Comparison of direct and indirect soil organic carbon prediction at farm field scale.

To advance sustainable and resilient agricultural management policies, especially during land use changes, it is imperative to monitor, report, and verify soil organic carbon (SOC) content rigorously to inform its stock. However, conventional methods often entail challenging, time-consuming, and costly direct soil measurements. Integrating data from long-term experiments (LTEs) with freely available remote sensing (RS) techniques presents exciting prospects for assessing SOC temporal and spatial change. The objective of this study was to develop a low-cost, field-based statistical model that could be used as a decision-making aid to understand the temporal and spatial variation of SOC content in temperate farmland under different land use and management. A ten-year dataset from the North Wyke Farm Platform, a 20-field, LTE system established in southwestern England in 2010, was used as a case study in conjunction with an RS dataset. Linear, additive and mixed regression models were compared for predicting SOC content based upon combinations of environmental variables that are freely accessible (termed open) and those that require direct measurement or farmer questionnaires (termed closed). These included an RS-derived Ecosystem Services Provision Index (ESPI), topography (slope, aspect), weather (temperature, precipitation), soil (soil units, total nitrogen [TN], pH), and field management practices. Additive models (specifically Generalised Additive Models (GAMs)) were found to be the most effective at predicting space-time SOC variability. When the combined open and closed factors (excluding TN) were considered, significant predictors of SOC were: management related to ploughing being the most important predictor, soil unit (class), aspect, and temperature (GAM fit with a normalised RMSE = 9.1%, equivalent to 0.4% of SOC content). The relative strength of the best-fitting GAM with open data only, which included ESPI, aspect, and slope (normalised RMSE = 13.0%, equivalent to 0.6% of SOC content), suggested that this more practical and cost-effective model enables sufficiently accurate prediction of SOC.

Effects of Post-Anthesis High-Temperature Stress on Carbon Partitioning and Starch Biosynthesis in a Spring Wheat (Triticum aestivum L.) Adapted to Moderate Growth Temperatures.

This study investigates carbon partitioning in the developing endosperm of a European variety of spring wheat subjected to moderately elevated daytime temperatures (27°C/16°C d/night) from anthesis to grain maturity. Elevated daytime temperatures caused significant reductions in both fresh and dry weights and reduced the starch content of harvested grains compared to plants grown under a 20°C/16°C d/night regimen. Accelerated grain development caused by elevated temperatures was accounted for by representing plant development as thermal time (°C DPA). We examined the effects of high-temperature stress (HTS) on the uptake and partitioning of [U-14C]-sucrose supplied to isolated endosperms. HTS caused reduced sucrose uptake into developing endosperms from the second major grain-filling stage (approximately 260°C DPA) up to maturity. Enzymes involved in sucrose metabolism were unaffected by HTS, whereas key enzyme activities involved in endosperm starch deposition such as ADP-glucose pyrophosphorylase and soluble isoforms of starch synthase were sensitive to HTS throughout grain development. HTS caused a decrease in other major carbon sinks such as evolved CO2, ethanol-soluble material, cell walls and protein. Despite reductions in the labeling of carbon pools caused by HTS, the relative proportions of sucrose taken up by endosperm cells allocated to each cellular pool remain unchanged, except for evolved CO2, which increased under HTS and may reflect enhanced respiratory activity. The results of this study show that moderate temperature increases can cause significant yield reductions in some temperate wheat cultivars chiefly through three effects: reduced sucrose uptake by the endosperm, reduced starch synthesis and increased partitioning of carbon into evolved CO2.

A mathematical model for simulating the spread of a disease through a country divided into geographical regions with different population densities.

The SIR (susceptible-infectious-recovered) model is a well known method for predicting the number of people (or animals) in a population who become infected by and then recover from a disease. Modifications can include categories such people who have been exposed to the disease but are not yet infectious or those who die from the disease. However, the model has nearly always been applied to the entire population of a country or state but there is considerable observational evidence that diseases can spread at different rates in densely populated urban regions and sparsely populated rural areas. This work presents a new approach that applies a SIR type model to a country or state that has been divided into a number of geographical regions, and uses different infection rates in each region which depend on the population density in that region. Further, the model contains a simple matrix based method for simulating the movement of people between different regions. The model is applied to the spread of disease in the United Kingdom and the state of Rio Grande do Sul in Brazil.

Simulating grazing beef and sheep systems.

CONTEXT: Ruminant livestock make an important contribution to global food security by converting feed that is unsuitable for human consumption into high value food protein, demand for which is currently increasing at an unprecedented rate because of increasing global population and income levels. Factors affecting production efficiency, product quality, and consumer acceptability, such as animal fertility, health and welfare, will ultimately define the sustainability of ruminant production systems. These more complex systems can be developed and analysed by using models that can predict system responses to environment and management. OBJECTIVE: We present a framework that dynamically models, using a process-based and mechanistic approach, animal and grass growth, nutrient cycling and water redistribution in a soil profile taking into account the effects of animal genotype, climate, feed quality and quantity on livestock production, greenhouse gas emissions, water use and quality, and nutrient cycling in a grazing system. METHODS: A component to estimate ruminant animal growth was developed and integrated with the existing components of the SPACSYS model. Intake of herbage and/or concentrates and partitioning of the energy and protein contained in consumed herbage and/or concentrates were simulated in the component. Simulated animal growth was validated using liveweight data from over 200 finishing beef cattle and 900 lambs collected from the North Wyke Farm Platform (NWFP) in southwest England, UK, between 2011 and 2018. Annual nitrous oxide (N2O), ammonia, methane and carbon dioxide emissions from individual fields were simulated based on previous validated parameters. RESULTS AND CONCLUSIONS: A series of statistical indicators demonstrated that the model could simulate liveweight gain of beef cattle and lamb. Simulated nitrogen (N) cycling estimated N input of 190 to 260 kg ha-1, of which 37-61% was removed from the fields either as silage or animal intake, 15-26% was lost through surface runoff or lateral drainage and 1.14% was emitted to the atmosphere as N2O. About 13% of the manure N applied to the NWFP and excreta N deposited at grazing was lost via ammonia volatilisation. SIGNIFICANCE: The extended model has the potential to investigate the responses of the system on and consequences of a range of agronomic management and grazing strategies. However, modelling of multi-species swards needs to be validated including the dynamics of individual species in the swards, preferential selection by grazing animals and the impact on animal growth and nutrient flows.

Association Between Minimum Inhibitory Concentration, Beta-lactamase Genes and Mortality for Patients Treated With Piperacillin/Tazobactam or Meropenem From the MERINO Study.

INTRODUCTION: This study aims to assess the association of piperacillin/tazobactam and meropenem minimum inhibitory concentration (MIC) and beta-lactam resistance genes with mortality in the MERINO trial. METHODS: Blood culture isolates from enrolled patients were tested by broth microdilution and whole genome sequencing at a central laboratory. Multivariate logistic regression was performed to account for confounders. Absolute risk increase for 30-day mortality between treatment groups was calculated for the primary analysis (PA) and the microbiologic assessable (MA) populations. RESULTS: In total, 320 isolates from 379 enrolled patients were available with susceptibility to piperacillin/tazobactam 94% and meropenem 100%. The piperacillin/tazobactam nonsusceptible breakpoint (MIC >16 mg/L) best predicted 30-day mortality after accounting for confounders (odds ratio 14.9, 95% confidence interval [CI] 2.8-87.2). The absolute risk increase for 30-day mortality for patients treated with piperacillin/tazobactam compared with meropenem was 9% (95% CI 3%-15%) and 8% (95% CI 2%-15%) for the original PA population and the post hoc MA populations, which reduced to 5% (95% CI -1% to 10%) after excluding strains with piperacillin/tazobactam MIC values >16 mg/L. Isolates coharboring extended spectrum ß-lactamase (ESBL) and OXA-1 genes were associated with elevated piperacillin/tazobactam MICs and the highest risk increase in 30-day mortality of 14% (95% CI 2%-28%). CONCLUSIONS: After excluding nonsusceptible strains, the 30-day mortality difference from the MERINO trial was less pronounced for piperacillin/tazobactam. Poor reliability in susceptibility testing performance for piperacillin/tazobactam and the high prevalence of OXA coharboring ESBLs suggests that meropenem remains the preferred choice for definitive treatment of ceftriaxone nonsusceptible Escherichia coli and Klebsiella.

Molecular Epidemiology of Third-Generation-Cephalosporin-Resistant Enterobacteriaceae in Southeast Queensland, Australia.

Third-generation cephalosporin-resistant (3GC-R) Enterobacteriaceae represent a major threat to human health. Here, we captured 288 3GC-R Enterobacteriaceae clinical isolates from 264 patients presenting at a regional Australian hospital over a 14-month period. In addition to routine mass spectrometry and antibiotic sensitivity testing, isolates were examined using rapid (∼40-min) real-time PCR assays targeting the most common extended-spectrum ß-lactamases (ESBLs; blaCTX-M-1 and blaCTX-M-9 groups, plus blaTEM, blaSHV, and an internal 16S rRNA gene control). AmpC CMY ß-lactamase (blaCMY) prevalence was also examined. Escherichia coli (80.2%) and Klebsiella pneumoniae (17.0%) were dominant, with Klebsiella oxytoca, Klebsiella aerogenes, and Enterobacter cloacae infrequently identified. Ceftriaxone and cefoxitin resistance were identified in 97.0% and 24.5% of E. coli and K. pneumoniae isolates, respectively. Consistent with global findings in Enterobacteriaceae, most (98.3%) isolates harbored at least one ß-lactamase gene, with 144 (50%) harboring blaCTX-M-1 group, 92 (31.9%) harboring blaCTX-M-9 group, 48 (16.7%) harboring blaSHV, 133 (46.2%) harboring blaTEM, and 34 (11.8%) harboring blaCMY genes. A subset of isolates (n = 98) were subjected to whole-genome sequencing (WGS) to identify the presence of cryptic resistance determinants and to verify genotyping accuracy. WGS of ß-lactamase-negative or carbapenem-resistant isolates identified uncommon ESBL and carbapenemase genes, including blaNDM and blaIMP, and confirmed all PCR-positive genotypes. We demonstrate that our PCR assays enable the rapid and cost-effective identification of ESBLs in the hospital setting, which has important infection control and therapeutic implications.

Robustness of convolutional neural networks to physiological electrocardiogram noise.

The electrocardiogram (ECG) is a widespread diagnostic tool in healthcare and supports the diagnosis of cardiovascular disorders. Deep learning methods are a successful and popular technique to detect indications of disorders from an ECG signal. However, there are open questions around the robustness of these methods to various factors, including physiological ECG noise. In this study, we generate clean and noisy versions of an ECG dataset before applying symmetric projection attractor reconstruction (SPAR) and scalogram image transformations. A convolutional neural network is used to classify these image transforms. For the clean ECG dataset, F1 scores for SPAR attractor and scalogram transforms were 0.70 and 0.79, respectively. Scores decreased by less than 0.05 for the noisy ECG datasets. Notably, when the network trained on clean data was used to classify the noisy datasets, performance decreases of up to 0.18 in F1 scores were seen. However, when the network trained on the noisy data was used to classify the clean dataset, the decrease was less than 0.05. We conclude that physiological ECG noise impacts classification using deep learning methods and careful consideration should be given to the inclusion of noisy ECG signals in the training data when developing supervised networks for ECG classification. This article is part of the theme issue 'Advanced computation in cardiovascular physiology: new challenges and opportunities'.

REDCap on FHIR: Clinical Data Interoperability Services.

BACKGROUND: Despite widespread use of electronic data capture (EDC) systems for research and electronic health records (EHR), most transfer of data between EHR and EDC systems is manual and error prone. Increased adoption of Health Level Seven Fast Healthcare Interoperability Resource (FHIR) application programming interfaces (APIs) in recent years by EHR systems has increased the availability of patient data for external applications such as REDCap. OBJECTIVE: Describe the development of the REDCap Clinical Data Interoperability Services (CDIS) module that provides seamless data exchange between the REDCap research EDC and any EHR system with a FHIR API. CDIS enables end users to independently set up their data collection projects, map EHR data to fields, and adjudicate data transfer without project-by-project involvement from Health Information Technology staff. METHODS: We identified two use cases for EHR data transfer into REDCap. Clinical Data Pull (CDP) automatically pulls EHR data into user-defined REDCap fields and replaces the workflow of having to transcribe or copy and paste data from the EHR. Clinical Data Mart (CDM) collects all specified data for a patient over a given time period and replaces the process of importing EHR data for registries from research databases. With an iterative process, we designed our access control, authentication, variable selection, and mapping interfaces in such a way that end users could easily set up and use CDIS. RESULTS: Since its release, the REDCap CDIS has been used to pull over 19.5 million data points for 82 projects at Vanderbilt University Medical Center. Software and documentation are available through the REDCap Consortium. CONCLUSIONS: The new REDCap Clinical Data and Interoperability Services (CDIS) module leverages the FHIR standard to enable real-time and direct data extraction from the EHR. Researchers can self-service the mapping and adjudication of EHR data into REDCap. The uptake of CDIS at VUMC and other REDCap consortium sites is improving the accuracy and efficiency of EHR data collection by reducing the need for manual transcription and flat file uploads.

Data blinding for the nEDM experiment at PSI.

Psychological bias towards, or away from, prior measurements or theory predictions is an intrinsic threat to any data analysis. While various methods can be used to try to avoid such a bias, e.g. actively avoiding looking at the result, only data blinding is a traceable and trustworthy method that can circumvent the bias and convince a public audience that there is not even an accidental psychological bias. Data blinding is nowadays a standard practice in particle physics, but it is particularly difficult for experiments searching for the neutron electric dipole moment (nEDM), as several cross measurements, in particular of the magnetic field, create a self-consistent network into which it is hard to inject a false signal. We present an algorithm that modifies the data without influencing the experiment. Results of an automated analysis of the data are used to change the recorded spin state of a few neutrons within each measurement cycle. The flexible algorithm may be applied twice (or more) to the data, thus providing the option of sequentially applying various blinding offsets for separate analysis steps with independent teams. The subtle manner in which the data are modified allows one subsequently to adjust the algorithm and to produce a re-blinded data set without revealing the initial blinding offset. The method was designed for the 2015/2016 measurement campaign of the nEDM experiment at the Paul Scherrer Institute. However, it can be re-used with minor modification for the follow-up experiment n2EDM, and may be suitable for comparable projects elsewhere.

Current advisory interventions for grazing ruminant farming cannot close exceedance of modern background sediment loss - Assessment using an instrumented farm platform and modelled scaling out.

Water quality impairment by elevated sediment loss is a pervasive problem for global water resources. Sediment management targets identify exceedance or the sediment loss 'gap' requiring mitigation. In the UK, palaeo-limnological reconstruction of sediment loss during the 100-150 years pre-dating the post-World War II intensification of agriculture, has identified management targets (0.20-0.35 t ha-1 yr-1) representing 'modern background sediment delivery to rivers'. To assess exceedance on land for grazing ruminant farming, an integrated approach combined new mechanistic evidence from a heavily-instrumented experimental farm platform and a scaling out framework of modelled commercial grazing ruminant farms in similar environmental settings. Monitoring (2012-2016) on the instrumented farm platform returned sediment loss ranges of 0.11-0.14 t ha-1 yr-1 and 0.21-0.25 t ha-1 yr-1 on permanent pasture, compared with between 0.19-0.23 t ha-1 yr-1 and 0.43-0.50 t ha-1 yr-1and 0.10-0.13 t ha-1 yr-1and 0.25-0.30 t ha-1 yr-1 on pasture with scheduled plough and reseeds. Excess sediment loss existed on all three farm platform treatments but was more extensive on the two treatments with scheduled plough and reseeds. Excessive sediment loss from land used by grazing ruminant farming more strategically across England, was estimated to be up to >0.2 t ha-1 yr-1. Modelled scenarios of alternative farming futures, based on either increased uptake of interventions typically recommended by visual farm audits, or interventions selected using new mechanistic understanding for sediment loss from the instrumented farm platform, returned minimum sediment loss reductions. On the farm platform these were 2.1 % (up to 0.007 t ha-1 yr-1) and 5.1 % (up to 0.018 t ha-1 yr-1). More strategically, these were up to 2.8 % (0.014 t ha-1 yr-1) and 4.1 % (0.023 t ha-1 yr-1). Conventional on-farm measures will therefore not fully mitigate the sediment loss gap, meaning that more severe land cover change is required.

Thiel-embalmed porcine placenta: A valid and reusable microsurgical practice model.

BACKGROUND: Simulation models are increasingly important for skill acquisition during microsurgery training. Prosthetics, living and non-living biological models have been proposed in the literature in the optics of recreating real-life scenarios in a controlled environment. This study aims to validate and prove the reusability of a novel non-living biological model: the porcine placenta. METHODS: A prospective comparative study was carried out to assess face and content validities of the proposed model, as well as the reusability and quality of the Thiel-embalming method. Participants were asked answer a questionnaire for each anastomosis they performed on porcine placental vessels of ≤2mm (small) and 2-4mm (large). Scores were classified according to different subgroups, either small or large vessels and first or second sessions. Reliability analysis of the questionnaire was carried out using Cronbach's α, to ensure an α>0.7. Median scores for each question were analyzed using boxplots and compared amongst each subgroup using a non-parametric independent Mann-Whitney U test. RESULTS: With nine participants, the Cronbach's α for each category of question was 0.867, 0.778, 0.720 and 0.593. Statistical differences were found between responses of small and large vessels on 5/10 questions, where large vessels reported higher validity. No statistical differences were found between scores of the first and second sessions. CONCLUSION: By evaluating face and content validity, the Thiel-embalmed porcine placenta has proven its suitability as a microsurgery model, especially for vessels of larger caliber. Qualities that distinguish this model is its reliable reusability, its low cost-effectiveness, and its ethical acceptability.

Measurement of the Permanent Electric Dipole Moment of the Neutron.

We present the result of an experiment to measure the electric dipole moment (EDM) of the neutron at the Paul Scherrer Institute using Ramsey's method of separated oscillating magnetic fields with ultracold neutrons. Our measurement stands in the long history of EDM experiments probing physics violating time-reversal invariance. The salient features of this experiment were the use of a ^{199}Hg comagnetometer and an array of optically pumped cesium vapor magnetometers to cancel and correct for magnetic-field changes. The statistical analysis was performed on blinded datasets by two separate groups, while the estimation of systematic effects profited from an unprecedented knowledge of the magnetic field. The measured value of the neutron EDM is d_{n}=(0.0±1.1_{stat}±0.2_{sys})×10^{-26} e.cm.

Beliefs about inevitable decline among home-living older adults at risk of malnutrition: a qualitative study.

BACKGROUND: Approximately 14% of free-living adults aged ≥65 years are at risk of malnutrition. Malnutrition screen and treat interventions in primary care are few, show mixed results, and the advice given is not always accepted and followed. We need to better understand the experiences and contexts of older adults when aiming to develop interventions that are engaging, optimally persuasive and relevant. METHODS: Using the Person-based Approach, we carried out 23 semi-structured interviews with purposively selected adults ≥65 years with chronic health or social conditions associated with malnutrition risk. Thematic analysis informed the development of key principles to guide planned intervention development. RESULTS: We found that individuals' beliefs about an inevitable decline in appetite and eating in older age compound the many and varied physical and physiological barriers that they experience. Also, we found that expectations of decline in appetite and physical ability may encourage resignation, reduce self-efficacy to overcome barriers, and reduce motivation to address weight loss and/or recognise it as an issue that needs to be addressed. Fear of loss of independence may also reduce the likelihood of asking general practitioners for advice. CONCLUSIONS: The key findings identified include a sense of resignation, multiple different barriers to eating and a need for independence, each underpinned by the expectation of a decline in older adulthood. Interventions need to address misperceptions about the inevitability of decline, highlight how and why diet recommendations are somewhat different from recommendations for the general population, and suggest easy ways to increase food intake that address common barriers.

Building a Culture of Wellness When Systems Do Not Allow for Collaborative Care.

INTRODUCTION: Health care is fragmented and frustrating to patients and physicians. The consequences include patient and physician dissatisfaction. METHODS: The author's perspective is informed by his research, innovation, and leadership to optimize the experience of care for physicians and patients. RESULTS: Understanding and prioritizing the touchpoints between patients and physicians is essential to designing health care delivery that is compassionate to patients and is fulfilling and sustainable for physicians. CONCLUSIONS: Hospital administrative leaders and physicians must reject the culture of a dichotomy in purpose, and partner to create systems that make the right thing to do, the easy thing to do. LEVELS OF EVIDENCE: Level V-expert opinion.

Elucidating three-way interactions between soil, pasture and animals that regulate nitrous oxide emissions from temperate grazing systems.

Pasture-based livestock farming contributes considerably to global emissions of nitrous oxide (N2O), a powerful greenhouse gas approximately 265 times more potent than carbon dioxide. Traditionally, the estimation of N2O emissions from grasslands is carried out by means of plot-scale experiments, where externally sourced animal excreta are applied to soils to simulate grazing conditions. This approach, however, fails to account for the impact of different sward types on the composition of excreta and thus the functionality of soil microbiomes, creating unrealistic situations that are seldom observed under commercial agriculture. Using three farming systems under contrasting pasture management strategies at the North Wyke Farm Platform, an instrumented ruminant grazing trial in Devon, UK, this study measured N2O emissions from soils treated with cattle urine and dung collected within each system as well as standard synthetic urine shared across all systems, and compared these values against those from two forms of controls with and without inorganic nitrogen fertiliser applications. Soil microbial activity was regularly monitored through gene abundance to evaluate interactions between sward types, soil amendments, soil microbiomes and, ultimately, N2O production. Across all systems, N2O emissions attributable to cattle urine and standard synthetic urine were found to be inconsistent with one another due to discrepancy in nitrogen content. Despite previous findings that grasses with elevated levels of water-soluble carbohydrates tend to generate lower levels of N2O, the soil under high sugar grass monoculture in this study recorded higher emissions when receiving excreta from cattle fed the same grass. Combined together, our results demonstrate the importance of evaluating environmental impacts of agriculture at a system scale, so that the feedback mechanisms linking soil, pasture, animals and microbiomes are appropriately considered.

A comparison of Landsat 8, RapidEye and Pleiades products for improving empirical predictions of satellite-derived bathymetry.

Satellite derived bathymetry (SDB) enables rapid mapping of large coastal areas through measurement of optical penetration of the water column. The resolution of bathymetric mapping and achievable horizontal and vertical accuracies vary but generally, all SDB outputs are constrained by sensor type, water quality and other environmental conditions. Efforts to improve accuracy include physics-based methods (similar to radiative transfer models e.g. for atmospheric/vegetation studies) or detailed in-situ sampling of the seabed and water column, but the spatial component of SDB measurements is often under-utilised in SDB workflows despite promising results suggesting potential to improve accuracy significantly. In this study, a selection of satellite datasets (Landsat 8, RapidEye and Pleiades) at different spatial and spectral resolutions were tested using a log ratio transform to derive bathymetry in an Atlantic coastal embayment. A series of non-spatial and spatial linear analyses were then conducted and their influence on SDB prediction accuracy was assessed in addition to the significance of each model's parameters. Landsat 8 (30 m pixel size) performed relatively weak with the non-spatial model, but showed the best results with the spatial model. However, the highest spatial resolution imagery used - Pleiades (2 m pixel size) showed good results across both non-spatial and spatial models which suggests a suitability for SDB prediction at a higher spatial resolution than the others. In all cases, the spatial models were able to constrain the prediction differences at increased water depths.

The role for cyclic Glycine-Proline, a biological regulator of insulin-like growth factor-1 in pregnancy-related obesity and weight changes.

Cyclic Glycine-Proline (cGP) regulates the homeostasis of insulin-like growth factor (IGF)-1 function and cGP/IGF-1 ratio determines IGF-1 bioactivity in vitro and in vivo. Plasma IGF-1 represents largely inactive IGF-1 and weakly associated with human obesity and hypertension. We evaluated the regulatory role for cGP in pregnancy-related obesity and hypertension, and in obesity status between pregnancy and postpartum. Women were recruited in their first pregnancy. A cross-sectional study compared plasma concentration of cGP, IGF-1 and IGF binding protein (IGFBP)-3 in women with obesity and/or hypertension to normal controls 6-year postpartum using UPLC-MS and ELISA. A longitudinal study compared the changes of these peptides from 15-week gestation to 6-year post-partum in the women who remained normal weight, remained obese or changed to obese or to normal respectively. Study 1 is a cross-sectional study. The obese group had lower IGF-1(p = 0.001), higher cGP/IGF-1 ratio (p = 0.0055) and the hypertensive group had lower IGFBP-3 (p = 0.046) and cGP (p = 0.043) than the controls. Study 2 is a longitudinal study. Women with weight loss had increased cGP/IGF-1 ratio (p = 0.0026) and decreased IGFBP-3 (p = 0.0001) compared with women whose weight remained normal. Women with weight gain had lower IGFBP-3 (p less than 0.0001) only. Women who remained obese had increased cGP/IGF-1 ratio (p = 0.006) only. Increase in cGP/IGF-1 ratio is associated with obesity, but not hypertension. Changes of IGFBP-3 and/or cGP/IGF-1 ratio are associated with weight changes. The data suggest the role for cGP in obesity through autocrine regulation of IGF-1.

Utility of the Spanish version of the Everyday Cognition scale in the diagnosis of mild cognitive impairment and mild dementia in an older cohort from the Argentina-ADNI.

INTRODUCTION: The performance of activities of daily living in elderly patients with memory disorders is directly related to living independently and to autonomy. Documenting and assessing functional capacity through detailed scales is important for both diagnostic and treatment recommendations. The Everyday Cognition (ECog) scale is a relatively new informant-rated measure of cognitive and functional abilities. In the present study, the discriminant validity of the ECog scale was evaluated in cognitively intact controls (CN) and in patients with mild cognitive impairment (MCI) and mild Alzheimer's disease (AD) from the Argentina-ADNI cohort to establish diagnostic accuracy. In addition, we compared the sensitivity and specificity of ECog against Functional Assessment Questionnaire (FAQ) scale to discriminate among the three groups. METHODS: We evaluated 15 CN, 28 MCI, and 13 mild AD subjects. External, convergent and divergent validity and internal consistency were examined. RESULTS: The average total score on the ECog was significantly different across the three diagnostic syndromes (p < .05). The ECog was more sensitive than FAQ in discriminating between CN and MCI patients and between MCI and AD subjects. The ECog showed a strong correlation with FAQ, and moderate correlations with neuropsychological tests. Cronbach's alpha was .98. CONCLUSIONS: The ECog scale is an efficient instrument for the differentiation of individuals with mild dementia or MCI from normal older adults, with good accuracy and good correlation with other tests measuring daily and cognitive functions. Comparing against FAQ, ECog was more useful in assessing changes in functionality in MCI patients.

Intergenerational care: an exploration of consumer preferences and willingness to pay for care.

OBJECTIVES: To identify feasible models of intergenerational care programmes, that is, care of children and older people in a shared setting, to determine consumer preferences and willingness to pay. METHOD: Feasible models were constructed in extensive consultations with a panel of experts using a Delphi technique (n = 23) and were considered based on their practical implementation within an Australian setting. This informed a survey tool that captured the preferences and willingness to pay for these models by potential consumers, when compared to the status quo. Information collected from the surveys (n = 816) was analysed using regression analysis to identify fundamental drivers of preferences and the prices consumers were willing to pay for intergenerational care programmes. RESULTS: The shared campus and visiting models were identified as feasible intergenerational care models. Key attributes of these models included respite day care; a common educational pedagogy across generations; screening; monitoring; and evaluation of participant outcomes. Although parents were more likely to take up intergenerational care compared to the status quo, adult carers reported a higher willingness to pay for these services. Educational attainment also influenced the likely uptake of intergenerational care. CONCLUSIONS: The results of this study show that there is demand for the shared campus and the visiting campus models among the Australian community. The findings support moves towards consumer-centric models of care, in line with national and international best practice. This consumer-centric approach is encapsulated in the intergenerational care model and enables greater choice of care to match different consumer demands.

Functional gastrointestinal disorders in children from low socio-economic status and Helicobacter pylori infection.

BACKGROUND: Most studies on functional gastrointestinal disorders (FGIDs) in children are based on data from the northern hemisphere. Scientific reports are arising in South American population, but little is still known about children from low socio-economic status (SES), where Helicobacter pylori infection is endemic. Our objective was to evaluate the prevalence of FGIDs in school children from low SES and its relationship with H. pylori infection. METHODS: Children from 3 public schools of low SES from Santiago de Chile were included. Students completed the Rome III Questionnaire and a survey about other symptoms. Also, the 13 C urea breath test determined the presence of H. pylori infection. RESULTS: Five hundred six children were included, where 48% were male, with a median age of 15.7 years (range 7.1-19.6). Forty-two percent had some FGID, aerophagia and functional constipation being the most frequent. Females (adjusted OR 1.5, 95% CI [1.1, 2.2]), those children with parents within the lowest level of education (adjusted OR 1.6, 95% CI: 1.1-2.4), and family history of gastric cancer (adjusted OR 1.9, 95% CI: 1.2-3.1) were related to FGIDs. The prevalence of H. pylori infection was 55.9% (95% CI [50.7, 60.9]). In multivariable analysis, the presence of abdominal pain (OR 1.55, 95% CI [1.02, 2.36]), but not FGIDs, was related to H. pylori infection. CONCLUSIONS: FGIDs are common in low SES students. A low educational level of the household head, family history of gastric cancer. and being female are related to the development of FGIDs. In this study, no relationship between the presence of H. pylori and FGIDs was found.