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Introduction Sciatica can be very painful and, in most cases, is due to pressure on a spinal nerve root from a disc herniation with associated inflammation. For some patients, the pain persists, and one management option is a spinal epidural steroid injection (ESI). The aim of an ESI is to relieve leg pain, improve function and reduce the need for surgery. ESIs work well in some patients but not in others, but we cannot identify these patient subgroups currently. This study aims to identify factors, including patient characteristics, clinical examination and imaging findings, that help in predicting who does well and who does not after an ESI. The overall objective is to develop a prognostic model to support individualised patient and clinical decision-making regarding ESI.Methods POiSE is a prospective cohort study of 439 patients with sciatica referred by their clinician for an ESI. Participants will receive weekly text messages until 12 weeks following their ESIand then again at 24 weeks following their ESI to collect data on leg pain severity. Questionnaires will be sent to participants at baseline, 6, 12 and 24 weeks after their ESI to collect data on pain, disability, recovery and additional interventions. The prognosis for the cohort will be described. The primary outcome measure for the prognostic model is leg pain at 6 weeks. Prognostic models will also be developed for secondary outcomes of disability and recovery at 6 weeks and additional interventions at 24 weeks following ESI. Statistical analyses will include multivariable linear and logistic regression with mixed effects model.Ethics and dissemination The POiSE study has received ethical approval (South Central Berkshire B Research Ethics Committee 21/SC/0257). Dissemination will be guided by our patient and public engagement group and will include scientific publications, conference presentations and social media.

Virtual exchange (VE) is an educational practice that involves the engagement of groups of learners in extended periods of online intercultural interaction and collaboration with international peers as an integrated part of their educational programs and under the guidance of educators and/or facilitators. Despite more than 20 years of research and recent large-scale initiatives such as Erasmus+ Virtual Exchange, this approach remains relatively unknown and often misunderstood in international education. Based on the qualitative and quantitative data of an Erasmus+ KA3 "European Policy Experiment," which brought together practitioners, researchers, and ministerial policy makers from five European countries and autonomous regions, this article examines the challenges involved in implanting and upscaling an innovative practice such as VE in university internationalization practices. A case study from a Spanish regional autonomy, which took part in the project, is used to highlight barriers to take-up and integration at classroom, institutional, and policy levels. The data also provide a clear illustration of how an international practice such as VE can gain recognition and support though the coordination of bottom-up and top-down initiatives.

A global in situ data set for validation of ocean colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI) is presented. This version of the compilation, starting in 1997, now extends to 2021, which is important for the validation of the most recent satellite optical sensors such as Sentinel 3B OLCI and NOAA-20 VIIRS. The data set comprises in situ observations of the following variables: spectral remote-sensing reflectance, concentration of chlorophyll-a, spectral inherent optical properties, spectral diffuse attenuation coefficient, and total suspended matter. Data were obtained from multi-project archives acquired via open internet services or from individual projects acquired directly from data providers. Methodologies were implemented for homogenization, quality control, and merging of all data. Minimal changes were made on the original data, other than conversion to a standard format, elimination of some points, after quality control and averaging of observations that were close in time and space. The result is a merged table available in text format. Overall, the size of the data set grew with 148 432 rows, with each row representing a unique station in space and time (cf. 136 250 rows in previous version; Valente et al., 2019). Observations of remote-sensing reflectance increased to 68 641 (cf. 59 781 in previous version; Valente et al., 2019). There was also a near tenfold increase in chlorophyll data since 2016. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) are included in the final table. By making the metadata available, provenance is better documented and it is also possible to analyse each set of data separately. The compiled data are available at https://doi.org/10.1594/PANGAEA.941318 (Valente et al., 2022).

Abstract Staggered-peak production (SP)—a measure to halt industrial production in the heating season—has been implemented in North China Plain to alleviate air pollution. We compared the variations of PM1 composition in Beijing during the SP period in the 2016 heating season (SPhs) with those in the normal production (NP) periods during the 2015 heating season (NPhs) and 2016 non-heating season (NPnhs) to investigate the effectiveness of SP. The PM1 mass concentration decreased from 70.0 ± 54.4 μg m−3 in NPhs to 53.0 ± 56.4 μg m−3 in SPhs, with prominent reductions in primary emissions. However, the fraction of nitrate during SPhs (20.2%) was roughly twice that during NPhs (12.7%) despite a large decrease of NOx, suggesting an efficient transformation of NOx to nitrate during the SP period. This is consistent with the increase of oxygenated organic aerosol (OOA), which almost doubled from NPhs (22.5%) to SPhs (43.0%) in the total organic aerosol (OA) fraction, highlighting efficient secondary formation during SP. The PM1 loading was similar between SPhs (53.0 ± 56.4 μg m−3) and NPnhs (50.7 ± 49.4 μg m−3), indicating a smaller difference in PM pollution between heating and non-heating seasons after the implementation of the SP measure. In addition, a machine learning technique was used to decouple the impact of meteorology on air pollutants. The deweathered results were comparable with the observed results, indicating that meteorological conditions did not have a large impact on the comparison results. Our study indicates that the SP policy is effective in reducing primary emissions but promotes the formation of secondary species.

Skin inflammation is often accompanied by systemic disease, yet the pathways that regulate this escalation are little known. Here authors show that transgenic expression of human CD1a in mice leads to the escalation of experimental skin inflammation and systemic inflammatory disease, and the generalized symptoms could be alleviated by blocking antibodies developed against CD1a.

Despite a large number of studies, out of all drivers of radiative forcing, the effect of aerosols has the largest uncertainty in global climate model radiative forcing estimates. There have been studies of aerosol optical properties in climate models, but the effects of particle number size distribution need a more thorough inspection. We investigated the trends and seasonality of particle number concentrations in nucleation, Aitken, and accumulation modes at 21 measurement sites in Europe and the Arctic. For 13 of those sites, with longer measurement time series, we compared the field observations with the results from five climate models, namely EC-Earth3, ECHAM-M7, ECHAM-SALSA, NorESM1.2, and UKESM1. This is the first extensive comparison of detailed aerosol size distribution trends between in situ observations from Europe and five earth system models (ESMs). We found that the trends of particle number concentrations were mostly consistent and decreasing in both measurements and models. However, for many sites, climate models showed weaker decreasing trends than the measurements. Seasonal variability in measured number concentrations, quantified by the ratio between maximum and minimum monthly number concentration, was typically stronger at northern measurement sites compared to other locations. Models had large differences in their seasonal representation, and they can be roughly divided into two categories: for EC-Earth and NorESM, the seasonal cycle was relatively similar for all sites, and for other models the pattern of seasonality varied between northern and southern sites. In addition, the variability in concentrations across sites varied between models, some having relatively similar concentrations for all sites, whereas others showed clear differences in concentrations between remote and urban sites. To conclude, although all of the model simulations had identical input data to describe anthropogenic mass emissions, trends in differently sized particles vary among the models due to assumptions in emission sizes and differences in how models treat size-dependent aerosol processes. The inter-model variability was largest in the accumulation mode, i.e. sizes which have implications for aerosol–cloud interactions. Our analysis also indicates that between models there is a large variation in efficiency of long-range transportation of aerosols to remote locations. The differences in model results are most likely due to the more complex effect of different processes instead of one specific feature (e.g. the representation of aerosol or emission size distributions). Hence, a more detailed characterization of microphysical processes and deposition processes affecting the long-range transport is needed to understand the model variability.

This article provides an introduction to the EVALUATE project (Evaluating and Upscaling Telecollaborative Teacher Education). This project aims to gauge the impact of telecollaborative learning on student-teachers involved in Initial Teacher Education in various European countries and regions. The project is funded by the Erasmus+ KA3 programme (EACEA/34/2015) and is a European Policy Experiment (EPE).

Introduction Composite indicators of quality and safety in healthcare summarise performance across multiple indicators into a single performance measure. Composite indicators can identify domains and drivers of quality, improve the ability to detect differences, aid prioritisation for quality improvement and facilitate decision making about future healthcare needs. However, the use of composite indicators can be controversial, particularly when used to rank healthcare providers. Many of the concerns around transparency, appropriateness and uncertainty may be addressed by a robust and transparent development and review process.The aim of this scoping review is to describe methodologies used at each of the stages of development of composite indicators of quality and safety in healthcare. This review will provide those tasked with developing or reviewing composite indicators with a valuable consolidated analysis of a substantial and wide-ranging literature.Methods and analysis The framework proposed by the Joanna Briggs Institute and enhancements proposed by Peters et al (2015, 2017, 2020) will be used in conducting this scoping review, and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for scoping reviews will guide the reporting. Grey literature and peer-reviewed documents will be in-scope. Electronic databases (PubMed, Embase, CINAHL, ABI/INFORM and SafetyLit) will be searched, and publications will be screened by two reviewers. Discussion, policy and guidance publications will be included if they discuss any aspect of the methods used in the development of a composite indicator of quality or safety in a healthcare setting. The search period ranges from 1 January 2000 to 31 December 2022. Data extraction will capture information on 11 stages of composite indicator development, augmenting a 10-stage framework developed by the European Commission Joint Research Centre.Ethics and dissemination Ethical approval is not required. Review findings will be published in a peer-reviewed journal and presented at scientific conferences.

Numerous studies have shown negative health effects related to exposure to ambient particulate matter (PM), likely due to induced oxidative stress. In this study, we have examined ambient PM samples from Birr, a small (~5000 inhabitants) town in central Ireland, for their water-soluble DTT-based oxidative potential (OP_DTT) with a resolution of 6 h, together with online chemical characterization measurements, to assess the OP of organic aerosols, in particular from residential solid fuel burning. The OP_DTT normalized by the volume of sampled air shows a high variability, ranging from −1 m−3, and a high correlation with PM mass. A lower variability was associated with the mass-normalized OP. Nevertheless, both tended to present higher values during night-time pollution episodes. Simple and multivariate linear regression approaches linked OP_DTT to residential solid fuel burning, and in particular to wood (~87%) and peat (~13%) combustion. The results of the present study show how residential solid fuel burning can have a severe impact on air quality, even in small towns, with potential negative health effects on the exposed population.

Quasars are bright and unobscured active galactic nuclei (AGN) thought to be powered by the accretion of matter around supermassive black holes at the centers of galaxies. The temporal variability of a quasar’s brightness contains valuable information about its physical properties. The UV/optical variability is thought to be a stochastic process, often represented as a damped random walk described by a stochastic differential equation (SDE). Upcoming wide-field telescopes such as the Rubin Observatory Legacy Survey of Space and Time (LSST) are expected to observe tens of millions of AGN in multiple filters over a ten year period, so there is a need for efficient and automated modeling techniques that can handle the large volume of data. Latent SDEs are machine learning models well suited for modeling quasar variability, as they can explicitly capture the underlying stochastic dynamics. In this work, we adapt latent SDEs to jointly reconstruct multivariate quasar light curves and infer their physical properties such as the black hole mass, inclination angle, and temperature slope. Our model is trained on realistic simulations of LSST ten year quasar light curves, and we demonstrate its ability to reconstruct quasar light curves even in the presence of long seasonal gaps and irregular sampling across different bands, outperforming a multioutput Gaussian process regression baseline. Our method has the potential to provide a deeper understanding of the physical properties of quasars and is applicable to a wide range of other multivariate time series with missing data and irregular sampling.

Institutions should value teaching and service, and not just research, when considering faculty for promotion and tenure.

Abstract The serine/threonine protein kinase AKT plays a pivotal role within the PI3K pathway in regulating cellular proliferation and apoptotic cellular functions, and AKT hyper-activation via gene amplification and/or mutation has been implicated in multiple human malignancies. There are 3 AKT isoenzymes (AKT1-3) which mediate critical, non-redundant functions. We present the discovery and development of ALM301, a novel, allosteric, sub-type selective inhibitor of AKT1/2. ALM301 binds in an allosteric pocket created by the combined movement of the PH domain and the catalytic domain, resulting in a DFG out conformation. ALM301 was shown to be highly selective against a panel of over 450 kinases and potently inhibited cellular proliferation. These effects were particularly pronounced in MCF-7 cells containing a PI3KCA mutation. Subsequent cellular downstream pathway analysis in this sensitive cell line revealed potent inhibition of pAKT signalling up to 48 h post dosing. ALM301 treatment was well tolerated in an MCF-7 xenograft model and led to a dose-dependent reduction in tumour growth. Enhanced efficacy was observed in combination with tamoxifen. In summary, ALM301 is a highly specific AKT 1/2 inhibitor with an excellent pharmacological profile suitable for further clinical development.

Particulate matter (PM) has become a major concern in terms of human health and climate impact. In particular, the source apportionment (SA) of organic aerosols (OA) present in submicron particles (PM1) has gained relevance as an atmospheric research field due to the diversity and complexity of its primary sources and secondary formation processes. Moreover, relatively simple but robust instruments such as the Aerosol Chemical Speciation Monitor (ACSM) are now widely available for the near-real-time online determination of the composition of the non-refractory PM1. One of the most used tools for SA purposes is the source-receptor positive matrix factorisation (PMF) model. Even though the recently developed rolling PMF technique has already been used for OA SA on ACSM datasets, no study has assessed its added value compared to the more common seasonal PMF method using a practical approach yet. In this paper, both techniques were applied to a synthetic dataset and to nine European ACSM datasets in order to spot the main output discrepancies between methods. The main advantage of the synthetic dataset approach was that the methods' outputs could be compared to the expected “true” values, i.e. the original synthetic dataset values. This approach revealed similar apportionment results amongst methods, although the rolling PMF profile's adaptability feature proved to be advantageous, as it generated output profiles that moved nearer to the truth points. Nevertheless, these results highlighted the impact of the profile anchor on the solution, as the use of a different anchor with respect to the truth led to significantly different results in both methods. In the multi-site study, while differences were generally not significant when considering year-long periods, their importance grew towards shorter time spans, as in intra-month or intra-day cycles. As far as correlation with external measurements is concerned, rolling PMF performed better than seasonal PMF globally for the ambient datasets investigated here, especially in periods between seasons. The results of this multi-site comparison coincide with the synthetic dataset in terms of rolling–seasonal similarity and rolling PMF reporting moderate improvements. Altogether, the results of this study provide solid evidence of the robustness of both methods and of the overall efficiency of the recently proposed rolling PMF approach.

Secondary organic aerosol (SOA) plays an important role in particulate air pollution, but its formation mechanism is still not fully understood. The chemical composition of non-refractory particulate matter with a diameter ≤2.5 µm (NR-PM2.5), OA sources, and SOA formation mechanisms were investigated in urban Xi'an during winter 2018. The fractional contribution of SOA to total OA mass (58 %) was larger than primary OA (POA, 42 %). Biomass-burning-influenced oxygenated OA (OOA-BB) was resolved in urban Xi'an and was formed from the photochemical oxidation and aging of biomass burning OA (BBOA). The formation of OOA-BB was more favorable on days with a larger OA fraction and higher BBOA concentration. In comparison, the aqueous-phase processed oxygenated OA (aq-OOA) was more dependent on the secondary inorganic aerosol (SIA) content and aerosol liquid water content (ALWC), and it showed a large increase (to 50 % of OA) during SIA-enhanced periods. Further van Krevelen (VK) diagram analysis suggests that the addition of carboxylic acid groups with fragmentation dominated OA aging on reference days, while the increased aq-OOA contributions during SIA-enhanced periods likely reflect OA evolution due to the addition of alcohol or peroxide groups.

To investigate the physio-chemical properties of aerosol transported from major pollution regions in China, observations were conducted ∼ 200 m above the ground at the junction location of the North China Plain and Fenwei Basin, which are two regions of top priority for China's Blue Sky Campaign. We identified three pollution transport sectors including those from Beijing–Tianjin–Hebei (BTH), urban Guanzhong Basin (GZB) and northern China and one clean transport sector from the rural Guanzhong Basin region. Secondary inorganic aerosol (SIA) constituted a major fraction (39 %–46 %) in all pollution transport sectors, with a high sulfur oxidation ratio (0.44–0.58) and a high nitrogen oxidation ratio (0.24–0.29), suggesting efficient formation of secondary inorganic aerosol during regional transport. More oxidized oxygenated organic aerosol (MO-OOA) played a dominant role in the source of organic aerosol in all sectors including the clean one, accounting for 42 %–58 % of total organic aerosol. Elemental analysis (O and C) shows that aerosol particles at this receptor site were much more oxidized than in urban regions, pointing that long-range transport contributed markedly to the organic aerosol oxidation and aging. Case studies of pollution events with high sulfate, nitrate and more-oxidized oxygenated organic aerosol production rate indicate the strong formation efficiency of secondary aerosol during regional transport in the Beijing–Tianjin–Hebei transport sector.