60 research outputs found

    Soil networks become more connected and take up more carbon as nature restoration progresses

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    Soil organisms have an important role in aboveground community dynamics and ecosystem functioning in terrestrial ecosystems. However, most studies have considered soil biota as a black box or focussed on specific groups, whereas little is known about entire soil networks. Here we show that during the course of nature restoration on abandoned arable land a compositional shift in soil biota, preceded by tightening of the belowground networks, corresponds with enhanced efficiency of carbon uptake. In mid- and long-term abandoned field soil, carbon uptake by fungi increases without an increase in fungal biomass or shift in bacterial-to-fungal ratio. The implication of our findings is that during nature restoration the efficiency of nutrient cycling and carbon uptake can increase by a shift in fungal composition and/or fungal activity. Therefore, we propose that relationships between soil food web structure and carbon cycling in soils need to be reconsidered

    Development of a Prediction Model for COVID-19 Acute Respiratory Distress Syndrome in Patients With Rheumatic Diseases: Results From the Global Rheumatology Alliance Registry

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    OBJECTIVE: Some patients with rheumatic diseases might be at higher risk for coronavirus disease 2019 (COVID-19) acute respiratory distress syndrome (ARDS). We aimed to develop a prediction model for COVID-19 ARDS in this population and to create a simple risk score calculator for use in clinical settings. METHODS: Data were derived from the COVID-19 Global Rheumatology Alliance Registry from March 24, 2020, to May 12, 2021. Seven machine learning classifiers were trained on ARDS outcomes using 83 variables obtained at COVID-19 diagnosis. Predictive performance was assessed in a US test set and was validated in patients from four countries with independent registries using area under the curve (AUC), accuracy, sensitivity, and specificity. A simple risk score calculator was developed using a regression model incorporating the most influential predictors from the best performing classifier. RESULTS: The study included 8633 patients from 74 countries, of whom 523 (6%) had ARDS. Gradient boosting had the highest mean AUC (0.78; 95% confidence interval [CI]: 0.67-0.88) and was considered the top performing classifier. Ten predictors were identified as key risk factors and were included in a regression model. The regression model that predicted ARDS with 71% (95% CI: 61%-83%) sensitivity in the test set, and with sensitivities ranging from 61% to 80% in countries with independent registries, was used to develop the risk score calculator. CONCLUSION: We were able to predict ARDS with good sensitivity using information readily available at COVID-19 diagnosis. The proposed risk score calculator has the potential to guide risk stratification for treatments, such as monoclonal antibodies, that have potential to reduce COVID-19 disease progression

    Results From the Global Rheumatology Alliance Registry

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    Funding Information: We acknowledge financial support from the ACR and EULAR. The ACR and EULAR were not involved in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Publisher Copyright: © 2022 The Authors. ACR Open Rheumatology published by Wiley Periodicals LLC on behalf of American College of Rheumatology.Objective: Some patients with rheumatic diseases might be at higher risk for coronavirus disease 2019 (COVID-19) acute respiratory distress syndrome (ARDS). We aimed to develop a prediction model for COVID-19 ARDS in this population and to create a simple risk score calculator for use in clinical settings. Methods: Data were derived from the COVID-19 Global Rheumatology Alliance Registry from March 24, 2020, to May 12, 2021. Seven machine learning classifiers were trained on ARDS outcomes using 83 variables obtained at COVID-19 diagnosis. Predictive performance was assessed in a US test set and was validated in patients from four countries with independent registries using area under the curve (AUC), accuracy, sensitivity, and specificity. A simple risk score calculator was developed using a regression model incorporating the most influential predictors from the best performing classifier. Results: The study included 8633 patients from 74 countries, of whom 523 (6%) had ARDS. Gradient boosting had the highest mean AUC (0.78; 95% confidence interval [CI]: 0.67-0.88) and was considered the top performing classifier. Ten predictors were identified as key risk factors and were included in a regression model. The regression model that predicted ARDS with 71% (95% CI: 61%-83%) sensitivity in the test set, and with sensitivities ranging from 61% to 80% in countries with independent registries, was used to develop the risk score calculator. Conclusion: We were able to predict ARDS with good sensitivity using information readily available at COVID-19 diagnosis. The proposed risk score calculator has the potential to guide risk stratification for treatments, such as monoclonal antibodies, that have potential to reduce COVID-19 disease progression.publishersversionepub_ahead_of_prin

    Allopregnanolone-induced rise in intracellular calcium in embryonic hippocampal neurons parallels their proliferative potential

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    <p>Abstract</p> <p>Background</p> <p>Factors that regulate intracellular calcium concentration are known to play a critical role in brain function and neural development, including neural plasticity and neurogenesis. We previously demonstrated that the neurosteroid allopregnanolone (APα; 5α-pregnan-3α-ol-20-one) promotes neural progenitor proliferation <it>in vitro </it>in cultures of rodent hippocampal and human cortical neural progenitors, and <it>in vivo </it>in triple transgenic Alzheimer's disease mice dentate gyrus. We also found that APα-induced proliferation of neural progenitors is abolished by a calcium channel blocker, nifedipine, indicating a calcium dependent mechanism for the proliferation.</p> <p>Methods</p> <p>In the present study, we investigated the effect of APα on the regulation of intracellular calcium concentration in E18 rat hippocampal neurons using ratiometric Fura2-AM imaging.</p> <p>Results</p> <p>Results indicate that APα rapidly increased intracellular calcium concentration in a dose-dependent and developmentally regulated manner, with an EC<sub>50 </sub>of 110 ± 15 nM and a maximal response occurring at three days <it>in vitro</it>. The stereoisomers 3β-hydroxy-5α-hydroxy-pregnan-20-one, and 3β-hydroxy-5β-hydroxy-pregnan-20-one, as well as progesterone, were without significant effect. APα-induced intracellular calcium concentration increase was not observed in calcium depleted medium and was blocked in the presence of the broad spectrum calcium channel blocker La<sup>3+</sup>, or the L-type calcium channel blocker nifedipine. Furthermore, the GABA<sub>A </sub>receptor blockers bicuculline and picrotoxin abolished APα-induced intracellular calcium concentration rise.</p> <p>Conclusion</p> <p>Collectively, these data indicate that APα promotes a rapid, dose-dependent, stereo-specific, and developmentally regulated increase of intracellular calcium concentration in rat embryonic hippocampal neurons via a mechanism that requires both the GABA<sub>A </sub>receptor and L-type calcium channel. These data suggest that APα-induced intracellular calcium concentration increase serves as the initiation mechanism whereby APα promotes neurogenesis.</p

    Inborn errors of OAS-RNase L in SARS-CoV-2-related multisystem inflammatory syndrome in children

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    Multisystem inflammatory syndrome in children (MIS-C) is a rare and severe condition that follows benign COVID-19. We report autosomal recessive deficiencies of OAS1, OAS2, or RNASEL in five unrelated children with MIS-C. The cytosolic double-stranded RNA (dsRNA)-sensing OAS1 and OAS2 generate 2'-5'-linked oligoadenylates (2-5A) that activate the single-stranded RNA-degrading ribonuclease L (RNase L). Monocytic cell lines and primary myeloid cells with OAS1, OAS2, or RNase L deficiencies produce excessive amounts of inflammatory cytokines upon dsRNA or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) stimulation. Exogenous 2-5A suppresses cytokine production in OAS1-deficient but not RNase L-deficient cells. Cytokine production in RNase L-deficient cells is impaired by MDA5 or RIG-I deficiency and abolished by mitochondrial antiviral-signaling protein (MAVS) deficiency. Recessive OAS-RNase L deficiencies in these patients unleash the production of SARS-CoV-2-triggered, MAVS-mediated inflammatory cytokines by mononuclear phagocytes, thereby underlying MIS-C
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