dataesr/scientific-paragraphs-categorization huggingface dataset:
Study design Step 1: Training program. In study Step 1, all participating centers received an EBUS system (BF-UC160F-OL8; Olympus, Keymed, UK) and dedicated puncture kits sufficient for 40 procedures free-of-charge, provided that they accepted prospective evaluation of all subsequent procedures. All the investigators underwent 2 days of high-benchmark training to learn the EBUS-TBNA procedure and were certified for study Step 2 if, during a 6-month period, at least nine of their 10 consecutive procedures were informative (tissue biopsies containing lymphocytes or tumor cells in at least one station). Several investigators could be certified in each center. All consecutive eligible patients were informed of the protocol, gave their signed informed consent to participate and were enrolled in a central database before the procedure.
Statistical analyses Demographic and clinical characteristics of the study population are summarized as means ± standard deviation, medians or numbers (%), depending on their type and distribution. The accuracies of EBUS-TBNA and mediastinoscopy were calculated, in terms of their sensitivity and negative-predictive value, for the entire population and the subgroups with positive-or negative positron-emission tomography (PET) scans. The design, running, analysis and reporting of this study conformed to the Standard of Reporting Diagnostic Accuracy Guidelines  [15]. The Nord-Ouest Research Ethics Committee, France, approved the study protocol on 26 March 2010. The ClinicalTrial. gov identifier is NCT00960271.
05) (Dataset S1). As expected, the number of dysregulated transcripts further increased at 8 wk of age: Over 687 genes were differentially expressed in the striatum of R6/1 mice, and an overwhelming majority of these genes (609) were downregulated, while fewer genes (78) showed increased expression in R6/1s compared to wild-types. Gene ontology (GO) analysis of the down-regulated genes revealed significant enrichments of numerous neuron-specific GO terms, such as synaptic signaling, neurological system process, and regulation of response to stimulus, indicating overall disruption of neuronal gene-expression programs early on in the striatum of R6/1 mice (Dataset S2). Key HD genes that are typically down-regulated across models and HD patients, such as dopamine receptor subtypes Drd1a and Drd2, adenosine receptor Adora2a, and many neuronal activity-regulated immediateearly genes, were among the down-regulated transcripts in the striatum of R6/1 mice at 8 wk of age.
1C ). To ascertain the concordance of the transcriptional changes in the HD mice and patients, we compared the differentially expressed genes in the striata of R6/1 and CHL2 mice with a previous HD patient study, which analyzed low-grade postmortem HD patient caudate (Vonsattel grades 0 to 2) by microarray analysis  (4, 5). This revealed a significant overlap of the genes differentially expressed in the striata of the R6/1 and CHL2 mice with differentially expressed genes in the caudate nuclei of postmortem brains from HD patients (161 genes in R6/1 [P < 3e-54] and 51 genes in CHL2 [P < 1. 3e-10]) (SI Appendix, Fig. S1  A and B and Dataset S3). Altogether, our results confirm that transcriptional dysregulation is a prominent disease feature in HD, and that the down-regulation of neuronal genes dominates the dysregulated HD transcriptome during the prodromal disease stage (before weight loss or appearance of clasping behavior in R6/1 and in CHL2 mice) (SI Appendix, Fig.
S1 C-E ). Histone H3K27acetylation Changes in Coordination with Transcription in the Striatum of Presymptomatic HD Mice. To understand the regulation of genes whose expression is altered in the striatum of HD mice during prodromal disease stages, we examined genomewide chromatin changes. Our aim was to measure changes in activities in both proximal and distal regulatory sites, which are key players for regulation of tissue-specific gene expression, during early HD. For this purpose, we performed ChIP-seq for histone H3K27acetylation, which marks active TSSs and enhancers, in the striatum of R6/1 mice at 8 wk of age when we measured the highest number of differentially expressed genes by RNA-seq in our study. Subsequent analysis of the ChIP-seq data confirmed H3K27acetylation occupancy at TSSs and distal regulatory sites (SI Appendix, Fig.
S2A ). To identify genes that show changes in H3K27acetylation occupancy in HD mouse striatum, we focused our analysis on a ±10-kb window around each TSS, associating H3K27acetylation peaks to the nearest TSS within this window. Analysis of the data in wild-type mice against a nonspecific background (IgG) showed highest H3K27acetylation signal for genes (top 1,000 genes by tags) that were enriched for GO terms relevant to brain functions, such as regulation of synaptic plasticity, regulation of neuron projection development, regulation of gene expression, and modulation of synaptic transmission, indicating the active chromatin environment surrounding neuronal genes in the striatum (Dataset S4). Comparative analysis of the data for overall changes in H3K27acetylation showed that 118 genes had significantly higher and 429 genes had lower H3K27acetylation levels in the striatum of 8-wk-old R6/1 mice compared to wild-type littermates.
Genes with reduced H3K27acetylation in the R6/1 striatum were associated with GO terms, such as regulation of localization and response to endogenous stimulus, while the genes with increased H3K27acetylation were enriched for dendrite morphogenesis and chromatin organization (Dataset S5). Integrative analysis of the H3K27acetylation ChIP-seq and RNA-seq datasets revealed a highly significant overlap between genes with decreased H3K27acetylation and decreased expression and between those with increased H3K27acetylation and increased expression in the striatum of R6/1 mice at 8 wk of age (t test P < 1. 5e-84 and P < 1. 5e-20, respectively) (Fig. 2A ), suggesting a high degree of coordination between the changes of chromatin and transcription starting from early stages of HD pathogenesis. We next analyzed our H3K27acetylation ChIP-seq data for a chromatin pattern that we previously described as marking the TSSs of neuronal genes that were down-regulated in the R6/2 strain of HD transgenic mice  (11).
In line with our previous findings, we detected 5 predominant patterns, or classes, of H3K27acetylation that occur in both wild-type and R6/1 mice (Fig. 2B ). The class 1 pattern, which has a broad peak of H3K27acetylation downstream of the TSS in wild-type as well as in R6/1 mice, captures 47% of genes that were down-regulated in the striatum of R6/1 mice (Fig. 2C ). The remaining 24%, 23%, 1%, and 4% of down-regulated genes were assigned to H3K27acetylation classes 2, 3, 4, and 5, respectively. Genes in class 1 were enriched in GO biological processes that are key for neuronal functions, such as signal transduction, regulation of nervous system development, regulation of cell communication, regulation of neurogenesis, neuron differentiation, axon guidance, behavior, and regulation of synaptic plasticity (Dataset S6).
To identify the highestconfidence transcription factor motifs, we used 3 separate methods for sequence analysis; the first based on motifs derived from TRANSFAC  (27) , the second based on overrepresentation of motifs using THEME  (28) , and the third method was a regressionbased approach combining the H3K27acetylation and gene-expression datasets  (29). The TRANSFAC-based approach searched for enrichment of known transcription factor binding motifs in so-called histone valleys, which have depletion of H3K27acetylation in the center and H3K27acetylation peaks on either side of the center, as the center of these chromatin structures could be accessible for transcriptional regulator binding  (11). The other 2 approaches were based on motif enrichments in the vicinity of the H3K27acetylation peaks.
These analyses revealed a set of common transcriptional regulator motifs. The top motif associated with regions with lower H3K27acetylation in the R6/1 striatum at 8 wk of age was repressor element-1 transcription factor (REST)/neuron-restrictive silencer factor (NRSF)/neuron-restrictive silencer element (NRSE) (P = 1. 26e-05), followed by Elk-1 binding motif (P = 2. 08e-03) and cAMP-responsive element binding protein (CREB) (P = 6. 35e-03) (P values derived from the TRANSFAC-based method) (Fig. 2D  and Dataset S7). Both REST  (30)  and CREB  (31)  have been previously linked to HD. Our regression-based motif analysis suggested possible regulators linked to H3K27acetylation peaks in the vicinity of the down-regulated genes in R6/1, such as NF-κB, and ETS family members, including Elk-1, NEUROD1, and REST.
Notably, some of these motifs, including REST and NF-κB, were also enriched in the promoters of the genes that were differentially expressed in the striatum of 4-wk-old R6/1 mice (Dataset S7), suggesting that their activities may be altered very early in the HD brain. In addition, in the CHL2 mice, H3K27acetylation ChIP-seq followed by motif analyses also showed enrichments for the ETS family, AP-1, and REST/NRSF/NRSE motifs linked to lower H3K27acetylation in the striatum of 1-y-old CHL2 mice. On the other hand, regions associated with higher H3K27acetylation in the R6/1 and CHL2 striata were associated with motifs, including members of the transcription factor OCT, ATF, and TCF families (Dataset S7).
In contrast, the Elk-1 experiments were of high quality. Elk-1 is a master regulator of genes regulated by neuronal activity and in the striatum, where it is considered a major transcriptional regulator together with CREB  (23, 24, 32). In our RNA-seq data, Elk-1 was not differentially expressed between the striata of HD and wild-type animals and, similarly, Western blotting showed that total cellular Elk-1 protein levels were not changed between the striata of R6/1 and wild-type mice at 8 wk of age (SI Appendix, Fig. S3 A  and B ). We used ChIP-seq to test whether Elk-1's binding to DNA is in fact altered in HD, as predicted by our motif-analysis results. Analysis of Elk-1 ChIP-seq data showed that the top genes bound by Elk-1 in wild-type animals were associated with GO biological processes, including regulation of chromatin organization, gene expression, RNA metabolic process to cellular localization, regulation of cell differentiation, and cellular response to stimulus (Dataset S8).
Differential analysis of the Elk-1 ChIP-seq data revealed many sites where Elk-1 binding differed significantly between the R6/1 vs. wild-type striata at 8 wk of age: 1,261 genes showed significantly higher and 193 genes showed lower Elk-1 binding in the R6/1 striatum compared to wild-type littermates (P < 1e-5). Genes with increased binding in R6/1 were enriched for the G protein-coupled receptor signaling pathway, signal transduction, cell differentiation, and regulation of localization, cellular calcium ion homeostasis GO terms, while genes with reduced binding in the R6/1 striatum were not significantly enriched for any particular categories (Fig. 3A  and Dataset S9). Importantly, of 687 differentially expressed genes in our 8-wk-old R6/1 RNAseq dataset, 101 were significantly differentially bound by Elk-1 (hypergeometric test P value for the overlap is P < 0.
02) (Dataset S10). Some of these genes were Drd2, Clspn, Adora2a, Mapk4, and Rasgrp1. Fig. 3B  shows genome browser views of example genes for increased and reduced Elk-1 binding around promoters of genes in R6/1, Drd2 and Clspn, respectively. As expected, the Elk-1 motif was top among the enriched motifs within the Elk-1-bound sites (Dataset S11). However, when we focused specifically on regions that changed in binding, we were able to identify additional motifs that may provide insights into combinatorial regulation. Sites with increased Elk-1 binding in R6/1 were enriched for a number of motifs, including the Pax transcription factor family (P = 2. 8e-07). On the other hand, reduced binding in R6/1 was associated with a distinct set of motifs, including the Egr transcription factor family DNA binding motif (P = 1.
4e-11) (Dataset S12). We next analyzed the localization of the Elk-1-bound sites with respect to TSSs. Notably, 45% of the Elk-1-bound sites in wild-type mice striatum were promoter regions; however, a majority of the differential Elk-1-bound sites between the R6/1 and wild-types were in distal sites (65% of all differential binding) (SI Appendix, Fig. S3C ). Elk-1 binding was present both at the promoter and distal enhancer sites around c-Fos and Egr-1 genes (Fig. 3C  and SI Appendix, Fig. S3D ) and, as illustrated in Fig. 3C , Elk-1 peaks fell precisely within the so-called histone valleys of H3K27acetylation regions around the c-Fos gene. In line with this observation, genome-wide analysis of H3K27acetylation read distribution around all Elk-1 binding events revealed a precise valley shape with Elk-1 binding in its center (Fig.
Further analysis of the datasets, without imposing cutoff criteria on the data, revealed a much more extensive impact of Elk-1 AAV treatment on expression of the dysregulated genes in HD. Of the 387 down-regulated genes in the control AAV-injected R6/1 striatum, expression of 88% were enhanced by Elk-1 AAV treatment of R6/1s, and among these were key genes, such as Drd1a, Drd2, Ppp1r1b, and Egr1, whose expression showed a shift toward wild-type levels (Fig. 5A  and Dataset S13). Similarly, expression of 78% of the genes up-regulated in the control AAV-injected R6/1 striatum were reduced by the Elk-1 AAV treatment. The effect of Elk-1 on the up-regulated genes in R6/1 is exemplified by Oxt, Agt, and Hap1 genes, which have been previously implicated in HD pathophysiology (40-42) (Fig. 5B  and Dataset S13).
5  A and B visualize a large effect of Elk-1 AAV treatment to counter transcriptional dysregulation induced by mutant Huntingtin expression in the striatum of R6/1 mice. Next, we explored which pathways were affected by Elk-1 overexpression. Using single-sample gene set enrichment analysis (ssGSEA)  (43, 44)  and gene sets from the Molecular Signatures Database (MSigDB)  (45, 46) , we analyzed all measured genes ranked by their fold-changes in expression in control AAV-treated R6/1 and Elk-1 AAV-treated R6/1 striatal transcriptomes compared to wild-types. This analysis associated a large number of gene sets with genes with altered expression in R6/1 striatum compared to wild-type mice within the control AAV-treated group (FDR < 0. 005) (Fig. 5C  and Dataset S14). Fig. 5C  illustrates a selection from the most enriched gene sets in control AAV-treated R6/1 mice and their enrichments in Elk-1 AAV-treated R6/1s.
Given that transcriptional dysregulation is an early and central pathogenic mechanism in HD, therapies that promote Elk-1 expression and its transcriptional activity may alleviate aspects of HD progression. Transcriptional dysregulation is a central mechanism in the cascade of pathogenic events triggered by mutant Huntingtin  (3, 10, 11). Here, focusing on prodromal disease stage, we found that transcription of hundreds of key neuronal genes was altered in HD mice striatum already before the onset of overt disease symptoms. To our knowledge, this study presents the earliest transcriptional profiling data reported so far in any HD mouse model (4-wk-old R6/1). Comparison of the mice differential expression datasets with a previous HD patient postmortem caudate microarray data (up to Vonsattel grade 2) (5) showed a large overlap of dysregulated genes, suggesting that HD mice faithfully recapitulate key elements of transcriptional dysfunction in human HD and that a significant portion of the early transcriptional changes persists throughout the disease progression.
Notably, our transcriptional dataset from 8-wk-old R6/1 mice was dominated by down-regulation of genes (90% of all differentially expressed genes) and these were enriched for GO terms typical for neuronal functions, indicating that disruption of neuronal geneexpression programs predominates the early transcriptional changes in HD pathogenesis. Supporting this, our histone H3K27acetylation ChIP-seq data showed a distinctly broad chromatin pattern, which is present both in wild-type and HD mice, surrounding the promoters of neuronal genes that are down-regulated in R6/1 striatum. This is a chromatin pattern we previously described in R6/2 mouse brain, as well as in HD patient induced pluripotent stem cell-derived medium spiny neurons  (11, 47). Broad chromatin patterns at regulatory regions and superenhancers control the expression of genes that are important for maintenance of tissue identities, and therefore are strongly expressed in their respective tissue types  (48) , such as the expression of neuron-specific genes in brain.
It is therefore conceivable that perturbations of these chromatin patterns may lead to loss of control of tissue-specific gene expression and the consequent loss of tissue identity may be associated to aberrant expression of developmental genes that are normally not expressed in differentiated cell types. In line with this, our present and previous RNA-seq datasets showed aberrant expression of genes belonging to various developmental programs in HD mice brains. Our current and previous epigenetic findings, revealing a distinct chromatin pattern around the promoters of neuronal genes that are down-regulated in the HD brain, points to a neuron-specific regulatory machinery that is selectively perturbed by mutant Huntingtin expression in neurons and that this machinery is not present or important in nonneuronal cell types.
This is an exciting finding for progressing the understanding of HD pathogenesis in that it uncovers a possible key mechanism underlying the enhanced vulnerability of neurons (i. e. , regulation of neuron-specific gene-expression programs) to mutant Huntingtin toxicity. These data also highlight the role of transcriptional dysregulation as a central disease mechanism in leading to neuronal dysfunction and demise in HD. Moreover, our current histone acetylation data show that expression of genes that display other chromatin patterns, which are not related to neuronal functions, are significantly less affected in the R6/1 striatum, confirming again the selectivity of mutant Huntingtin toxicity to expression of neuronal genes in HD. DNA sequence analysis for known transcription factor DNAbinding motifs revealed strong enrichments for REST, CREB, NEUROD1, and Elk-1 transcription factors in connection with lower H3K27acetylation both in the R6/1 and CHL2 ChIP-seq datasets.
Materials and Methods RNA-Seq. RNA-seq was performed following the Illumina mRNA Sequencing Sample Preparation Guide (Ilumina, Cat # RS-930-1001) and according to our previously published protocol  (11). Details of the experimental procedures and data analyses are provided in SI Appendix, Materials and Methods. ChIP-Seq. Brain tissues were cross-linked with 1% (vol/vol) formaldehyde for 10 min, and the cross-linking was quenched by 0. 125 M glycine. The crosslinked tissue was then homogenized, rinsed with PBS, pelleted, and frozen in liquid nitrogen. ChIP-seq assays were performed as previously described  (11, 60). Details of the ChIP-seq experiments and their computational analyses are provided in SI Appendix, Materials and Methods. Generation of AAV. Mouse Elk-1 cDNA along with mCherry cDNA linked to an internal ribosome entry site fragment were cloned into a recombinant AAV2/1 AAV expression vector containing a CMV promoter (provided by the University of Iowa Vector Core, Iowa City).
ACKNOWLEDGMENTS. We acknowledge generation of AAVs by the  University of Iowa  Vector Core; and thank the  Massachusetts Institute of Technology (MIT) BioMicro Center  and the  Scientific Genomics Platforms at Max-Delbrück-Center for Molecular Medicine Berlin  and at  Berlin Institute of Health  for sequencing of the RNA-seq and  ChIP-Seq  libraries. This work was supported by  German Research Foundation (Deutsche Forschungsgemeinschaft )  Exc 257/2   NeuroCure Cluster of Excellence  (F. Y. ); the  Hereditary Disease Foundation  (F. Y. );  National Institute of Health  Grant  R01 NS089076  (to E. F. and D. E. H. ); and sequencing support from the  National Institutes of Health  ( P30-ES002109 ) through the  MIT BioMicro Center.
Background. Morbidity, severity, and mortality associated with annual influenza epidemics are of public health concern. We analyzed surveillance data on hospitalized laboratory-confirmed influenza cases admitted to intensive care units to identify common determinants for fatal outcome and inform and target public health prevention strategies, including risk communication. Methods. We performed a descriptive analysis and used Poisson regression models with robust variance to estimate the association of age, sex, virus (sub)type, and underlying medical condition with fatal outcome using European Union data from 2009 to 2017. Results. Of 13 368 cases included in the basic dataset, 2806 (21%) were fatal. Age ≥40 years and infection with influenza A virus were associated with fatal outcome. Of 5886 cases with known underlying medical conditions and virus A subtype included in a more detailed analysis, 1349 (23%) were fatal.
Data Source During each influenza surveillance season, ECDC collects weekly case-based data on hospitalized laboratory-confirmed influenza cases admitted to ICU from a number of European Union (EU)/European Economic Area (EEA) Member States  [22, 23]. The data for the seasons 2009-2010 to 2016-2017 (weeks  were retrieved from the European Surveillance System (TESSy) database. A description of the surveillance systems in the countries reporting data is available at FluNewsEurope webpage  [24].
Data Set Reported information on laboratory-confirmed cases in ICUs included the following: influenza virus type; subtype (A(H1N1) pdm09, A(H3N2)) and lineage (B/Victoria, B/Yamagata); age (year); sex; duration of hospitalization (time between admission to hospital and either discharge or death); complications (acute respiratory distress syndrome [ARDS], bronchitis, encephalitis, myocarditis, pneumonia, sepsis, other); vaccination status (not vaccinated, pandemic, seasonal, or both vaccines); date of vaccination; respiratory support (not required, ventilation or oxygen support); and outcome (deceased or alive). Due to limited data reported on B-lineage, specific analysis in relation to B lineages was not feasible. The following underlying conditions were reported: asthma, cancer, chronic heart, kidney, liver or lung disease, diabetes, human immunodeficiency virus (HIV)/ other immune deficiency, neurocognitive and neuromuscular disorders, pregnancy, obesity, and morbid obesity.
Data Analysis A basic dataset was compiled to analyze the relationship between age, sex, virus type, and fatal outcome. Inclusion criteria were as follows: laboratory-confirmed influenza cases admitted to ICU, influenza virus type A or B confirmation, known age, sex, and outcome (Basic dataset) (Figure  1 ). Underlying medical conditions and A virus subtypes were only available for a subset of cases within the basic dataset but were considered important factors for analysis. Therefore, we created a subset of the basic dataset that included cases with known influenza A virus subtype (or B type) and underlying condition(s) (Specific dataset) (Figure  1 ). Additional variables analyzed independently were duration of hospitalization, complications, vaccination status, and respiratory support. Because these additional variables were only incompletely reported, they were not included in any multivariable analysis because they would have substantially reduced the number of eligible cases.
Crude and adjusted risk ratios (incidence rate ratio [IRR]) and 95% confidence intervals (CIs) were determined. The reporting country was included in the final model to adjust for country effects. A second model was developed based on the subset of the basic dataset that included cases with known underlying conditions and influenza A virus subtype (A(H3N2) or A(H1N1)pdm09) or B type. The significance level was set at 0. 05. Stata 14 (StataCorp) was used for the statistical analysis.