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Antisynthetase syndrome (ASSD) is a rare clinical condition that is characterized by the occurrence of a classic clinical triad, encompassing myositis, arthritis, and interstitial lung disease (ILD), along with specific autoantibodies that are addressed to different aminoacyl tRNA synthetases (ARS). Until now, it has been unknown whether the presence of a different ARS might affect the clinical presentation, evolution, and outcome of ASSD. In this study, we retrospectively recorded the time of onset, characteristics, clustering of triad findings, and survival of 828 ASSD patients (593 anti-Jo1, 95 anti-PL7, 84 anti-PL12, 38 anti-EJ, and 18 anti-OJ), referring to AENEAS (American and European NEtwork of Antisynthetase Syndrome) collaborative group’s cohort. Comparisons were performed first between all ARS cases and then, in the case of significance, while using anti-Jo1 positive patients as the reference group. The characteristics of triad findings were similar and the onset mainly began with a single triad finding in all groups despite some differences in overall prevalence. The “ex-novo” occurrence of triad findings was only reduced in the anti-PL12-positive cohort, however, it occurred in a clinically relevant percentage of patients (30%). Moreover, survival was not influenced by the underlying anti-aminoacyl tRNA synthetase antibodies’ positivity, which confirmed that antisynthetase syndrome is a heterogeneous condition and that antibody specificity only partially influences the clinical presentation and evolution of this condition.
In Luxemburg sind infolge von Landnutzungsintensivierungen nur noch wenige Relikte nährstoffarmer Feuchthabitate mit hohem Naturschutzwert erhalten. Eine kleinräumig differenzierte Untersuchung der Zusammenhänge zwischen Bodenfaktoren und Vegetation stand für diese Relikte bisher aus. Aus diesem Grund wurden in fünf Luxemburger Niedermoorkomplexen Vegetationszusammensetzung, Vegetationsstruktur (90 %-Perzentil der Vegetationshöhe, Streudeckung) und für die Pflanzenernährung relevante, bodenchemische Variablen (pH-Wert, Phosphor-, Kalium-, Calcium-, Magnesium-Gehalt) erfasst sowie Ellenberg-Zeigerwerte (Feuchte- und Nährstoff-Zahl) ausgewertet. Dabei ging es insbesondere um die Klärung der Fragen, welche Umweltgradienten der auffälligen Zonierung in Kern- und Randbereiche zugrunde liegen und welche Habitateigenschaften mit der Anzahl von gefährdeten Arten korrelieren. Hierzu wurden insgesamt 74 Kleinflächen in den beiden Zonen angelegt und floristisch sowie bodenchemisch analysiert.
Die Kleinflächen spannten einen Säuregradienten von annähernd drei pH-Stufen über die Gebiete hinweg auf (pH 3,9–6,5). Es ließen sich floristische, strukturelle und bodenchemische Unterschiede zwischen den Zonen ausmachen. In den meisten Gebieten unterschieden sich Diversität (in Kernbereichen erhöht) und Produktivität (nach Maßgabe von 90 %-Perzentil und Nährstoff-Zahl in Randbereichen erhöht). Die bodenchemischen Variablen zeigten je nur in einzelnen Gebieten Zonenunterschiede. Die beiden Gebiete mit den niedrigsten bzw. höchsten pH-Werten wiesen die meisten Variablen mit signifikanten Zonenunterschieden auf. Die Feuchte-Zahl war in keinem Gebiet zonenkennzeichnend. Die Diversität an bedrohten Arten korrelierte am häufigsten mit dem Magnesiumgehalt im Boden (meist positiv) und dem 90 %-Perzentil (stets negativ).
Unsere Ergebnisse legen nahe, dass in den untersuchten Niedermoorkomplexen mehrere Variablen zugleich und in unterschiedlicher Kombination für die Zonation verantwortlich sein könnten. Es werden Managementoptionen für die gefährdeten Gebiete diskutiert.
Status and restoration potential of heathlands and sand grasslands in the southwest of Luxembourg
(2017)
In Europe, semi-natural nutrient-poor ecosystems such as sand grasslands and heathlands have shown extreme declines in surface area and species richness within the last century. The remaining sites are hence of high conservation value. This study analysed the vascular plant species inventory of established and recently restored heathlands and sand grasslands in the southwest of Luxembourg. Analyses to explain differences in vegetation composition between “old” (remnant sites or sites restored a long time ago) and “new” (recently restored) sites in relation to environmental variables were carried out with DCAs and ANOVA/Mann-Whitney-U tests, respectively. The vegetation of old heathlands had few character species of typical heathland communities (Calluno-Ulicetea, Nardetalia), whereas new heathland sites were preponderantly marked by taxa of meso- or eutrophic grasslands and ruderal communities. New heathland sites mainly differed from old sites by higher soil phosphorus contents. Sand grassland vegetation was species-rich and composed by species of the Sedo-Scleranthetea and Festuco-Brometea. With increasing age of the sites, vegetation composition shifted to grass dominance with species of the Molinio-Arrhenateretea. New sand grasslands differed from old sand grasslands by higher soil pH, higher soil potassium content and lower graminoid cover. The differences between new and old sites of both habitat types could mainly be explained by successional processes or were a result of topsoil removal. In some cases, former anthropogenic impact at or in close proximity of restored sites resulted in unsuitable conditions, such as alkaline soil on former landfill sites or highly eutrophic soil due to intensive agriculture. Future management options for the study sites are discussed.
The main goal of the present study was the identification of cellular phenotypes in attention-deficit-/hyperactivity disorder (ADHD) patient-derived cellular models from carriers of rare copy number variants (CNVs) in the PARK2 locus that have been previously associated with ADHD. Human-derived fibroblasts (HDF) were cultured and human-induced pluripotent stem cells (hiPSC) were reprogrammed and differentiated into dopaminergic neuronal cells (mDANs). A series of assays in baseline condition and in different stress paradigms (nutrient deprivation, carbonyl cyanide m-chlorophenyl hydrazine (CCCP)) focusing on mitochondrial function and energy metabolism (ATP production, basal oxygen consumption rates, reactive oxygen species (ROS) abundance) were performed and changes in mitochondrial network morphology evaluated. We found changes in PARK2 CNV deletion and duplication carriers with ADHD in PARK2 gene and protein expression, ATP production and basal oxygen consumption rates compared to healthy and ADHD wildtype control cell lines, partly differing between HDF and mDANs and to some extent enhanced in stress paradigms. The generation of ROS was not influenced by the genotype. Our preliminary work suggests an energy impairment in HDF and mDAN cells of PARK2 CNV deletion and duplication carriers with ADHD. The energy impairment could be associated with the role of PARK2 dysregulation in mitochondrial dynamics.
Background: Altered neuronal development is discussed as the underlying pathogenic mechanism of autism spectrum disorders (ASD). Copy number variations of 16p11.2 have recurrently been identified in individuals with ASD. Of the 29 genes within this region, quinolinate phosphoribosyltransferase (QPRT) showed the strongest regulation during neuronal differentiation of SH-SY5Y neuroblastoma cells. We hypothesized a causal relation between this tryptophan metabolism-related enzyme and neuronal differentiation. We thus analyzed the effect of QPRT on the differentiation of SH-SY5Y and specifically focused on neuronal morphology, metabolites of the tryptophan pathway, and the neurodevelopmental transcriptome.
Methods: The gene dosage-dependent change of QPRT expression following Chr16p11.2 deletion was investigated in a lymphoblastoid cell line (LCL) of a deletion carrier and compared to his non-carrier parents. Expression of QPRT was tested for correlation with neuromorphology in SH-SY5Y cells. QPRT function was inhibited in SH-SY5Y neuroblastoma cells using (i) siRNA knockdown (KD), (ii) chemical mimicking of loss of QPRT, and (iii) complete CRISPR/Cas9-mediated knock out (KO). QPRT-KD cells underwent morphological analysis. Chemically inhibited and QPRT-KO cells were characterized using viability assays. Additionally, QPRT-KO cells underwent metabolite and whole transcriptome analyses. Genes differentially expressed upon KO of QPRT were tested for enrichment in biological processes and co-regulated gene-networks of the human brain.
Results: QPRT expression was reduced in the LCL of the deletion carrier and significantly correlated with the neuritic complexity of SH-SY5Y. The reduction of QPRT altered neuronal morphology of differentiated SH-SY5Y cells. Chemical inhibition as well as complete KO of the gene were lethal upon induction of neuronal differentiation, but not proliferation. The QPRT-associated tryptophan pathway was not affected by KO. At the transcriptome level, genes linked to neurodevelopmental processes and synaptic structures were affected. Differentially regulated genes were enriched for ASD candidates, and co-regulated gene networks were implicated in the development of the dorsolateral prefrontal cortex, the hippocampus, and the amygdala.
Conclusions: In this study, QPRT was causally related to in vitro neuronal differentiation of SH-SY5Y cells and affected the regulation of genes and gene networks previously implicated in ASD. Thus, our data suggest that QPRT may play an important role in the pathogenesis of ASD in Chr16p11.2 deletion carriers.
Background: Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 patient clinical outcomes upon ICU admission remain inadequate. This study aimed to develop a machine learning model, based on retrospective & prospective clinical data, to stratify patient risk and predict ICU survival and outcomes. Methods: A Germany-wide electronic registry was established to pseudonymously collect admission, therapeutic and discharge information of SARS-CoV-2 ICU patients retrospectively and prospectively. Machine learning approaches were evaluated for the accuracy and interpretability of predictions. The Explainable Boosting Machine approach was selected as the most suitable method. Individual, non-linear shape functions for predictive parameters and parameter interactions are reported. Results: 1039 patients were included in the Explainable Boosting Machine model, 596 patients retrospectively collected, and 443 patients prospectively collected. The model for prediction of general ICU outcome was shown to be more reliable to predict “survival”. Age, inflammatory and thrombotic activity, and severity of ARDS at ICU admission were shown to be predictive of ICU survival. Patients’ age, pulmonary dysfunction and transfer from an external institution were predictors for ECMO therapy. The interaction of patient age with D-dimer levels on admission and creatinine levels with SOFA score without GCS were predictors for renal replacement therapy. Conclusions: Using Explainable Boosting Machine analysis, we confirmed and weighed previously reported and identified novel predictors for outcome in critically ill COVID-19 patients. Using this strategy, predictive modeling of COVID-19 ICU patient outcomes can be performed overcoming the limitations of linear regression models. Trial registration “ClinicalTrials” (clinicaltrials.gov) under NCT04455451.