Ultrasonic enhancement of antibiotic action on several species of bacteria

Journal ArticleThe effect of the antibiotics gentamicin, streptomycin, kanamycin, tetracycline, and ampicillin on planktonic cultures of Enterobacter aerogenes, Serratia marcescens, Salmonella derby, Streptococcus mitis, and Staphylococcus epidermidis with and without an application of 70 kHz ultrasound was studied. The ultrasound was applied at levels that had no inhibitory effect on planktonic cultures of bacteria. Measurements of viability at, above, and below the minimum inhibitory concentration of the above antibiotics on the planktonic cultures of these bacteria showed that a simultaneous application of 70 kHz ultrasound and antibiotic significantly increased the effectiveness of selected antibiotics. Bacterial viability was reduced several orders of magnitude when harmless levels of ultrasound were combined with some antibiotics, especially the aminoglycosides. Similar synergistic effects of combined ultrasound and antibiotic treatment were seen in both Gram-positive and Gram-negative bacteria with several classes of antibiotics. These results may have application in the treatment of bacterial infections normally resistant to some antibiotics

Supporting active database learning and training through interactive multimedia

The learning objectives of a database course include aspects from conceptual and theoretical knowledge to practical development and implementation skills. We present an interactive educational multimedia system based on the virtual apprenticeship model for the knowledge- and skills-oriented Web-based education of database course students. Combining knowledge learning and skills training in an integrated environment is a central aspect of our system. We show that tool-mediated independent learning and training in an authentic setting is an alternative to traditional classroom-based approaches

Autophagy: A cyto-protective mechanism which prevents primary human hepatocyte apoptosis during oxidative stress

The role of autophagy in the response of human hepatocytes to oxidative stress remains unknown. Understanding this process may have important implications for the understanding of basic liver epithelial cell biology and the responses of hepatocytes during liver disease. To address this we isolated primary hepatocytes from human liver tissue and exposed them ex vivo to hypoxia and hypoxia-reoxygenation (H-R). We showed that oxidative stress increased hepatocyte autophagy in a reactive oxygen species (ROS) and class III PtdIns3K-dependent manner. Specifically, mitochondrial ROS and NADPH oxidase were found to be key regulators of autophagy. Autophagy involved the upregulation of BECN1, LC3A, Atg7, Atg5 and Atg 12 during hypoxia and H-R. Autophagy was seen to occur within the mitochondria of the hepatocyte and inhibition of autophagy resulted in the lowering a mitochondrial membrane potential and onset of cell death. Autophagic responses were primarily observed in the large peri-venular (PV) hepatocyte subpopulation. Inhibition of autophagy, using 3-methyladenine, increased apoptosis during H-R. Specifically, PV human hepatocytes were more susceptible to apoptosis after inhibition of autophagy. These findings show for the first time that during oxidative stress autophagy serves as a cell survival mechanism for primary human hepatocytes

Segmentation and modelling of hela nuclear envelope

This paper describes an algorithm to segment the 3D nuclear envelope of HeLa cancer cells from electron microscopy images and model the volumetric shape of the nuclear envelope against an ellipsoid. The algorithm was trained on a single cell and then tested in six separate cells. To assess the algorithm, Jaccard similarity index and Hausdorff distance against a manually-delineated gold standard were calculated on two cells. The mean Jaccard value and Hausdorff distance that the segmentation achieved for central slices were 98% and 4 pixels for the first cell and 94% and 13 pixels for the second cell and outperformed segmentation with active contours. The modelling projects a 3D to a 2D surface that summarises the complexity of the shape in an intuitive result. Measurements extracted from the modelled surface may be useful to correlate shape with biological characteristics. The algorithm is unsupervised, fully automatic, fast and processes one image in less than 10 seconds. Code and data are freely available at https://github.com/reyesaldasoro/Hela-Cell-Segmentation and http://dx.doi.org/10.6019/EMPIAR-10094

Semantic segmentation of HeLa cells: An objective comparison between one traditional algorithm and four deep-learning architectures

The quantitative study of cell morphology is of great importance as the structure and condition of cells and their structures can be related to conditions of health or disease. The first step towards that, is the accurate segmentation of cell structures. In this work, we compare five approaches, one traditional and four deep-learning, for the semantic segmentation of the nuclear envelope of cervical cancer cells commonly known as HeLa cells. Images of a HeLa cancer cell were semantically segmented with one traditional image-processing algorithm and four three deep learning architectures: VGG16, ResNet18, Inception-ResNet-v2, and U-Net. Three hundred slices, each 2000 × 2000 pixels, of a HeLa Cell were acquired with Serial Block Face Scanning Electron Microscopy. The first three deep learning architectures were pre-trained with ImageNet and then fine-tuned with transfer learning. The U-Net architecture was trained from scratch with 36, 000 training images and labels of size 128 × 128. The image-processing algorithm followed a pipeline of several traditional steps like edge detection, dilation and morphological operators. The algorithms were compared by measuring pixel-based segmentation accuracy and Jaccard index against a labelled ground truth. The results indicated a superior performance of the traditional algorithm (Accuracy = 99%, Jaccard = 93%) over the deep learning architectures: VGG16 (93%, 90%), ResNet18 (94%, 88%), Inception-ResNet-v2 (94%, 89%), and U-Net (92%, 56%)

A programming environment for distributed complex computing. An overview of the Framework for Interdisciplinary Design Optimization (FIDO) project. NASA Langley TOPS exhibit H120b

The Framework for Interdisciplinary Design Optimization (FIDO) is a general programming environment for automating the distribution of complex computing tasks over a networked system of heterogeneous computers. For example, instead of manually passing a complex design problem between its diverse specialty disciplines, the FIDO system provides for automatic interactions between the discipline tasks and facilitates their communications. The FIDO system networks all the computers involved into a distributed heterogeneous computing system, so they have access to centralized data and can work on their parts of the total computation simultaneously in parallel whenever possible. Thus, each computational task can be done by the most appropriate computer. Results can be viewed as they are produced and variables changed manually for steering the process. The software is modular in order to ease migration to new problems: different codes can be substituted for each of the current code modules with little or no effect on the others. The potential for commercial use of FIDO rests in the capability it provides for automatically coordinating diverse computations on a networked system of workstations and computers. For example, FIDO could provide the coordination required for the design of vehicles or electronics or for modeling complex systems

The effect of match standard and referee experience on the objective and subjective match workload of English Premier League referees

The aim of the present study was to examine the effect of match standard and referee experience upon the objective and subjective workload of referees during Premier and Football league soccer matches. We also examined the relationship between heart rate (HR) and ratings of perceived exertion (RPE) for assessing match intensity in soccer referees. Heart rate responses were recorded using short-range telemetry and RPE scores were collected using a 10-point scale. Analysis revealed a significant relationship between mean match HR and match RPE scores (r = 0.485, p < 0.05, n =18). There were significant differences in match HR (Premier league 83.6 2.6 %HRmax vs. Football league 81.5 2.2 %HRmax, p < 0.05) and match RPE scores (Premier league 7.8 0.8 vs. Football league 6.9 0.8, p < 0.05) between standards of competition. Referee experience had no effect upon match heart rate and RPE responses to Premier and Football league matches. The results of the present study demonstrate the validity of using HR and RPE as a measure of global match intensity in soccer referees. Referee experience had no effect upon the referees’ objective and subjective match workload assessments, whereas match intensity was correlated to competition standard. These findings have implications for fitness preparation and evaluation in soccer referees. When progressing to a higher level of competition, referees should ensure that appropriate levels of fitness are developed in order to enable them to cope with an increase in physical match demands