805 research outputs found

    Supplemental Material - Time to diagnosis in systemic lupus erythematosus: Associated factors and its impact on damage accrual and mortality. Data from a multi-ethnic, multinational Latin American lupus cohort

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    Supplemental Material for Time to diagnosis in systemic lupus erythematosus: Associated factors and its impact on damage accrual and mortality. Data from a multi-ethnic, multinational Latin American lupus cohort by Romina Nieto, Rosana Quintana, Ernesto Zavala-Flores, Rosa Serrano, Karen Roberts, Luis J Catoggio, Mercedes A García, Guillermo A Berbotto, Verónica Saurit, Eloisa Bonfa, Eduardo F Borba, Lilian T Lavras Costallat, Nilzio A Da Silva, Emilia I Sato, Joao C Tavares Brenol, Loreto Massardo, Oscar J Neira, Gloria Vázquez, Marlene Guibert Toledano, Virginia Pascual-Ramos, María J Sauza del Pozo, Leonor A Barile-Fabris, Mary-Carmen Amigo, Ignacio García De La Torre, Eduardo M Acevedo-Vásquez, María I Segami, Rosa Chacón-Díaz, María H Esteva-Spinetti, Graciela S Alarcón, Bernardo A Pons-Estel, and Guillermo J Pons-Estel in Lupus.</p

    Updated constraints on sterile neutrino mixing in the OPERA experiment using a new ν e identification method

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    High-resolution mapping and dispersion analyses of volcanic ballistics emitted during the 3rd July 2019 paroxysm at Stromboli

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    Abstract A detailed mapping of volcanic ballistic projectiles emplaced in a defined area, represents the starting point to derive preparatory data in hazard and risk studies of ballistics phenomena. Considering as case study the 3rd July 2019 paroxysmal eruption occurred at Stromboli volcano, we map and analyse at very high spatial resolution (8 cm) the distribution of the ballistic spatter clasts emplaced on the E flank of the volcano. The resulting map identifies and reproduces as geospatial polygon elements 152,228 spatter clasts with areal dimensions from 0.03 to 4.23 m2. Dispersed on 0.407 km2, the spatters cover an area of 29,000 m2 corresponding to an erupted products volume from 2.3 to 7.0 × 103 m3, calculated here for the first time. Spatial analyses indicate that the area mostly affected by the clasts emplacement is between N67.5 and N135 directions, identifying a preferential deposition between N112.50 and N123.75 directions. The clasts size distribution rapidly decreases with the size increase, highlighting a nearly constant ratio small/large clasts regardless the distance from the vent. Finally, additional investigations reveal that clasts dispersion parameters decrease progressively with the distance from the vent only along one direction (N67.5), highlighting how the morphology influences the deposition and remobilisation of mapped ballistics

    HCG18, LEF1AS1 and lncCEACAM21 as biomarkers of disease severity in the peripheral blood mononuclear cells of COVID-19 patients

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    Background: Even after 3&nbsp;years from SARS-CoV-2 identification, COVID-19 is still a persistent and dangerous global infectious disease. Significant improvements in our understanding of the disease pathophysiology have now been achieved. Nonetheless, reliable and accurate biomarkers for the early stratification of COVID-19 severity are still lacking. Long noncoding RNAs (LncRNAs) are ncRNAs longer than 200 nucleotides, regulating the transcription and translation of protein-coding genes and they can be found in the peripheral blood, thus holding a promising biomarker potential. Specifically, peripheral blood mononuclear cells (PBMCs) have emerged as a source of indirect biomarkers mirroring the conditions of tissues: they include monocytes, B and T lymphocytes, and natural killer T cells (NKT), being highly informative for immune-related events. Methods: We profiled by RNA-Sequencing a panel of 2906 lncRNAs to investigate their modulation in PBMCs of a pilot group of COVID-19 patients, followed by qPCR validation in 111 hospitalized COVID-19 patients. Results: The levels of four lncRNAs were found to be decreased in association with COVID-19 mortality and disease severity: HLA Complex Group 18-242 and -244 (HCG18-242 and HCG18-244), Lymphoid Enhancer Binding Factor 1-antisense 1 (LEF1-AS1) and lncCEACAM21 (i.e. ENST00000601116.5, a lncRNA in the CEACAM21 locus). Interestingly, these deregulations were confirmed in an independent patient group of hospitalized patients and by the re-analysis of publicly available single-cell transcriptome datasets. The identified lncRNAs were expressed in all of the PBMC cell types and inversely correlated with the neutrophil/lymphocyte ratio (NLR), an inflammatory marker. In vitro, the expression of LEF1-AS1 and lncCEACAM21 was decreased upon THP-1 monocytes exposure to a relevant stimulus, hypoxia. Conclusion: The identified COVID-19-lncRNAs are proposed as potential innovative biomarkers of COVID-19 severity and mortality

    Autoantibodies against the cardiovascular protective BPIFB4 in hospitalized patients with COVID-19

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    Abstract Background/Introduction The bactericidal/permeability-increasing fold-containing family-B-member-4 (BPIFB4) serves as a biomarker of healthy aging [1,2] and displays prognostic relevance in vascular pathology [3–5]. We recently described a drop in plasma BPIFB4 level in patients with severe COVID-19 compared to low-grade disease patients [6]. Purpose As COVID-19 is associated with autoimmune features, we developed the methods for determination of Anti-BPIFB4 IgG (autoAbs) and then characterized their neutralizing activity in COVID-19 patients. Methods A sandwich ELISA-based colorimetric assay followed by immunoblot analysis detected the presence of autoAbs against BPIFB4 in 60 hospitalized COVID-19 patients and in 30 healthy volunteers. Compared to the healthy controls, the optical density (OD) level of autoAbs in COVID-19 showed considerable variability distributing over a range between 0.13 and 0.85. We thus divided the patients into two groups, one with OD &gt;0,29 and the other one with a OD &gt;0,29, where 0,29 represents the OD mean value of autoAbs against BPIFB4 in physiological conditions. Results Since patients with higher OD are mainly those who spend in average a higher number of days in hospital, we stratified the patients according to the Length of Stay (LoS) in hospital (Figure 1), and found a trend towards a positive correlation between AutoAbs OD level and length of hospitalization within COVID-19 patients. When present, autoAbs exclusively target the WT-BPIFB4 autoantigens and neglect the recognition of the Longevity-associated-variant-(LAV) of the BPIFB4 gene known for its therapeutic efficacy in cardiomyopathy, atherosclerosis (4), diabetes (6) and platelets' reactivity. As expected, the pre-treatment of human PrP with the recombinant rhLAV-BPIFB4 reduces platelets' aggregation in response to ADP and collagen in COVID-19 patients in vitro. On the other hand, at functional level, the well established LAV-BPIFB4-regulated M2 macrophage polarization (4,7), is neutralized in presence of anti-BPIFB4 autoAbs-enriched plasma. Conclusion We conclude that a significant proportion of hospitalized COVID-19 patients displays BPIFB4-AutoAbs which are positively correlated with the Length of Stay (LoS) in hospital. In future, it will be of utmost importance to clarify if the 4 missense SNPs which distinguish LAV-BPIFB4 gene from its WT-counterpart, are instrumental to prevent the self-tolerance brake-down and the potential development of specific antibodies against endogenous cardiovascular protectors. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Cariplo Foundation (n.2016-0874) to AAP and CV; Ministry of Health (RF-2016-02364864) to AAP and C

    Early and Rapid Identification of COVID-19 Patients with Neutralizing Type I Interferon Auto-antibodies.

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    Funder: Charité - Universitätsmedizin Berlin (3093)PURPOSE: Six to 19% of critically ill COVID-19 patients display circulating auto-antibodies against type I interferons (IFN-AABs). Here, we establish a clinically applicable strategy for early identification of IFN-AAB-positive patients for potential subsequent clinical interventions. METHODS: We analyzed sera of 430 COVID-19 patients from four hospitals for presence of IFN-AABs by ELISA. Binding specificity and neutralizing activity were evaluated via competition assay and virus-infection-based neutralization assay. We defined clinical parameters associated with IFN-AAB positivity. In a subgroup of critically ill patients, we analyzed effects of therapeutic plasma exchange (TPE) on the levels of IFN-AABs, SARS-CoV-2 antibodies and clinical outcome. RESULTS: The prevalence of neutralizing AABs to IFN-α and IFN-ω in COVID-19 patients from all cohorts was 4.2% (18/430), while being undetectable in an uninfected control cohort. Neutralizing IFN-AABs were detectable exclusively in critically affected (max. WHO score 6-8), predominantly male (83%) patients (7.6%, 18/237 for IFN-α-AABs and 4.6%, 11/237 for IFN-ω-AABs in 237 patients with critical COVID-19). IFN-AABs were present early post-symptom onset and at the peak of disease. Fever and oxygen requirement at hospital admission co-presented with neutralizing IFN-AAB positivity. IFN-AABs were associated with lower probability of survival (7.7% versus 80.9% in patients without IFN-AABs). TPE reduced levels of IFN-AABs in three of five patients and may increase survival of IFN-AAB-positive patients compared to those not undergoing TPE. CONCLUSION: IFN-AABs may serve as early biomarker for the development of severe COVID-19. We propose to implement routine screening of hospitalized COVID-19 patients for rapid identification of patients with IFN-AABs who most likely benefit from specific therapies

    Development and validation of a prognostic model for the early identification of COVID-19 patients at risk of developing common long COVID symptoms

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    Background: The coronavirus disease 2019 (COVID-19) pandemic demands reliable prognostic models for estimating the risk of long COVID. We developed and validated a prediction model to estimate the probability of known common long COVID symptoms at least 60 days after acute COVID-19. Methods: The prognostic model was built based on data from a multicentre prospective Swiss cohort study. Included were adult patients diagnosed with COVID-19 between February and December 2020 and treated as outpatients, at ward or intensive/intermediate care unit. Perceived long-term health impairments, including reduced exercise tolerance/reduced resilience, shortness of breath and/or tiredness (REST), were assessed after a follow-up time between 60 and 425 days. The data set was split into a derivation and a geographical validation cohort. Predictors were selected out of twelve candidate predictors based on three methods, namely the augmented backward elimination (ABE) method, the adaptive best-subset selection (ABESS) method and model-based recursive partitioning (MBRP) approach. Model performance was assessed with the scaled Brier score, concordance c statistic and calibration plot. The final prognostic model was determined based on best model performance. Results: In total, 2799 patients were included in the analysis, of which 1588 patients were in the derivation cohort and 1211 patients in the validation cohort. The REST prevalence was similar between the cohorts with 21.6% (n = 343) in the derivation cohort and 22.1% (n = 268) in the validation cohort. The same predictors were selected with the ABE and ABESS approach. The final prognostic model was based on the ABE and ABESS selected predictors. The corresponding scaled Brier score in the validation cohort was 18.74%, model discrimination was 0.78 (95% CI: 0.75 to 0.81), calibration slope was 0.92 (95% CI: 0.78 to 1.06) and calibration intercept was -0.06 (95% CI: -0.22 to 0.09). Conclusion: The proposed model was validated to identify COVID-19-infected patients at high risk for REST symptoms. Before implementing the prognostic model in daily clinical practice, the conduct of an impact study is recommended. Keywords: Clinical prediction model; Long COVID; Prognostic factors; Stratified medicin

    LRR-protein RNH1 dampens the inflammasome activation and is associated with COVID-19 severity.

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    Inflammasomes are cytosolic innate immune sensors of pathogen infection and cellular damage that induce caspase-1-mediated inflammation upon activation. Although inflammation is protective, uncontrolled excessive inflammation can cause inflammatory diseases and can be detrimental, such as in coronavirus disease (COVID-19). However, the underlying mechanisms that control inflammasome activation are incompletely understood. Here we report that the leucine-rich repeat (LRR) protein ribonuclease inhibitor (RNH1), which shares homology with LRRs of NLRP (nucleotide-binding oligomerization domain, leucine-rich repeat, and pyrin domain containing) proteins, attenuates inflammasome activation. Deletion of RNH1 in macrophages increases interleukin (IL)-1β production and caspase-1 activation in response to inflammasome stimulation. Mechanistically, RNH1 decreases pro-IL-1β expression and induces proteasome-mediated caspase-1 degradation. Corroborating this, mouse models of monosodium urate (MSU)-induced peritonitis and lipopolysaccharide (LPS)-induced endotoxemia, which are dependent on caspase-1, respectively, show increased neutrophil infiltration and lethality in Rnh1 &lt;sup&gt;-/-&lt;/sup&gt; mice compared with wild-type mice. Furthermore, RNH1 protein levels were negatively related with disease severity and inflammation in hospitalized COVID-19 patients. We propose that RNH1 is a new inflammasome regulator with relevance to COVID-19 severity

    Updated constraints on sterile neutrino mixing in the OPERA experiment using a new νe\nu_e identification method

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    This paper describes a new νe\nu_e identification method specifically designed to improve the low-energy (<30GeV< 30\,\mathrm{GeV}) νe\nu_e identification efficiency attained by enlarging the emulsion film scanning volume with the next generation emulsion readout system. A relative increase of 25-70% in the νe\nu_e low-energy region is expected, leading to improvements in the OPERA sensitivity to neutrino oscillations in the framework of the 3 + 1 model. The method is applied to a subset of data where the detection efficiency increase is expected to be more relevant, and one additional νe\nu_e candidate is found. The analysis combined with the ντ\nu_\tau appearance results improves the upper limit on sin22θμe\sin^2 2\theta_{\mu e} to 0.016 at 90% C.L. in the MiniBooNE allowed region Δm4120.3eV2\Delta m^2_{41} \sim 0.3\,\mathrm{eV}^2