dataesr/scientific-paragraphs-categorization huggingface dataset:
The Package1, developed by CNRS, is the IAGOS central system. It can last 6 months in operation before replacement and it includes the O 3 instrument, the carbon monoxide (CO) instrument, the data acquisition system and the interface that collects aircraft parameters such as position, speed and ambient meteorological data (see Table  1 ). Associated components to Package1 are the MOZAIC water vapour sensor from FZJ  (Helten et al. , 1998; Neis et al. , 2014)  and the University of Manchester Backscatter Cloud Particle probe (BCP;  Beswick et al. , 2014). After landing, all data are transmitted to the IAGOS receiver station (see Section 3. 5). More details on Package1 are provided in Section 3. The Package2 are optional instruments that can be installed in addition to Package1. The IAGOS project counts four different Package2 types so far.
At the date of March 2015, six Airbus A340 or A330 have been equipped with the IAGOS system (see Table  2 ). Aircraft are then operated by airlines similar to IAGOS non-equipped aircraft without any additional restrictions. Only superficial check-up are periodically requested for aircraft airworthiness such as inlet plate visual inspection or relay functional tests. Instrument replacements (Package1, pump box, H 2 O and BCP) are performed by airlines maintenance staff during scheduled layovers approximately every 6 months or before in case of functional failures detected after reception data analysis.
As one pump in normally sufficient for providing the requested flow in altitude (up to 12. 5 km), only one pump is used (alternate every day) to increase pump lifetimes. Data acquisition starts during take-off (ground speed !25 m s (1 ) and stops after landing (ground speed B25 m s (1 ). Using 'Landing gear up and locked' and 'Engine 2 oil pressure' analogue aircraft signals, the BCP is started about 1 min after take-off and stopped when landing gear is descended prior to landing. BCP data are recorded via a CPU serial port RS232 and are stored every 4 s. H 2 O sensor measurements (Rosemount RH and Air Temperature) are analogue voltages stored every 4 s.
An example is shown in Fig. 7. These quick-look pictures display the raw data (without any filters or corrections) to immediately identify any dysfunctioning that directly impact the O 3 and CO measurements. As a critical parameter, the internal pump flow (here in Volts) is shown in green for good functioning and in red if the flow is insufficient. Rosemount humidity (here also in Volts and it will calculated later by the FZJ) and temperature measurements are also checked along with the independent aircraft temperature sensor. On ascent pro-files, the flight data are shown along with the profiles of the previous flight if it landed maximum 8 h before. The latter gives an idea upon the measurements quality consistency. The quick-look is always sent to the PIs and co-PIs to continuously verify the good functioning of the measurements on a daily basis.
Data validation The data validation by the PI (Philippe Nedelec, CNRS Laboratoire d'Ae´rologie) represents the pass from the L0 raw data to the L1 validated final data (the data processing is fully described in a IAGOS overview paper,  Petzold et al. , 2015). At the beginning of the IAGOS programme and regarding the large number of data received every day, several attempts were done to automatically filter data points resulting from instrument failures or not resulting from a natural physical processes outside the aircraft. Fully automatic data processing actually reveal to be too complex and almost impossible to achieve efficiently. This is mainly due to the large diversity of issues that can occur to the measurement chain, from sampling inlets to the data reception at CNRS, and the lack of experience on longterm operation with the IAGOS system.
For altitudes !1000 m, the root mean square deviations between the MOZAIC and the IAGOS measurements are 4 and 12 ppb for O 3 and CO, respectively. Taking in account the comments made for Fig. 9  about natural variability close to the surface and the upper part of the atmosphere, it can be concluded that the performances of the IAGOS instruments compared with the MOZAIC instruments are excellent. In the near future, we expect to do the same data analysis for flight intercomparisons for cruising altitudes. For the moment, only 134 intercomparisons have been identified in total, including non-validated data and not enough cases comparing the MOZAIC and the IAGOS systems to be statistically significant. However, an individual example is shown in  Fig. 11. The latter presents a flight intercomparison between two aircraft following the same route (between 388E and 128E) with only an 18-min time difference and during more than 2 h at the same altitude.
IAGOS is the only programme for in situ data at global scale in the troposphere and the UTLS (see the use of IAGOS O 3 and CO data in this context; www. iagos. fr/macc). The Global Monitoring for Environment and Security (GMES) and the Monitoring Atmospheric Composition and Climate projects have made routine uses of MOZAICÁIAGOS data  (Elguindi et al. , 2010; Ordo´nez et al. , 2010; Gaudel et al. , 2015) , which have been particularly useful for independent validation of the products developed in the projects. Their potential for use in data assimilation (either as an 'anchor' for bias-correction schemes or in 'active' assimilation) has also been explored. The future deployment of a larger fleet (20 aircraft in 2020) of IAGOSequipped aircraft measuring a wider variety of atmospheric constituents is a very important perspective for CAMS.
The near real-time processing and data transmission capabilities of IAGOS will also make it possible to include the corresponding data stream into operational processing, similar to the aircraft meteorological data relay that is used for numerical weather prediction. Continued IAGOS operation has been assured through sustainable funding in the framework of international observing strategies such as Global Earth Observation System of Systems and its European component Copernicus, as well as from national funding institutions. IAGOS builds on previous European initiatives using novel technological developments and there is a strong emphasis on expanding the network to cover the Pacific, North America and further into the Southern Hemisphere. Its success relies heavily on the willingness of airlines to support operations.
shows a world map with all the airports that have been visited at least one time by a MOZAIC/IAGOS aircraft. Since the beginning of IAGOS, in July 2011, 147 airports have seen a MOZAIC/IAGOS aircraft land and take-off, sometimes several times a day. It has frequently happened that several of the MOZAIC and IAGOS aircraft have land or take-off at the same airport within a time window narrow enough to perform relevant instrument intercomparisons. These flight intercomparisons are automatically generated within the database as soon as at least two flights landed or took off at the same airport in B3 h and are particularly useful to detect any drifts in an instrument functioning. It is also a good way to compare the MOZAIC system performances to the IAGOS system for O3 and CO measurements during operation.
Figure9shows a flight profile intercomparison over Franckfurt on January 10, 2013. Since July 2011, 988 profile intercomparisons are currently available in the database but the example presented in this study was chosen because three different MOZAIC systems are compared with two different IAGOS systems. It also represent data that have been validated by the PI. The intercomparison figures always display tables summarising the flight schedules (see Fig. 9a and b). The flights are always named with the departure.
Acknowledgements IAGOS gratefully acknowledges financial support during its preparation, implementation and operation phase from the  European Commission  in  FP6  and  FP7 programmes , the  IAGOS  for the  GMES Atmospheric Service national (IGAS), research programmes in Germany (BMBF) ,  France  ( INSU-CNRS, MESR, CNES ) and the  UK (NERC) , in addition to institutional resources in Germany ( Helmholtz Association, Max-Planck-Society, Leibniz Association), France (Universite´de Toulouse, Me´te´o-France ) and the  UK (University of Manchester, University of Cambridge ) and the continuing support of participating airlines (Lufthansa,  Air France ,  Iberia in Europe, China Airlines and Cathay Pacific in Asia). IAGOS emphasise the excellence of the industrial partners involved in the technical development and realisation:  Sabena Technics Bordeaux  for aircraft systems definition and certification,  LGM Inge´nierie  for the instruments realisation and aeronautic qualification and enviscope  GmbH Frankfort  for operating the maintenance centre of IAGOS.
By contrast, operons are very rare in eukaryotes  [30, 31]. Only a few gene systems, e. g. , Hox, β-globin, GPAT/AIRC  [32]  and invertebrate species  [33]  exceptions have been reported. As a result, cis proximity of genes along eukaryote chromosomes does not relate to function and molecular phylogeny. High-throughput (HTP) transcript sequencing across tissues and species now enables biologists to study gene expression through the lens of evolution  [34, 35]. However, molecular phylogenetic analysis is recommended before profiling gene expression  [36, 37]. Gene expression patterns across tissues and species may provide valuable information to elucidate gene function. Among expression profiling methods, RNA-seq has been a breakthrough to quantify gene expressions on a genome wide scale. A plethora of RNA-seq experiments carried out in mammalian tissues has been made publicly available in the sequence read archive (SRA) database  [38].
Using a 13 protein sequence alignment, we previously established the mammalian specificity of Tex19  [7]. The recent availability of a series of mammalian genome sequences for Prototheria, Metatheria and Eutheria prompted us to revisit Tex19 molecular phylogeny. Intriguingly, we noticed that both Tex19 and Sectm1 were unique in human but duplicated in mouse and rat, i. e. , a quite unusual gene copy number pattern. In addition, both genes were neighbors on human, mouse and rat genomes. This unusual gene system and loci proximity in human and rodents encouraged us to simultaneously investigate Tex19 and Sectm1 molecular phylogenies. In the present study, 2 sequence homology searches have been carried out in protein databases and 2 high quality MACS of 58 proteins have been built. First, the sequence homologs searches show that both genes are eutherian-specific.
MACS construction We used PipeAlign  [39]  to generate the MACS. Homologs of mouse full-length Tex19. 1 and human full-length Sectm1 proteins were searched in Uniprot, RefSeq and the Protein Data Bank (PDB) using BLASTp (expect threshold 10 -4 , word size 3, BLOSUM62, gop 11 and gep 1). For Tex19 and Sectm1 homolog searches, the score, identities and positives cut-off values were set to 65 bits, 28 % and 40 %, respectively. In addition, whole genome shotguns (WGS) were searched by tBLASTn for further homologs. The mouse Tex19. 1 sequence was used as a query because human Tex19 lacks the C-terminal region. Conversely, the human Sectm1 sequence was used as a query because mouse Sectm1 proteins lack the C-terminal region. Alignment quality was manually refined in the SeqLab (GCG, Wisconsin package) editor by moving residues.
For each protein, basic data, i. e. , accession number, organism, brief taxonomy, sequence length and coding origin were reported in a file (publicly available on the FigShare repository http://figshare. com/articles/Catalog_of_Tex19_ protein_sequences/1491365 and http://figshare. com/ articles/Catalog_of_Sectm1_protein_sequences/1491366). Multiple alignment schemas were drawn in Jalview 2  [40]. Sequence logos were created in WebLogo 2. 8. 2  [41].
Sequence comparisons and secondary structure predictions Pairwise sequence comparisons were carried out with Needleman & Wunsch or Smith & Waterman algorithms implemented in the needle and water EMBOSS tools (Olson SA) (default parameters), respectively. Secondary structures were predicted with PSIPRED (Jones DT). Position-specific-iterated BLAST (PSI-BLAST) were carried out in the NCBI nr protein database with default parameters to search for remote homologs of Tex19 and Sectm1. Ten and three iterations were carried out for Tex19 and Sectm1, respectively.
Molecular modelling A HHpred search was carried out in the PDB with human Sectm1 as a query. The [PDB:3SOB] structure (X-ray, 1. 9 Angström resolution) was selected as a template to model by homology Sectm1 Ig-like domain in the Modeller 9. 13 program (Sali A). Sectm1 3D model was validated using MolProbity (Chen V. B. et al. , 2010) and PROSA (Wiederstein M. and Sippl M. J. , 2007). 3D structures were analyzed in PyMOL 1. 4. 1 (Schrödinger, LLC. ).
RNA-seq profiles across tissues and species RNA-seq experiments were selected from the SRA database. Tex19 and Sectm1 transcripts were masked for interspersed repetitive elements (IRE) (RepeatMasker, Smit A, unpublished) and used as queries on selected RNA-seq experiments. Reads were mapped to Tex19 and Sectm1 masked transcripts using MegaBLAST. Thanks to its default large word size (W = 28), MegaBLAST selectively retrieves sequences that are highly similar to a query. In double paralog species, i. e. , mouse, rat and cow, a best score approach was applied to reliably map reads to their proper paralog. Ex-aequo scoring reads were discarded.
EST profiles Human and cow placenta ESTs were automatically selected from Genbank release 199 using taxonomy and tissue_type fields. Genbank records were converted to BLAST databases. Human Sectm1 [RefSeq:NM_003004] and cow Tex19. alpha [RefSeq:XM_002696130], Tex19. beta [RefSeq:XM_001251766], Sectm1. alpha [RefSeq:NM_ 001102326] and Sectm1. beta [RefSeq:NM_001102326] masked transcripts were used as queries. MegaBLAST was used to search the EST database. For cow, ESTs were properly mapped to Tex19 or Sectm1 paralogs using a best score approach. Ex-aequo scoring ESTs were discarded.
Tex19 and Sectm1 are not homologs A dot plot was drawn to determine if Tex19 and Sectm1 proteins exhibit sequence similarity (Additional file 1). As controls of sequence homology, human Tex19 and Sectm1 were compared to mouse Tex19. 1 and Sectm1a orthologs, respectively. Human Tex19 and Sectm1 proteins do not show any similarity while homology between human and mouse orthologs was obvious. To determine if Tex19 and Sectm1 proteins might be distant homologs, i. e. , structure was conserved while sequences diverged, folds were investigated. First, Sectm1 structure is unknown. However, a weak sequence similarity with the Ig domain was previously mentioned  [12]. Second, Tex19 structure has not been resolved yet. Using Tex19 protein sequence as a query, a conserved domain database (CDD) search did not produce any hit.
Tex19 does not show any sequence similarity with known proteins or domains. Strategies have been described to detect remote homology  [45] , i. e. , fold conservation between proteins that share weak primary sequence similarity. Using the human "MCP" region sequence (Met-1 to Trp-54) as a query, remote homolog search algorithms, e. g. , PSI-BLAST, Interproscan and HMMER, did not produce any significant hit. Human Tex19 "MCP" region was submitted to PSIPRED secondary structure prediction program which predicted 2 alpha-helices (Fig. 3c ). The first helix spans residues Ser-15 to His-27 with a 7. 4 +/-1. 8 confidence value while the second helix spans residues Ser-32 to Ser-51 with a 6. 05 +/-2. 8 confidence value (maximum confidence is 9). Invariant Cys-2 and His-27 amino-acids were predicted in a coil region and in the first alpha-helix, respectively.
A conserved domaine database (CDD) search with human CD79A sequence as a query retrieved the Ig domain without ambiguity (E-value = 3. 85e-08). However, CD79A structure has not been resolved yet. Therefore, CD79A could not be used as a template for homology modelling. Using human Sectm1 sequence from residue 1 to 186 (i. e. , residues that aligned on CD79A) as a query, a HHpred search  [46]  in the structure database retrieved [PDB:3SOB_L] (Score 48. 5, E-value = 0. 0013), i. e. , an antibody light chain (Table  5 ). A predominant feature of most Ig domains is a sandwich of H and C symbols represent alpha-helix and coil predicted residues, respectively. Confidence value of secondary structure prediction is reported for each residue (maximum confidence equals 9). Invariant cysteines are depicted with a red background while invariant His-27 is shown with a blue background 2 beta-sheets connected by a disulfide bridge  [47].
The classical disulfide bridge was present in [PDB:3SOB_L] template structure between Cys-46 and Cys-111 (Fig. 4c ). Using 3SOB_L as a template, the 3D structure of Sectm1 Ig-like domain could be modelled (Fig. 4d ). The model was submitted to ProSA  [48]  which calculated an overall quality score of -4. 21, i. e. , in the range of native protein structures. Knowledge-based energy of the molecule was in an acceptable range. Moreover, using MolProbity, Phi and Psi dihedral angles of the Sectm1 Ig-like model were checked. 96 % (96/100) of all residues showed dihedral angles in Ramachandran plot favored regions. However, a peculiarity of the Sectm1 sequence is that the conserved cysteine are rather close in sequence (Cys-38 and Cys-55) and situated in N-terminal of the respect to classical Ig-domains, and they were therefore not aligned with those of the template.
Tex19 and Sectm1 expression patterns are opposite in testis and placenta across species Both gene expression profiles were investigated across species using publicly available RNA-seq data. In human, Sectm1 is expressed in a large variety of unrelated tissues, e. g. , colon, placenta, kidney, stomach, lung and thymus (Additional file 3). In mouse, it has been established that  Tex19. 1 and Tex19. 2 are specifically expressed in reproduction and embryonic tissues, i. e. , testis, placenta, ovary and primordial germ cells (PGC)  [11]. Therefore, we selected testis and placenta as reference tissues to simultaneously investigate both gene expressions in mouse, cow (or bull) and primates including human. 68 RNA-seq datasets, i. e. , 2. 8 billion reads, were processed. Liver and heart served as Tex19 negative controls while colon was used as Sectm1 positive control.
5c ). For cow, placenta RNA-seq experiments were not available. Therefore, expressed sequence tags (ESTs) were analyzed. EST detect only abundantly expressed genes. Both Sectm1. alpha (7 ESTs) and Sectm1. beta (42 ESTs)  transcripts were retrieved by sequence similarity searches (Table  6 ) (Additional files 4 and 5) and supported Sectm1 abundant expression in cow placenta. Moreover, RT-PCR detected Tex19. alpha but not Tex19. beta expression (Fig. 6a ) which means i) that Tex19. alpha is expressed in cow placenta but it is not abundant and ii) Tex19. beta is not expressed at all in cow placenta. In rat, placenta RNA-seq and EST data were unavailable. Using RT-PCR, Tex19. 1 was detected but not Tex19. 2 expression (Fig. 6b ). Therefore, mouse and rat exhibit similar expression patterns of Tex19 genes in placenta.
Homo sapiens [RefSeq:NM_207459], Pan troglodytes [RefSeq:NM_001246469], Pan paniscus [RefSeq:XM_ 003808957], Papio anubis [RefSeq:XM_003913613] and Macaca mulatta [RefSeq:NM_001194590] Tex19 transcripts were used as queries. Sectm1 expression was searched with Homo sapiens [RefSeq:NM_003004], Pan troglodytes [RefSeq:XM_001167936], Papio anubis [RefSeq:XM_003913612] and Macaca mulatta [Genbank:EHH25327] transcript sequences as queries. Mouse experiments were searched with Tex19. 1 [RefSeq:NM_028602], Tex19. 2 [RefSeq:NM_027622], Sectm1a [RefSeq:NM_145373] and Sectm1b [RefSeq: NM_026907]. Finally, cow Tex19. alpha [RefSeq:XM_ 002696130], Tex19. beta [RefSeq:XM_001251766], Sectm1. alpha [RefSeq:NM_001102326] and Sectm1. beta [RefSeq: NM_001083787] were used as queries on cow RNA-seq experiments.
Acknowledgements This work was supported by the  National Institute of Health and Medical Research (INSERM) , the  National Center of Scientific Research (CNRS)  and the  Strasbourg University (UdS). We are grateful to  Dr Marius Télétin  for helpful comments. We express our gratitude to  Prof. Catherine Eltchebest. We thank  Dr. Corinne Di Trani  and  Dr. David Di Paolo  ( Zoological and botanical park of Mulhouse, France ) for stimulating discussions. Finally,  Laurent Bianchetti  would like to thank  Dr. Gula Yusupova ,  Dr. Patrick Schultz ,  Dr. Christelle Thibault-Carpentier ,  Dr Isabelle Lebars  and  Dr. Stéphanie Kleinlogel  for their support.
Genomes We sequenced the two acorn worm genomes by random shotgun methods with a variety of read types (Methods; Supplementary Note 2), each starting from sperm from a single outbred diploid individual. The haploid lengths of the two genomes are both about 1 Gbp (Extended Data Fig. 1 ), but differ in nucleotide heterozygosity. Both acorn worm genomes were annotated using extensive transcriptome data as well as standard homology-based and de novo methods (Supplementary Note 3). Counting gene models with at least one detectable orthologue in another sequenced metazoan species, we find that Ptychodera and Saccoglossus encode at least 18,556 and 19,270 genes, respectively (Methods). Additional de novo gene predictions include divergent and/or novel genes (Extended Data Fig. 1 ). Despite the ancient divergence of the Saccoglossus and Ptychodera lineages (more than 370 million years ago, see below) and their different modes of development, the two acorn worm genomes have similar bulk gene content, as discussed later (Extended Data Fig.
Our analyses also placed pterobranch hemichordates as the sistergroup to enteropneusts 7 rather than within them  12. These phylogenetic analyses imply that genomic traits shared by chordates and ambulacrarians can be attributed to the last common deuterostome ancestor (see below). Using a relaxed molecular clock, we estimate a Cambrian origin of hemichordates (Methods, Extended Data Fig. 3  and Supplementary Note 6). We also performed several analyses to assess the controversial relationships between Xenoturbella, acoelomorphs and deuterostomes (Supplementary Note 6). With conventional site-homogeneous models, acoels remain outside deuterostomes  [20] [21] [22] [23]  (Fig. 2 , Supplementary Figs 6. 1 and 6. 2). Alternative models  24  , however, show equivocal branching of acoels depending on the inclusion of the current sparse data for Xenoturbella (Supplementary Note 6).
Gene predictions Transcriptome data for both species were used, along with homology-guided and ab initio methods, to predict protein-coding genes (Supplementary Note 3). For Saccoglossus, 8. 6 million RNAseq reads were generated from 7 adult tissues and 15 developmental stages using Roche 454 sequencing, along with previously deposited ESTs in GenBank. For Ptychodera, extensive EST data from egg, blastulae, gastrulae, larvae, juveniles, adult proboscis, stomochord, and gills defining 34,159 cDNA clones  53  , and 879,000 Roche/454 RNAseq reads from a mixed library of developmental stages  54  were used. The Saccoglossus genome was annotated using JGI gene prediction pipeline  55  , while Augustus 56 was used to produce gene models for Ptychodera. We find a total of 34,239 gene predictions for Saccoglossus (68% with transcript evidence) and 34,687 for Ptychodera (43% with transcript evidence), although these are overestimates of the true gene number due to fragmented gene predictions, mis-annotated repetitive sequences, and spurious predictions.