The effect of type of femoral component fixation on mortality and morbidity after hip hemiarthroplasty:A systematic review and meta-analysis

Background: Hip hemiarthroplasty is a well-established treatment of displaced femoral neck fracture, although debate exists over whether cemented or uncemented fixation is superior. Uncemented prostheses have typically been used in younger, healthier patients and cemented prostheses in older patients with less-stable bone. Also, earlier research has suggested that bone cement has cytotoxic effects and may trigger cardiovascular and respiratory adverse events. Questions/Purposes: The aim of this systematic review and meta-analysis was to compare morbidity and mortality rates after cemented and uncemented hemiarthroplasty for the treatment of displaced femoral neck fractures in elderly patients. Methods: Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched seven medical databases for randomized clinical trials and observational studies. We compared cemented and uncemented hemiarthroplasty using the Harris Hip Score (HHS), as well as measures of postoperative pain, mortality, and complications. Data were extracted and pooled as risk ratios or standardized mean difference with their corresponding 95% confidence intervals in a meta-analysis model. Results: The meta-analysis included 34 studies (12 randomized trials and 22 observational studies), with a total of 42,411 patients. In the pooled estimate, cemented hemiarthroplasty was associated with less risk of postoperative pain than uncemented hemiarthroplasty. There were no significant differences between groups regarding HHS or rates of postoperative mortality, pulmonary embolism, cardiac arrest, myocardial infarction, acute cardiac arrhythmia, or deep venous thrombosis. Conclusions: While we found that cemented hemiarthroplasty results in less postoperative pain than uncemented hemiarthroplasty in older patients with femoral neck fracture, the lack of significant differences in functional hip scores, mortality, and complications was surprising. Further high-level research is needed

Sumac (Rhus coriaria L.) essential oil composition and its antimicrobial effect on Salmonella typhimurium

Consumers' interest over natural preservatives and their application as food ingredients is growing, which encourage complementary researches on various natural antimicrobials such as plant essential oils. Sumac (Rhus coriaria L.), is a plant that is used as a flavouring agent in Iranian traditional foods. Therefore, in this study Sumac essential oil composition and antimicrobial activity was evaluated. Sumac ssential oil was extracted with distillation and analyzed by gas chromatography method. Antimicrobial effect of Sumac essential oil against Salmonella typhimurium, that is considers as one of important pathogen in food, was evaluated. Antimicrobial effect of essential oil was evaluated by measuring turbidity as a result of bacterial growth at a broth media by Bioscreen C instrument at 35°C. Result showed that the most important fraction of essential oil that may have antimicrobial effect is Caryophyllen. Although Sumac essential oil had bacteriostatic effect at low concentration of 30 ppm, it showed bactericidal activity at high concentration of 1000 ppm. It could be concluded that, Sumac essential oil by its antimicrobial fractions can be used to control the growth of Salmonella typhimurium in food stuff

Hydrodesulphurization Nanocatalyst, Its Use and a Process for Its Production

A nano-supported hydrodesulphurization (HDS) catalyst is prepared for hydrodesulphurization of hydrocarbonaceous feed stock. The catalyst can be prepared through different methods and also used under milder conditions than those required for conventionally used HDS catalysts, but can also function under other hydrodesulphurization operating condition

Application of support vector machine with firefly algorithm for investigation of the factors affecting the shear strength of angle shear connectors

The factors affecting the shear strength of the angle shear connectors in the steel-concrete composite beams can play an important role to estimate the efficacy of a composite beam. Therefore, the current study has aimed to verify the output of shear capacity of angle shear connector according to the input provided by Support Vector Machine (SVM) coupled with Firefly Algorithm (FFA). SVM parameters have been optimized through the use of FFA, while genetic programming (GP) and artificial neural networks (ANN) have been applied to estimate and predict the SVM-FFA models' results. Following these results, GP and ANN have been applied to develop the prediction accuracy and generalization capability of SVM-FFA. Therefore, SVM-FFA could be performed as a novel model with predictive strategy in the shear capacity estimation of angle shear connectors. According to the results, the Firefly algorithm has produced a generalized performance and be learnt faster than the conventional learning algorithms