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Journal articleKirsebom F, Michalaki C, Agueda-Oyarzabal M, et al., 2020,
Neutrophils do not impact viral load or the peak of disease severity during RSV infection
, Scientific Reports, Vol: 10, ISSN: 2045-2322Lung and airway neutrophils are a hallmark of severe disease in infants with respiratory syncytial virus (RSV)-induced lower respiratory tract infections. Despite their abundance in the lungs during RSV infection of both mice and man, the role of neutrophils in viral control and in immune pathology is not clear. Here, antibody mediated neutrophil depletion was used to investigate the degree to which neutrophils impact the lung immune environment, the control of viral replication and the peak severity of disease after RSV infection of mice. Neutrophil depletion did not substantially affect the levels of inflammatory mediators such as type I interferons, IL-6, TNF-α or IL-1β in response to RSV. In addition, the lack of neutrophils did not change the viral load during RSV infection. Neither neutrophil depletion nor the enhancement of lung neutrophils by administration of the chemoattractant CXCL1 during RSV infection affected disease severity as measured by weight loss. Therefore, in this model of RSV infection, lung neutrophils do not offer obvious benefits to the host in terms of increasing anti-viral inflammatory responses or restricting viral replication and neutrophils do not contribute to disease severity.
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Journal articleAtkinson SR, Hamesch K, Spivak I, et al., 2020,
Serum transferrin is an independent predictor of mortality in severe alcoholic hepatitis.
, American Journal of Gastroenterology, Vol: 115, Pages: 398-405, ISSN: 0002-9270OBJECTIVES: Severe alcoholic hepatitis (sAH) confers substantial mortality, but the disease course is difficult to predict. As iron parameters are attractive outcome predictors in other liver diseases, we tested their prognostic ability in sAH. METHODS: Serum ferritin, transferrin, iron, transferrin saturation, nontransferrin-bound iron, soluble transferrin receptor, and hepcidin were measured in 828 patients with sAH recruited prospectively through the STOPAH trial. The cohort was randomly divided into exploratory (n = 200) and validation sets (n = 628). RESULTS: Patients with sAH had diminished serum transferrin but increased transferrin saturation. Among iron parameters, baseline transferrin was the best predictor of 28-day (area under the receiver operated characteristic 0.72 [95% confidence interval 0.67-0.78]) and 90-day survival (area under the receiver operated characteristic 0.65 [0.61-0.70]). Transferrin's predictive ability was comparable with the composite scores, namely model of end-stage liver disease, Glasgow alcoholic hepatitis score, and discriminant function, and was independently associated with survival in multivariable analysis. These results were confirmed in a validation cohort. Transferrin did not correlate with markers of liver synthesis nor with non-transferrin-bound iron or soluble transferrin receptor (as markers of excess unbound iron and functional iron deficiency, respectively). DISCUSSION: In patients with sAH, serum transferrin predicts mortality with a performance comparable with commonly used composite scoring systems. Hence, this routinely available parameter might be a useful marker alone or as a component of prognostic models.
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Journal articleEntwistle L, Gregory L, Oliver R, et al., 2020,
Pulmonary group 2 innate lymphoid cell phenotype is context specific: Determining the effect of strain, location and stimuli
, Frontiers in Immunology, Vol: 10, ISSN: 1664-3224Group 2 innate lymphoid cells (ILC2s) are enriched at mucosal sites, including the lung, and play a central role in type 2 immunity and maintaining tissue homeostasis. As a result, since their discovery in 2010, research into ILC2s has increased markedly. Numerous strategies have been used to define ILC2s by flow cytometry, often utilizing different combinations of surface markers despite their expression being variable and context-dependent. In this study, we sought to generate a comprehensive characterization of pulmonary ILC2s, identifying stable and context specific markers from different pulmonary compartments following different airway exposures in different strains of mice. Our analysis revealed that pulmonary ILC2 surface marker phenotype is heterogeneous and is influenced by mouse strain, pulmonary location, in vivo treatment/exposure and ex vivo stimulation. Therefore, we propose that a lineage negative cell expressing CD45 and Gata3 defines an ILC2, and subsequent surface marker expression should be used to describe their phenotype in context-specific scenarios.
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Conference paperGhani R, Mullish BH, McDonald J, et al., 2020,
Disease prevention not decolonisation: a cohort study for faecal microbiota transplantation for patients colonised with multidrug-resistant organisms
, ECCMID 2020 -
Journal articleVanderleyden I, Fra-Bido SC, Innocentin S, et al., 2020,
Follicular regulatory T cells can access the germinal center independently of CXCR5
, Cell Reports, Vol: 30, Pages: 611-619.e4, ISSN: 2211-1247The germinal center (GC) response is critical for generating high-affinity humoral immunity and immunological memory, which forms the basis of successful immunization. Control of the GC response is thought to require follicular regulatory T (Tfr) cells, a subset of suppressive Foxp3+ regulatory T cells located within GCs. Relatively little is known about the exact role of Tfr cells within the GC and how they exert their suppressive function. A unique feature of Tfr cells is their reported CXCR5-dependent localization to the GC. Here, we show that the lack of CXCR5 on Foxp3+ regulatory T cells results in a reduced frequency, but not an absence, of GC-localized Tfr cells. This reduction in Tfr cells is not sufficient to alter the magnitude or output of the GC response. This demonstrates that additional, CXCR5-independent mechanisms facilitate Treg cell homing to the GC.
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Journal articleDeliu M, Fontanella S, Haider S, et al., 2020,
Longitudinal trajectories of severe wheeze exacerbations from infancy to school age and their association with early-life risk factors and late asthma outcomes
, Clinical and Experimental Allergy, Vol: 50, Pages: 315-324, ISSN: 0954-7894IntroductionExacerbation‐prone asthma subtype has been reported in studies using data‐driven methodologies. However, patterns of severe exacerbations have not been studied.ObjectiveTo investigate longitudinal trajectories of severe wheeze exacerbations from infancy to school age.MethodsWe applied longitudinal k‐means clustering to derive exacerbation trajectories among 887 participants from a population‐based birth cohort with severe wheeze exacerbations confirmed in healthcare records. We examined early‐life risk factors of the derived trajectories, and their asthma‐related outcomes and lung function in adolescence.Results498/887 children (56%) had physician‐confirmed wheeze by age 8 years, of whom 160 had at least one severe exacerbation. A two‐cluster model provided the optimal solution for severe exacerbation trajectories among these 160 children: “Infrequent exacerbations (IE)” (n = 150, 93.7%) and “Early‐onset frequent exacerbations (FE)” (n = 10, 6.3%). Shorter duration of breastfeeding was the strongest early‐life risk factor for FE (weeks, median [IQR]: FE, 0 [0‐1.75] vs. IE, 6 [0‐20], P < .001). Specific airway resistance (sRaw) was significantly higher in FE compared with IE trajectory throughout childhood. We then compared children in the two exacerbation trajectories with those who have never wheezed (NW, n = 389) or have wheezed but had no severe exacerbations (WNE, n = 338). At age 8 years, FEV1/FVC was significantly lower and FeNO significantly higher among FE children compared with all other groups. By adolescence (age 16), subjects in FE trajectory were significantly more likely to have current asthma (67% FE vs. 30% IE vs. 13% WNE, P < .001) and use inhaled corticosteroids (77% FE vs. 15% IE vs. 18% WNE, P < .001). Lung function was significantly diminished in the FE trajectory (FEV1/FVC, mean [95%CI]: 89.9% [89.3‐90.5] vs. 88.1% [87.3‐88.8] vs. 85.1% [83.4‐86.7] vs. 74.7% [61.5‐87.8], NW, WNE, IE, FE respective
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Journal articleBittner VA, Szarek M, Aylward PE, et al., 2020,
Effect of Alirocumab on Lipoprotein(a) and Cardiovascular Risk After Acute Coronary Syndrome
, JACC-JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, Vol: 75, Pages: 133-144, ISSN: 0735-1097- Cite
- Citations: 429
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Working paperHurault G, Domínguez-Hüttinger E, Langan SM, et al., 2020,
Personalised prediction of daily eczema severity scores using a mechanistic machine learning model
<jats:title>ABSTRACT</jats:title> <jats:sec> <jats:title>Background</jats:title> <jats:p>Atopic dermatitis (AD) is a chronic inflammatory skin disease with periods of flares and remission. Designing personalised treatment strategies for AD is challenging, given the apparent unpredictability and large variation in AD symptoms and treatment responses within and across individuals. Better prediction of AD severity over time for individual patients could help to select optimum timing and type of treatment for improving disease control.</jats:p> </jats:sec> <jats:sec> <jats:title>Objective</jats:title> <jats:p>We aimed to develop a mechanistic machine learning model that predicts the patient-specific evolution of AD severity scores on a daily basis.</jats:p> </jats:sec> <jats:sec> <jats:title>Methods</jats:title> <jats:p>We designed a probabilistic predictive model and trained it using Bayesian inference with the longitudinal data from two published clinical studies. The data consisted of daily recordings of AD severity scores and treatments used by 59 and 334 AD children over 6 months and 16 weeks, respectively. Internal and external validation of the predictive model was conducted in a forward-chaining setting.</jats:p> </jats:sec> <jats:sec> <jats:title>Results</jats:title> <jats:p>Our model was able to predict future severity scores at the individual level and improved chance-level forecast by 60%. Heterogeneous patterns in severity trajectories were captured with patient-specific parameters such as the short-term persistence of AD severity and responsiveness to topical steroids, calcineur
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Journal articleKurz W, Yetisen AK, Kaito MV, et al., 2020,
UV-sensitive wearable devices for colorimetric monitoring of UV exposure
, Advanced Optical Materials, Vol: 8, ISSN: 2195-1071The extensive exposure of the human epidermis to solar radiation creates a health risk that results in skin cancer. Commercial sunscreens offer sufficient protection from ultraviolet (UV) radiation; however, the ability to determine UV exposure limits can provide informed decisions about the dose of sunscreen required and the frequency of re-application. Here, a wide range of wearable devices that colorimetrically report on UV exposure are developed. Under UV radiation, UV-sensitive dyes change their color from 280 to 400 nm in the visible spectrum. By correlating the current color value and the UV dose, the amount of sun exposure is determined with an accuracy of 95%. A smartphone camera algorithm is coded to automatically perform the color analysis of these dyes. The UV-sensitive dyes are incorporated in wearable devices, skin patches, textiles, contact lenses, and tattoo inks. The developed wearable devices will ensure monitoring UV radiation to rationally manage the user's behavior in order to prevent harmful sun exposure.
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Working paperGonzalez G, Gong S, Laponogov I, et al., 2020,
Graph attentional autoencoder for anticancer hyperfood prediction
, Publisher: arXivRecent research efforts have shown the possibility to discover anticancerdrug-like molecules in food from their effect on protein-protein interactionnetworks, opening a potential pathway to disease-beating diet design. Weformulate this task as a graph classification problem on which graph neuralnetworks (GNNs) have achieved state-of-the-art results. However, GNNs aredifficult to train on sparse low-dimensional features according to ourempirical evidence. Here, we present graph augmented features, integratinggraph structural information and raw node attributes with varying ratios, toease the training of networks. We further introduce a novel neural networkarchitecture on graphs, the Graph Attentional Autoencoder (GAA) to predict foodcompounds with anticancer properties based on perturbed protein networks. Wedemonstrate that the method outperforms the baseline approach andstate-of-the-art graph classification models in this task.
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