Effect of Phosphate Group Addition on the Properties of Denture Base Resins

Statement of problem Acrylic resins are prone to microbial adherence, especially by Candida albicans. Surface-charged resins alter the ionic interaction between the denture resin and Candida hyphae, and these resins are being developed as a means to reduce microbial colonization on the denture surface. Purpose The purpose of this study was to investigate the physical and mechanical properties of phosphate-containing polymethyl methacrylate resins for their suitability as a denture material. Material and methods Using PMMA with cross-linker (Lucitone 199) as a control, 4 experimental groups containing various levels of phosphate with and without cross-linker were generated. The properties examined were impact strength, fracture toughness, wettability (contact angle), and resin bonding ability to denture teeth. Impact strength was tested in the Izod configuration (n=16), and fracture toughness (n=13) was measured using the single-edge notched bend test. Wettability was determined by calculating the contact angle of water on the material surface (n=12), while ISO 1567 was used for bonding ability (n=12). The data were analyzed by 1- and 2-way ANOVA (α=.05). Results A trend of increased hydrophilicity, as indicated by lower contact angle, was observed with increased concentrations of phosphate. With regard to the other properties, no significant differences were found when compared with the control acrylic resin. Conclusions No adverse physical effect due to the addition of a phosphate-containing monomer was found in the acrylic denture resins. Additional mechanical and physical properties, biocompatibility, and clinical efficacy studies are needed to confirm the in vivo anti-Candida activity of these novel resins

Mitigating effects of vaccination on influenza outbreaks given constraints in stockpile size and daily administration capacity

<p>Abstract</p> <p>Background</p> <p>Influenza viruses are a major cause of morbidity and mortality worldwide. Vaccination remains a powerful tool for preventing or mitigating influenza outbreaks. Yet, vaccine supplies and daily administration capacities are limited, even in developed countries. Understanding how such constraints can alter the mitigating effects of vaccination is a crucial part of influenza preparedness plans. Mathematical models provide tools for government and medical officials to assess the impact of different vaccination strategies and plan accordingly. However, many existing models of vaccination employ several questionable assumptions, including a rate of vaccination <it>proportional </it>to the population at each point in time.</p> <p>Methods</p> <p>We present a SIR-like model that explicitly takes into account vaccine supply and the <it>number </it>of vaccines administered per day and places data-informed limits on these parameters. We refer to this as the <it>non-proportional </it>model of vaccination and compare it to the proportional scheme typically found in the literature.</p> <p>Results</p> <p>The proportional and non-proportional models behave similarly for a few different vaccination scenarios. However, there are parameter regimes involving the vaccination campaign duration and daily supply limit for which the non-proportional model predicts smaller epidemics that peak later, but may last longer, than those of the proportional model. We also use the non-proportional model to predict the mitigating effects of variably timed vaccination campaigns for different levels of vaccination coverage, using specific constraints on daily administration capacity.</p> <p>Conclusions</p> <p>The non-proportional model of vaccination is a theoretical improvement that provides more accurate predictions of the mitigating effects of vaccination on influenza outbreaks than the proportional model. In addition, parameters such as vaccine supply and daily administration limit can be easily adjusted to simulate conditions in developed and developing nations with a wide variety of financial and medical resources. Finally, the model can be used by government and medical officials to create customized pandemic preparedness plans based on the supply and administration constraints of specific communities.</p

Image quality characterization of fine resolution RISAT-1 data using impulse response function

This study presents the results obtained from image quality assessment of Radar Imaging SATellite (RISAT-1). Image quality parameters such as spatial resolution, peak to sidelobe ratio (PSLR) and integrated sidelobe ratio (ISLR) are calculated by the analysis of impulse response function (IRF) of the point target. The study is carried out to assess temporal stability and consistency of image quality parameters obtained from analysis of IRF of 44 point targets. The results obtained from this study show that the mean values of the range and azimuth resolution are 2.048 ± 0.081 m and 3.383 ± 0.097 m for RH and 1.981 ± 0.081 m and 3.348 ± 0.076 m for RV, respectively. PSLR/ISLR values for RH channel are obtained as −26.492 dB/−26.823 dB for azimuth and −19.209 dB/−19.921 dB for the range. For RV channel, PSLR/ISLR values are −26.300 dB/−27.572 dB for azimuth and −19.146 dB/−19.827 dB for range