Weak convergence of finite element approximations of linear stochastic evolution equations with additive noise II. Fully discrete schemes

We present an abstract framework for analyzing the weak error of fully discrete approximation schemes for linear evolution equations driven by additive Gaussian noise. First, an abstract representation formula is derived for sufficiently smooth test functions. The formula is then applied to the wave equation, where the spatial approximation is done via the standard continuous finite element method and the time discretization via an I-stable rational approximation to the exponential function. It is found that the rate of weak convergence is twice that of strong convergence. Furthermore, in contrast to the parabolic case, higher order schemes in time, such as the Crank-Nicolson scheme, are worthwhile to use if the solution is not very regular. Finally we apply the theory to parabolic equations and detail a weak error estimate for the linearized Cahn-Hilliard-Cook equation as well as comment on the stochastic heat equation

Inherited predisposition to breast cancer in the Carolina Breast Cancer Study

The Carolina Breast Cancer Study (CBCS) phases I–II was a case-control study of biological and social risk factors for invasive breast cancer that enrolled cases and controls between 1993 and 1999. Case selection was population-based and stratified by ancestry and age at diagnosis. Controls were matched to cases by age, self-identified race, and neighborhood of residence. Sequencing genomic DNA from 1370 cases and 1635 controls yielded odds ratios (with 95% confidence limits) for breast cancer of all subtypes of 26.7 (3.59, 189.1) for BRCA1, 8.8 (3.44, 22.48) for BRCA2, and 9.0 (2.06, 39.60) for PALB2; and for triple-negative breast cancer (TNBC) of 55.0 (7.01, 431.4) for BRCA1, 12.1 (4.18, 35.12) for BRCA2, and 10.8 (1.97, 59.11) for PALB2. Overall, 5.6% of patients carried a pathogenic variant in BRCA1, BRCA2, PALB2, or TP53, the four most highly penetrant breast cancer genes. Analysis of cases by tumor subtype revealed the expected association of TNBC versus other tumor subtypes with BRCA1, and suggested a significant association between TNBC versus other tumor subtypes with BRCA2 or PALB2 among African-American (AA) patients [2.95 (1.18, 7.37)], but not among European-American (EA) patients [0.62 (0.18, 2.09)]. AA patients with pathogenic variants in BRCA2 or PALB2 were 11 times more likely to be diagnosed with TNBC versus another tumor subtype than were EA patients with pathogenic variants in either of these genes (P = 0.001). If this pattern is confirmed in other comparisons of similarly ascertained AA and EA breast cancer patients, it could in part explain the higher prevalence of TNBC among AA breast cancer patients

Schistosoma mansoni secretes a chemokine binding protein with antiinflammatory activity

The coevolution of humans and infectious agents has exerted selective pressure on the immune system to control potentially lethal infections. Correspondingly, pathogens have evolved with various strategies to modulate and circumvent the host's innate and adaptive immune response. Schistosoma species are helminth parasites with genes that have been selected to modulate the host to tolerate chronic worm infections, often for decades, without overt morbidity. The modulation of immunity by schistosomes has been shown to prevent a range of immune-mediated diseases, including allergies and autoimmunity. Individual immune-modulating schistosome molecules have, therefore, therapeutic potential as selective manipulators of the immune system to prevent unrelated diseases. Here we show that S. mansoni eggs secrete a protein into host tissues that binds certain chemokines and inhibits their interaction with host chemokine receptors and their biological activity. The purified recombinant S. mansoni chemokine binding protein (smCKBP) suppressed inflammation in several disease models. smCKBP is unrelated to host proteins and is the first described chemokine binding protein encoded by a pathogenic human parasite and may have potential as an antiinflammatory agent

Interactions between cell surface protein disulphide isomerase and S-nitrosoglutathione during nitric oxide delivery

In this study, we investigated the role of protein disulphide isomerase (PDI) in rapid metabolism of S-nitrosoglutathione (GSNO) and S-nitrosoalbumin (albSNO) and in NO delivery from these compounds into cells. Incubation of GSNO or albSNO (1 μM) with the megakaryocyte cell line MEG-01 resulted in a cell-mediated removal of each compound which was inhibited by blocking cell surface thiols with 5,5′-dithiobis 2-nitrobenzoic acid (DTNB) (100 μM) or inhibiting PDI with bacitracin (5 mM). GSNO, but not albSNO, rapidly inhibited platelet aggregation and stimulated cyclic GMP (cGMP) accumulation (used as a measure of intracellular NO entry). cGMP accumulation in response to GSNO (1 μM) was inhibited by MEG-01 treatment with bacitracin or DTNB, suggesting a role for PDI and surface thiols in NO delivery. PDI activity was present in MEG-01 conditioned medium, and was inhibited by high concentrations of GSNO (500 μM). A number of cell surface thiol-containing proteins were labelled using the impermeable thiol specific probe 3-(N-maleimido-propionyl) biocytin (MPB). Pretreatment of cells with GSNO resulted in a loss of thiol reactivity on some but not all proteins, suggesting selective cell surface thiol modification. Immunoprecipitation experiments showed that GSNO caused a concentration-dependent loss of thiol reactivity of PDI. Our data indicate that PDI is involved in both rapid metabolism of GSNO and intracellular NO delivery and that during this process PDI is itself altered by thiol modification. In contrast, the relevance of PDI-mediated albSNO metabolism to NO signalling is uncertain

Initial Clinical Experience with Stationary Digital Breast Tomosynthesis

Rationale and Objectives: A linear array of carbon nanotube-enabled x-ray sources allows for stationary digital breast tomosynthesis (sDBT), during which projection views are collected without the need to move the x-ray tube. This work presents our initial clinical experience with a first-generation sDBT device. Materials and Methods: Following informed consent, women with a “suspicious abnormality” (Breast Imaging Reporting and Data System 4), discovered by digital mammography and awaiting biopsy, were also imaged by the first generation sDBT. Four radiologists participated in this paired-image study, completing questionnaires while interpreting the mammograms and sDBT image stacks. Areas under the receiver operating characteristic curve were used to measure reader performance (likelihood of correctly identifying malignancy based on pathology as ground truth), while a multivariate analysis assessed preference, as readers compared one modality to the next when interpreting diagnostically important image features. Results: Findings from 43 women were available for analysis, in whom 12 cases of malignancy were identified by pathology. The mean areas under the receiver operating characteristic curve was significantly higher (p < 0.05) for sDBT than mammography for all breast density categories and breast thicknesses. Additionally, readers preferred sDBT over mammography when evaluating mass margins and shape, architectural distortion, and asymmetry, but preferred mammography when characterizing microcalcifications. Conclusion: Readers preferred sDBT over mammography when interpreting soft-tissue breast features and were diagnostically more accurate using images generated by sDBT in a Breast Imaging Reporting and Data System 4 population. However, the findings also demonstrated the need to improve microcalcification conspicuity, which is guiding both technological and image-processing design changes in future sDBT devices

OOI Biogeochemical Sensor Data: Best Practices and User Guide. Version 1.0.0.

The OOI Biogeochemical Sensor Data Best Practices and User Guide is intended to provide current and prospective users of data generated by biogeochemical sensors deployed on the Ocean Observatories Initiative (OOI) arrays with the information and guidance needed for them to ensure that the data is science-ready. This guide is aimed at researchers with an interest or some experience in ocean biogeochemical processes. We expect that users of this guide will have some background in oceanography, however we do not assume any prior experience working with biogeochemical sensors or their data. While initially envisioned as a “cookbook” for end users seeking to work with OOI biogeochemical (BGC) sensor data, our Working Group and Beta Testers realized that the processing required to meet the specific needs of all end users across a wide range of potential scientific applications and combinations of OOI BGC data from different sensors and platforms couldn’t be synthesized into a single “recipe”. We therefore provide here the background information and principles needed for the end user to successfully identify and understand all the available “ingredients” (data), the types of “cooking” (end user processing) that are recommended to prepare them, and a few sample “recipes” (worked examples) to support end users in developing their own “recipes” consistent with the best practices presented here. This is not intended to be an exhaustive guide to each of these sensors, but rather a synthesis of the key information to support OOI BGC sensor data users in preparing science-ready data products. In instances when more in-depth information might be helpful, references and links have been provided both within each chapter and in the Appendix