Miracle-dz/UniFAR-FTUs huggingface dataset:
Coronary Artery Disease Detected by Coronary Computed Tomographic Angiography Is Associated With Intensification of Preventive Medical Therapy and Lower Low-Density Lipoprotein Cholesterol

Background—Coronary computed tomographic angiography (CCTA) is an accurate test for the identification of coronary artery disease (CAD), yet the impact of CCTA results on subsequent medical therapy and risk factors has not been widely reported. Methods and Results—We identified consecutive patients aged >18 years without prior CAD who underwent CCTA from 2004 to 2011 and had complete data on medications before and after CCTA. CCTA results were categorized as no CAD, <50% stenosis, and ≥50% stenosis. Based on the number of involved segments, extent of disease was categorized as nonextensive (⩽4 segments) or extensive CAD (>4 segments). Electronic medical records and patient interviews were reviewed blinded to CCTA findings to assess initiation of aspirin and intensification of lipid-lowering therapies. Survival analysis was performed to evaluate intensification of lipid therapy as a predictor of cardiovascular death or nonfatal myocardial infarction. Among 2839 patients with mean follow-up of 3.6 years, the odds of physician intensification of lipid-lowering therapy significantly increased for those with nonobstructive CAD (odds ratio, 3.6; 95% confidence interval, 2.9–4.9; P<0.001) and obstructive CAD (odds ratio, 5.6; 95% confidence interval, 4.3–7.3; P<0.001). Low-density lipoprotein cholesterol levels declined significantly in association with intensification of lipid-lowering therapy after CCTA in all patient subgroups. In a hypothesis-generating analysis, among patients with nonobstructive but extensive CAD, statin use after CCTA was associated with a reduction in cardiovascular death or myocardial infarction (hazards ratio, 0.18; 95% confidence interval, 0.05–0.66; P=0.01). Conclusions—Abnormal CCTA findings are associated with downstream intensification in statin and aspirin therapy. In particular, CCTA may lead to increased use of prognostically beneficial therapies in patients identified as having extensive, nonobstructive CAD.
Pregnancy and levels of depression and anxiety: A prospective cohort study of Australian women

Objective: The effects of pregnancy on depression and anxiety remain unclear. Previous research is predominantly cross-sectional, not representative of the general community, and does not include data on mental health prior to pregnancy. This study used longitudinal Australian population-based data to examine whether pregnancy is associated with increases in women’s anxiety and depression levels (from pre-pregnancy). Method: A community sample of Australian women aged 20–24 years were recruited prospectively and assessed in 1999, 2003 and 2007. At the follow-up assessments 76 women were pregnant (with no prior children) and 542 remained nulliparous. Mixed models repeated measures analyses of variance were undertaken to compare change in levels of anxiety and depression (Goldberg Anxiety and Depression scales) between those who became pregnant and those who remained non-pregnant. Results: Pregnancy was not associated with increased symptoms of depression or anxiety. No association was found with depression, while pregnancy was associated with a decrease in anxiety. Including somatic items in the measures of depression and anxiety resulted in higher symptom levels in pregnancy, suggesting possible item bias. Conclusions: This study is one of the first to follow a community sample of women from pre-pregnancy to pregnancy. The findings suggest that pregnancy is not typically detrimental to women’s mental health. The current study offers a starting point for future prospective studies to follow women from pre-pregnancy to postpartum. Study limitations to be improved upon in follow-up research include expanding the sample size, and including both pregnancy-specific measures and trimester-specific data. Future research should continue to identify those women who are most (and least) at risk during pregnancy in order to target resources and assistance most effectively.
Allergen‐induced cytokine secretion in atopic and non‐atopic asthmatic children

Atopic asthma is characterized by excessive T helper 2 (Th2)‐like immunity to allergens in the bronchial mucosa. The Th2‐cytokine interleukin (IL)‐4 induces IgE production, while the Th2‐cytokine IL‐5 promotes eosinophilic inflammation in the airways of asthmatics. Most asthmatics are atopic, but a subgroup is non‐atopic. We hypothesize that allergen‐induced Th2, particularly IL‐5, responses can be observed in peripheral blood in both atopic and non‐atopic asthmatic children but not in healthy control children. The aim of the present study was to determine IL‐4, IL‐5, IL‐9, IL‐10, IL‐13 and IFN‐γ secretion induced from peripheral blood mononuclear cells (PBMC) by a broad panel of inhalant allergens (timothy, cat, birch, dog and house dust mite) in asthmatic children with and without sensitization. The study included 13 atopic asthmatic, 5 non‐atopic asthmatic, and 12 non‐atopic non‐asthmatic children. PBMC were stimulated with allergens and cytokine production was measured with enzyme‐linked immunosorbent assay (ELISA). Higher levels of cat and dog antigen‐induced IL‐5 release were more commonly observed in both atopic and non‐atopic asthmatics than in controls. Children with atopic, but not non‐atopic, asthma produced higher levels of allergen‐induced IL‐4 and IL‐9 than controls. Non‐atopic asthmatics produced more IL‐10 than atopic asthmatics after cat stimulation. High levels of eosinophilia‐associated IL‐5 responses are induced by cat and dog allergen in both atopic and non‐atopic asthmatic children. The Th2 cytokines IL‐4 and IL‐9 were associated only with atopic asthma, probably due to their IgE‐inducing properties.
Influence of Weed Management Practices on Growth Parameters and Economics of Cowpea [Vigna unguiculata (L.) Wasp.]

and (quizalofop-ethyl + 1 HW + 1 IC) very effective in weed control and had positive impact on plant height, plant spread, number of branch per plant, number of pods per plant and number of seeds per pods. These treatments were as good as weed free plot. These integrated weed management treatments gave broad spectrum weed control and higher gross, net return and B:C ratio. By adopting appropriate weed management practices farmer can get 3000 to 4000 net increase in return over the other treatment. So integrated weed management is better option and cowpea grower combine cultural practices with suitable pre and post herbicides like as pendimethalin, quizalofop-ethyl and imazethapyr to get similar return as weed free plot.
Feature Selection for Gene Expression Using Model-Based Entropy

Gene expression data usually contain a large number of genes but a small number of samples. Feature selection for gene expression data aims at finding a set of genes that best discriminate biological samples of different types. Using machine learning techniques, traditional gene selection based on empirical mutual information suffers the data sparseness issue due to the small number of samples. To overcome the sparseness issue, we propose a model-based approach to estimate the entropy of class variables on the model, instead of on the data themselves. Here, we use multivariate normal distributions to fit the data, because multivariate normal distributions have maximum entropy among all real-valued distributions with a specified mean and standard deviation and are widely used to approximate various distributions. Given that the data follow a multivariate normal distribution, since the conditional distribution of class variables given the selected features is a normal distribution, its entropy can be computed with the log-determinant of its covariance matrix. Because of the large number of genes, the computation of all possible log-determinants is not efficient. We propose several algorithms to largely reduce the computational cost. The experiments on seven gene data sets and the comparison with other five approaches show the accuracy of the multivariate Gaussian generative model for feature selection, and the efficiency of our algorithms.
Emergent Spatial Patterns of Excitatory and Inhibitory Synaptic Strengths Drive Somatotopic Representational Discontinuities and their Plasticity in a Computational Model of Primary Sensory Cortical Area 3b

Mechanisms underlying the emergence and plasticity of representational discontinuities in the mammalian primary somatosensory cortical representation of the hand are investigated in a computational model. The model consists of an input lattice organized as a three-digit hand forward-connected to a lattice of cortical columns each of which contains a paired excitatory and inhibitory cell. Excitatory and inhibitory synaptic plasticity of feedforward and lateral connection weights is implemented as a simple covariance rule and competitive normalization. Receptive field properties are computed independently for excitatory and inhibitory cells and compared within and across columns. Within digit representational zones intracolumnar excitatory and inhibitory receptive field extents are concentric, single-digit, small, and unimodal. Exclusively in representational boundary-adjacent zones, intracolumnar excitatory and inhibitory receptive field properties diverge: excitatory cell receptive fields are single-digit, small, and unimodal; and the paired inhibitory cell receptive fields are bimodal, double-digit, and large. In simulated syndactyly (webbed fingers), boundary-adjacent intracolumnar receptive field properties reorganize to within-representation type; divergent properties are reacquired following syndactyly release. This study generates testable hypotheses for assessment of cortical laminar-dependent receptive field properties and plasticity within and between cortical representational zones. For computational studies, present results suggest that concurrent excitatory and inhibitory plasticity may underlie novel emergent properties.
Shift Work Disorder in a Random Population Sample – Prevalence and Comorbidities

Few studies have investigated the presence of shift work disorder (SWD) in the general community. We addressed many of the limitations in this literature and present new findings. SWD has been treated as an ‘all or none’ construct but we propose the need to consider the ‘severity’ of the disorder. Using random digit dialling, we randomly recruited 1163 participants. Participants completed an extensive battery of scales and questions concerning work, health and individual differences. Three questions based on the criteria from the International Classification for Sleep Disorders were used to categorise participants with SWD (n = 176). In addition, we asked participants whether SWD interfered with aspects of their life and high ratings were used to define severe shift work disorder (SSWD). The prevalence of SWD was 32.1% among night workers and 10.1% in day workers (p<.001). SSWD was present in 9.1% of night workers and 1.3% of day workers (p<.001). Adjusted logistic regression analyses found significant associations between SWD and night work (OR = 3.35, CI 2.19-5.12), weekly work hours (OR = 1.02, CI 1.00–1.04), short sleep (≤6 h; OR = 2.93, CI 1.94–4.41), languidity (OR = 1.11, CI 1.06–1.16) and resilience (OR = 0.56, CI 0.43–0.81). Night work, short sleep, languidity, and hypertension were significantly associated with SSWD. Overall, participants with SSWD slept 0.80 h less than other participants (p<.001). Night work, short sleep and languidity were associated with both SWD and SSWD. Day workers with SWD symptoms reported significantly shorter sleep duration, higher levels of languidity and worked longer working hours compared to day workers without SWD.
JAC: declarative Java concurrency

The Java programming language has a low‐level concurrency model which is hard to use and does not blend well with inheritance. JAC is an extension of Java that introduces a higher level of concurrency, hiding threads and separating thread synchronization from application logic in a declarative fashion. The emphasis is on limiting the differences between sequential and concurrent code, thus furthering code reuse, and on avoiding inheritance anomalies. This is achieved by taking a middle road between concurrent code on the one hand and complete separation of sequential application logic from concurrency mechanisms on the other. An extensive comparison with related approaches is given for motivating our design decisions. Copyright © 2005 John Wiley & Sons, Ltd.
Quasiperiodic Whistler Mode Emissions Observed by the Van Allen Probes Spacecraft

Quasiperiodic (QP) emissions are whistler mode electromagnetic waves observed in the inner magnetosphere that exhibit a QP time modulation of the wave intensity. We analyze 768 QP events observed during the first 5 years of the operation of the Van Allen Probes spacecraft (September 2012 to October 2017). Multicomponent wave measurements performed in the equatorial region, where the emissions are likely generated, are used to reveal new experimental information about their properties. We show that the events are observed nearly exclusively inside the plasmasphere. Wave frequencies are mostly between about 0.5 and 4 kHz. The events observed at larger radial distances and on the duskside tend to have slightly lower frequencies than the emissions observed elsewhere. The maximum event frequencies are limited by half of the equatorial electron gyrofrequency, suggesting the importance of wave ducting. Modulation periods are typically between about 0.5 and 5 min, and they increase with the in situ measured plasma number density. This increase is consistent with the main mechanisms suggested to explain the origin of the QP modulation. Two‐point measurements performed by the Van Allen Probes are used to estimate a typical spatial extent of the emissions to about 1 RE in radial distance and 1.5 hr in magnetic local time. Detailed wave analysis shows that the emissions are right‐hand circularly polarized, and they usually come from several different directions simultaneously. They, however, predominantly propagate at rather low wave normal angles and away from the geomagnetic equator.
Non-invasive magnetic resonance thermometry using thulium-1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetate (TmDOTA-)

Non-invasive thermometry is pivotal to the future advances of regional hyperthermia as a cancer treatment modality. Current magnetic resonance (MR) thermometry methods suffer from poor thermal resolution due to relatively weak dependence of chemical shift of the 1 H water signal on temperature. This study evaluated the feasibility of using thulium-1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetate (TmDOTA-) for MR thermometry. TmDOTA- is non-toxic and the gadolinium complex of DOTA4- is widely used as a MR contrast agent. The results demonstrate that the temperature dependence of the TmDOTA- proton shifts are about two orders of magnitudes higher than the water proton and, thus, provide excellent accuracy and resolution. In addition, TmDOTA - proton shifts are insensitive to the paramagnetic complex concentration, pH, Ca2+ or presence of plasma macromolecules and ions. Because hyperthermia is known to produce changes in tissue pH and other physiological parameters, these properties of TmDOTA- greatly simplify the procedures for using the lanthanide complex for MR thermometry. Application of TmDOTA- for measurement of temperature in a subcutaneously implanted human melanoma xenograft is demonstrated. Finally, the feasibility of imaging one of the 1H resonances of the lanthanide complex is demonstrated in phantom experiments. Overall, TmDOTA- appears to be a promising probe for MR thermometry in vivo.
Using real-time polymerase chain reaction as an alternative rapid method for enumeration of colony count in live Brucella vaccines

Aim:: Brucellosis is a major bacterial zoonosis of global importance affecting a range of animal species and man worldwide. It has economic, public health, and bio-risk importance. Control and prevention of animal brucellosis mainly depend on accurate diagnostic tools and implementation of effective and safe animal vaccination program. There are three types of animal Brucella live vaccines - Brucella melitensis Rev-1 vaccine, Brucella abortus S19, and B. abortus RB51. Evaluation of these vaccines depends mainly on enumeration of Brucella viable count. At present, used colony count method is time consuming, costly and requires especial skills. Hence, the aim of this study is to use and standardize real-time polymerase chain reaction (RT-PCR) as an alternative, quantitative, sensitive, and rapid method to detect the colony count of Brucella in live Brucella vaccine. Materials and Methods:: Four batches of different live Brucella vaccines were evaluated using of conventional bacterial count and RT-quantitative PCR (RT-qPCR) using BSCP31 gene specific primers and probe. Standard curve was generated from DNA template extracted from 10-fold serial dilution of living B. abortus RB51 vaccine to evaluate the sensitivity of RT-qPCR. Results:: Results revealed that three batches of living Brucella vaccines were acceptable for Brucella colony count when traditional bacterial enumeration method was used. Results of RT-qPCR were identical to that of conventional bacterial count. Conclusions:: Results concluded that RT-qPCR was relatively sensitive compared to traditional bacterial colony count of these vaccines.
Discovery of the most metal-poor damped Lyman-α system

We report the discovery and analysis of the most metal-poor damped Lyman α (DLA) system currently known, based on observations made with the Keck HIRES spectrograph. The metal paucity of this system has only permitted the determination of three element abundances: [C/H] = −3.43 ± 0.06, [O/H] = −3.05 ± 0.05 and [Si/H] = −3.21 ± 0.05, as well as an upper limit on the abundance of iron: [Fe/H] ≤ −2.81. This DLA is among the most carbon-poor environment currently known with detectable metals. By comparing the abundance pattern of this DLA to detailed models of metal-free nucleosynthesis, we find that the chemistry of the gas is consistent with the yields of a 20.5 M_⊙ metal-free star that ended its life as a core-collapse supernova; the abundances we measure are inconsistent with the yields of pair-instability supernovae. Such a tight constraint on the mass of the progenitor Population III star is afforded by the well-determined C/O ratio, which we show depends almost monotonically on the progenitor mass when the kinetic energy of the supernova explosion is Eexp ≳ 1.5 × 10^(51) erg. We find that the DLA presented here has just crossed the critical ‘transition discriminant’ threshold, rendering the DLA gas now suitable for low mass star formation. We also discuss the chemistry of this system in the context of recent models that suggest some of the most metal-poor DLAs are the precursors of the ‘first galaxies’, and are the antecedents of the ultrafaint dwarf galaxies.
Chromatin silencing and the maintenance of a functional germline in Caenorhabditis elegans.

The germline of the nematode Caenorhabditis elegans exhibits a remarkable ability to specifically silence transgenic DNA. We have shown that this silencing mechanism is disrupted in animals mutant for the maternal effect sterile genes mes-2, mes-3, mes-4 and mes-6. The proteins encoded by mes-2 and mes-6 have been shown to be related to the Polycomb Group of transcriptional repressors (Holdeman, R., Nehrt, S. and Strome, S. (1998). Development 125, 2457-2467; Korf, I. , Fan, F. and Strome, S. (1998). Development 125, 2469-2478). These results suggest that a genetic silencing process is essential for sustained germline function, and that this silencing is mediated, at least in part, by Polycomb Group proteins.
Asymmetric Volterra Models Based on Ladder-Structured Generalized Orthonormal Basis Functions

In this paper, an improved method to construct and estimate Volterra models using Generalized Orthonormal Basis Functions (GOBF) is presented. The proposed method extends results obtained in previous works, where an exact technique for optimizing the GOBF parameters (poles) for symmetric Volterra models of any order was presented. The proposed extensions take place in two different ways: (i) the new formulation is derived in such a way that each multidimensional kernel of the model is decomposed into a set of independent orthonormal bases (rather than a single, common basis), each of which is parameterized by an individual set of poles responsible for representing the dominant dynamic of the kernel along a particular dimension; and (ii) the new formulation is based on a ladder-structured GOBF architecture that is characterized by having only real-valued parameters to be estimated, regardless of whether the GOBF poles encoded by these parameters are real- or complex-valued. The exact gradients of an error functional with respect to the parameters to be optimized are computed analytically and provide exact search directions for an optimization process that uses only input-output data measured from the dynamic system to be modeled. Computational experiments are presented to illustrate the benefits of the proposed approach when modeling nonlinear systems.
Inter-Method Discrepancies in Brain Volume Estimation May Drive Inconsistent Findings in Autism

Previous studies applying automatic preprocessing methods on Structural Magnetic Resonance Imaging (sMRI) report inconsistent neuroanatomical abnormalities in Autism Spectrum Disorder (ASD). In this study we investigate inter-method differences as a possible cause behind these inconsistent findings. In particular, we focus on the estimation of the following brain volumes: gray matter (GM), white matter (WM), cerebrospinal fluid (CSF), and total intra cranial volume (TIV). T1-weighted sMRIs of 417 ASD subjects and 459 typically developing controls (TDC) from the ABIDE dataset were estimated using three popular preprocessing methods: SPM, FSL, and FreeSurfer (FS). Brain volumes estimated by the three methods were correlated but had significant inter-method differences; except TIVSPM vs. TIVFS, all inter-method differences were significant. ASD vs. TDC group differences in all brain volume estimates were dependent on the method used. SPM showed that TIV, GM, and CSF volumes of ASD were larger than TDC with statistical significance, whereas FS and FSL did not show significant differences in any of the volumes; in some cases, the direction of the differences were opposite to SPM. When methods were compared with each other, they showed differential biases for autism, and several biases were larger than ASD vs. TDC differences of the respective methods. After manual inspection, we found inter-method segmentation mismatches in the cerebellum, sub-cortical structures, and inter-sulcal CSF. In addition, to validate automated TIV estimates we performed manual segmentation on a subset of subjects. Results indicate that SPM estimates are closest to manual segmentation, followed by FS while FSL estimates were significantly lower. In summary, we show that ASD vs. TDC brain volume differences are method dependent and that these inter-method discrepancies can contribute to inconsistent neuroimaging findings in general. We suggest cross-validation across methods and emphasize the need to develop better methods to increase the robustness of neuroimaging findings.