Self-assembled 2D Free-Standing Janus Nanosheets with Single-Layer Thickness

We report the thermodynamically controlled growth of solution-processable and free-standing nanosheets via peptide assembly in two dimensions. By taking advantage of self-sorting between peptide β-strands and hydrocarbon chains, we have demonstrated the formation of Janus 2D structures with single-layer thickness, which enable a predetermined surface heterofunctionalization. A controlled 2D-to-1D morphological transition was achieved by subtly adjusting the intermolecular forces. These nanosheets provide an ideal substrate for the engineering of guest components (e.g., proteins and nanoparticles), where enhanced enzyme activity was observed. We anticipate that sequence-specific programmed peptides will offer promise as design elements for 2D assemblies with face-selective functionalization

Myocardial infarction, ST-elevation and non-ST-elevation myocardial infarction and modelled daily pollution concentrations; a case-crossover analysis of MINAP data

Objectives: To investigate associations between daily concentrations of air pollution and myocardial infarction (MI), ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI). Methods: Modelled daily ground-level gaseous, total and speciated particulate pollutant concentrations and ground-level daily mean temperature, all at 5 km x 5 km horizontal resolution, were linked to 202,550 STEMI and 322,198 NSTEMI events recorded on the England and Wales Myocardial Ischaemia National Audit Project (MINAP) database. The study period was 2003-2010. A case-crossover design was used, stratified by year, month, and day of the week. Data were analysed using conditional logistic regression, with pollutants modelled as unconstrained distributed lags 0-2 days. Results are presented as percentage change in risk per 10 µg/m3 increase in the pollutant relevant metric, having adjusted for daily mean temperature, public holidays, weekly flu consultation rates, and a sine-cosine annual cycle. Results: There was no evidence of an association between MI or STEMI and any of O3, NO2, PM2.5, PM10 or selected PM2.5 components (sulphate and elemental carbon). For NSTEMI there was a positive association with daily maximum 1-hour NO2 (0.27% (95% CI: 0.01 to 0.54)), which persisted following adjustment for O3 and adjustment for PM2.5. The association appeared to be confined to the midland and southern regions of England and Wales. Conclusions: The study found no evidence of an association between the modelled pollutants (including components) investigated and STEMI but did find some evidence of a positive association between NO2 and NSTEMI. Confirmation of this association in other studies is required

Inspiratory muscle warm-up does not improve cycling time-trial performance

Purpose: This study examined the effects of an active cycling warm-up, with and without the addition of an inspiratory muscle warm-up (IMW), on 10-km cycling time-trial performance

Surface dynamics and ligand-core interactions of quantum sized photoluminescent gold nanoclusters

Quantum-sized metallic clusters protected by biological ligands represent a new class of luminescent materials; yet the understanding of structural information and photoluminescence origin of these ultrasmall clusters remains a challenge. Herein we systematically study the surface ligand dynamics and ligand–metal core interactions of peptide-protected gold nanoclusters (AuNCs) with combined experimental characterizations and theoretical molecular simulations. We show that the peptide sequence plays an important role in determining the surface peptide structuring, interfacial water dynamics and ligand–Au core interaction, which can be tailored by controlling peptide acetylation, constituent amino acid electron donating/withdrawing capacity, aromaticity/hydrophobicity and by adjusting environmental pH. Specifically, emission enhancement is achieved through increasing the electron density of surface ligands in proximity to the Au core, discouraging photoinduced quenching, and by reducing the amount of surface-bound water molecules. These findings provide key design principles for understanding the surface dynamics of peptide-protected nanoparticles and maximizing the photoluminescence of metallic clusters through the exploitation of biologically relevant ligand properties

Coupling models of cattle and farms with models of badgers for predicting the dynamics of bovine tuberculosis (TB)

Bovine TB is a major problem for the agricultural industry in several countries. TB can be contracted and spread by species other than cattle and this can cause a problem for disease control. In the UK and Ireland, badgers are a recognised reservoir of infection and there has been substantial discussion about potential control strategies. We present a coupling of individual based models of bovine TB in badgers and cattle, which aims to capture the key details of the natural history of the disease and of both species at approximately county scale. The model is spatially explicit it follows a very large number of cattle and badgers on a different grid size for each species and includes also winter housing. We show that the model can replicate the reported dynamics of both cattle and badger populations as well as the increasing prevalence of the disease in cattle. Parameter space used as input in simulations was swept out using Latin hypercube sampling and sensitivity analysis to model outputs was conducted using mixed effect models. By exploring a large and computationally intensive parameter space we show that of the available control strategies it is the frequency of TB testing and whether or not winter housing is practised that have the most significant effects on the number of infected cattle, with the effect of winter housing becoming stronger as farm size increases. Whether badgers were culled or not explained about 5%, while the accuracy of the test employed to detect infected cattle explained less than 3% of the variance in the number of infected cattle

Spatiotemporal evaluation of EMEP4UK-WRF v4.3 atmospheric chemistry transport simulations of health-related metrics for NO2, O3, PM10 and PM2.5 for 2001-2010

This study was motivated by the use in air pollution epidemiology and health burden assessment of data simulated at 5 km  ×  5 km horizontal resolution by the EMEP4UK-WRF v4.3 atmospheric chemistry transport model. Thus the focus of the model–measurement comparison statistics presented here was on the health-relevant metrics of annual and daily means of NO2, O3, PM2. 5, and PM10 (daily maximum 8 h running mean for O3). The comparison was temporally and spatially comprehensive, covering a 10-year period (2 years for PM2. 5) and all non-roadside measurement data from the UK national reference monitor network, which applies consistent operational and QA/QC procedures for each pollutant (44, 47, 24, and 30 sites for NO2, O3, PM2. 5, and PM10, respectively). Two important statistics highlighted in the literature for evaluation of air quality model output against policy (and hence health)-relevant standards – correlation and bias – together with root mean square error, were evaluated by site type, year, month, and day-of-week. Model–measurement statistics were generally better than, or comparable to, values that allow for realistic magnitudes of measurement uncertainties. Temporal correlations of daily concentrations were good for O3, NO2, and PM2. 5 at both rural and urban background sites (median values of r across sites in the range 0.70–0.76 for O3 and NO2, and 0.65–0.69 for PM2. 5), but poorer for PM10 (0.47–0.50). Bias differed between environments, with generally less bias at rural background sites (median normalized mean bias (NMB) values for daily O3 and NO2 of 8 and 11 %, respectively). At urban background sites there was a negative model bias for NO2 (median NMB  =  −29 %) and PM2. 5 (−26 %) and a positive model bias for O3 (26 %). The directions of these biases are consistent with expectations of the effects of averaging primary emissions across the 5 km  ×  5 km model grid in urban areas, compared with monitor locations that are more influenced by these emissions (e.g. closer to traffic sources) than the grid average. The biases are also indicative of potential underestimations of primary NOx and PM emissions in the model, and, for PM, with known omissions in the model of some PM components, e.g. some components of wind-blown dust. There were instances of monthly and weekday/weekend variations in the extent of model–measurement bias. Overall, the greater uniformity in temporal correlation than in bias is strongly indicative that the main driver of model–measurement differences (aside from grid versus monitor spatial representivity) was inaccuracy of model emissions – both in annual totals and in the monthly and day-of-week temporal factors applied in the model to the totals – rather than simulation of atmospheric chemistry and transport processes. Since, in general for epidemiology, capturing correlation is more important than bias, the detailed analyses presented here support the use of data from this model framework in air pollution epidemiology

Interaction between M2-branes and Bulk Form Fields

We construct the interaction terms between the world-volume fields of multiple M2-branes and the 3- and 6-form fields in the context of ABJM theory with U($N$)$\times$U($N$) gauge symmetry. A consistency check is made in the simplest case of a single M2-brane, i.e, our construction matches the known effective action of M2-brane coupled to antisymmetric 3-form field. We show that when dimensionally reduced, our couplings coincide with the effective action of D2-branes coupled to R-R 3- and 5-form fields in type IIA string theory. We also comment on the relation between a coupling with a specific 6-form field configuration and the supersymmetry preserving mass deformation in ABJM theory.Comment: 30 pages, version to appear in JHE