TERMINATING REPLICATION AT TERS AT EUKARYOTIC CHROMOSOMES

Faithful transmission of genetic material is challenged by the presence of natural impediments affecting replication fork progression that jeopardize genome integrity. Transcription, which competes with DNA replication for the same template, is a common barrier to replication in both prokaryotes and higher eukaryotes. Multiple mechanisms minimize the consequences of DNA replication and transcription collisions in order to prevent torsional stress accumulation that occurs when replication fork encounters the transcription machinery. Defects in resolving topological problems during chromosome replication lead to fork reversal, R loop formation and recombination-induced genome rearrangements. Our interest is focused on the processes that coordinate replication with transcription at TERs (termination sites) and on the molecular pathways involved in termination of DNA replication. We investigated the roles of Rrm3, a DNA helicase that assists replication fork progression, and of Sen1, a DNA/RNA helicase that resolves the conflicts between replication and transcription. We found that Rrm3 and Sen1 mediate replication termination at specific TERs, preventing aberrant events ultimately leading to chromosome fragility. Our results contribute to the elucidation of mechanisms coordinating replication and transcription at TER zones in eukaryotes

Controlled Release of Vancomycin and Tigecycline from an Orthopaedic Implant Coating Prevents Staphylococcus aureus Infection in an Open Fracture Animal Model.

Introduction:Treatment of open fractures routinely involves multiple surgeries and delayed definitive fracture fixation because of concern for infection. If implants were made less susceptible to infection, a one-stage procedure with intramedullary nailing would be more feasible, which would reduce morbidity and improve outcomes. Methods:In this study, a novel open fracture mouse model was developed using Staphylococcus aureus (S. aureus) and single-stage intramedullary fixation. The model was used to evaluate whether implants coated with a novel "smart" polymer coating containing vancomycin or tigecycline would be colonized by bacteria in an open fracture model infected with S. aureus. In vivo bioluminescence, ex vivo CFUs, and X-ray images were evaluated over a 42-day postoperative period. Results:We found evidence of a markedly decreased bacterial burden with the local release of vancomycin and tigecycline from the PEG-PPS polymer compared to polymer alone. Vancomycin was released in a controlled fashion and maintained local drug concentrations above the minimum inhibition concentration for S. aureus for greater than 7 days postoperatively. Bacteria were reduced 139-fold from implants containing vancomycin and undetected from the bone and soft tissue. Tigecycline coatings led to a 5991-fold reduction in bacteria isolated from bone and soft tissue and 15-fold reduction on the implants compared to polymer alone. Antibiotic coatings also prevented osteomyelitis and implant loosening as observed on X-ray. Conclusion:Vancomycin and tigecycline can be encapsulated in a polymer coating and released over time to maintain therapeutic levels during the perioperative period. Our results suggest that antibiotic coatings can be used to prevent implant infection and osteomyelitis in the setting of open fracture. This novel open fracture mouse model can be used as a powerful in vivo preclinical tool to evaluate and optimize the treatment of open fractures before further studies in humans

Infering Air Quality from Traffic Data using Transferable Neural Network Models

This work presents a neural network based model for inferring air quality from traffic measurements. It is important to obtain information on air quality in urban environments in order to meet legislative and policy requirements. Measurement equipment tends to be expensive to purchase and maintain. Therefore, a model based approach capable of accurate determination of pollution levels is highly beneficial. The objective of this study was to develop a neural network model to accurately infer pollution levels from existing data sources in Leicester, UK. Neural Networks are models made of several highly interconnected processing elements. These elements process information by their dynamic state response to inputs. Problems which were not solvable by traditional algorithmic approaches frequently can be solved using neural networks. This paper shows that using a simple neural network with traffic and meteorological data as inputs, the air quality can be estimated with a good level of generalisation and in near real-time. By applying these models to links rather than nodes, this methodology can directly be used to inform traffic engineers and direct traffic management decisions towards enhancing local air quality and traffic management simultaneously.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

A demonstration of monitoring and measuring data centers for energy efficiency using opensource tools

Data centers are complex systems that require sophisticated operational management approaches to provide the availability of digital services against the backdrop of cost and energy efficiency. To achieve this, data center telemetry data is required since, as is commonly said it is not possible to manage what cannot be measured. This paper details how it is possible to construct the key data center infrastructure management (DCIM) elements of monitoring and measuring by a combination of available opensource software tools that permit both scalability and an environment where analytics can be employed on the data center operation, which can offer relevant insight into energy efficient operational practices

Breathlessness and presentation to the emergency department : a survey and clinical record review

BACKGROUND: Breathlessness is a frequently occurring symptom of cardiorespiratory conditions and is a common cause of emergency department presentation. The aim of this study was to estimate the prevalence of acute-on-chronic breathlessness as a cause for presentation to the major emergencies area of the emergency department. METHODS: A prospective patient self-report survey and clinical record review of consecutive attendees to the major emergencies area of the emergency department in a single tertiary hospital between 12/5/14 and 29/5/14 was conducted. Eligible patients were clinically stable and had mental capacity to provide data. RESULTS: There were 2,041 presentations during the study period, of whom 1,345 (66%) were eligible. There was a 90% survey response rate (1,212/1,345); 424/1,212 (35%) self-reported breathlessness most days over the past month of whom 245 gave breathlessness as a reason for this presentation. Therefore, the prevalence of acute-on-chronic breathlessness as a reason to present to the major emergencies area was 20.2% (245/1,212, 95% CI 17.9% to 22.5%). During this period there were 4,692 major and minor presentations; breathlessness was therefore a cause of at least 5.2% (245/4,692, 95% CI 4.6 to 5.9%) of all emergency department presentations. CONCLUSIONS: This study found that one in five ambulance presentations to the ED were due to acute-on-chronic breathlessness. Most patients had non-malignant underlying conditions, had experienced considerable breathlessness for an extended period, had discussed breathlessness with their GP and presented out of daytime hours. Others were often involved in their decision to present. This represents clinically significant burden for patients, their family carers and the emergency health services

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Estimation of PM10-bound As, Cd, Ni and Pb levels by means of statistical modelling: PLSR and ANN approaches

Air quality assessment regarding metals and metalloids using experimental measurements is expensive and time consuming due to the cost and time required for the analytical determination of the levels of these pollutants. According to the European Union (EU) Air Quality Framework Directive (Directive 2008/50/EC), other alternatives, such as objective estimation techniques, can be considered for ambient air quality assessment in zones and agglomerations where the level of pollutants is below a certain concentration value known as the lower assessment threshold. These conditions occur in urban areas in Cantabria (northern Spain). This work aims to estimate the levels of As, Cd, Ni and Pb in airborne PM10 at two urban sites in the Cantabria region (Castro Urdiales and Reinosa) using statistical models as objective estimation techniques. These models were developed based on three different approaches: partial least squares regression (PLSR), artificial neural networks (ANNs) and an alternative approach consisting of principal component analysis (PCA) coupled with ANNs (PCA-ANN). Additionally, these models were externally validated using previously unseen data. The results show that the models developed in this work based on PLSR and ANNs fulfil the EU uncertainty requirements for objective estimation techniques and provide an acceptable estimation of the mean values. As a consequence, they could be considered as an alternative to experimental measurements for air quality assessment regarding the aforementioned pollutants in the study areas while saving time and resources.The authors gratefully acknowledge the financial support from the Spanish Ministry of Economy and Competitiveness through the Project CMT2010-16068. The authors also thank the Regional Environment Ministry of the Cantabria Government for providing the PM10 samples at the Castro Urdiales and Reinosa sites

Health System Resource Gaps and Associated Mortality from Pandemic Influenza across Six Asian Territories

BACKGROUND: Southeast Asia has been the focus of considerable investment in pandemic influenza preparedness. Given the wide variation in socio-economic conditions, health system capacity across the region is likely to impact to varying degrees on pandemic mitigation operations. We aimed to estimate and compare the resource gaps, and potential mortalities associated with those gaps, for responding to pandemic influenza within and between six territories in Asia. METHODS AND FINDINGS: We collected health system resource data from Cambodia, Indonesia (Jakarta and Bali), Lao PDR, Taiwan, Thailand and Vietnam. We applied a mathematical transmission model to simulate a "mild-to-moderate" pandemic influenza scenario to estimate resource needs, gaps, and attributable mortalities at province level within each territory. The results show that wide variations exist in resource capacities between and within the six territories, with substantial mortalities predicted as a result of resource gaps (referred to here as "avoidable" mortalities), particularly in poorer areas. Severe nationwide shortages of mechanical ventilators were estimated to be a major cause of avoidable mortalities in all territories except Taiwan. Other resources (oseltamivir, hospital beds and human resources) are inequitably distributed within countries. Estimates of resource gaps and avoidable mortalities were highly sensitive to model parameters defining the transmissibility and clinical severity of the pandemic scenario. However, geographic patterns observed within and across territories remained similar for the range of parameter values explored. CONCLUSIONS: The findings have important implications for where (both geographically and in terms of which resource types) investment is most needed, and the potential impact of resource mobilization for mitigating the disease burden of an influenza pandemic. Effective mobilization of resources across administrative boundaries could go some way towards minimizing avoidable deaths