18S rDNA Phylogeny of Lamproderma and Allied Genera (Stemonitales, Myxomycetes, Amoebozoa)

The phylogenetic position of the slime-mould genus Lamproderma (Myxomycetes, Amoebozoa) challenges traditional taxonomy: although it displays the typical characters of the order Stemonitales, it appears to be sister to Physarales. This study provides a small subunit (18S or SSU) ribosomal RNA gene-based phylogeny of Lamproderma and its allies, with new sequences from 49 specimens in 12 genera. We found that the order Stemonitales and Lamproderma were both ancestral to Physarales and that Lamproderma constitutes several clades intermingled with species of Diacheopsis, Colloderma and Elaeomyxa. We suggest that these genera may have evolved from Lamproderma by multiple losses of fruiting body stalks and that many taxonomic revisions are needed. We found such high genetic diversity within three Lamproderma species that they probably consist of clusters of sibling species. We discuss the contrasts between genetic and morphological divergence and implications for the morphospecies concept, highlighting the phylogenetically most reliable morphological characters and pointing to others that have been overestimated. In addition, we showed that the first part (∼600 bases) of the SSU rDNA gene is a valuable tool for phylogeny in Myxomycetes, since it displayed sufficient variability to distinguish closely related taxa and never failed to cluster together specimens considered of the same species

Gender and observed complexity in palliative home care : A prospective multicentre study using the hexcom model

This study analyses gender differences in the complexity observed in palliative home care through a multicentre longitudinal observational study of patients with advanced disease treated by palliative home care teams in Catalonia (Spain). We used the HexCom model, which includes six dimensions and measures three levels of complexity: high (non-modifiable situation), medium (difficult) and low. Results: N = 1677 people, 44% women. In contrast with men, in women, cancer was less prevalent (64.4% vs. 73.9%) (p < 0.001), cognitive impairment was more prevalent (34.1% vs. 26.6%; p = 0.001) and professional caregivers were much more common (40.3% vs. 24.3%; p < 0.001). Women over 80 showed less complexity in the following subareas: symptom management (41.7% vs. 51,1%; p = 0.011), emotional distress (24.5% vs. 32.8%; p = 0.015), spiritual distress (16.4% vs. 26.4%; p = 0.001), socio-familial distress (62.7% vs. 70.1%; p = 0.036) and location of death (36.0% vs. 49.6%; p < 0.000). Men were more complex in the subareas of "practice" OR = 1.544 (1.25-1.90 p = 0.000) and "transcendence" OR = 1.52 (1.16-1.98 p = 0.002). Observed complexity is related to male gender in people over 80 years of age. Women over the age of 80 are remarkably different from their male counterparts, showing less complexity regarding care for their physical, psycho-emotional, spiritual and socio-familial needs

Flexible modelling of spatial variation in agricultural field trials with the R package INLA

The objective of this paper was to fit different established spatial models for analysing agricultural field trials using the open-source R package INLA. Spatial variation is common in field trials, and accounting for it increases the accuracy of estimated genetic effects. However, this is still hindered by the lack of available software implementations. We compare some established spatial models and show possibilities for flexible modelling with respect to field trial design and joint modelling over multiple years and locations. We use a Bayesian framework and for statistical inference the integrated nested Laplace approximations (INLA) implemented in the R package INLA. The spatial models we use are the well-known independent row and column effects, separable first-order autoregressive ( AR1⊗AR1 ) models and a Gaussian random field (Matérn) model that is approximated via the stochastic partial differential equation approach. The Matérn model can accommodate flexible field trial designs and yields interpretable parameters. We test the models in a simulation study imitating a wheat breeding programme with different levels of spatial variation, with and without genome-wide markers and with combining data over two locations, modelling spatial and genetic effects jointly. The results show comparable predictive performance for both the AR1⊗AR1 and the Matérn models. We also present an example of fitting the models to a real wheat breeding data and simulated tree breeding data with the Nelder wheel design to show the flexibility of the Matérn model and the R package INLA

Genetic Structure of Two Protist Species (Myxogastria, Amoebozoa) Suggests Asexual Reproduction in Sexual Amoebae

Plasmodial slime molds (Myxogastria or Myxomycetes) are common and widespread unicellular organisms that are commonly assumed to have a sexual life cycle culminating with the formation of often macroscopic fruiting bodies that efficiently disseminate spores. However, laboratory studies based on mating compatibility revealed the coexistence of asexual as well as sexual strains. To test this hypothesis in natural populations, we investigated the genetic variability of two species of the genus Lamproderma. Detailed ecological relevés were carried out in 2007 and 2009 in several deep ravines in the Elbsandsteingebirge (Saxony, south-eastern Germany). Morphological characters of 93 specimens of Lamproderma were recorded and genetic analyses, based on the small subunit ribosomal gene, the internal transcribed spacer 1 and partial elongation factor 1α sequences were carried out for 52 specimens. Genetic analyses showed the existence of two major clades, each composed of several discrete lineages. Most of these lineages were composed of several identical sequences (SSU, ITS 1 and EF-1α) which is explained best by an asexual mode of reproduction. Detrended Correspondence Analysis of morphological characters revealed two morphospecies that corresponded to the two major clades, except for one genotype (Lc6), thus challenging the morphospecies concept. Genetic patterns were not related to the geographical distribution: specimens belonging to the same genotype were found in distinct ravines, suggesting effective long-distance dispersal via spores, except for the Lc6 genotype which was found only in one ravine. Implications for the morphological and biological species concept are discussed

Local primordial non-Gaussianity from the large-scale clustering of photometric DESI luminous red galaxies

We use angular clustering of luminous red galaxies from the Dark Energy Spectroscopic Instrument (DESI) imaging surveys to constrain the local primordial non-Gaussianity parameter fNL. Our sample comprises over 12 million targets, covering 14,000 square degrees of the sky, with redshifts in the range 0.2< z < 1.35. We identify Galactic extinction, survey depth, and astronomical seeing as the primary sources of systematic error, and employ linear regression and artificial neural networks to alleviate non-cosmological excess clustering on large scales. Our methods are tested against log-normal simulations with and without fNL and systematics, showing superior performance of the neural network treatment in reducing remaining systematics. Assuming the universality relation, we find fNL $= 47^{+14(+29)}_{-11(-22)}$ at 68\%(95\%) confidence. With a more aggressive treatment, including regression against the full set of imaging maps, our maximum likelihood value shifts slightly to fNL$\sim 50$ and the uncertainty on fNL increases due to the removal of large-scale clustering information. We apply a series of robustness tests (e.g., cuts on imaging, declination, or scales used) that show consistency in the obtained constraints. Despite extensive efforts to mitigate systematics, our measurements indicate fNL > 0 with a 99.9 percent confidence level. This outcome raises concerns as it could be attributed to unforeseen systematics, including calibration errors or uncertainties associated with low-\ell systematics in the extinction template. Alternatively, it could suggest a scale-dependent fNL model--causing significant non-Gaussianity around large-scale structure while leaving cosmic microwave background scales unaffected. Our results encourage further studies of fNL with DESI spectroscopic samples, where the inclusion of 3D clustering modes should help separate imaging systematics.Comment: 19 pages, 15 figures, 6 tables (Appendix excluded). Submitted to MNRA

Development and validation of a clinical score to estimate progression to severe or critical state in Covid-19 pneumonia hospitalized patients

The prognosis of a patient with Covid-19 pneumonia is uncertain. Our objective was to establish a predictive model of disease progression to facilitate early decision-making. A retrospective study was performed of patients admitted with Covid-19 pneumonia, classified as severe (admission to the intensive care unit, mechanic invasive ventilation, or death) or non-severe. A predictive model based on clinical, analytical, and radiological parameters was built. The probability of progression to severe disease was estimated by logistic regression analysis. Calibration and discrimination (receiver operating characteristics curves and AUC) were assessed to determine model performance. During the study period 1,152 patients presented with Covid-19 infection, of whom 229 (19.9%) were admitted for pneumonia. During hospitalization, 51 (22.3%) progressed to severe disease, of whom 26 required ICU care (11.4); 17 (7.4%) underwent invasive mechanical ventilation, and 32 (14%) died of any cause. Five predictors determined within 24 hours of admission were identified: Diabetes, Age, Lymphocyte count, SaO2, and pH (DALSH score). The prediction model showed a good clinical performance, including discrimination (AUC 0.87 CI 0.81, 0.92) and calibration (Brier score = 0.11). In total, 0%, 12%, and 50% of patients with severity risk scores ≤5%, 6-25%, and >25% exhibited disease progression, respectively. A simple risk score based on five factors predicts disease progression and facilitates early decision-making according to prognosis.Carlos III Health Institute, Spain, Ministry of Economy and Competitiveness (SPAIN) and the European Regional Development Fund (FEDER)Instituto de Salud Carlos II