Multiple Soft Tissue Sarcomas in a Single Patient:An International Multicentre Review

Developing multiple soft tissue sarcomas (STSs) is a rare process, sparsely reported in the literature to date. Little is known about the pattern of disease development or outcomes in these patients. Patients were identified from three tertiary orthopaedic oncology centres in Canada and the UK. Patients who developed multiple extremity STSs were collated retrospectively from prospective oncology databases. A literature review using MEDLINE was also performed. Six patients were identified in the case series from these three institutions, and five studies were identified from the literature review. Overall, 17 patients were identified with a median age of 51 years (range: 19 to 77). The prevalence of this manifestation in STS patients is 1 in 1225. The median disease-free interval between diagnoses was 2.3 years (range: 0 to 19 years). Most patients developed the secondary STS in a metachronous pattern, the remaining, synchronously. The median survival after the first sarcoma was 6 years, and it was 1.6 years after the second sarcoma. The 5-year overall survival rate was 83.3% and 50% following the first and second STS diagnoses, respectively. A diagnosis of two STSs does not confer a worse prognosis than the diagnosis of a single STS. Developing a second STS is a rare event with no identifiable histological pattern of occurrence. Presentation in a metachronous pattern is more common. A high degree of vigilance is required in patients with a previous STS both to detect both local recurrence and to identify new masses remote from the previous STS site. Acquiring an early histological diagnosis should be attempted

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world\u27s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km² resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e., offset) between in-situ soil temperature measurements, based on time series from over 1200 1-km² pixels (summarized from 8500 unique temperature sensors) across all the world’s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in-situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature.

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Delusional infestation in healthcare professionals: Outcomes from a multi‐centre case series

Abstract Delusional infestation (DI) describes an unwavering fixed belief of infestation with pathogens, despite a lack of medical evidence supporting this. Effective management of DI with antipsychotics is made challenging by the fixed belief that the condition is an infestation or infection rather than a mental illness. A case series of individuals diagnosed with DI included 11% who were healthcare professionals (HCPs). We sought to characterise a cohort of HCPs who presented with DI in the UK. The case notes of HCPs diagnosed with DI at specialist clinics between 2015 and 2019 were reviewed. Demographic and clinical data were obtained. Twelve HCPs were identified out of a total of 381 individuals diagnosed with DI. Median age was 52.5 (IQR = 14.5) years. 75% (n = 9) were women. Ten individuals had primary DI, whilst two had secondary DI (one to recreational drug use, one to depression). Four individuals (33%) engaged with antipsychotic treatment. Two responded well, both had secondary DI. Of the two individuals with primary DI who engaged, one did not respond to antipsychotic medication and the other was unable to tolerate two antipsychotic drugs. In Primary DI (n = 10), the rate of adherence was lower at 20% (n = 2). In DI, high engagement and adherence rates to treatment have been reported in specialist centres. Improvement has been reported as high as 70%–75%. This indicates that a large proportion of individuals who adhere to treatment appear to derive benefit. In this series, engagement with treatment by HCPs with primary DI was low at 20%, and improvement was only achieved in individuals with secondary DI. Mental illness‐related stigma, feelings of distress and difficulty forming therapeutic relationships with a professional peer are significant challenges. Developing rapport is key to treatment success in DI. In HCPs this may be suboptimal due to these negative feelings, resulting in lower engagement. A diagnosis of DI in a HCP may raise concerns regarding fitness to practise. An assessment of the impact of DI and the potential to interfere with professional duties warrants consideration. We highlight the occurrence of DI in HCPs, and the apparent lower engagement with treatment in this cohort

New tool for integration of wind power forecasting into power system operation

Paper presented at the IEEE PowerTech 2009 conference, Bucharest, June 28 2009-July 2 2009The paper describes the methodology that has been developed for Transmission System Operators (TSOs) of Republic of Ireland, Eirgrid, and Northern Ireland, SONI the TSO in Northern Ireland, to study the effects of advanced wind power forecasting on optimal short-term power system scheduling. The resulting schedules take into account the electricity market conditions and feature optimal reserve scheduling. The short-term wind power prediction is provided by the Anemos tool, and the scheduling function, including the reserve optimisation, by the Wilmar tool. The proposed methodology allows for evaluation of the impacts that different types of wind energy forecasts (stochastic vs. deterministic vs. perfect) have on the schedules, and how the new incoming information via in-day scheduling impacts the quality of the schedules. Within the methodology, metrics to assess the quality of the schedules is proposed, including the costs, reliability and cycling. The resulting schedules are compared to the Day-ahead and In-day results of the existing scheduling methodology, Reserve Constrained Unit Commitment (RCUC), with the historical data used as the input for calibration.Science Foundation IrelandANEMOS.Plus projectEuropean Union, 6th Framework Program (FP6)Charles parson pe, la, ke, ab - kpw2/11/1