The International NERSH Data Pool-A Methodological Description of a Data Pool of Religious and Spiritual Values of Health Professionals from Six Continents

Collaboration within the recently established Network for Research on Spirituality and Health (NERSH) has made it possible to pool data from 14 different surveys from six continents. All surveys are largely based on the questionnaire by Curlin " Religion and Spirituality in Medicine, Perspectives of Physicians" (RSMPP). This article is a methodological description of the process of building the International NERSH Data Pool. The larger contours of the data are described using frequency statistics. Five subscales in the data pool (including the already established DUREL scale) were tested using Cronbach's alpha and Principal Component Analysis (PCA) in an Exploratory Factor Analysis (EFA). 5724 individuals were included, of which 57% were female and the mean age was 41.5 years with a 95% confidence interval (CI) ranging from 41.2 to 41.8. Most respondents were physicians (n = 3883), nurses (n = 1189), and midwives (n = 286);but also psychologists (n = 50), therapists (n = 44), chaplains (n = 5), and students (n = 10) were included. The DUREL scale was assessed with Cronbach's alpha (ff = 0.92) and PCA confirmed its reliability and unidimensionality. The new scales covering the dimensions of "Religiosity of Health Professionals (HPs)" (alpha = 0.89), "Willingness of Physicians to Interact with Patients Regarding R/S Issues" (alpha = 0.79), "Religious Objections to Controversial Issues in Medicine" (alpha = 0.78), and "R/S as a Calling" (alpha = 0.82), also proved unidimensional in the PCAs. We argue that the proposed scales are relevant and reliable measures of religious dimensions within the data pool. Finally, we outline future studies already planned based on the data pool, and invite interested researchers to join the NERSH collaboration

Cerebrospinal Fluid Space Alterations in Melancholic Depression

Melancholic depression is a biologically homogeneous clinical entity in which structural brain alterations have been described. Interestingly, reports of structural alterations in melancholia include volume increases in Cerebro-Spinal Fluid (CSF) spaces. However, there are no previous reports of CSF volume alterations using automated whole-brain voxel-wise approaches, as tissue classification algorithms have been traditionally regarded as less reliable for CSF segmentation. Here we aimed to assess CSF volumetric alterations in melancholic depression and their clinical correlates by means of a novel segmentation algorithm (‘new segment’, as implemented in the software Statistical Parametric Mapping-SPM8), incorporating specific features that may improve CSF segmentation. A three-dimensional Magnetic Resonance Image (MRI) was obtained from seventy patients with melancholic depression and forty healthy control subjects. Although imaging data were pre-processed with the ‘new segment’ algorithm, in order to obtain a comparison with previous segmentation approaches, tissue segmentation was also performed with the ‘unified segmentation’ approach. Melancholic patients showed a CSF volume increase in the region of the left Sylvian fissure, and a CSF volume decrease in the subarachnoid spaces surrounding medial and lateral parietal cortices. Furthermore, CSF increases in the left Sylvian fissure were negatively correlated with the reduction percentage of depressive symptoms at discharge. None of these results were replicated with the ‘unified segmentation’ approach. By contrast, between-group differences in the left Sylvian fissure were replicated with a non-automated quantification of the CSF content of this region. Left Sylvian fissure alterations reported here are in agreement with previous findings from non-automated CSF assessments, and also with other reports of gray and white matter insular alterations in depressive samples using automated approaches. The reliable characterization of CSF alterations may help in the comprehensive characterization of brain structural abnormalities in psychiatric samples and in the development of etiopathogenic hypotheses relating to the disorders

GrassPlot - a database of multi-scale plant diversity in Palaearctic grasslands

GrassPlot is a collaborative vegetation-plot database organised by the Eurasian Dry Grassland Group (EDGG) and listed in the Global Index of Vegetation-Plot Databases (GIVD ID EU-00-003). GrassPlot collects plot records (releves) from grasslands and other open habitats of the Palaearctic biogeographic realm. It focuses on precisely delimited plots of eight standard grain sizes (0.0001; 0.001;... 1,000 m(2)) and on nested-plot series with at least four different grain sizes. The usage of GrassPlot is regulated through Bylaws that intend to balance the interests of data contributors and data users. The current version (v. 1.00) contains data for approximately 170,000 plots of different sizes and 2,800 nested-plot series. The key components are richness data and metadata. However, most included datasets also encompass compositional data. About 14,000 plots have near-complete records of terricolous bryophytes and lichens in addition to vascular plants. At present, GrassPlot contains data from 36 countries throughout the Palaearctic, spread across elevational gradients and major grassland types. GrassPlot with its multi-scale and multi-taxon focus complements the larger international vegetationplot databases, such as the European Vegetation Archive (EVA) and the global database " sPlot". Its main aim is to facilitate studies on the scale-and taxon-dependency of biodiversity patterns and drivers along macroecological gradients. GrassPlot is a dynamic database and will expand through new data collection coordinated by the elected Governing Board. We invite researchers with suitable data to join GrassPlot. Researchers with project ideas addressable with GrassPlot data are welcome to submit proposals to the Governing Board