Characterization of a novel population of low-density granulocytes associated with disease severity in HIV-1 infection

The mechanisms resulting in progressive immune dysfunction during the chronic phase of HIV infection are not fully understood. We have previously shown that arginase, an enzyme with potent immunosuppressive properties, is increased in HIV seropositive (HIV+) patients with low CD4(+) T cell counts. Here we show that the cells expressing arginase in peripheral blood mononuclear cells of HIV+ patients are low-density granulocytes (LDGs) and that whereas these cells have a similar morphology to normal-density granulocyte, they are phenotypically different. Importantly, our results reveal that increased frequencies of LDGs correlate with disease severity in HIV+ patients

Proposal for a new meteotsunami intensity index

Atmospherically generated coastal waves labelled as meteotsunami are known to cause destruction, injury, and fatality due to their rapid onset and unexpected nature. Unlike other coastal hazards such as tsunami, there exist no standardised means of quantifying this phenomenon, which is crucial to understand shoreline impacts and to enable researchers to establish a shared language and framework for meteotsunami analysis and comparison. In this study, we present a new five-level Lewis Meteotsunami Intensity Index (LMTI) trialled in the United Kingdom (UK) but designed for global applicability. A comprehensive dataset of meteotsunami events recorded in the UK was utilised, and the index's effectiveness was evaluated, with intensity level and spatial distribution of meteotsunami occurrence derived. Results revealed a predominant occurrence of Level 2 moderate intensity meteotsunami (69 %) in the UK, with distinct hotspots identified in south-western England and Scotland. Further trial implementation of the LMTI in a global capacity revealed its potential adaptability to other meteotsunami-prone regions, facilitating the comparison of events and promoting standardisation of assessment methodologies.</p

Antiretroviral therapy abrogates association between arginase activity and HIV disease severity.

Arginase-induced L-arginine deprivation is emerging as a key mechanism for the downregulation of immune responses. We hypothesised that arginase activity increases with disease severity in HIV-seropositive patients. Our results show that peripheral blood mononuclear cells (PBMCs) from 23 HIV-seropositive patients with low CD4(+) T cell counts (≤350 cells/μl) expressed significantly more arginase compared with 21 patients with high CD4(+) T cell counts. Furthermore, we found a significant association between the two principal prognostic markers used to monitor HIV disease (CD4(+) T cell count and plasma viral load) and PBMC arginase activity in antiretroviral therapy naïve patients but not in patients undergoing therapy

Meteotsunami in the United Kingdom: the hidden hazard

This paper examines the occurrence and seasonality of meteotsunami in the United Kingdom (UK) to present a revised and updated catalogue of events that have occurred since 1750. Previous case studies have alluded to a summer prevalence and rarity of this hazard in the UK. We have verified and classified 98 events using a developed set of identification criteria. The results have revealed a prominent seasonal pattern of winter events which are related to mid-latitude depressions with precipitating convective weather systems. A geographical pattern has also emerged, highlighting three “hotspot” areas at the highest risk from meteotsunami. The evidence reviewed and new data presented here show that the hazard posed by meteotsunami has been underestimated in the UK.</p

The impact of uncertain precipitation data on insurance loss estimates using a flood catastrophe model

Catastrophe risk models used by the insurance industry are likely subject to significant uncertainty, but due to their proprietary nature and strict licensing conditions they are not available for experimentation. In addition, even if such experiments were conducted, these would not be repeatable by other researchers because commercial confidentiality issues prevent the details of proprietary catastrophe model structures from being described in public domain documents. However, such experimentation is urgently required to improve decision making in both insurance and reinsurance markets. In this paper we therefore construct our own catastrophe risk model for flooding in Dublin, Ireland, in order to assess the impact of typical precipitation data uncertainty on loss predictions. As we consider only a city region rather than a whole territory and have access to detailed data and computing resources typically unavailable to industry modellers, our model is significantly more detailed than most commercial products. The model consists of four components, a stochastic rainfall module, a hydrological and hydraulic flood hazard module, a vulnerability module, and a financial loss module. Using these we undertake a series of simulations to test the impact of driving the stochastic event generator with four different rainfall data sets: ground gauge data, gauge-corrected rainfall radar, meteorological reanalysis data (European Centre for Medium-Range Weather Forecasts Reanalysis-Interim; ERA-Interim) and a satellite rainfall product (The Climate Prediction Center morphing method; CMORPH). Catastrophe models are unusual because they use the upper three components of the modelling chain to generate a large synthetic database of unobserved and severe loss-driving events for which estimated losses are calculated. We find the loss estimates to be more sensitive to uncertainties propagated from the driving precipitation data sets than to other uncertainties in the hazard and vulnerability modules, suggesting that the range of uncertainty within catastrophe model structures may be greater than commonly believed

Governing decentralised energy provision: approaches to energy transitions in Kenya [poster]

Governing decentralised energy provision: approaches to energy transitions in Kenya [poster

More than sense of place? Exploring the emotional dimension of rural tourism experiences

It is widely suggested that participation in rural tourism is underpinned by a sense of rural place or “rurality”. However, although nature and the countryside have long been recognised as a source of spiritual or emotional fulfilment, few have explored the extent to which tourism, itself often claimed to be a sacred experience, offers an emotional/spiritual dimension in the rural context. This paper addresses that literature gap. Using in-depth interviews with rural tourists in the English Lake District, it explores the extent to which, within respondents’ individual understanding of spirituality, a relationship exists between sense of place and deeper, emotional experiences and, especially, whether participation in rural tourism may induce spiritual or emotional responses. The research revealed that all respondents felt a strong attachment to the Lake District; similarly, and irrespective of their openness to spirituality, engaging in rural tourism activities resulted in highly emotive experiences for all respondents, the description/interpretation of such experiences being determined by individual “beliefs”. However, sense of place was not a prerequisite to emotional or spiritual experiences. Being in and engaging with the landscape � effectively becoming part of it � especially through physical activity is fundamental to emotional responses

ERA-Interim/Land: a global land surface reanalysis data set

ERA-Interim/Land is a global land surface reanalysis data set covering the period 1979–2010. It describes the evolution of soil moisture, soil temperature and snowpack. ERA-Interim/Land is the result of a single 32-year simulation with the latest ECMWF (European Centre for Medium-Range Weather Forecasts) land surface model driven by meteorological forcing from the ERA-Interim atmospheric reanalysis and precipitation adjustments based on monthly GPCP v2.1 (Global Precipitation Climatology Project). The horizontal resolution is about 80 km and the time frequency is 3-hourly. ERA-Interim/Land includes a number of parameterization improvements in the land surface scheme with respect to the original ERA-Interim data set, which makes it more suitable for climate studies involving land water resources. The quality of ERA-Interim/Land is assessed by comparing with ground-based and remote sensing observations. In particular, estimates of soil moisture, snow depth, surface albedo, turbulent latent and sensible fluxes, and river discharges are verified against a large number of site measurements. ERA-Interim/Land provides a global integrated and coherent estimate of soil moisture and snow water equivalent, which can also be used for the initialization of numerical weather prediction and climate models