Comparison between single-beat and multiple-beat methods for estimation of right ventricular contractility.

OBJECTIVE: It was investigated whether pharmacologically induced changes in right ventricular contractility can be detected by a so-called "single-beat" method that does not require preload reduction. DESIGN: Prospective animal research. SETTING: Laboratory at a large university medical center. SUBJECTS: Eight anesthetized pigs. INTERVENTIONS: End-systolic elastance values obtained by a recently proposed single-beat method (Eessb) were compared with those obtained using the reference multiple-beat method (Eesmb). MEASUREMENTS AND MAIN RESULTS: Administration of dobutamine increased Eesmb from 1.6 +/- 0.3 to 3.8 +/- 0.5 mm Hg/mL (p =.001), whereas there was only a trend toward an increase in Eessb from 1.5 +/- 0.2 to 1.7 +/- 0.4 mm Hg/mL. Esmolol decreased Eesmb from 1.7 +/- 0.3 to 1.1 +/- 0.2 mm Hg/mL (p =.006), whereas there was only a trend for a decrease in Eessb from 1.5 +/- 0.2 to 1.3 +/- 0.1. CONCLUSIONS: The present method using single-beat estimation to assess right ventricular contractility does not work as expected, since it failed to detect either increases or decreases in right ventricular contractility induced by pharmacologic interventions.Peer reviewe

Pharmacological Characterization of N-tert-Butyl-NЈ-[2-(4Ј- methylphenylamino)-5-nitrobenzenesulfonyl]urea (BM-573), a Novel Thromboxane A 2 Receptor Antagonist and Thromboxane Synthase Inhibitor in a Rat Model of Arterial Thrombosis and Its Effects on Bl

ABSTRACT The present study was undertaken to characterize the antiplatelet and antithrombotic effects of BM-573 [N-tert-butyl-NЈ-[2-(4Ј-methylphenylamino)-5-nitrobenzenesulfonyl]urea], an original combined thromboxane receptor antagonist and thromboxane synthase inhibitor in rats, and to determine its effects on mice bleeding time. Intraperitoneal injection of a single dose of 5 mg/kg BM-573 to rats inhibited U-46619 (9,11-dideoxy-9,11-methanoepoxy-prostaglandin F 2 )-induced washed platelet aggregation 30 min and 1, 2, and 4 h after drug administration with a maximum antiplatelet effect observed after 1 and 2 h. In a rat model of thrombosis induced by ferric chloride application on the abdominal aorta, BM-573 significantly reduced the thrombus weight by 92.53, 80.20, 64.75, and 18.21% at doses of 5, 2, 0.5, and 0.2 mg/kg, respectively. Time to occlusion of abdominal aorta in the BM-573-treated group (41.50 Ϯ 5.21 min) was significantly prolonged compared with the vehicle-treated rats (16.16 Ϯ 0.79 min). Like furegrelate, seratrodast, and acetylsalicylic acid, BM-573 did not affect the tail bleeding time induced by tail transection in mice compared with vehicle-treated mice. Moreover, BM-573, a close derivative of the loop diuretic torasemide, failed to induce a significant increase in diuresis in rat and did not produce a decrease in blood glucose concentration as observed with the sulfonylurea glibenclamide. In conclusion, we have demonstrated that the nitrobenzenic sulfonylurea BM-573, an original combined thromboxane receptor antagonist and thromboxane synthase inhibitor, is a potent antithrombotic agent that does not affect bleeding time. Moreover, BM-573 lost the diuretic property of torasemide and has no impact on glycemia. The isozymes cyclooxygenase (COX)-1 and -2 catalyze the conversion of arachidonic acid into thromboxane A 2 (TXA 2 ) and prostaglandins (PGs). The eicosanoid TXA 2 is the major COX-1 product of arachidonic acid metabolism in platelets

Investigating the relations between motivation, tool use, participation, and performance in an e-learning course using web-videoconferencing

Web-videoconference systems offer several tools (like chat, audio, and webcam) that vary in the amount and type of information learners can share with each other and the teacher. It has been proposed that tools fostering more direct social interaction and feedback amongst learners and teachers would foster higher levels of engagement. If so, one would expect that the richer the tools used, the higher the levels of learner engagement. However, the actual use of tools and contributions to interactions in the learning situation may relate to students’ motivation. Therefore, we investigated the relationship between available tools used, student motivation, participation, and performance on a final exam in an online course in economics (N = 110). In line with our assumptions, we found some support for the expected association between autonomous motivation and participation in web-videoconferences as well as between autonomous motivation and the grade on the final exam. Students’ tool use and participation were significantly correlated with each other and with exam scores, but participation appeared to be a stronger predictor of the final exam score than tool use. This study adds to the knowledge base needed to develop guidelines on how synchronous communication in e-learning can be used

Modeling methane fluxes in wetlands with gas-transporting plants. 3. Plot scale.

A process model based on kinetic principles was developed for methane fluxes from wetlands with gas-transporting plants and a fluctuating water table. Water dynamics are modeled with the 1-D Richards equation. For temperature a standard diffusion equation is used. The depth-dependent dynamics of methane, oxygen, molecular nitrogen, carbon dioxide, soil carbon, electron acceptors in oxidized and in reduced form are affected by transport processes and kinetic processes. Modeled transport processes are convection and diffusion in the soil matrix, ebullition, and plant-mediated gas transport. Modeled kinetic processes are carbon mineralization, aerobic respiration, methane production, methane oxidation, electron acceptor reduction, and electron acceptor reoxidation. Concentration gradients around gas-transporting roots in water-saturated soil are accounted for by the models from the two previous papers, ensuring an explicit connection between process knowledge at the kinetic level (millimeter scale) and methane fluxes at the plot scale. We applied the model to a fen, and without any fitting, simulated methane fluxes are within 1 order of magnitude of measured methane fluxes. The seasonal variations however, are much weaker in the simulations compared to the measurements. Simulated methane fluxes are sensitive to several uncertain parameters such as the distribution over depth of carbon mineralization, the total pool size of reduced and oxidized electron acceptors, and the root-shoot ratio. Because of the process-based character of the model it is probable that these sensitivities are present in reality as well, which explains why the measured variability is usually very high. Interestingly, heterogeneities within a rooted soil layer seem to be less important than heterogeneities between different soil layers. This is due to the strong influence of the interaction between water table and profile scale processes on the oxygen input to the system and hence on net methane production. Other existing process models are discussed and compared with the presented model

Pengaruh Brand Trust dan Brand Equity terhadap Loyalitas Konsumen pada Produk Kosmetik Wardah (Survey Konsumen pada PT. Paragon Technology And Innovation Cabang Pekanbaru)

The purpose of this study was to determine the influence of brand trust ( X1 ) and brand equity ( X2 ) customer loyalty ( Y ) in cosmetic products Wardah ( consumer survey on PT . Paragon technology and innovation branches pekanbaru ) . The method in this research is quantitatively using SPSS 21 program , where samples were used that consumers using cosmetic products Wardah by respondents as many as 100 people sampling technique is accidental sampling using the formula slovin . The results showed that the test results simultaneously obtained from the F count was 34.888 while the value of F table 3.090 . This means that F count> F table and significant value 0,000 < alpha of 0.05 . This means that brand trust and brand equity simultaneously significant effect on consumer loyalty to cosmetic products Wardah

Brain age as a biomarker for pathological versus healthy ageing – a REMEMBER study

Objectives: This study aimed to evaluate the potential clinical value of a new brain age prediction model as a single interpretable variable representing the condition of our brain. Among many clinical use cases, brain age could be a novel outcome measure to assess the preventive effect of life-style interventions. Methods: The REMEMBER study population (N = 742) consisted of cognitively healthy (HC,N = 91), subjective cognitive decline (SCD,N = 65), mild cognitive impairment (MCI,N = 319) and AD dementia (ADD,N = 267) subjects. Automated brain volumetry of global, cortical, and subcortical brain structures computed by the CE-labeled and FDA-cleared software icobrain dm (dementia) was retrospectively extracted from T1-weighted MRI sequences that were acquired during clinical routine at participating memory clinics from the Belgian Dementia Council. The volumetric features, along with sex, were combined into a weighted sum using a linear model, and were used to predict ‘brain age’ and ‘brain predicted age difference’ (BPAD = brain age–chronological age) for every subject. Results: MCI and ADD patients showed an increased brain age compared to their chronological age. Overall, brain age outperformed BPAD and chronological age in terms of classification accuracy across the AD spectrum. There was a weak-to-moderate correlation between total MMSE score and both brain age (r = -0.38,p < .001) and BPAD (r = -0.26,p < .001). Noticeable trends, but no significant correlations, were found between BPAD and incidence of conversion from MCI to ADD, nor between BPAD and conversion time from MCI to ADD. BPAD was increased in heavy alcohol drinkers compared to non-/sporadic (p = .014) and moderate (p = .040) drinkers. Conclusions: Brain age and associated BPAD have the potential to serve as indicators for, and to evaluate the impact of lifestyle modifications or interventions on, brain health

Injectable Materials for the Treatment of Myocardial Infarction and Heart Failure: The Promise of Decellularized Matrices

Cardiovascular disease continues to be the leading cause of death, suggesting that new therapies are needed to treat the progression of heart failure post-myocardial infarction. As cardiac tissue has a limited ability to regenerate itself, experimental biomaterial therapies have focused on the replacement of necrotic cardiomyocytes and repair of the damaged extracellular matrix. While acellular and cellular cardiac patches are applied surgically to the epicardial surface of the heart, injectable materials offer the prospective advantage of minimally invasive delivery directly into the myocardium to either replace the damaged extracellular matrix or to act as a scaffold for cell delivery. Cardiac-specific decellularized matrices offer the further advantage of being biomimetic of the native biochemical and structural matrix composition, as well as the potential to be autologous therapies. This review will focus on the requirements of an ideal scaffold for catheter-based delivery as well as highlight the promise of decellularized matrices as injectable materials for cardiac repair

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery