Systematic review and meta-analysis of the growth and rupture rates of small abdominal aortic aneurysms: implications for surveillance intervals and their cost-effectiveness.

BACKGROUND: Small abdominal aortic aneurysms (AAAs; 3.0-5.4 cm in diameter) are usually asymptomatic and managed by regular ultrasound surveillance until they grow to a diameter threshold (commonly 5.5 cm) at which surgical intervention is considered. The choice of appropriate surveillance intervals is governed by the growth and rupture rates of small AAAs, as well as their relative cost-effectiveness. OBJECTIVES: The aim of this series of studies was to inform the evidence base for small AAA surveillance strategies. This was achieved by literature review, collation and analysis of individual patient data, a focus group and health economic modelling. DATA SOURCES: We undertook systematic literature reviews of growth rates and rupture rates of small AAAs. The databases MEDLINE, EMBASE on OvidSP, Cochrane Central Register of Controlled Trials 2009 Issue 4, ClinicalTrials.gov, and controlled-trials.com were searched from inception up until the end of 2009. We also obtained individual data on 15,475 patients from 18 surveillance studies. REVIEW METHODS: Systematic reviews of publications identified 15 studies providing small AAA growth rates, and 14 studies with small AAA rupture rates, up to December 2009 (later updated to September 2012). We developed statistical methods to analyse individual surveillance data, including the effects of patient characteristics, to inform the choice of surveillance intervals and provide inputs for health economic modelling. We updated an existing health economic model of AAA screening to address the cost-effectiveness of different surveillance intervals. RESULTS: In the literature reviews, the mean growth rate was 2.3 mm/year and the reported rupture rates varied between 0 and 1.6 ruptures per 100 person-years. Growth rates increased markedly with aneurysm diameter, but insufficient detail was available to guide surveillance intervals. Based on individual surveillance data, for each 0.5-cm increase in AAA diameter, growth rates increased by about 0.5 mm/year and rupture rates doubled. To control the risk of exceeding 5.5 cm to below 10% in men, on average a 7-year surveillance interval is sufficient for a 3.0-cm aneurysm, whereas an 8-month interval is necessary for a 5.0-cm aneurysm. To control the risk of rupture to below 1%, the corresponding estimated surveillance intervals are 9 years and 17 months. Average growth rates were higher in smokers (by 0.35 mm/year) and lower in patients with diabetes (by 0.51 mm/year). Rupture rates were almost fourfold higher in women than men, doubled in current smokers and increased with higher blood pressure. Increasing the surveillance interval from 1 to 2 years for the smallest aneurysms (3.0-4.4 cm) decreased costs and led to a positive net benefit. For the larger aneurysms (4.5-5.4 cm), increasing surveillance intervals from 3 to 6 months led to equivalent cost-effectiveness. LIMITATIONS: There were no clear reasons why the growth rates varied substantially between studies. Uniform diagnostic criteria for rupture were not available. The long-term cost-effectiveness results may be susceptible to the modelling assumptions made. CONCLUSIONS: Surveillance intervals of several years are clinically acceptable for men with AAAs in the range 3.0-4.0 cm. Intervals of around 1 year are suitable for 4.0-4.9-cm AAAs, whereas intervals of 6 months would be acceptable for 5.0-5.4-cm AAAs. These intervals are longer than those currently employed in the UK AAA screening programmes. Lengthening surveillance intervals for the smallest aneurysms was also shown to be cost-effective. Future work should focus on optimising surveillance intervals for women, studying whether or not the threshold for surgery should depend on patient characteristics, evaluating the usefulness of surveillance for those with aortic diameters of 2.5-2.9 cm, and developing interventions that may reduce the growth or rupture rates of small AAAs. FUNDING: The National Institute for Health Research Health Technology Assessment programme

Degradation of metaldehyde in water by nanoparticle catalysts and powdered activated carbon

Metaldehyde, an organic pesticide widely used in the UK, has been detected in drinking water in the UK with a low concentration (<1 μg L−1) which is still above the European and UK standard requirements. This paper investigates the efficiency of four materials: powdered activated carbon (PAC) and carbon-doped titanium dioxide nanocatalyst with different concentrations of carbon (C-1.5, C-40, and C-80) for metaldehyde removal from aqueous solutions by adsorption and oxidation via photocatalysis. PAC was found to be the most effective material which showed almost over 90% removal. Adsorption data were well fitted to the Langmuir isotherm model, giving a qm (maximum/saturation adsorption capacity) value of 32.258 mg g−1 and a KL (Langmuir constant) value of 2.013 L mg−1. In terms of kinetic study, adsorption of metaldehyde by PAC fitted well with a pseudo-second-order equation, giving the adsorption rate constant k2 value of 0.023 g mg−1 min−1, implying rapid adsorption. The nanocatalysts were much less effective in oxidising metaldehyde than PAC with the same metaldehyde concentration and 0.2 g L−1 loading concentration of materials under UV light; the maximum removal achieved by carbon-doped titanium dioxide (C-1.5) nanocatalyst was around 15% for a 7.5 ppm metaldehyde solution

Optimization of total trihalomethanes' (TTHMs) and their precursors' removal by granulated activated carbon (GAC) and sand dual media by response surface methodology (RSM)

A response surface methodology (RSM) applying central composite design with rotatable full factorial (14 non-center and six center points) was used to discern the effect of granular activated carbon (GAC), sand and pH on total trihalomethanes (TTHMs) and humic acid (HA) removal from drinking water. Results showed efficient TTHMs and HA removal by GAC while a sand column showed little effect for TTHMs but was significant for total organic carbon (TOC) removal. With GAC and a sand column of 4 cm, a pH increase from 6 to 8 caused an increase in TTHM removal from 79.8 to 83.6% while a decrease in HA removal from 26.6 to 6.6% was observed. An increase in GAC column depth from 10 to 20 cm caused a slight increase in TTHM removal from 99.4 to 99.7%, while TOC removal was increased from an average of 38.85% to 57.4% removal. The developed quadratic model for TTHM removal (p = 0.048) and linear model for TOC removal (p = 0.039) were significant. GAC column depth (p < 0.0117) and column depth2 (p < 0.039) were the most significant factors. A 98% TTHMs, 30%TOC and 51% residual chlorine removal were optimized at 9 cm GAC and 4 cm sand column depth at pH 8 with desirability factor (D) 0.64

Central composite rotatable design for optimization of trihalomethane extraction and detection through gas chromatography: a case study

Central composite rotatable design (CCRD) was employed to optimize initial temperature (ºC), ramp function (ºC/min) and salt addition for trihalomethane extraction/quantification from the drinking water distribution network in Ratta Amral, Rawalpindi., Pakistan. Drinking water samples were collected from the treatment plant, overhead reservoir and consumer’s taps. The USEPA method for trihalomethane detection 551.1 via gas chromatography was applied using liquid–liquid extraction. The experiments with input variables for sample preparation and operational conditions were performed in a randomized order as per design of experiment by central composite rotatable design and responses were evaluated for model development. A significant (p = 0.005) two-factor interaction model was optimized. Initial temperature was observed to be insignificant (p = 0.64), while ramp function (p = 0.0043) and salt addition (p = 0.04) were significant. Product of salt addition and ramp was significant (p = 0.004), while product of initial temperature and salt addition was insignificant (p = 0.008). With a desirability function of 0.97, an initial temperature of 50 ºC, 6 ºC rise/min to 180 ºC and 0.5 g salt were optimized. It was found that development and optimization of the analytical methods for rapid trihalomethane detection would improve optimization of the current treatment practices in the country

Biomass Ashes for Acid Mine Drainage Remediation

Acid mine drainage (AMD) is the largest environmental problem facing the world mining and processing industry because it has low pH and can contain high concentrations of potential pollutants. Biomass ash (BA) can be considered as a potential material for AMD treatment. The main goal of this work was to investigate potential use of Biomass ash of CPK-LA and PK-LA types for AMD remediation. Four UK BAs from diferent fuels (i.e. straw, meat and bone meal, poultry litter), synthetic AMD, and raw AMDs (Belovo and Ursk) were used for the AMD treatment experiments. Batch experiments showed that in 1 h the biomass ash from straw combustion can efectively neutralise the synthetic AMD and the Belovo AMD with removal of potential pollutants at the liquid-to-solid ratio (L/S) of 100–250 and 10–50, respectively. The biomass ashes from straw and poultry litter combustion can efectively remove pollutants from the Ursk AMD at L/S 100 and adjust pH. The metal concentrations of those treated AMDs met receiving water quality standards. Potential pollutants precipitated as carbonate/hydroxide/sulphate, co-precipitated with Fe oxyhydroxides and Ca phosphates, and appeared as new phases such as Ca, Cu, Zn phosphates and Ca, Fe phosphates. This investigation is essential for development of appropriate, environmentally friendly and economically rational waste management

Upregulation of the microRNA cluster at the Dlk1-Dio3 locus in lung adenocarcinoma.

Mice in which lung epithelial cells can be induced to express an oncogenic Kras(G12D) develop lung adenocarcinomas in a manner analogous to humans. A myriad of genetic changes accompany lung adenocarcinomas, many of which are poorly understood. To get a comprehensive understanding of both the transcriptional and post-transcriptional changes that accompany lung adenocarcinomas, we took an omics approach in profiling both the coding genes and the non-coding small RNAs in an induced mouse model of lung adenocarcinoma. RNAseq transcriptome analysis of Kras(G12D) tumors from F1 hybrid mice revealed features specific to tumor samples. This includes the repression of a network of GTPase-related genes (Prkg1, Gnao1 and Rgs9) in tumor samples and an enrichment of Apobec1-mediated cytosine to uridine RNA editing. Furthermore, analysis of known single-nucleotide polymorphisms revealed not only a change in expression of Cd22 but also that its expression became allele specific in tumors. The most salient finding, however, came from small RNA sequencing of the tumor samples, which revealed that a cluster of ∼53 microRNAs and mRNAs at the Dlk1-Dio3 locus on mouse chromosome 12qF1 was markedly and consistently increased in tumors. Activation of this locus occurred specifically in sorted tumor-originating cancer cells. Interestingly, the 12qF1 RNAs were repressed in cultured Kras(G12D) tumor cells but reactivated when transplanted in vivo. These microRNAs have been implicated in stem cell pleuripotency and proteins targeted by these microRNAs are involved in key pathways in cancer as well as embryogenesis. Taken together, our results strongly imply that these microRNAs represent key targets in unraveling the mechanism of lung oncogenesis

Interval valued intuitionistic fuzzy evaluations for analysis of a student's knowledge in university e-learning courses

© The Korean Institute of Intelligent Systems. In the paper a method is proposed for evaluation of the students' knowledge obtained in the university e-learning courses and an evaluation of the whole student class. For the assessment of the student's solution of the respective assessment units the theory of intuitionistic fuzzy sets is used, while for the class evaluation, interval valued intuitionistic fuzzy sets is used. The obtained intuitionistic fuzzy estimations reflect the degree of each student's good or poor performances, for each assessment unit. The interval valued intuitionistic fuzzy evaluations are based on the separate student's evaluations. We also consider a degree of uncertainty that represents such cases wherein the student is currently unable to solve the problem. The method presented here provides the possibility for the algorithmization of the process of forming the student's evaluations

Regulation of stanniocalcin-1 secretion by BeWo cells and first trimester human placental tissue from normal pregnancies and those at increased risk of developing preeclampsia.

Stanniocalcin-1 (STC-1) is a multi-functional glycosylated peptide present in the plasma of healthy women postpartum and increased further in pregnancies complicated by preeclampsia. Although the STC-1 gene is expressed by the placenta what regulates its secretion and from which cells at the feto-maternal interface is unknown. Here, we demonstrate for the first time that the syncytiotrophoblast and cytotrophoblast are a major site of STC-1 protein expression in first trimester placental tissue. Further, in response to low oxygen, first trimester chorionic villous tissue from pregnancies at increased risk of developing preeclampsia secreted significantly more STC-1 than normal tissue under the same conditions. Using the human trophoblast cell line BeWo we have shown that low oxygen increased the secretion of STC-1 but it required co-stimulation with the Adenosine-3', 5'-cyclic monophosphate (cAMP) analogue, 8-Bromo adenosine-3', 5'-cyclic monophosphate cAMP (8 Br-cAMP) to reach significance. Inhibition of Hypoxia inducible factor 2α (HIF-2α) and the Phosphatidylinositol-3 kinase (PI3 -Kinase)/AKT/Serum and glucocorticoid-induced kinase-1(SGK-1) pathway resulted in significant inhibition of STC-1 secretion. As both low oxygen and cAMP are known to play a central role in placental function, their regulation of STC-1 points to a potentially important role in the maintenance of a normal healthy pregnancy and we would hypothesize that it may act to protect against prolonged placental hypoxia seen in preeclampsia

The impact of partially missing communities~on the reliability of centrality measures

Network data is usually not error-free, and the absence of some nodes is a very common type of measurement error. Studies have shown that the reliability of centrality measures is severely affected by missing nodes. This paper investigates the reliability of centrality measures when missing nodes are likely to belong to the same community. We study the behavior of five commonly used centrality measures in uniform and scale-free networks in various error scenarios. We find that centrality measures are generally more reliable when missing nodes are likely to belong to the same community than in cases in which nodes are missing uniformly at random. In scale-free networks, the betweenness centrality becomes, however, less reliable when missing nodes are more likely to belong to the same community. Moreover, centrality measures in scale-free networks are more reliable in networks with stronger community structure. In contrast, we do not observe this effect for uniform networks. Our observations suggest that the impact of missing nodes on the reliability of centrality measures might not be as severe as the literature suggests