170 resultados para GAMMA-ALUMINA SURFACES


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Serum gamma-glutamyl transferase (GGT) activity is a marker of liver disease which is also prospectively associated with the risk of all-cause mortality, cardiovascular disease, type 2 diabetes and cancers. We have discovered novel loci affecting GGT in a genome-wide association study (rs1497406 in an intergenic region of chromosome 1, P = 3.9 x 10(-8); rs944002 in C14orf73 on chromosome 14, P = 4.7 x 10(-13); rs340005 in RORA on chromosome 15, P = 2.4 x 10(-8)), and a highly significant heterogeneity between adult and adolescent results at the GGT1 locus on chromosome 22 (maximum P(HET) = 5.6 x 10(-12) at rs6519520). Pathway analysis of significant and suggestive single-nucleotide polymorphism associations showed significant overlap between genes affecting GGT and those affecting common metabolic and inflammatory diseases, and identified the hepatic nuclear factor (HNF) family as controllers of a network of genes affecting GGT. Our results reinforce the disease associations of GGT and demonstrate that control by the GGT1 locus varies with age.

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Strategies that confine antibacterial and/or antifouling property to the surface of the implant, by modifying the surface chemistry and morphology or by encapsulating the material in an antibiotic-loaded coating, are most promising as they do not alter bulk integrity of the material. Among them, plasma-assisted modification and catechol chemistry stand out for their ability to modify a wide range of substrates. By controlling processing parameters, plasma environment can be used for surface nano structuring, chemical activation, and deposition of biologically active and passive coatings. Catechol chemistry can be used for material-independent, highly-controlled surface immobilisation of active molecules and fabrication of biodegradable drug-loaded hydrogel coatings. In this article, we comprehensively review the role plasma-assisted processing and catechol chemistry can play in combating bacterial colonisation on medically relevant coatings, and how these strategies can be coupled with the use of natural antimicrobial agents to produce synthetic antibiotic-free antibacterial surfaces.

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The nanometer scale surface topography of a solid substrate is known to influence the extent of bacterial attachment and their subsequent proliferation to form biofilms. As an extension of our previous work on the development of a novel organic polymer coating for the prevention of growth of medically significant bacteria on three-dimensional solid surfaces, this study examines the effect of surface coating on the adhesion and proliferation tendencies of Staphylococcus aureus and compares to those previously investigated tendencies of Pseudomonas aeruginosa on similar coatings. Radio frequency plasma enhanced chemical vapor deposition was used to coat the surface of the substrate with thin film of terpinen-4-ol, a constituent of tea-tree oil known to inhibit the growth of a broad range of bacteria. The presence of the coating decreased the substrate surface roughness from approximately 2.1 nm to 0.4 nm. Similar to P. aeruginosa, S. aureus presented notably different patterns of attachment in response to the presence of the surface film, where the amount of attachment, extracellular polymeric substance production, and cell proliferation on the coated surface was found to be greatly reduced compared to that obtained on the unmodified surface. This work suggests that the antimicrobial and antifouling coating used in this study could be effectively integrated into medical and other clinically relevant devices to prevent bacterial growth and to minimize bacteria-associated adverse host responses.

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Heavy metals build-up on urban road surfaces is a complex process and influenced by a diverse range of factors. Although numerous research studies have been conducted in the area of heavy metals build-up, limited research has been undertaken to rank these factors in terms of their influence on the build-up process. This results in limitations in the identification of the most critical factor/s for accurately estimating heavy metal loads and for designing effective stormwater treatment measures. The research study undertook an in-depth analysis of the factors which influence heavy metals build-up based on data generated from a number of different geographical locations around the world. Traffic volume was found to be the highest ranked factor in terms of influencing heavy metals build-up while land use was ranked the second. Proximity to arterial roads, antecedent dry days and road surface roughness has a relatively lower ranking. Furthermore, the study outcomes advances the conceptual understanding of heavy metals build-up based on the finding that with increasing traffic volume, total heavy metal build-up load increases while the variability decreases. The outcomes from this research study are expected to contribute to more accurate estimation of heavy metals build-up loads leading to more effective stormwater treatment design.

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In the context of increasing threats to the sensitive marine ecosystem by toxic metals, this study investigated the metal build-up on impervious surfaces specific to commercial seaports. The knowledge generated in this study will contribute to managing toxic metal pollution of the marine ecosystem. The study found that inter-modal operations and main access roadway had the highest loads followed by container storage and vehicle marshalling sites, while the quay line and short term storage areas had the lowest. Additionally, it was found that Cr, Al, Pb, Cu and Zn were predominantly attached to solids, while significant amount of Cu, Pb and Zn were found as nutrient complexes. As such, treatment options based on solids retention can be effective for some metal species, while ineffective for other species. Furthermore, Cu and Zn are more likely to become bioavailable in seawater due to their strong association with nutrients. Mathematical models to replicate the metal build-up process were also developed using experimental design approach and partial least square regression. The models for Cr and Pb were found to be reliable, while those for Al, Zn and Cu were relatively less reliable, but could be employed for preliminary investigations.