Role of Bryophytes And Tree Canopy In Mist Trapping In Mt. Marsabit Forest

Mt. Marsabit forest, is an isolated Tropical Rain Forest, oasis, located 560 Km north of Nairobi, Kenya; and surrounded by deserts of Chalbi, Kaisut and Bubisa. The forest is under threat mainly by anthropogenic effects before the forest biota is studied. This research was to investigate the role of bryophytes and forest canopy in trapping mist water, for supporting Mt. Marsabit forest community development. The experiments were located 1450 m. asl windward of Mt. Marsabit. Stem simulates of varying circumferences were dressed with bryophytes and bryophytes mounted mist traps were located on same site. The water retention capacity was 6 times own dry weight with a hygroscopic capacity of 13%. The mist water trapped by bryophytes was 8 liters of water / m ²/ mist day translating to 196 mm of rainfall per year. The stem simulates of 20 cm circumference, 50 cm long trapped 30 ml of water per mist day using surface area of 0.05 m² translating to 914 ml of water per m² per mist day equivalent to 65 mm of rainfall per year. The study revealed that vegetation is an important catchments area surface (attract rain) whose loss leads to reduced water resource for plant and animal use; climate moderation. Further, mist water is the compensation factor that supports the forest ecosystem. The cooling effect of water is lost with the loss of vegetation. The loss of water leads to drier environment with climate change as the ripple effect. The change in river regimes and the general hydrologic cycle is due to loss in vegetation, where mist water was not accounted for by science. The mist water resource is renewable water resource that can be used to recharge ground water, conserve and rehabilitate forest and provide water for domestic, agricultural and industrial use

Automatic identification of epileptic and background EEG signals using frequency domain parameters

The analysis of electroencephalograms continues to be a problem due to our limited understanding of the signal origin. This limited understanding leads to ill-defined models, which in turn make it hard to design effective evaluation methods. Despite these shortcomings, electroencephalogram analysis is a valuable tool in the evaluation of neurological disorders and the evaluation of overall cerebral activity. We compared different model based power spectral density estimation methods and different classification methods. Specifically, we used the autoregressive moving average as well as from Yule-Walker and Burg's methods, to extract the power density spectrum from representative signal samples. Local maxima and minima were detected from these spectra. In this paper, the locations of these extrema are used as input to different classifiers. The three classifiers we used were: Gaussian mixture model, artificial neural network, and support vector machine. The classification results are documented with confusion matrices and compared with receiver operating characteristic curves. We found that Burg's method for spectrum estimation together with a support vector machine classifier yields the best classification results. This combination reaches a classification rate of 93.33%, the sensitivity is 98.33% and the specificy is 96.67%

High time-resolution simulation of E. coli on hands reveals large variation in microbial exposures amongst Vietnamese farmers using human excreta for agriculture

Infectious disease transmission is frequently mediated by the environment, where people's movements through and interactions with the environment dictate risks of infection and/or illness. Capturing these interactions, and quantifying their importance, offers important insights into effective interventions. In this study, we capture high time-resolution activity data for twenty-five Vietnamese farmers during collection and land application of human excreta for agriculture. Although human excreta use improves productivity, the use increases risks of enteric infections for both farmers and end users. In our study, the activity data are integrated with environmental microbial sampling data into a stochastic-mechanistic simulation of E. coli contamination on hands and E. coli ingested. Results from the study include frequent and variable contact rates for farmers' hands (from 34 to 1344 objects contacted per hour per hand), including highly variable hand-to-mouth contact rates (from 0 to 9 contacts per hour per hand). The frequency of hand-to-mouth contacts was substantially lower than the widely-used frequency previously reported for U.S. Office Workers. Environmental microbial contamination data highlighted ubiquitous E. coli contamination in the environment, including excreta, hands, toilet pit, handheld tools, soils, surfaces, and water. Results from the simulation suggest dynamic changes in E. coli contamination on hands, and wide variation in hand contamination and E. coli ingested amongst the farmers studied. Sensitivity analysis suggests that E. coli contamination on hands and ingested doses are most influenced by contamination of handheld tools, excreta, and the toilet pit as well as by frequency of hand-to-mouth contacts. The study findings are especially relevant given the context: no farmers reported adequate storage time of human excreta, and personal protective mask availability did not prevent hand-to-mouth contacts. Integrating high time-resolution activity data into exposure assessments highlights variation in exposures amongst farmers, and offers greater insight into effective interventions and their potential impacts

Inferring Gene-Phenotype Associations via Global Protein Complex Network Propagation

BACKGROUND: Phenotypically similar diseases have been found to be caused by functionally related genes, suggesting a modular organization of the genetic landscape of human diseases that mirrors the modularity observed in biological interaction networks. Protein complexes, as molecular machines that integrate multiple gene products to perform biological functions, express the underlying modular organization of protein-protein interaction networks. As such, protein complexes can be useful for interrogating the networks of phenome and interactome to elucidate gene-phenotype associations of diseases. METHODOLOGY/PRINCIPAL FINDINGS: We proposed a technique called RWPCN (Random Walker on Protein Complex Network) for predicting and prioritizing disease genes. The basis of RWPCN is a protein complex network constructed using existing human protein complexes and protein interaction network. To prioritize candidate disease genes for the query disease phenotypes, we compute the associations between the protein complexes and the query phenotypes in their respective protein complex and phenotype networks. We tested RWPCN on predicting gene-phenotype associations using leave-one-out cross-validation; our method was observed to outperform existing approaches. We also applied RWPCN to predict novel disease genes for two representative diseases, namely, Breast Cancer and Diabetes. CONCLUSIONS/SIGNIFICANCE: Guilt-by-association prediction and prioritization of disease genes can be enhanced by fully exploiting the underlying modular organizations of both the disease phenome and the protein interactome. Our RWPCN uses a novel protein complex network as a basis for interrogating the human phenome-interactome network. As the protein complex network can capture the underlying modularity in the biological interaction networks better than simple protein interaction networks, RWPCN was found to be able to detect and prioritize disease genes better than traditional approaches that used only protein-phenotype associations

Grape Seed Proanthocyanidins Inhibit the Invasiveness of Human HNSCC Cells by Targeting EGFR and Reversing the Epithelial-To-Mesenchymal Transition

Head and neck squamous cell carcinoma (HNSCC) is responsible for approximately 20,000 deaths per year in the United States. Most of the deaths are due to the metastases. To develop more effective strategies for the prevention of metastasis of HNSCC cells, we have determined the effect of grape seed proanthocyanidins (GSPs) on the invasive potential of HNSCC cell and the mechanisms underlying these effects using OSC19 cells as an in vitro model. Using cell invasion assays, we established that treatment of the OSC19 cells with GSPs resulted in a dose-dependent inhibition of cell invasion. EGFR is over-expressed in 90% of HNSCCs and the EGFR inhibitors, erlotinib and gefitinib, are being explored as therapies for this disease. We found that GSPs treatment reduced the levels of expression of EGFR in the OSC19 cells as well as reducing the activation of NF-κB/p65, a downstream target of EGFR, and the expression of NF-κB-responsive proteins. GSPs treatment also reduced the activity of ERK1/2, an upstream regulator of NF-κB and treatment of the cells with caffeic acid phenethyl ester, an inhibitor of NF-κB, inhibited cell invasion. Overexpression of EGFR and high NF-κB activity play a key role in the epithelial-to-mesenchymal transition, which is of critical importance in the processes underlying metastasis, and we found treatment with GSPs enhanced the levels of epithelial (E-cadherin, cytokeratins and desmoglein-2) and reduced the levels of mesenchymal (vimentin, fibronectin, N-cadherin and Slug) biomarkers in the OSC19 cells. These results indicate that GSPs have the ability to inhibit HNSCC cell invasion, and do so by targeting the expression of EGFR and activation of NF-κB as well as inhibiting the epithelial-to-mesenchymal transition

Molecular Prognostic Prediction for Locally Advanced Nasopharyngeal Carcinoma by Support Vector Machine Integrated Approach

BACKGROUND:Accurate prognostication of locally advanced nasopharyngeal carcinoma (NPC) will benefit patients for tailored therapy. Here, we addressed this issue by developing a mathematical algorithm based on support vector machine (SVM) through integrating the expression levels of multi-biomarkers. METHODOLOGY/PRINCIPAL FINDINGS:Ninety-seven locally advanced NPC patients in a randomized controlled trial (RCT), consisting of 48 cases serving as training set and 49 cases as testing set of SVM models, with 5-year follow-up were studied. We designed SVM models by selecting the variables from 38 tissue molecular biomarkers, which represent 6 tumorigenesis signaling pathways, and 3 EBV-related serological biomarkers. We designed 3 SVM models to refine prognosis of NPC with 5-year follow-up. The SVM1 displayed highly predictive sensitivity (sensitivity, specificity were 88.0% and 81.9%, respectively) by integrating the expression of 7 molecular biomarkers. The SVM2 model showed highly predictive specificity (sensitivity, specificity were 84.0% and 94.5%, respectively) by grouping the expression level of 12 molecular biomarkers and 3 EBV-related serological biomarkers. The SVM3 model, constructed by combination SVM1 with SVM2, displayed a high predictive capacity (sensitivity, specificity were 88.0% and 90.3%, respectively). We found that 3 SVM models had strong power in classification of prognosis. Moreover, Cox multivariate regression analysis confirmed these 3 SVM models were all the significant independent prognostic model for overall survival in testing set and overall patients. CONCLUSIONS/SIGNIFICANCE:Our SVM prognostic models designed in the RCT displayed strong power in refining patient prognosis for locally advanced NPC, potentially directing future target therapy against the related signaling pathways

Positional Cloning of a Type 2 Diabetes Quantitative Trait Locus; Tomosyn-2, a Negative Regulator of Insulin Secretion

We previously mapped a type 2 diabetes (T2D) locus on chromosome 16 (Chr 16) in an F2 intercross from the BTBR T (+) tf (BTBR) Lepob/ob and C57BL/6 (B6) Lepob/ob mouse strains. Introgression of BTBR Chr 16 into B6 mice resulted in a consomic mouse with reduced fasting plasma insulin and elevated glucose levels. We derived a panel of sub-congenic mice and narrowed the diabetes susceptibility locus to a 1.6 Mb region. Introgression of this 1.6 Mb fragment of the BTBR Chr 16 into lean B6 mice (B6.16BT36–38) replicated the phenotypes of the consomic mice. Pancreatic islets from the B6.16BT36–38 mice were defective in the second phase of the insulin secretion, suggesting that the 1.6 Mb region encodes a regulator of insulin secretion. Within this region, syntaxin-binding protein 5-like (Stxbp5l) or tomosyn-2 was the only gene with an expression difference and a non-synonymous coding single nucleotide polymorphism (SNP) between the B6 and BTBR alleles. Overexpression of the b-tomosyn-2 isoform in the pancreatic β-cell line, INS1 (832/13), resulted in an inhibition of insulin secretion in response to 3 mM 8-bromo cAMP at 7 mM glucose. In vitro binding experiments showed that tomosyn-2 binds recombinant syntaxin-1A and syntaxin-4, key proteins that are involved in insulin secretion via formation of the SNARE complex. The B6 form of tomosyn-2 is more susceptible to proteasomal degradation than the BTBR form, establishing a functional role for the coding SNP in tomosyn-2. We conclude that tomosyn-2 is the major gene responsible for the T2D Chr 16 quantitative trait locus (QTL) we mapped in our mouse cross. Our findings suggest that tomosyn-2 is a key negative regulator of insulin secretion

HIF-Independent Regulation of Thioredoxin Reductase 1 Contributes to the High Levels of Reactive Oxygen Species Induced by Hypoxia

Cellular adaptation to hypoxic conditions mainly involves transcriptional changes in which hypoxia inducible factors (HIFs) play a critical role. Under hypoxic conditions, HIF protein is stabilized due to inhibition of the activity of prolyl hydroxylases (EGLNs). Because the reaction carried out by these enzymes uses oxygen as a co-substrate it is generally accepted that the hypoxic inhibition of EGLNs is due to the reduction in oxygen levels. However, several studies have reported that hypoxic generation of mitochondrial reactive oxygen species (ROS) is required for HIF stabilization. Here, we show that hypoxia downregulates thioredoxin reductase 1 (TR1) mRNA and protein levels. This hypoxic TR1 regulation is HIF independent, as HIF stabilization by EGLNs inhibitors does not affect TR1 expression and HIF deficiency does not block TR1 hypoxic-regulation, and it has an effect on TR1 function, as hypoxic conditions also reduce TR1 activity. We found that, when cultured under hypoxic conditions, TR1 deficient cells showed a larger accumulation of ROS compared to control cells, whereas TR1 over-expression was able to block the hypoxic generation of ROS. Furthermore, the changes in ROS levels observed in TR1 deficient or TR1 over-expressing cells did not affect HIF stabilization or function. These results indicate that hypoxic TR1 down-regulation is important in maintaining high levels of ROS under hypoxic conditions and that HIF stabilization and activity do not require hypoxic generation of ROS

Dimerization of Translationally Controlled Tumor Protein Is Essential For Its Cytokine-Like Activity

BACKGROUND:Translationally Controlled Tumor Protein (TCTP) found in nasal lavage fluids of allergic patients was named IgE-dependent histamine-releasing factor (HRF). Human recombinant HRF (HrHRF) has been recently reported to be much less effective than HRF produced from activated mononuclear cells (HRFmn). METHODS AND FINDINGS:We found that only NH(2)-terminal truncated, but not C-terminal truncated, TCTP shows cytokine releasing activity compared to full-length TCTP. Interestingly, only NH(2)-terminal truncated TCTP, unlike full-length TCTP, forms dimers through intermolecular disulfide bonds. We tested the activity of dimerized full-length TCTP generated by fusing it to rabbit Fc region. The untruncated-full length protein (Fc-HrTCTP) was more active than HrTCTP in BEAS-2B cells, suggesting that dimerization of TCTP, rather than truncation, is essential for the activation of TCTP in allergic responses. We used confocal microscopy to evaluate the affinity of TCTPs to its putative receptor. We detected stronger fluorescence in the plasma membrane of BEAS-2B cells incubated with Del-N11TCTP than those incubated with rat recombinant TCTP (RrTCTP). Allergenic activity of Del-N11TCTP prompted us to see whether the NH(2)-terminal truncated TCTP can induce allergic airway inflammation in vivo. While RrTCTP had no influence on airway inflammation, Del-N11TCTP increased goblet cell hyperplasia in both lung and rhinal cavity. The dimerized protein was found in sera from allergic patients, and bronchoalveolar lavage fluids from airway inflamed mice. CONCLUSIONS:Dimerization of TCTP seems to be essential for its cytokine-like activity. Our study has potential to enhance the understanding of pathogenesis of allergic disease and provide a target for allergic drug development

Friedreich's Ataxia (GAA)n•(TTC)n Repeats Strongly Stimulate Mitotic Crossovers in Saccharomyces cerevisae

Expansions of trinucleotide GAA•TTC tracts are associated with the human disease Friedreich's ataxia, and long GAA•TTC tracts elevate genome instability in yeast. We show that tracts of (GAA)230•(TTC)230 stimulate mitotic crossovers in yeast about 10,000-fold relative to a “normal” DNA sequence; (GAA)n•(TTC)n tracts, however, do not significantly elevate meiotic recombination. Most of the mitotic crossovers are associated with a region of non-reciprocal transfer of information (gene conversion). The major class of recombination events stimulated by (GAA)n•(TTC)n tracts is a tract-associated double-strand break (DSB) that occurs in unreplicated chromosomes, likely in G1 of the cell cycle. These findings indicate that (GAA)n•(TTC)n tracts can be a potent source of loss of heterozygosity in yeast