dataesr/scientific-paragraphs-categorization huggingface dataset:
ACKNOWLEDGMENTS The authors thank the staff of the  Station d'expérimentation appliquée et de démonstration sur l'oie et le canard (Dordogne, France)  for their excellent supervision of this study, especially  C. Mondoux  and the staff of the  UMR1388 Génétique Physiologie et Systèmes d'Elevage , and  E. Cobo  in particular for blood sampling. The authors also acknowledge the  Interprofession Foie Gras (CIFOG) , the  Aquitaine Regional Council  and the  Dordogne Departemental Council  for funding the project.
Methods: In this systematic review and network meta-analysis, we plan to search electronic databases (Cochrane Central Register of Controlled Trials [CENTRAL], MEDLINE, EMBASE, Science Citation Index Expanded on Web of Science and relevant trial registries) for relevant randomised and non-randomised trials. Citations will be reviewed by title, abstract and full text by two independent reviewers and disagreement resolved by discussion and a third independent reviewer, if necessary. The Cochrane Risk of Bias tool will be used to assess risk of bias in randomised trials and the Risk of Bias in Nonrandomised Studies of Interventions (ROBINS-I) tool will be used for nonrandomised studies. Statistical analysis will be carried out using R package meta and netmeta. We will first conduct a pairwise meta-analysis.
Criteria for including studies in this review This systematic review and network meta-analysis will be conducted in accordance with The Cochrane Collaboration principles of Systematic Reviews and reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and the PRISMA Network Meta-Analysis Extension statement  [21, 22]. The protocol for this study will be registered with the International Prospective Register of Systematic Reviews (PROSPERO) database (registration number: CRD42019121739).
Type of participants Papers that include adults admitted to a critical care setting (ICU, HDU, Emergency Department, Acute medical unit) who have developed or develop NOAF, including paroxysmal AF (rhythm classification by continuous electrocardiograph (ECG) monitoring or 12 lead ECG) will be included. Papers that include the following and which cannot be disaggregated from the data of interest will be excluded: Patients younger than 18 years Pregnant women Any patient with known AF or a history of previous episodes of AF All patients who have undergone or planning to undergo cardiac surgery, permanent pacemaker insertion or surgical ablation Patients post cardiac/thoracic surgery.
Search methods of identification of studies Search strategy We will identify all relevant studies regardless of publication status (published, unpublished, in press and ongoing). Where possible, individual patient data will be sourced via communication with trialists. We will focus our search strategy on the population (acutely unwell/critically unwell) and the interventions (anti-arrhythmic/rate control medication or cardioversion) components of our review question. It will not be limited by outcome studied in order to broaden the scope of eligible studies. A comprehensive search strategy will be constructed and implemented with the help of a health information specialist with experience in developing searches for systematic reviews. Subject index terms (such as MeSH in MEDLINE) will be used to capture the principle elements of the systematic review question.
Database searches We will search the following databases using the search terms described in Additional file 1: Cochrane Central Register of Controlled Trials (CENTRAL); MEDLINE; Embase (OVID); the Science Citation Index Expanded, accessed via Web of Science. Identified studies published since 1990 will be included. We will also search the following ongoing trial registers to identify ongoing studies: the metaRegister of Controlled trials (www. controlled-trials. com); the US National Institutes of Health Register (www. clinicaltrials. gov); and the World Health Organisation (WHO) International Clinical Trials Registry platform (ICTRP) (www. who. int/trialsearch).
Searching other resources A review of the grey literature will be conducted using 'Google Scholar' and Web of Science databases. We will check relevant conference proceedings and include any potentially relevant studies. We will include guidelines and conference proceedings from the American Society of Chest Physicians, American Thoracic Society, Society of Critical Care, European Society of Intensive Care Medicine, Intensive Care Society and the European Society of Cardiology. We will also check the reference lists of all included trials for other potentially relevant studies, and review authors' personal collections. We will update our searches within 6 months of publication of the resulting review; we will check our citations in the protocol and update as necessary and cross check with our authors.
Data collection and analysis Citation management and screening Citations for all studies identified during the search strategy will be exported to EndNote. All citations will be imported into Covidence systematic review platform (Veritas Health Innovation, Melbourne, Australia). Duplicate citations will be removed using the automated features of EndNote and Covidence before screening. We will retrieve full text papers that are not excluded after title and abstract screening. Full text articles will be reviewed against inclusion and exclusion criteria by two independent reviewers. Study authors will be contacted in cases where further information is required to make a screening decision (where reports are unclear or conference abstracts from ongoing studies). Differences will be resolved through discussion, and a consensus decision reached.
Data extraction and management Data will be extracted from studies following full text screening. A custom data extraction form will be generated in Covidence. The data extraction form will be piloted on 10% of included studies. Data will be extracted by two independent reviewers. Consistency between reviewers will be assessed using the kappa statistic in Covidence. A kappa statistic of > 0. 6 (moderate agreement) will be required prior to full data extraction on all included studies. The data extraction form will be designed to capture information regarding: Study.
Network meta-analysis In addition to pairwise meta-analysis, we will assess if sufficient clinical and statistical data is retrieved to proceed to a network meta-analysis (NMA). It is likely that a number of relevant studies will be observational in nature. We will inspect studies carefully to assess for design limitations and follow a sequential approach, considering randomised trials first followed by non-randomised trials. We will assess the homogeneity of the evidence base and if it satisfies the assumption of transitivity, that is, that the distribution of the effect modifiers are comparable across treatments, in deciding whether to progress to a network meta-analysis  [28]. If network meta-analysis is conducted, we will use a frequentist approach and a random effects model for binomial and continuous outcomes assessing the effect estimate of each treatment for AF  [29].
Mean difference and OR ratios with 95% confidence and predictive intervals will be presented  [29]. We will estimate and explore any orderings of treatment hierarchy in key measures of effect and present treatment rankings with P-score using Netrank of the R package netmeta  [30]. Following unadjusted analysis, secondary analyses will be conducted to account for any imbalance in the distribution of effect modifiers and between study differences. Network meta-regression methods will be conducted to account for these differences  [25]. Data will be formatted in contrast-based rows as specified for data input with the R packages meta and netmeta  [30]. Inconsistency in the data will be assessed by fitting inconsistency model scatterplots and using Cochran's Q test. We will engage the services of a statistician with experience in systematic review, meta-analysis and network meta-analysis to advise on and assist with the statistical analysis.
Viruses modulate ecosystems by directly altering host metabolisms through auxiliary metabolic genes. However, viral genomes are not known to encode the core components of translation machinery, such as ribosomal proteins (RPs). Here, using reference genomes and global-scale viral metagenomic datasets, we identify 14 different RPs across viral genomes arising from cultivated viral isolates and metagenome-assembled viruses. Viruses tend to encode dynamic RPs, easily exchangeable between ribosomes, suggesting these proteins can replace cellular versions in host ribosomes. Functional assays confirm that the two most common virus-encoded RPs, bS21 and bL12, are incorporated into 70S ribosomes when expressed in Escherichia coli. Ecological distribution of virus-encoded RPs suggests some level of ecosystem adaptations as aquatic viruses and viruses of animal-associated bacteria are enriched for different subsets of RPs.
In fact, this feature-ribosome-encoding or not-has been proposed to signify a major divide between cellular life forms and viruses  26, 27. However, viral genome fragments assembled from environmental viral community sequence datasets (viral metagenomes), which vastly expand upon cultured sequence space, suggested that viruses might encode ribosomal proteins, specifically, bS1 and bS21. Though challenges insuring removal of contamination from cellular genomes and the lack of host context available warrants caution about such observations of "cellular features" in metagenome-only datasets  22, 28  , the findings are intriguing. Here we leverage the greater genomic context now available from large-scale metagenomes and genomes to revisit the question of whether viral genomes encode ribosomal proteins (RPs).
The last ribosomes-associated protein encoded in sequenced viral genomes was the ribosome hibernation promotion factor (HPF), or Ribosomal_S30AE (PF02482) domain-containing protein, which was encoded by 7 phages infecting Cronobacter and E. coli (six closely related phages with 92-97% average nucleotide identity) (Supplementary Fig. 6 ). HPF proteins are expressed during stasis and under unfavorable growth conditions; HPF binds ribosomes to stabilize 100S dimers that inhibit translation to enable cells to control translational activity without costly alteration of the ribosomal pool  37. Multiple sequence alignment shows high conservation of the viral and cellular HPF homologs (Supplementary Fig. 7 ), suggesting that the gene transfer has occurred in a relatively recent past. In the HPF phylogeny, homologs from E.
Ribosomal proteins detected in viral metagenomes. To place these findings of cultivated virus-encoded RPs into broader ecological context, we searched 424,225 viral contigs from two global metagenomic datasets  8, 38  for putative RPs using the same 106 sequence profiles (see Methods). Overall, 13 putative ribosomal protein genes were identified across 1403 contigs (Fig. 2 , Supplementary Table  2 , Supplementary Fig. 3 ). By matching CRISPR spacers, comparing k-mer nucleotide frequencies and performing BLASTn homology searches against reference cellular sequences, hosts could be predicted for 74 (5. 3%) of the uncultivated viruses encoding 7 different RPs (Supplementary Data 1). Despite this relatively low fraction of predicted hosts, RPencoding phages are already associated with 8 bacterial phyla (Proteobacteria, Firmicutes, Verrucomicrobia, Bacteroidetes, Deinococcus-Thermus, Thermotogae, Cyanobacteria, and Actinobacteria).
Methods Sequence analyses. All viral genomes were downloaded from viral RefSeq database (ftp://ftp. ncbi. nlm. nih. gov/refseq/release/viral/). A hidden Markov model (HMM) profile was downloaded from the PFAM database (http://pfam. xfam. org/) for each domain listed in Supplementary Table  1. In total, 106 sequence profiles corresponding to distinct ribosomal protein domains were used as seeds to search the proteomes of viruses infecting hosts from the three cellular domains, as well as proteins predicted on viral contigs from two previously published global metagenomic datasets, Global Ocean Virome 8 , and Earth's Virome  38  , which are available at https://img. jgi. doe. gov/cgi-bin/vr/main. cgi and http://datacommons. cyverse. org/ browse/iplant/home/shared/iVirus/GOV. Notably, domain S1, which is repeated 4 to 6 times in the ribosomal protein bS1, is not exclusive to RPs as it is common across diverse RNA-binding proteins and fused to non-ribosomal functional motifs (pfam id: PF00575.
The ribosomal structure was downloaded from PDB database and visualized using Chimera  68. Putative temperate phages were identified by searching for the following PFAM domains in ribosomal protein-encoding viral contigs: Mu-transpos_C, Phage_int_SAM_5, and Phage_integrase (hmmsearch, threshold of 30 on bit score). Host predictions for viral metagenomic contig were obtained from the original studies (i. e. , ref. 8  and  38  ) and, in the case of the Earth's virome  38  , complemented with a k-mer based prediction computed with WIsH 69 (p-value threshold of 0. 001). To further confirm the functionality of RPs encoded on uncultivated viral genomes, selective constraint on these AMGs was evaluated through pN/pS calculation, as in ref. 46. Briefly, synonymous and non-synonymous SNPs were observed in each ribosomal protein gene covered ≥10 × , and compared to expected ratio of synonymous and non-synonymous SNPs under a neutral evolution model if at least 1 SNP was identified.
Fluorescence intensity of translated GFP was determined using the FinLab software with following conditions: λ excitation 485 nm/slit 10/photomultiplicator 775/λ emission 510 nm. Negative staining. Following ribosome separation, we diluted samples 10 times in Buffer 2 and applied them to freshly glow-discharged 300-mesh collodion/carboncoated grids. After three washes in this buffer, grids were stained with 2% uranyl acetate for 30S. The grids were then observed with a Tecnai G2 Sphera transmission electron microscope operating at 200 kV. Images were recorded with a 4000 × 4000 Gatan Ultrascan 4000 CCD camera at a nominal magnification of ×50,000. Liquid digestion of ribosomal samples. 25 µg of ribosomes were digested according to the following protocol: first, 53. 5 µl of 50 mM ammonium bicarbonate buffer (pH 7,8) was added to the sample to 65 µL total volume.
Peaks selected for fragmentation were automatically put on a dynamic exclusion list for 30S with a mass tolerance of ± 10 ppm to avoid selecting the same ion for fragmentation more than once. The following parameters were used: the repeat count was set to 1, the exclusion list size limit was 500, singly charged precursors were rejected, and the maximum injection time was set at 500 and 300 ms for full MS and MS/MS scan events, respectively. For an optimal duty cycle, the fragment ion spectra were recorded in the LTQ mass spectrometer in parallel with the Orbitrap full scan detection. For Orbitrap measurements, an external calibration was used before each injection series ensuring an overall error mass accuracy below 5 ppm for the detected peptides. MS data were saved in RAW file format (Thermo Fisher Scientific) using XCalibur 2.
0. 7 with tune 2. 4. The data analysis was performed with Proline software 1. 4 supported by Mascot Distiller and Mascot server (v2. 5. 1; http://www. matrixscience. com) database search engine for peptide and protein identification using its automatic decoy database search to calculate a false discovery rate (FDR) of 1% at the peptide level. MS/MS spectra were compared to the Escherichia coli Reference proteome set database containing the phage ribosomal proteins (UniProt release 2017_01, 18 January 2017, 23022 sequences, 7070297 residues). Mass tolerance for MS and MS/MS was set at 10 ppm and 0. 5 Da, respectively. The enzyme selectivity was set to full trypsin with one miscleavage allowed for samples HPF and bL12 and the enzyme selectivity was set to full V8-DE with one miscleavage allowed for sample bS21.
Data availability The authors declare that the data supporting the findings of this study are available within the paper and its supplementary information files. Viral contigs analyzed in this study are from two previously published global metagenomic datasets (Global Ocean Virome and Earth's Virome) that are available at https://img. jgi. doe. gov/cgi-bin/vr/main. cgi and http://datacommons. cyverse. org/browse/iplant/home/shared/iVirus/GOV.
Introduction Chronic total occlusion (CTO) is present in about 16% to 30% of patients undergoing coronary angiography  [1] [2] [3]. Despite the increased experience due to the growth of the number of the performed procedures and the introduction of new techniques and equipment, CTO still remains one of the most demanding procedures in interventional cardiology. Using large registry databases, differences in outcomes and revascularization success in patients with CTO were published during the past years  [4] [5] [6] [7] [8] [9]. However, as determining age of the CTO may be very challenging, most of them did not include this factor in the analysis. There are several reports describing how and whether CTO duration may affect lesion and procedural characteristics  [10] [11] [12] [13] [14]. However, none of those studies focused on such a large cohort of patients treated in recent years, and therefore benefiting the most from the latest developments in the field of CTO.
Material and methods The European Registry of CTOs (ERCTO) is a prospective real-world monitored based registry involving over 100 centers across Europe including patients treated with CTO percutanous coronary intervention (PCI)  [6]. For the purpose of our study we included patients admitted to the hospitals between January 2015 and the end of April 2017. The treatment indication for CTO was symptomatic myocardial ischemia and/or evidence of reversible myocardial ischemia by perfusion imaging or stress testing. Registry data from both members and associates of the Euro CTO Club were included. Only patients with certain or likely CTO duration were included in the analysis. Out of 10699 patients in the database recruited during the selected period of time, 5933 patients were excluded due to undetermined age of the occlusion.
Out of the remaining 4766 patients we excluded 287 patients with an additional acute coronary syndrome and 435 patients with insufficient further data regarding the occlusion characteristics. In the end, a total of 4044 patients were included in the data analysis (Figure  1 ). Patients were divided into 3 groups according to age of the CTO: 1) 3-6 months; 2) 7-12 months; 3) over 12 months. Coronary CTO was defined as angiographic evidence of total occlusions with thrombolysis in myocardial infarction (TIMI) flow grade of 0 and estimated duration of at least 3 months. The length of coronary occlusions was estimated from angiographic projections. Degree of calcification was estimated visually on fluoroscopy. Moderate and severe calcifications were defined as calcium extending for less than half or equal/greater than half of the total CTO segment, respectively.
Results A total of 4044 of patients were included in the main analysis. Patients with the longest CTO duration as compared to patients with CTO duration 3-6 months were Figure  1. Flow chart. Out of 10699 patients in the database recruited during the selected period of time, 5933 patients were excluded due to undetermined age of the occlusion. Out of the remaining 4766 patients we excluded 287 patients with an additional acute coronary syndrome and 435 patients with insufficient further data regarding the occlusion characteristics. In the end a total of 4044 patients were included in the data analysis significantly older (63. 0 (56. 0-70. 0) vs. 66. 0 (59. 0-73. 0) years) and had higher prevalence of peripheral artery disease (8. 8% vs. 12. 4%) (Table  I ). The group with the longest CTO duration had higher incidence of myocardial infarction (MI) and prior coronary artery bypass grafting (CABG) as compared to other groups.
Limitations First, our study is limited by its observational design. Second, angiography-dependent and clinical outcomes were not independently adjudicated. Third, data regard-ing patients and lesion and procedural characteristics were missing in some cases. Moreover, only in half of the patients could CTO age be assessed. Out of 10 699 patients, 4044 (37. 8%) were included in the final analysis, which could have involved selection bias. Further, patients excluded from the study differed from those included in important lesion characteristics such as lesion location, number of previous attempts and severity of coronary artery disease. Lastly, the exact age of the CTO is often unclear. Hence, it is often very challenging to determine the exact age of the CTO.
Background: Cystic fibrosis (CF) is a life-shortening genetic condition that usually affects several organs and involves significant treatment burden. Adherence to medication is important for successful CF management. Objective: To describe medication adherence according to age, therapeutic class, and pharmaceutical form in adults and children followed in four regional CF centers in France. Methods: We conducted a cross-sectional study with non-transplanted patients followed in two adult and two pediatric centers during 2015 who were covered by the French National Health Insurance (NHI). Sociodemographic, clinical, hospitalization, and prescription data were collected from patient medical records. Medication dispensations were extracted from the regional French NHI database. Adherence was calculated over 12 months using continuous medication availability (CMA) accounting for dose adjustments and hospitalizations.
Drug-specific CMA was computed in R with the AdhereR package for each medication prescribed more than 3 months, which was averaged to obtain a composite CMA score (cCMA) for all treatments and per therapeutic class as well as pharmaceutical form for each patient. Results: A total of 228 patients were included. The number of chronic medications increased with age (r=0. 50, p<0. 001): a median of 7 medications per patient were prescribed. The mean±SD cCMA was significantly different between age groups (p=0. 0098): it was 0. 71 ±0. 20 for the 0-5 years age group, 0. 73±0. 16 for 6-11 years, 0. 64±0. 17 for 12-17 years, 0. 57 ±0. 23 for 18-25 years, and 0. 65±0. 20 for the over 25 years age group. cCMA varied significantly according to pharmaceutical forms: the mean±SD cCMA was 0. 70±0. 21 for oral medications and 0.
Demographic and clinical data We extracted the following demographic and clinical data from medical records: gender, age, age at CF diagnosis, context of diagnosis, cystic fibrosis transmembrane conductance regulator (CFTR) genotype, Pseudomonas aeruginosa colonization status, presence of CF-related diabetes, body mass index at the last visit to the CF center before 1 January 2015. The FEV 1 collected was the best value during 2014, and was expressed as percentage of the predicted value according to Knudson's reference. Occurrence and total duration of course of intravenous (IV) antibiotic courses, number of outpatient visits in CF centers, and occurrence and total duration of hospitalizations were collected for 2014. Prescription data for medications prescribed more than 3 months (name of drugs, pharmaceutical forms, dosage, and durations of prescription) were collected from the prescription made on the last visit prior to 1 January 2015 and throughout 2015.