Identification of nine new susceptibility loci for endometrial cancer

Endometrial cancer is the most commonly diagnosed cancer of the female reproductive tract in developed countries. Through genome-wide association studies (GWAS) we have previously identified eight risk loci for endometrial cancer. Here, we present an expanded meta-analysis of 12,906 endometrial cancer cases and 108,979 controls (including new genotype data for 5,624 cases) and identify nine novel genome-wide significant loci, including a locus on 12q24.12 previously identified by meta-GWAS of endometrial and colorectal cancer. At five loci, expression quantitative trait locus (eQTL) analyses identify candidate causal genes and risk alleles at two of these loci that associate with decreased expression of genes which encode negative regulators of oncogenic signal transduction proteins (SH2B3 (12q24.12) and NF1 (17q11.2)). In summary, this study has doubled the number of known endometrial cancer risk loci and revealed candidate causal genes for future study

Rapid production of cyclonic spray chambers for inductively coupled plasma applications using low cost 3D printer technology

The development of low cost 3D printer technology is having a profound effect on everyday life. Over the past few years there have been many reports in the media detailing futuristic uses of this technology. Whilst the merits of these applications are clear there is an opportunity for this technology to enhance current research where a degree of fabrication is required. This work describes some initial research into the use of 3D printing for the fabrication of cyclonic spray chambers for inductively coupled plasma applications. The linearity, precision and detection limits obtained from the 3D printed chamber have been compared to a commercial model with largely positive results. Comparison between the performance of subsequent prints of the same spray chamber has also been carried out and has been shown to be highly reproducible. This work suggests that low-cost 3D printing techniques can be used as an inexpensive way to fabricate prototype spray chambers to accelerate the research in this area

Evaluation and characterisation of metal sorption and retention by drinking water treatment residuals (WTRs) for environmental remediation

Drinking water treatment residuals (WTRs) are wastes generated when water is clarified using aluminium or iron salts. They are increasingly being considered as a resource with potential reuse value, particularly in relation to soil or water remediation. Adsorption–desorption capacity of Al-based (Al-WTR) and Fe-based (Fe-WTR) materials was investigated here for Pb and Zn, both separately and in combination, as a preliminary trial to assess their utility for immobilising contaminant metals in environmental settings. Maximum adsorption observed at the highest test solution concentrations imposed (400 mg/L) was similar for each WTR type and each metal; Al-WTRs sorbed Zn at 3579 mg/kg and Pb at 4025 mg/kg, while Fe-WTRs sorbed Zn and Pb at 3579 mg/kg and 3980 mg/kg, respectively. Equilibrium adsorption data were tested against Langmuir, Freundlich, and Temkin isotherm models, which indicated a substantial reserve capacity for further Pb sorption and that multiple sorption mechanisms were involved. Subsequent desorption tests with 0.001 M CaCl2 solution indicated that > 89.76% of sorbed metal remained sorbed. When in solution together, both metals were strongly sorbed by WTRs, but a slight preference for Pb was observed. The results indicate that WTRs would be very effective immobilising agents if placed in contaminated soil or if used to treat contaminated waters

Simple, Robust, and Plasticizer-Free Iodide-Selective Sensor Based on Copolymerized Triazole-Based Ionic Liquid

Novel solid-contact iodide-selective electrodes based on covalently attached 1,2,3 triazole ionic liquid (IL) were prepared and investigated in this study. Triazole-based IL moieties were synthesized using click chemistry and were further copolymerized with lauryl methacrylate via a simple one-step free radical polymerization to produce a "self-plasticized" copolymer. The mechanical properties of the copolymer are suitable for the fabrication of plasticizer-free ion-selective membrane electrodes. We demonstrate that covalently attached IL moieties provide adequate functionality to the ion-selective membrane, thus achieving a very simple, one-component sensing membrane. We also demonstrate that the presence of iodide as the counterion in the triazole moiety has direct influence on the membrane's functionality. Potentiometric experiments revealed that each electrode displays high selectivity toward iodide anions over a number of inorganic anions. Moreover, the inherent presence of the iodide in the membrane reduces the need for conditioning. The nonconditioned electrodes show strikingly similar response characteristics compared to the conditioned ones. The electrodes exhibited a near Nernstian behavior with a slope of -56.1 mV per decade across a large concentration range with lower detection limits found at approximately 6.3 × 10(-8) M or 8 ppb. These all-solid-state sensors were utilized for the selective potentiometric determination of iodide ions in artificial urine samples in the nanomolar concentration range

Sequential Deliberation for Social Choice

In large scale collective decision making, social choice is a normative study of how one ought to design a protocol for reaching consensus. However, in instances where the underlying decision space is too large or complex for ordinal voting, standard voting methods of social choice may be impractical. How then can we design a mechanism - preferably decentralized, simple, scalable, and not requiring any special knowledge of the decision space - to reach consensus? We propose sequential deliberation as a natural solution to this problem. In this iterative method, successive pairs of agents bargain over the decision space using the previous decision as a disagreement alternative. We describe the general method and analyze the quality of its outcome when the space of preferences define a median graph. We show that sequential deliberation finds a 1.208- approximation to the optimal social cost on such graphs, coming very close to this value with only a small constant number of agents sampled from the population. We also show lower bounds on simpler classes of mechanisms to justify our design choices. We further show that sequential deliberation is ex-post Pareto efficient and has truthful reporting as an equilibrium of the induced extensive form game. We finally show that for general metric spaces, the second moment of of the distribution of social cost of the outcomes produced by sequential deliberation is also bounded

A comprehensive model for familial breast cancer incorporating BRCA1, BRCA2 and other genes

In computing the probability that a woman is a BRCA1 or BRCA2 carrier for genetic counselling purposes, it is important to allow for the fact that other breast cancer susceptibility genes may exist. We used data from both a population based series of breast cancer cases and high risk families in the UK, with information on BRCA1 and BRCA2 mutation status, to investigate the genetic models that can best explain familial breast cancer outside BRCA1 and BRCA2 families. We also evaluated the evidence for risk modifiers in BRCA1 and BRCA2 carriers. We estimated the simultaneous effects of BRCA1, BRCA2, a third hypothetical gene ‘BRCA3’, and a polygenic effect using segregation analysis. The hypergeometric polygenic model was used to approximate polygenic inheritance and the effect of risk modifiers. BRCA1 and BRCA2 could not explain all the observed familial clustering. The best fitting model for the residual familial breast cancer was the polygenic, although a model with a single recessive allele produced a similar fit. There was also significant evidence for a modifying effect of other genes on the risks of breast cancer in BRCA1 and BRCA2 mutation carriers. Under this model, the frequency of BRCA1 was estimated to be 0.051% (95% CI: 0.021–0.125%) and of BRCA2 0.068% (95% CI: 0.033–0.141%). The breast cancer risk by age 70 years, based on the average incidence over all modifiers was estimated to be 35.3% for BRCA1 and 50.3% for BRCA2. The corresponding ovarian cancer risks were 25.9% for BRCA1 and 9.1% for BRCA2. The findings suggest that several common, low penetrance genes with multiplicative effects on risk may account for the residual non-BRCA1/2 familial aggregation of breast cancer. The modifying effect may explain the previously reported differences between population based estimates for BRCA1/2 penetrance and estimates based on high-risk families

Switching of magnetic domains reveals evidence for spatially inhomogeneous superconductivity

The interplay of magnetic and charge fluctuations can lead to quantum phases with exceptional electronic properties. A case in point is magnetically-driven superconductivity, where magnetic correlations fundamentally affect the underlying symmetry and generate new physical properties. The superconducting wave-function in most known magnetic superconductors does not break translational symmetry. However, it has been predicted that modulated triplet p-wave superconductivity occurs in singlet d-wave superconductors with spin-density wave (SDW) order. Here we report evidence for the presence of a spatially inhomogeneous p-wave Cooper pair-density wave (PDW) in CeCoIn5. We show that the SDW domains can be switched completely by a tiny change of the magnetic field direction, which is naturally explained by the presence of triplet superconductivity. Further, the Q-phase emerges in a common magneto-superconducting quantum critical point. The Q-phase of CeCoIn5 thus represents an example where spatially modulated superconductivity is associated with SDW order

Modeling the impact of prevention policies on future diabetes prevalence in the United States: 2010-2030

Background Although diabetes is one of the most costly and rapidly increasing serious chronic diseases worldwide, the optimal mix of strategies to reduce diabetes prevalence has not been determined. Methods Using a dynamic model that incorporates national data on diabetes prevalence and incidence, migration, mortality rates, and intervention effectiveness, we project the effect of five hypothetical prevention policies on future US diabetes rates through 2030: 1) no diabetes prevention strategy; 2) a “high-risk” strategy, wherein adults with both impaired fasting glucose (IFG) (fasting plasma glucose of 100–124 mg/dl) and impaired glucose tolerance (IGT) (2-hour post-load glucose of 141–199 mg/dl) receive structured lifestyle intervention; 3) a “moderate-risk” strategy, wherein only adults with IFG are offered structured lifestyle intervention; 4) a “population-wide” strategy, in which the entire population is exposed to broad risk reduction policies; and 5) a “combined” strategy, involving both the moderate-risk and population-wide strategies. We assumed that the moderate- and high-risk strategies reduce the annual diabetes incidence rate in the targeted subpopulations by 12.5% through 2030 and that the population-wide approach would reduce the projected annual diabetes incidence rate by 2% in the entire US population. Results We project that by the year 2030, the combined strategy would prevent 4.6 million incident cases and 3.6 million prevalent cases, attenuating the increase in diabetes prevalence by 14%. The moderate-risk approach is projected to prevent 4.0 million incident cases, 3.1 million prevalent cases, attenuating the increase in prevalence by 12%. The high-risk and population approaches attenuate the projected prevalence increases by 5% and 3%, respectively. Even if the most effective strategy is implemented (the combined strategy), our projections indicate that the diabetes prevalence rate would increase by about 65% over the 23 years (i.e., from 12.9% in 2010 to 21.3% in 2030). Conclusions While implementation of appropriate diabetes prevention strategies may slow the rate of increase of the prevalence of diabetes among US adults through 2030, the US diabetes prevalence rate is likely to increase dramatically over the next 20 years. Demand for health care services for people with diabetes complications and diabetes-related disability will continue to grow, and these services will need to be strengthened along with primary diabetes prevention efforts