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Hepatitis E virus (HEV) is the most common cause of acute viral hepatitis worldwide. An increased risk for HEV infection has been reported in organ-transplant recipients, mainly from Europe. Prospective data on HEV prevalence in the United States (U.S.) organ transplant population are limited. To determine the prevalence and factors associated with HEV infection among solid organ transplant-recipients, we conducted a prospective, cross-sectional, multicentre study among transplant-recipients and age- and organ-matched waitlist patients. Participants answered a risk-exposure questionnaire and were tested for HEV-RNA (in-house PCR), HEV-IgG, and IgM (ELISA, Wantai). Among 456 participants, 224 were transplant-recipients, and 232 were waitlist patients. The mean age was 58 years, 35% female, and 74% White. HEV seroprevalence of the entire cohort was 20.2% and associated with older age (p 0.0001) and organ transplantation (p = 0.02). The HEV seropositivity was significantly higher among transplant-recipients compared with waitlist patients (24% vs. 16.4%, p = 0.042). Among transplant recipients, relative-risk of being HEV seropositive increased with older age (RR = 3.4 [1.07-10.74] in patients70 years compared with ≤50 years, p = 0.037); history of graft hepatitis (2.2 [1.27-3.72], p = 0.005); calcineurin inhibitor use (RR = 1.9 [1.03-3.34], p = 0.02); and kidney transplantation (2.4 [1.15-5.16], p = 0.02). HEV-RNA, genotype 3 was detected in only two patients (0.4%), both transplant-recipients. HEV seroprevalence was higher among transplant-recipients than waitlist patients. HEV should be considered in transplant-recipients presenting with graft hepatitis. Detection of HEV-RNA was rare, suggesting that progression to chronic HEV infection is uncommon in transplant-recipients in the U.S.

Little attention has been given to language support for block-based compression algorithms, despite their high implementation complexity. Current implementations have to deal with both the intricacies of the algorithm itself, as well as the low-level optimizations necessary for generating fast code. However, many block-based compression algorithms share a common structure in terms of their data representations, data partitioning operations, and data traversals. In this work, we propose a set of high-level language abstractions that can succinctly capture this structure. These abstractions provide the building blocks for the development of a domain-specific language and an associated optimizing compiler. With compression-specific language support, researchers can focus on algorithm development rather than the low-level implementation details.

Erythrocytes bind circulating immune complexes (ICs) and facilitate IC clearance from the circulation. Chronic hepatitis C virus (HCV) infection is associated with IC-related disorders. In this study, we investigated the kinetics and mechanism of HCV and HCV-IC binding to and dissociation from erythrocytes. Cell culture-produced HCV was mixed with erythrocytes from healthy blood donors, and erythrocyte-associated virus particles were quantified. Purified complement proteins, complement-depleted serum, and complement receptor antibodies were used to investigate complement-mediated HCV-erythrocyte binding. Purified HCV-specific immunoglobulin G (IgG) from a chronic HCV-infected patient was used to study complement-mediated HCV-IC/erythrocyte binding. Binding of HCV to erythrocytes increased 200- to 1,000-fold after adding complement active human serum in the absence of antibody. Opsonization of free HCV occurred within 10 minutes, and peak binding to erythrocytes was observed at 20-30 minutes. Complement protein C1 was required for binding, whereas C2, C3, and C4 significantly enhanced binding. Complement receptor 1 (CR1, CD35) antibodies blocked the binding of HCV to erythrocytes isolated from chronically infected HCV patients and healthy blood donors. HCV-ICs significantly enhanced complement-mediated binding to erythrocytes compared to unbound HCV. Dissociation of complement-opsonized HCV from erythrocytes depended on the presence of Factor I. HCV released by Factor I bound preferentially to CD19+ B cells compared to other leukocytes. Conclusion: These results demonstrate that complement mediates the binding of free and IC-associated HCV to CR1 on erythrocytes and provide a mechanistic rationale for investigating the differential phenotypic expression of HCV-IC-related disease.

Data curation is the process of acquiring multiple sources of data, assessing and improving data quality, standardizing, and integrating the data into a usable information product, and eventually disposing of the data. The research describes the building of a proof-of-concept for an unsupervised data curation process addressing a basic form of data cleansing in the form of identifying redundant records through entity resolution and spelling corrections. The novelty of the approach is to use ER as the first step using an unsupervised blocking and stop word scheme based on token frequency. A scoring matrix is used for linking unstandardized references, and an unsupervised process for evaluating linking results based on cluster entropy. The ER process is iterative, and in each iteration, the match threshold is increased. The prototype was tested on 18 fully-annotated test samples of primarily synthetic person data varied in two different ways, good data quality versus poor data quality, and a single record layout versus two different record layouts. In samples with good data quality and using both single and mixed layouts, the final clusters had an average F-measure of 0.91, precision of 0.96, and recall of 0.87 outcomes comparable to results from a supervised ER process. In samples with poor data quality whether mixed or single layout, the average F-measure was 0.78, precision 0.74, and recall 0.83 showing that data quality assessment and improvement is still a critical component of successful data curation. The results demonstrate the feasibility of building an unsupervised ER engine to support data integration for good quality references while avoiding the time and effort to standardize reference sources to a common layout, design, and test matching rules, design blocking keys, or test blocking alignment. Also, the paper proposes how unsupervised data quality improvement processes could also be incorporated into the design allowing the model to address an even broader range of data curation applications.

The goal of this study was to determine whether an association exists between circulating microRNA (miRNA) levels and disease progression in chronic hepatitis C (CHC), whether plasma or extracellular vesicles (EVs) were optimal for miRNA measurement and their correlation with hepatic miRNA expression, and the mechanistic plausibility of this association. We studied 130 CHC patients prospectively followed over several decades. A comprehensive miRNA profile in plasma using microarray with 2578 probe sets showed 323 miRNAs differentially expressed between healthy individuals and CHC patients, but only six that distinguished patients with mild versus severe chronic hepatitis. Eventually, let-7a/7c/7d-5p and miR-122-5p were identified as candidate predictors of disease progression. Cross-sectional analyses at the time of initial liver biopsy showed that reduced levels of let-7a/7c/7d-5p (let-7s) in plasma were correlated with advanced histological hepatic fibrosis stage and other fibrotic markers, whereas miR-122-5p levels in plasma were positively correlated with inflammatory activity, but not fibrosis. Measuring let-7s levels in EVs was not superior to intact plasma for discriminating significant hepatic fibrosis. Longitudinal analyses in 60 patients with paired liver biopsies showed that let-7s levels in plasma markedly declined over time in parallel with fibrosis progression. However, circulating let-7s levels did not parallel those in the liver. Conclusion: Of all miRNAs screened, the let-7 family showed the best correlation with hepatic fibrosis in CHC. A single determination of let-7s levels in plasma did not have superior predictive value for significant hepatic fibrosis compared with that of fibrosis-4 index, but the rate of let-7s decline in paired longitudinal samples correlated well with fibrosis progression. Pathway analysis suggested that low levels of let-7 may influence hepatic fibrogenesis through activation of transforming growth factor β signaling in hepatic stellate cells. (Hepatology 2016;64:732-745)

Clinical cases of paralytic shellfish poisoning (PSP) are common in Alaska, and result from human consumption of shellfish contaminated with saxitoxin (STX) and its analogues. Diagnosis of PSP is presumptive and based on recent ingestion of shellfish and presence of manifestations consistent with symptoms of PSP; diagnosis is confirmed by detection of paralytic shellfish toxins in a clinical specimen or food sample. A clinical diagnostic analytical method using high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) was used to evaluate the diagnosis of saxitoxin-induced PSP (STX-PSP) in 11 Alaskan patients using urine specimens collected between June 2010 and November 2011. Concentrations of urinary STX were corrected for creatinine concentrations to account for dilution or concentration of urine from water intake or restriction, respectively. Of the 11 patients with suspected PSP, four patients were confirmed to have STX-PSP by urine testing (24-364ng STX/g creatinine). Five patients had clinical manifestations of PSP though no STX was detected in their urine. Two patients were ruled out for STX-PSP based on non-detected urinary STX and the absence of clinical findings. Results revealed that dysphagia and dysarthria may be stronger indicators of PSP than paresthesia and nausea, which are commonly used to clinically diagnose patients with PSP. PSP can also occur from exposure to a number of STX congeners, such as gonyautoxins, however their presence in urine was not assessed in this investigation. In addition, meal remnants obtained from six presumptive PSP cases were analyzed using the Association of Official Analytical Chemists' mouse bioassay. All six samples tested positive for PSP toxins. In the future, the clinical diagnostic method can be used in conjunction with the mouse bioassay or HPLC-MS/MS to assess the extent of STX-PSP in Alaska where it has been suggested that PSP is underreported.

The perovskite SrCo0.9Nb0.1O3−δ (SCN) has excellent electrochemical activity toward oxygen reduction, and it is also valuable as a possible model material for other state-of-the-art perovskite catalysts based on strontium and cobalt, such as Ba0.5Sr0.5Co0.8Fe0.2O3−δ (BSCF). Here we report thermogravimetric, conductivity, and diffraction measurements from SCN. We find that the thermodynamic stability limits of SCN are slightly more favorable than those reported for BSCF, although both materials exhibit a slow oxidative partial decomposition under likely operating conditions. In SCN, this decomposition is thermodynamically preferred when the average formal oxidation state of cobalt is greater than ∼3.0+, but due to sluggish kinetics, metastable SCN with higher cobalt valence can be observed. The oxygen stoichiometry 3−δ varies from 2.45 to 2.70 under the conditions studied, 500–1000 °C and 10–4–1 bar O2, which encompass both stable and metastable behavior. The electronic conductivity is p-type and thermally...

Author(s): Mudan, Anita; Copan, Lori; Wang, Richard; Pugh, Amy; Lebin, Jacob; Barreau, Tracy; Jones, Robert L; Ghosal, Sutapa; Lee, Mai; Albertson, Timothy; Jarrett, Jeffery M; Lee, Jean; Betting, David; Ward, Cynthia D; De Leon Salazar, Alfonsina; Smollin, Craig G; Blanc, Paul D

Introduction Polybrominated diphenyl ethers (PBDEs) comprise a class of halogenated compounds used extensively as flame retardant chemicals in consumer products resulting in nearly ubiquitous human exposure. Mounting evidence suggests that PBDEs are developmental neurotoxicants; however, associations between early life exposure and child behavior have been largely limited to a single developmental time point. Methods The study population consists primarily of white, black and Chinese women who were pregnant on 11 September 2001 and delivered at 1 of 3 downtown New York City hospitals. Maternal–child pairs were followed through age 7 years. Cord blood was collected at delivery and PBDE plasma levels for 210 samples were analyzed by the U.S. Centers for Disease Control and Prevention. The Child Behavior Checklist, a validated maternal-report instrument used for assessing child behavior, was administered annually between the ages of 3 and 7 years. We analyzed the association between natural log-transformed and dichotomized (low vs. high) PBDEs and attention problems using multivariable adjusted negative binomial regression. Results We detected 4 PBDE congeners in more than 50% of samples, with concentrations highest for BDE-47 (median ± IQR: 11.2 ± 19.6 ng/g). In adjusted analyses, we detected associations between BDE-47 (1.21, 95% CI: 1.00, 1.47), and BDE-153 (1.18, 95% CI: 1.00, 1.39) in cord plasma and increased attention problems among children at age 4 (n = 109) but not 6 (n = 107) years. Conclusions Our findings demonstrate a positive trend between prenatal PBDE exposure and early childhood attention problems, and are consistent with previous research reporting associations between prenatal PBDE exposure and disrupted child behaviors.

Enhancing student academic performance and transdisciplinary ability is challenging, but the time and effort put into accomplishing this ambitious feat is priceless. We develop secure privacy preserving across Personal Health Data (PHD) repository and single-cell genomics research for building an Innovative Systematic Pedagogy for Integrated Research - Education (INSPIRE) (http://americancse.org/events/csce2017/csce17_awards). In this paper we further build a novel, eclectic, and insightful framework based on classical and popular machine learning approaches to help us meet the educational challenge. Our framework focuses on using integrative research technologies to help solve “Education’s Performance Prediction Data Mining Crisis” (EPPDMC), by putting to rest issues associated with mining and making best use of big data for educational enhancement, such as multi-source education acquisition, data fusion, and unstructured data analysis. We exploit the uses of deep learning, text classification, and semi-supervised learning approaches to solve challenging problems that educators face when analyzing multiplatform big data involved in education, research and training students. Based on new machine learning approached we developed for genomic big-data research and in combination with machine learning methods (http://americancse.org/events/csce2017/keynotes_lectures/yang_talk) and the vast availability of education data available to us, not only can we utilize structured, unstructured, and even multi-media data, but while engaging in leaning intelligent thinking along the way, we can also maximize the utilization of big data by studying the motion and performance of these data. Hence we build the INSPIRE model that can further incorporate Student Face Expression in Class (SFEiC) to help educators and managers make further improvements as they become involved in the teaching-learning process. This research further facilitates the effectiveness of the INSPIRE model.

The presence of metals in the environment is ubiquitous and humans are constantly being exposed to them. As such, a general concern exists about potential health consequences that result from the exposure to metals. The continued efforts of environmental scientists to measure metals in clinical specimens are important for defining the extent of human exposure to these chemicals. Laboratory methods to measure the concentration of metals in human blood or urine are available, and they can be used to assess the extent of human exposure to these chemicals. However, several considerations should be reviewed when requesting a laboratory measurement of metals because some factors can affect the test result or its interpretation. These considerations are discussed in this article and include pre-analytical, analytical, and post-analytical factors. Clinicians with this knowledge will be able to request these laboratory tests for their patients with enhanced confidence.

Protein kinase R (PKR), a sensor of double-stranded RNA, plays an important role in the host response to viral infection. Hepatitis C genotype 2a virus (HCV2a) has been shown to induce PKR activation to suppress the translation of antiviral interferon stimulated genes (ISGs), suggesting that PKR inhibitor can be beneficial for treating chronically HCV-infected patients in conjunction with interferon alpha and ribavirin. However, in this study, we found that PKR inhibition using siRNA PKR, shRNA PKR or PKR inhibitor enhanced HCV 1a replication and rendered Huh7.5.1 cells more susceptible to HCV1a infection. Additionally, PKR silencing suppressed NF-kB activation and NF-kB mediated STAT1 phosphorylation in Huh7.5.1 cells and HCV1a persistently infected Huh7.5.1 cells (2HDD4). These effects were accompanied by a reduction of interferon beta response and thereby enhanced HCV1a replication in Huh7.5.1 cells. We conclude that host cells can employ PKR activation to restrict HCV1a replication through regulation of NF-kB expression.

Arrays of aligned carbon nanotubes (CNTs) under compression are known to exhibit a dissipative hysteretic response similar to classical foams. Here, we control the microstructure of the arrays during synthesis using a variable supply of carbon source and catalyst. We control CNT alignment and density along the array height, creating bands of high- and low-density regions. We study the dynamic response of these materials and show the ability to tailor the location and extent of strain localization under compression. We show that the synthesis procedures described herein allow for construction of CNT arrays with improved protection and energy dissipation in impact tests.