Using image segmentation models to analyse high-resolution earth observation data: new tools to monitor disease risks in changing environments.

BACKGROUND: In the near future, the incidence of mosquito-borne diseases may expand to new sites due to changes in temperature and rainfall patterns caused by climate change. Therefore, there is a need to use recent technological advances to improve vector surveillance methodologies. Unoccupied Aerial Vehicles (UAVs), often called drones, have been used to collect high-resolution imagery to map detailed information on mosquito habitats and direct control measures to specific areas. Supervised classification approaches have been largely used to automatically detect vector habitats. However, manual data labelling for model training limits their use for rapid responses. Open-source foundation models such as the Meta AI Segment Anything Model (SAM) can facilitate the manual digitalization of high-resolution images. This pre-trained model can assist in extracting features of interest in a diverse range of images. Here, we evaluated the performance of SAM through the Samgeo package, a Python-based wrapper for geospatial data, as it has not been applied to analyse remote sensing images for epidemiological studies. RESULTS: We tested the identification of two land cover classes of interest: water bodies and human settlements, using different UAV acquired imagery across five malaria-endemic areas in Africa, South America, and Southeast Asia. We employed manually placed point prompts and text prompts associated with specific classes of interest to guide the image segmentation and assessed the performance in the different geographic contexts. An average Dice coefficient value of 0.67 was obtained for buildings segmentation and 0.73 for water bodies using point prompts. Regarding the use of text prompts, the highest Dice coefficient value reached 0.72 for buildings and 0.70 for water bodies. Nevertheless, the performance was closely dependent on each object, landscape characteristics and selected words, resulting in varying performance. CONCLUSIONS: Recent models such as SAM can potentially assist manual digitalization of imagery by vector control programs, quickly identifying key features when surveying an area of interest. However, accurate segmentation still requires user-provided manual prompts and corrections to obtain precise segmentation. Further evaluations are necessary, especially for applications in rural areas.

Can sodium and potassium measured in timed voids be used as reference instruments for validating self-report instruments? Results from a urine calibration study.

BACKGROUND: Sodium and potassium measured in 24-h urine collections are often used as reference measurements to validate self-reported dietary intake instruments. OBJECTIVES: To evaluate whether collection and analysis of a limited number of urine voids at specified times during the day ("timed voids") can provide alternative reference measurements, and to identify their optimal number and timing. METHODS: We used data from a urine calibration study among 441 adults aged 18-39 y. Participants collected each urine void in a separate container for 24 h and recorded the collection time. For the same day, they reported dietary intake using a 24-h recall. Urinary sodium and potassium were analyzed in a 24-h composite sample and in 4 timed voids (morning, afternoon, evening, and overnight). Linear regression models were used to develop equations predicting log-transformed 24-h urinary sodium or potassium levels using each of the 4 single timed voids, 6 pairs, and 4 triples. The equations also included age, sex, race, BMI (kg/m2), and log creatinine. Optimal combinations minimizing the mean squared prediction error were selected, and the observed and predicted 24-h levels were then used as reference measures to estimate the group bias and attenuation factors of the 24-h dietary recall. These estimates were compared. RESULTS: Optimal combinations found were as follows: single voids-evening; paired voids-afternoon + overnight (sodium) and morning + evening (potassium); and triple voids-morning + evening + overnight (sodium) and morning + afternoon + evening (potassium). Predicted 24-h urinary levels estimated 24-h recall group biases and attenuation factors without apparent bias, but with less precision than observed 24-h urinary levels. To recover lost precision, it was estimated that sample sizes need to be increased by ∼2.6-2.7 times for a single void, 1.7-2.1 times for paired voids, and 1.5-1.6 times for triple voids. CONCLUSIONS: Our results provide the basis for further development of new reference biomarkers based on timed voids. CLINICAL TRIAL REGISTRY: clinicaltrials.gov as NCT01631240.

Validation of Total Water Intake from the Automated Self-Administered 24-h Recall, 4-d Food Records, and a Food Frequency Questionnaire Using Doubly Labeled Water.

BACKGROUND: Although prior evidence indicates that water intake is important for health, the ability to accurately measure community-dwelling intake is limited. Only a few studies have evaluated self-reported water intake against an objective recovery biomarker. OBJECTIVES: The aim was to compare preformed water intakes (all sources including food) by multiple Automated Self-Administered 24-h recalls (ASA24s), food frequency questionnaires (FFQs), and 4-d food records (4DFRs) against a recovery biomarker, doubly labeled water (DLW), to assess measurement error. METHODS: Over 1 y, 1082 women and men (50%), aged 50 to 74 y, were asked to complete 6 ASA24s, 2 FFQs, 2 unweighted 4DFRs, and an administration of DLW (n = 686). Geometric means of water intake by self-report tools were compared with DLW. Attenuation factors and correlation coefficients between self-reported and the recovery biomarker (DLW) were estimated. RESULTS: Mean water intakes by DLW were 2777 mL/d (interquartile range, 2350 to 3331) in women and 3243 mL/d (interquartile range, 2720 to 3838) in men. Compared with DLW, water intake was underestimated by 18% to 31% on ASA24s and 43% to 44% on 4DFRs. Estimated geometric means from FFQs differed from DLW by -1% to +13%. For a single ASA24, FFQ, and 4DFR, attenuation factors were 0.28, 0.27, and 0.32 and correlation coefficients were 0.46, 0.48, and 0.49, respectively. Repeated use of 6 ASA24s, 2 FFQs, and 2 4DFRs improved attenuation factors to 0.43, 0.32, and 0.39 and correlation coefficients to 0.58, 0.53, and 0.54, respectively. CONCLUSIONS: FFQs may better estimate population means for usual water intake compared with ASA24 and 4DFR. Similar attenuation factors and correlation coefficients across all self-report tools indicate that researchers have 3 feasible options if the goal is understanding intake-disease relationships. The findings are useful for planning future nutrition studies that set policy priorities for populations and to understand the health impact of water. This trial was registered at clinicaltrials.gov as NCT03268577.

Urinary Sucrose and Fructose From Spot Urine May Be Used as a Predictive Biomarker of Total Sugar Intake-Findings From a Controlled Feeding Study.

BACKGROUND: Recently, we confirmed 24-h urinary sucrose plus fructose (24 uSF) as a predictive biomarker of total sugar intake. However, the collection of 24-h urine samples has limited feasibility in population studies. OBJECTIVE: We investigated the utility of the urinary sucrose plus fructose (uSF) biomarker measured in spot urine as a measure of 24 uSF biomarker and total sugar intake. METHODS: Hundred participants, 18-70 y of age, from the Phoenix Metropolitan Area completed a 15-d feeding study. For 2 of the 8 collected 24-h urine samples, each spot urine sample was collected in a separate container. We considered 4 timed voids of the day [morning (AM) void: first void 08:30-12:30; afternoon (PM) void: first void 12:31-17:30; evening (EVE) void: first void 17:31-12:00; and next-day (ND) void: first void 04:00-12:00]. We investigated the performance of uSF from 1 void, and uSF combined from 2 and 3 voids as a measure of 24 uSF and sugar intake. RESULTS: The biomarker averaged from PM/EVE void strongly correlated with 24 uSF (partial r = 0.75). The 24 uSF predicted from the PM/EVE combination was significantly associated with observed sugar intake and was selected for building the calibrated biomarker equation (marginal R2 = 0.36). Spot urine-based calibrated biomarker, ie, biomarker-estimated sugar intake was moderately correlated with the 15-d mean-observed sugar intake (r = 0.50). CONCLUSIONS: uSF measured from a PM and EVE void may be used to generate biomarker-based sugar intake estimate when collecting 24-h urine samples is not feasible, pending external validation.

Do biodiversity monitoring citizen science surveys meet the core principles of open science practices?

Citizen science (CS), as an enabler of open science (OS) practices, is a low-cost and accessible method for data collection in biodiversity monitoring, which can empower and educate the public both on scientific research priorities and on environmental change. Where OS increases research transparency and scientific democratisation; if properly implemented, CS should do the same. Here, we present the findings of a systematic review exploring "openness" of CS in biodiversity monitoring. CS projects were scored between - 1 (closed) and 1 (open) on their adherence to defined OS principles: accessible data, code, software, publication, data management plans, and preregistrations. Openness scores per principle were compared to see where OS is more frequently utilised across the research process. The relationship between interest in CS and openness within the practice was also tested. Overall, CS projects had an average open score of 0.14. There was a significant difference in open scores between OS principles (p = < 0.0001), where "open data" was the most adhered to practice compared to the lowest scores found in relation to preregistrations. The apparent level of interest in CS was not shown to correspond to a significant increase in openness within CS (p = 0.8464). These results reveal CS is not generally "open" despite being an OS approach, with implications for how the public can interact with the research that they play an active role in contributing to. The development of systematic recommendations on where and how OS can be implemented across the research process in citizen science projects is encouraged.

Evaluating a Model of Added Sugar Intake Based on Amino Acid Carbon Isotope Ratios in a Controlled Feeding Study of U.S. Adults.

Previous studies suggest that amino acid carbon stable isotope ratios (CIRAAs) may serve as biomarkers of added sugar (AS) intake, but this has not been tested in a demographically diverse population. We conducted a 15-day feeding study of U.S. adults, recruited across sex, age, and BMI groups. Participants consumed personalized diets that resembled habitual intake, assessed using two consecutive 7-day food records. We measured serum (n = 99) CIRAAs collected at the end of the feeding period and determined correlations with diet. We used forward selection to model AS intake using participant characteristics and 15 CIRAAs. This model was internally validated using bootstrap optimism correction. Median (25th, 75th percentile) AS intake was 65.2 g/day (44.7, 81.4) and 9.5% (7.2%, 12.4%) of energy. The CIR of alanine had the highest, although modest, correlation with AS intake (r = 0.32, p = 0.001). Serum CIRAAs were more highly correlated with animal food intakes, especially the ratio of animal to total protein. The AS model included sex, body weight and 6 CIRAAs. This model had modest explanatory power (multiple R2 = 0.38), and the optimism-corrected R2 was lower (R2 = 0.15). Further investigations in populations with wider ranges of AS intake are warranted.

Establishing 24-Hour Urinary Sucrose Plus Fructose as a Predictive Biomarker for Total Sugars Intake.

BACKGROUND: Twenty-four-hour urinary sucrose and fructose (24uSF) has been studied as a biomarker of total sugars intake in two feeding studies conducted in the United Kingdom (UK) and Arizona (AZ). We compare the biomarker performance in these populations, testing whether it meets the criteria for a predictive biomarker. METHODS: The UK and AZ feeding studies included 13 and 98 participants, respectively, aged 18 to 70 years, consuming their usual diet under controlled conditions. Linear mixed models relating 24uSF to total sugars and personal characteristics were developed in each study and compared. The AZ calibrated biomarker equation was applied to generate biomarker-estimated total sugars intake in UK participants. Stability of the model across AZ study subpopulations was also examined. RESULTS: Model coefficients were similar between the two studies [e.g., log(total sugars): UK 0.99, AZ 1.03, P = 0.67], as was the ratio of calibrated biomarker person-specific bias to between-person variance (UK 0.32, AZ 0.25, P = 0.68). The AZ equation estimated UK log(total sugar intakes) with mean squared prediction error of 0.27, similar to the AZ study estimate (0.28). Within the AZ study, the regression coefficients of log(total sugars) were similar across age, gender, and body mass index subpopulations. CONCLUSIONS: Similar model coefficients in the two studies and good prediction of UK sugar intakes by the AZ equation suggest that 24uSF meets the criteria for a predictive biomarker. Testing the biomarker performance in other populations is advisable. IMPACT: Applications of the 24uSF biomarker will enable improved assessment of the role of sugars intake in risk of chronic disease, including cancer. See related commentary by Prentice, p. 1151.

Measurement Error Affecting Web- and Paper-Based Dietary Assessment Instruments: Insights From the Multi-Cohort Eating and Activity Study for Understanding Reporting Error.

Few biomarker-based validation studies have examined error in online self-report dietary assessment instruments, and food records (FRs) have been considered less than food frequency questionnaires (FFQs) and 24-hour recalls (24HRs). We investigated measurement error in online and paper-based FFQs, online 24HRs, and paper-based FRs in 3 samples drawn primarily from 3 cohorts, comprising 1,393 women and 1,455 men aged 45-86 years. Data collection occurred from January 2011 to October 2013. Attenuation factors and correlation coefficients between reported and true usual intake for energy, protein, sodium, potassium, and respective densities were estimated using recovery biomarkers. Across studies, average attenuation factors for energy were 0.07, 0.07, and 0.19 for a single FFQ, 24HR, and FR, respectively. Correlation coefficients for energy were 0.24, 0.23, and 0.40, respectively. Excluding energy, the average attenuation factors across nutrients and studies were 0.22 for a single FFQ, 0.22 for a single 24HR, and 0.51 for a single FR. Corresponding correlation coefficients were 0.31, 0.34, and 0.53, respectively. For densities (nutrient expressed relative to energy), the average attenuation factors across studies were 0.37, 0.17, and 0.50, respectively. The findings support prior research suggesting different instruments have unique strengths that should be leveraged in epidemiologic research.

Ecosystem services and disservices in the Luanhe River Basin in China under past, current and future land uses: implications for the sustainable development goals.

Understanding how ecosystem services (ES) and ecosystem disservices (EDS) are affected by human-induced landscape changes is important to minimise trade-offs and maximise synergies between Sustainable Development Goals (SDGs) and targets, and for equitable development across governance scales. However, limited research investigates how ES and EDS can change under past, current, and future land uses. This study, conducted in the Luanhe River Basin (LRB), demonstrates the interaction between humans and the environment under past, current, and future land uses at the river basin scale in China, using a stakeholders' participatory capacity matrix to characterise both ES and EDS. Results indicate that forests and water bodies provided the highest overall ES capacity, while the lowest scores were reached in built-up and unused land areas. Built-up land and cropland provided the highest overall EDS, while the lowest EDS scores were for water bodies. By applying the ecosystem services potential index (ESPI) and ecosystem disservices potential index (EDSPI), we found that the ESPI of all the ES declined from 1980 to 2018 and would continue to decline until 2030 without sustainable and conservation development strategies in the LRB. The EDSPI under all future scenarios in 2030 was projected to increase compared to the baseline in 1980. This study recommends establishing and implementing sustainable environmental protection policies and cross-regional and trans-provincial eco-compensation schemes for minimising trade-offs in ES. The study proposes an integrated research framework that could be useful for understanding the effect of historical and future human-environment interactions on ES and EDS, and SDGs achievement. Supplementary Information: The online version contains supplementary material available at 10.1007/s11625-021-01078-8.

An evaluation of the serum carbon isotope ratio as a candidate predictive biomarker of the dietary animal protein ratio (animal protein/total protein) in a 15-day controlled feeding study of US adults.

BACKGROUND: The serum natural abundance carbon isotope ratio (CIR) was recently identified as a candidate biomarker of animal protein intake in postmenopausal women. Such a biomarker would help clarify the relation between dietary protein source (plant or animal) and chronic disease risk. OBJECTIVES: We aimed to evaluate the performance of the serum CIR as a biomarker of dietary protein source in a controlled feeding study of men and women of diverse age and BMI. METHODS: We conducted a 15-d feeding study of 100 adults (age: 18-70 y, 55% women) in Phoenix, AZ. Participants were provided individualized diets that approximated habitual food intakes. Serum was collected at the end of the feeding period for biomarker measurements. RESULTS: Median [IQR] animal protein intake was 67 g/d [55-88 g/d], which was 64% of total protein. The serum CIR was positively correlated with animal protein and inversely correlated with plant protein intake, leading to a strong correlation (r2 = 0.76) with the dietary animal protein ratio (APR; animal/total protein). Regressing serum CIR on the APR, serum nitrogen isotope ratio (NIR), gender, age, and body weight generated an R2 of 0.78. Following the measurement error model for predictive biomarkers, the resulting regression equation was then inverted to develop a calibrated biomarker equation for APR. Added sugars ratio (added/total sugars intake) and corn intakes also influenced the serum CIR but to a much lesser degree than the APR; variations in these intakes had only small effects on biomarker-estimated APR. CONCLUSIONS: Based on our findings in this US cohort of mixed sex and age, we propose the serum CIR alongside NIR as a predictive dietary biomarker of the APR. We anticipate using this biomarker to generate calibrated estimates based on self-reported intake and ultimately to obtain more precise disease risk estimates according to dietary protein source.

Modelling land system evolution and dynamics of terrestrial carbon stocks in the Luanhe River Basin, China: a scenario analysis of trade-offs and synergies between sustainable development goals.

A more holistic understanding of land use and land cover (LULC) will help minimise trade-offs and maximise synergies, and lead to improved future land use management strategies for the attainment of Sustainable Development Goals (SDGs). However, current assessments of future LULC changes rarely focus on the multiple demands for goods and services, which are related to the synergies and trade-offs between SDGs and their targets. In this study, the land system (combinations of land cover and land use intensity) evolution trajectories of the Luanhe River Basin (LRB), China, and major challenges that the LRB may face in 2030, were explored by applying the CLUMondo and InVEST models. The results indicate that the LRB is likely to experience agricultural intensification and urban growth under all four scenarios that were explored. The cropland intensity and the urban growth rate were much higher under the historical trend (Trend) scenario compared to those with more planning interventions (Expansion, Sustainability, and Conservation scenarios). Unless the forest area and biodiversity conservation targets are implemented (Conservation scenario), the forest areas are projected to decrease by 2030. The results indicate that water scarcity in the LRB is likely to increase under all scenarios, and the carbon storage will increase under the Conservation scenario but decrease under all other scenarios by 2030. Our methodological framework and findings can guide regional sustainable development in the LRB and other large river basins in China, and will be valuable for policy and planning purposes to the pursuance of SDGs at the sub-national scale. Supplementary Information: The online version contains supplementary material available at 10.1007/s11625-021-01004-y.

Development and Validation of a Risk Prediction Model for Second Primary Lung Cancer.

BACKGROUND: With advancing therapeutics, lung cancer (LC) survivors are rapidly increasing in number. Although mounting evidence suggests LC survivors have high risk of second primary lung cancer (SPLC), there is no validated prediction model available for clinical use to identify high-risk LC survivors for SPLC. METHODS: Using data from 6325 ever-smokers in the Multiethnic Cohort (MEC) study diagnosed with initial primary lung cancer (IPLC) in 1993-2017, we developed a prediction model for 10-year SPLC risk after IPLC diagnosis using cause-specific Cox regression. We evaluated the model's clinical utility using decision curve analysis and externally validated it using 2 population-based data-Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) and National Lung Screening Trial (NLST)-that included 2963 and 2844 IPLC (101 and 93 SPLC cases), respectively. RESULTS: Over 14 063 person-years, 145 (2.3%) ever-smoking IPLC patients developed SPLC in MEC. Our prediction model demonstrated a high predictive accuracy (Brier score = 2.9, 95% confidence interval [CI] = 2.4 to 3.3) and discrimination (area under the receiver operating characteristics [AUC] = 81.9%, 95% CI = 78.2% to 85.5%) based on bootstrap validation in MEC. Stratification by the estimated risk quartiles showed that the observed SPLC incidence was statistically significantly higher in the 4th vs 1st quartile (9.5% vs 0.2%; P < .001). Decision curve analysis indicated that in a wide range of 10-year risk thresholds from 1% to 20%, the model yielded a larger net-benefit vs hypothetical all-screening or no-screening scenarios. External validation using PLCO and NLST showed an AUC of 78.8% (95% CI = 74.6% to 82.9%) and 72.7% (95% CI = 67.7% to 77.7%), respectively. CONCLUSIONS: We developed and validated a SPLC prediction model based on large population-based cohorts. The proposed prediction model can help identify high-risk LC patients for SPLC and can be incorporated into clinical decision making for SPLC surveillance and screening.

Investigating the performance of 24-h urinary sucrose and fructose as a biomarker of total sugars intake in US participants - a controlled feeding study.

BACKGROUND: Developing approaches for the objective assessment of sugars intake in population research is crucial for generating reliable disease risk estimates, and evidence-based dietary guidelines. Twenty-four-hour urinary sucrose and fructose (24uSF) was developed as a predictive biomarker of total sugars intake based on 3 UK feeding studies, yet its performance as a biomarker of total sugars among US participants is unknown. OBJECTIVES: To investigate the performance of 24uSF as a biomarker of sugars intake among US participants, and to characterize its use. METHODS: Ninety-eight participants, aged 18-70 y, consumed their usual diet under controlled conditions of a feeding study for 15 d, and collected 8 nonconsecutive 24-h urines measured for sucrose and fructose. RESULTS: A linear mixed model regressing log 24uSF biomarker on log total sugars intake along with other covariates explained 56% of the biomarker variance. Total sugars intake was the strongest predictor in the model (Marginal R2 = 0.52; P <0.0001), followed by sex (P = 0.0002) and log age (P = 0.002). The equation was then inverted to solve for total sugars intake, thus generating a calibrated biomarker equation. Calibration of the biomarker produced mean biomarker-based log total sugars of 4.79 (SD = 0.59), which was similar to the observed log 15-d mean total sugars intake of 4.69 (0.35). The correlation between calibrated biomarker and usual total sugars intake was 0.59 for the calibrated biomarker based on a single biomarker measurement, and 0.76 based on 4 biomarker repeats spaced far apart. CONCLUSIONS: In this controlled feeding study, total sugars intake was the main determinant of 24uSF confirming its utility as a biomarker of total sugars in this population. Next steps will include validation of stability assumptions of the biomarker calibration equation proposed here, which will allow its use as an instrument for dietary validation and measurement error correction in diet-disease association studies.

Examining the association between meal context and diet quality: an observational study of meal context in older adults.

BACKGROUND: Though a healthy diet is widely associated with reduced risks for chronic disease and mortality, older adults in the U.S. on average do not meet dietary recommendations. Given that few studies have examined the association between meal context on older adult diet quality, the aims of this study were (1) to compare the dietary quality of foods consumed in different meal contexts, as measured by the Healthy Eating Index 2015 (HEI-2015): meal location, the presence of others, and the use of electronic screens; and (2) to examine which components of the HEI-2015 drove differences in HEI-2015 total scores by meal context. METHODS: Interactive Diet and Activity Tracking in AARP study participants (50-74 years) completed the Automated Self-Administered 24-h Dietary Assessment tool (ASA24, version 2011) that included foods and beverages consumed and three meal contexts: "at home" versus "away from home," "alone" versus "with company," and "with screen time" versus "without screen time." A population ratio approach was used to estimate HEI-2015 total and component scores for all food items consumed by meal context. Mean HEI-2015 scores (range: 0-100) for the three meal context variables were compared using t-tests. Where there were significant differences in total scores, additional t-tests were used to explore which HEI-2015 components were the primary drivers. All tests were stratified by sex and adjusted for multiple comparisons. RESULTS: HEI-2015 scores were lower for meals consumed away vs. at home (mean difference (SE), males: - 8.23 (1.02); females: - 7.29 (0.93); both p < 0.0001) and for meals eaten with vs. without company (mean difference (SE), males: - 6.61 (1.06); females: - 7.34 (1.18); both p < 0.0001). There was no difference comparing with vs. without screen time. When HEI-2015 component scores were examined, fewer total fruits, whole grains, and dairy were consumed away from home or with company; more total vegetables and greens and beans, and less added sugars were consumed with company. CONCLUSIONS: Our findings suggest an association between the behavior cues of meal location and companions and dietary choices among older adults. Future studies can explore the individual and interactive effects of meal context on diet quality and subsequent health outcomes.

The role of stress concentration in calcified bicuspid aortic valve.

Calcific aortic valve disease (CAVD) is the most common valvular heart disease in the aging population, and is now believed to be a slow, progressive, yet actively regulated process. The disease progression can be divided into two phases: initiation phase associated with lipid deposition and inflammation response, and the later propagation phase with active calcification growth. It has been hypothesized that elevated mechanical stress plays a major role in both phases of disease progression. In order to identify a direct link between leaflet stress and calcification development, we performed patient-specific finite-element (FE) analyses of six bicuspid aortic valves (BAV), where the leaflets, raphe and calcifications were all considered. The results showed that during the initiation phase, calcium buildup is likely to occur along the leaflet-root attachment curve (ATC), and the commissures, which are subject to the most drastic changes in stress during the cardiac cycle. During the propagation phase, the presence of calcification would lead to local stress concentration along its boundary, hence further calcification growth. Three patterns of calcification formation were identified on BAV leaflets: 'radial', which extended radially from ATC into the leaflet belly region; 'commissure to commissure', which extended circumferentially along the coaptation; and 'raphe', which located in the vicinity of the raphe. Furthermore, we found a strong correlation between regions with a high risk of calcium buildup and regions with elevated mechanical stress. The high-risk regions predicted at diastole on the non-calcified leaflet from FE models agreed reasonably well with the in vivo calcification locations, which indicates that patient-specific FE modelling could help us to evaluate the potential risk of calcification formation in the early stage of CAVD.

Standardizing the assessment of emotional development in adults with intellectual and developmental disability.

OBJECTIVE: The Scale of Emotional Development-Short (SED-S) is an instrument to assess the level of emotional development (ED) in people with intellectual and developmental disability. Index cases are developed as a didactic tool to standardize the application of the scale. METHOD: In a stepwise process, a European working group from six countries developed five index cases, one for each level of ED. All cases were first scored by 20 raters using the SED-S and then rephrased to reduce inter-rater variations (SD > 0.5). RESULTS: All five index cases yielded overall ratings that matched the intended level of ED. Across the range of ED, Regulating Affect needed rephrasing most to ensure a distinct description within each level of ED. CONCLUSIONS: The tri-lingual, cross-cultural evolution of five index cases contributes to a standardized application of the SED-S and can serve as training material to improve the inter-rater reliability of the SED-S across different cultures and languages.

Scale of emotional development-Short.

BACKGROUND: Intellectual disability (ID) is often accompanied by delays in emotional development (ED) that may result in challenging behavior. Insight into emotional functioning is crucial for appropriate diagnostic assessment in adults with ID. However, few standardized assessment instruments are available. AIMS: The aim of this study was to develop a short, psychometrically sound instrument for assessing levels of ED in individuals with ID: The Scale of Emotional Development - Short (SED-S), which can be applied to adults. METHODS AND PROCEDURES: The Scale for ED - Revised2 (SED-R2) was taken as a point of departure. In a first step, the validity and observability of the items (N=556) in the SED-R2 were assessed by 30 experts from Germany, Belgium, and The Netherlands. The SED-S was then constituted in a consecutive consensus process, in which items to be included were selected based on their assessments and subsequently rephrased, and in which the structure and method of administering the new scale were agreed upon. OUTCOMES AND RESULTS: The SED-S consists of 200 binary items describing five levels of emotional functioning (reference ages: 0-12 years) within eight domains: Relating to His/Her Own Body, Relating to Significant Others, Dealing with Change - Object Permanence, Differentiating Emotions, Relating to Peers, Engaging with the Material World, Communicating with Others, and Regulating Affect. CONCLUSIONS AND IMPLICATIONS: The SED-S offers an empirical-based, practical tool to assessing ED in adults with ID. Further research will be needed to meet the requirements of a standardized diagnostic instrument.

Upland vegetation mapping using Random Forests with optical and radar satellite data.

Uplands represent unique landscapes that provide a range of vital benefits to society, but are under increasing pressure from the management needs of a diverse number of stakeholders (e.g. farmers, conservationists, foresters, government agencies and recreational users). Mapping the spatial distribution of upland vegetation could benefit management and conservation programmes and allow for the impacts of environmental change (natural and anthropogenic) in these areas to be reliably estimated. The aim of this study was to evaluate the use of medium spatial resolution optical and radar satellite data, together with ancillary soil and topographic data, for identifying and mapping upland vegetation using the Random Forests (RF) algorithm. Intensive field survey data collected at three study sites in Ireland as part of the National Parks and Wildlife Service (NPWS) funded survey of upland habitats was used in the calibration and validation of different RF models. Eight different datasets were analysed for each site to compare the change in classification accuracy depending on the input variables. The overall accuracy values varied from 59.8% to 94.3% across the three study locations and the inclusion of ancillary datasets containing information on the soil and elevation further improved the classification accuracies (between 5 and 27%, depending on the input classification dataset). The classification results were consistent across the three different study areas, confirming the applicability of the approach under different environmental contexts.

Forest Cover Estimation in Ireland Using Radar Remote Sensing: A Comparative Analysis of Forest Cover Assessment Methodologies.

Quantification of spatial and temporal changes in forest cover is an essential component of forest monitoring programs. Due to its cloud free capability, Synthetic Aperture Radar (SAR) is an ideal source of information on forest dynamics in countries with near-constant cloud-cover. However, few studies have investigated the use of SAR for forest cover estimation in landscapes with highly sparse and fragmented forest cover. In this study, the potential use of L-band SAR for forest cover estimation in two regions (Longford and Sligo) in Ireland is investigated and compared to forest cover estimates derived from three national (Forestry2010, Prime2, National Forest Inventory), one pan-European (Forest Map 2006) and one global forest cover (Global Forest Change) product. Two machine-learning approaches (Random Forests and Extremely Randomised Trees) are evaluated. Both Random Forests and Extremely Randomised Trees classification accuracies were high (98.1-98.5%), with differences between the two classifiers being minimal (<0.5%). Increasing levels of post classification filtering led to a decrease in estimated forest area and an increase in overall accuracy of SAR-derived forest cover maps. All forest cover products were evaluated using an independent validation dataset. For the Longford region, the highest overall accuracy was recorded with the Forestry2010 dataset (97.42%) whereas in Sligo, highest overall accuracy was obtained for the Prime2 dataset (97.43%), although accuracies of SAR-derived forest maps were comparable. Our findings indicate that spaceborne radar could aid inventories in regions with low levels of forest cover in fragmented landscapes. The reduced accuracies observed for the global and pan-continental forest cover maps in comparison to national and SAR-derived forest maps indicate that caution should be exercised when applying these datasets for national reporting.

Chromosome inversions, adaptive cassettes and the evolution of species' ranges.

A chromosome inversion can spread when it captures locally adapted alleles or when it is introduced into a species by hybridization with adapted alleles that were previously absent. We present a model that shows how both processes can cause a species range to expand. Introgression of an inversion that carries novel, locally adapted alleles is a particularly powerful mechanism for range expansion. The model supports the earlier proposal that introgression of an inversion triggered a large range expansion of a malaria mosquito. These results suggest a role for inversions as cassettes of genes that can accelerate adaptation by crossing species boundaries, rather than protecting genomes from introgression.