14 research outputs found

    Hypoxia-inducible factor 1 alpha-mediated RelB/APOBEC3B down-regulation allows hepatitis B virus persistence

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    Background and Aims: Therapeutic strategies against HBV focus, among others, on the activation of the immune system to enable the infected host to eliminate HBV. Hypoxia‐inducible factor 1 alpha (HIF1α) stabilization has been associated with impaired immune responses. HBV pathogenesis triggers chronic hepatitis‐related scaring, leading inter alia to modulation of liver oxygenation and transient immune activation, both factors playing a role in HIF1α stabilization. Approach and Results: We addressed whether HIF1α interferes with immune‐mediated induction of the cytidine deaminase, apolipoprotein B mRNA editing enzyme catalytic subunit 3B (APOBEC3B; A3B), and subsequent covalently closed circular DNA (cccDNA) decay. Liver biopsies of chronic HBV (CHB) patients were analyzed by immunohistochemistry and in situ hybridization. The effect of HIF1α induction/stabilization on differentiated HepaRG or mice ± HBV ± LTβR‐agonist (BS1) was assessed in vitro and in vivo. Induction of A3B and subsequent effects were analyzed by RT‐qPCR, immunoblotting, chromatin immunoprecipitation, immunocytochemistry, and mass spectrometry. Analyzing CHB highlighted that areas with high HIF1α levels and low A3B expression correlated with high HBcAg, potentially representing a reservoir for HBV survival in immune‐active patients. In vitro, HIF1α stabilization strongly impaired A3B expression and anti‐HBV effect. Interestingly, HIF1α knockdown was sufficient to rescue the inhibition of A3B up‐regulation and ‐mediated antiviral effects, whereas HIF2α knockdown had no effect. HIF1α stabilization decreased the level of v‐rel reticuloendotheliosis viral oncogene homolog B protein, but not its mRNA, which was confirmed in vivo. Noteworthy, this function of HIF1α was independent of its partner, aryl hydrocarbon receptor nuclear translocator. Conclusions: In conclusion, inhibiting HIF1α expression or stabilization represents an anti‐HBV strategy in the context of immune‐mediated A3B induction. High HIF1α, mediated by hypoxia or inflammation, offers a reservoir for HBV survival in vivo and should be considered as a restricting factor in the development of immune therapies

    Electronic Support for Retrospective Analysis in the Field of Radiation Oncology: Proof of Principle Using an Example of Fractionated Stereotactic Radiotherapy of 251 Meningioma Patients

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    Introduction: The purpose of this study is to verify the possible benefit of a clinical data warehouse (DWH) for retrospective analysis in the field of radiation oncology. Material and methods: We manually and electronically (using DWH) evaluated demographic, radiotherapy, and outcome data from 251 meningioma patients, who were irradiated from January 2002 to January 2015 at the Department of Radiation Oncology of the Erlangen University Hospital. Furthermore, we linked the Oncology Information System (OIS) MOSAIQ® to the DWH in order to gain access to irradiation data. We compared the manual and electronic data retrieval method in terms of congruence of data, corresponding time, and personal requirements (physician, physicist, scientific associate). Results: The electronically supported data retrieval (DWH) showed an average of 93.9% correct data and significantly (p = 0.009) better result compared to manual data retrieval (91.2%). Utilizing a DWH enables the user to replace large amounts of manual activities (668 h), offers the ability to significantly reduce data collection time and labor demand (35 h), while simultaneously improving data quality. In our case, work time for manually data retrieval was 637 h for the scientific assistant, 26 h for the medical physicist, and 5 h for the physician (total 668 h). Conclusion: Our study shows that a DWH is particularly useful for retrospective analysis in the radiation oncology field. Routine clinical data for a large patient group can be provided ready for analysis to the scientist and data collection time can be significantly reduced. Furthermore, linking multiple data sources in a DWH offers the ability to improve data quality for retrospective analysis, and future research can be simplified

    The generic Informed Consent Service gICS®: implementation and benefits of a modular consent software tool to master the challenge of electronic consent management in research

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    Background Defining and protecting participants’ rights is the aim of several ethical codices and legal regulations. According to these regulations, the Informed Consent (IC) is an inevitable element of research with human subjects. In the era of “big data medicine”, aspects of IC become even more relevant since research becomes more complex rendering compliance with legal and ethical regulations increasingly difficult. Methods Based on literature research and practical experiences gathered by the Institute for Community Medicine (ICM), University Medicine Greifswald, requirements for digital consent management systems were identified. Results To address the requirements, the free-of-charge, open-source software “generic Informed Consent Service” (gICS®) was developed by ICM to provide a tool to facilitate and enhance usage of digital ICs for the international research community covering various scenarios. gICS facilitates IC management based on IC modularisation and supports various workflows within research, including (1) electronic depiction of paper-based consents and (2) fully electronic consents. Numerous projects applied gICS and documented over 336,000 ICs and 2400 withdrawals since 2014. Discussion Since the consent’s content is a prerequisite for securing participants’ rights, application of gICS is no guarantee for legal compliance. However, gICS supports fine-granular consents and accommodation of differentiated consent states, which can be directly exchanged between systems, allowing automated data processing. Conclusion gICS simplifies and supports sustained IC management as a major key to successfully conduct studies and build trust in research with human subjects. Therefore, interested researchers are invited to use gICS and provide feedback for further improvements

    Acceptance by laypersons and medical professionals of the personalized eHealth platform, eHealthMonitor

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    <p><i>Introduction and background</i>: Often, eHealth services are not accepted because of factors such as eHealth literacy or trust. Within this study, eHealthMonitor was evaluated in three European countries (Germany, Greece, and Poland) by medical professionals and laypersons with respect to numerous acceptance factors. <i>Methods</i>: Questionnaires were created on the basis of factors from literature and with the help of scales which have already been validated. A qualitative survey was conducted in Germany, Poland, and Greece. <i>Results</i>: The eHealth literacy of all participants was medium/high. Laypersons mostly agreed that they could easily become skillful with eHealthMonitor and that other people thought that they should use eHealthMonitor. Amongst medical professionals, a large number were afraid that eHealthMonitor could violate their privacy or the privacy of their patients. Overall, the participants thought that eHealthMonitor was a good concept and that they would use it. <i>Discussion and conclusion</i>: The main hindrances to the use of eHealthMonitor were found in trust issues including data privacy. In the future, more research on the linkage of all measured factors is needed, for example, to address the question of whether highly educated people tend to mistrust eHealth information more than people with lower levels of education.</p

    The actin remodeling protein cofilin is crucial for thymic αβ but not γδ T-cell development

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    <div><p>Cofilin is an essential actin remodeling protein promoting depolymerization and severing of actin filaments. To address the relevance of cofilin for the development and function of T cells in vivo, we generated knock-in mice in which T-cell–specific nonfunctional (nf) cofilin was expressed instead of wild-type (WT) cofilin. Nf cofilin mice lacked peripheral αβ T cells and showed a severe thymus atrophy. This was caused by an early developmental arrest of thymocytes at the double negative (DN) stage. Importantly, even though DN thymocytes expressed the TCRβ chain intracellularly, they completely lacked TCRβ surface expression. In contrast, nf cofilin mice possessed normal numbers of γδ T cells. Their functionality was confirmed in the γδ T-cell–driven, imiquimod (IMQ)-induced, psoriasis-like murine model. Overall, this study not only highlights the importance of cofilin for early αβ T-cell development but also shows for the first time that an actin-binding protein is differentially involved in αβ versus γδ T-cell development.</p></div

    Mice expressing nf cofilin show a severe thymus atrophy and a developmental arrest at the DN3 stage.

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    <p>(A) Total T-cell number in spleen of B6 mice and nf cofilin knock-in mice (<i>n</i> = 6 independent experiments with a total of ≥8 mice per group). (B) Thymus was isolated and weighed, and the total cell number was determined from 4–5-weeks-old B6 or nf cofilin knock-in mice (<i>n</i> = 6 independent experiments with a total of ≥10 mice per group). (C) Flow cytometric analysis of thymocyte differentiation by CD4, CD8, CD25, and CD44 staining (<i>n</i> ≥ 8 mice per group). Exemplary dot blots from representative mice are shown on the left, whereas the statistical evaluation of summary data is shown in the middle (for DN, DP, and SP stages) and on the right (for DN cell stages). (D) Creation of mixed bone marrow chimera. Lethally irradiated B6 mice were reconstituted with equal numbers of CD3<sup>+</sup> cell–depleted BM cells from CD45.2<sup>+</sup> tester (Cfl1<sup>nf/nf</sup>) and CD45.1<sup>+</sup> competitor (B6) mice. Total chimerism was measured and CD4 versus CD8 plots show the developmental stage of thymocytes derived from CD45.1<sup>+</sup> or CD45.2<sup>+</sup> BM cells. Plots are representative of six mixed chimeras per group. Bar graphs show the average abundance of each major thymocyte population within the chimera from both tester (CD45.2<sup>+</sup>) and competitor (CD45.1<sup>+</sup>) donor cells. Data is represented as mean ± SEM. **** = p<0.0001; ** = p<0.01. Underlying Data can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2005380#pbio.2005380.s006" target="_blank">S1 Data</a>. BM, bone marrow; DN, double negative; DP, double positive; SP, single positive.</p

    DN thymocytes of Cfl1<sup>nf/nf</sup> mice show a dramatically enhanced F-actin content and impaired migratory capacity as well as a lack of TCRβ surface expression.

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    <p>(A) CD3<sup>+</sup> splenocytes were analyzed for expression of TCRβ and TCRγδ. Shown are representative dot blots (left panels) and calculated absolute cell numbers (right panel) of TCRβ and TCRγδ expressing cells. Data is represented as mean ± SEM and summarizes 3 independent experiments with a total of 6 mice per group. (B) Total F-actin amount of DN thymocytes or γδ thymocytes was determined by SiR-actin staining (<i>n</i> = 3 independent experiments with a total ≥6 mice per group). (C) Migratory capacity of DN cells or γδ thymocytes was determined in a transwell assay (pore size 5 μm) in which SDF-1α (200 ng/ml) was used as chemotactic stimulus. Migration was carried out for 3 h (<i>n</i> = 3 independent experiments with ≥4 mice per group). (D) TCRβ surface (surface TCRβ) and intracellular (ic TCRβ) expression was analyzed in DN cells by flow cytometry. Representative dot plots from TCRβ versus TCRγδ staining on B6 and Cfl1<sup>nf/nf</sup> DN cells are shown (<i>n</i> = 4 independent experiments with a total of ≥7 mice per group). (E) Analysis of surface and ic expression of TCRβ in DN cells of B6 (grey bar) and Cfl1<sup>nf/nf</sup> mice (black bar) (left bar chart). Analysis of MFI of TCRβ of icTCRβ<sup>+</sup> DN cells of B6 (grey bar) and Cfl1<sup>nf/nf</sup> mice (black bar) (right bar chart). (F) Analysis of surface expression of TCRβ in DN thymocytes of B6 and Cfl1<sup>nf/nf</sup> mice before (-cytoD) and after cytochalasin D treatment (+cytoD). Data is represented as mean ± SEM. **** <i>p</i> < 0.0001; *** <i>p</i> < 0.001; ** <i>p</i> < 0.01; * <i>p</i> < 0.05; Underlying data can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2005380#pbio.2005380.s006" target="_blank">S1 Data</a>. cytoD, cytochalasin D; ic, intracellular; MFI, mean fluorescence intensity nf, nonfunctional; ns, not significant.</p

    Cfl1<sup>nf/nf</sup> mice show normal γδ T-cell subsets which remain functional.

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    <p>(A) Analysis of the surface expression of Vγ1, Vγ2, and Vγ3 of γδ T-cells isolated from the spleen, skin, lung, and thymus of B6 (grey bar) or Cfl1<sup>nf/nf</sup> mice (black bar) (<i>n</i> = 4 independent experiments with ≥4 mice per group). (B) Analysis of the surface expression of CD24, CD27, and CD44 of γδ thymocytes of B6 (grey bar) or Cfl1<sup>nf/nf</sup> mice (black bar) (<i>n</i> = 4 independent experiments with ≥4 mice per group). (C) In vitro activation of splenic γδ T cells of Cfl1<sup>nf/nf</sup> (black bar) and control mice (grey bar) by plate-bound CD3 and CD28 antibodies for 24 h. Determination of the T-cell activation markers CD25 (left bar chart) and CD69 (right bar chart) by flow cytometry. (D) Age- and sex-matched Cfl1<sup>nf/nf</sup> (red line) and Cfl1<sup>+/+</sup> (black line) mice at 7 weeks of age were used for an IMQ-induced psoriasis-like model. Over 6 days, prior to topical application of IMQ, scores of individual parameters such as scaling, back skin thickness, and erythema formation were measured and the accumulated PASI was calculated. (E) Flow cytometric analysis of IL-17A and RORγt expression in γδ T cells of skin-draining LNs. Cytokine production was assessed after 6 days of topical application of IMQ containing Aldara crème (Sham) or control crème (Aldara) (experiment with ≥4 mice per group). Data are represented as mean ± SEM. **** <i>p</i> < 0.0001; *** <i>p</i> < 0.001; ** <i>p</i> < 0.01; * <i>p</i> < 0.05; Underlying data can be found in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2005380#pbio.2005380.s006" target="_blank">S1 Data</a>. Cfl1, cofilin-1; IMQ, imiquimod; ns, not significant; PASI, psoriasis area severity index.</p
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