Enhancements in nocturnal surface ozone at urban sites in the UK

Analysis of diurnal patterns of surface ozone (O3) at multiple urban sites in the UK shows the occurrence of prominent nocturnal enhancements during the winter months (November–March). Whilst nocturnal surface ozone (NSO) enhancement events have been observed at other locations, this is the first time that such features have been demonstrated to occur in the UK and the second location globally. The observed NSO enhancement events in the UK were found to be so prevalent that they are clearly discernible in monthly diurnal cycles averaged over several years of data. Long-term (2000–2010) analysis of hourly surface ozone data from 18 urban background stations shows a bimodal diurnal variation during the winter months with a secondary nighttime peak around 0300 hours along with the primary daytime peak. For all but one site, the daily maxima NSO concentrations during the winter months exceeded 60 μg/m3 on >20 % of the nights. The highest NSO value recorded was 118 μg/m3. During the months of November, December, and January, the monthly averaged O3 concentrations observed at night (0300 h) even exceeded those observed in the daytime (1300 h). The analysis also shows that these NSO enhancements can last for several hours and were regional in scale, extending across several stations simultaneously. Interestingly, the urban sites in the north of the UK exhibited higher NSO than the sites in the south of the UK, despite their daily maxima being similar. In part, this seems to be related to the sites in the north typically having lower concentrations of nitrogen oxides

Plasticity of the Muscle Stem Cell Microenvironment

Satellite cells (SCs) are adult muscle stem cells capable of repairing damaged and creating new muscle tissue throughout life. Their functionality is tightly controlled by a microenvironment composed of a wide variety of factors, such as numerous secreted molecules and different cell types, including blood vessels, oxygen, hormones, motor neurons, immune cells, cytokines, fibroblasts, growth factors, myofibers, myofiber metabolism, the extracellular matrix and tissue stiffness. This complex niche controls SC biology-quiescence, activation, proliferation, differentiation or renewal and return to quiescence. In this review, we attempt to give a brief overview of the most important players in the niche and their mutual interaction with SCs. We address the importance of the niche to SC behavior under physiological and pathological conditions, and finally survey the significance of an artificial niche both for basic and translational research purposes

W18O49 Nanowires as Ultraviolet Photodetector

Photodetectors in a configuration of field effect transistor were fabricated based on individual W18O49 nanowires. Evaluation of electrical transport behavior indicates that the W18O49 nanowires are n-type semiconductors. The photodetectors show high sensitivity, stability and reversibility to ultraviolet (UV) light. A high photoconductive gain of 104 was obtained, and the photoconductivity is up to 60 nS upon exposure to 312 nm UV light with an intensity of 1.6 mW/cm2. Absorption of oxygen on the surface of W18O49 nanowires has a significant influence on the dark conductivity, and the ambient gas can remarkably change the conductivity of W18O49 nanowire. The results imply that W18O49 nanowires will be promising candidates for fabricating UV photodetectors

Retrospective comparison between a regular and a split-dose protocol of 5-fluorouracil, cisplatin, and mitoxantrone for the treatment of far advanced hepatocellular carcinoma

<p>Abstract</p> <p>Background</p> <p>In patients with advanced hepatocellular carcinoma (HCC), combination chemotherapy using 5- fluorouracil, cisplatin, and mitoxantrone (FMP) could achieve a response rate > 20%, but the beneficial effect was compromised by formidable adverse events. Chemotherapy given in a split-dose manner was associated with reduced toxicities. In this retrospective study, we compared the efficacies and side effects between a regular and a split-dose FMP protocol approved in our medical center.</p> <p>Methods</p> <p>From 2005 to 2008, the clinical data of 84 patients with far advanced HCC, who had either main portal vein thrombosis and/or extrahepatic metastasis, were reviewed. Of them, 65 were treated by either regular (n = 27) or split-dose (n = 38) FMP and had completed at least one therapeutic course. The remaining 19 patients were untreated. Clinical parameters, therapeutic responses, survivals and adverse events were compared.</p> <p>Results</p> <p>The median overall survival was 6.0, 5.2, and 1.5 months, respectively, in patients receiving regular FMP, split-dose FMP, and no treatment (regular versus split-dose group, P = 0.447; regular or split-dose versus untreated group; P < 0.0001). Patients receiving split-dose treatment had a significantly lower risk of grade 3/4 neutropenia (51.9 versus 10.5%, P = 0.0005). When the two treated groups were combined, the median overall survival was 10.6 and 3.8 months respectively for patients achieving disease control and progressive disease (P < 0.001). Cox proportion hazard model identified Child-Pugh stage B (hazard ratio [HR], 2.216; P = 0.006), presence of extrahepatic metastasis (HR, 0.574; P = 0.048), and achievement of disease control (HR, 0.228; P < 0.001) as independent factors associated with overall survival. Logistic regression analysis revealed that anti-hepatitis C virus antibody (odds ratio [OR], 9.219; P = 0.002) tumor size (OR, 0.816; P = 0.036), and previous anti-cancer therapy (OR, 0.195; P = 0.017) were significantly associated with successful disease control.</p> <p>Conclusions</p> <p>Comparable overall survival was observed between patients receiving regular and split-dose FMP therapies. Patients receiving split-dose therapy had a significantly lower risk of grade 3/4 neutropenia. Positive anti-hepatitis C virus antibody, smaller tumor size, and absence of previous anti-cancer therapy were independent predictors for successful disease control.</p

RNAi-mediated silencing of CD147 inhibits tumor cell proliferation, invasion and increases chemosensitivity to cisplatin in SGC7901 cells in vitro

<p>Abstract</p> <p>Background</p> <p>CD147 is a widely distributed cell surface glycoprotein that belongs to the Ig superfamily. CD147 has been implicated in numerous physiological and pathological activities. Enriched on the surface of many tumor cells, CD147 promotes tumor growth, invasion, metastasis and angiogenesis and confers resistance to some chemotherapeutic drugs. In this study, we investigated the possible role of CD147 in the progression of gastric cancer.</p> <p>Methods</p> <p>Short hairpin RNA (shRNA) expressing vectors targeting CD147 were constructed and transfected into human gastric cancer cells SGC7901 and CD147 expression was monitored by quantitative realtime RT-PCR and Western blot. Cell proliferation, the activities of MMP-2 and MMP-9, the invasive potential and chemosensitivity to cisplatin of SGC7901 cells were determined by MTT, gelatin zymography, Transwell invasion assay and MTT, respectively.</p> <p>Results</p> <p>Down-regulation of CD147 by RNAi approach led to decreased cell proliferation, MMP-2 and MMP-9 activities and invasive potential of SGC7901 cells as well as increased chemosensitivity to cisplatin.</p> <p>Conclusion</p> <p>CD147 involves in proliferation, invasion and chemosensitivity of human gastric cancer cell line SGC7901, indicating that CD147 may be a promising therapeutic target for gastric cancer.</p

Development of a Surface Plasmon Resonance Biosensor for Real-Time Detection of Osteogenic Differentiation in Live Mesenchymal Stem Cells

Surface plasmon resonance (SPR) biosensors have been recognized as a useful tool and widely used for real-time dynamic analysis of molecular binding affinity because of its high sensitivity to the change of the refractive index of tested objects. The conventional methods in molecular biology to evaluate cell differentiation require cell lysis or fixation, which make investigation in live cells difficult. In addition, a certain amount of cells are needed in order to obtain adequate protein or messenger ribonucleic acid for various assays. To overcome this limitation, we developed a unique SPR-based biosensing apparatus for real-time detection of cell differentiation in live cells according to the differences of optical properties of the cell surface caused by specific antigen-antibody binding. In this study, we reported the application of this SPR-based system to evaluate the osteogenic differentiation of mesenchymal stem cells (MSCs). OB-cadherin expression, which is up-regulated during osteogenic differentiation, was targeted under our SPR system by conjugating antibodies against OB-cadherin on the surface of the object. A linear relationship between the duration of osteogenic induction and the difference in refractive angle shift with very high correlation coefficient was observed. To sum up, the SPR system and the protocol reported in this study can rapidly and accurately define osteogenic maturation of MSCs in a live cell and label-free manner with no need of cell breakage. This SPR biosensor will facilitate future advances in a vast array of fields in biomedical research and medical diagnosis

Y-Chromosome Evidence for Common Ancestry of Three Chinese Populations with a High Risk of Esophageal Cancer

High rates of esophageal cancer (EC) are found in people of the Henan Taihang Mountain, Fujian Minnan, and Chaoshan regions of China. Historical records describe great waves of populations migrating from north-central China (the Henan and Shanxi Hans) through coastal Fujian Province to the Chaoshan plain. Although these regions are geographically distant, we hypothesized that EC high-risk populations in these three areas could share a common ancestry. Accordingly, we used 16 East Asian-specific Y-chromosome biallelic markers (single nucleotide polymorphisms; Y-SNPs) and six Y-chromosome short tandem repeat (Y-STR) loci to infer the origin of the EC high-risk Chaoshan population (CSP) and the genetic relationship between the CSP and the EC high-risk Henan Taihang Mountain population (HTMP) and Fujian population (FJP). The predominant haplogroups in these three populations are O3*, O3e*, and O3e1, with no significant difference between the populations in the frequency of these genotypes. Frequency distribution and principal component analysis revealed that the CSP is closely related to the HTMP and FJP, even though the former is geographically nearer to other populations (Guangfu and Hakka clans). The FJP is between the CSP and HTMP in the principal component plot. The CSP, FJP and HTMP are more closely related to Chinese Hans than to minorities, except Manchu Chinese, and are descendants of Sino-Tibetans, not Baiyues. Correlation analysis, hierarchical clustering analysis, and phylogenetic analysis (neighbor-joining tree) all support close genetic relatedness among the CSP, FJP and HTMP. The network for haplogroup O3 (including O3*, O3e* and O3e1) showed that the HTMP have highest STR haplotype diversity, suggesting that the HTMP may be a progenitor population for the CSP and FJP. These findings support the potentially important role of shared ancestry in understanding more about the genetic susceptibility in EC etiology in high-risk populations and have implications for determining the molecular basis of this disease

Gene ontology based transfer learning for protein subcellular localization

<p>Abstract</p> <p>Background</p> <p>Prediction of protein subcellular localization generally involves many complex factors, and using only one or two aspects of data information may not tell the true story. For this reason, some recent predictive models are deliberately designed to integrate multiple heterogeneous data sources for exploiting multi-aspect protein feature information. Gene ontology, hereinafter referred to as <it>GO</it>, uses a controlled vocabulary to depict biological molecules or gene products in terms of biological process, molecular function and cellular component. With the rapid expansion of annotated protein sequences, gene ontology has become a general protein feature that can be used to construct predictive models in computational biology. Existing models generally either concatenated the <it>GO </it>terms into a flat binary vector or applied majority-vote based ensemble learning for protein subcellular localization, both of which can not estimate the individual discriminative abilities of the three aspects of gene ontology.</p> <p>Results</p> <p>In this paper, we propose a Gene Ontology Based Transfer Learning Model (<it>GO-TLM</it>) for large-scale protein subcellular localization. The model transfers the signature-based homologous <it>GO </it>terms to the target proteins, and further constructs a reliable learning system to reduce the adverse affect of the potential false <it>GO </it>terms that are resulted from evolutionary divergence. We derive three <it>GO </it>kernels from the three aspects of gene ontology to measure the <it>GO </it>similarity of two proteins, and derive two other spectrum kernels to measure the similarity of two protein sequences. We use simple non-parametric cross validation to explicitly weigh the discriminative abilities of the five kernels, such that the time & space computational complexities are greatly reduced when compared to the complicated semi-definite programming and semi-indefinite linear programming. The five kernels are then linearly merged into one single kernel for protein subcellular localization. We evaluate <it>GO-TLM </it>performance against three baseline models: <it>MultiLoc, MultiLoc-GO </it>and <it>Euk-mPLoc </it>on the benchmark datasets the baseline models adopted. 5-fold cross validation experiments show that <it>GO-TLM </it>achieves substantial accuracy improvement against the baseline models: 80.38% against model <it>Euk-mPLoc </it>67.40% with <it>12.98% </it>substantial increase; 96.65% and 96.27% against model <it>MultiLoc-GO </it>89.60% and 89.60%, with <it>7.05% </it>and <it>6.67% </it>accuracy increase on dataset <it>MultiLoc plant </it>and dataset <it>MultiLoc animal</it>, respectively; 97.14%, 95.90% and 96.85% against model <it>MultiLoc-GO </it>83.70%, 90.10% and 85.70%, with accuracy increase <it>13.44%</it>, <it>5.8% </it>and <it>11.15% </it>on dataset <it>BaCelLoc plant</it>, dataset <it>BaCelLoc fungi </it>and dataset <it>BaCelLoc animal </it>respectively. For <it>BaCelLoc </it>independent sets, <it>GO-TLM </it>achieves 81.25%, 80.45% and 79.46% on dataset <it>BaCelLoc plant holdout</it>, dataset <it>BaCelLoc plant holdout </it>and dataset <it>BaCelLoc animal holdout</it>, respectively, as compared against baseline model <it>MultiLoc-GO </it>76%, 60.00% and 73.00%, with accuracy increase <it>5.25%</it>, <it>20.45% </it>and <it>6.46%</it>, respectively.</p> <p>Conclusions</p> <p>Since direct homology-based <it>GO </it>term transfer may be prone to introducing noise and outliers to the target protein, we design an explicitly weighted kernel learning system (called Gene Ontology Based Transfer Learning Model, <it>GO-TLM</it>) to transfer to the target protein the known knowledge about related homologous proteins, which can reduce the risk of outliers and share knowledge between homologous proteins, and thus achieve better predictive performance for protein subcellular localization. Cross validation and independent test experimental results show that the homology-based <it>GO </it>term transfer and explicitly weighing the <it>GO </it>kernels substantially improve the prediction performance.</p