Miracle-dz/UniFAR-FTUs huggingface dataset:
Factors Affecting the Aldosterone/Renin Ratio

Abstract Although the aldosterone/renin ratio (ARR) is the most reliable screening test for primary aldosteronism, false positives and negatives occur. Dietary salt restriction, concomitant malignant or renovascular hypertension, pregnancy and treatment with diuretics (including spironolactone), dihydropyridine calcium blockers, angiotensin converting enzyme inhibitors, and angiotensin receptor antagonists can produce false negatives by stimulating renin. We recently reported selective serotonin reuptake inhibitors lower the ratio. Because potassium regulates aldosterone, uncorrected hypokalemia can lead to false negatives. Beta-blockers, alpha-methyldopa, clonidine, and nonsteroidal anti-inflammatory drugs suppress renin, raising the ARR with potential for false positives. False positives may occur in patients with renal dysfunction or advancing age. We recently showed that (1) females have higher ratios than males, and (2) false positive ratios can occur during the luteal menstrual phase and while taking an oral ethynylestradiol/drospirenone (but not implanted subdermal etonogestrel) contraceptive, but only if calculated using direct renin concentration and not plasma renin activity. Where feasible, diuretics should be ceased at least 6 weeks and other interfering medications at least 2 before ARR measurement, substituting noninterfering agents (e. g., verapamil slow-release±hydralazine and prazosin or doxazosin) were required. Hypokalemia should be corrected and a liberal salt diet encouraged. Collecting blood midmorning from seated patients following 2–4 h upright posture improves sensitivity. The ARR is a screening test only and should be repeated once or more before deciding whether to proceed to confirmatory suppression testing. Liquid chromatography-tandem mass spectrometry aldosterone assays represent a major advance towards addressing inaccuracies inherent in other available methods.
‘Glocal’ Rhetorical Practices in Academic Writing

This article examines the rhetorical effects of a wide typological spectrum of epistemic modality markers in a contrastive English–Spanish corpus. The article seeks to provide evidence of the way non-native English scholars adopt standard Anglophone strategies for modelling persuasion while at the same time transferring some rhetorical practices of their national language into their L2 English texts. This gives rise to a hybrid modelling of persuasion. In discussing the hybrid (‘glocal’) nature of ‘alternative academic written Englishes’, this article also considers the feasibility of codifying these academic Englishes variants for effective transnational communication. Further, it is argued that academic writing pedagogy should provide exposure to the standard Anglophone norms as well as to its culture-determined variants, since the discoursal heterogeneity of those variants represents alternative spaces of linguistic and cultural production in contemporary research writing.
Blood pressure regulation via the epithelial sodium channel: From gene to kidney and beyond

The epithelial sodium channel (ENaC) has long been recognized as playing a vital role in blood pressure (BP) regulation due to its involvement in fluid balance. The genes encoding the three ENaC subunits are likewise important contributors to hypertension, both in rare monogenic diseases and in the general population. The unusually high numbers of genetic variants associated with complex traits, including BP, that are located in non‐coding areas suggest an involvement of these variants in regulatory functions. This may involve differential regulation of expression in different tissues. Emerging evidence indicates that the ENaC plays an important role in BP determination not only via its actions in the kidney, but also in other tissues commonly involved in BP regulation. The ENaC in the central nervous system is proposed to regulate BP via sympathetic nervous system activity. Recent evidence suggests that the ENaC contributes to vascular function and the myogenic response. Additional roles potentially include initiation of the baroreceptor reflex via ENaC in the baroreceptors and driving high salt intake with a ‘taste for salt’ via ENaC in the tongue. The present review describes the involvement of the ENaC in the determination of BP at a genetic and physiological level, detailing recent evidence for its role in the kidney and in other pertinent tissues.
Interpretations of Discovered Knowledge in Multidimensional Databases

It is a big challenge to guarantee the quality of discovered knowledge in multidimensional databases because of the huge amount of patterns and noises. The essential issue is to provide efficient methods for interpreting meaningful discovered knowledge in databases. This research presents a new technique called granule mining to improve the performance of data mining. Rather than using patterns, it uses granules in different tiers to generalize knowledge in databases. It also provides a mechanism to formally discuss meaningless discovered rules based on relationships between granules in different tiers.
Intelligent Traffic Light Controlling Algorithms Using Vehicular Networks

In this paper, we propose an intelligent traffic light controlling (ITLC) algorithm. ITLC is intended to schedule the phases of each isolated traffic light efficiently. This algorithm considers the real-time traffic characteristics of the competing traffic flows at the signalized road intersection. Moreover, we have adopted the ITLC algorithm to design a traffic scheduling algorithm for an arterial street scenario; we have thus proposed an arterial traffic light (ATL) controlling algorithm. In the ATL controlling algorithm, the intelligent traffic lights installed at each road intersection coordinate with each other to generate an efficient traffic schedule for the entire road network. We report on the performance of ITLC and ATL algorithms for several scenarios using NS-2. From the experimental results, we infer that the ITLC algorithm reduces, at each isolated traffic light, the queuing delay and increases the traffic fluency by 30% compared with the online algorithm (OAF) traffic light scheduling algorithm. The latter algorithm achieved the best performance when compared with the OAF traffic light scheduling algorithm. On the other hand, the ATL controlling algorithm increases the traffic fluency of traveling vehicles at arterial street coordinations by 70% more than the random and separate traffic light scheduling system. Furthermore, compared with the previously introduced traffic scheduling ART-SYS, the ATL controlling algorithm decreases the average delay at each traffic light by 10%.
Diffuse affect as regulator of attitude and behavior processes

The influence of diffuse affect (or mood) on automatic attitude activation and the attitude behavior link was examined. Positive mood induces an intuitive processing style, while negative mood elicits a rather deliberative and cautious processing style. Due to a cautious processing style in negative mood, in several studies it was found that quick responding to automatically activated attitudes is suppressed in negative mood as measured with several automatic evaluation paradigms like evaluative priming. In positive mood, however, a standard automatic evaluation effect was found (i.e., quick responding to automatically activated attitudes). In a second line of research the influence of mood on the attitude-behavior link was studied. As negative mood leads to more deliberative information processing and less reliance on automatic evaluations it was expected that explicit (or belief-based attitudes) would be a good predictor for behavior, while the relation between implicit attitudes and behavior would be weak. On the other hand, as positive mood leads to intuitive processing implicit attitudes should predict behavior more strongly than explicit attitudes. Several studies using different attitude objects and behavior confirmed these hypotheses. The two lines of research show that negative mood elicits a tendency to suppress quick responding to automatically activated information, while positive mood does not. Consistently, the relation between implicit attitudes and behavior is weak in negative mood, but strong in positive mood. Belief-based attitudes predict behavior in negative mood, rather than in positive mood.
Optimal multi-step k-nearest neighbor search

For an increasing number of modern database applications, efficient support of similarity search becomes an important task. Along with the complexity of the objects such as images, molecules and mechanical parts, also the complexity of the similarity models increases more and more. Whereas algorithms that are directly based on indexes work well for simple medium-dimensional similarity distance functions, they do not meet the efficiency requirements of complex high-dimensional and adaptable distance functions. The use of a multi-step query processing strategy is recommended in these cases, and our investigations substantiate that the number of candidates which are produced in the filter step and exactly evaluated in the refinement step is a fundamental efficiency parameter. After revealing the strong performance shortcomings of the state-of-the-art algorithm for k-nearest neighbor search [Korn et al. 1996], we present a novel multi-step algorithm which is guaranteed to produce the minimum number of candidates. Experimental evaluations demonstrate the significant performance gain over the previous solution, and we observed average improvement factors of up to 120 for the number of candidates and up to 48 for the total runtime.
Pleiotropy and Heterogeneity in the Expression of Atherogenic Lipoproteins: The IRAS Family Study

Objective: Dyslipidemia is an important determinant of coronary disease. Phenotypic correlations between atherogenic lipids are well established, but the contribution of common genetic influences is less clear. Methods: This study investigates the pair-wise genetic (ρ<sub>g</sub>) and environmental (ρ<sub>e</sub>) correlations between apoB, LDL-C, HDL-C, and triglyceride (Tg) from Hispanic and African American families of the IRAS Family Study. Results: Heritability estimates (hcirc;<sup>2</sup>) indicate significant genetic effects on apoB (hcirc;<sup>2</sup> = 0.46 ± 0.05), LDL-C (hcirc;<sup>2</sup> = 0.40 ± 0.05), HDL-C (hcirc;<sup>2</sup> = 0.47 ± 0.05), and Tg (hcirc;<sup>2</sup> = 0.35 ± 0.05) (all p < 0.001). Genetic and environmental correlations were strong for apoB – LDL-C (ρ<sub>g</sub> = 0.87, ρ<sub>e</sub> = 0.84), apoB – Tg (ρ<sub>g</sub> = 0.38, ρ<sub>e</sub> = 0.65), and HDL-C – Tg (ρ<sub>g</sub> = –0.42, ρ<sub>e</sub> = –0.46). Environmental correlations were strong for apoB – HDL-C (ρ<sub>e</sub> = –0.40), LDL-C – HDL-C (ρ<sub>e</sub> = –0.24), and Tg – LDL-C (ρ<sub>e</sub> = 0.33) with weak genetic correlations for these pairs (ρ<sub>g</sub> = –0.09, 0.10, 0.09 respectively). Conclusions: These results suggest multiple pathways leading to atherogenic dyslipidemia. There are common genetic and environmental influences contributing to variations in apoB and LDL-C as well as apoB and Tg. In addition, the inverse relation between Tg and HDL-C appears to have both genetic and environmental basis. Identifying genes involved in atherogenic dyslipidemia will require careful dissection of the genetic architecture of these pathways.
Scalable Sparse Subspace Clustering

In this paper, we address two problems in Sparse Subspace Clustering algorithm (SSC), i.e., scalability issue and out-of-sample problem. SSC constructs a sparse similarity graph for spectral clustering by using l1-minimization based coefficients, has achieved state-of-the-art results for image clustering and motion segmentation. However, the time complexity of SSC is proportion to the cubic of problem size such that it is inefficient to apply SSC into large scale setting. Moreover, SSC does not handle with out-of-sample data that are not used to construct the similarity graph. For each new datum, SSC needs recalculating the cluster membership of the whole data set, which makes SSC is not competitive in fast online clustering. To address the problems, this paper proposes out-of-sample extension of SSC, named as Scalable Sparse Subspace Clustering (SSSC), which makes SSC feasible to cluster large scale data sets. The solution of SSSC adopts a "sampling, clustering, coding, and classifying" strategy. Extensive experimental results on several popular data sets demonstrate the effectiveness and efficiency of our method comparing with the state-of-the-art algorithms.
A QM–MM interface between CHARMM and TURBOMOLE: Implementation and application to systems in bulk phase and biologically active systems

The implementation of a hybrid QM–MM approach combining ab initio and density functional methods of TURBOMOLE with the molecular mechanics program package CHARMM is described. An interface has been created to allow data exchange between the two applications. With this method the efficient multiprocessor capabilities of TURBOMOLE can be utilized with CHARMM running as a single processor application. Therefore, features of nonparallel running code in CHARMM like the TRAVEL module for locating saddle points or VIBRAN for the calculation of second derivatives can be exploited by running the CPU intensive QM calculations in parallel. To test the methodology, several small systems are studied with both Hartree–Fock and density functional methods and varying QM–MM boundaries. Also, the computationally efficient RI‐J method has been examined for use in QM–MM applications. A B12 cofactor containing cobalt has been studied, to examine systems with a large QM region and transition metals. All tested methods perform satisfactory in comparison with pure quantum calculations. Additionally, algorithms for the characterization of saddle points have been tested for their potential use in QM–MM problems. The TRAVEL module of CHARMM has been applied to the Menshutkin reaction in the condensed phase, and a saddle point was located. This saddle point was verified by calculation of a steepest descent path connecting educt, transition state, and product, and by calculation of vibrational modes. © 2003 Wiley Periodicals, Inc. J Comput Chem 24: 1240–1249, 2003
Salivary cortisol during opiate dependence and withdrawal

Seventeen inpatients (14 men, three women) with opiate dependence and polysubstance misuse participated in a longitudinal study of salivary cortisol secretion during and after lofexidine detoxification treatment. Both opiate withdrawal symptoms and salivary cortisol were measured every morning for up to 25 days. Results were compared with a control group of 10 normal volunteers. There was an 80% reduction in withdrawal symptom severity between the first 12 days and the subsequent 12 days of treatment. Salivary cortisol fell from a mean of 22.3 nm/l over days 1–12 to 18.5 nm/l during days 13–25, a reduction of 17%. Salivary cortisol concentration correlated significantly with withdrawal symptom severity. Salivary cortisol levels remained significantly higher than controls for the duration of the study. The study supports a role for hypothalamo–pituitary–adrenal (HPA) activation in opiate withdrawal. The contribution of persistant dysregulation of the HPA, found in this study, to the vulnerability for relapse after abstinence has been achieved, is discussed.
Selective Strolls: Fixation and Extinction in Diploids Are Slower for Weakly Selected Mutations Than for Neutral Ones

In finite populations, an allele disappears or reaches fixation due to two main forces, selection and drift. Selection is generally thought to accelerate the process: a selected mutation will reach fixation faster than a neutral one, and a disadvantageous one will quickly disappear from the population. We show that even in simple diploid populations, this is often not true. Dominance and recessivity unexpectedly slow down the evolutionary process for weakly selected alleles. In particular, slightly advantageous dominant and mildly deleterious recessive mutations reach fixation slightly more slowly than neutral ones (at most 5%). This phenomenon determines genetic signatures opposite to those expected under strong selection, such as increased instead of decreased genetic diversity around the selected site. Furthermore, we characterize a new phenomenon: mildly deleterious recessive alleles, thought to represent a wide fraction of newly arising mutations, on average survive in a population slightly longer than neutral ones, before getting lost. Consequently, these mutations are on average slightly older than neutral ones, in contrast with previous expectations. Furthermore, they slightly increase the amount of weakly deleterious polymorphisms, as a consequence of the longer unconditional sojourn times compared to neutral mutations.
Task-relevant roadmaps: A framework for humanoid motion planning

To plan complex motions of robots with many degrees of freedom, our novel, very flexible framework builds task-relevant roadmaps (TRMs), using a new sampling-based optimizer called Natural Gradient Inverse Kinematics (NGIK) based on natural evolution strategies (NES). To build TRMs, NGIK iteratively optimizes postures covering task-spaces expressed by arbitrary task-functions, subject to constraints expressed by arbitrary cost-functions, transparently dealing with both hard and soft constraints. TRMs are grown to maximally cover the task-space while minimizing costs. Unlike Jacobian-based methods, our algorithm does not rely on calculation of gradients, making application of the algorithm much simpler. We show how NGIK outperforms recent related sampling algorithms. A video demo (http://youtu.be/N6x2e1Zf_yg) successfully applies TRMs to an iCub humanoid robot with 41 DOF in its upper body, arms, hands, head, and eyes. To our knowledge, no similar methods exhibit such a degree of flexibility in defining movements.
MICROARRAY DATA INTEGRATION AND TOP-DOWN MODELING OF GENE REGULATION

Microarray technologies allow monitoring of gene activity (or expression) of thousands of genes in parallel at the same time. Although very powerful, their complexity makes the observed data very difficult to integrate across experiments. In the first part of this paper I will introduce the microarray technology and several of our bioinformatics approaches for integrating multiple gene expression data sets using combinatorial and visualization methods. In the second part of the paper I will present some thoughts towards formalizing biological models of gene regulation towards a language of transcription.
Biological activity of human immunodeficiency virus type 1 Vif requires membrane targeting by C-terminal basic domains

Human immunodeficiency virus type 1 (HIV-1) encodes a Vif protein which is important for virus replication and infectivity. Vif is a cytoplasmic protein which exists in both membrane-associated and soluble forms. The membrane-associated form is an extrinsic membrane protein which is tightly associated with the cytoplasmic side of membranes. We have analyzed the mechanism of membrane targeting of Vif and its role in HIV-1 replication. Mutagenesis studies demonstrate that C-terminal basic domains are required for membrane association. Vif mutations which disrupt membrane association also inhibit HIV-1 replication, indicating that membrane localization of Vif is likely to be required for its biological activity in vivo. Membrane binding of Vif is almost completely abolished by trypsin treatment of membranes. These results demonstrate that membrane localization of Vif requires C-terminal basic domains and interaction with a membrane-associated protein(s). This interaction may serve to direct Vif to a specific cellular site, since immunofluorescence staining and plasma membrane fractionation studies show that Vif is localized predominantly to an internal cytoplasmic compartment rather than to the plasma membrane. The mechanism of membrane targeting of Vif is different in some respects from that of other extrinsic membrane proteins, such as Ras, Src, and MARCKS, which utilize a basic domain together with a lipid modification for membrane targeting. Membrane targeting of Vif is likely to play an important role in HIV-1 replication and thus may be a therapeutic target.
Social representations of healthy eating: An empirical study in Colombia.

The practice of health promotion has been dominated by approaches based on theories of the attitude and social cognition. Drawing on two basic assumptions, (a) that individuals are primarily rational, and (b) that there is a causal relationship between attitudes and behaviour, the interventions based on these models assume that the provision of information will affect the attitude and hence lead to behaviour change. Based on the theory of social representations the thesis develops a broader and more heuristic perspective for the study of health issues. This theory proposes that rationality is a collective issue and views the relationship between concepts and actions as symbolic phenomena to be understood in their context of occurrence. Based on this theory the thesis explores the contents and structure of the representation of healthy eating in four groups in Colombian society (two rural and two urban, professionals and non-professionals). A multi-method approach combines an observational study, a multi-level content analysis of media and group discussions, and the structural analysis of the representation using free association procedures. The data are analysed using qualitative techniques, analysis of corpus, factor correspondence analysis and calling into question procedures, and interpreted within the structural perspective of social representations theory. The results indicate that eating is being transformed into a dilemmatic issue, of everyday life, reflecting important social and economic changes at the end of the century. The ambiguous and paradoxical representation of health and healthy eating is evident in the more affluent environments and both a transformation in the perceived relations between culture and nature, and concerns about the longevity and disease prevention. Health marketing and policy implementation, it is argued, must take account of these influences to develop effective campaigns. The thesis concludes with an examination of the potential contributions of the theory of social representations to understand the social psychological aspects of nutritional behaviour.
Together Alone: What Students Need from an E-moderator

It has often been suggested that education via the Internet, or e-learning, leads to a sense of separation in individual learners; this need not be the case. Teaching is a relationship: a relationship that is built on a connection between teaching and learner, between learner and learner, and between the learners and the content. What then is the role of the instructor in moderating online learning? This paper will explore how that connection might be better made in an online environment and will explore the interpersonal or emotive distinctiveness needed in an e-moderator from the perspective of a group of graduate students engaged in an online master of education degree offered in Canada.
Head pose estimation on depth data based on Particle Swarm Optimization

We propose a method for human head pose estimation based on images acquired by a depth camera. During an initialization phase, a reference depth image of a human subject is obtained. At run time, the method searches the 6-dimensional pose space to find a pose from which the head appears identical to the reference view. This search is formulated as an optimization problem whose objective function quantifies the discrepancy of the depth measurements between the hypothesized views to the reference view. The method is demonstrated in several data sets including ones with known ground truth and comparatively evaluated with respect to state of the art methods. The obtained experimental results show that the proposed method outperforms existing methods in accuracy and tolerance to occlusions. Additionally, compared to the state of the art, it handles head pose estimation in a wider range of head poses.