Miracle-dz/UniFAR-FTUs huggingface dataset:
A Variant of the α2 Subunit of Soluble Guanylyl Cyclase Contains an Insert Homologous to a Region within Adenylyl Cyclases and Functions as a Dominant Negative Protein (*)

A variant of the α2 subunit of soluble guanylyl cyclase (α2i) containing 31 additional amino acids was identified in a number of cell lines and tissues. The in-frame sequence of the insert was within the proposed catalytic domain of guanylyl cyclases and was homologous to a region within the putative catalytic domain of adenylyl cyclases. Messenger RNA for the new variant was detected in some but not all cell lines and tissues expressing the α2 subunit. The novel form, as well as the α2 subunit lacking the insert, were coexpressed with the β1 subunit in Sf9 and COS-7 cells; α2/β1 coexpression yielded a NO-sensitive recombinant protein, whereas the coexpressed α2i/β1 subunits exhibited no guanylyl or adenylyl cyclase activities. Because both subunits (α2i/β1) copurified, the novel variant retains its ability to heterodimerize. In coexpression experiments, the α2i subunit competed with the α2 subunit for dimerization with the β1 subunit, thereby reducing α2/β1-catalyzed guanylyl cyclase activity. These data show that the novel variant functions as a dominant negative protein and that post-transcriptional mRNA processing represents a potential mechanism for regulation of NO-sensitive guanylyl cyclase acitivity.
A Generalized Restricted Isometry Property

Compressive Sampling (CS) describes a method for reconstructing high-dimensional sparse signals from a small number of linear measurements. Fundamental to the success of CS is the existence of special measurement matrices which satisfy the so-called Restricted Isometry Property (RIP). In essence, a matrix satisfying RIP is such that the lengths of all sufficiently sparse vectors are approximately preserved under transformation by the matrix. In this paper we describe a natural consequence of this property ‐ if a matrix satisfies RIP, then acute angles between sparse vectors are also approximately preserved. We formulate this property as a Generalized Restricted Isometry Property (GRIP) and describe one application in robust signal detection.
Effects of nitric oxide synthase inhibitor on decrease in peripheral arterial stiffness with acute low-intensity aerobic exercise.

We previously reported that even low-intensity, short-duration acute aerobic exercise decreases arterial stiffness. We aimed to test the hypothesis that the exercise-induced decrease in arterial stiffness is caused by the increased production of NO in vascular endothelium with exercise. Nine healthy men (age: approximately 22-28 yr) performed a 5-min single-leg cycling exercise (30 W) in the supine position under an intravenous infusion of NG-monomethyl-L-arginine (L-NMMA; 3 mg/kg during the initial 5 min and subsequent continuous infusion of 50 mug.kg(-1). min(-1) in saline) or vehicle (saline) in random order on separate days. The pulse wave velocity (PWV) from the femoral to posterior tibial artery was measured on both legs before and after the infusion at rest and 2 min after exercise. Under the control condition, exercised leg PWV significantly decreased after exercise (P <0.05), whereas nonexercised leg PWV did not show a significant change throughout the experiment. Under L-NMMA administration, exercised leg PWV was increased significantly by the infusion (P <0.05) but decreased significantly after the exercise (P <0.05). Nonexercised leg PWV increased with L-NMMA administration and maintained a significantly higher level during the administration compared with baseline (before the infusion, all P <0.05). The NO synthase blockade x time interaction on exercised leg PWV was not significant (P=0.706). These results suggest that increased production of NO is not a major factor in the decrease of regional arterial stiffness with low-intensity, short-duration aerobic exercise.
Diffusion Tensor Imaging and Resting-State Functional MRI-Scanning in 5- and 6-Year-Old Children: Training Protocol and Motion Assessment

Advanced Magnetic Resonance Imaging (MRI) techniques such as Diffusion Tensor Imaging (DTI) and resting-state functional MRI (rfMRI) are widely used to study structural and functional neural connectivity. However, as these techniques are highly sensitive to motion artifacts and require a considerable amount of time for image acquisition, successful acquisition of these images can be challenging to complete with certain populations. This is especially true for young children. This paper describes a new approach termed the ‘submarine protocol’, designed to prepare 5- and 6-year-old children for advanced MRI scanning. The submarine protocol aims to ensure that successful scans can be acquired in a time- and resource-efficient manner, without the need for sedation. This manuscript outlines the protocol and details its outcomes, as measured through the number of children who completed the scanning procedure and analysis of the degree of motion present in the acquired images. Seventy-six children aged between 5.8 and 6.9 years were trained using the submarine protocol and subsequently underwent DTI and rfMRI scanning. After completing the submarine protocol, 75 of the 76 children (99%) completed their DTI-scan and 72 children (95%) completed the full 35-minute scan session. Results of diffusion data, acquired in 75 children, showed that the motion in 60 of the scans (80%) did not exceed the threshold for excessive motion. In the rfMRI scans, this was the case for 62 of the 71 scans (87%). When placed in the context of previous studies, the motion data of the 5- and 6-year-old children reported here were as good as, or better than those previously reported for groups of older children (i.e., 8-year-olds). Overall, this study shows that the submarine protocol can be used successfully to acquire DTI and rfMRI scans in 5 and 6-year-old children, without the need for sedation or lengthy training procedures.
The CENP-S complex is essential for the stable assembly of outer kinetochore structure

The constitutive centromere-associated network (CCAN) proteins are central to kinetochore assembly. To define the molecular architecture of this critical kinetochore network, we sought to determine the full complement of CCAN components and to define their relationships. This work identified a centromere protein S (CENP-S)–containing subcomplex that includes the new constitutive kinetochore protein CENP-X. Both CENP-S– and CENP-X–deficient chicken DT40 cells are viable but show abnormal mitotic behavior based on live cell analysis. Human HeLa cells depleted for CENP-X also showed mitotic errors. The kinetochore localization of CENP-S and -X is abolished in CENP-T– or CENP-K–deficient cells, but reciprocal experiments using CENP-S–deficient cells did not reveal defects in the localization of CCAN components. However, CENP-S– and CENP-X–deficient cells show a significant reduction in the size of the kinetochore outer plate. In addition, we found that intrakinetochore distance was increased in CENP-S– and CENP-X–deficient cells. These results suggest that the CENP-S complex is essential for the stable assembly of the outer kinetochore.
Smoothing clickthrough data for web search ranking

Incorporating features extracted from clickthrough data (called clickthrough features) has been demonstrated to significantly improve the performance of ranking models for Web search applications. Such benefits, however, are severely limited by the data sparseness problem, i.e., many queries and documents have no or very few clicks. The ranker thus cannot rely strongly on clickthrough features for document ranking. This paper presents two smoothing methods to expand clickthrough data: query clustering via Random Walk on click graphs and a discounting method inspired by the Good-Turing estimator. Both methods are evaluated on real-world data in three Web search domains. Experimental results show that the ranking models trained on smoothed clickthrough features consistently outperform those trained on unsmoothed features. This study demonstrates both the importance and the benefits of dealing with the sparseness problem in clickthrough data.
State of the art for measurement of urine albumin: comparison of routine measurement procedures to isotope dilution tandem mass spectrometry.

BACKGROUND Urine albumin is the primary biomarker for detection and monitoring of kidney damage. Because fixed decision criteria are used to identify patients with increased values, we investigated if commonly used routine measurement procedures gave comparable results. METHODS Results from 17 commercially available urine albumin measurement procedures were investigated vs an isotope dilution mass spectrometry (IDMS) procedure. Nonfrozen aliquots of freshly collected urine from 332 patients with chronic kidney disease, diabetes, cardiovascular disease, and hypertension were distributed to manufacturers to perform urine albumin measurements according to the respective instructions for use for each procedure. Frozen aliquots were used for measurements by the IDMS procedure. An error model was used to determine imprecision and bias components. RESULTS Median differences between the largest positive and negative biases vs IDMS were 45%, 37%, and 42% in the concentration intervals of 12-30 mg/L, 31-200 mg/L, and 201-1064 mg/L, respectively. Biases varied with concentration for most procedures and exceeded ± 10% over the concentration interval for 14 of 16 quantitative procedures. Mean biases ranged from -35% to 34% at 15 mg/L. Dilution of samples with high concentrations introduced bias for 4 procedures. The combined CV was >10% for 5 procedures. It was not possible to estimate total error due to dependence of bias on concentration. CVs for sample-specific influences were 0% to 15.2%. CONCLUSIONS Bias was the dominant source of disagreement among routine measurement procedures. Consequently, standardization efforts will improve agreement among results. Variation of bias with concentration needs to be addressed by manufacturers.
Bottleneck identification and scheduling in multithreaded applications

Performance of multithreaded applications is limited by a variety of bottlenecks, e.g. critical sections, barriers and slow pipeline stages. These bottlenecks serialize execution, waste valuable execution cycles, and limit scalability of applications. This paper proposes Bottleneck Identification and Scheduling in Multithreaded Applications (BIS), a cooperative software-hardware mechanism to identify and accelerate the most critical bottlenecks. BIS identifies which bottlenecks are likely to reduce performance by measuring the number of cycles threads have to wait for each bottleneck, and accelerates those bottlenecks using one or more fast cores on an Asymmetric Chip Multi-Processor (ACMP). Unlike previous work that targets specific bottlenecks, BIS can identify and accelerate bottlenecks regardless of their type. We compare BIS to four previous approaches and show that it outperforms the best of them by 15% on average. BIS' performance improvement increases as the number of cores and the number of fast cores in the system increase.
Role of Circulating Fibroblast Growth Factor 21 Measurement in Primary Prevention of Coronary Heart Disease Among Chinese Patients With Type 2 Diabetes Mellitus

Background Fibroblast growth factor 21 (FGF21) has demonstrated beneficial effects on lipid and carbohydrate metabolism. In cross‐sectional studies, an association of raised circulating FGF21 levels with coronary heart disease (CHD) was found in some but not all studies. Here we investigated prospectively whether baseline serum FGF21 levels could predict incident CHD in subjects with type 2 diabetes mellitus and no known cardiovascular diseases. Methods and Results Baseline serum FGF21 levels were measured in 3528 Chinese subjects with type 2 diabetes mellitus recruited from the Hong Kong West Diabetes Registry. The role of baseline serum FGF21 levels in predicting incident CHD over a median follow‐up of 3.8 years was analyzed using Cox regression analysis. Among 3528 recruited subjects without known cardiovascular diseases, 147 (4.2%) developed CHD over a mean follow‐up of 4 years. Baseline serum log‐transformed FGF21 levels were significantly higher in those who had incident CHD than those who did not (222.7 pg/mL [92.8–438.4] versus 151.1 pg/mL [75.6–274.6]; P<0.001). On multivariable Cox regression analysis, baseline serum FGF21 levels, using an optimal cutoff of 206.22 pg/mL derived from our study, independently predicted incident CHD (hazard ratio, 1.55; 95% CI, 1.10–2.19; P=0.013) and significantly improved net reclassification index and integrated discrimination improvement after adjustment for conventional cardiovascular risk factors. Conclusions We have demonstrated, for the first time, that serum FGF21 level is an independent predictor of incident CHD and might be usefully utilized as a biomarker for identifying type 2 diabetes mellitus subjects with raised CHD risk, for primary prevention.
Is Impact of Statin Therapy on All-Cause Mortality Different in HIV-Infected Individuals Compared to General Population? Results from the FHDH-ANRS CO4 Cohort

Background The effect of statins on all-cause mortality in the general population has been estimated as 0.86 (95%CI 0.79-0.94) for primary prevention. Reported values in HIV-infected individuals have been discordant. We assessed the impact of statin-based primary prevention on all-cause mortality among HIV-infected individuals. Methods Patients were selected among controls from a multicentre nested case-control study on the risk of myocardial infarction. Patients with prior cardiovascular or cerebrovascular disorders were not eligible. Potential confounders, including variables that were associated either with statin use and/or death occurrence and statin use were evaluated within the last 3 months prior to inclusion in the case-control study. Using an intention to continue approach, multiple imputation of missing data, Cox’s proportional hazard models or propensity based weighting, the impact of statins on the 7-year all-cause mortality was evaluated. Results Among 1,776 HIV-infected individuals, 138 (8%) were statins users. During a median follow-up of 53 months, 76 deaths occurred, including 6 in statin users. Statin users had more cardiovascular risk factors and a lower CD4 T cell nadir than statin non-users. In univariable analysis, the death rate was higher in statins users (11% vs 7%, HR 1.22, 95%CI 0.53-2.82). The confounders accounted for were age, HIV transmission group, current CD4 T cell count, haemoglobin level, body mass index, smoking status, anti-HCV antibodies positivity, HBs antigen positivity, diabetes and hypertension. In the Cox multivariable model the estimated hazard ratio of statin on all-cause mortality was estimated as 0.86 (95%CI 0.34-2.19) and it was 0.83 (95%CI 0.51-1.35) using inverse probability treatment weights. Conclusion The impact of statin for primary prevention appears similar in HIV-infected individuals and in the general population.
Deformation invariant image matching

We propose a novel framework to build descriptors of local intensity that are invariant to general deformations. In this framework, an image is embedded as a 2D surface in 3D space, with intensity weighted relative to distance in x-y. We show that as this weight increases, geodesic distances on the embedded surface are less affected by image deformations. In the limit, distances are deformation invariant. We use geodesic sampling to get neighborhood samples for interest points, and then use a geodesic-intensity histogram (GIH) as a deformation invariant local descriptor. In addition to its invariance, the new descriptor automatically finds its support region. This means it can safely gather information from a large neighborhood to improve discriminability. Furthermore, we propose a matching method for this descriptor that is invariant to affine lighting changes. We have tested this new descriptor on interest point matching for two data sets, one with synthetic deformation and lighting change, and another with real non-affine deformations. Our method shows promising matching results compared to several other approaches
Image Denoising via Multiscale Nonlinear Diffusion Models

Image denoising is a fundamental operation in image processing and holds considerable practical importance for various real-world applications. Arguably several thousands of papers are dedicated to image denoising. In the past decade, sate-of-the-art denoising algorithm have been clearly dominated by non-local patch-based methods, which explicitly exploit patch self-similarity within image. However, in recent two years, discriminatively trained local approaches have started to outperform previous non-local models and have been attracting increasing attentions due to the additional advantage of computational efficiency. Successful approaches include cascade of shrinkage fields (CSF) and trainable nonlinear reaction diffusion (TNRD). These two methods are built on filter response of linear filters of small size using feed forward architectures. Due to the locality inherent in local approaches, the CSF and TNRD model become less effective when noise level is high and consequently introduces some noise artifacts. In order to overcome this problem, in this paper we introduce a multi-scale strategy. To be specific, we build on our newly-developed TNRD model, adopting the multi-scale pyramid image representation to devise a multi-scale nonlinear diffusion process. As expected, all the parameters in the proposed multi-scale diffusion model, including the filters and the influence functions across scales, are learned from training data through a loss based approach. Numerical results on Gaussian and Poisson denoising substantiate that the exploited multi-scale strategy can successfully boost the performance of the original TNRD model with single scale. As a consequence, the resulting multi-scale diffusion models can significantly suppress the typical incorrect features for those noisy images with heavy noise.
Kinetic equations for the pure jump models of k-nary interacting particle systems

1. Aims of the paper. The paper is devoted to the description of the deterministic hydrodinamic limits (kinetic equations) of the general pure jump Markov modelds of knary interacting particle systems. The major particular cases are given by (i) the mass exchange processes which include the Smoluchovski coagulation model and its extensions with not necessary binary coagulations or fragmentation and also more general processes, where, say, the rate of coagulation or fragmentation of two particles can be increased or decreased by the presence of a third particle, or where a particle can split another particle in pieces and coagulate with one of them, (2) k-nary collision processes including Boltzmann’s collisions, (iii) various combinations of the mass exchange and collision processes. The main objectives of the paper are (i) to show that as a number of particles go to infinity and under a natural scaling of interaction rates, these processes converge weakly to measure-valued deterministic processes, (ii) to derive general kinetic equations that describe the evolution of these limiting processes (equations (3.7),(3.8) below that include the Smoluchovski equations and the Boltzmann equation as particular cases), (iii) to prove the well-posedness of the Cauchy problem for these equations. In [BK] we used a different method to obtain similar kinetic equations which was formal (i.e. without any rigorous convergence or existence results). In fact, we developed two such methods, one was suggested in [Be] and was based on the study of the evolution of
CellTrack: an open-source software for cell tracking and motility analysis

MOTIVATION Cell motility is a critical part of many important biological processes. Automated and sensitive cell tracking is essential to cell motility studies where the tracking results can be used for diagnostic or curative decisions and where mathematical models can be developed to deepen our understanding of the mechanisms underlying cell motility. RESULTS We have developed CellTrack: a self-contained, extensible, and cross-platform software package for cell tracking and motility analysis. Besides the general purpose image enhancement, object segmentation and tracking algorithms, we have implemented a novel edge-based method for sensitive tracking of the cell boundaries, and constructed an ensemble of methods that achieves refined tracking results even under large displacements or deformations of the cells. AVAILABILITY CellTrack is an Open Source project and is freely available at http://db.cse. ohio-state.edu/CellTrack.
Acetaminophen-induced proliferation of breast cancer cells involves estrogen receptors.

Previous studies have shown that acetaminophen, a common analgesic/antipyretic, induces proliferation of cultured breast cancer cells containing both estrogen and progesterone receptors (ER+/PR+). The main objective of this study was to evaluate the involvement of ERs in this effect. First, the effects of therapeutic acetaminophen concentrations were compared in breast cancer cells with high ERs and in T47Dco cells with lower ERs, to determine if acetaminophen-induced proliferation depends on ER levels. Second, the effects of two antiestrogens (ICI 182,780 and 4'-hydroxytamoxifen) on acetaminophen-induced proliferation were determined in three human breast cancer cell lines: two ER+/PR+ (MCF7, T47D) and one ER-/PR- (MDA-MB-231). Third, ER binding assays were performed in MCF7 cells to determine if acetaminophen competed with estradiol for binding to ERs. Proliferation endpoints monitored included percent cells in the DNA synthesis phase of the cell cycle, 3H-thymidine incorporation into DNA, and cell number. Acetaminophen did not induce DNA synthesis in T47Dco cells, but did in cells with higher ER levels, suggesting high ER levels are necessary for acetaminophen to induce proliferation. Antiestrogens inhibited acetaminophen-induced proliferation in ER+/PR+ cells while no effects were observed in ER-/PR- cells, further supporting ER involvement. However, acetaminophen did not compete with estradiol for binding to ERs in ER+/PR+ cells. Collectively, these data suggest that acetaminophen induces breast cancer cell proliferation via ERs without binding to ERs like estradiol. The second purpose of this study was to determine if acetaminophen is estrogenic/antiestrogenic in vivo (uterotrophic assays). Acetaminophen has no antiestrogenic/estrogenic activity in mice or rats uteri.