dataesr/scientific-paragraphs-categorization huggingface dataset:
Genome annotation and comparison The genome's assembly was performed with a pipeline that enabled us to create an assembly with different software (Velvet  [22] , Spades  [23]  and Soap Denovo  [24] ) on trimmed (MiSeq and Trimmomatic softwares)  [25]  or untrimmed data (only MiSeq software). For each of the six assemblies performed, GapCloser  [24]  was used to reduce gaps. Then contamination with Phage Phix was identified (BLASTn against Phage Phix174 DNA sequence) and eliminated. Finally, scaffolds of size <800 bp were removed, and scaffolds with a depth value of <25% of the mean depth were removed (identified as possible contaminants). The best assembly was selected by using different criteria (number of scaffolds, N50, number of N). For the studied strain, Spades gave the best assembly, with a depth coverage of 99×.
Open reading frames (ORFs) were predicted using Prodigal  [26]  with default parameters, but the predicted ORFs were excluded if they were spanning a sequencing gap region (contained N). The predicted bacterial protein sequences were searched against the Clusters of Orthologous Groups (COGs) database using BLASTP (E value 1e-03, coverage 0. 7 and identity percentage 30%). If no hit was found, sequences were searched against the NR database using BLASTP with a E value of 1e-03, coverage 0. 7 and identity percentage 30%. If the sequence length was smaller than 80 aa, we used an E value of 1e-05. The tRNAScanSE tool  [27]  was used to find transfer RNA genes, whereas ribosomal RNAs were found using RNAmmer  [28]. Lipoprotein signal peptides and the number of transmembrane helices were predicted using Phobius  [29].
ORFans were identified if the BLASTP performed did not give positive results (E value was lower than 1e-03 for ORFs with sequence size >80 aa; if alignment lengths were <80 aa, we used an E value of 1e-05). Such parameter thresholds have been used in previous work to define ORFans. The annotation process was performed in DAGOBAH  [30] , which includes Figenix  [31]  libraries that provided pipeline analysis. Artemis was used for data management and DNAPlotter  [32]  for visualization of genomic features. The Mauve alignment tool (version 2. 3. 1) was used for multiple genomic sequence alignment  [33]. To estimate the mean level of nucleotide sequence similarity at the genome level, we used MAGI homemade software to calculate the average genomic identity of orthologous gene sequences (AGIOS) among compared genomes.
Briefly, this software is combined with the Proteinortho software  [34]  for detecting orthologous proteins in pairwise genomic comparisons; it then retrieves the corresponding genes and determines the mean percentage of nucleotide sequence identity among orthologous ORFs using the Needleman-Wunsch global alignment algorithm. Genomes from the genus Bacillus and closely related genera were used for the calculation of AGIOS values. The genomic similarity was evaluated among studied species close to the isolate by digital DNA-DNA hybridization (http://ggdc. dsmz. de/distcalc2. php).
Results and discussion Strain identification and phylogenetic analyses Strain ES3 T was first isolated in May 2014 (Table  1 ) after 30 days of preincubation in aerobic culture on our homemade culture medium at 37°C. No significant MALDI-TOF MS score was obtained for strain ES3 T against the Bruker and URMITE databases, suggesting that our isolate was not a member of a known species  [9]. An almost complete 16S rRNA gene sequence of strain ES3 T (accession no. LN827530) comprising 1505 nt was analysed. Comparative 16S rRNA gene sequences analyses showed that strain ES3 T is phylogenetically affiliated with the Bacillus genus (Fig. 1 ). The phylogenetic distinctiveness (16S rRNA gene sequence similarity of <97%) confirms that strain ES3 T represents a distinct species from the recognized species belonging to Bacillus genus  [35].
The type strain was sensitive to imipenem, doxycycline, rifampicin, vancomycin, amoxicillin, ceftriaxone, gentamicin (500 μg), trimethoprim/sulfamethoxazole, erythromycin, ciprofloxacin, nitrofurantoin, ampicillin, penicillin and gentamicin (15 μg) but resistant to metronidazole (500 μg). The major fatty acids found for this strain were branched: 12-methyl-tetradecanoic acid (60%), 14-methyl-hexadecanoic acid (17%) and 13-methyl-tetradecanoic acid (10%). The most abundant fatty acids were saturated ones (99%). The G+C content of the genome was 39. 19%. The 16S rRNA gene sequence and whole-genome shotgun sequence of B. salis strain ES3 T were deposited in GenBank under accession numbers LN827530 and FNMN00000000, respectively. The type strain of Bacillus salis is strain ES3 T (= CSUR P1478 = DSM 100598) and was isolated from salt.
04 Amino acid transport and metabolism F 208 2. 56 Nucleotide transport and metabolism H 318 3. 92 Coenzyme transport and metabolism I 333 4. 10 Lipid transport and metabolism P 323 3. 98 Inorganic ion transport and metabolism Q 176 2. 17 Secondary metabolites biosynthesis, transport and catabolism R 560 6. 90 General function prediction only S 403 4. 96 Function unknown - 2832 34. 92 Not in COGs COGs, Clusters of Orthologous Groups database.
Disentangling the effects of ENSO and QBO on this anomalous trace gas variability and identifying the dominant driver of recent lower stratospheric water vapor changes during 2015-2016 is a challenging task. A detailed explanation of the reasons for this lower stratospheric water vapor variability in 2015-2016 is still lacking. Here, we quantify the impact of the interaction between the most recent El Niño event and the QBO disruption on lower stratospheric ozone and water vapor from spaceborne measurements during the 2015-2016 period. We describe the satellite observational data record and multiple regressions in Sect. 3. Section 4 describes the anomalous stratospheric circulation in boreal winter of 2015-2016 and Sect. 5 shows evidence for the impact of the El Niño event and QBO disruption on stratospheric ozone and water vapor.
In order to determine the optimal values of τ 1 (φ, z), τ 2 (φ, z) and τ 3 (φ, z), the residual is first minimized at fixed lag and then selected from a range of possible lags. This is done in sequence for QBO, ENSO and AOD. Here we neglect solar forcing, because our data set covers only one solar period. Uncertainty estimates for the statistical fits are calculated using a Student's t test technique  (Zwiers and von Storch, 1995; Bence, 1995; von Storch and Zwiers, 1999). 4 Anomalous stratospheric circulation in the 2015-2016 boreal winter Almost simultaneously with the exceptionally strong El Niño peaking in boreal winter of 2015-2016  (Huang et al. , 2016) , the fairly regular QBO cycle was disrupted by an unexpected shift from westerly (positive QBOi) to easterly (negative QBOi) winds.
Acknowledgements. We particularly thank the  NASA Jet Propulsion Laboratory  and the  European Centre for Medium-Range Weather Forecasts  for providing the Aura Microwave Limb Sounder product (https://mls. jpl. nasa. gov/,last access: 4 September 2018) and the  ERA-Interim reanalysis data. Work at the  Jet Propulsion Laboratory, California Institute of Technology , was done under contract with the  National Aeronautics and Space Administration. This work was funded by the  Helmholtz Association  under grant number  VH-NG-1128  ( Helmholtz-Hochschul-Nachwuchsforschergruppe ). The authors thank the organizing committee of SPARC training school on stratosphere-troposphere interactions during which this work was initiated. We sincerely thank  Chen Schwartz  at the  Hebrew University of Jerusalem, Israel , and  Abebe Kebede  of  Bahir Dar University, Ethiopia , for helpful discussions.
Data availability. The Aura Microwave Limb Sounder product (http://disc. sci. gsfc. nasa. gov/Aura/data-holdings/MLS/index. shtml, last access: 4 September 2018, Livesey et al. , 2017; Santee  et al. , 2017)  and ERA-Interim reanalysis data (https://www. ecmwf. int/en/forecasts/datasets/reanalysis-datasets/era-interim, last access: 4 September 2018,  Dee et al. , 2011)  are available. The CLaMS H 2 O data set can be requested from the corresponding author Mohamadou Diallo (m. diallo@fz-juelich. de).
Liver Transcriptome -Microarray Hybridizations and Image Analysis Transcriptomic analysis was performed in liver using a custom-designed 4 × 44 k Atlantic salmon oligo microarray (Agilent Technologies, Wokingham, United Kingdom; ArrayExpress accession no. A-MEXP-2065). The salmon microarray and laboratory procedures utilized in this study have been widely used and validated in many previous studies  (Morais et al. , 2012; Tacchi et al. , 2012; Bicskei et al. , 2014; Martinez-Rubio et al. , 2014; Betancor et al. , 2015a,b). Replicate RNA samples were amplified using TargetAmp TM 1-Round Aminoallyl-aRNA Amplification Kit, (Epicentre Technologies Corporation, Madison, Wisconsin, United States) following recommended procedures. Aminoallyl-amplified RNA (aRNA) samples were labeled with Cy3 dye (GE HealthCare Life Sciences, Buckinghamshire, United Kingdom) while a pool of all aRNA samples was labeled with Cy5 dye (GE HealthCare Life Sciences) and was used as a common reference in a dual-label common reference design and finally hybridized.
Scanning was performed using a GenePix 4200 AL Scanner (Molecular Devices (United Kingdom) Ltd. , Wokingham, United Kingdom), and the resulting images analyzed with Agilent Feature Extraction Software v. 9. 5 (Agilent Technologies) to extract the intensity values and identify the features. Features considered outliers (i. e. , defined as those probes whose background intensity was between the 0. 05 and 99. 95th percentile of the distribution) in two or more replicates within at least one treatment were excluded from further analyses. Additionally, features consistently expressed just above background noise (defined as those features whose intensity was lower than 5th percentile of the distribution in 75% or more of the analyzed samples) were also removed. The full protocol for microarray laboratory and data analysis has been reported previously  (Betancor et al.
Gene Ontology Analysis Gene ontology (GO) analysis was performed using the functional annotation cluster from the DAVID (Database for Annotation, Visualization and Integrated Discovery) bioinformatics resource  (da Huang et al. , 2009a,b). The IDs of genes exclusively affected by population were used as input and processed with the functional annotation cluster from DAVID. The resulting data were used as input in the Enrichment Map App from the Bader Lab  (Merico et al. , 2010 (Merico et al. , , 2011) )  in the Cytoscape network visualization tool (version 3. 5. 1) (Cline et al. , 2007). Selected mRNA probes differentially expressed by population and assigned to be part of significantly affected GO process were used as an input in ClueGo  (Bindea et al. , 2009 (Bindea et al. , , 2013) )  which visualizes the selected terms in a functionally grouped annotation network that reflects the relationships between the terms based on the similarity of their associated genes.
Statistical Analysis Microarray hybridization data were analyzed in GeneSpring GX version 12. 6. 1 (Agilent Technologies, Wokingham, Berkshire, United Kingdom) by two-way analysis of variance (ANOVA), which examined the explanatory power of the variables, diet and population, as well as "diet x population" interaction. No multiple test correction was employed as previous analyses indicated that they were over-conservative for these nutritional data  (Morais et al. , 2011). Data were submitted to the Kyoto Encyclopedia of Genes and Genomes (KEGG)  (Kanehisa and Goto, 2000)  for biological function analysis. The results of plasma metabolites and gene expression are presented as means ± SD The effects of diets, populations and the diet population interaction on the different parameters were tested using R software (v3.
Introduction Despite the demonstrated feasibility and policies to enable more to receive chemotherapy at home, in a few countries, parenteral chemotherapy administration at home remains currently marginal. Of note, findings of different studies on health outcomes and resources utilisation vary, leading to conflicting results. This protocol outlines a systematic review that seeks to synthesise and critically appraise the current state of evidence on the comparison between home setting and hospital setting for parenteral chemotherapy administration within the same high standards of clinical care. Methods and analysis This protocol has been prepared following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols approach. Electronic searches will be conducted on bibliographic databases selected from the earliest available data through 15 November 2017 published in French and English languages.
Additional potential papers in the selected studies and grey literature will be also included in the review. The review will include all types of studies exploring patients receiving anticancer drugs for injection at home compared with patients receiving the drugs in a hospital setting, and will assess at least one of the following criteria: patients' health outcomes, patients' or caregivers' satisfaction, resource utilisation with cost savings, and incentives and/or barriers of each admission setting according to patients' and relatives' points of view. Two reviewers will independently screen studies and extract relevant data from the included studies. Methodological quality of studies will be assessed using the 'Quality Assessment Tool for Quantitative Studies' developed by the Effective Public Health Practice Project tool, in addition to the Consolidated Health Economic Evaluation Reporting Standards statement for economic studies.
Eligibility criteria All studies exploring parenteral anticancer drug administration at home setting, mainly intravenous and subcutaneous administrations, will be selected from the earliest available data through 15 November 2017, published in French and English languages, regardless of country. The inclusion criterion defining the scope of publications included in the review will be the comparison of parenteral chemotherapy administration at home with administration in inpatients and/or outpatients wards. As our goal is to study the home-based setting as an alternative context for providing the highest standards of clinical care concerning parenteral drug delivery, we will exclude all community-based services with no anticancer drug administration at home, and studies targeting only postadministration chemotherapy monitoring, disconnection of portable diffuser, management of central venous catheter and supportive care therapy.
databases and search strategy A detailed literature search will be conducted to identify all articles studying chemotherapy administration in a home setting for adults and paediatric patients. Published studies will be identified through searches of the Medline, Cochrane, Web of Science, Embase and Cumulative Index to Nursing and Allied Health from the earliest available date through 15 November 2017. HAH is defined as the delivery of hospital ward-level care and replaces the hospital by ensuring the continuity of care for the patient it takes care of. 6] [17]  According to Medical Subject Headings (MeSH) definition, 'Home Care Services' is a community health and nursing service providing coordinated multiple services to patients at their homes. These home care services are provided by a visiting nurse, home health agencies, hospitals or organised community groups using professional staff for care delivery.
They differ from home nursing, which is provided by non-professionals, and from 'Home Care Agencies', public or private organisations, which provide home health services in patients' home either directly or through arrangements with other organisations. Therefore, we have developed a strategy in Medline to retrieve relevant literature on the topic. The Medline Open Access search strategy will be ("Neoplasms"[Mesh] AND ("Antineoplastic Combined Chemotherapy Protocols"[Mesh] OR "Antineoplastic Agents"[Mesh])) AND ("Home Care Services"[Mesh] OR "Home Care Agencies" [Mesh]). This search strategy will be adapted in searching other databases (see search strategy in online supplementary file). The references from potentially relevant papers were manually searched for additional studies. A further research will be performed in OpenGrey, in Research Papers in Economics and in Google Scholar databases to find relevant unpublished studies in grey literature.
study selection We will use a two-stage process to identify papers that met our inclusion criteria. The first stage accumulated all papers from two types of searches using the already mentioned databases. The first type of search will use combinations of keywords to retrieve titles of potentially relevant studies. The search output will be screened independently by two review authors (MDS, BM-M) to identify studies that potentially meet the inclusion criteria outlined above. In case of discrepancy, the abstract of the concerned study will be retrieved. If disagreements remained, a third author (EB) will arbitrate. In the second type of search, all papers citing or cited by articles that had already met our inclusion criteria will be identified, then screened as the first ones. In the second stage, the full text of these selected studies will be retrieved and independently assessed for eligibility by the same two review members.
Data will be extracted independently by two review members; discrepancies will be identified and resolved through a discussion with a third reviewer (PA). data assessment and synthesis Quality assessment Two reviewers (MDS and BM-M) will independently assess the quality of included studies and the potential risk of bias. We will use the 'Quality Assessment Tool for Quantitative Studies' developed by the Effective Public Health Practice Project tool,  18  as it can be applied to articles of any public health topic area, assessing the components of studies (design, methods, bias). Likewise, we will use the Consolidated Health Economic Evaluation Reporting Standards statement,  19  focusing on the design quality of the cost studies. It leads to an overall methodological rating of strong, moderate or weak.
Background: Territorial differences in the access to innovative anticancer drugs have been reported from many countries. The objectives of this study were to evaluate access to innovative treatments for metastatic lung cancer in France, and to assess whether socioeconomic indicators were predictors of access at the level of the municipality of residence. Methods: All incident cases of metastatic lung cancer hospitalised for a chemotherapy in public hospitals in 2011 were identified from the French National Hospital discharge database. Information on prescription of innovative drugs from an associated database (FICHCOMP) was crossed with the population density of the municipality and a social deprivation index based on national census data. Results: Overall, 21,974 incident cases of metastatic lung cancer were identified, all of whom were followed for 2 years.
Therapies included in this list are fully reimbursed up to reimbursement tariffs. Payment comes out of a specific national budget that protects hospitals from the costs of expensive new drugs. The goal is to ensure rapid diffusion of innovative therapies and to minimise the risk of 'postcode prescribing'. The list of eligible treatments is reviewed annually and all drug use funded through this mechanism is documented in a specific database (FICHCOMP). At the time of the analysis, access to the FICHCOMP database was only available for public hospitals. Since the introduction of the extra-DRG funding of innovative and expensive drugs, limited data is available regarding the performance of this system in minimising inequalities in access to anticancer drugs in the public domain. The objectives of the present study were to assess access to these treatments by patients with metastatic lung cancer using the French hospital discharge database and to assess whether socioeconomic indicators were predictors of access at the level of the municipality of residence.
Study design The TERRITOIRE study was a historical cohort analysis of a medico-administrative database. Data was extracted from the French National Hospital discharge database (PMSI; Programme de Médicalisation des Systèmes d'Information) relating to all patients hospitalised in the public sector, crossed with geographically aggregated socioeconomic variables at the lowest local authority level, documented in the databases of the national census of the French national statistics office (INSEE) through individual patient postcodes.
Hospital discharge database The PMSI hospital discharge database covers all hospitalisations in the public and private sectors involving short-term stays in medical, surgical or obstetric facilities, representing more than 95% of all hospitalisations in France  [11]. The reasons for hospitalisation are coded by International Classification of Diseases, 10th revision (ICD-10) codes  [12] , either as principal diagnoses (PD; the condition for which the patient was hospitalised), related diagnoses (RD; any underlying condition which may have been related to the PD) or as significantly-associated diagnoses (SAD; comorbidities which may affect the course or cost of hospitalisation). Sociodemographic data is limited to age at inclusion, gender and home address postcode. Patients can be tracked across multiple hospitalisations through a unique anonymous patient identifier, which is retained until the patient dies.
Data collection At the first documented hospitalisation for metastatic lung cancer (index visit), the gender and age of each patient was documented, as well as the presence of significant chronic comorbidities (hypertension, diabetes mellitus, renal insufficiency and other chronic lung diseases). The choice of these comorbidities was justified by the fact that these are systematically taken into account during the MCT meeting at which the decision to use a FICHCOMP drug is made. The type of hospital at which the patient was diagnosed was identified. Data was collected for the two-year period following the index hospitalisation.
Sociodemographic variables The municipality of residence (commune) for each patient at the time of the initial hospitalisation was determined from their postcode. Patients whose postcode was not documented in the PMSI database were excluded from the analysis. The commune is the lowest tier of local authority in France and generally consists of a single population centre together with any surrounding hamlets or countryside, with a typical area of 10-50 km 2. There are around 36,000 such municipalities in France, and these are grouped into 6000 geographical units which are coded in the PMSI database. Data were retrieved from the French national statistics office (INSEE) on the sociodemographic make-up of each municipality and used to classify them in terms of population density and social deprivation.
Study population A total of 41,715 incident cases of lung cancer (all forms and all stages) were identified in the hospital discharge database in 2011, all of whom were followed for 2 years. Of these, 21,974 fulfilled the criteria for metastatic disease. These patients made 298,652 hospital visits, including both overnight stays and day hospitalisations for chemotherapy sessions, corresponding to an average of 13. 6 visits per patient over the course of the follow-up period. Out of all incident patients, 64. 0% received chemotherapy over the observation period, the majority in the public sector (82. 4%). Of the 11,486 analysable patients receiving chemotherapy in the public sector, 6959 (60. 6%) were treated at least once with a specific lung cancer drug (FICHCOMP). The flow chart for the selection of patients is presented in Fig.