Measurement Properties of ID-PALL, A New Instrument for the Identification of Patients With General and Specialized Palliative Care Needs.

To improve access to palliative care, identification of patients in need of general or specialized palliative care is necessary. To our knowledge, no available identification instrument makes this distinction. ID-PALL is a screening instrument developed to differentiate between these patient groups. To assess the structural and criterion validity and the inter-rater agreement of ID-PALL. In this multicenter, prospective, cross-sectional study, nurses and physicians assessed medical patients hospitalized for 2 to 5 days in two tertiary hospitals in Switzerland using ID-PALL. For the criterion validity, these assessments were compared to a clinical gold standard evaluation performed by palliative care specialists. Structural validity, internal consistency and inter-rater agreement were assessed. 2232 patients were assessed between January and December 2018, 97% by nurses and 50% by physicians. The variances for ID-PALL G and S are explained by two factors, the first one explaining most of the variance in both cases. For ID-PALL G, sensitivity ranged between 0.80 and 0.87 and specificity between 0.56 and 0.59. ID-PALL S sensitivity ranged between 0.82 and 0.94, and specificity between 0.35 and 0.64. A cut-off value of 1 delivered the optimal values for patient identification. Cronbach's alpha was 0.78 for ID-PALL G and 0.67 for ID-PALL S. The agreement rate between nurses and physicians was 71.5% for ID-PALL G and 64.6% for ID-PALL S. ID-PALL is a promising screening instrument allowing the early identification of patients in need of general or specialized palliative care. It can be used by nurses and physicians without a specialized palliative care training. Further testing of the finalized clinical version appears warranted

Parametric expressions for the adjusted Hargreaves coefficient in Eastern Spain

The application of simple empirical equations for estimating reference evapotranspiration (ETo) is the only alternative in many cases to robust approaches with high input requirements, especially at the local scale. In particular, temperature-based approaches present a high potential applicability, among others, because temperature might explain a high amount of ETo variability, and also because it can be measured easily and is one of the most available climatic inputs. One of the most well-known temperature-based approaches, the Hargreaves (HG) equation, requires a preliminary local calibration that is usually performed through an adjustment of the HG coefficient (AHC). Nevertheless, these calibrations are sitespecific, and cannot be extrapolated to other locations. So, they become useless in many situations, because they are derived from already available benchmarks based on more robust methods, which will be applied in practice. Therefore, the development of accurate equations for estimating AHC at local scale becomes a relevant task. This paper analyses the performance of calibrated and non-calibrated HG equations at 30 stations in Eastern Spain at daily, weekly, fortnightly and monthly scales. Moreover, multiple linear regression was applied for estimating AHC based on different inputs, and the resulting equations yielded higher performance accuracy than the non-calibrated HG estimates. The approach relying on the ratio mean temperature to temperature range did not provide suitable AHC estimations, and was highly improved by splitting it into two independent predictors. Temperature-based equations were improved by incorporating geographical inputs. Finally, the model relying on temperature and geographic inputs was further improved by incorporating wind speed, even just with simple qualitative information about wind category (e.g. poorly vs. highly windy). The accuracy of the calibrated and non-calibrated HG estimates increased for longer time steps (daily < weekly < fortnightly < monthly), although with a decreasing accuracy improvement rate. The variability of goodness-of-fit between AHC models was translated into lower variability of accuracy between the corresponding HG calibrated ETo estimates, because a single AHC was applied per station. The AHC fluctuations throughout the year suggest the convenience of using monthly or, at least, seasonal models. 2015 Elsevier B.V. All rights reserved.P. Marti acknowledges the financial support of the research grant Juan de la Cierva JCI-2012-13513 (Spanish Ministry of Economy and Competitiveness).Martí Pérez, PC.; Zarzo Castelló, M.; Vanderlinden, K.; Girona, J. (2015). Parametric expressions for the adjusted Hargreaves coefficient in Eastern Spain. Journal of Hydrology. 529(3):1713-1724. https://doi.org/10.1016/j.jhydrol.2015.07.054S17131724529

Early alterations in the MCH system link aberrant neuronal activity and sleep disturbances in a mouse model of Alzheimer’s disease

Early Alzheimer’s disease (AD) is associated with hippocampal hyperactivity and decreased sleep quality. Here we show that homeostatic mechanisms transiently counteract the increased excitatory drive to CA1 neurons in App NL-G-F mice, but that this mechanism fails in older mice. Spatial transcriptomics analysis identifies Pmch as part of the adaptive response in App NL-G-F mice. Pmch encodes melanin-concentrating hormone (MCH), which is produced in sleep–active lateral hypothalamic neurons that project to CA1 and modulate memory. We show that MCH downregulates synaptic transmission, modulates firing rate homeostasis in hippocampal neurons and reverses the increased excitatory drive to CA1 neurons in App NL-G-F mice. App NL-G-F mice spend less time in rapid eye movement (REM) sleep. App NL-G-F mice and individuals with AD show progressive changes in morphology of CA1-projecting MCH axons. Our findings identify the MCH system as vulnerable in early AD and suggest that impaired MCH-system function contributes to aberrant excitatory drive and sleep defects, which can compromise hippocampus-dependent functions

Farmers review of Best Management Practices: drivers and barriers as seen by adopters and non-adopters

Assessing farmers’ intention to adopt best management practices across eight European countrie

Metabolite-related dietary patterns and the development of islet autoimmunity

The role of diet in type 1 diabetes development is poorly understood. Metabolites, which reflect dietary response, may help elucidate this role. We explored metabolomics and lipidomics differences between 352 cases of islet autoimmunity (IA) and controls in the TEDDY (The Environmental Determinants of Diabetes in theYoung) study. We created dietary patterns reflecting pre-IA metabolite differences between groups and examined their association with IA. Secondary outcomes included IA cases positive for multiple autoantibodies (mAb+). The association of 853 plasma metabolites with outcomes was tested at seroconversion to IA, just prior to seroconversion, and during infancy. Key compounds in enriched metabolite sets were used to create dietary patterns reflecting metabolite composition, which were then tested for association with outcomes in the nested case-control subset and the full TEDDY cohort. Unsaturated phosphatidylcholines, sphingomyelins, phosphatidylethanolamines, glucosylceramides, and phospholipid ethers in infancy were inversely associated with mAb+ risk, while dicarboxylic acids were associated with an increased risk. An infancy dietary pattern representing higher levels of unsaturated phosphatidylcholines and phospholipid ethers, and lower sphingomyelins was protective for mAb+ in the nested case-control study only. Characterization of this high-risk infant metabolomics profile may help shape the future of early diagnosis or prevention efforts