Miracle-dz/UniFAR-FTUs huggingface dataset:
Cytoskeletal Filamin A Differentially Modulates RNA Polymerase III Gene Transcription in Transformed Cell Lines*

Cytoskeletal filamin A (FLNA) is an important protein involved in multiple cellular processes. Previous studies have shown that FLNA can promote or inhibit cancer growth and development; however, the mechanisms underlying these events are not fully understood. Here we show that, in both 293T and SaOS2 cells, knockdown of FLNA significantly enhanced transcription of RNA polymerase (pol) III-transcribed genes except for a subset of tRNA genes. In contrast, re-expression of FLNA in an FLNA-deficient melanoma cell line (A7) repressed transcription of all pol III-transcribed genes, suggesting that FLNA inhibits pol III transcription in a cell type-specific manner. Chromatin immunoprecipitation assays revealed that the repression of pol III gene transcription by FLNA correlates with the decreased occupancy of the RNA pol III transcription machinery at promoters. Immunofluorescence microscopy and coimmunoprecipitation assays revealed that FLNA can associate with the RNA pol III transcription machinery through its actin-binding domain within nuclei. Mechanistic analysis revealed that FLNA suppresses pol III gene transcription by confining the recruitment of the RNA pol III transcription machinery at the promoters of the genes that are sensitive to the alteration of FLNA expression. These findings not only extend the understanding of FLNA function in cells but also provide novel insights into the mechanism by which FLNA represses cell proliferation.
Analysis of Bead Sizes for MR Capsules Labeled for Sprinkle

The bead sizes used in approved modified release capsules labeled for sprinkling on food was investigated to generate bead size guidelines for generic products labeled for sprinkling. The conclusions from a survey of FDA databases were corroborated with experimental data obtained by measuring the bead sizes of several reference-listed drugs on the market labeled for administration by sprinkling on food. The experimental data show that majority of the marketed products were found to have bead sizes of less than 1,500 μm (1.5 mm). Based on this information, a bead size of less than 1,500 μm should generally be considered acceptable for use in generic products labeled for sprinkling.
A comparison of mixed‐effects quantile stratification propensity adjustment strategies for longitudinal treatment effectiveness analyses of continuous outcomes

The propensity adjustment is used to reduce bias in treatment effectiveness estimates from observational data. We show here that a mixed‐effects implementation of the propensity adjustment can reduce bias in longitudinal studies of non‐equivalent comparison groups. The strategy examined here involves two stages. Initially, a mixed‐effects ordinal logistic regression model of propensity for treatment intensity includes variables that differentiate subjects who receive various doses of time‐varying treatments. Second, a mixed‐effects linear regression model compares the effectiveness of those ordinal doses on a continuous outcome over time. Here, a simulation study compares bias reduction that is achieved by implementing this propensity adjustment through various forms of stratification. The simulations demonstrate that bias decreased monotonically as the number of quantiles used for stratification increased from two to five. This was particularly pronounced with stronger effects of the confounding variables. The quartile and quintile strategies typically removed in excess of 80–90 per cent of the bias detected in unadjusted models; whereas a median‐split approach removed from 20 to 45 per cent of bias. The approach is illustrated in an evaluation of the effectiveness of somatic treatments for major depression in a longitudinal, observational study of affective disorders. Copyright © 2006 John Wiley & Sons, Ltd.
Why Am I Depressed?: An Investigation of Whether Patients’ Beliefs About Depression Concur With Their Diagnostic Subtype

We investigated whether patients’ beliefs about the causes of their depression concurred with their diagnostic subtype. Depressed patients (N = 196) attending a tertiary referral clinic completed a questionnaire regarding putative biological and nonbiological causes of their depression. Subtyping diagnoses of melancholic or nonmelancholic depression were made. Patients with nonmelancholic depression were more likely to attribute nonbiological factors as the cause of their depression than those with melancholic depression, whereas patients with melancholic depression were no more likely to attribute biological factors as the cause of their depression. Patients can distinguish differing causes of depression. The implications of the findings for the current classificatory systems of depression are discussed.
Information Transfer Effects of Bond Rating Downgrades

This paper investigates information transfer effects of bond rating downgrades measured by equity abnormal returns for industry portfolios. Industry rivals can be subject to two opposing effects, the contagion effect and the competition effect. We find that the net effect is strongly dependent on the original bond rating of the downgraded firm. For investment-grade (speculative-grade) firms, industry abnormal equity returns are negative (positive), which implies a predominant "contagion (competition)" effect. The analysis reveals a rich pattern of positive and negative correlations across negative credit events, which can be used to improve our understanding of portfolio credit risk models. Copyright (c) 2010, The Eastern Finance Association.
Rapid identification of legionellae by a colony blot assay based on a genus-specific monoclonal antibody

We recently developed a monoclonal antibody immunoglobulin G2a (2125) recognizing a genus-specific epitope on the 60-kDa heat shock protein of all Legionella species. In the current study, this antibody was used in a colony blot enzyme-linked immunosorbent assay for the rapid identification of Legionella cultures on agar plates. The whole protocol was completed in less than 2 h. All 59 Legionella species and serogroups that were tested gave a positive signal. No unspecific reactions with nonlegionellae were observed. This test is a rapid procedure for the identification of legionellae growing on agar medium to the genus level.
Quantitative proteomics of nasal mucus in chronic sinusitis with nasal polyposis.

BACKGROUND Proteomics has been used as a tool for identification of the protein content of nasal mucus in diseased and healthy subjects. Thirty-five proteins in both chronic rhinosinusitis (CRS) and control groups were identified in a previous study by our group using conventional mass spectrometry analysis. Ten of these proteins were related to innate and acquired immunity and showed differences in expression between the two groups. OBJECTIVE To investigate the quantitative differential expression of specific nasal mucus proteins previously identified by our group using multiple reaction monitoring (MRM) mass spectrometry in patients with CRS with nasal polyposis compared with normal subjects. METHODS In a prospective case control study, nasal mucus from patients and control subjects was collected, desalted, resolubilized, and digested using proteolytic enzymes. Previously identified nasal mucus proteins with differential expression in CRS patients were targeted and quantitatively measured using MRM mass spectrometry. RESULTS Analysis of 12 samples (6 patients and 6 controls) identified 7 of the 10 targeted proteins, many of which were related to innate and acquired immunity. Quantitative analysis showed differential expression in CRS patients compared with control subjects. A detailed analysis and characterization of the protein isolates is outlined. CONCLUSION This is the first proteomics study of nasal mucus in CRS with polyposis using the MRM technique. The findings suggest that innate and acquired immunity may play a role in the pathophysiology of CRS. Future steps in evaluating the protein characteristics of the mucus of CRS patients are aimed at developing biomarkers and potentially targeted therapies.
Design of an efficient authentication method for modern image and video

Data origin and data integrity authentication are, very important factors in image and video security. As modern image and video coding techniques become standards, authentication methods should be devised that cope with the modern standards' intrinsic capabilities: scalability and a trend towards more content-oriented compression. So far no efficient authentication system addresses these properties. The design of an efficient scalable authentication technique under reasonable system considerations is reviewed. The technique addresses modern coding standards such as JPEG2000 and MPEG4. In addition, the authentication method is enhanced by introducing novel cryptographic primitives that further enhance the method's applicability to real-world scenarios.
Bone Markers Predict Cardiovascular Events in Chronic Kidney Disease

Recent studies have indicated a link between bone metabolism and cardiovascular events in patients with chronic kidney disease (CKD). CKD is a major health problem worldwide. This study evaluates the role of noninvasive markers of bone metabolism in predicting cardiovascular morbidity (coronary artery disease, peripheral vascular disease, stroke) and mortality in patients with mild to severe forms of CKD. In a prospective cohort study, 627 patients with CKD were screened. To focus on bone metabolism, traditional risk factors for cardiovascular events were excluded, and 135 patients with CKD stages 1–5 were followed for 4 yr. Glomerular filtration rate was calculated by the Modification of Diet in Renal Disease formula. PTH (measured by four different assays), vitamin D 25 and 1,25, bone‐specific alkaline phosphatase (BSALP), TRACP‐5b, osteocalcin, serum collagen cross‐link molecules, RANKL, and osteoprotegerin were determined. Predictors of cardiovascular events were evaluated by multivariable logistic regression, Kaplan‐Meier survival, and Cox regression analysis. There were a total of 45 cardiovascular events (33%). Event rates were 5.6%, 29.1%, 45.2%, and 45.0% in CKD stages 1–2, 3, 4, and 5, respectively. In logistic regression, cardiovascular events were predicted only by (1) CKD stage (independent of age or sex; p < 0.001); (2) BSALP (p = 0.03); and (3) TRACP‐5b (p = 0.04). Markers of bone formation (BSALP) and resorption (TRACP‐5b) can serve as predictors of cardiovascular morbidity and mortality in CKD.
Modelling time of day substitution using the second moments of demand

Time of day (TOD) rates are a commonly used method for peak load pricing of many services. Such services as; electricity, communications, transportation, shared computer facilities, and computer networks (i.e. the Internet), either use, or will use, some form of TOD pricing. However, TOD rates do not ensure a movement towards economic efficiency unless the patterns of TOD substitution are known. The model presented here provedes a method for estimating TOD substitution without the need for rate experiments that have proven to be both costly and limited by sample selection bias problems. This model employs the estimated second moment of demand to estimate a matrix of relative own- and cross-price elasticities and it can estimate elasticities even when there is no apparent TOD price variation. The low level of computations required for the estimates allows the application of a bootstrap procedure to estimate the covariance matrix of the elasticities. Two applications of this model are presented: a case of aggregate demand for computer services and a case of an individual household's electricity demand.
A medical ontology for intelligent web-based skin lesions image retrieval

Researchers have applied increasing efforts towards providing formal computational frameworks to consolidate the plethora of concepts and relations used in the medical domain. In the domain of skin related diseases, the variability of semantic features contained within digital skin images is a major barrier to the medical understanding of the symptoms and development of early skin cancers. The desideratum of making these standards machine-readable has led to their formalization in ontologies. In this work, in an attempt to enhance an existing Core Ontology for skin lesion images, hand-coded from image features, high quality images were analyzed by an autonomous ontology creation engine. We show that by exploiting agglomerative clustering methods with distance criteria upon the existing ontological structure, the original domain model could be enhanced with new instances, attributes and even relations, thus allowing for better classification and retrieval of skin lesion categories from the web.
Examining the robustness of cointegration analysis under weighted symmetric estimation

The research of Leybourne and Newbold (2003) is extended to examine the finite-sample size of the weighted symmetric cointegration test when applied to independent unit root processes subject to structural change. The results obtained show the weighted symmetric cointegration test to be more robust to structural change than previously examined cointegration tests. Combined with its previously noted higher power, the findings of the present analysis suggest the recently proposed weighted symmetric cointegration test to be of use to the practitioner.
The role of primary care clinician attitudes, beliefs, and training in the diagnosis and treatment of depression. A report from the Ambulatory Sentinel Practice Network Inc.

OBJECTIVE To examine the relation between primary care clinicians' attitudes, beliefs, and training and their perceptions of the importance and frequency of depression. DESIGN A 56-item questionnaire was mailed to 226 clinicians in the Ambulatory Sentinel Practice Network Inc (ASPN), a primary care research network. SETTING The ASPN, consisting of 69 primary care practices in the United States and Canada, cares for approximately 350,000 patients. MAIN OUTCOME MEASURE The degree to which clinician training in depression and clinician attitudes and beliefs about treating depression predict their perceptions of the importance of depression in their primary care practices. RESULTS Results of path analysis indicate that clinician training in depression, beliefs about the burden and discomfort associated with diagnosing and treating depression, perceptions of their patients' discomfort, and self-efficacy in diagnosing and treating depression are all significantly related to clinician perceptions of whether depression was an important and frequent primary care problem. Further analysis indicates that actual prevalence of depression accounted for little variability in clinicians' beliefs and attitudes about depression. CONCLUSIONS What clinicians think their patients feel about issues on depression and how they view their own abilities may profoundly influence the degree to which they recognize depression in primary care. Understanding these factors may help explain and subsequently decrease clinician variability in the recognition of depression in primary care.
Determinants of the Innovation Process: An Empirical Test for the Portuguese Manufacturing Industry

The aim of this paper is to analyze the determinants of the main phases of the innovation process in Portuguese manufacturing firms. The analysis will adopt as its main frame of reference an interactive model of the innovation process, on which empirical tests will be carried out, making use of tobit and probit models and simultaneous equation systems. It is broadly concluded that the relationships shown between the main variables that are typical of the innovation process in the context of Portuguese manufacturing firms are tenuous and unsystematic.
Short-term Memory Solar Energy Forecasting at University of Illinois

Climate change and energy crisis have motivated the use and development of solar power generation. Since solar power generation is highly intermittent and dependent on local weather characteristics, we apply a variety of linear and non-linear ensemble machine learning models to predict short-term solar energy output at the University of Illinois campus. Implemented models include weighted linear regression with and without dimension reduction, boosting regression trees, and artificial neural networks with and without vanishing temporal gradient. Additionally, we apply a variety of variable selection techniques, which suggest that air temperature, relative humidity, and dew point are the most informative weather parameters for predicting the solar energy generation at the Illinois power plant. Findings from our paper indicate that deep learning with vanishing time-series gradient (long short-term memory layer; LSTM) is the most promising technique for solar predictions based on temporal weather characteristics. The LSTM layer reduces both median training and test error by an order of magnitude compared to the remaining algorithms. This conclusion confirms the presence of short-term temporal dependence in both weather and solar power magnitudes.
Potent Activity of a Nucleoside Reverse Transcriptase Inhibitor, 4′-Ethynyl-2-Fluoro-2′-Deoxyadenosine, against Human Immunodeficiency Virus Type 1 Infection in a Model Using Human Peripheral Blood Mononuclear Cell-Transplanted NOD/SCID Janus Kinase 3 Knockout Mice

ABSTRACT 4′-Ethynyl-2-fluoro-2′-deoxyadenosine (EFdA), a recently discovered nucleoside reverse transcriptase inhibitor, exhibits activity against a wide spectrum of wild-type and multidrug-resistant clinical human immunodeficiency virus type 1 (HIV-1) isolates (50% effective concentration, 0.0001 to 0.001 μM). In the present study, we used human peripheral blood mononuclear cell-transplanted, HIV-1-infected NOD/SCID/Janus kinase 3 knockout mice for in vivo evaluation of the anti-HIV activity of EFdA. Administration of EFdA decreased the replication and cytopathic effects of HIV-1 without identifiable adverse effects. In phosphate-buffered saline (PBS)-treated mice, the CD4+/CD8+ cell ratio in the spleen was low (median, 0.04; range, 0.02 to 0.49), while that in mice receiving EFdA was increased (median, 0.65; range, 0.57 to 1.43). EFdA treatment significantly suppressed the amount of HIV-1 RNA (median of 9.0 × 102 copies/ml [range, 8.1 × 102 to 1.1 × 103 copies/ml] versus median of 9.9 × 104 copies/ml [range, 8.1 × 102 to 1.1 × 103 copies/ml]; P < 0.001), the p24 level in plasma (2.5 × 103 pg/ml [range, 8.2 × 102 to 5.6 × 103 pg/ml] versus 2.8 × 102 pg/ml [range, 8.2 × 101 to 6.3 × 102 pg/ml]; P < 0.001), and the percentage of p24-expressing cells in the spleen (median of 1.90% [range, 0.33% to 3.68%] versus median of 0.11% [range, 0.00% to 1.00%]; P = 0.003) in comparison with PBS-treated mice. These data suggest that EFdA is a promising candidate for a new age of HIV-1 chemotherapy and should be developed further as a potential therapy for individuals with multidrug-resistant HIV-1 variants.
Customer profitability analysis an avant-garde approach to revenue optimisation in hotels

The widespread use of customer relationship management systems has provided hospitality/hotel organisations with detailed insights into the profitability of their individual customers and at the same time have highlighted unprofitable patrons. Critically appreciating contributions in the area of customer profitability analysis (CPA), this paper provides a retrospective (management accounting) and prospective (customer lifetime value) approach to estimate profitability of customer/guest segments in the hotel business environment. The research enumerates antecedents and outcomes of CPA and proposes an integrated framework to render robustness to the prevalent revenue management systems.
The Heat-Kernel Most-Likely-Path Approximation

In this article, we derive a new most-likely-path (MLP) approximation for implied volatility in terms of local volatility, based on time-integration of the lowest order term in the heat-kernel expansion. This new approximation formula turns out to be a natural extension of the well-known formula of Berestycki, Busca and Florent. Various other MLP approximations have been suggested in the literature involving different choices of most-likely-path; our work fixes a natural definition of the most-likely-path. We confirm the improved performance of our new approximation relative to existing approximations in an explicit computation using a realistic S&P500 local volatility function.
Complementarities in scientific production. Evidence from scientific research.

Complementarities in scientific production. Evidence from scientific research Christian MARTINEZ DIAZ Laboratory: BETA Universite de Strasbourg Currently in my 4th year of enrolment Expected final date: November 2012 Email address: camartinezdiaz@unistra.fr Abstrasct Evidence from studies of scientific productivity reveals a skewed distribution of individual contributions. Using data from research groups affiliated with the University of Strasbourg, I apply the methodology of supermodularity to investigate complementarities between principal investigators who are highly productive and other members of their research groups. The results reveal interdependences between principal investigators and their collaborators.
Life Cycle and Cohort Productivity in Economic Research: The Case of Germany

Abstract We examine the research productivity of German academic economists over their life cycles. It turns out that the career patterns of research productivity as measured by journal publications are characterized by marked cohort effects. Moreover, the life cycles of younger German economists are hump shaped and resemble the life cycles identified for US economists, whereas the life cycles of older German economists are much flatter. Finally, we find that not only productivity, but also research quality follows distinct life cycles. Our study employs econometric techniques that are likely to produce estimates that are more trustworthy than previous estimates.
Monetary Policy, Composite Leading Economic Indicators, and Predicting the 2001 Recession

On 26 November 2001, the National Bureau of Economic Research announced that the US economy had officially entered into a recession in March 2001. This decision was a surprise and did not end all the conflicting opinions expressed by economists. This matter was finally settled in July 2002 after a revision to the 2001 real gross domestic product showed negative growth rates for its first three quarters. A series of political and economic events in the years 2000-01 have increased the amount of uncertainty in the state of the economy, which in turn has resulted in the production of less reliable economic indicators and forecasts. This paper evaluates the performance of two very reliable methodologies for predicting a downturn in the US economy using composite leading economic indicators (CLI) for the years 2000-01. It explores the impact of the monetary policy on CLI and on the overall economy and shows how the gradualness and uncertainty of this impact on the overall economy have affected the forecasts of these methodologies. It suggests that the overexposure of the CLI to the monetary policy tools and a strong, but less effective, expansionary money policy have been the major factors in deteriorating the predictions of these methodologies. To improve these forecasts, it has explored the inclusion of the CLI diffusion index as a prior in the Bayesian methodology. Copyright © 2004 John Wiley & Sons, Ltd.