Miracle-dz/UniFAR-FTUs huggingface dataset:
Peripheral blood reverse transcription PCR assay for prostate stem cell antigen correlates with androgen‐independent progression in advanced prostate cancer

Recent studies show that prostate stem cell antigen (PSCA) mRNA positivity in peripheral blood correlates with disease progression in prostate cancer (PCa). Our study is to evaluate the association between peripheral blood PSCA status and androgen‐independent progression (AIP) in a cohort of patients with advanced PCa under androgen deprivation therapy (ADT). PSCA mRNA was measured by reverse transcriptase polymerase chain reaction (RT‐PCR) assay in peripheral blood samples from 116 patients with locally advanced or metastatic PCa who were treated with primary ADT and from 40 healthy controls. The Kaplan–Meier and the Cox proportional hazards methods were used to assess potential predictors of AIP. Pretreatment RT‐PCR‐PSCA was positive in 37 (31.9%) of 116 patients. All healthy volunteers were negative for PSCA mRNA. Although seven (14.9%) of 47 patients with Gleason score ≤7 were PSCA positive, 30 (43.5%) of 69 patients with Gleason score >7 were PSCA positive (p = 0.016). PSCA mRNA was detected in 28 (58.3%) of 48 patients with metastatic PCa, compared to nine (13.2%) of 68 patients with locally advanced disease (p = 0.012). AIP developed in 59 (50.9%) patients during a median follow‐up period of 35.4 months (range: 4–78 months). Patients with PSCA negativity experienced significantly longer remissions compared to those with PSCA positivity (log‐rank test: p < 0.001). Multivariate Cox regression analysis further demonstrated that PSCA positivity had a significantly increased risk of AIP (HR = 4.303, 95% CI: 3.761–7.482, p < 0.001). Pretreatment RT‐PCR PSCA positivity in peripheral blood independently signals the presence of AIP in patients with advanced PCa treated with ADT.
Quantitative PCR for Detection and Enumeration of Genetic Markers of Bovine Fecal Pollution

ABSTRACT Accurate assessment of health risks associated with bovine (cattle) fecal pollution requires a reliable host-specific genetic marker and a rapid quantification method. We report the development of quantitative PCR assays for the detection of two recently described bovine feces-specific genetic markers and a method for the enumeration of these markers using a Markov chain Monte Carlo approach. Both assays exhibited a range of quantification from 25 to 2 × 106 copies of target DNA, with a coefficient of variation of <2.1%. One of these assays can be multiplexed with an internal amplification control to simultaneously detect the bovine-specific genetic target and presence of amplification inhibitors. The assays detected only cattle fecal specimens when tested against 204 fecal DNA extracts from 16 different animal species and also demonstrated a broad distribution among individual bovine samples (98 to 100%) collected from five geographically distinct locations. The abundance of each bovine-specific genetic marker was measured in 48 individual samples and compared to quantitative PCR-enumerated quantities of rRNA gene sequences representing total Bacteroidetes, Bacteroides thetaiotaomicron, and enterococci in the same specimens. Acceptable assay performance combined with the prevalence of DNA targets across different cattle populations provides experimental evidence that these quantitative assays will be useful in monitoring bovine fecal pollution in ambient waters.
Comparison of Deformation Models of Flexible Manipulator Joints for Use in DEMO

The joint deformation contributes significantly to final end-effector displacement of a manipulator, especially when the manipulator is in the form a serial kinematics with long links. When the manipulators employed in the DEMO are under the heavy payload, the deformation of manipulator is inevitable and the magnitude is significant. In order to maneuver the large object through several via points with high positioning accuracy in the remote handling process of DEMO, the real-time computation of manipulator deformation has to be conducted, which is crucial to the DEMO adaptive position control system for the displacement compensation. Three computation-effective deformation modeling methods are proposed in this paper, which are parametric modeling method, nonparametric deterministic artificial neural network (ANN) modeling method, and nonparametric Bayesian ANN modeling method, respectively. A specific joint in a boom equipped in a telescopic articulated remote mast is taken as the study object in this paper. A nodal deformation in the joint is investigated by three modeling methods, respectively. The parametric deformation model is derived by using the structural mechanics, whose parameters are identified by using the Markov chain Monte Carlo (MCMC) method; the deformation model of deterministic ANN is trained by using the Levenberg–Marquardt method; and the deformation model of the Bayesian ANN is trained by using the MCMC method. The results show that the parametric model from the structural mechanics is linear and is incompetent in the deformation modeling when the nonlinearity presents; both the deterministic and Bayesian ANNs are capable of model the nodal deformation of joint. The performance of both the deterministic network and Bayesian network cannot rival for one another in the application scenario of this paper. The training of the Bayesian network can provide the criterions for estimation of possible ranges of the modeling outputs from its probabilistic distribution curves, and the judgment of proper size of network.
On the Ability of Galactose to Influence Hexose and Amino Acid Uptake by Isolated Rat Brain Capillaries

Abstract: The uptake of glucose, 2‐deoxyglucose, proline, methionine, and α‐methylamino isobutyric acid was studied in brain capillaries preincubated with 50 mM galactose either in vitro or isolated from galactose‐fed rats. The uptake was not decreased in both cases. The linear rate of glucose oxidation by capillaries was also not altered by preincubation with galactose.
Perinatal outcome after maternal primary cytomegalovirus infection in the first trimester: a practical update and counseling aid

Cytomegalovirus (CMV) is the most common cause of congenital infection with approximately 0.5% of pregnant women in developed countries seroconverting during pregnancy. In utero transmission occurs in about one third of women who develop primary infection in the first trimester, and these fetuses are at risk for adverse perinatal outcomes and long‐term neurological complications. The great promise of a prenatal therapy to reduce fetal infection after maternal primary CMV infection has not been realized to date. The prediction of CMV sequelae is particularly challenging for clinicians because of the heterogeneity of the published literature, the wide spectrum of perinatal outcomes, the adjustment of fetal risk at each stage of assessment, and the variable quality of published data. Given the continued lack of a proven fetal therapy, it is timely to review the natural history of congenital CMV in the modern management era. We have analyzed the recent literature, integrated findings from multiple studies, and calculated stage‐specific risks for adverse perinatal outcome to assist in counseling women with first trimester primary CMV infection. © 2014 John Wiley & Sons, Ltd.
An Empirical Assessment of Common Fundamentals In National E-Readiness Frameworks

Abstract While e-business and e-government are becoming drivers for the socioeconomic modernization of nations, much remains to be learned about the economic, political, and infrastructural factors associated with nations' e-business and e-government activity. In recent years, numerous e-readiness frameworks - derived in large part from theory in developmental and institutional socioeconomics - have been proffered to help guide nations in these modernization efforts. The present study derives a research model based upon common variables across e-readiness frameworks as well as related prior research to investigate associations between hypothesized key national factors and reported levels of e-business and e-government activity. Six potentially key factors are identified, cascading from general national characteristics to internet-specific characteristics: general economic prosperity, technological innovativeness, and tertiary education; internet service provider competition, law, and penetration. Data made available by the World Bank, the International Telecommunications Union, UNESCO, and the World Economic Forum are used to investigate the hypothesized associations across ninety-two countries. PLS is used to analyze the models and shows that the proposed models explain substantial variance in reported e-business and e-government levels. Moreover, intriguing similarities and differences are found.
Conflict of Interest and Reputation in the Issuance of Public Securities: Evidence from Venture Capital

In this paper we investigate potential conflicts of interest in the issuance of public securities in a setting analogous to a universal bank, i.e., the underwriting of initial public offerings by investment banks that hold equity in a firm through a venture capital subsidiary. We contrast two hypotheses. Under "rational discounting," all market participants fully anticipate the conflict. The "naive investor" hypothesis suggests that investment banks are able to utilize superior information when they underwrite securities. The evidence supports the rational discounting hypothesis. Initial public offerings that are underwritten by affiliated investment banks perform as well or better than issues of firms in which none of the investment banks held a prior equity position. Investors do, however, require a greater discount at the offering to compensate for potential adverse selection. We also provide evidence that investment bank-affiliated venture firms address the potential conflict by investing in and subsequently underwriting less information-sensitive issues. Our evidence provides no support for the prohibitions on universal banking instituted by the Glass-Steagall Act of 1933.
White Matter Fiber Tracking Method by Vector Interpolation with Diffusion Tensor Imaging Data in Human Brain

The directional diffusion information obtained by diffusion tensor magnetic resonance imaging (DT-MRI) can be used to noninvasively visualize white matter fibers in human brain. And it is the unique way to reconstruct those fibers in vivo. However, there are some obstacles for the reconstruction process, e.g., partial volume effect caused by low spatial resolution negatively affects the DT-MRI results, and continuous fibers are indicated by the discrete signal on the DT-MRI. A fiber tracking algorithm is proposed in this paper. Major eigenvectors and fractional anisotropy (FA) values of the correlative voxels are used for fiber tracking. As a result, this method shows stronger potential to depict the distribution of white matter fibers in human brain
Simple and Enlarged Separation Portfolios: On their Use when Arbitraging and Synthesizing Securities

This paper seeks to provide a framework for separation portfolios when they are used not only as synthetics of a matching security but also as building blocks of arbitrage portfolios, in a background provided by the CAPM world. Firstly, synthetics are defined by means of a vectorial framework that maps portfolios onto their risk-return profiles. Separation portfolios are extensively analyzed afterwards, establishing three propositions that lay the groundwork for using them as synthetics. Next, a distinction is brought about between plain separation portfolios (which are located on the Capital Market Line) and enlarged separation portfolios (which lie outside the CML). Furthermore, it is shown that simple separation portfolios become synthetics in few cases only, whereas enlarged portfolios allow for synthetics in much wider contexts. Later, arbitrage portfolios are designed by means of simple separation portfolios in the context of the Security Market Line, and also by resorting to the enlarged ones without requiring the SML as a benchmark. Finally, the discussion extends over bond portfolios, to embody their risky features into the viewpoint set forth in the paper.
Dynamics of a morbillivirus at the domestic–wildlife interface: Canine distemper virus in domestic dogs and lions

Significance Morbilliviruses are a growing concern because of their ability to infect multiple species. The spill-over of canine distemper virus (CDV) from domestic dogs has been associated with severe declines in wild carnivores worldwide, and therefore mass dog vaccination has been suggested as a potential control strategy. Focusing on three decades of CDV exposure data in dogs and lions of the Serengeti, we show that cyclic infection dynamics in lions initially driven by dogs became more frequent and asynchronous, suggesting that the wider dog population and other wildlife species drive CDV dynamics. Hence, although widespread dog vaccination reduced the infection in dogs, transmission to lion populations still occurred, warranting further investigation into effective management options of CDV in this species-rich ecosystem. Morbilliviruses cause many diseases of medical and veterinary importance, and although some (e.g., measles and rinderpest) have been controlled successfully, others, such as canine distemper virus (CDV), are a growing concern. A propensity for host-switching has resulted in CDV emergence in new species, including endangered wildlife, posing challenges for controlling disease in multispecies communities. CDV is typically associated with domestic dogs, but little is known about its maintenance and transmission in species-rich areas or about the potential role of domestic dog vaccination as a means of reducing disease threats to wildlife. We address these questions by analyzing a long-term serological dataset of CDV in lions and domestic dogs from Tanzania’s Serengeti ecosystem. Using a Bayesian state–space model, we show that dynamics of CDV have changed considerably over the past three decades. Initially, peaks of CDV infection in dogs preceded those in lions, suggesting that spill-over from dogs was the main driver of infection in wildlife. However, despite dog-to-lion transmission dominating cross-species transmission models, infection peaks in lions became more frequent and asynchronous from those in dogs, suggesting that other wildlife species may play a role in a potentially complex maintenance community. Widespread mass vaccination of domestic dogs reduced the probability of infection in dogs and the size of outbreaks but did not prevent transmission to or peaks of infection in lions. This study demonstrates the complexity of CDV dynamics in natural ecosystems and the value of long-term, large-scale datasets for investigating transmission patterns and evaluating disease control strategies.
Structure and Function of a Family 10 β-Xylanase Chimera of Streptomyces olivaceoviridis E-86 FXYN and Cellulomonas fimi Cex*

The catalytic domain of xylanases belonging to glycoside hydrolase family 10 (GH10) can be divided into 22 modules (M1 to M22; Sato, Y., Niimura, Y., Yura, K., and Go, M. (1999) Gene (Amst.) 238, 93-101). Inspection of the crystal structure of a GH10 xylanase from Streptomyces olivaceoviridis E-86 (SoXyn10A) revealed that the catalytic domain of GH10 xylanases can be dissected into two parts, an N-terminal larger region and C-terminal smaller region, by the substrate binding cleft, corresponding to the module border between M14 and M15. It has been suggested that the topology of the substrate binding clefts of GH10 xylanases are not conserved (Charnock, S. J., Spurway, T. D., Xie, H., Beylot, M. H., Virden, R., Warren, R. A. J., Hazlewood, G. P., and Gilbert, H. J. (1998) J. Biol. Chem. 273, 32187-32199). To facilitate a greater understanding of the structure-function relationship of the substrate binding cleft of GH10 xylanases, a chimeric xylanase between SoXyn10A and Xyn10A from Cellulomonas fimi (CfXyn10A) was constructed, and the topology of the hybrid substrate binding cleft established. At the three-dimensional level, SoXyn10A and CfXyn10A appear to possess 5 subsites, with the amino acid residues comprising subsites -3 to +1 being well conserved, although the +2 subsites are quite different. Biochemical analyses of the chimeric enzyme along with SoXyn10A and CfXyn10A indicated that differences in the structure of subsite +2 influence bond cleavage frequencies and the catalytic efficiency of xylooligosaccharide hydrolysis. The hybrid enzyme constructed in this study displays fascinating biochemistry, with an interesting combination of properties from the parent enzymes, resulting in a low production of xylose.
Using of a graphite-polyurethane composite electrode modified with a Schiff base as a bio-inspired sensor in the dopamine determination

A solid composite electrode based on graphite and polyurethane resin modified with a copper(II) complex of the symmetrical tetradentate Schiff's base type, N, N'-ethylenebis(salicylideneiminato) copper(II) ([Cu(II)Salen]), was evaluated as a bio-inspired sensor using dopamine (DA) as a model analyte. The voltammetric behavior of the modifier [Cu(II)Salen] was investigated at a modified carbon paste electrode and a redox mechanism was proposed. The analytical potentialities of the composite electrode based on graphite and polyurethane resin (GPU) modified with [Cu(II)Salen] (MGPU) were evaluated using DA as probe. MGPU presents best results when compared with GPU without modification, with electrocatalytic effect, indicating that the electrode can be characterized as a bio-inspired sensor. The MGPU electrode was applied in the determination of DA in pharmaceutical formulation using DPV and the results were compared to those obtained with the official method (high performance liquid chromatography, HPLC) as described in US Pharmacopoeia, agreeing within 95% confidence level according to student's t-test.
The evaluation of a dynamic, mechanistic, thermal balance model for Bos indicus and Bos taurus

SUMMARY The Thompson model (Thompson et al., in press), a heat balance model for cattle, was evaluated for Bos indicus and B. taurus under different climate conditions through the use of two local and one global sensitivity analyses and tested against independent datasets. The local analyses, which evaluate the individual effects of parameters on model output, showed that the vasodilation/vasoconstriction parameter and reference body temperature (Tbref) strongly affected body temperature. The global analysis, which evaluates the overall effect of parameters on model output, showed that 6 out of 24 parameters account for 0·79–0·89 of the model variation. The high proportion of variation accounted for by the parameters demonstrates that the model is linear in its parameters, with little interaction between the parameters. The Thompson model was tested against four independent datasets which included both B. indicus and B. taurus animals. The prediction of the relationship between skin and body temperature from the model aligned closely with the relationship in the datasets (R2 ranged from 0·55 to 0·87, mean bias ranged from 0·32 to 1·49). The prediction of sweating and respiration rates from the model aligned closely with the rates measured in the datasets (R2 ranged from 0·80 to 0·98 and 0·79 to 0·93, respectively). The delay in the diurnal body temperature variation, relative to air temperature, was more accurately predicted for cattle in the sun than for cattle in climate chambers. Given the limited datasets for construction and parameterization (both of which are described in Thompson et al., in press), the model evaluated in the current study performed relatively well compared to the literature and known biology.
Diachronic semantic cohesion for topic segmentation of TV broadcast news

This paper proposes a new way to integrate semantic relations into a topic segmentation process by deﬁning the notion of semantic cohesion. In the context of a sliding window based automatic topic segmentation algorithm, semantic relations are incorporated in the similarity measure between adjacent blocs. Additionaly, in the context of TV Brodcast News topic segmentation, we propose a new protocole to gather relevant data for semantic relations computation, showing that a small set of di-achronic data can be more relevant for the task than using a large amount of general or asynchronous data. Experiments on a corpus of 86 various French TV Broadcast News shows recorded during one week, in conjunction with text articles collected through the Google News homepage at the same period for semantic relation estimation show signiﬁcant improvement in topic segmentation performance.
Compression of convolutional neural networks: A short survey

Nowadays, convolutional neural networks (CNN) are considered as the state-of-the-art algorithms for various tasks, especially for image classification and recognition. Because of that, more and more attention is aimed towards implementation of CNNs on embedded systems. Main obstacles for implementing CNNs on embedded systems are their large model size and large number of operations needed for inference. In order to surpass these obstacles, algorithms for CNN compression tend to lower model size and number of operations needed for inference. In this paper we review the state-of-the-art in CNN compression. To this end we divided all approaches for CNN compression into three groups: precision reduction, network pruning and design of compact network architectures. After presenting the main approaches in each group we conclude that the future CNN compression algorithms should be co-designed with hardware which will process deep learning algorithms.
Explaining Governance Outcomes: Epistemology, Network Governance and Policy Network Analysis

This article focuses on two sets of literature that have developed out of a shared concern with networks: the network governance school, which has been engaged in a set of macro-level questions about the extent to which networks are changing the nature of state-society relations; and the policy network analysis school, which has focused on the relationship between processes of interest intermediation and their impact on policy-making outcomes. We examine how each school is underpinned by important epistemological differences between positivist, interpretivist and critical realist approaches. We argue that these differences complicate and make contestable what would otherwise seem to be an intuitively attractive argument in favour of combining these two schools. In seeking to understand better how these two schools might be combined, we adopt a critical realist approach and make a distinction between vertical coordination on the state-society axis and horizontal coordination on the interest integration axis. This produces a typology of governance arrangements, which are evaluated according to the level of input and output legitimacy that they are likely to generate, two criteria that are taken as overarching measures of how governance outcomes vary between different governance arrangements. This provides the basis for a broader discussion of how these outcomes are conditioned by both a network's structural characteristics and the way in which it is managed.