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Introduction: Endothelial cells (ECs), being located at the interface between flowing blood and vessel wall, maintain cardiovascular homeostasis by virtue of their ability to integrate chemical and physical cues through a spatio-temporally coordinated increase in their intracellular Ca2+ concentration ([Ca2+]i). Endothelial heterogeneity suggests the existence of spatially distributed functional clusters of ECs that display different patterns of intracellular Ca2+ response to extracellular inputs. Characterizing the overall Ca2+ activity of the endothelial monolayer in situ requires the meticulous analysis of hundreds of ECs. This complex analysis consists in detecting and quantifying the true Ca2+ events associated to extracellular stimulation and classifying their intracellular Ca2+ profiles (ICPs). The injury assay technique allows exploring the Ca2+-dependent molecular mechanisms involved in angiogenesis and endothelial regeneration. However, there are true Ca2+ events of nearly undetectable magnitude that are almost comparable with inherent instrumental noise. Moreover, undesirable artifacts added to the signal by mechanical injury stimulation complicate the analysis of intracellular Ca2+ activity. In general, the study of ICPs lacks uniform criteria and reliable approaches for assessing these highly heterogeneous spatial and temporal events. Methods: Herein, we present an approach to classify ICPs that consists in three stages: 1) identification of Ca2+ candidate events through thresholding of a feature termed left-prominence; 2) identification of non-true events, known as artifacts; and 3) ICP classification based upon event temporal location. Results: The performance assessment of true-events identification showed competitive sensitivity = [0.9995, 0.9831], specificity = [0.9946, 0.7818] and accuracy = [0.9978, 0.9579] improvements of 2x and 14x, respectively, compared with other methods. The ICP classifier enhanced by artifact detection showed 0.9252 average accuracy with the ground-truth sets provided for validation. Discussion: Results indicate that our approach ensures sturdiness to experimental protocol maneuvers, besides it is effective, simple, and configurable for different studies that use unidimensional time dependent signals as data. Furthermore, our approach would also be effective to analyze the ICPs generated by other cell types, other dyes, chemical stimulation or even signals recorded at higher frequency.

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Introduction. The use of automated systems in identification and susceptibility tests can improve antimicrobial therapy, and positively impact clinical outcomes with a decrease in antimicrobial resistance, hospitalization time, costs, and mortality.Aim. The aim of this study was to evaluate the clinical impact of an automated method for identification and susceptibility testing of microbial isolates.Methodology. This was a retrospective cross-sectional study aimed to analyse the results before and after the implementation period of a VITEK 2 system in a Brazilian university hospital. Based on data from medical records, patients with a positive culture of clinical samples from January to July 2017 (conventional method) and from August to December 2017 (automated method) were included in this study. Demographic data, hospitalization time, time interval between culture collection and results, culture results and site, susceptibility profile, minimum inhibitory concentration, and outcome data were evaluated. Chi-square and Fischer's tests were used in the analysis.Results. Of the total samples, 836 were considered valid by the inclusion criteria, with 219 patients before VITEK 2 system implementation group and 545 in the post-implementation group. The comparison between the two periods showed a reduction of 25 % of the time to culture reports, a decrease of 33.5 to 17.0 days of hospitalization, and a reduction in mortality from 44.3-31.0 %, respectively.Conclusion. The VITEK 2 system provided early access to appropriate antimicrobial therapy for patients and effected a positive clinical impact with a reduction in mortality and hospitalization time.

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Most tissue banks use the conventional method; however, the automated method has advantages over the conventional method. The aim of this study was to compare the conventional and automated methods of culture in human cardiac tissue using an artificial contamination model. Myocardial samples were contaminated with sequential concentration (104 to 10-1 CFU/mL) with Pseudomonas aeruginosa, Escherichia coli, Staphylococcus aureus and Candida albicans. Cultures were obtained from solution were the fragment was immersed and minced tissue, before and after the routine decellularization solution, with automated and conventional culture methods. Automated and conventional methods were compared and a p value ≤ 0.05 was considered significant. Staphylococcus aureus presented a significantly higher growth in the automated method, as well as faster than the conventional (p < 0.05). The positivity for growth in the automated method was higher in concentrated inoculum (> 102 CFU/mL) (p < 0.05). The growth in the automated method was significantly faster than conventional when inoculum concentration was above 103 CFU/mL. The automated culture method is faster than conventional method with a higher positivity in a contaminated model of myocardial and transport solution used in tissue banks.

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BACKGROUND AND AIM: The measurement of carotid intima-media thickness (cIMT) has been used as a marker of arterial wall disease. Manual measurements have been performed in most epidemiological studies, but, due to the introduction of new technologies, automated software has been increasingly used. This study aimed to compare manual versus automated cIMT measurements in common carotid (CC), bifurcation (BIF), and internal carotid (IC). METHODS: Automated and manual cIMT measurements were performed online in 43 middle-aged females. Carotid segment measurements were compared by Bland-Altman plot and the variation and repeatability coefficients between observers were also determined for comparison. RESULTS: The average timespan for manual measurements (57.30 s) were significantly higher than for automated measurements (2.52 s). There were no systematic errors between methods in any carotid segments. The variation coefficient was 5.54% to 6.34% for CC and BIF, 9.76% for IC, and absolute differences were 85% below 0.1 mm and 70% below 0.05 mm. Interobserver agreement showed no systematic error. The variation and the repeatability coefficients were better for the automated than manual measures. CONCLUSION: Although both methods are reliable for cIMT measurements, the automated technique allows faster evaluation with lesser variability for all carotid segments currently used in atherosclerosis research.

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