by RegNetB include the regulation of RLN1, RLN2, by PAX4, the regulation of ACPP (PAP) by JUN, BACH1 and BACH2, and the co-regulation of PGC and GDF15 by MAZ and TAF8. These target genes are known to participate in tumor progression, but the suggested regulatory roles of PAX4, BACH1, BACH2, MAZ and TAF8 in the process is new.</p> <p>Conclusion</p> <p>Integrating gene expression data and regulatory topologies can aid in identifying potentially causal mechanisms for observed changes in gene expression.</p

Theoretical analysis of the dose dependence of the oxygen enhancement ratio and its relevance for clinical applications

<p>Abstract</p> <p>Background</p> <p>The increased resistance of hypoxic cells to ionizing radiation is usually believed to be the primary reason for treatment failure in tumors with oxygen-deficient areas. This oxygen effect can be expressed quantitatively by the oxygen enhancement ratio (OER). Here we investigate theoretically the dependence of the OER on the applied local dose for different types of ionizing irradiation and discuss its importance for clinical applications in radiotherapy for two scenarios: small dose variations during hypoxia-based dose painting and larger dose changes introduced by altered fractionation schemes.</p> <p>Methods</p> <p>Using the widespread Alper-Howard-Flanders and standard linear-quadratic (LQ) models, OER calculations are performed for T1 human kidney and V79 Chinese hamster cells for various dose levels and various hypoxic oxygen partial pressures (pO2) between 0.01 and 20 mmHg as present in clinical situations <it>in vivo</it>. Our work comprises the analysis for both low linear energy transfer (LET) treatment with photons or protons and high-LET treatment with heavy ions. A detailed analysis of experimental data from the literature with respect to the dose dependence of the oxygen effect is performed, revealing controversial opinions whether the OER increases, decreases or stays constant with dose.</p> <p>Results</p> <p>The behavior of the OER with dose per fraction depends primarily on the ratios of the LQ parameters alpha and beta under hypoxic and aerobic conditions, which themselves depend on LET, pO2 and the cell or tissue type. According to our calculations, the OER variations with dose <it>in vivo </it>for low-LET treatments are moderate, with changes in the OER up to 11% for dose painting (1 or 3 Gy per fraction compared to 2 Gy) and up to 22% in hyper-/hypofractionation (0.5 or 20 Gy per fraction compared to 2 Gy) for oxygen tensions between 0.2 and 20 mmHg typically measured clinically in hypoxic tumors. For extremely hypoxic cells (0.01 mmHg), the dose dependence of the OER becomes more pronounced (up to 36%). For high LET, OER variations up to 4% for the whole range of oxygen tensions between 0.01 and 20 mmHg were found, which were much smaller than for low LET.</p> <p>Conclusions</p> <p>The formalism presented in this paper can be used for various tissue and radiation types to estimate OER variations with dose and help to decide in clinical practice whether some dose changes in dose painting or in fractionation can bring more benefit in terms of the OER in the treatment of a specific hypoxic tumor.</p

Musculoskeletal symptoms of the upper extremities and the neck: A cross-sectional study on prevalence and symptom-predicting factors at visual display terminal (VDT) workstations

<p>Abstract</p> <p>Background</p> <p>The aim of this study was to determine the prevalence and the predictors of musculoskeletal symptoms in the upper extremities and neck at visual display terminal (VDT) workstations.</p> <p>Methods</p> <p>In a cross-sectional study 1,065 employees working at VDT > 1 h/d completed a standardised questionnaire. Workstation conditions were documented in a standardised checklist, and a subgroup of 82 employees underwent a physical examination.</p> <p>Results</p> <p>Using the Nordic Questionnaire, the 12-month prevalence of symptoms of the neck, shoulder region, hand/wrist, or elbow/lower arm was 55%, 38%, 21%, and 15% respectively. The duration of VDT work had a significant impact on the frequency of neck symptoms in employees performing such work > 6 h/d.</p> <p>Conclusion</p> <p>With regard to musculoskeletal symptoms of the upper extremities, preventive measures at VDT workstations should be focused on neck and shoulder symptoms (e.g. ergonomic measures, breaks to avoid sitting over long periods).</p

ApoB siRNA-induced Liver Steatosis is Resistant to Clearance by the Loss of Fatty Acid Transport Protein 5 (Fatp5)

The association between hypercholesterolemia and elevated serum apolipoprotein B (APOB) has generated interest in APOB as a therapeutic target for patients at risk of developing cardiovascular disease. In the clinic, mipomersen, an antisense oligonucleotide (ASO) APOB inhibitor, was associated with a trend toward increased hepatic triglycerides, and liver steatosis remains a concern. We found that siRNA-mediated knockdown of ApoB led to elevated hepatic triglycerides and liver steatosis in mice engineered to exhibit a human-like lipid profile. Many genes required for fatty acid synthesis were reduced, suggesting that the observed elevation in hepatic triglycerides is maintained by the cell through fatty acid uptake as opposed to fatty acid synthesis. Fatty acid transport protein 5 (Fatp5/Slc27a5) is required for long chain fatty acid (LCFA) uptake and bile acid reconjugation by the liver. Fatp5 knockout mice exhibited lower levels of hepatic triglycerides due to decreased fatty acid uptake, and shRNA-mediated knockdown of Fatp5 protected mice from diet-induced liver steatosis. Here, we evaluated if siRNA-mediated knockdown of Fatp5 was sufficient to alleviate ApoB knockdown-induced steatosis. We determined that, although Fatp5 siRNA treatment was sufficient to increase the proportion of unconjugated bile acids 100-fold, consistent with FATP5's role in bile acid reconjugation, Fatp5 knockdown failed to influence the degree, zonal distribution, or composition of the hepatic triglycerides that accumulated following ApoB siRNA treatment

PathFinder: mining signal transduction pathway segments from protein-protein interaction networks

<p>Abstract</p> <p>Background</p> <p>A Signal transduction pathway is the chain of processes by which a cell converts an extracellular signal into a response. In most unicellular organisms, the number of signal transduction pathways influences the number of ways the cell can react and respond to the environment. Discovering signal transduction pathways is an arduous problem, even with the use of systematic genomic, proteomic and metabolomic technologies. These techniques lead to an enormous amount of data and how to interpret and process this data becomes a challenging computational problem.</p> <p>Results</p> <p>In this study we present a new framework for identifying signaling pathways in protein-protein interaction networks. Our goal is to find biologically significant pathway segments in a given interaction network. Currently, protein-protein interaction data has excessive amount of noise, e.g., false positive and false negative interactions. First, we eliminate false positives in the protein-protein interaction network by integrating the network with microarray expression profiles, protein subcellular localization and sequence information. In addition, protein families are used to repair false negative interactions. Then the characteristics of known signal transduction pathways and their functional annotations are extracted in the form of association rules.</p> <p>Conclusion</p> <p>Given a pair of starting and ending proteins, our methodology returns candidate pathway segments between these two proteins with possible missing links (recovered false negatives). In our study, <it>S. cerevisiae </it>(yeast) data is used to demonstrate the effectiveness of our method.</p