Potential and limitation of air pollution mitigation by vegetation and uncertainties of deposition-based evaluations.

The potential to capture additional air pollutants by introducing more vegetation or changing existing short vegetation to woodland on first sight provides an attractive route for lowering urban pollution. Here, an atmospheric chemistry and transport model was run with a range of landcover scenarios to quantify pollutant removal by the existing total UK vegetation as well as the UK urban vegetation and to quantify the effect of large-scale urban tree planting on urban air pollution. UK vegetation as a whole reduces area (population)-weighted concentrations significantly, by 10% (9%) for PM2.5, 30% (22%) for SO2, 24% (19%) for NH3 and 15% (13%) for O3, compared with a desert scenario. By contrast, urban vegetation reduces average urban PM2.5 by only approximately 1%. Even large-scale conversion of half of existing open urban greenspace to forest would lower urban PM2.5 by only another 1%, suggesting that the effect on air quality needs to be considered in the context of the wider benefits of urban tree planting, e.g. on physical and mental health. The net benefits of UK vegetation for NO2 are small, and urban tree planting is even forecast to increase urban NO2 and NOx concentrations, due to the chemical interaction with changes in BVOC emissions and O3, but the details depend on tree species selection. By extrapolation, green infrastructure projects focusing on non-greenspace (roadside trees, green walls, roof-top gardens) would have to be implemented at very large scales to match this effect. Downscaling of the results to micro-interventions solely aimed at pollutant removal suggests that their impact is too limited for their cost-benefit analysis to compare favourably with emission abatement measures. Urban vegetation planting is less effective for lowering pollution than measures to reduce emissions at source. The results highlight interactions that cannot be captured if benefits are quantified via deposition models using prescribed concentrations, and emission damage costs. This article is part of a discussion meeting issue 'Air quality, past present and future'.

Biodiversity Improves Life Cycle Sustainability Metrics in Algal Biofuel Production.

Algal biofuel has yet to realize its potential as a commercial and sustainable bioenergy source, largely due to the challenge of maximizing and sustaining biomass production with respect to energetic and material inputs in large-scale cultivation. Experimental studies have shown that multispecies algal polycultures can be designed to enhance biomass production, stability, and nutrient recycling compared to monocultures. Yet, it remains unclear whether these impacts of biodiversity make polycultures more sustainable than monocultures. Here, we present results of a comparative life cycle assessment (LCA) for algal biorefineries to compare the sustainability metrics of monocultures and polycultures of six fresh-water algal species. Our results showed that when algae were grown in outdoor experimental ponds, certain bicultures improved the energy return on investment (EROI) and greenhouse gas emissions (GHGs) by 20% and 16%, respectively, compared to the best monoculture. Bicultures outperformed monocultures by performing multiple functions simultaneously (e.g., improved stability, nutrient efficiency, biocrude characteristics), which outweighed the higher productivity attainable by a monoculture. Our results demonstrate that algal polycultures with optimized multifunctionality lead to enhanced life cycle metrics, highlighting the significant potential of ecological engineering for enabling future environmentally sustainable algal biorefineries.

DETERMINING INSULIN DOSE AT THE TIME OF DISCHARGE IN A HIGH-RISK POPULATION: IS THERE ROOM FOR IMPROVEMENT?

OBJECTIVE: To evaluate the adequacy of the insulin dose prescribed at hospital discharge in a high-risk population and assess patient characteristics that influence insulin dose requirement in the immediate postdischarge period. METHODS: This was a retrospective study conducted at Parkland Health System. We included all patients admitted to a medical floor who received an insulin prescription at discharge and had at least one follow-up visit within 6 months of discharge. All data were extracted by a detailed manual review of each electronic medical record. RESULTS: At the postdischarge follow-up (N = 797, median 33 days from discharge), 60% of patients required an insulin dose adjustment; 47% of the patients required a dose decrease. Significant predictors of a decrease insulin requirement postdischarge included (multiple regression beta coefficient [95% confidence interval]): newly diagnosed diabetes, -12.7 (-17.7, -7.7); ketosis-prone diabetes, -8.4 (-15, -1.8); glycated hemoglobin A1c (HbA1c), <10% (86 mmol/mol) -7.0 (-11.4, -2.6); discharge insulin total daily dose, -5.3 (-9.3, -1.3); and metformin prescription, -4.9 (-8.4, -1.3). CONCLUSION: An insulin dose adjustment (most commonly a decrease) was necessary shortly after discharge in more than half of our patients. A better model to estimate insulin dose at discharge is needed along with short-term follow-up after discharge for insulin titration. A pre-emptive insulin dose reduction at discharge should be considered for patients with newly diagnosed diabetes, ketosis-prone diabetes, metformin prescription, and those with HbA1c <10% at presentation. ABBREVIATIONS: DKA = diabetic ketoacidosis; HbA1c = glycated hemoglobin A1c; KPDM = ketosis-prone diabetes mellitus; TDD = total daily dose.

Development and Evaluation of the R-LINE Model Algorithms to Account for Chemical Transformation in the Near-road Environment.

With increased urbanization, there is increased mobility leading to higher amount of traffic-related activity on a global scale. Most NOx from combustion sources (about 90-95%) are emitted as NO, which is then readily converted to NO2 in the ambient air, while the remainder is emitted largely as NO2. Thus, the bulk of ambient NO2 is formed due to secondary production in the atmosphere, and which R-LINE cannot predict given that it can only model the dispersion of primary air pollutants. NO2 concentrations near major roads are appreciably higher than those measured at monitors in existing networks in urban areas, motivating a need to incorporate a mechanism in R-LINE to account for NO2 formation. To address this, we implemented three different approaches in order of increasing degrees of complexity and barrier to implementation from simplest to more complex. The first is an empirical approach based upon fitting a 4th order polynomial to existing near-road observations across the continental U.S., the second involves a simplified two-reaction chemical scheme, and the third involves a more detailed set of chemical reactions based upon the Generic Reaction Set (GRS) mechanism. All models were able to estimate more than 75% of concentrations within a factor of two of the near-road monitoring data and produced comparable performance statistics. These results indicate that the performance of the new R-LINE chemistry algorithms for predicting NO2 is comparable to other models (i.e. ADMS-Roads with GRS), both showing less than ±15% fractional bias and less than 45% normalized mean square error.

Birmingham Behçet's service: classification of disease and application of the 2014 International Criteria for Behçet's Disease (ICBD) to a UK cohort.

BACKGROUND: This study reports on the analysis of the application and diagnostic predictability of the revised 2014 ICBD criteria in an unselected cohort of UK patients, and the ensuing organ associations and patterns of disease. METHODS: A retrospective cohort study was conducted using a database of electronic medical records. Three categories were recognised: clinically defined BD, incomplete BD and rejected diagnoses of BD. We applied the ISG 1990 and ICBD 2014 classification criteria to these subgroups to validate diagnostic accuracy against the multidisciplinary assessment. RESULTS: Between 2012 and 2015, 281 patients underwent initial assessment at an urban tertiary care centre: 190 patients with a confirmed diagnosis of BD, 7 with an incomplete diagnosis, and 84 with a rejected diagnosis. ICBD 2014 demonstrated an estimated sensitivity of 97.89% (95% CI: 94.70 to 99.42) and positive likelihood ratio of 1.21 (1.10 to 1.28). The strongest independent predictors were: Central nervous lesions (OR = 10.57, 95% CI: 1.34 to 83.30); Genital ulceration (OR = 9.05, 95% CI: 3.35 to 24.47); Erythema nodosum (OR = 6.59, 95% CI: 2.35 to 18.51); Retinal vasculitis (OR = 6.25, 95% CI: 1.47 to 26.60); Anterior uveitis (OR = 6.16, 95% CI: 2.37 to 16.02); Posterior uveitis (OR = 4.82, 95% CI: 1.25 to 18.59). CONCLUSIONS: The ICBD 2014 criteria were more sensitive at picking up cases than ISG 1990 using the multidisciplinary assessment as the gold standard. ICBD may over-diagnose BD in a UK population. Patients who have an incomplete form of BD represent a distinct group that should not be given an early diagnostic label. Behçet's disease is a complex disease that is best diagnosed by multidisciplinary clinical assessment. Patients in the UK differ in their clinical presentation and genetic susceptibility from the original descriptions. This study also highlights an incomplete group of Behçet's patients that are less well defined by their clinical presentation.

Assessing chemistry schemes and constraints in air quality models used to predict ozone in London against the detailed Master Chemical Mechanism.

Air pollution is the environmental factor with the greatest impact on human health in Europe. Understanding the key processes driving air quality across the relevant spatial scales, especially during pollution exceedances and episodes, is essential to provide effective predictions for both policymakers and the public. It is particularly important for policy regulators to understand the drivers of local air quality that can be regulated by national policies versus the contribution from regional pollution transported from mainland Europe or elsewhere. One of the main objectives of the Coupled Urban and Regional processes: Effects on AIR quality (CUREAIR) project is to determine local and regional contributions to ozone events. A detailed zero-dimensional (0-D) box model run with the Master Chemical Mechanism (MCMv3.2) is used as the benchmark model against which the less explicit chemistry mechanisms of the Generic Reaction Set (GRS) and the Common Representative Intermediates (CRIv2-R5) schemes are evaluated. GRS and CRI are used by the Atmospheric Dispersion Modelling System (ADMS-Urban) and the regional chemistry transport model EMEP4UK, respectively. The MCM model uses a near-explicit chemical scheme for the oxidation of volatile organic compounds (VOCs) and is constrained to observations of VOCs, NOx, CO, HONO (nitrous acid), photolysis frequencies and meteorological parameters measured during the ClearfLo (Clean Air for London) campaign. The sensitivity of the less explicit chemistry schemes to different model inputs has been investigated: Constraining GRS to the total VOC observed during ClearfLo as opposed to VOC derived from ADMS-Urban dispersion calculations, including emissions and background concentrations, led to a significant increase (674% during winter) in modelled ozone. The inclusion of HONO chemistry in this mechanism, particularly during wintertime when other radical sources are limited, led to substantial increases in the ozone levels predicted (223%). When the GRS and CRIv2-R5 schemes are run with the equivalent model constraints to the MCM, they are able to reproduce the level of ozone predicted by the near-explicit MCM to within 40% and 20% respectively for the majority of the time. An exception to this trend was observed during pollution episodes experienced in the summer, when anticyclonic conditions favoured increased temperatures and elevated O3. The in situ O3 predicted by the MCM was heavily influenced by biogenic VOCs during these conditions and the low GRS [O3] : MCM [O3] ratio (and low CRIv2-R5 [O3] : MCM [O3] ratio) demonstrates that these less explicit schemes under-represent the full O3 creation potential of these VOCs. To fully assess the influence of the in situ O3 generated from local emissions versus O3 generated upwind of London and advected in, the time since emission (and, hence, how far the real atmosphere is from steady state) must be determined. From estimates of the mean transport time determined from the NOx : NOy ratio observed at North Kensington during the summer and comparison of the O3 predicted by the MCM model after this time, ∼60% of the median observed [O3] could be generated from local emissions. During the warmer conditions experienced during the easterly flows, however, the observed [O3] may be even more heavily influenced by London's emissions.

Microbial production of high octane and high sensitivity olefinic ester biofuels.

BACKGROUND: Advanced spark ignition engines require high performance fuels with improved resistance to autoignition. Biologically derived olefinic alcohols have arisen as promising blendstock candidates due to favorable octane numbers and synergistic blending characteristics. However, production and downstream separation of these alcohols are limited by their intrinsic toxicity and high aqueous solubility, respectively. Bioproduction of carboxylate esters of alcohols can improve partitioning and reduce toxicity, but in practice has been limited to saturated esters with characteristically low octane sensitivity. If olefinic esters retain the synergistic blending characteristics of their alcohol counterparts, they could improve the bioblendstock combustion performance while also retaining the production advantages of the ester moiety. RESULTS: Optimization of Escherichia coli isoprenoid pathways has led to high titers of isoprenol and prenol, which are not only excellent standalone biofuel and blend candidates, but also novel targets for esterification. Here, a selection of olefinic esters enhanced blendstock performance according to their degree of unsaturation and branching. E. coli strains harboring optimized mevalonate pathways, thioester pathways, and heterologous alcohol acyltransferases (ATF1, ATF2, and SAAT) were engineered for the bioproduction of four novel olefinic esters. Although prenyl and isoprenyl lactate titers were limited to 1.48 ± 0.41 mg/L and 5.57 ± 1.36 mg/L, strains engineered for prenyl and isoprenyl acetate attained titers of 176.3 ± 16.0 mg/L and 3.08 ± 0.27 g/L, respectively. Furthermore, prenyl acetate (20% bRON = 125.8) and isoprenyl acetate (20% bRON = 108.4) exhibited blend properties comparable to ethanol and significantly better than any saturated ester. By further scaling cultures to a 2-L bioreactor under fed-batch conditions, 15.0 ± 0.9 g/L isoprenyl acetate was achieved on minimal medium. Metabolic engineering of acetate pathway flux further improved titer to attain an unprecedented 28.0 ± 1.0 g/L isoprenyl acetate, accounting for 75.7% theoretical yield from glucose. CONCLUSION: Our study demonstrated novel bioproduction of four isoprenoid oxygenates for fuel blending. Our optimized E. coli production strain generated an unprecedented titer of isoprenyl acetate and when paired with its favorable blend properties, may enable rapid scale-up of olefinic alcohol esters for use as a fuel blend additive or as a precursor for longer-chain biofuels and biochemicals.

An observational study of endothelial function in early arthritis.

BACKGROUND: Endothelial dysfunction is present in established rheumatoid arthritis, but it is not clear at what stage of the disease this abnormality develops. We set out to determine whether endothelial damage/dysfunction is present in a group of patients with early arthritis (EA) (new onset inflammatory arthritis, EA). MATERIALS AND METHODS: Eighteen patients with EA, 48 healthy controls and 25 disease controls were recruited. Plasma was obtained for endothelial [von Willebrand factor (vWF) and soluble E-selectin] and angiogenesis markers (vascular endothelial growth factor and its receptor sFlt-1), adhesion molecules (intercellular adhesion molecule 1 and vascular cell adhesion molecule 1) and circulating endothelial cells (CECs, as a marker of endothelial damage). Microvascular endothelial function was assessed using laser Doppler perfusion imaging and macrovascular function using flow-mediated dilatation of the brachial artery. RESULTS: von Willebrand factor and CECs (both P < 0.05) were significantly elevated in EA suggesting endothelial dysfunction and damage but were unrelated to classical laboratory markers of inflammation C-reactive protein, erythrocyte sedimentation rate or IL6. No other biomarkers was elevated in EA. Microvascular and macrovascular abnormalities were confined to endothelium-independent (smooth muscle cell) responses. CONCLUSIONS: Endothelial damage/dysfunction is present early in the course of inflammatory arthritis but is not directly related to inflammation markers.

Translating advances in microbial bioproduction to sustainable biotechnology.

Advances in synthetic biology have radically changed our ability to rewire microorganisms and significantly improved the scalable production of a vast array of drop-in biopolymers and biofuels. The success of a drop-in bioproduct is contingent on market competition with petrochemical analogues and weighted upon relative economic and environmental metrics. While the quantification of comparative trade-offs is critical for accurate process-level decision making, the translation of industrial ecology to synthetic biology is often ambiguous and assessment accuracy has proven challenging. In this review, we explore strategies for evaluating industrial biotechnology through life cycle and techno-economic assessment, then contextualize how recent developments in synthetic biology have improved process viability by expanding feedstock availability and the productivity of microbes. By juxtaposing biological and industrial constraints, we highlight major obstacles between the disparate disciplines that hinder accurate process evaluation. The convergence of these disciplines is crucial in shifting towards carbon neutrality and a circular bioeconomy.

Implications of Mitigating Ozone and Fine Particulate Matter Pollution in the Guangdong-Hong Kong-Macau Greater Bay Area of China Using a Regional-To-Local Coupling Model.

Ultrahigh-resolution air quality models that resolve sharp gradients of pollutant concentrations benefit the assessment of human health impacts. Mitigating fine particulate matter (PM2.5) concentrations over the past decade has triggered ozone (O3) deterioration in China. Effective control of both pollutants remains poorly understood from an ultrahigh-resolution perspective. We propose a regional-to-local model suitable for quantitatively mitigating pollution pathways at various resolutions. Sensitivity scenarios for controlling nitrogen oxide (NOx) and volatile organic compound (VOC) emissions are explored, focusing on traffic and industrial sectors. The results show that concurrent controls on both sectors lead to reductions of 17%, 5%, and 47% in NOx, PM2.5, and VOC emissions, respectively. The reduced traffic scenario leads to reduced NO2 and PM2.5 but increased O3 concentrations in urban areas. Guangzhou is located in a VOC-limited O3 formation regime, and traffic is a key factor in controlling NOx and O3. The reduced industrial VOC scenario leads to reduced O3 concentrations throughout the mitigation domain. The maximum decrease in median hourly NO2 is >11 µg/m³, and the maximum increase in the median daily maximum 8-hr rolling O3 is >10 µg/m³ for the reduced traffic scenario. When controls on both sectors are applied, the O3 increase reduces to <7 µg/m³. The daily averaged PM2.5 decreases by <2 µg/m³ for the reduced traffic scenario and varies little for the reduced industrial VOC scenario. An O3 episode analysis of the dual-control scenario leads to O3 decreases of up to 15 µg/m³ (8-hr metric) and 25 µg/m³ (1-hr metric) in rural areas.

Source terms for benchmarking models of SARS-CoV-2 transmission via aerosols and droplets.

There is ongoing and rapid advancement in approaches to modelling the fate of exhaled particles in different environments relevant to disease transmission. It is important that models are verified by comparison with each other using a common set of input parameters to ensure that model differences can be interpreted in terms of model physics rather than unspecified differences in model input parameters. In this paper, we define parameters necessary for such benchmarking of models of airborne particles exhaled by humans and transported in the environment during breathing and speaking.

Comparison of the complex terrain algorithms incorporated into two commonly used local-scale air pollution dispersion models (ADMS and AERMOD) using a hybrid model.

ADMS and AERMOD are the two most widely used dispersion models for regulatory purposes. It is, therefore, important to understand the differences in the predictions of the models and the causes of these differences. The treatment by the models of flat terrain has been discussed previously; in this paper the focus is on their treatment of complex terrain. The paper includes a discussion of the impacts of complex terrain on airflow and dispersion and how these are treated in ADMS and AERMOD, followed by calculations for two distinct cases: (i) sources above a deep valley within a relatively flat plateau area (Clifty Creek power station, USA); (ii) sources in a valley in hilly terrain where the terrain rises well above the stack tops (Ribblesdale cement works, England). In both cases the model predictions are markedly different. At Clifty Creek, ADMS suggests that the terrain markedly increases maximum surface concentrations, whereas the AERMOD complex terrain module has little impact. At Ribblesdale, AERMOD predicts very large increases (a factor of 18) in the maximum hourly average surface concentrations due to plume impaction onto the neighboring hill; although plume impaction is predicted by ADMS, the increases in concentration are much less marked as the airflow model in ADMS predicts some lateral deviation of the streamlines around the hill.

Diversifying Isoprenoid Platforms via Atypical Carbon Substrates and Non-model Microorganisms.

Isoprenoid compounds are biologically ubiquitous, and their characteristic modularity has afforded products ranging from pharmaceuticals to biofuels. Isoprenoid production has been largely successful in Escherichia coli and Saccharomyces cerevisiae with metabolic engineering of the mevalonate (MVA) and methylerythritol phosphate (MEP) pathways coupled with the expression of heterologous terpene synthases. Yet conventional microbial chassis pose several major obstacles to successful commercialization including the affordability of sugar substrates at scale, precursor flux limitations, and intermediate feedback-inhibition. Now, recent studies have challenged typical isoprenoid paradigms by expanding the boundaries of terpene biosynthesis and using non-model organisms including those capable of metabolizing atypical C1 substrates. Conversely, investigations of non-model organisms have historically informed optimization in conventional microbes by tuning heterologous gene expression. Here, we review advances in isoprenoid biosynthesis with specific focus on the synergy between model and non-model organisms that may elevate the commercial viability of isoprenoid platforms by addressing the dichotomy between high titer production and inexpensive substrates.

Comprehensive evaluation of an advanced street canyon air pollution model.

A street canyon pollution dispersion model is described which accounts for a wide range of canyon geometries including deep and/or asymmetric canyons. The model uses up to six component sources to represent different effects of street canyons on the dispersion of road traffic emissions. The final concentration is a weighted sum of the component concentrations dependent on output point location; canyon geometry; and wind direction relative to canyon orientation. Conventional approaches to modeling pollution in street canyons, such as the "Operational Street Pollution Model" (OSPM), do not account for canyons with high aspect ratios, pavements, and building porosity, so are not applicable for all urban morphologies. The new model has been implemented within the widely used, street-level resolution ADMS-Urban air quality model, which is used for air quality assessment and forecasting in cities such as Hong Kong where high-rise buildings form deep and complex street canyons. The new model is evaluated in relation to measured pollutant concentration data from the "Optimisation of modelling methods for traffic pollution in streets" (TRAPOS) project and routine measurements from 42 monitoring sites in London. Comparisons have been made between modeling using the new canyon model; a simpler approach to canyon modeling based on the OSPM formulation; and without any inclusion of canyon effects. The TRAPOS dataset has been used to highlight the model's ability to replicate the dependence of concentration on wind speed and direction, and also to show improved model performance for the prediction of high concentration values, which is particularly important for model applications such as planning and assessment. The London dataset, in which the street canyons are less well defined, has also been used to demonstrate improved model performance for this advanced approach compared to the simpler methods, by categorizing the measurement locations according to site type (background, near-road, and strong canyon). Implications: Currently available air dispersion models do not allow for a number of geometric features that influence air dispersion within street canyon environments. The new advanced street canyon model described in this paper accounts for: emissions from each road carriageway separately; canyon asymmetry; canyon porosity; and pavements. The extensive model evaluation presented shows that the new model demonstrates good performance, better than more basic approaches in which the complex geometries that define "canyons" are neglected.

Optimized gene expression from bacterial chromosome by high-throughput integration and screening.

Chromosomal integration of recombinant genes is desirable compared with expression from plasmids due to increased stability, reduced cell-to-cell variability, and elimination of the need for antibiotics for plasmid maintenance. Here, we present a new approach for tuning pathway gene expression levels via random integration and high-throughput screening. We demonstrate multiplexed gene integration and expression-level optimization for isobutanol production in Escherichia coli The integrated strains could, with far lower expression levels than plasmid-based expression, produce high titers (10.0 ± 0.9 g/liter isobutanol in 48 hours) and yields (69% of the theoretical maximum). Close examination of pathway expression in the top-performing, as well as other isolates, reveals the complexity of cellular metabolism and regulation, underscoring the need for precise optimization while integrating pathway genes into the chromosome. We expect this method for pathway integration and optimization can be readily extended to a wide range of pathways and chassis to create robust and efficient production strains.

Inflammatory cytokines, endothelial markers and adhesion molecules in rheumatoid arthritis: effect of intensive anti-inflammatory treatment.

Tumour necrosis factor alpha (TNF-alpha) and interlekin-6 (IL-6) are key inflammatory cytokines in the pathogenesis of rheumatoid arthritis (RA), a disease also associated with endothelial perturbation and increased serum levels of adhesion molecules. As relationships between these processes and molecules are unclear, we tested the hypotheses (a) that TNF-alpha and IL-6 are linked to endothelial activation/damage and levels of soluble adhesion molecules, and (b) that intensive anti-inflammatory treatment improves levels of these indices. We recruited 66 patients with RA, 48 community controls (CC), and 25 disease controls (DC). Plasma TNF-alpha and IL-6 were compared to markers of vascular biology (vWF, sE-sel), soluble adhesion molecules (sICAM, sVCAM) and routine inflammatory markers (CRP and ESR). Blood was obtained at baseline and at 1 week and again 4 weeks after anti-inflammatory treatment in a subgroup of 29 patients with RA. With the exception of sE-selectin, RA patients had increased levels of all plasma markers compared to the HCs, whilst levels in the DCs were largely intermediate between RA and the CCs. Within the RA group, sEsel correlated with both CRP and ESR whilst TNF-alpha correlated with sVCAM (all r > 0.32, P < 0.01). After 1 week of combined anti-inflammatory therapy, only CRP, ESR, sEsel and sVCAM were significantly reduced (all P < 0.05). In RA, endothelial activation (as sEsel) correlates with classical markers of inflammation and is reduced by intensive anti-inflammatory medications.

Vasculitis integrated clinical assessment database: a data management system to support studies into systemic vasculitis.

BACKGROUND: The systemic vasculitides are characterized by immune inflammation affecting blood vessels, which can lead to organ and tissue damage. Treatment has improved but optimum long-term management still remains unsatisfactory, requiring ongoing therapeutic studies. These often base their measures of efficacy on the outcome of clinical assessments which include the Birmingham Vasculitis Activity Score and the Vasculitis Damage Index. OBJECTIVES: Efficient management of assessment data is complex and often hampered by working with time-consuming paper-based systems. The Vasculitis Integrated Clinical Assessment Database (VICAD) was created to improve the process. METHODS: VICAD was developed using Microsoft Access. Visual Basic for Applications and the Data Access Objects Application Programming Interface provide the functionality to assist with scoring, calculation of results, and storing of data. RESULTS: VICAD is an efficient system for managing data. Evaluation of its use showed an improvement in the completeness of patient assessments from 77% (paper based: n = 44) to 98% (computer based: n = 30). During development clinicians (n = 4) rated it at 8/10 for its layout and visual presentation and 8/10 for easy to use (intuitiveness and navigability). CONCLUSIONS: The development of an integrated and standardized system of data collection (VICAD) helps to support clinical decision making processes and report findings in a more timely manner. It is available free for use and modification under the GNU General Public License. The open source nature of VICAD could help to inform the design of other databases where management of complex information into important multisystem diseases is needed.

Random Chromosomal Integration and Screening Yields E. coli K-12 Derivatives Capable of Efficient Sucrose Utilization.

Chromosomal expression of heterologous genes offers stability and maintenance advantages over episomal expression, yet remains difficult to optimize through site-specific integration. The challenge has in large part been due to the variability of chromosomal gene expression, which has only recently been shown to be affected by multiple factors, including the local genomic context. In this work we utilize Tn5 transposase to randomly integrate a three-gene csc operon encoding nonphosphotransferase sucrose catabolism into the E. coli K-12 chromosome. Isolates from the transposon library yielded a range of growth rates on sucrose as the sole carbon source, including some that were comparable to that of E. coli K-12 on glucose (µmax = 0.70 ± 0.03 h-1). Narrowness of the growth rate distributions and faster growth compared to plasmids indicate that efficient csc expression is attainable. Furthermore, enhanced growth rate upon transduction into strains that underwent adaptive laboratory evolution indicate that sucrose catabolism is not limiting to cellular growth. We also show that transduction of a csc fast-growth locus into an isobutanol production strain yields high titer (7.56 ± 0.25 g/L) on sucrose as the sole carbon source. Our results demonstrate that random integration is an effective strategy for optimizing heterologous expression within the context of cellular metabolism for both fast growth and biochemical production phenotypes.

Impact of air pollution on educational attainment for respiratory health treated students: A cross sectional data linkage study.

INTRODUCTION: There is some evidence that exam results are worse when students are acutely exposed to air pollution. Studies investigating the association between air pollution and academic attainment have been constrained by small sample sizes. METHODS: Cross sectional educational attainment data (2009-2015) from students aged 15-16 years in Cardiff, Wales were linked to primary health care data, modelled air pollution and measured pollen data, and analysed using multilevel linear regression models. Annual cohort, school and individual level confounders were adjusted for in single and multi-pollutant/pollen models. We stratified by treatment of asthma and/or Seasonal Allergic Rhinitis (SAR). RESULTS: A unit (10µg/m3) increase of short-term exposure to NO2 was associated with 0.044 (95% CI: -0.079, -0.008) reduction of standardised Capped Point Score (CPS) after adjusting for individual and household risk factors for 18,241 students. This association remained statistically significant after controlling for other pollutants and pollen. There was no association of PM2.5, O3, or Pollen with standardised CPS remaining after adjustment. We found no evidence that treatment for asthma or SAR modified the observed NO2 effect on educational attainment. CONCLUSION: Our study showed that short-term exposure to traffic-related air pollution, specifically NO2, was associated with detrimental educational attainment for students aged 15-16. Longitudinal investigations in different settings are required to confirm this possible impact and further work may uncover the long-term economic implications, and degree to which impacts are cumulative and permanent.

Circulating endothelial cells and rheumatoid arthritis: relationship with plasma markers of endothelial damage/dysfunction.

OBJECTIVES: RA is associated with endothelial cell dysfunction (ECD) and increased cardiovascular mortality and morbidity. Circulating endothelial cells (CECs) are a novel marker of severe endothelial damage. We hypothesized altered CECs in patients with RA compared with community controls (CCs) and hospital controls (HCs, with diabetes and hypertension) correlate with established plasma markers of inflammation and of ECD. METHODS: CECs (CD146-immunobeads), von Willebrand factor, soluble E-selectin, soluble intercellular adhesion molecule-1, soluble vascular endothelial adhesion molecule-1 (sVCAM, all ELISA) and C-reactive protein (CRP, immunonephelometry) were measured in 57 patients with RA, 45 CC and 23 HC patients. RESULTS: CECs in RA [median/interquartile range 8 (5-13.5) cells/ml] were elevated compared with either CC [4 (2-8.5) cells/ml] or HC [4 (1-8) cells/ml] (both P < 0.001). Levels of CECs did not correlate with other markers of ECD or of inflammation but did correlate inversely with sVCAM. CONCLUSION: Evidence of endothelial damage in the form of mildly increased numbers of CECs is present in RA and is independent of plasma markers of inflammation and of ECD.