Genotypes and antibiotic resistances of Campylobacter jejuni and Campylobacter coli isolates from domestic and travel-associated human cases

Multilocus sequence typing (MLST) extended with flaB typing of 425 Campylobacter jejuni isolates and 42 Campylobacter coli isolates revealed quite a low overlap between human isolates from travel-associated and domestic cases in Switzerland. Men were more frequently affected by Campylobacter than women, but strains from women and, overall, from travel-associated cases showed mutations conferring quinolone resistance more frequently than strains from men and domestic cases, respectively.

Description and repeatability of a newly developed spinal cord injury scale for dogs.

The objectives of this study were to describe a new spinal cord injury scale for dogs, evaluate repeatability through determining inter-rater variability of scores, compare these scores to another established system (a modified Frankel scale), and determine if the modified Frankel scale and the newly developed scale were useful as prognostic indicators for return to ambulation. A group of client-owned dogs with spinal cord injury were examined by 2 independent observers who applied the new Texas Spinal Cord Injury Score (TSCIS) and a modified Frankel scale that has been used previously. The newly developed scale was designed to describe gait, postural reactions and nociception in each limb. Weighted kappa statistics were utilized to determine inter-rater variability for the modified Frankel scale and individual components of the TSCIS. Comparisons were made between raters for the overall TSCIS score and between scales using Spearman's rho. An additional group of dogs with surgically treated thoracolumbar disk herniation was enrolled to look at correlation of both scores with spinal cord signal characteristics on magnetic resonance imaging (MRI) and ambulatory outcome at discharge. The actual agreement between raters for the modified Frankel scale was 88%, with a weighted kappa value of 0.93. The TSCIS had weighted kappa scores for gait, proprioceptive positioning and nociception components that ranged from 0.72 to 0.94. Correlation between raters for the overall TSCIS score was Spearman's rho=0.99 (P<0.001). Comparison of the overall TSCIS score to the modified Frankel score resulted in a Spearman's rho value of 0.90 (P<0.001). The modified Frankel score was weakly correlated with the length of hyperintensity of the spinal cord: L2 vertebral body length ratio on mid-sagittal T2-weighted MRI (Spearman's rho=-0.45, P=0.042) as was the overall TSCIS score (Spearman's rho=-0.47, P=0.037). There was also a significant difference in admitting modified Frankel scores (P=0.029) and admitting overall TSCIS scores (P=0.02) between dogs that were ambulatory at discharge and those that were not. Results from this study suggest that the TSCIS is an easy to administer scale for evaluating canine spinal cord injury based on the standard neurological exam and correlates well with a previously described modified Frankel scale.

Mobility and Bandwidth Prediction as a Service in Virtualized LTE Systems

Recently telecommunication industry benefits from infrastructure sharing, one of the most fundamental enablers of cloud computing, leading to emergence of the Mobile Virtual Network Operator (MVNO) concept. The most momentous intents by this approach are the support of on-demand provisioning and elasticity of virtualized mobile network components, based on data traffic load. To realize it, during operation and management procedures, the virtualized services need be triggered in order to scale-up/down or scale-out/in an instance. In this paper we propose an architecture called MOBaaS (Mobility and Bandwidth Availability Prediction as a Service), comprising two algorithms in order to predict user(s) mobility and network link bandwidth availability, that can be implemented in cloud based mobile network structure and can be used as a support service by any other virtualized mobile network services. MOBaaS can provide prediction information in order to generate required triggers for on-demand deploying, provisioning, disposing of virtualized network components. This information can be used for self-adaptation procedures and optimal network function configuration during run-time operation, as well. Through the preliminary experiments with the prototype implementation on the OpenStack platform, we evaluated and confirmed the feasibility and the effectiveness of the prediction algorithms and the proposed architecture.