35 resultados para Linear correlation


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Cerebral electrical activity is highly nonstationary because the brain reacts to ever changing external stimuli and continuously monitors internal control circuits. However, a large amount of energy is spent to maintain remarkably stationary activity patterns and functional inter-relations between different brain regions. Here we examine linear EEG correlations in the peri-ictal transition of focal onset seizures, which are typically understood to be manifestations of dramatically changing inter-relations. Contrary to expectations we find stable correlation patterns with a high similarity across different patients and different frequency bands. This skeleton of spatial correlations may be interpreted as a signature of standing waves of electrical brain activity constituting a dynamical ground state. Such a state could promote the formation of spatiotemporal neuronal assemblies and may be important for the integration of information stemming from different local circuits of the functional brain network.

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INTRODUCTION The aim of this study was to determine the reproducibility and accuracy of linear measurements on 2 types of dental models derived from cone-beam computed tomography (CBCT) scans: CBCT images, and Anatomodels (InVivoDental, San Jose, Calif); these were compared with digital models generated from dental impressions (Digimodels; Orthoproof, Nieuwegein, The Netherlands). The Digimodels were used as the reference standard. METHODS The 3 types of digital models were made from 10 subjects. Four examiners repeated 37 linear tooth and arch measurements 10 times. Paired t tests and the intraclass correlation coefficient were performed to determine the reproducibility and accuracy of the measurements. RESULTS The CBCT images showed significantly smaller intraclass correlation coefficient values and larger duplicate measurement errors compared with the corresponding values for Digimodels and Anatomodels. The average difference between measurements on CBCT images and Digimodels ranged from -0.4 to 1.65 mm, with limits of agreement values up to 1.3 mm for crown-width measurements. The average difference between Anatomodels and Digimodels ranged from -0.42 to 0.84 mm with limits of agreement values up to 1.65 mm. CONCLUSIONS Statistically significant differences between measurements on Digimodels and Anatomodels, and between Digimodels and CBCT images, were found. Although the mean differences might be clinically acceptable, the random errors were relatively large compared with corresponding measurements reported in the literature for both Anatomodels and CBCT images, and might be clinically important. Therefore, with the CBCT settings used in this study, measurements made directly on CBCT images and Anatomodels are not as accurate as measurements on Digimodels.

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One key problem in modern medical imaging is linking measured data and actual physiological quantities. In this article we derive such a link between the electrical bioimpedance of lung parenchyma, which can be measured by electrical impedance tomography (EIT), and the magnitude of regional ventilation, a key to understanding lung mechanics and developing novel protective ventilation strategies. Two rat-derived three-dimensional alveolar microstructures obtained from synchrotron-based x-ray tomography are each exposed to a constant potential difference for different states of ventilation in a finite element simulation. While the alveolar wall volume remains constant during stretch, the enclosed air volume varies, similar to the lung volume during ventilation. The enclosed air, serving as insulator in the alveolar ensemble, determines the resulting current and accordingly local tissue bioimpedance. From this we can derive a relationship between lung tissue bioimpedance and regional alveolar ventilation. The derived relationship shows a linear dependence between air content and tissue impedance and matches clinical data determined from a ventilated patient at the bedside.

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There is a growing concern by regulatory authorities for the selection of antibiotic resistance caused by the use of biocidal products. We aimed to complete the detailed information on large surveys by investigating the relationship between biocide and antibiotic susceptibility profiles of a large number of Staphylococcus aureus isolates using four biocides and antibiotics commonly used in clinical practice. The minimal inhibitory concentration (MIC) for most clinically-relevant antibiotics was determined according to the standardized methodology for over 1600 clinical S. aureus isolates and compared to susceptibility profiles of benzalkonium chloride, chlorhexidine, triclosan, and sodium hypochlorite. The relationship between antibiotic and biocide susceptibility profiles was evaluated using non-linear correlations. The main outcome evidenced was an absence of any strong or moderate statistically significant correlation when susceptibilities of either triclosan or sodium hypochlorite were compared for any of the tested antibiotics. On the other hand, correlation coefficients for MICs of benzalkonium chloride and chlorhexidine were calculated above 0.4 for susceptibility to quinolones, beta-lactams, and also macrolides. Our data do not support any selective pressure for association between biocides and antibiotics resistance and furthermore do not allow for a defined risk evaluation for some of the compounds. Importantly, our data clearly indicate that there does not involve any risk of selection for antibiotic resistance for the compounds triclosan and sodium hypochlorite. These data hence infer that biocide selection for antibiotic resistance has had so far a less significant impact than feared.

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The thickness of 210 A1 pulleys of 21 male and female healthy volunteers in two different age groups (20-35 y and 50-70 y) were measured by ultrasound. In a second group, the thickness of 15 diseased A1 pulleys and 15 A1 pulleys of the corresponding other hand of 10 patients with the clinical diagnosis of trigger finger were measured by ultrasound. During open trigger finger release, a strip of A1 pulley was excised and immediately measured using an electronic caliper. The average pulley thickness of healthy volunteers was 0.43-0.47 mm, compared to 0.77-0.79 mm in patients with trigger finger. Based on the receiver operating characteristic (ROC) curve, a diagnostic cut-off value of the pulley thickness at 0.62 mm was defined in order to differ a trigger finger from a healthy finger (sensitivity and specificity of 85%). The correlation between sonographic and effective intra-operative measurements of pulley thickness was linear and very strong (Pearson coefficient 0.86-0.90). In order to distinguish between healthy and diseased A1 pulleys, 0.62 mm is a simple value to use, which can be applied regardless of age, sex, body mass index (BMI) and height in adults.