Quartz-based flat-crystal resonant inelastic x-ray scattering spectrometer with sub-10 meV energy resolution

Continued improvement of the energy resolution of resonant inelastic x-ray scattering (RIXS) spectrometers is crucial for fulfilling the potential of this technique in the study of electron dynamics in materials of fundamental and technological importance. In particular, RIXS is the only alternative tool to inelastic neutron scattering capable of providing fully momentum resolved information on dynamic spin structures of magnetic materials, but is limited to systems whose magnetic excitation energy scales are comparable to the energy resolution. The state-of-the-art spherical diced crystal analyzer optics provides energy resolution as good as 25 meV but has already reached its theoretical limit. Here, we demonstrate a novel sub-10meV RIXS spectrometer based on flat-crystal optics at the Ir-L$_3$ absorption edge (11.215$\sim$ keV) that achieves an analyzer energy resolution of 3.9$\sim$meV, very close to the theoretical value of 3.7$\sim$meV. In addition, the new spectrometer allows efficient polarization analysis without loss of energy resolution. The performance of the instrument is demonstrated using longitudinal acoustical and optical phonons in diamond, and magnon in Sr$_3$Ir$_2$O$_7$. The novel sub-10$\sim$meV RIXS spectrometer thus provides a window into magnetic materials with small energy scales

Improving identification of differentially expressed genes in microarray studies using information from public databases

We demonstrate that the process of identifying differentially expressed genes in microarray studies with small sample sizes can be substantially improved by extracting information from a large number of datasets accumulated in public databases. The improvement comes from more reliable estimates of gene-specific variances based on other datasets. For a two-group comparison with two arrays in each group, for example, the result of our method was comparable to that of a t-test analysis with five samples in each group or to that of a regularized t-test analysis with three samples in each group. Our results are further improved by weighting the results of our approach with the regularized t-test results in a hybrid method

Metformin as a Therapeutic Target in Endometrial Cancers.

Endometrial cancer is the most common gynecologic malignancy in developed countries. Its increasing incidence is thought to be related in part to the rise of metabolic syndrome, which has been shown to be a risk factor for the development of hyperestrogenic and hyperinsulinemic states. This has consequently lead to an increase in other hormone-responsive cancers as well e.g., breast and ovarian cancer. The correlation between obesity, hyperglycemia, and endometrial cancer has highlighted the important role of metabolism in cancer establishment and persistence. Tumor-mediated reprogramming of the microenvironment and macroenvironment can range from induction of cytokines and growth factors to stimulation of surrounding stromal cells to produce energy-rich catabolites, fueling the growth, and survival of cancer cells. Such mechanisms raise the prospect of the metabolic microenvironment itself as a viable target for treatment of malignancies. Metformin is a biguanide drug that is a first-line treatment for type 2 diabetes that has beneficial effects on various markers of the metabolic syndrome. Many studies suggest that metformin shows potential as an adjuvant treatment for uterine and other cancers. Here, we review the evidence for metformin as a treatment for cancers of the endometrium. We discuss the available clinical data and the molecular mechanisms by which it may exert its effects, with a focus on how it may alter the tumor microenvironment. The pleiotropic effects of metformin on cellular energy production and usage as well as intercellular and hormone-based interactions make it a promising candidate for reprogramming of the cancer ecosystem. This, along with other treatments aimed at targeting tumor metabolic pathways, may lead to novel treatment strategies for endometrial cancer

Rabies Surveillance Identifies Potential Risk Corridors and Enables Management Evaluation

Intensive efforts are being made to eliminate the raccoon variant of rabies virus (RABV) from the eastern United States and Canada. The United States Department of Agriculture (USDA) Wildlife Services National Rabies Management Program has implemented enhanced rabies surveillance (ERS) to improve case detection across the extent of the raccoon oral rabies vaccination (ORV) management area. We evaluated ERS and public health surveillance data from 2006 to 2017 in three northeastern USA states using a dynamic occupancy modeling approach. Our objectives were to examine potential risk corridors for RABV incursion from the U.S. into Canada, evaluate the effectiveness of ORV management strategies, and identify surveillance gaps. ORV management has resulted in a decrease in RABV cases over time within vaccination zones (from occupancy (ψ) of 0.60 standard error (SE) = 0.03 in the spring of 2006 to ψ of 0.33 SE = 0.10 in the spring 2017). RABV cases also reduced in the enzootic area (from ψ of 0.60 SE = 0.03 in the spring of 2006 to ψ of 0.45 SE = 0.05 in the spring 2017). Although RABV occurrence was related to habitat type, greater impacts were associated with ORV and trap–vaccinate–release (TVR) campaigns, in addition to seasonal and yearly trends. Reductions in RABV occupancy were more pronounced in areas treated with Ontario Rabies Vaccine Bait (ONRAB) compared to RABORAL V-RG®. Our approach tracked changes in RABV occurrence across space and time, identified risk corridors for potential incursions into Canada, and highlighted surveillance gaps, while evaluating the impacts of management actions. Using this approach, we are able to provide guidance for future RABV management

Inorganic Biodegradable Substrates for Devices and Systems

Disclosed are biodegradable glass substrates that are useful as functional elements of solid-state devices. In particular, biodegradable glass substrates having a rapidly degradable glass and a slowly degradable glass provide a structural platform that completely dissolves following a desired operational lifetime of devices such as implanted electronic devices, implanted sensor devices, and optical fibers

Preventive measures in infancy to reduce under-five mortality: a case-control study in The Gambia.

OBJECTIVE: To investigate the relationship between child mortality and common preventive interventions: vaccination, trained birthing attendants, tetanus toxoid during pregnancy, breastfeeding and vitamin A supplementation. METHODS: Case-control study in a population under demographic surveillance. Cases (n = 141) were children under five who died. Each was age and sex-matched to five controls (n = 705). Information was gathered by interviewing primary caregivers. RESULTS: All but one of the interventions - whether the mother had received tetanus toxoid during pregnancy - were protective against child mortality after multivariate analysis. Having a trained person assisting at child birth (OR 0.2 95% CI 0.1-0.4), receiving all vaccinations by 9 months of age (OR 0.1; 95% CI 0.01-0.3), being breastfed for more than 12 months (Children breastfed between 13 and 24 months OR 0.1 95% CI 0.03-0.3, more than 25 months OR 0.1 95% CI 0.01-0.5) and receiving vitamin A supplementation at or after 6 months of age (OR 0.05; 95% CI 0.01-0.2) were protective against child death. CONCLUSIONS: This study confirms the value of at least four available interventions in the prevention of under-five death in The Gambia. It is now important to identify those who are not receiving them and why, and to intervene to improve coverage across the population

The Projected Covariance Measure for assumption-lean variable significance testing

Testing the significance of a variable or group of variables $X$ for predicting a response $Y$, given additional covariates $Z$, is a ubiquitous task in statistics. A simple but common approach is to specify a linear model, and then test whether the regression coefficient for $X$ is non-zero. However, when the model is misspecified, the test may have poor power, for example when $X$ is involved in complex interactions, or lead to many false rejections. In this work we study the problem of testing the model-free null of conditional mean independence, i.e. that the conditional mean of $Y$ given $X$ and $Z$ does not depend on $X$. We propose a simple and general framework that can leverage flexible nonparametric or machine learning methods, such as additive models or random forests, to yield both robust error control and high power. The procedure involves using these methods to perform regressions, first to estimate a form of projection of $Y$ on $X$ and $Z$ using one half of the data, and then to estimate the expected conditional covariance between this projection and $Y$ on the remaining half of the data. While the approach is general, we show that a version of our procedure using spline regression achieves what we show is the minimax optimal rate in this nonparametric testing problem. Numerical experiments demonstrate the effectiveness of our approach both in terms of maintaining Type I error control, and power, compared to several existing approaches.Comment: 89 pages, 5 figure