Semiparametric estimation of random coefficients in structural economic models

This paper discusses nonparametric estimation of the distribution of random coefficients in a structural model that is nonlinear in the random coefficients. We establish that the problem of recovering the probability density function (pdf) of random parameters falls into the class of convexly-constrained inverse problems. The framework offers an estimation method that separates computational solution of the structural model from estimation. We first discuss nonparametric identification. Then, we propose two alternative estimation procedures to estimate the density and derive their asymptotic properties. Our general framework allows us to deal with unobservable nuisance variables, e.g., measurement error, but also covers the case when there are no such nuisance variables. Finally, Monte Carlo experiments for several structural models are provided which illustrate the performance of our estimation procedure

Facile O-atom insertion into C-C and C-H bonds by a trinuclear copper complex designed to harness a singlet oxene

Two trinuclear copper [CuICuICuI(L)]1+ complexes have been prepared with the multidentate ligands (L) 3,3'-(1,4-diazepane-1,4-diyl)bis(1-((2-(dimethylamino)ethyl)(methyl)amino)propan-2-ol) (7-Me) and (3,3'-(1,4-diazepane-1,4-diyl)bis(1-((2-(diethylamino) ethyl)(ethyl) amino)propan-2-ol) (7-Et) as models for the active site of the particulate methane monooxygenase (pMMO). The ligands were designed to form the proper spatial and electronic geometry to harness a "singlet oxene," according to the mechanism previously suggested by our laboratory. Consistent with the design strategy, both [CuICuICuI(L)]1+ reacted with dioxygen to form a putative bis(µ3-oxo)CuIICuIICuIII species, capable of facile O-atom insertion across the central C-C bond of benzil and 2,3-butanedione at ambient temperature and pressure. These complexes also catalyze facile O-atom transfer to the C-H bond of CH3CN to form glycolonitrile. These results, together with our recent biochemical studies on pMMO, provide support for our hypothesis that the hydroxylation site of pMMO contains a trinuclear copper cluster that mediates C-H bond activation by a singlet oxene mechanism

Association Between Proportion of Nuclei With High Chromatin Entropy and Prognosis in Gynecological Cancers

Background: Nuclear texture analysis measuring differences in chromatin structure has provided prognostic biomarkers in several cancers. There is a need for improved cell-by-cell chromatin analysis to detect nuclei with highly disorganized chromatin. The purpose of this study was to develop a method for detecting nuclei with high chromatin entropy and to evaluate the association between the presence of such deviating nuclei and prognosis. Methods: A new texture-based biomarker that characterizes each cancer based on the proportion of high–chromatin entropy nuclei (<25% vs ≥25%) was developed on a discovery set of 175 uterine sarcomas. The prognostic impact of this biomarker was evaluated on a validation set of 179 uterine sarcomas, as well as on independent validation sets of 246 early-stage ovarian carcinomas and 791 endometrial carcinomas. More than 1 million images of nuclei stained for DNA were included in the study. All statistical tests were two-sided. Results: An increased proportion of high–chromatin entropy nuclei was associated with poor clinical outcome. The biomarker predicted five-year overall survival for uterine sarcoma patients with a hazard ratio (HR) of 2.02 (95% confidence interval [CI] = 1.43 to 2.84), time to recurrence for ovarian cancer patients (HR = 2.91, 95% CI = 1.74 to 4.88), and cancer-specific survival for endometrial cancer patients (HR = 3.74, 95% CI = 2.24 to 6.24). Chromatin entropy was an independent prognostic marker in multivariable analyses with clinicopathological parameters (HR = 1.81, 95% CI = 1.21 to 2.70, for sarcoma; HR = 1.71, 95% CI = 1.01 to 2.90, for ovarian cancer; and HR = 2.03, 95% CI = 1.19 to 3.45, for endometrial cancer). Conclusions: A novel method detected high–chromatin entropy nuclei, and an increased proportion of such nuclei was associated with poor prognosis. Chromatin entropy supplemented existing prognostic markers in multivariable analyses of three gynecological cancer cohorts.publishedVersio

Integrated Water Resources Management: STRIVER Efforts to Assess the Current Status and Future Possibilities in Four River Basins

The contemporary concept of Integrated Water Resources Management (IWRM) was primarily conceived for the purpose of promoting sustainable water management. There are many elements included in modern IWRM perceptions, e.g., natural resource utilization planning combined with at strategy to balance between social, economic and environmental objectives based on an overall sustainability concept. However, the concept behind IWRM is not new. The historical development of the concept of Integrated Water Resources Management (IWRM) can be found in Rahaman and Varis (2005).Peer Reviewe

Cooperative Regulation of the Activity of Factor Xa within Prothrombinase by Discrete Amino Acid Regions from Factor Va Heavy Chain†

ABSTRACT: The prothrombinase complex catalyzes the activation of prothrombin to R-thrombin. We have repetitively shown that amino acid region 695DYDY698 from the COOH terminus of the heavy chain of factor Va regulates the rate of cleavage of prothrombin at Arg271 by prothrombinase. We have also recently demonstrated that amino acid region 334DY335 is required for the optimal activity of prothrombinase. To assess the effect of these six amino acid residues on cofactor activity, we created recombinant factor Va molecules combining mutations at amino acid regions 334–335 an

Cleavage Requirements for Activation of Factor V by Factor Xa

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65728/1/j.1432-1033.1997.00012.x.pd

False-Positive Human Immunodeficiency Virus Enzyme Immunoassay Results in Pregnant Women

Objective: Examine whether false-positive HIV enzyme immunoassay (EIA) test results occur more frequently among pregnant women than among women who are not pregnant and men (others). Design: To obtain a large number of pregnant women and others tested for HIV, we identified specimens tested at a national laboratory using Genetic Systems HIV-1/HIV-2 Plus O EIA from July 2007 to June 2008. Methods: Specimens with EIA repeatedly reactive and Western blot-negative or indeterminate results were considered EIA false-positive. We compared the false-positive rate among uninfected pregnant women and others, adjusting for HIV prevalence. Among all reactive EIAs, we evaluated the proportion of false-positives, positive predictive value (PPV), and Western blot bands among indeterminates, by pregnancy status. Results: HIV prevalence was 0.06 % among 921,438 pregnant women and 1.34 % among 1,103,961 others. The false-positive rate was lower for pregnant women than others (0.14 % vs. 0.21%, odds ratio 0.65 [95 % confidence interval 0.61, 0.70]). Pregnant women with reactive EIAs were more likely than others (p,0.01) to have Western blot-negative (52.9 % vs. 9.8%) and indeterminate results (17.0 % vs. 3.7%) and lower PPV (30 % vs. 87%). The p24 band was detected more often among pregnant women (p,0.01). Conclusions: False-positive HIV EIA results were rare and occurred less frequently among pregnant women than others

Deep learning for prediction of colorectal cancer outcome: a discovery and validation study

Background Improved markers of prognosis are needed to stratify patients with early-stage colorectal cancer to refine selection of adjuvant therapy. The aim of the present study was to develop a biomarker of patient outcome after primary colorectal cancer resection by directly analysing scanned conventional haematoxylin and eosin stained sections using deep learning. Methods More than 12 000 000 image tiles from patients with a distinctly good or poor disease outcome from four cohorts were used to train a total of ten convolutional neural networks, purpose-built for classifying supersized heterogeneous images. A prognostic biomarker integrating the ten networks was determined using patients with a non-distinct outcome. The marker was tested on 920 patients with slides prepared in the UK, and then independently validated according to a predefined protocol in 1122 patients treated with single-agent capecitabine using slides prepared in Norway. All cohorts included only patients with resectable tumours, and a formalin-fixed, paraffin-embedded tumour tissue block available for analysis. The primary outcome was cancer-specific survival. Findings 828 patients from four cohorts had a distinct outcome and were used as a training cohort to obtain clear ground truth. 1645 patients had a non-distinct outcome and were used for tuning. The biomarker provided a hazard ratio for poor versus good prognosis of 3·84 (95% CI 2·72–5·43; p<0·0001) in the primary analysis of the validation cohort, and 3·04 (2·07–4·47; p<0·0001) after adjusting for established prognostic markers significant in univariable analyses of the same cohort, which were pN stage, pT stage, lymphatic invasion, and venous vascular invasion. Interpretation A clinically useful prognostic marker was developed using deep learning allied to digital scanning of conventional haematoxylin and eosin stained tumour tissue sections. The assay has been extensively evaluated in large, independent patient populations, correlates with and outperforms established molecular and morphological prognostic markers, and gives consistent results across tumour and nodal stage. The biomarker stratified stage II and III patients into sufficiently distinct prognostic groups that potentially could be used to guide selection of adjuvant treatment by avoiding therapy in very low risk groups and identifying patients who would benefit from more intensive treatment regimes