Miracle-dz/UniFAR-FTUs huggingface dataset:
Brain "ouabain" and angiotensin II contribute to cardiac dysfunction after myocardial infarction.

In chronic heart failure (CHF), sympathetic activity increases in parallel with the impairment of left ventricle (LV) function, and sympathetic hyperactivity has been postulated to contribute to the progression of heart failure. In the brain, compounds with ouabain-like activity ("ouabain," for brevity) and the renin-angiotensin system contribute to sympathetic hyperactivity in rats with CHF after myocardial infarction (MI). In the present studies, we assessed whether, in rats, chronic blockade of brain "ouabain" or the brain renin-angiotensin system inhibits the post-MI LV dysfunction. In rats, an MI was induced by acute coronary artery ligation. At either 0.5 or 4 wk post-MI, chronic treatment with Fab fragments for blocking brain "ouabain" or with losartan for blocking brain AT1 receptors was started and continued until 8 wk post-MI using osmotic minipumps connected to intracerebroventricular cannulas. At 8 wk post-MI, in conscious rats, LV pressures were measured at rest and in response to volume and pressure overload, followed by LV passive pressure-volume curves in vitro. At 8 wk post-MI, control MI rats exhibited clear increases in LV end-diastolic pressure (LVEDP) at rest and in response to pressure and volume overload. LV pressure-volume curves in vitro showed a marked shift to the right. Intravenous administration of the Fab fragments or losartan at rates used for central blockade did not affect these parameters. In contrast, chronic central blockade with either Fab fragments or losartan significantly lowered LVEDP at rest (only in 0.5- to 8-wk groups) and particularly in response to pressure or volume overload. LV dilation, as assessed from LV pressure-volume curves, was also significantly inhibited. These results indicate that chronic blockade of brain "ouabain" or brain AT1 receptors substantially inhibits development of LV dilation and dysfunction in rats post-MI.
Text mining for product attribute extraction

We describe our work on extracting attribute and value pairs from textual product descriptions. The goal is to augment databases of products by representing each product as a set of attribute-value pairs. Such a representation is beneficial for tasks where treating the product as a set of attribute-value pairs is more useful than as an atomic entity. Examples of such applications include demand forecasting, assortment optimization, product recommendations, and assortment comparison across retailers and manufacturers. We deal with both implicit and explicit attributes and formulate both kinds of extractions as classification problems. Using single-view and multi-view semi-supervised learning algorithms, we are able to exploit large amounts of unlabeled data present in this domain while reducing the need for initial labeled data that is expensive to obtain. We present promising results on apparel and sporting goods products and show that our system can accurately extract attribute-value pairs from product descriptions. We describe a variety of application that are built on top of the results obtained by the attribute extraction system.
FOLIAGE APPLIED ZINC IMPROVE THE GROWTH AND PRODUCTIVITY OF WHEAT

A field experiment was conducted to investigate the effect of foliar application of zinc fertilizer on the growth, yield and yield components of wheat. Experiment was laid out in a factorial randomized completely block design consisting of twelve treatments with three replications. The levels of zinc sulfate were 0 (control water spray), 0.25% solution of zinc, 0.5% solution of zinc, 0.75% solution of zinc. Levels of zinc sulfate were applied at tillering, booting and tillering × booting stages of growth. Results revealed that highest values for relative growth rate, leaf area index, net assimilation rate, total number of fertile tillers m -2 , plant height, number of spikelets spike -1 , spike length, grain spike -1 , 1000 grains weight, grain yield, straw yield, biological yield and harvest index was observed with 0.5% solution of zinc sulfate. Foliar application of 0.5% solution of zinc sulfate (at the time of tillering booting) appeared to be the best doze for wheat crop under Multan conditions.
Higher Dietary Magnesium Intake and Higher Magnesium Status Are Associated with Lower Prevalence of Coronary Heart Disease in Patients with Type 2 Diabetes

In type 2 diabetes mellitus (T2D), the handling of magnesium is disturbed. Magnesium deficiency may be associated with a higher risk of coronary heart disease (CHD). We investigated the associations between (1) dietary magnesium intake; (2) 24 h urinary magnesium excretion; and (3) plasma magnesium concentration with prevalent CHD in T2D patients. This cross-sectional analysis was performed on baseline data from the DIAbetes and LifEstyle Cohort Twente-1 (DIALECT-1, n = 450, age 63 ± 9 years, 57% men, and diabetes duration of 11 (7–18) years). Prevalence ratios (95% CI) of CHD by sex-specific quartiles of magnesium indicators, as well as by magnesium intake per dietary source, were determined using multivariable Cox proportional hazard models. CHD was present in 100 (22%) subjects. Adjusted CHD prevalence ratios for the highest compared to the lowest quartiles were 0.40 (0.20, 0.79) for magnesium intake, 0.63 (0.32, 1.26) for 24 h urinary magnesium excretion, and 0.62 (0.32, 1.20) for plasma magnesium concentration. For every 10 mg increase of magnesium intake from vegetables, the prevalence of CHD was, statistically non-significantly, lower (0.75 (0.52, 1.08)). In this T2D cohort, higher magnesium intake, higher 24 h urinary magnesium excretion, and higher plasma magnesium concentration are associated with a lower prevalence of CHD.
Risk assessment in pulmonary arterial hypertension

In its August 2017 issue, the European Respiratory Journal published two papers on risk assessment in pulmonary arterial hypertension (PAH), one coming from the French registry [1], the other from COMPERA, a European pulmonary hypertension (PH) registry [2]. Both groups utilised abbreviated versions of the risk assessment strategy proposed in the current European PH guidelines [3, 4] and both included basically the same variables, i.e. World Health Organization functional class (FC), 6-min walking distance (6MWD), cardiac index, right atrial pressure and serum levels of brain natriuretic peptide (BNP) or the N-terminal fragment of its propeptide (NT-proBNP). In both studies, the cut-off values used to determine risk were those proposed in the European guidelines [3, 4]. However, the strategy to determine individual risk differed in the two studies: COMPERA calculated the average individual risk by assigning a score of 1, 2 or 3 to each criterion (1: low risk; 2; intermediate risk; 3: high risk) and rounding to the mean of the available variables, as had been previously proposed by a group from Sweden [5]. The French group, in contrast, looked at the number of variables that met the low-risk criteria. Despite these differences, the main results of both studies were similar, especially 1) that the risk stratification tool proposed by the European guidelines adequately predicted mortality, 2) that follow-up risk assessment on treatment was a more reliable predictor of survival than the initial risk assessment at the time of diagnosis, and 3) that FC, 6MWD and BNP/NT-proBNP at follow-up were independent predictors of outcome. However, there also were important differences in the two analyses: in the French study, 19% of the patients with idiopathic PAH (IPAH) met all three noninvasive low-risk criteria at follow-up, i.e. FC I or II, 6MWD >440 m, BNP <50 ng·L−1 or NT-proBNP <300 ng·L−1; these patients had a 1-year survival of 100% and a 5-year survival of 97%. In COMPERA, 21% of the IPAH patients were classified as low risk at follow-up; these patients had a 1-year survival of 96% but the 5-year survival of these patients was only 72% (data available in the online supplement of [2]). We wondered whether the differences in long-term survival were due to the fact that the low-risk definition was less strict with the COMPERA strategy than with the French strategy or whether differences in the two patient cohorts were responsible for these findings (patients in French cohort were younger than the patients in COMPERA and combinations of PAH drugs were used more frequently in the French series than in the COMPERA cohort). PAH patients reaching a low risk profile with targeted therapies have an excellent long-term survival http://ow.ly/RBjo30i6N57
Linear Feature Projection-Based Sensory Event Detection from the Multiunit Activity of Dorsal Root Ganglion Recordings

Afferent signals recorded from the dorsal root ganglion can be used to extract sensory information to provide feedback signals in a functional electrical stimulation (FES) system. The goal of this study was to propose an efficient feature projection method for detecting sensory events from multiunit activity-based feature vectors of tactile afferent activity. Tactile afferent signals were recorded from the L4 dorsal root ganglion using a multichannel microelectrode for three types of sensory events generated by mechanical stimulation on the rat hind paw. The multiunit spikes (MUSs) were extracted as multiunit activity-based feature vectors and projected using a linear feature projection method which consisted of projection pursuit and negentropy maximization (PP/NEM). Finally, a multilayer perceptron classifier was used to detect sensory events. The proposed method showed a detection accuracy superior to those of other linear and nonlinear feature projection methods and all processes were completed within real-time constraints. Results suggest that the proposed method could be useful to detect sensory events in real time. We have demonstrated the methodology for an efficient feature projection method to detect real-time sensory events from the multiunit activity of dorsal root ganglion recordings. The proposed method could be applied to provide real-time sensory feedback signals in closed-loop FES systems.
Revealing critical channels and frequency bands for emotion recognition from EEG with deep belief network

For EEG-based emotion recognition tasks, there are many irrelevant channel signals contained in multichannel EEG data, which may cause noise and degrade the performance of emotion recognition systems. In order to tackle this problem, we propose a novel deep belief network (DBN) based method for examining critical channels and frequency bands in this paper. First, we design an emotion experiment and collect EEG data while subjects are watching emotional film clips. Then we train DBN for recognizing three emotions (positive, neutral, and negative) with extracted differential entropy features as input and compare DBN with other shallow models such as KNN, LR, and SVM. The experiment results show that DBN achieves the best average accuracy of 86.08%. We further explore critical channels and frequency bands by examining the weight distribution learned by DBN, which is different from the existing work. We identify four profiles with 4, 6, 9 and 12 channels, which achieve recognition accuracies of 82.88%, 85.03%, 84.02%, 86.65%, respectively, using SVM.
Hypothalamic-pituitary-adrenal axis changes allow seasonal modulation of corticosterone in a bird.

We examined possible mechanisms underlying seasonal stress modulation in Lapland longspurs ( Calcarius lapponicus), a species that breeds and molts (the energetically costly replacement of feathers) in the Alaskan Arctic. Free-living Lapland longspurs show dramatically reduced maximal corticosterone release during molt compared with the breeding season, an effect lost in captive birds. Neither changes in corticosterone binding proteins nor the overall condition of the bird (assessed by weight and fat storage) can explain different seasonal corticosterone responses. Adrenal insensitivity also does not fully explain reduced maximal output because exogenous ACTH enhanced corticosterone release during molt. Exogenous ACTH in molting birds, however, cannot stimulate corticosterone to stress-induced levels during breeding, implying reduced adrenal capacity. Lapland longspur pituitaries appeared to respond to exogenous corticotropin-releasing factor, arginine vasotocin, and mesotocin (the avian equivalents of arginine vasopressin and oxytocin) during molt, suggesting that a mechanism upstream of the pituitary blunts corticosterone release. Taken together, these results indicate that seasonal modulation of corticosterone release in this species is controlled at multiple sites in the hypothalamic-pituitary-adrenal axis.
Identifying HLA supertypes by learning distance functions

MOTIVATION The development of epitope-based vaccines crucially relies on the ability to classify Human Leukocyte Antigen (HLA) molecules into sets that have similar peptide binding specificities, termed supertypes. In their seminal work, Sette and Sidney defined nine HLA class I supertypes and claimed that these provide an almost perfect coverage of the entire repertoire of HLA class I molecules. HLA alleles are highly polymorphic and polygenic and therefore experimentally classifying each of these molecules to supertypes is at present an impossible task. Recently, a number of computational methods have been proposed for this task. These methods are based on defining protein similarity measures, derived from analysis of binding peptides or from analysis of the proteins themselves. RESULTS In this paper we define both peptide derived and protein derived similarity measures, which are based on learning distance functions. The peptide derived measure is defined using a peptide-peptide distance function, which is learned using information about known binding and non-binding peptides. The protein derived similarity measure is defined using a protein-protein distance function, which is learned using information about alleles previously classified to supertypes by Sette and Sidney (1999). We compare the classification obtained by these two complimentary methods to previously suggested classification methods. In general, our results are in excellent agreement with the classifications suggested by Sette and Sidney (1999) and with those reported by Buus et al. (2004). The main important advantage of our proposed distance-based approach is that it makes use of two different and important immunological sources of information-HLA alleles and peptides that are known to bind or not bind to these alleles. Since each of our distance measures is trained using a different source of information, their combination can provide a more confident classification of alleles to supertypes.
Knowledge-Assisted Ranking: A Visual Analytic Application for Sports Event Data

Organizing sports video data for performance analysis can be challenging, especially in cases involving multiple attributes and when the criteria for sorting frequently changes depending on the user's task. The proposed visual analytic system enables users to specify a sort requirement in a flexible manner without depending on specific knowledge about individual sort keys. The authors use regression techniques to train different analytical models for different types of sorting requirements and use visualization to facilitate knowledge discovery at different stages of the process. They demonstrate the system with a rugby case study to find key instances for analyzing team and player performance. Organizing sports video data for performance analysis can be challenging in cases with multiple attributes, and when sorting frequently changes depending on the user's task. As this video shows, the proposed visual analytic system allows interactive data sorting and exploration.https://youtu.be/Cs6SLtPVDQQ.
Caffeine does not inhibit substance P-evoked intracellular Ca2+ mobilization in rat salivary acinar cells.

We used the Ca2+-sensitive fluorescent dye fura 2, together with measurements of intracellulard- myo-inositol 1,4,5-trisphosphate [Ins(1,4,5) P 3], to assess the inhibitory effects of caffeine on signal transduction via G protein-coupled receptor pathways in isolated rat mandibular salivary acinar cells. ACh, norepinephrine (NE), and substance P (SP) all evoked substantial increases in the intracellular free Ca2+ concentration ([Ca2+]i). Responses to ACh and NE were markedly inhibited by prior application of 20 mM caffeine. The inhibitory effect of caffeine was not reproduced by phosphodiesterase inhibition with IBMX or addition of cell-permeant dibutyryl cAMP. In contrast to the ACh and NE responses, the [Ca2+]iresponse to SP was unaffected by caffeine. Despite this, SP and ACh appeared to mobilize Ca2+ from a common intracellular pool. Measurements of agonist-induced changes in Ins(1,4,5) P 3levels confirmed that caffeine inhibited the stimulus-response coupling pathway at a point before Ins(1,4,5) P 3generation. Caffeine did not, however, inhibit [Ca2+]iresponses evoked by direct activation of G proteins with 40 mM F-. These data show that caffeine inhibits G protein-coupled signal transduction in these cells at some element that is common to the muscarinic and α-adrenergic signaling pathways but is not shared by the SP signaling pathway. We suggest that this element might be a specific structural motif on the G protein-coupled muscarinic and α-adrenergic receptors.
Topology- and error-driven extension of scalar functions from surfaces to volumes

The behavior of a variety of phenomena measurable on the boundary of 3D shapes is studied by modeling the set of known measurements as a scalar function f :P → R, defined on a surface P. Furthermore, the large amount of scientific data calls for efficient techniques to correlate, describe, and analyze this data. In this context, we focus on the problem of extending the measures captured by a scalar function f, defined on the boundary surface P of a 3D shape, to its surrounding volume. This goal is achieved by computing a sequence of volumetric functions that approximate f up to a specified accuracy and preserve its critical points. More precisely, we compute a smooth map g : R3 → R such that the piecewise linear function h :=gP : P → R, which interpolates the values of g at the vertices of the triangulated surface P, is an approximation of f with the same critical points. In this way, we overcome the limitation of traditional approaches to function approximation, which are mainly based on a numerical error estimation and do not provide measurements of the topological and geometric features of f. The proposed approximation scheme builds on the properties of f related to its global structure, that is, its critical points, and ignores the local details of f, which can be successively introduced according to the target approximation accuracy.
Full 3D navigation correction using low frequency visual tracking with a stereo camera

Robust and accurate navigation of underwater vehicles is an essential cornerstone for mission success. Integrative techniques, e.g., using inertial navigation or Doppler velocity logs (DVL), can show significant drift. Even absolute input, such as GNSS input or magnetometers, can either be biased by surrounding structures or very noisy. For good navigation performance in critical maneuvers close to underwater structures like sea mounts, cliffs or man-made constructions where DVLs fail, navigation based on visual input can be very helpful. This paper presents a technique to correct a traditional navigation solution with visual tracking feedback from a stereo camera with small computational overhead. Experiments with real data from an ATLAS SeaCat AUV shows very good navigation performance on two trajectories over a variety of 3D structures.
Reverse polarization switching in ferroelectric lead zirconate titanate (PZT) thin films

The effect of shear stress on polarization retention in ferroelectric thin films was assessed using a nonlinear finite element phase field model. It is shown that reverse switching can occur when tetragonal phase films are grown in the <111> orientation. The effect of a substrate and a top electrode are modeled by applying rigid constraints and shear loads to the finite element phase field model to predict the evolution of ferroelectric domain structures. The residual shear stress in the film is shown to increase when the film is rigidly clamped to a substrate. When shear stress is applied to the top surface of the thin film model, 90° domain walls move in the direction of shear loading. Model predictions are found to qualitatively correlate with piezoelectric response microscopy experiments given in the literature.
A framework for evolutionary optimization with approximate fitness functions

It is not unusual that an approximate model is needed for fitness evaluation in evolutionary computation. In this case, the convergence properties of the evolutionary algorithm are unclear due to the approximation error of the model. In this paper, extensive empirical studies are carried out to investigate the convergence properties of an evolution strategy using an approximate fitness function on two benchmark problems. It is found that incorrect convergence will occur if the approximate model has false optima. To address this problem, individual- and generation-based evolution control are introduced and the resulting effects on the convergence properties are presented. A framework for managing approximate models in generation-based evolution control is proposed. This framework is well suited for parallel evolutionary optimization, which is able to guarantee the correct convergence of the evolutionary algorithm, as well as to reduce the computation cost as much as possible. Control of the evolution and updating of the approximate models are based on the estimated fidelity of the approximate model. Numerical results are presented for three test problems and for an aerodynamic design example.
ERK activation protects against DNA damage and apoptosis in hyperoxic rat AEC2.

The survival of type 2 alveolar epithelial cells (AEC2) in the lung after hyperoxic injury is regulated by signals from the cellular environment. Keratinocyte growth factor and Matrigel can ameliorate the hallmarks of apoptosis seen in hyperoxic AEC2 after 24-h culture on plastic [S. Buckley, L. Barsky, B. Driscoll, K. Weinberg, K. D. Anderson, and D. Warburton. Am. J. Physiol. 274 ( Lung Cell. Mol. Physiol. 18): L714-L720, 1998]. We used the same model of in vivo short-term hyperoxia to characterize the protective effects of substrate attachment. Culture of hyperoxic AEC2 on various biological adhesion substrates showed reduced DNA end labeling in cells grown on all biological substrates compared with growth on plastic. In contrast, the synthetic substrate poly-d-lysine conferred no protection. Hyperoxic AEC2 cultured on laminin showed an increased ratio of expression of Bcl-2 to interleukin-1β-converting enzyme compared with culture on plastic. Laminin also partially restored hyperoxia-depleted glutathione levels and conferred improved optimal mitochondrial viability as measured by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Conversely, attachment to the nonphysiological substrate poly-d-lysine afforded no such protection, suggesting that protection against hyperoxia-induced damage may be associated with integrin signaling. Increased activation of extracellular signal-regulated kinase (ERK), as detected by increased ERK tyrosine phosphorylation, was seen in hyperoxic AEC2 as soon as the cells started to attach to laminin and was sustained after 24 h of culture in contrast to that in control AEC2. To confirm that protection against DNA strand breakage and apoptosis was being conferred by ERK activation, the cells were also plated in the presence of 50 μM PD-98059, an inhibitor of the ERK-activating mitogen-activating kinase. Culture for 24 h with PD-98059 abolished the protective effect of laminin. We speculate that after hyperoxic lung injury, signals through the basement membrane confer specific protection against oxygen-induced DNA strand breakage and apoptosis through an ERK activation-dependent pathway.