dataesr/scientific-paragraphs-categorization huggingface dataset:
Genome assembly and quality evaluation We applied Canu  (Koren et al. , 2017)  to correct the SMRT reads, then used smartdenovo (https://github. com/ruanjue/ smartdenovo) to perform de novo assembly. The assembly was error-corrected using Quiver  (Chin et al. , 2013)  and Pilon  (Walker et al. , 2014)  based on alignment of 30-fold Illumina paired-end reads. The Hi-C sequencing reads were aligned to the assembled contigs using the bowtie2 end-to-end algorithm  (Langmead & Salzberg, 2012). We used Lachesis  (Burton et al. , 2013)  to cluster, order, and direct the assembled contigs onto 31 pseudo-chromosomes (TS_2. 0 assembly), which was arbitrarily defined based on the number of haploid chromosomes of the tree shrew  (Liu et al. , 1989). A total of 4 104 benchmarking universal single-copy orthologs in the mammalian dataset of the Benchmarking with Universal Single-Copy Orthologs (BUSCO)  (Simao et al.
, 2015)  were mapped to the assembled contigs using tBlastn  (Altschul et al. , 1997)  to assess overall assembly quality. We also used the whole-genome sequencing data of the male Chinese tree shrew to assess the quality of the TS_2. 0 assembly. In brief, we aligned the reads to the TS_2. 0 assembly and previous TS_1. 0 assembly  (Fan et al. , 2013)  using BWA  (Li & Durbin, 2009). We called genetic variants (SNPs and indels (insertions and deletions)) using FreeBayes  (Garrison & Marth, 2012)  and the structural variants (SVs) using Lumpy-SV  (Layer et al. , 2014) , respectively. The feature response curve (FRC)  (Vezzi et al. , 2012)  was estimated based on the aligned reads. The quality value (QV) was calculated as described previously  (Bickhart et al. , 2017) : QV =-log 10 ( ) S B (1) where, S indicates the cumulative length of all SNPs and indels identified using FreeBayes  (Garrison & Marth, 2012)  that had a probability of being heterozygous greater than 0.
Gene prediction and annotation A total of 13 RNA-seq datasets from our previous studies  (Fan et al. , 2013 (Fan et al. , , 2018) )  were cleaned using Trimmomatic  (Bolger et al. , 2014) , then aligned to the TS_2. 0 assembly using Tophat2  (Kim et al. , 2013). The cleaned reads were also de novo assembled using Trinity  (Grabherr et al. , 2011). The above RNA-seq assemblies were further combined using PASA  (Haas et al. , 2008). For homology-based gene prediction, we downloaded protein sequences of humans (Homo sapiens), chimpanzees (Pan troglodytes), macaques (Macaca mulatta) and mice (Mus musculus) from Ensembl (release 71;https://asia. ensembl. org/ index. html), which display more accurate annotation of gene models. These protein sequences were mapped to the TS_2. 0 assembly using TblastN  (Altschul et al.
, 1997). GeneWise  (Birney et al. , 2004)  was used to define gene models. For ab initio gene prediction, Augustus  (Stanke & Waack, 2003) , Genescan  (Salamov & Solovyev, 2000) , SNAP  (Korf, 2004) , and GeneMark  (Besemer & Borodovsky, 2005)  were used to predict coding genes. We employed EVidenceModeler  (Haas et al. , 2008)  to combine the RNA-seq, cDNA, and protein alignments with different weights (RNA-seq>cDNA/protein>ab initio gene predictions) to achieve a comprehensive and non-redundant reference gene set. This gene set was further updated using PASA  (Haas et al. , 2008) , followed by annotation based on the best matches derived from the protein sequence alignments described in the SwissProt and TrEMBL databases  (O'Donovan et al. , 2002)  using Blastp (with default parameters)  (Altschul et al.
, 1997). We annotated motifs and domains of proteins using InterPro  (Mulder & Apweiler, 2007)  to search publicly available databases, including Pfam (http:// pfam. sanger. ac. uk/), PRINTS (http://www. bioinf. manchester. ac. uk/dbbrowser/PRINTS/index. php), PROSITE (http://prosite. expasy. org/), ProDom (http://prodom. prabi. fr/prodom/current/ html/home. php), and SMART (http://smart. embl-heidelberg. de/). Descriptions of gene products, such as Gene Ontology  (Ashburner et al. , 2000)  information, were retrieved from InterPro  (Mulder & Apweiler, 2007). Pathway information was obtained by blasting the above reference gene set with the KEGG database  (Kanehisa & Goto, 2000) , with the best hit for each gene used for the annotation.
Whole genome sequencing and SNP calling Low-quality raw short reads were removed using Trimmomatic v0. 32  (Bolger et al. , 2014)  with the parameters "LEADING: 3 TRAILING: 3 SLIDINGWINDOW: 4: 15 MINLEN: 36". Qualityfiltered reads were aligned to the reference TS_2. 0 assembly using BWA-MEM  (Li & Durbin, 2009). Picard Tools (http:// broadinstitute. github. io/picard/) were used to flag duplicate reads. Only non-duplicate reads were used for subsequent analyses. GenomeAnalysisTK-3. 7 (GATK)  (McKenna et al. , 2010)  was used to realign indels and recalibrate base quality. We retained all single-nucleotide variants (SNVs) called by GATK UG with a Phred-quality score>Q10. The SNVs were hard filtered with the parameters "DP>8 & QD>5. 0 & HRun<5 & SB<0. 00 & QUAL>50 & FS<60. 0 & MQ>40. 0 & HaplotypeScore>13.
Population genetic analyses Nucleotide diversity (π) and Tajima's D value  (Tajima, 1989)  were estimated using VCFtools based on the six wild Chinese tree shrews, with a sliding window of 100 kb in each genome. For each coding gene, we estimated the population genetic parameters, including π, Watterson theta estimate (θw)  (Watterson, 1975 ), Tajima's D  (Tajima, 1989) , Fu and Li's D  (Fu & Li, 1993) ,  Fu and Li's F (Fu & Li, 1993) , and Fay and Wu's H  (Fay & Wu, 2000) , using in-house perl scripts. Manhattan plot analysis was performed using the R package qqman (https://cran. r-project. org/web/packages/qqman/index. html).
Tree shrew database Our developed tree shrew database (TreeshrewDB v2. 0) runs on a dual-processor server with an Ubuntu operating system and is implemented under the LAMP (Linux-Apache-MySQL-Perl) software stack. The Chinese tree shrew genome TS_2. 0 assembly, gene set, gene annotation, and other information are stored in the MySQL, and are administrated with the help of phpMyAdmin. The web interfaces were developed using various computer languages such as HTML, CSS, JavaScript, and Perl.
4% of the assembled genome. The longest contig was 16. 2 Mb (Table  1 ; Figure  1 ). We used BUSCO analysis, which is a powerful tool for assessing genome assembly and annotation completeness with single-copy orthologs  (Simao et al. , 2015) , to evaluate the quality of the TS_2. 0 contigs. About 91. 4% of the 4 104 core genes in the mammalian dataset were complete BUSCO genes (Table  2 ). These tests all showed that the newly assembled tree shrew genome contigs had superior quality to those in recently reported ape genomes  (Kronenberg et al. , 2018). We also generated ~264 x (705 Gb) Hi-C data (Table  3 ) to cluster the contigs into chromosome-scale scaffolds. A total of 1 728 contigs (comprising 96. 2% of the assembled genome sequence) were anchored into 31 pseudo-molecules, whereas 1 616 contigs (102 Mb, 3.
Genomic sequence variations at population level To understand genomic sequence variations in the Chinese tree shrew, we analyzed the whole-genome sequencing data of six individuals (each with a sequencing depth of 30x). After mapping to TS_2. 0, we identified a total of 12. 8 million (M) SNPs in these individuals (Figure  1B ), with 293 128 (including 194 751 synonymous and 98 377 non-synonymous SNPs) located in the coding regions. We estimated population genetic parameters for the Chinese tree shrew using the six captive individuals. We calculated the nucleotide diversity based on SNPs located in coding regions and identified 30 genes with high nucleotide diversity based on a cut-off π value of 0. 025 (Figure  1C ). Among these genes, five were located in the MHC loci or belonged to the immunoglobulin gene family, suggesting that immune genes may have a relatively high evolutionary rate in tree shrews, although this needs to be validated by analyzing more samples and including non-coding regions (Figure  1C ).
Tree shrew database updates Based on the TS_2. 0 assembly, we updated TreeshrewDB v2. 0 (Figure  4 ) to distribute the new high-quality tree shrew genome and our newly annotated gene and genome information. The main database updates included revision and expansion of genomic data, gene co-expression patterns, population genetic statistics, and improvements to the web interface. Briefly, for the retrieval module, we updated the reference sequence ID, genomic location and map, transcript sequence, and functional annotation based on the new gene set. We added five primate species (gibbon (Nomascus leucogenys), golden snub-nosed monkey (Rhinopithecus roxellana), black snub-nosed monkey (R. bieti), Bolivian squirrel monkey (Saimiri boliviensis boliviensis), and bushbaby (Otolemur garnettii)) in the orthologous gene sets from Ensembl (release 71;https://asia.
0, which is free to download. The updated gene sequences can be extracted in batches or individually by our homemade ExtractSeq. We incorporated Blast  (Altschul et al. , 1997)  and Genewise  (Birney et al. , 2004)  to show the mapping of genes in the genome. Overall, the updated database now provides a comprehensive annotation of the Chinese tree shrew genome to satisfy the needs of evolutionary analysis and biomedical research.
Furthermore, the inclusion of the reported transcriptomic data from 26 tissues and cells (Supplementary Table  S1 ) has enhanced our knowledge of mRNA expression profiling in the Chinese tree shrew. This database will be regularly updated to include recently released genetic data and serve as a platform for data sharing among tree shrew studies and for further elucidation of the genetic features of this animal. We believe that the tree shrew genome assembly TS_2. 0 and the updates will meet the increasing needs in the field. (Watterson, 1975 ), Tajima' s D  (Tajima, 1989) ,  Fu and Li' s D (Fu & Li, 1993) , Fu and Li' s F  (Fu & Li, 1993) , and Fay and Wu' s H  (Fay & Wu, 2000) ) were estimated based on SNPs located in coding regions in the whole genome sequences of six wild tree shrews. The database is freely accessible at http://www.
length of genomic sequence in which the order of bases has a high confidence level. Gaps occur where reads from two sequenced ends of at least one fragment overlap with other reads in two different contigs. Scaffolds are composed of contigs and gaps. N50: N50 statistic defines assembly quality in terms of contiguity. Given a set of contigs ranked by contig size, N50 is defined as the size of the shortest contig, which adds contigs with larger size to reach 50% of total genome length. -: Not available. with Universal Single-Copy Orthologs. A total of 4 104 benchmarking universal single-copy orthologs of the mammalian dataset were retrieved from.
Optical microscopy and image analysis One-centimeter-long fixed and immunostained vesseloid portions were included in 1% low gelling agarose (A9414, Sigma-Aldrich) within the tailored wells of the UniverSlide (33) filled with DMEM. Confocal images of vascular tubes were acquired with a Nikon Eclipse Ti inverted microscope equipped with a C2Si scan head acquisition software (NIS-Element, NIS). Image analysis was performed with Fiji (https://fiji. sc/).
We then analyzed the registered images with a homemade LabView-based (National Instruments) software. The algorithm workflow was the following: (i) The background was subtracted using a region outside of the tube in each image. (ii) The temporal variation of fluorescence was then extracted pixel by pixel. (iii) Pixel fluorescence variations along the entire acquisition were used for automated segmentation of the cells (watershed based segmentation). (iv) For each segmented cell, time to peak and morphological features were computed. The effect of ET-1 and angiotensin on in vivo contractility is classically shown by measuring the change in vascular tone  (32). Since one advantage of the vesseloid model is that it is manipulable, contraction could be assessed here by handling vesseloids inside an imaging chamber and by directly measuring the diameter of the vesseloid before drug application and at maximal contraction.
Introduction Until recently, bacterial identification in clinical laboratories has been mainly relying on conventional phenotypic and gene sequencing identification techniques. The identification of anaerobic bacteria is still fastidious due to slow bacteria growing. Many anaerobes are difficult in most diagnostic systems. For example, 12 weeks are needed for a clear diagnosis of active tuberculosis. This very long-time frame are really challenging for case identification. However, the last decade has seen the introduction of mass spectrometry into clinics for bacteria biotyping  (1) (2) (3) (4). Bacterial typing by MS is based on the fingerprinting of bacteria ribosomal proteins profiles using Matrix-Assisted Laser Desorption Ionization (MALDI) Mass Spectrometry (MS) through interrogation of a database of reference profiles  (5, 6).
Real-time analysis For real time analysis, the built model was exported to a second software module called OMB Recognition. The parameters for this analysis were: a TIC threshold of 1E+4 count for irradiation detection, a normalized intensity threshold of 1E+6, and an outlier limit of 5 standard deviations. The software analyzes 1 scan per spectrum and has a 3s timeout waiting for good spectrum. The cross-validated models are exported from the OMB software and then loaded in the OMB Recognition software module before any real time piece of tissue analysis by the SpiderMass  (18, 20). The real time acquired data are then directly interrogated, giving an immediate feedback using a color scale predefined from the specified classes. Lipid identification m/z intervals corresponding to loadings with the largest contribution to the explained variance observed in the different groups were selected for MS/MS-based identification.
For these experiments, the settings were exactly the same as described in the Instrumentation section and published  (18, 20). The identifications were performed directly on the tissue by doing a full scan first to verify the presence of the targeted masses. Then after switching to MS/MS mode, they were subjected to collision-induced dissociation (CID) in the transfer cell with respectively 20 and 35 V. The resulting spectra were annotated manually, and assignments were verified by interrogating the high accuracy mass measurements of the precursor ions using the LipidsMap database.
Acknowledgements This research was supported by grants from the  Ministère de L'Education Nationale, de L'Enseignement Supérieur et de la Recherche ,  ANR (IF) ,  Inserm Physicancer plan Cancer Physique, Mathématiques et Sciences de l'ingénieur appliqués au Cancer (MS) ,  SATT Nord de France (MS ; IF) ,  Region Haut de France (MS, IF).
2003)  -is the much more extended sky coverage because during the two-year duration of the main mission, the satellite will survey over 90% of the sky, avoiding only a narrow band around the ecliptic already explored, in part, by K2. The TESS nominal two-year survey is sectorized, with each sector consisting of a nearly continuous observation of the same 24 • ×90 • field for ∼ 27 days. Some overlap between sectors exists for the highest northern and southern ecliptic latitudes, meaning that some stars can be observed longer. In particular, stars located in the continuous viewing zone (CVZ), close to the ecliptic caps, could be monitored for as much as a year. The TESS data products include fullframe images (FFI) taken every 30 minutes and containing the entire field of view, as well as short-cadence observa-tions sampled every 120 seconds, providing a better time resolution for a selection of approximately 16,000 stars per sector.
2000) , have the potential to reveal the structure of the deepest regions, including the thermonuclear furnace and core boundary structure  (Charpinet et al. 2014b,a; Ghasemi et al. 2017). Van Grootel et al. (2010a,b)  and  Charpinet et al. (2011)  showed that important constraints on the inner core, such as its chemical composition (related to the age of the star on the EHB) and its size, are indeed accessible, suggesting in particular that the mixed core may be larger than expected. This would imply that efficient extra mixing processes (e. g. , core convection overshoot, and semi-convection) are effective. More analyses of this kind, with improved modeling tools, are required to fully and objectively map the internal properties of hot subdwarf stars. The Kepler and K2 legacy are already providing a remarkable set of seismic data that remains to be fully exploited in that context, but TESS adds another dimension at this level and has the promise of considerably expanding the sample of objects exploitable through asteroseismology.
As anticipated, the delivery of the TESS data for hundreds of selected TASC WG8 targets monitored in the first sectors has revealed a wealth of photometric variations occurring in all types of evolved compact stars, including many eclipsing or non-eclipsing binaries and compact pulsators. These will be presented in forthcoming dedicated publications. In this work, we focus on one of these objects, EC 21494-7018 (TIC 278659026), whose observation establishes that it is a bright, long-period pulsating sdB star that was not previously known to pulsate. The data reveal a particularly clean and rich pulsation spectrum, making this star a perfect target to attempt a detailed asteroseismic study. We present in Sect. 2, the analysis of the TESS light curve obtained for TIC 278659026, which constitutes the basis of the detailed asteroseismic study that follows in Sect.
TESS photometry Despite having no previously known variability due to pulsations or other causes, TIC 278659026 was positioned at a high priority rank among the stars proposed by the TASC Working Group 8 because its atmospheric parameters, T eff Article number, page 3 of 24 and log g, places this source well within the sdB g-mode instability region (see, e. g. , Figure  4  of  Charpinet et al. 2009). It was observed in TESS Sector 1, from July 25 to August 22, 2018, and the time series consists of 18102 individual photometric measurements 5  obtained with the 120 s cadence mode, covering almost continuously 27. 88 days (669. 12 hours) of observation. We based our analysis on the corrected time series extracted with the TESS data processing pipeline developed by the Science Processing Operations Center (SPOC) at NASA Ames Research Center.
Pulsation spectrum in g-mode We performed a standard prewhitening and nonlinear leastsquares fitting analysis to extract the frequencies present in the brightness modulations of TIC 278659026  (Deeming 1976). For that purpose, we used the dedicated software felix  (Charpinet et al. 2010 , see also  Zong et al. 2016a) , which greatly facilitates the application of this procedure. Most of the coherent variability is found to reside in the 95 -650 µHz range, where we could easily extract up to 23 frequencies above a chosen detection threshold at 4 times the median noise level 7  (see Table  1 ). The result of this extraction is illustrated in Fig. 2 , showing that the signal in Fourier space reconstructed from the 23 identified frequencies (plotted upside-down) reproduces very well the periodogram of the TESS light curve and no significant residual is found after subtraction of this signal.
35395-v20191104 where Ai, νi, and φi is the given amplitude, frequency, and phase, respectively. The phase is relative to a starting time TS = 2458325. 297922 BJD. * Frequencies interpreted as independent pulsation modes and used for the detailed asteroseismic analysis. ‡ These signals are difficult to interpret. Intrumental artifacts of yet unclear origin may be present in this frequency range and contamination from a bright nearby object, TIC 278659026 (TYC 9327-275-1), cannot be excluded. † Evaluated from a specific Monte-Carlo test as described in  Zong et al. (2016b). Finally, we emphasize from Table  1  a few numbers characterizing the quality of these first TESS data obtained for a pulsating sdB star. With only one sector (27. 88 days), targeting a bright (V = 11. 57), hot, and blue object (while TESS CCDs are red sensitive), the amplitude of the noise in Fourier space is around 0.
The latter in particular, although more massive as it has a canonical mass of 0. 471 ± 0. 002 M , happens to be nearly at the same stage of its core helium-burning phase, with ∼ 59% (in mass) of helium left in the central region, while its estimated core size is log q(core) = -0. 27 ± 0. 01 (M core = 0. 22 ± 0. 01 M ). Nonetheless,  Van Grootel et al. (2010a)  also provided a seismic estimate of the core mass for the sdB pulsator KPD 1943+4058, but obtained a significantly larger measurement for this quantity. This star may need to be reinvestigated with our most recent modeling tools applied to the full data set now available; the Van Grootel et al. 2010a analysis was based on Kepler 's Q0 light curve only. Remarkably, and for the first time in a sdB star, our present seismic modeling of TIC 278659026 also provides an estimate for the oxygen mass fraction in the helium burning core.
Summary and conclusions We have reported on the discovery of a new bright g-mode pulsating sdB star, TIC 278659026  (EC 21494-7078) , by the NASA/TESS mission. This object is just one of the hundreds of evolved compact stars (mostly hot subdwarfs and white dwarfs) monitored with the 120 s cadence mode in the first TESS sector. This effort is part of a larger program driven by TASC Working Group 8 to survey thousands of bright evolved compact stars for variability. The data consists of 27. 88 days of photometry with a nearly continuous coverage, thus offering a clear view of the pulsation spectrum of TIC 278659026. The analysis of the time series revealed the presence of many frequencies in the 90-650 µHz range, among which 20 are interpreted as independent lowdegree ( = 1 and 2) gravity modes later used to provide strong seismic constraints on the structure and fundamental parameters of the star.
16 +0. 13  -0. 05 (and for carbon, X(C) core = 0. 27 +0. 06  -0. 14 ). These values, along with the determination of the core size mentioned previously, are directly connected to the 12 C(α, γ) 16 O nuclear reaction, which is important in many areas of astrophysics but whose rate is still highly uncertain. TIC 278659026, through the present seismic analysis, may thus become an important test to improve our knowledge on this issue as well. We conclude this paper by emphasizing that this analysis of the hot sdB star TIC 278659026 discovered to be pulsating by TESS, and based on only one sector, is a demonstration that this instrument, even if not technically optimized for asteroseismology of hot and faint evolved compact stars, is providing outstanding data that can significantly drive this field forward.
Acknowledgements. We thank  S. Jeffery  for useful comments and suggestions that helped improve this manuscript. Stéphane Charpinet  acknowledges financial support from the  Centre National d'Études Spatiales  ( CNES, France ) and from the  Agence Nationale de la Recherche  ( ANR, France)  under grant  ANR-17-CE31-0018 , funding the  INSIDE  project. This work was granted access to the high-performance computing resources of the CALMIP computing center under allocation numbers  2018-p0205  and  2019-p0205. This paper includes data collected by the TESS mission. Funding for the TESS mission is provided by the  NASA   Explorer Program. Funding for the  TESS Asteroseismic Science Operations Centre  is provided by the  Danish National Research Foundation  (Grant agreement no. :  DNRF106 ),  ESA  PRODEX Article number, page 18 of 24 S.