Outdoor music festivals: Cacophonous consumption or melodious moderation?

Large outdoor music festivals have emerged as part of a general expansion of licensed recreational activities, but in research terms they have been largely impenetrable due to commercial sensitivities. These sensitivities notwithstanding, the number and scale of such events necessitate a greater understanding of alcohol and drug use and the potential to promote normative protective behaviours in this context. This study examines self-reported alcohol and drug behaviours of 1589 attendees at a music festival in Scotland during the summer of 2008. Similarities between the outdoor rock music festivals and the dance club scene are considered alongside the challenges associated with risk reduction in these settings. Results show that alcohol was consumed by the majority of samples; however, negative consequences were reported by a minority of respondents, suggesting evidence of controlled hedonism within a situation traditionally associated with unrestrained excess. Similarly, the majority of samples did not use drugs. The majority also report a number of self-regulating protective behaviours suggesting that alcohol and drug use is contained within a developing social culture of ‘controlled intoxication’. Results further suggest that although music festivals are transitory events, there is a degree of consistency amongst attendees. Music festivals may therefore be atypical but potentially effective environments to increase protective behaviours using normative messaging and modern communications media. This study was resourced exclusively by local alcohol and drug partnerships

Chronic IL9 and IL-13 Exposure Leads to an Altered Differentiation of Ciliated Cells in a Well-Differentiated Paediatric Bronchial Epithelial Cell Model

Asthma is a chronic inflammatory disease characterised by airways remodelling. In mouse models IL-9 and IL-13 have been implicated in airways remodelling including mucus hypersecretion and goblet cell hyperplasia. Their role, especially that of IL-9, has been much less studied in authentic human ex vivo models of the bronchial epithelium from normal and asthmatic children. We assessed the effects of IL-9, IL-13 and an IL-9/IL-13 combination, during differentiation of bronchial epithelial cells from normal (n = 6) and asthmatic (n = 8) children. Cultures were analysed for morphological markers and factors associated with altered differentiation (MUC5AC, SPDEF and MMP-7). IL-9, IL-9/IL-13 combination and IL-13 stimulated bronchial epithelial cells from normal children had fewer ciliated cells [14.8% (SD 8.9), p = 0.048, 12.4 (SD 6.1), p = 0.016 and 7.3% (SD 6.6), p = 0.031] respectively compared with unstimulated [(21.4% (SD 9.6)]. IL-9 stimulation had no effect on goblet cell number in either group whereas IL-9/IL-13 combination and IL-13 significantly increased goblet cell number [24.8% (SD 8.8), p = 0.02), 32.9% (SD 8.6), p = 0.007] compared with unstimulated normal bronchial cells [(18.6% (SD 6.2)]. All stimulations increased MUC5AC mRNA in bronchial epithelial cells from normal children and increased MUC5AC mucin secretion. MMP-7 localisation was dysregulated in normal bronchial epithelium stimulated with Th2 cytokines which resembled the unstimulated bronchial epithelium of asthmatic children. All stimulations resulted in a significant reduction in transepithelial electrical resistance values over time suggesting a role in altered tight junction formation. We conclude that IL-9 does not increase goblet cell numbers in bronchial epithelial cell cultures from normal or asthmatic children. IL-9 and IL-13 alone and in combination, reduce ciliated cell numbers and transepithelial electrical resistance during differentiation of normal epithelium, which clinically could inhibit mucociliary clearance and drive an altered repair mechanism. This suggests an alternative role for IL-9 in airways remodelling and reaffirms IL-9 as a potential therapeutic target

SIMBIG{\rm S{\scriptsize IM}BIG}: The First Cosmological Constraints from the Non-Linear Galaxy Bispectrum

We present the first cosmological constraints from analyzing higher-order galaxy clustering on non-linear scales. We use ${\rm S{\scriptsize IM}BIG}$, a forward modeling framework for galaxy clustering analyses that employs simulation-based inference to perform highly efficient cosmological inference using normalizing flows. It leverages the predictive power of high-fidelity simulations and robustly extracts cosmological information from regimes inaccessible with current standard analyses. In this work, we apply ${\rm S{\scriptsize IM}BIG}$ to a subset of the BOSS galaxy sample and analyze the redshift-space bispectrum monopole, $B_0(k_1, k_2, k_3)$, to $k_{\rm max}=0.5\,h/{\rm Mpc}$. We achieve 1$\sigma$ constraints of $\Omega_m=0.293^{+0.027}_{-0.027}$ and $\sigma_8= 0.783^{+0.040}_{-0.038}$, which are more than 1.2 and 2.4$\times$ tighter than constraints from standard power spectrum analyses of the same dataset. We also derive 1.4, 1.4, 1.7$\times$ tighter constraints on $\Omega_b$, $h$, $n_s$. This improvement comes from additional cosmological information in higher-order clustering on non-linear scales and, for $\sigma_8$, is equivalent to the gain expected from a standard analysis on a $\sim$4$\times$ larger galaxy sample. Even with our BOSS subsample, which only spans 10% of the full BOSS volume, we derive competitive constraints on the growth of structure: $S_8 = 0.774^{+0.056}_{-0.053}$. Our constraint is consistent with results from both cosmic microwave background and weak lensing. Combined with a $\omega_b$ prior from Big Bang Nucleosynthesis, we also derive a constraint on $H_0=67.6^{+2.2}_{-1.8}\,{\rm km\,s^{-1}\,Mpc^{-1}}$ that is consistent with early universe constraints.Comment: 13 pages, 7 figures, submitted to PRD, comments welcom

SimBIG: Field-level Simulation-Based Inference of Galaxy Clustering

We present the first simulation-based inference (SBI) of cosmological parameters from field-level analysis of galaxy clustering. Standard galaxy clustering analyses rely on analyzing summary statistics, such as the power spectrum, $P_\ell$, with analytic models based on perturbation theory. Consequently, they do not fully exploit the non-linear and non-Gaussian features of the galaxy distribution. To address these limitations, we use the {\sc SimBIG} forward modelling framework to perform SBI using normalizing flows. We apply SimBIG to a subset of the BOSS CMASS galaxy sample using a convolutional neural network with stochastic weight averaging to perform massive data compression of the galaxy field. We infer constraints on $\Omega_m = 0.267^{+0.033}_{-0.029}$ and $\sigma_8=0.762^{+0.036}_{-0.035}$. While our constraints on $\Omega_m$ are in-line with standard $P_\ell$ analyses, those on $\sigma_8$ are $2.65\times$ tighter. Our analysis also provides constraints on the Hubble constant $H_0=64.5 \pm 3.8 \ {\rm km / s / Mpc}$ from galaxy clustering alone. This higher constraining power comes from additional non-Gaussian cosmological information, inaccessible with $P_\ell$. We demonstrate the robustness of our analysis by showcasing our ability to infer unbiased cosmological constraints from a series of test simulations that are constructed using different forward models than the one used in our training dataset. This work not only presents competitive cosmological constraints but also introduces novel methods for leveraging additional cosmological information in upcoming galaxy surveys like DESI, PFS, and Euclid.Comment: 14 pages, 4 figures. A previous version of the paper was published in the ICML 2023 Workshop on Machine Learning for Astrophysic

SIMBIG{\rm S{\scriptsize IM}BIG}: Galaxy Clustering Analysis with the Wavelet Scattering Transform

The non-Gaussisan spatial distribution of galaxies traces the large-scale structure of the Universe and therefore constitutes a prime observable to constrain cosmological parameters. We conduct Bayesian inference of the $\Lambda$CDM parameters $\Omega_m$, $\Omega_b$, $h$, $n_s$, and $\sigma_8$ from the BOSS CMASS galaxy sample by combining the wavelet scattering transform (WST) with a simulation-based inference approach enabled by the ${\rm S{\scriptsize IM}BIG}$ forward model. We design a set of reduced WST statistics that leverage symmetries of redshift-space data. Posterior distributions are estimated with a conditional normalizing flow trained on 20,000 simulated ${\rm S{\scriptsize IM}BIG}$ galaxy catalogs with survey realism. We assess the accuracy of the posterior estimates using simulation-based calibration and quantify generalization and robustness to the change of forward model using a suite of 2,000 test simulations. When probing scales down to $k_{\rm max}=0.5~h/\text{Mpc}$, we are able to derive accurate posterior estimates that are robust to the change of forward model for all parameters, except $\sigma_8$. We mitigate the robustness issues with $\sigma_8$ by removing the WST coefficients that probe scales smaller than $k \sim 0.3~h/\text{Mpc}$. Applied to the BOSS CMASS sample, our WST analysis yields seemingly improved constraints obtained from a standard PT-based power spectrum analysis with $k_{\rm max}=0.25~h/\text{Mpc}$ for all parameters except $h$. However, we still raise concerns on these results. The observational predictions significantly vary across different normalizing flow architectures, which we interpret as a form of model misspecification. This highlights a key challenge for forward modeling approaches when using summary statistics that are sensitive to detailed model-specific or observational imprints on galaxy clustering.Comment: 11+5 pages, 8+2 figure

Improving our understanding of metal implant failures: Multiscale chemical imaging of exogenous metals in ex-vivo biological tissues

Biological exposures to micro- and nano-scale exogenous metal particles generated as a consequence of in-service degradation of orthopaedic prosthetics can result in severe adverse tissues reactions. However, individual reactions are highly variable and are not easily predicted, due to in part a lack of understanding of the speciation of the metal-stimuli which dictates cellular interactions and toxicity. Investigating the chemistry of implant derived metallic particles in biological tissue samples is complicated by small feature sizes, low concentrations and often a heterogeneous speciation and distribution. These challenges were addressed by developing a multi-scale two-dimensional X-ray absorption spectroscopic (XAS) mapping approach to discriminate sub-micron changes in particulate chemistry within ex-vivo tissues associated with failed CoCrMo total hip replacements (THRs). As a result, in the context of THRs, we demonstrate much greater variation in Cr chemistry within tissues compared with previous reports. Cr compounds including phosphate, hydroxide, oxide, metal and organic complexes were observed and correlated with Co and Mo distributions. This variability may help explain the lack of agreement between biological responses observed in experimental exposure models and clinical outcomes. The multi-scale 2D XAS mapping approach presents an essential tool in discriminating the chemistry in dilute biological systems where speciation heterogeneity is expected. Significance: Metal implants are routinely used in healthcare but may fail following degradation in the body. Although specific implants can be identified as ‘high-risk’, our analysis of failures is limited by a lack of understanding of the chemistry of implant metals within the peri-prosthetic milieu. A new approach to identify the speciation and variability in speciation at sub-micron resolution, of dilute exogenous metals within biological tissues is reported; applied to understanding the failure of metallic (CoCrMo) total-hip-replacements widely used in orthopedic surgery. Much greater variation in Cr chemistry was observed compared with previous reports and included phosphate, hydroxide, oxide, metal and organic complexes. This variability may explain lack of agreement between biological responses observed in experimental exposure models and clinical outcomes

SIMBIG{\rm S{\scriptsize IM}BIG}: The First Cosmological Constraints from Non-Gaussian and Non-Linear Galaxy Clustering

The 3D distribution of galaxies encodes detailed cosmological information on the expansion and growth history of the Universe. We present the first cosmological constraints that exploit non-Gaussian cosmological information on non-linear scales from galaxy clustering, inaccessible with current standard analyses. We analyze a subset of the BOSS galaxy survey using ${\rm S{\scriptsize IM}BIG}$, a new framework for cosmological inference that leverages high-fidelity simulations and deep generative models. We use two clustering statistics beyond the standard power spectrum: the bispectrum and a convolutional neural network based summary of the galaxy field. We infer constraints on $\Lambda$CDM parameters, $\Omega_b$, $h$, $n_s$, $\Omega_m$, and $\sigma_8$, that are 1.6, 1.5, 1.7, 1.2, and 2.3$\times$ tighter than power spectrum analyses. With this increased precision, we derive constraints on the Hubble constant, $H_0$, and $S_8 = \sigma_8 \sqrt{\Omega_m/0.3}$ that are competitive with other cosmological probes, even with a sample that only spans 10% of the full BOSS volume. Our $H_0$ constraints, imposing the Big Bang Nucleosynthesis prior on the baryon density, are consistent with the early time constraints from the cosmic microwave background (CMB). Meanwhile, our $S_8$ constraints are consistent with weak lensing experiments and similarly lie below CMB constraints. Lastly, we present forecasts to show that future work extending ${\rm S{\scriptsize IM}BIG}$ to upcoming spectroscopic galaxy surveys (DESI, PFS, Euclid) will produce leading $H_0$ and $S_8$ constraints that bridge the gap between early and late time measurements and shed light on current cosmic tensions.Comment: 13 pages, 5 figures, submitted to Nature Astronomy, comments welcom

Carbon on the Northwest European Shelf: Contemporary Budget and Future Influences

A carbon budget for the northwest European continental shelf seas (NWES) was synthesized using available estimates for coastal, pelagic and benthic carbon stocks and flows. Key uncertainties were identified and the effect of future impacts on the carbon budget were assessed. The water of the shelf seas contains between 210 and 230 Tmol of carbon and absorbs between 1.3 and 3.3 Tmol from the atmosphere annually. Off-shelf transport and burial in the sediments account for 60–100 and 0–40% of carbon outputs from the NWES, respectively. Both of these fluxes remain poorly constrained by observations and resolving their magnitudes and relative importance is a key research priority. Pelagic and benthic carbon stocks are dominated by inorganic carbon. Shelf sediments contain the largest stock of carbon, with between 520 and 1600 Tmol stored in the top 0.1 m of the sea bed. Coastal habitats such as salt marshes and mud flats contain large amounts of carbon per unit area but their total carbon stocks are small compared to pelagic and benthic stocks due to their smaller spatial extent. The large pelagic stock of carbon will continue to increase due to the rising concentration of atmospheric CO2, with associated pH decrease. Pelagic carbon stocks and flows are also likely to be significantly affected by increasing acidity and temperature, and circulation changes but the net impact is uncertain. Benthic carbon stocks will be affected by increasing temperature and acidity, and decreasing oxygen concentrations, although the net impact of these interrelated changes on carbon stocks is uncertain and a major knowledge gap. The impact of bottom trawling on benthic carbon stocks is unique amongst the impacts we consider in that it is widespread and also directly manageable, although its net effect on the carbon budget is uncertain. Coastal habitats are vulnerable to sea level rise and are strongly impacted by management decisions. Local, national and regional actions have the potential to protect or enhance carbon storage, but ultimately global governance, via controls on emissions, has the greatest potential to influence the long-term fate of carbon stocks in the northwestern European continental shelf

High ventilatory inefficiency with low psoas muscle index is associated with an increase in the risk of 3-year mortality after liver resection and pancreaticoduodenectomy

Body composition assessed with computed tomography (CT)1 images and cardiopulmonary exercise fitness (CPET)2 of liver resection or pancreaticoduodenectomy patients show promising value to prognose surgical outcomes. The combination of CT and CPET may better predict patients’ survival rate after surgery than these techniques independently. This is a retrospective study that collected abdominal CT images and CPET measures of liver resection or pancreaticoduodenectomy patients from the CPET NHS Manchester Foundation Trust research databases. Abdominal CT images were segmented based on Hounsfield Units and CPET was performed until volitional exhaustion. Parameters derived from abdominal CT image analysis at L3 L4 were psoas muscle index (P index), calculated as psoas muscle cross-sectional area (tissue at 29 to 150 Hounsfield units [HU])/height2, and psoas intramuscular adipose tissue (tissue at 190 to -30 HU). CPET parameters were maximum volume of oxygen consumption, anaerobic threshold and ventilatory equivalents of CO2 (VE/VCO2 slope). Cox regression identified CT- and CPET derived parameters with a significant relationship with 1- and 3-year survival rate. After, Patients were classified into two groups based on the median value of the CT or CPET parameters related with 1- or 3-year survival rate. The 1- and 3-year mortality Hazard Ratios (HRs) of the two groups were calculated using Cox regression. Overall, 89 patients (57 men and 32 women, 70 [64-74] years old) were included. P index (HR [95%CI]: 0.830 [0.699-0.984], p=0.032) and VE/VCO2 slope (HR [95%CI]: 1.041 [1.012-1.070], p32.1) showed a higher risk of 3-year mortality (HR [95%CI]: 2.471 [1.292-4.723], p<0.01). The combined used of CT images and CPET analysis better prognosed the risk of 3 year mortality after pancreaticoduodenectomy and liver resection than the use of CT and CPET independently