Diagnosing evapotranspiration responses to water deficit across biomes using deep learning.

Accounting for water limitation is key to determining vegetation sensitivity to drought. Quantifying water limitation effects on evapotranspiration (ET) is challenged by the heterogeneity of vegetation types, climate zones and vertically along the rooting zone. Here, we train deep neural networks using flux measurements to study ET responses to progressing drought conditions. We determine a water stress factor (fET) that isolates ET reductions from effects of atmospheric aridity and other covarying drivers. We regress fET against the cumulative water deficit, which reveals the control of whole-column moisture availability. We find a variety of ET responses to water stress. Responses range from rapid declines of fET to 10% of its water-unlimited rate at several savannah and grassland sites, to mild fET reductions in most forests, despite substantial water deficits. Most sensitive responses are found at the most arid and warm sites. A combination of regulation of stomatal and hydraulic conductance and access to belowground water reservoirs, whether in groundwater or deep soil moisture, could explain the different behaviors observed across sites. This variety of responses is not captured by a standard land surface model, likely reflecting simplifications in its representation of belowground water storage

Undiagnosed diabetes from cross-sectional GP practice data: an approach to identify communities with high likelihood of undiagnosed diabetes

OBJECTIVES To estimate undiagnosed diabetes prevalence from general practitioner (GP) practice data and identify areas with high levels of undiagnosed and diagnosed diabetes. DESIGN Data from the North-West Adelaide Health Survey (NWAHS) were used to develop a model which predicts total diabetes at a small area. This model was then applied to cross-sectional data from general practices to predict the total level of expected diabetes. The difference between total expected and already diagnosed diabetes was defined as undiagnosed diabetes prevalence and was estimated for each small area. The patterns of diagnosed and undiagnosed diabetes were mapped to highlight the areas of high prevalence. SETTING North-West Adelaide, Australia. PARTICIPANTS This study used two population samples-one from the de-identified GP practice data (n=9327 active patients, aged 18 years and over) and another from NWAHS (n=4056, aged 18 years and over). MAIN OUTCOME MEASURES Total diabetes prevalence, diagnosed and undiagnosed diabetes prevalence at GP practice and Statistical Area Level 1. RESULTS Overall, it was estimated that there was one case of undiagnosed diabetes for every 3-4 diagnosed cases among the 9327 active patients analysed. The highest prevalence of diagnosed diabetes was seen in areas of lower socioeconomic status. However, the prevalence of undiagnosed diabetes was substantially higher in the least disadvantaged areas. CONCLUSIONS The method can be used to estimate population prevalence of diabetes from general practices wherever these data are available. This approach both flags the possibility that undiagnosed diabetes may be a problem of less disadvantaged social groups, and provides a tool to identify areas with high levels of unmet need for diabetes care which would enable policy makers to apply geographic targeting of effective interventions

Burden of early, advanced and metastatic breast cancer in The Netherlands

BACKGROUND: The aim of this study was to estimate the total economic and health related burden of breast cancer in the Netherlands. METHODS: Data on incidence, prevalence, mortality and survival were extracted from the Dutch National Cancer Registry and were used to calculate the economic and health related burden of breast cancer for overall, DCIS (stage 0), early- (stage I), locally advanced- (stage II-III) and metastatic- (stage IV) breast cancer by age groups and by year (if applicable). RESULTS: The overall incidence of breast cancer increased from 103.4 up to 153.2 per 100,000 women between 1990 and 2014. The increase was driven by DCIS and early breast cancer as the incidence of locally advanced and metastatic breast cancer remained stable. Between 1990 and 2014, ten-year overall survival rates increased from 87% to 93% for early breast cancer, 41% to 62% for locally advanced- and from 6% to 9% for metastatic disease. Annually, breast cancer in the Netherlands is responsible for approximately 3100 deaths, 26,000 life years lost, 65,000 Disability Adjusted Life Years (DALYs) and an economic burden of €1.27 billion. CONCLUSIONS: This study provides a comprehensive assessment of the burden of breast cancer and subsequent trends over time in the Netherlands

Spatial inequities of mental health nurses in rural and remote Australia

Abstract Despite an increased burden from chronic mental health conditions, access to effective mental health services in rural and remote areas is limited, and these services remain spatially undefined. We examine the spatial availability of mental health nurses across local government areas in Australia and identify gaps in mental health service delivery capacity in a finer-grained level than the state/territory data. A spatial distribution of mental health nurses was conducted. We utilized the 2017 National Health Workforce Dataset which was aggregated to LGA level based on the 2018 Australian Bureau Statistics (ABS) Data. The availability of mental health nurses was measured using the full time equivalent (FTE) rates per 100 000 population. We calculated the proportion of LGAs with zero total FTE rates based on remoteness categories. We also compared the mean of total FTE rates based on remoteness categories using analysis of variance. A spatial distribution of mental health nurses was visualized using GIS software for total FTE rates. Our analysis included 544 LGA across Australia, with 24.8% being defined as remote and very remote. The mean total FTE for mental health nurses per 100 000 populations is 56.6 (±132.2) with a median of 17.4 (IQR: 61.8). A wide standard deviation reflects unequal distribution of mental health nurses across LGAs. The availability of total FTE rates for mental health nurses per 100 000 populations is significantly lower in remote and very remote LGAs in comparison with major cities. As many as 35.1% of LGAs across Australia have no FTE for mental health nurses with 46% are remote and very remote. Our study reflects the existing unequal distribution of mental health nurses between metropolitan/urban setting and rural and remote areas. We suggest three broad strategies to address these spatial inequities: improving supply and data information systems; revisiting task-shifting strategies, retraining the existing health workforce to develop skills necessary for mental health care to rural and remote communities; and incorporating the provision of mental health services within expanding innovative delivery models including consumer-led, telemedicine and community-based groups

The determinants of vulnerability to currency crises: country-specific factors versus regional factors

We investigate the determinants of exchange market pressures (EMP) for some new EU member states at both the national and regional levels, where macroeconomic and financial variables are considered as potential sources. The regional common factors are extracted from these variables by using dynamic factor analysis. The linear empirical analysis, in general, highlights the importance of country-specific factors to defend themselves against vulnerability in their external sectors. Yet, given a significant impact of the common component in credit on EMP, a contagion effect is apparent through the conduit of credit market integration across these countries under investigation

Undiagnosed diabetes from cross-sectional GP practice data: an approach to identify communities with high likelihood of undiagnosed diabetes

OBJECTIVES: To estimate undiagnosed diabetes prevalence from general practitioner (GP) practice data and identify areas with high levels of undiagnosed and diagnosed diabetes. DESIGN: Data from the North-West Adelaide Health Survey (NWAHS) were used to develop a model which predicts total diabetes at a small area. This model was then applied to cross-sectional data from general practices to predict the total level of expected diabetes. The difference between total expected and already diagnosed diabetes was defined as undiagnosed diabetes prevalence and was estimated for each small area. The patterns of diagnosed and undiagnosed diabetes were mapped to highlight the areas of high prevalence. SETTING: North-West Adelaide, Australia. PARTICIPANTS: This study used two population samples-one from the de-identified GP practice data (n=9327 active patients, aged 18 years and over) and another from NWAHS (n=4056, aged 18 years and over). MAIN OUTCOME MEASURES: Total diabetes prevalence, diagnosed and undiagnosed diabetes prevalence at GP practice and Statistical Area Level 1. RESULTS: Overall, it was estimated that there was one case of undiagnosed diabetes for every 3-4 diagnosed cases among the 9327 active patients analysed. The highest prevalence of diagnosed diabetes was seen in areas of lower socioeconomic status. However, the prevalence of undiagnosed diabetes was substantially higher in the least disadvantaged areas. CONCLUSIONS: The method can be used to estimate population prevalence of diabetes from general practices wherever these data are available. This approach both flags the possibility that undiagnosed diabetes may be a problem of less disadvantaged social groups, and provides a tool to identify areas with high levels of unmet need for diabetes care which would enable policy makers to apply geographic targeting of effective interventions.Nasser Bagheri, Ian McRae, Paul Konings, Danielle Butler, Kirsty Douglas, Peter Del Fante, Robert Adam

Calorie restriction-like effects of 30 days of resveratrol supplementation on energy metabolism and metabolic profile in obese humans

Resveratrol is a natural compound that affects energy metabolism and mitochondrial function and serves as a calorie restriction mimetic, at least in animal models of obesity. Here we treated 11 healthy, obese men with placebo and 150 mg/day resveratrol in a randomized double-blind cross-over study for 30 days. Resveratrol significantly reduced sleeping- and resting metabolic rate. In muscle, resveratrol activated AMPK, increased SIRT1 and PGC-1α protein levels, increased citrate synthase activity without change in mitochondrial content, and improved muscle mitochondrial respiration on a fatty acid-derived substrate. Furthermore, resveratrol elevated intramyocellular lipid levels, and decreased intrahepatic lipid content, circulating glucose, triglycerides, alanine-aminotransferase, and inflammation markers. Systolic blood pressure dropped and HOMA index improved after resveratrol. In the postprandial state, adipose tissue lipolysis and plasma fatty acid and glycerol decreased. In conclusion, we demonstrate that 30 days of resveratrol supplementation induces metabolic changes in obese humans, mimicking the effects of calorie restriction