Miracle-dz/UniFAR-FTUs huggingface dataset:
Genome-Wide Binding and Transcriptome Analysis of Human Farnesoid X Receptor in Primary Human Hepatocytes

Background & Aims Farnesoid X receptor (FXR, NR1H4) is a ligand-activated transcription factor, belonging to the nuclear receptor superfamily. FXR is highly expressed in the liver and is essential in regulating bile acid homeostasis. FXR deficiency is implicated in numerous liver diseases and mice with modulation of FXR have been used as animal models to study liver physiology and pathology. We have reported genome-wide binding of FXR in mice by chromatin immunoprecipitation - deep sequencing (ChIP-seq), with results indicating that FXR may be involved in regulating diverse pathways in liver. However, limited information exists for the functions of human FXR and the suitability of using murine models to study human FXR functions. Methods In the current study, we performed ChIP-seq in primary human hepatocytes (PHHs) treated with a synthetic FXR agonist, GW4064 or DMSO control. In parallel, RNA deep sequencing (RNA-seq) and RNA microarray were performed for GW4064 or control treated PHHs and wild type mouse livers, respectively. Results ChIP-seq showed similar profiles of genome-wide FXR binding in humans and mice in terms of motif analysis and pathway prediction. However, RNA-seq and microarray showed more different transcriptome profiles between PHHs and mouse livers upon GW4064 treatment. Conclusions In summary, we have established genome-wide human FXR binding and transcriptome profiles. These results will aid in determining the human FXR functions, as well as judging to what level the mouse models could be used to study human FXR functions.
Hybrid Directed Test Suite Augmentation: An Interleaving Framework

Test suite augmentation techniques generate test cases to cover code missed by existing regression test suites. Various augmentation techniques have been proposed, utilizing several test case generation algorithms. Research has shown that different algorithms have different strengths, and that combining them into a single hybrid approach may be cost-effective. In this paper we present a framework for hybrid test suite augmentation that allows test case generation algorithms to be interleaved dynamically and that can easily incorporate new algorithms, interleaving strategies, and choices of other parameters that influence algorithm performance. We empirically study an implementation of this framework in which we use two test case generation algorithms and several algorithm interleavings. Our results show that specific instantiations of our framework can produce augmentation techniques that are more cost-effective than others, and illustrate tradeoffs between instantiations.
Multiple imputation based on restricted mean model for censored data

Most multiple imputation (MI) methods for censored survival data either ignore patient characteristics when imputing a likely event time, or place quite restrictive modeling assumptions on the survival distributions used for imputation. In this research, we propose a robust MI approach that directly imputes restricted lifetimes over the study period based on a model of the mean restricted life as a linear function of covariates. This method has the advantages of retaining patient characteristics when making imputation choices through the restricted mean parameters and does not make assumptions on the shapes of hazards or survival functions. Simulation results show that our method outperforms its closest competitor for modeling restricted mean lifetimes in terms of bias and efficiency in both independent censoring and dependent censoring scenarios. Survival estimates of restricted lifetime model parameters and marginal survival estimates regain much of the precision lost due to censoring. The proposed method is also much less subject to dependent censoring bias captured by covariates in the restricted mean model. This particular feature is observed in a full statistical analysis conducted in the context of the International Breast Cancer Study Group Ludwig Trial V using the proposed methodology. Copyright © 2011 John Wiley & Sons, Ltd.
Contour Flow: Middle-Level Motion Estimation by Combining Motion Segmentation and Contour Alignment

Our goal is to estimate contour flow (the contour pairs with consistent point correspondence) from inconsistent contours extracted independently in two video frames. We formulate the contour flow estimation locally as a motion segmentation problem where motion patterns grouped from optical flow field are exploited for local correspondence measurement. To solve local ambiguities, contour flow estimation is further formulated globally as a contour alignment problem. We propose a novel two-staged strategy to obtain global consistent point correspondence under various contour transitions such as splitting, merging and branching. The goal of the first stage is to obtain possible accurate contour-to-contour alignments, and the second stage aims to make a consistent fusion of many partial alignments. Such a strategy can properly balance the accuracy and the consistency, which enables a middle-level motion representation to be constructed by just concatenating frame-by-frame contour flow estimation. Experiments prove the effectiveness of our method.
Two‐Dimensional Assessment of Right Ventricular Function: An Echocardiographic–MRI Correlative Study

Background: While echocardiography is used most frequently to assess right ventricular (RV) function in clinical practice, echocardiography is limited in its ability to provide an accurate measure of RV ejection fraction (RVEF). Hence, quantitative estimation of RV function has proven difficult in clinical practice. Objective: We sought to determine which commonly used echocardiographic measures of RV function were most accurate in comparison with an MRI‐derived estimate of RVEF. Methods: We analyzed RV function in 36 patients who had cardiac MRI studies and echocardiograms within a 24 hour period. 2D parameters of RV function—right ventricular fractional area change (RVFAC), tricuspid annular motion (TAM), and transverse fractional shortening (TFS) were obtained from the four‐chamber view. RV volumes and EFs were derived from volumetric reconstruction based on endocardial tracing of the RV chamber from the short axis images. Echocardiographic assessment of RV function was correlated with MRI findings. Results: RVFAC measured by echocardiography correlated best with MRI‐derived RVEF (r = 0.80, P < 0.001). Neither TAM (r = 0.17; P = 0.30) nor TFC (r = 0.12; p< 0.38) were significantly correlated with RVEF. Conclusions: RVFAC is the best of commonly utilized echocardiographic 2D measure of RV function and correlated best with MRI‐derived RV ejection fraction. Condensed Abstract: While echocardiography is used most frequently to assess RV function in clinical practice, echocardiography is limited in its ability to provide an accurate measure of RV ejection fraction (RVEF). Using cardiac MRI, RV fractional area change (RVFAC), determined either by MRI or echocardiography, was found to correlate best with MRI‐derived RVEF.
Forecasting with Medium and Large Bayesian VARs

This paper is motivated by the recent interest in the use of Bayesian VARs for forecasting, even in cases where the number of dependent variables is large. In such cases, factor methods have been traditionally used but recent work using a particular prior suggests that Bayesian VAR methods can forecast better. In this paper, we consider a range of alternative priors which have been used with small VARs, discuss the issues which arise when they are used with medium and large VARs and examine their forecast performance using a US macroeconomic data set containing 168 variables. We ? nd that Bayesian VARs do tend to forecast better than factor methods and provide an extensive comparison of the strengths and weaknesses of various approaches. Our empirical results show the importance of using forecast metrics which use the entire predictive density, instead of using only point forecasts.
Evidence that vitamin D3 promotes mast cell–dependent reduction of chronic UVB-induced skin pathology in mice

Mast cell production of interleukin-10 (IL-10) can limit the skin pathology induced by chronic low-dose ultraviolet (UV)-B irradiation. Although the mechanism that promotes mast cell IL-10 production in this setting is unknown, exposure of the skin to UVB irradiation induces increased production of the immune modifying agent 1α,25-dihydroxyvitamin D3 (1α,25[OH]2D3). We now show that 1α,25(OH)2D3 can up-regulate IL-10 mRNA expression and induce IL-10 secretion in mouse mast cells in vitro. To investigate the roles of 1α,25(OH)2D3 and mast cell vitamin D receptor (VDR) expression in chronically UVB-irradiated skin in vivo, we engrafted the skin of genetically mast cell–deficient WBB6F1-KitW/W-v mice with bone marrow–derived cultured mast cells derived from C57BL/6 wild-type or VDR−/− mice. Optimal mast cell–dependent suppression of the inflammation, local production of proinflammatory cytokines, epidermal hyperplasia, and epidermal ulceration associated with chronic UVB irradiation of the skin in KitW/W-v mice required expression of VDR by the adoptively transferred mast cells. Our findings suggest that 1α,25(OH)2D3/VDR-dependent induction of IL-10 production by cutaneous mast cells can contribute to the mast cell’s ability to suppress inflammation and skin pathology at sites of chronic UVB irradiation.
Patch antennas for BAN/PAN applications at 2.45 GHz: A preliminary approach

A preliminary approach for the analysis and design of patch antennas located over biological tissues is presented. The study is performed in the 2.4 GHz ISM band envisaging body area and personal area network applications. A moment method numerical analysis is used to check the effects of the biological tissues on the patch antenna performance. Both single patches and two element arrays are analyzed. The conclusions obtained can be used as guidelines to conduct a more accurate approach where the complete model of the human body (shape and size) is taken into account.
Extending a Broad-Coverage Parser for a General NLP Toolkit

With the rapid growth of real world applications for NLP systems, there is a genuine demand for a general toolkit from which programmers with no linguistic knowledge can build specific NLP systems. Such a toolkit should have a parser that is general enough to be used across domains, and yet accurate enough for each specific application. In this paper, we describe a parser that extends a broad-coverage parser, Minipar (Lin, 2001), with an adaptable shallow parser so as to achieve both generality and accuracy in handling domain specific NL problems. We test this parser on our corpus and the results show that the accuracy is significantly higher than a system that uses Minipar alone.
DELAY OF GERMINATION1 (DOG1) regulates both seed dormancy and flowering time through microRNA pathways

Significance Annual plants adapt to their environments by matching their life cycles, particularly seed germination and flowering, to the appropriate seasons. Although genetic evidence has suggested connections among genes regulating seed dormancy and flowering, specific mechanisms for such coordination are unknown. We report that a gene [DELAY OF GERMINATION1 (DOG1)] involved in determining the depth of seed dormancy, and therefore the seasonal timing of germination, also influences the timing of flowering in Arabidopsis and lettuce. We further show that this gene acts through influencing the production of microRNAs that govern the progression of developmental phase transitions through the plant life cycle, providing a molecular genetic mechanism for the coordinate adaptation of seed dormancy and flowering phenotypes to environmental conditions. Seed germination and flowering, two critical developmental transitions in plant life cycles, are coordinately regulated by genetic and environmental factors to match plant establishment and reproduction to seasonal cues. The DELAY OF GERMINATION1 (DOG1) gene is involved in regulating seed dormancy in response to temperature and has also been associated genetically with pleiotropic flowering phenotypes across diverse Arabidopsis thaliana accessions and locations. Here we show that DOG1 can regulate seed dormancy and flowering times in lettuce (Lactuca sativa, Ls) and Arabidopsis through an influence on levels of microRNAs (miRNAs) miR156 and miR172. In lettuce, suppression of LsDOG1 expression enabled seed germination at high temperature and promoted early flowering in association with reduced miR156 and increased miR172 levels. In Arabidopsis, higher miR156 levels resulting from overexpression of the MIR156 gene enhanced seed dormancy and delayed flowering. These phenotypic effects, as well as conversion of MIR156 transcripts to miR156, were compromised in DOG1 loss-of-function mutant plants, especially in seeds. Overexpression of MIR172 reduced seed dormancy and promoted early flowering in Arabidopsis, and the effect on flowering required functional DOG1. Transcript levels of several genes associated with miRNA processing were consistently lower in dry seeds of Arabidopsis and lettuce when DOG1 was mutated or its expression was reduced; in contrast, transcript levels of these genes were elevated in a DOG1 gain-of-function mutant. Our results reveal a previously unknown linkage between two critical developmental phase transitions in the plant life cycle through a DOG1–miR156–miR172 interaction.
Activation of the estrogen receptor contributes to the progression of pulmonary lymphangioleiomyomatosis via matrix metalloproteinase-induced cell invasiveness.

CONTEXT The role of estrogens in the pathogenesis of lymphangioleiomyomatosis (LAM), an aggressive and destructive, eventually fatal lung disease of women, is poorly understood. OBJECTIVE The study was conducted to test the hypothesis that the lung disease in LAM is estrogen mediated and to determine whether estrogens contribute to the invasiveness of LAM. DESIGN In vitro cell culture of spindle-shaped LAM cells (LAMD-SM) were isolated and propagated from affected lungs. Estrogen receptor (ER)-alpha and ERbeta analyses were conducted by RT-PCR. ERalpha and ERbeta, tissue inhibitor of metalloproteinase-2, and matrix metalloproteinases (MMP)-2 had Western blot analysis for protein assessment. Activity assays were performed for MT1-MMP, MMP-2, and tissue inhibitor of metalloproteinase-2. Assessment of MMP-2 promoter function was done via transfection assays. Cell invasion chambers were used to determine and quantitate cell invasiveness. SETTING The study was conducted at an academic medical center. PATIENTS Tissue and cells were obtained from patients as outlined in approved institution review board protocol (97/007). INTERVENTION LAMD-SM cells were treated with a specific MMP-2 antibody or a nonspecific inhibitor, doxycycline. MAIN OUTCOME MEASURES Activity of MMP-2 and invasiveness of LAMD-SM cells were measured. RESULTS LAMD-SM cells express functional ERs (ERalpha and ERbeta), which undergo rapid intracellular turnover in their unbound state. 17beta-estradiol (E(2)) enhances the transcriptional ER activity. E(2)-induced ER activation increases synthesis and activity of MMP-2 through posttranscriptional mechanisms in LAMD-SM. The E(2)/ER-mediated increase of MMP-2 promotes LAMD-SM invasiveness, in assays in vitro, which can be inhibited by specific antibodies against MMP-2 or doxycycline, an inhibitor of MMPs. CONCLUSION The invasion and destruction of lung parenchyma in LAM is, at least partially, an estrogen-MMP-driven process, which has major implications for therapeutic interventions.
Capacity of fully correlated MIMO system using character expansion of groups

It is well known that the use of antenna arrays at both sides of communication link can result in high channel capacities provided that the propagation medium is rich scattering. In most previous works presented on MIMO wireless structures, Rayleigh fading conditions were considered. In this work, the capacity of MIMO systems under fully correlated (i.e., correlations between rows and columns of channel matrix) fading is considered. We use replica method and character expansions to calculate the capacity of correlated MIMO channel in closed form. In our calculations, it is assumed that the receiver has perfect channel state information (CSI) but no such information is available at the transmitter.
Methotrexate for ankylosing spondylitis.

BACKGROUND Ankylosing spondylitis (AS) is a chronic inflammatory disease of unknown cause, characterized by sacroiliitis and spondylitis. To date, treatment of AS has been limited to the alleviation of symptoms, mainly using non-steroidal anti-inflammatory drugs (NSAIDs). For patients refractory or intolerant to NSAIDs, the disease modifying antirheumatic drugs (DMARDs) have been used as a second line approach. Methotrexate (MTX) is currently one of the most widely used DMARDs and its efficacy in rheumatoid arthritis (RA) has been confirmed (Suarez-Almazor 2003). There is uncertainty whether MTX works in the treatment of AS. OBJECTIVES To evaluate the efficacy and toxicity of methotrexate in the treatment of ankylosing spondylitis. SEARCH STRATEGY Relevant randomised and quasi-randomised trials in any language were sought using the following sources: CENTRAL (Cochrane Central Register of Controlled Trials, Issue 2, 2003), MEDLINE (1966 to June Week 4 2003), EMBASE (1980 to 2003 Week 26), CINAHL (1982 to June Week 3 2003) and the reference section of retrieved articles. SELECTION CRITERIA We evaluated randomised and quasi-randomised trials examining the efficacy of methotrexate on AS. DATA COLLECTION AND ANALYSIS Unblinded trial reports were reviewed independently by two reviewers according to the selection criteria. Disagreements on the inclusion of the studies were resolved, where necessary, by recourse to a third reviewer. The methodological quality of included trials were independently assessed by the same reviewers on randomization, concealment, blindness (participants, care providers and outcome investigators), description of withdrawals and drop-outs and intention-to-treat analysis. The same reviewers independently entered the data extracted from the included trials, using RevMan's double entry facility. In the absence of significant heterogeneity, results were combined using weighted mean difference or standardised mean difference for continuous data, and relative risk for dichotomous data. MAIN RESULTS Two trials met the inclusion criteria. Altan 2001compared naproxen plus MTX (7.5 mg/week orally) with naproxen alone and Roychowdhury 2002 compared MTX (10 mg/week orally) with placebo. The duration of the trials were 12 months and 24 weeks, respectively. They assessed different outcomes except for C-reactive protein (CRP). The included trials treated a total of 81 patients and assessed more than 10 outcomes relevant to the review, covering function, pain, peripheral arthritis/enthesitis, morning stiffness, patient and physician global assessment, CRP and erythrocyte sedimentation rate (ESR). No significant difference between intervention groups was found favouring MTX over no MTX. No serious side effect was reported in either trial. REVIEWERS' CONCLUSIONS There was no statistically significant benefit of MTX in the examined outcomes for AS patients. High quality, larger sample and longer period of randomized controlled trials (possibly with higher dosage of MTX) are needed to verify the uncertainty about the efficacy and toxicity of MTX for the treatment of AS.
Does Institutional Selectivity Aid in the Prediction of Medical School Performance?

Various factors are considered in the decision to offer an admission interview to a medical school applicant, including Medical College Admission Test (MCAT) scores, undergraduate grade-point average (GPA), and the selectivity of the degree-granting undergraduate institution. Admission officers view MCAT scores, undergraduate GPA, and institutional selectivity as having high or moderate importance. Research has indicated that these factors, most notably the MCAT scores and the undergraduate GPA, are reliable in helping predict medical school performance. The strongest association has been shown between MCAT scores and performance on the United States Medical Licensing Examination, Step 1. Institutional selectivity data are used to help control for differences in grading stringency across undergraduate institutions. Previous reports have examined the role of institutional selectivity, or a specific undergraduate institution, as a predictor of performance in the first two years of medical school. With the exception of the study of Zelesnik et al., which examined ten specific undergraduate institutions, these reports have used the Higher Education Research Institute (HERI) Index, also called the ‘‘Astin Index,’’ as a measure of institutional selectivity. Other measures of institutional selectivity or categorization that schools of medicine may employ include the Barron’s Profiles of American Colleges Admissions Selector Rating and the Carnegie Classification from the Carnegie Foundation for the Advancement of Teaching. (These measures are explained in the next section.) Institutional validity studies of admission decision-making data help to determine which characteristics should be accorded highest importance in applicant selection. Given the reliance upon institutional selectivity as an important admission characteristic and the different types of selectivity classifications available for medical schools to use, the purpose of this study was to examine how well three measures of institutional selectivity could predict medical students’ performances, specifically their performances on the USMLE Step 1 and Step 2 and their final medical school GPAs.
Multi-level Modularity vs. Hierarchy: Global Production Networks in Singapore's Electronics Industry

Abstract An examination of Singapore's electronics industry is used to construct a generalized model of organizational forms in global production networks within the electronics industry. The model includes an extension of the modular production network derived from studies of the US electronic equipment industry where brand name firms concentrate on product innovation, design and marketing while contracting out manufacturing to turnkey suppliers. In the case of Singapore, however, the original model is too simple to incorporate the multiple levels of contract manufacturing relationships within the electronics industry. The modular network in the semiconductor industry is compared with the hierarchical production network identified in the hard disk drive industry, the other dominant segment of Singapore s electronics industry. The two industries are differently inserted in their global production networks in response to different production technology and corresponding differences in codifiability of the information needed for transactions between buyer and seller within the network. Despite their different organizational forms, the presence in Singapore of both segments is dependent on the maintenance and further development of regional production networks that are able to match requirements determined by global dynamics. State industrial policies in Singapore are already directed at the challenges and seem to be sufficiently comprehensive to withstand the challenges from the rapidly upcoming electronics industry in China and rivalling Southeast Asian neighbour states.