Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of Human Decay-Accelerating Factor in the Pathogenesis of Preterm Labor

Complement activation is thought to contribute to the pathogenesis of preterm labor (PTL). Decay-accelerating factor (DAF) is a natural complement pathway inhibitor. Our hypothesis was that DAF expression on maternal white blood cells (WBCs) in women with preterm labor is elevated compared with women with no preterm labor. Our secondary objective was to determine if differences in upregulation of DAF levels correlated with clinical outcomes. Serial blood samples were obtained from 30 patients with a clinical diagnosis of PTL and a control group of 30 pregnant individuals (same gestational age range) to determine DAF expression in peripheral WBCs in both groups. DAF expression was higher in women with PTL (less than 37 weeks) compared with the control group without PTL. Subjects with PTL who delivered before 34 weeks had less DAF expression and different kinetics of expression compared with those carrying pregnancies beyond 34 weeks. These data suggest that women with a clinical diagnosis of preterm labor have increased DAF expression on peripheral WBCs. Furthermore, it appears that failure to elevate DAF expression is associated with a risk of early premature delivery.
Redefining Performance Evaluation Tools for Real-Time QRS Complex Classification Systems

In a heartbeat classification procedure, the detection of QRS complex waveforms is necessary. In many studies, this heartbeat extraction function is not considered: the inputs of the classifier are assumed to be correctly identified. This communication aims to redefine classical performance evaluation tools in entire QRS complex classification systems and to evaluate the effects induced by QRS detection errors on the performance of heartbeat classification processing (normal versus abnormal). Performance statistics are given and discussed considering the MIT/BIH database records that are replayed on a real-time classification system composed of the classical detector proposed by Hamilton and Tompkins, followed by a neural-network classifier. This study shows that a classification accuracy of 96.72% falls to 94.90% when a drop of 1.78% error rate is introduced in the detector quality. This corresponds to an increase of about 50% bad classifications.
Effect of adaptive learning style scenarios on learning achievements

The reported study compares three adaptive learning style scenarios, namely: matching, compensating and monitoring. The matching and compensating scenarios operate in a design-time mode, while monitoring applies in a run-time adaptation mode. In addition, the study investigates the role of pre-assessment and embedded adaptation controls. In order to evaluate the effectiveness of the different adaptive scenarios, a software application serving as a test-bed was developed. An experimental study indicated that the monitoring adaptation led to higher learning achievements when compared to matching and compensating adaptation, although no significant effect was found.
A comprehensive model for power line interference in biopotential measurements

Power line interference is a major problem in high-resolution biopotential measurements. Because interference coupling is mostly capacitive, shielding electrode leads and a high common-mode rejection ratio (CMRR) are quite effective in reducing power-line interference but do not completely eliminate it. We propose a model that includes both interference external to the measuring system and interference coming from its internal power supply. Moreover, the model considers interference directly coupled to the measuring electrodes, because, as opposed to connecting leads, electrodes are not usually shielded. Experimental results confirm that reducing interference coupled through electrodes yields a negligible interference. The proposed model can be applied to other differential measurement systems, particularly those involving electrodes or sensors placed far apart.
Immunohistochemical localization of nicotinic acetylcholine receptor subunits in the mesencephalon and diencephalon of the chick (Gallus gallus)

Monoclonal antibodies against two α‐bungarotoxin‐binding subunits (α7 and α8) of the nicotinic acetylcholine receptors (nAChRs) were used as immunohistochemical probes to map their distribution in the chick diencephalon and mesencephalon. The distribution of the α7 and α8 nAChR subunits was compared to the distribution of immunoreactivity produced by a monoclonal antibody against the β2 structural subunit of the nAChRs.
The Effect of Calcium Sodium Phosphosilicate on Dentin Hypersensitivity: A Systematic Review and Meta-Analysis

Objective To investigate the effect of calcium sodium phosphosilicate (CSPS) in treating dentin hypersensitivity (DH) and to compare this effect to that of a negative (placebo) control. Materials and Methods Several databases, including Medline, EMBASE, Web of Science, The Cochrane Library, and the Chinese Biomedical Literature Database, were searched to identify relevant articles published through January 2015; grey literature (i.e., academic literature that is not formally published) was also searched. Two authors performed data extraction independently and jointly using data collection forms. The primary outcome was the DH pain response to routine activities or to thermal, tactile, evaporative, or electrical stimuli, and the secondary outcome was the side effects of CSPS use. Each study was evaluated using the Cochrane Collaboration tool for assessing risk bias. Meta-analysis of studies with the same participant demographics, interventions, controls, assessment methods and follow-up periods was performed. The Grading of Recommendations Assessment Development and Evaluation System was used to assess the quality of the evidence and the risk of bias across studies. Results Meta-analysis demonstrated that toothpaste containing 5% CSPS was more effective than the negative control at relieving dentin sensitivity, with the level of evidence classified as “moderate”. In addition, prophylaxis paste containing 15% calcium sodium phosphosilicate was favored over the negative control at reducing post-periodontal therapy hypersensitivity, with the level of evidence categorized as “low”. Only two studies reported side effects of CSPS use. Conclusions The majority of studies found that calcium sodium phosphosilicate was more effective than the negative control at alleviating DH. Because strong evidence is scarce, high-quality, well-designed clinical trials are required in the future before definitive recommendations can be made.
Large-scale detection and analysis of RNA editing in grape mtDNA by RNA deep-sequencing

RNA editing is a widespread post-transcriptional molecular phenomenon that can increase proteomic diversity, by modifying the sequence of completely or partially non-functional primary transcripts, through a variety of mechanistically and evolutionarily unrelated pathways. Editing by base substitution has been investigated in both animals and plants. However, conventional strategies based on directed Sanger sequencing are time-consuming and effectively preclude genome wide identification of RNA editing and assessment of partial and tissue-specific editing sites. In contrast, the high-throughput RNA-Seq approach allows the generation of a comprehensive landscape of RNA editing at the genome level. Short reads from Solexa/Illumina GA and ABI SOLiD platforms have been used to investigate the editing pattern in mitochondria of Vitis vinifera providing significant support for 401 C-to-U conversions in coding regions and an additional 44 modifications in non-coding RNAs. Moreover, 76% of all C-to-U conversions in coding genes represent partial RNA editing events and 28% of them were shown to be significantly tissue specific. Solexa/Illumina and SOLiD platforms showed different characteristics with respect to the specific issue of large-scale editing analysis, and the combined approach presented here reduces the false positive rate of discovery of editing events.
Modeling non-progressive phenomena for influence propagation

Most previous work on modeling influence propagation has focused on progressive models, i.e., once a node is influenced (active) the node stays in that state and cannot become inactive. However, this assumption is unrealistic in many settings where nodes can transition between active and inactive states. For instance, a user of a social network may stop using an app and become inactive, but again activate when instigated by a friend, or when the app adds a new feature or releases a new version. In this work, we study such non-progressive phenomena and propose an efficient model of influence propagation. Specifically, we model influence propagation as a continuous-time Markov process with 2 states: active and inactive. Such a model is both highly scalable (we evaluated on graphs with over 2 million nodes), 17-20 times faster, and more accurate for estimating the spread of influence, as compared with state-of-the-art progressive models for several applications where nodes may switch states.
Rotation-based RLS algorithms: unified derivations, numerical properties, and parallel implementations

This work presents a unified derivation of four rotation-based recursive least squares (RLS) algorithms. They solve the adaptive least squares problems of the linear combiner, the linear combiner without a desired signal, the single channel, and the multichannel linear prediction and transversal filtering. Compared to other approaches, the authors' derivation is simpler and unified, and may be useful to readers for better understanding the algorithms and their relationships. Moreover, it enables improvements of some algorithms in the literature in both the computational and the numerical issues. All algorithms derived in this work are based on Givens rotations. They offer superior numerical properties as shown by computer simulations. They are computationally efficient and highly concurrent. Aspects of parallel implementation and parameter identification are discussed. >
Dehydroepiandrosterone sulfotransferase as a possible shunt for the control of steroid metabolism in human mammary carcinoma.

Human primary mammary tumors were examined to determine what factors were of importance in deciding relative rates of sulfurylation of dehydroepiandrosterone and 17beta-estradiol, such rates having been shown to correlate with the patient's prognosis and response to adrenalectomy (T. L. Dao and P.R. Libby. Enzymic Synthesis of Steroid Sulfate by Mammary Cancer and Its Clinical Implications. Natl. Cancer Inst. Monographs, 34: 205-210, 1971). The sulfurylation of dehydroepiandrosterone and 17beta-estradiol was studied in 41 tumors in vitro using tumor cytosol, adenosine triphosphate, [35S]SO42-, Mg2+, and added steroid. Six tumors showed no sulfurylating ability, 9 sulfurylated dehydroepiandrosterone at a rate greater than that for 17beta-estradiol (ratio, greater than 1), and 26 sulfurylated dehydroepiandrosterone at a rate lower than that for 17beta-estradiol (ratio, less than 1). Evidence was obtained that low levels of dehydroepiandrosterone sulfotransferase were responsible for ratios of less than 1, in many instances. Adenosine 3'-phosphate 5'-phosphosulfate synthesis and steroid sulfotransferase activities were measured in 30 tumors. A significant correlation was found between synthesis of the former and levels of estrogen sulfotransferase, but this relationship did not hold for dehydroepiandrosterone sulfotransferase, again due to low levels of this enzyme in many tumors. It is suggested that dehydroepiandrosterone sulfate formation in the tumors is mainly controlled by the sulfotransferase, which acts as a shunt in regulating the level of free dehydroepiandrosterone, and related compounds, available for metabolism to steroids influencing the growth of mammary epithelial cells.
The feelings club: randomized controlled evaluation of school‐based CBT for anxious or depressive symptoms

Background: Children with anxious or depressive symptoms are at risk of developing internalizing disorders and their attendant morbidity. To prevent these outcomes, school‐based cognitive‐behavioral therapy (CBT) has been developed, but few studies include active control conditions. We evaluated a preventive CBT program targeting internalizing symptoms relative to an activity contrast condition post‐intervention and at 1‐year follow‐up. Methods: One thousand one hundred and thirty‐nine children from Grades 3–6 from a diverse sample of schools, were screened with the Multidimensional Anxiety Scale for Children and Children's Depression Inventory. Those with t>60 on either measure were offered participation in a randomized 12‐week trial, school‐based group CBT versus a structured after‐school activity group of equal duration. We explored several therapeutic elements as potential predictors of change. Results: One hundred and forty‐eight children participated (84 boys, 64 girls; 78 CBT, 70 contrast; 57% Caucasian) and 145 completed the program. Self‐reported anxious and depressive symptoms decreased significantly over time (η2=.15 and .133, respectively), with no group by time interaction. There was a trend toward fewer children meeting diagnostic criteria for an anxiety disorder on the Anxiety Disorders Interview Schedule at 1‐year post‐CBT than post‐contrast (6/76 versus 12/69). Positive reinforcement of child behavior was associated with change in anxiety symptoms; checking homework was understood with change in depressive symptoms. Conclusions: Findings suggest that children with internalizing symptoms may benefit from both school‐based CBT and structured activity programs. Replication, longer follow‐up, and further studies of therapeutic elements in child CBT are indicated. ISRCTN Registry identifier: ISRCTN88858028, url: http://www.controlled‐trials.com/ Depression and Anxiety, 2010. © 2010 Wiley‐Liss, Inc.
Regularizing max-margin exemplars by reconstruction and generative models

Part-based models are one of the leading paradigms in visual recognition. In the absence of costly part annotations, associating and aligning different training instances of a part classifier and finding characteristic negatives is challenging and computationally demanding. To avoid this costly mining of training samples, we estimate separate generative models for negatives and positives and integrate them into a max-margin exemplar-based model. The generative model and a sparsity constraint on the correlation between spatially neighboring feature dimensions regularize the part filters during learning and improve their generalization to similar instances. To suppress inappropriate positive part samples, we project the classifier back into the image domain and penalize against deviations from the original exemplar image patch. The part filter is then optimized to i) discriminate against clutter, to ii) generalize to similar instances of the part, and iii) to yield a good reconstruction of the original image patch. Moreover, we propose an approximation for estimating the geometric margin so that learning large numbers of parts becomes feasible. Experiments show improved part localization, object recognition, and part-based reconstruction performance compared to popular exemplar-based approaches on PASCAL VOC.
Pharmacological Characterization of a Dopamine Transporter Ligand That Functions as a Cocaine Antagonist

An N-butyl analog of benztropine, JHW007 [N-(n-butyl)-3α-[bis(4′-fluorophenyl)methoxy]-tropane], binds to dopamine transporters (DAT) but has reduced cocaine-like behavioral effects and antagonizes various effects of cocaine. The present study further examined mechanisms underlying these effects. Cocaine dose-dependently increased locomotion, whereas JHW007 was minimally effective but increased activity 24 hours after injection. JHW007 (3–10 mg/kg) dose-dependently and fully antagonized the locomotor-stimulant effects of cocaine (5–60 mg/kg), whereas N-methyl and N-allyl analogs and the dopamine (DA) uptake inhibitor GBR12909 [1-(2-[bis(4-fluorophenyl)methoxy]ethyl)-4-(3-phenylpropyl)piperazine dihydrochloride] stimulated activity and failed to antagonize effects of cocaine. JHW007 also blocked the locomotor-stimulant effects of the DAT inhibitor GBR12909 but not stimulation produced by the δ-opioid agonist SNC 80 [4-[(R)-[(2S,5R)-4-allyl-2,5-dimethylpiperazin-1-yl](3-methoxyphenyl)methyl]-N,N-diethylbenzamide], which increases activity through nondopaminergic mechanisms. JHW007 blocked locomotor-stimulant effects of cocaine in both DA D2- and CB1-receptor knockout and wild-type mice, indicating a lack of involvement of these targets. Furthermore, JHW007 blocked effects of cocaine on stereotyped rearing but enhanced stereotyped sniffing, suggesting that interference with locomotion by enhanced stereotypies is not responsible for the cocaine-antagonist effects of JHW007. Time-course data indicate that administration of JHW007 antagonized the locomotor-stimulant effects of cocaine within 10 minutes of injection, whereas occupancy at the DAT, as determined in vivo, did not reach a maximum until 4.5 hours after injection. The σ1-receptor antagonist BD 1008 [N-[2-(3,4-dichlorophenyl)ethyl]-N-methyl-2-(1-pyrrolidinyl)ethylamine dihydrobromide] blocked the locomotor-stimulant effects of cocaine. Overall, these findings suggest that JHW007 has cocaine-antagonist effects that are deviate from its DAT occupancy and that some other mechanism, possibly σ-receptor antagonist activity, may contribute to the cocaine-antagonist effect of JHW007 and like drugs.
Visual Search at Pinterest

We demonstrate that, with the availability of distributed computation platforms such as Amazon Web Services and open-source tools, it is possible for a small engineering team to build, launch and maintain a cost-effective, large-scale visual search system. We also demonstrate, through a comprehensive set of live experiments at Pinterest, that content recommendation powered by visual search improves user engagement. By sharing our implementation details and learnings from launching a commercial visual search engine from scratch, we hope visual search becomes more widely incorporated into today's commercial applications.
Restructuring of Focal Adhesion Plaques by Pi 3-Kinase

Focal adhesions are an elaborate network of interconnecting proteins linking actin stress fibers to the extracellular matrix substrate. Modulation of the focal adhesion plaque provides a mechanism for the regulation of cellular adhesive strength. Using interference reflection microscopy, we found that activation of phosphoinositide 3-kinase (PI 3-kinase) by PDGF induces the dissipation of focal adhesions. Loss of this close apposition between the cell membrane and the extracellular matrix coincided with a redistribution of α-actinin and vinculin from the focal adhesion complex to the Triton X-100–soluble fraction. In contrast, talin and paxillin remained localized to focal adhesions, suggesting that activation of PI 3-kinase induced a restructuring of the plaque rather than complete dispersion. Furthermore, phosphatidylinositol (3,4,5)-trisphosphate (PtdIns (3,4,5)-P3), a lipid product of PI 3-kinase, was sufficient to induce restructuring of the focal adhesion plaque. We also found that PtdIns (3,4,5)-P3 binds to α-actinin in PDGF-treated cells. Further evidence demonstrated that activation of PI 3-kinase by PDGF induced a decrease in the association of α-actinin with the integrin β subunit, and that PtdIns (3,4,5)-P3 could disrupt this interaction in vitro. Modification of focal adhesion structure by PI 3-kinase and its lipid product, PtdIns (3,4,5)-P3, has important implications for the regulation of cellular adhesive strength and motility.
Secondary Organic Aerosol Formation From Isoprene Epoxides in the Pearl River Delta, South China: IEPOX‐ and HMML‐Derived Tracers

Atmospheric photooxidation of isoprene forms isoprene epoxydiols (IEPOX) and hydroxymethel‐methyl‐α‐lactone (HMML) via hydroperoxyl radical (HO2) channel and NO/NO2 channel, respectively. Reactive uptake of these epoxides onto particles produces isoprene secondary organic aerosols (iSOA). Currently, there is little information regarding these two epoxides during iSOA formation in polluted regions. In this study, iSOA tracers from IEPOX and HMML were measured from summer to fall in the heavily polluted Pearl River Delta (PRD) region. The total concentration of the iSOA tracers ranged from 5.77 to 466 ng m−3. Isoprene SOA tracers correlated well with sulfate (p < 0.01), indicating that the abundant sulfate in the PRD plays an important role in iSOA formation. A kinetic model of IEPOX loss showed that 58% of IEPOX could undergo ring‐opening reactions under the polluted PRD conditions in summer. This leads to high levels of IEPOX‐derived SOA tracers in the PRD. High temperature in the PRD (>22 °C) suppresses the production of HMML, likely as a result of fast decomposition of HMML's precursor under high temperatures. Thus, the HMML‐derived tracers had lower levels than the IEPOX‐derived SOA tracers during the whole campaign. The ratios of the IEPOX‐derived tracers to the HMML‐derived SOA tracers in summer were ~3 times higher than those in fall. This seasonal trend may be explained by the relative high isoprene/NOx ratio, temperature, and fast heterogeneous reaction of IEPOX in summer. Our study shows that in highly polluted regions like PRD, reduction in SO2 emission can significantly reduce iSOA formation.
Asymptotic Distribution and Finite Sample Bias Correction of QML Estimators for Spatial Error Dependence Model

In studying the asymptotic and finite sample properties of quasi-maximum likelihood (QML) estimators for the spatial linear regression models, much attention has been paid to the spatial lag dependence (SLD) model; little has been given to its companion, the spatial error dependence (SED) model. In particular, the effect of spatial dependence on the convergence rate of the QML estimators has not been formally studied, and methods for correcting finite sample bias of the QML estimators have not been given. This paper fills in these gaps. Of the two, bias correction is particularly important to the applications of this model, as it leads potentially to much improved inferences for the regression coefficients. Contrary to the common perceptions, both the large and small sample behaviors of the QML estimators for the SED model can be different from those for the SLD model in terms of the rate of convergence and the magnitude of bias. Monte Carlo results show that the bias can be severe, and the proposed bias correction procedure is very effective.