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Background Post-viral symptoms have long been known in the medical community but have received more public attention during the COVID-19 pandemic. Many post-viral symptoms were reported as particularly frequent after SARS-CoV-2 infection. However, there is still a lack of evidence regarding the specificity, frequency and persistence of these symptoms in comparison to other viral infectious diseases such as influenza. Methods We investigated a large population-based cohort based on German routine healthcare data. We matched 573,791 individuals with a PCR-test confirmed SARS-CoV-2 infection from the year 2020 to contemporary controls without SARS-CoV-2 infection and controls from the last influenza outbreak in 2018 and followed them up to 18 months. Results We found that post-viral symptoms as defined for COVID-19 by the WHO as well as tissue damage were more frequent among the COVID-19 cohort than the influenza or contemporary control cohort. The persistence of post-viral symptoms was similar between COVID-19 and influenza. Conclusion Post-viral symptoms following SARS-CoV-2 infection constitute a substantial disease burden as they are frequent and often persist for many months. As COVID-19 is becoming endemic, the disease must not be trivialized. Research should focus on the development of effective treatments for post-viral symptoms.

Interleukin-6 (IL-6)-activated Signal Transducer and Activator of Transcription 3 (STAT3) facilitates survival in the multiple myeloma cell line INA-6 and therefore represents an oncogenic key player. However, the biological mechanisms are still not fully understood. In previous studies we identified microRNA-21 as a STAT3 target gene with strong anti-apoptotic potential, suggesting that noncoding RNAs have an impact on the pathogenesis of human multiple myeloma. Here, we describe five long noncoding RNAs (lncRNAs) induced by IL-6-activated STAT3, which we named STAiRs. While STAiRs 1, 2 and 6 remain unprocessed in the nucleus and show myeloma-specific expression, STAiRs 15 and 18 are spliced and broadly expressed. Especially STAiR2 and STAiR18 are promising candidates. STAiR2 originates from the first intron of a tumor suppressor gene. Our data support a mutually exclusive expression of either STAiR2 or the functional tumor suppressor in INA-6 cells and thus a contribution of STAiR2 to tumorigenesis. Furthermore, STAiR18 was shown to be overexpressed in every tested tumor entity, indicating its global role in tumor pathogenesis. Taken together, our study reveals a number of STAT3-induced lncRNAs suggesting that the interplay between the coding and noncoding worlds represents a fundamental principle of STAT3-driven cancer development in multiple myeloma and beyond.

In infective endocarditis (IE), a severe inflammatory disease of the endocardium with an unchanged incidence and mortality rate over the past decades, only 1% of the cases have been described as polymicrobial infections based on microbiological approaches. The aim of this study was to identify potential biodiversity of bacterial species from infected native and prosthetic valves. Furthermore, we compared the ultrastructural micro-environments to detect the localization and distribution patterns of pathogens in IE. Using next-generation sequencing (NGS) of 16S rDNA, which allows analysis of the entire bacterial community within a single sample, we investigated the biodiversity of infectious bacterial species from resected native and prosthetic valves in a clinical cohort of 8 IE patients. Furthermore, we investigated the ultrastructural infected valve micro-environment by focused ion beam scanning electron microscopy (FIB-SEM). Biodiversity was detected in 7 of 8 resected heart valves. This comprised 13 bacterial genera and 16 species. In addition to 11 pathogens already described as being IE related, 5 bacterial species were identified as having a novel association. In contrast, valve and blood culture-based diagnosis revealed only 4 species from 3 bacterial genera and did not show any relevant antibiotic resistance. The antibiotics chosen on this basis for treatment, however, did not cover the bacterial spectra identified by our amplicon sequencing analysis in 4 of 8 cases. In addition to intramural distribution patterns of infective bacteria, intracellular localization with evidence of bacterial immune escape mechanisms was identified. The high frequency of polymicrobial infections, pathogen diversity, and intracellular persistence of common IE-causing bacteria may provide clues to help explain the persistent and devastating mortality rate observed for IE. Improved bacterial diagnosis by 16S rDNA NGS that increases the ability to tailor antibiotic therapy may result in improved outcomes.

The formation of transient networks in response to external stimuli or as a reflection of internal cognitive processes is a hallmark of human brain function. However, its identification in fMRI data of the human brain is notoriously difficult. Here we propose a new method of fMRI data analysis that tackles this problem by considering large-scale, task-related synchronisation networks. Networks consist of nodes and edges connecting them, where nodes correspond to voxels in fMRI data, and the weight of an edge is determined via task-related changes in dynamic synchronisation between their respective times series. Based on these definitions, we developed a new data analysis algorithm that identifies edges that show differing levels of synchrony between two distinct task conditions and that occur in dense packs with similar characteristics. Hence, we call this approach \"Task-related Edge Density\" (TED). TED proved to be a very strong marker for dynamic network formation that easily lends itself to statistical analysis using large scale statistical inference. A major advantage of TED compared to other methods is that it does not depend on any specific hemodynamic response model, and it also does not require a presegmentation of the data for dimensionality reduction as it can handle large networks consisting of tens of thousands of voxels. We applied TED to fMRI data of a fingertapping and an emotion processing task provided by the Human Connectome Project. TED revealed network-based involvement of a large number of brain areas that evaded detection using traditional GLM-based analysis. We show that our proposed method provides an entirely new window into the immense complexity of human brain function.

Background The survival of INA-6 human multiple myeloma cells is strictly dependent upon the Interleukin-6-activated transcription factor STAT3. Although transcriptional analyses have revealed many genes regulated by STAT3, to date no protein-coding STAT3 target gene is known to mediate survival in INA-6 cells. Therefore, the aim here was to identify and analyze non-protein-coding STAT3 target genes. In addition to the oncogenic microRNA-21, we previously described five long noncoding RNAs (lncRNAs) induced by STAT3, named STAiRs. Here, we focus on STAT3-induced RNA 18 (STAiR18), an mRNA-like, long ncRNA that is duplicated in the human lineage. One STAiR18 locus is annotated as the already well described LINC00152/CYTOR, however, the other harbors the MIR4435-2HG gene and is, up to now, barely described. Methods CAPTURE-RNA-sequencing was used to analyze STAiR18 transcript architecture. To identify the STAiR18 and STAT3 phenotype, siRNA-based knockdowns were performed and microarrays were applied to identify their target genes. RNA-binding partners of STAiR18 were determined by Chromatin-Isolation-by-RNA-Purification (ChIRP) and subsequent sequencing. STAT3 expression in dependence of STAiR18 was investigated by immunoblots, chromatin- and RNA-immunoprecipitations. Results As identified by CAPTURE-RNA sequencing, a complex splice pattern originates from both STAiR18 loci, generating different transcripts. Knockdown of the most abundant STAiR18 isoforms dramatically decreased INA-6 cell vitality, suggesting a functional role in myeloma cells. Additionally, STAiR18 and STAT3 knockdowns yielded overlapping changes of transcription patterns in INA-6 cells, suggesting a close functional interplay between the two factors. Moreover, Chromatin isolation by RNA purification (ChIRP), followed by genome-wide RNA sequencing showed that STAiR18 associates specifically with the STAT3 primary transcript. Furthermore, the knockdown of STAiR18 reduced STAT3 levels on both the RNA and protein levels, suggesting a positive feedback between both molecules. Furthermore, STAiR18 knockdown changes the histone methylation status of the STAT3 locus, which explains the positive feedback and indicates that STAiR18 is an epigenetic modulator. Conclusion Hence, STAiR18 is an important regulator of myeloma cell survival and is strongly associated with the oncogenic function of STAT3. The close functional interplay between STAT3 and STAiR18 suggests a novel principle of regulatory interactions between long ncRNAs and signaling pathways.

In 2019, the novel highly infectious severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak rapidly led to a global pandemic with more than 346 million confirmed cases worldwide, resulting in 5.5 million associated deaths (January 2022). Entry of all SARS-CoV-2 variants is mediated by the cellular angisin-converting enzyme 2 (ACE2). The virus abundantly replicates in the epithelia of the upper respiratory tract. Beyond vaccines for immunization, there is an imminent need for novel treatment options in COVID-19 patients. So far, only a few drugs have found their way into the clinics, often with modest success. Specific gene silencing based on small interfering RNA (siRNA) has emerged as a promising strategy for therapeutic intervention, preventing/limiting SARS-CoV-2 entry into host cells or interfering with viral replication. Here, we pursued both strategies. We designed and screened nine siRNAs (siA1-9) targeting the viral entry receptor ACE2. SiA1, (siRNA against exon1 of ACE2 mRNA) was most efficient, with up to 90% knockdown of the ACE2 mRNA and protein for at least six days. In vitro, siA1 application was found to protect Vero E6 and Huh-7 cells from infection with SARS-CoV-2 with an up to ∼92% reduction of the viral burden indicating that the treatment targets both the endosomal and the viral entry at the cytoplasmic membrane. Since the RNA-encoded genome makes SARS-CoV-2 vulnerable to RNA interference (RNAi), we designed and analysed eight siRNAs (siV1-8) directly targeting the Orf1a/b region of the SARS-CoV-2 RNA genome, encoding for non-structural proteins (nsp). As a significant hallmark of this study, we identified siV1 (siRNA against leader protein of SARS-CoV-2), which targets the nsp1-encoding sequence (a.k.a. ‘host shutoff factor’) as particularly efficient. SiV1 inhibited SARS-CoV-2 replication in Vero E6 or Huh-7 cells by more than 99% or 97%, respectively. It neither led to toxic effects nor induced type I or III interferon production. Of note, sequence analyses revealed the target sequence of siV1 to be highly conserved in SARS-CoV-2 variants. Thus, our results identify the direct targeting of the viral RNA genome (ORF1a/b) by siRNAs as highly efficient and introduce siV1 as a particularly promising drug candidate for therapeutic intervention.

Background High-throughput sequencing technologies are improving in quality, capacity and costs, providing versatile applications in DNA and RNA research. For small genomes or fraction of larger genomes, DNA samples can be mixed and loaded together on the same sequencing track. This so-called multiplexing approach relies on a specific DNA tag or barcode that is attached to the sequencing or amplification primer and hence appears at the beginning of the sequence in every read. After sequencing, each sample read is identified on the basis of the respective barcode sequence. Alterations of DNA barcodes during synthesis, primer ligation, DNA amplification, or sequencing may lead to incorrect sample identification unless the error is revealed and corrected. This can be accomplished by implementing error correcting algorithms and codes. This barcoding strategy increases the total number of correctly identified samples, thus improving overall sequencing efficiency. Two popular sets of error-correcting codes are Hamming codes and Levenshtein codes. Result Levenshtein codes operate only on words of known length. Since a DNA sequence with an embedded barcode is essentially one continuous long word, application of the classical Levenshtein algorithm is problematic. In this paper we demonstrate the decreased error correction capability of Levenshtein codes in a DNA context and suggest an adaptation of Levenshtein codes that is proven of efficiently correcting nucleotide errors in DNA sequences. In our adaption we take the DNA context into account and redefine the word length whenever an insertion or deletion is revealed. In simulations we show the superior error correction capability of the new method compared to traditional Levenshtein and Hamming based codes in the presence of multiple errors. Conclusion We present an adaptation of Levenshtein codes to DNA contexts capable of correction of a pre-defined number of insertion, deletion, and substitution mutations. Our improved method is additionally capable of recovering the new length of the corrupted codeword and of correcting on average more random mutations than traditional Levenshtein or Hamming codes. As part of this work we prepared software for the flexible generation of DNA codes based on our new approach. To adapt codes to specific experimental conditions, the user can customize sequence filtering, the number of correctable mutations and barcode length for highest performance.

ObjectivesTo investigate whether the risk of developing an incident autoimmune disease is increased in patients with prior COVID-19 disease compared to those without COVID-19, a large cohort study was conducted.MethodA cohort was selected from German routine health care data. Based on documented diagnoses, we identified individuals with polymerase chain reaction (PCR)-confirmed COVID-19 through December 31, 2020. Patients were matched 1:3 to control patients without COVID-19. Both groups were followed up until June 30, 2021. We used the four quarters preceding the index date until the end of follow-up to analyze the onset of autoimmune diseases during the post-acute period. Incidence rates (IR) per 1000 person-years were calculated for each outcome and patient group. Poisson models were deployed to estimate the incidence rate ratios (IRRs) of developing an autoimmune disease conditional on a preceding diagnosis of COVID-19.ResultsIn total, 641,704 patients with COVID-19 were included. Comparing the incidence rates in the COVID-19 (IR=15.05, 95% CI: 14.69–15.42) and matched control groups (IR=10.55, 95% CI: 10.25–10.86), we found a 42.63% higher likelihood of acquiring autoimmunity for patients who had suffered from COVID-19. This estimate was similar for common autoimmune diseases, such as Hashimoto thyroiditis, rheumatoid arthritis, or Sjögren syndrome. The highest IRR was observed for autoimmune diseases of the vasculitis group. Patients with a more severe course of COVID-19 were at a greater risk for incident autoimmune disease.ConclusionsSARS-CoV-2 infection is associated with an increased risk of developing new-onset autoimmune diseases after the acute phase of infection. Key Points• In the 3 to 15 months after acute infection, patients who had suffered from COVID-19 had a 43% (95% CI: 37–48%) higher likelihood of developing a first-onset autoimmune disease, meaning an absolute increase in incidence of 4.50 per 1000 person-years over the control group.• COVID-19 showed the strongest association with vascular autoimmune diseases.

Functional magnetic resonance imaging (fMRI) is the workhorse of imaging-based human cognitive neuroscience. The use of fMRI is ever-increasing; within the last 4 years more fMRI studies have been published than in the previous 17 years. This large body of research has mainly focused on the functional localization of condition- or stimulus-dependent changes in the blood-oxygenation-level dependent signal. In recent years, however, many aspects of the commonly practiced analysis frameworks and methodologies have been critically reassessed. Here we summarize these critiques, providing an overview of the major conceptual and practical deficiencies in widely used brain-mapping approaches, and exemplify some of these issues by the use of imaging data and simulations. In particular, we discuss the inherent pitfalls and shortcomings of methodologies for statistical parametric mapping. Our critique emphasizes recent reports of excessively high numbers of both false positive and false negative findings in fMRI brain mapping. We outline our view regarding the broader scientific implications of these methodological considerations and briefly discuss possible solutions.

Purpose Evidence on the incidence and persistence of post-acute sequelae of COVID-19 (PASC) among children and adolescents is still limited. Methods In this retrospective cohort study, 59,339 children and adolescents with laboratory-confirmed COVID-19 in 2020 and 170,940 matched controls were followed until 2021-09-30 using German routine healthcare data. Incidence rate differences (ΔIR) and ratios (IRR) of 96 potential PASC were estimated using Poisson regression. Analyses were stratified according to age (0–11, 12–17 years), and sex. At the individual level, persistence of diagnoses in patients with onset symptoms was tracked starting from the first quarter post-infection. Results At 0–3 month follow-up, children and adolescents with a previous SARS-CoV-2 infection showed a 34% increased risk of adverse health outcome, and approximately 6% suffered from PASC in association with COVID-19. The attributable risk was higher among adolescents (≥ 12 years) than among children. For most common symptoms, IRRs largely persisted at 9–12 month follow-up. IRR were highest for rare conditions strongly associated with COVID-19, particularly inflammatory conditions among children 0–11 years, and chronic fatigue and respiratory insufficiency among adolescents. Tracking of diagnoses at the individual level revealed similar rates in the decline of symptoms among COVID-19 and control cohorts, generally leaving less than 10% of the patients with persistent diagnoses after 12 months. Conclusion Although very few patients presented symptoms for longer than 12 months, excess morbidity among children and, particularly, adolescents with a history of COVID-19 means a relevant burden for pediatric care.