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DNA methylation was shown previously to be a crucial mechanism responsible for transcriptional deregulation in the pathogenesis of classical Hodgkin lymphoma (cHL). To identify epigenetically inactivated miRNAs in cHL, we have analyzed the set of miRNAs downregulated in cHL cell lines using bisulfite pyrosequencing. We focused on miRNAs with promoter regions located within or <1000 bp from a CpG island. Most promising candidate miRNAs were further studied in primary Hodgkin and Reed-Sternberg (HRS) cells obtained by laser capture microdissection. Last, to evaluate the function of identified miRNAs, we performed a luciferase reporter assay to confirm miRNA: mRNA interactions and therefore established cHL cell lines with stable overexpression of selected miRNAs for proliferation tests. We found a significant reverse correlation between DNA methylation and expression levels of mir-339-3p, mir-148a-3p, mir-148a-5p and mir-193a-5 demonstrating epigenetic regulation of these miRNAs in cHL cell lines. Moreover, we demonstrated direct interaction between miR-148a-3p and IL15 and HOMER1 transcripts as well as between mir-148a-5p and SUB1 and SERPINH1 transcripts. Furthermore, mir-148a overexpression resulted in reduced cell proliferation in the KM-H2 cell line. In summary, we report that mir-148a is a novel tumor suppressor inactivated in cHL and that epigenetic silencing of miRNAs is a common phenomenon in cHL.
Background: International travel is a major driver of the introduction and spread of SARS- CoV-2. Aim: To investigate SARS-CoV-2 genetic diversity in the region of a major transport hub in Germany, we characterized the viral sequence diversity of the SARS-CoV-2 variants circulating in Frankfurt am Main, the city with the largest airport in Germany, from the end of October to the end of December 2020. Methods: In total, we recovered 136 SARS-CoV-2 genomes from nasopharyngeal swab samples. We isolated 104 isolates that were grown in cell culture and RNA from the recovered viruses and subjected them to full-genome sequence analysis. In addition, 32 nasopharyngeal swab samples were directly sequenced. Results and conclusion: We found 28 different lineages of SARS- CoV-2 circulating during the study period, including the variant of concern B.1.1.7 (∆69/70, N501Y). Six of the lineages had not previously been observed in Germany. We detected the spike protein (S) deletion ∆69/∆70 in 15% of all sequences, a four base pair (bp) deletion (in 2.9% of sequences) and a single bp deletion (in 0.7% of sequences) in ORF3a, leading to ORF3a truncations. In four sequences (2.9%), an amino acid deletion at position 210 in S was identified. In a single sample (0.7%), both a 9 bp deletion in ORF1ab and a 7 bp deletion in ORF7a were identified. One sequence in lineage B.1.1.70 had an N501Y substitution while lacking the ∆69/70 in S. The high diversity of sequences observed over two months in Frankfurt am Main highlights the persisting need for continuous SARS-CoV-2 surveillance using full-genome sequencing, particularly in cities with international airport connections.
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.
Systemic treatment is necessary for one third of patients with renal cell carcinoma. No valid biomarker is currently available to tailor personalized therapy. In this study we established a representative panel of patient derived xenograft (PDX) mouse models from patients with renal cell carcinomas and determined serum levels of high mobility group B1 (HMGB1) protein under treatment with sunitinib, pazopanib, sorafenib, axitinib, temsirolimus and bevacizumab. Serum HMGB1 levels were significantly higher in a subset of the PDX collection, which exhibited slower tumor growth during subsequent passages than tumors with low HMGB1 serum levels. Pre-treatment PDX serum HMGB1 levels also correlated with response to systemic treatment: PDX models with high HMGB1 levels predicted response to bevacizumab. Taken together, we provide for the first time evidence that the damage associated molecular pattern biomarker HMGB1 can predict response to systemic treatment with bevacizumab. Our data support the future evaluation of HMGB1 as a predictive biomarker for bevacizumab sensitivity in patients with renal cell carcinoma.
Hematopoietic differentiation is driven by transcription factors, which orchestrate a finely tuned transcriptional network. At bipotential branching points lineage decisions are made, where key transcription factors initiate cell type-specific gene expression programs. These programs are stabilized by the epigenetic activity of recruited chromatin-modifying cofactors. An example is the association of the transcription factor RUNX1 with protein arginine methyltransferase 6 (PRMT6) at the megakaryocytic/erythroid bifurcation. However, little is known about the specific influence of PRMT6 on this important branching point. Here, we show that PRMT6 inhibits erythroid gene expression during megakaryopoiesis of primary human CD34+ progenitor cells. PRMT6 is recruited to erythroid genes, such as glycophorin A. Consequently, a repressive histone modification pattern with high H3R2me2a and low H3K4me3 is established. Importantly, inhibition of PRMT6 by shRNA or small molecule inhibitors leads to upregulation of erythroid genes and promotes erythropoiesis. Our data reveal that PRMT6 plays a role in the control of erythroid/megakaryocytic differentiation and open up the possibility that manipulation of PRMT6 activity could facilitate enhanced erythropoiesis for therapeutic use.
Poster presentation: Introduction The ability of neurons to emit different firing patterns is considered relevant for neuronal information processing. In dopaminergic neurons, prominent patterns include highly regular pacemakers with separate spikes and stereotyped intervals, processes with repetitive bursts and partial regularity, and irregular spike trains with nonstationary properties. In order to model and quantify these processes and the variability of their patterns with respect to pharmacological and cellular properties, we aim to describe the two dimensions of burstiness and regularity in a single model framework. Methods We present a stochastic spike train model in which the degree of burstiness and the regularity of the oscillation are described independently and with two simple parameters. In this model, a background oscillation with independent and normally distributed intervals gives rise to Poissonian spike packets with a Gaussian firing intensity. The variability of inter-burst intervals and the average number of spikes in each burst indicate regularity and burstiness, respectively. These parameters can be estimated by fitting the model to the autocorrelograms. This allows to assign every spike train a position in the two-dimensional space described by regularity and burstiness and thus, to investigate the dependence of the firing patterns on different experimental conditions. Finally, burst detection in single spike trains is possible within the model because the parameter estimates determine the appropriate bandwidth that should be used for burst identification. Results and Discussion We applied the model to a sample data set obtained from dopaminergic substantia nigra and ventral tegmental area neurons recorded extracellularly in vivo and studied differences between the firing activity of dopaminergic neurons in wildtype and K-ATP channel knock-out mice. The model is able to represent a variety of discharge patterns and to describe changes induced pharmacologically. It provides a simple and objective classification scheme for the observed spike trains into pacemaker, irregular and bursty processes. In addition to the simple classification, changes in the parameters can be studied quantitatively, also including the properties related to bursting behavior. Interestingly, the proposed algorithm for burst detection may be applicable also to spike trains with nonstationary firing rates if the remaining parameters are unaffected. Thus, the proposed model and its burst detection algorithm can be useful for the description and investigation of neuronal firing patterns and their variability with cellular and experimental conditions.
Poster presentation: Introduction Dopaminergic neurons in the midbrain show a variety of firing patterns, ranging from very regular firing pacemaker cells to bursty and irregular neurons. The effects of different experimental conditions (like pharmacological treatment or genetical manipulations) on these neuronal discharge patterns may be subtle. Applying a stochastic model is a quantitative approach to reveal these changes. ...
Predominant polarity in bipolar disorder and validation of the polarity index in a German sample
(2014)
Background: A large number of patients with bipolar disorder (BD) can be characterized by predominant polarity (PP), which has important implications for relapse prevention. Recently, Popovic et al. (EUR NEUROPSYCHOPHARM 22(5): 339¿346, 2012) proposed the Polarity Index (PI) as a helpful tool in the maintenance treatment of BD. As a numeric expression, it reflects the efficacy of drugs used in treatment of BD. In the present retrospective study, we aimed to validate this Index in a large and well characterized German bipolar sample.
Methods: We investigated 336 bipolar patients (BP) according to their PP and calculated the PI for each patient in order to prove if maintenance treatment differs according to their PP. Furthermore, we analysed whether PP is associated with demographic and clinical characteristics of BP.
Results: In our sample, 63.9% of patients fulfilled criteria of PP: 169 patients were classified as depressive predominant polarity (DPP), 46 patients as manic predominant polarity (MPP). The two groups differed significantly in their drug regime: Patients with DPP were more often medicated with lamotrigine and antidepressants, patients with MPP were more often treated with lithium, valproate, carbamazepine and first generation antipsychotics. However, patients with DPP and MPP did not differ significantly with respect to the PI, although they received evidence-based and guideline-driven treatment.
Conclusion: The reason for this negative finding might well be that for several drugs, which were used frequently, no PI value is available. Nevertheless we suggest PP as an important concept in the planning of BD maintenance treatment.
Understanding the role of structure and social aspects regarding heat stress of people in urban areas requires an interdisciplinary scientific approach that connects methods from both natural sciences and social sciences. In this study, we combine three approaches to provide an interdisciplinary analysis of the structure and social components of heat stress in the city of Aachen, Germany. First, we assess the overall spatial structure of the urban heat island using spatially distributed measurements from mobile air temperature recordings on public transport units combined with spatially distributed geo-statistical data. The results indicate that the time of day matters: During the afternoon, areas with a relative low building density, like the industrial area northeast of the inner city, are the warmest, while surfaces in high-building-density areas like the inner city heat up faster during the evening. Second, we combine these measurements with place-based survey data collected in 2010 from residents aged 50 to 92 regarding their individual housing conditions, medical history and social integration to examine the match among heat-based stress of older residents, social conditions and elevated temperatures in their residential quarter. We identify disadvantaged areas for specific already-disadvantaged demographic groups in the city, pointing to a cumulation of inequalities, including heat stress among the most vulnerable. Third, we compare data of biometeorological measurements on urban public squares during the afternoon with results of the micrometeorological model ENVI-met to examine the spatial variability of the inner-city heat load. We complement the modelling results with on-site interviews to evaluate people’s heat perception at the same public places. A simulation shows that additional vegetation would increase thermal comfort at these public places, whereby the heat load assessed using the predicted mean vote (PMV) value would decrease by approximately 60 %. Furthermore, we demonstrate the strengths and weaknesses of heat stress simulation. ENVI-met allows for an overall reasonable representation of heat load during stable atmospheric conditions. However, due to the setup and structure of ENVI-met, large-scale atmospheric changes that occur during the day cannot readily be integrated into ENVI-met simulations.
The antiviral drugs tecovirimat, brincidofovir, and cidofovir are considered for mpox (monkeypox) treatment despite a lack of clinical evidence. Moreover, their use is affected by toxic side-effects (brincidofovir, cidofovir), limited availability (tecovirimat), and potentially by resistance formation. Hence, additional, readily available drugs are needed. Here, therapeutic concentrations of nitroxoline, a hydroxyquinoline antibiotic with a favourable safety profile in humans, inhibited the replication of 12 mpox virus isolates from the current outbreak in primary cultures of human keratinocytes and fibroblasts and a skin explant model by interference with host cell signalling. Tecovirimat, but not nitroxoline, treatment resulted in rapid resistance development. Nitroxoline remained effective against the tecovirimat-resistant strain and increased the anti-mpox virus activity of tecovirimat and brincidofovir. Moreover, nitroxoline inhibited bacterial and viral pathogens that are often co-transmitted with mpox. In conclusion, nitroxoline is a repurposing candidate for the treatment of mpox due to both antiviral and antimicrobial activity.