dataesr/scientific-paragraphs-categorization huggingface dataset:
Conclusion This article presents an R package, ASICS, integrating a complete analysis workflow of 1 H NMR spectra. This pipeline integrates an automatic metabolite identification and quantification method based on a reference library of pure metabolite spectra. ASICS showed better quantification results than existing methods and allowed to perform a complete and reproducible study on several hundreds spectra in only a few hours. Its use on two real world datasets exhibited similar results than the standard analysis on buckets followed by expert manual identification but also allowed to provide new information. For both studies, new metabolites, not extracted by expert identification, were found by ASICS, some of them confirmed by previous and independent studies. Obviously, as is the case for other omics data, in coming to a conclusion on whether the metabolites were really present in samples, a validation would be necessary.
, Tardivel, P. , Pere, M. -C. , Quesnel, H. , Paris, A. , Iannuccelli, N. , Vialaneix, N. (Co-dernier auteur), Servien, R. (Co-dernier auteur) (2019). ASICS: an R package for a whole analysis workflow of 1D 1H NMR spectra. Bioinformatics, 35 (21), 4356-4363. , DOI : 10. 1093/bioinformatics/btz248 "lefort_etal_p2018" -2019/4/20 -page 4 -#4 4 G. Lefort et al.
1 H NMR spectra were phased and baseline corrected. Glucose, fructose, and lactate were directly quantified by standard methods (they have been Comment citer ce document : Lefort, G. (Auteur de correspondance), Liaubet, L. , Canlet, C. , Tardivel, P. , Pere, M. -C. , Quesnel, H. , Paris, A. , Iannuccelli, N. , Vialaneix, N. (Co-dernier auteur), Servien, R. (Co-dernier auteur) (2019). ASICS: an R package for a whole analysis workflow of 1D 1H NMR spectra. Bioinformatics, 35 (21), 4356-4363. , DOI : 10. 1093/bioinformatics/btz248 "lefort_etal_p2018" -2019/4/20 -page 5 -#5.
citer ce document : Lefort, G. (Auteur de correspondance), Liaubet, L. , Canlet, C. , Tardivel, P. , Pere, M. -C. , Quesnel, H. , Paris, A. , Iannuccelli, N. , Vialaneix, N. (Co-dernier auteur), Servien, R. (Co-dernier auteur) (2019). ASICS: an R package for a whole analysis workflow of 1D 1H NMR spectra. Bioinformatics, 35 (21), 4356-4363. , DOI : 10. 1093/bioinformatics/btz248 "lefort_etal_p2018" -2019/4/20 -page 6 -#6.
in urine Comment citer ce document : Lefort, G. (Auteur de correspondance), Liaubet, L. , Canlet, C. , Tardivel, P. , Pere, M. -C. , Quesnel, H. , Paris, A. , Iannuccelli, N. , Vialaneix, N. (Co-dernier auteur), Servien, R. (Co-dernier auteur) (2019). ASICS: an R package for a whole analysis workflow of 1D 1H NMR spectra. Bioinformatics, 35 (21), 4356-4363. , DOI : 10. 1093/bioinformatics/btz248 "lefort_etal_p2018" -2019/4/20 -page 7 -#7.
Funding This project received financial support from  French National Agency of Research  ( PORCINET grant   ANR-09-GENM005 ). The PhD fellowship of  Gaelle Lefort  is supported by the  Digital Agriculture Convergence Lab  ( #DigitAg , http://www. hdigitag. fr/, ANR-16-CONV-0004 ), by the  INRA Mathematics and Computer Science Division , by the  INRA Animal Genetics Division  and by the  INRA Animal Health Divison.
Data collection and processing Data were collected for a crystal of the SeMet variant vitrified at 100 K with the mother liquor supplemented with 25% (v/v) of glycerol. As radiation damage was likely, the wavelength was fixed at the K edge absorption peak (0. 979 Å), in order to maximize the anomalous scattering factors (Se theoretical values: f″ 3. 84 and f′ -8. 32, according to: http://skuld. bmsc. washington. edu/scatter/AS_periodic. html), to collect a SAD dataset  (Gonzalez et al. , 1999). Data were indexed and integrated using DENZO (Otwinowski and Minor. 1997) and scaled using SCALEPACK  (Otwinowski et al. , 2003)  (Table  2 ).
Sequence alignments and structural comparison The Rv2991 sequence (163 residues, NCBI Reference Sequence: NP_217507. 1) was used to search non-redundant sequence databases (limiting the search to 500 entries maximum) using BLASTp  (Ye et al. , 2006). Of the 500 sequences found, 327 were selected for the uniqueness of the represented species, as many entries related to different strains of the same organism. A final alignment was carried out with COBALT (Papadopoulos and Agarwala, 2007)   using 27 selected sequences with decreasing sequence identity to Rv2991 (from 100% of the 163 residues long conserved hypothetical protein from Mycobacterium canettii to 64% of the 162 residues long F 420 -dependent oxidoreductase from Mycolicibacterium gilvum). Figures of the alignments were prepared with ESPript 3.
Acknowledgements The work was supported by a grant from the 5 th  PCRDT program  of the  European Union  (acronym X-TB). The authors thank the  EU  for support through the  grant 'Structural and Functional Genomics of Mycobacterium tuberculosis'  ( QLK2-CT-2001-02018 ). We thank the staff of the recombinant protein platform at the  Institut Pasteur  for the production and purification of Rv2991. We are grateful to  Dr. William Shepard  for the assistance during the collection of diffraction data at beamline ID29 at the  ESRF. Guy Dodson  and  Eleanor Dodson  are acknowledged for the helpful discussions and contribution to the project during structure determination in 2003. SB thanks all the co-authors for their patience during manuscript preparation.
Measurement of bronchiolar hyperplasia and tumor volumes H&E sections of the lungs of both control and Nanos3 LSL mice of the NSCLC model were scanned with the Axio Scan. Z1 Slide Scanner. To measure the extent of bronchiolar hyperplasia, the surrounding perimeter of bronchioles was manually drawn, and areas were measured using Volocity. The area inside the bronchioles was measured using the magic wand ROI tool of Volocity. The extent of bronchiolar hyperplasia was estimated by subtracting the inside area of the bronchiole from the area of the complete bronchiole. This value was divided by the perimeter of the bronchiole. Total tumor volumes were estimated using ImageJ 1. 51j. A program was written to calculate the tumor percentage making use of a classifier model manually trained on H&E sections of both control and Nanos3expressing mice, using the Trainable Weka Segmentation plugin in ImageJ.
Soft agarose assay Anchorage-independent growth was determined by seeding single-cell suspensions in medium containing 0. 35% agarose (Bioline) on top of a 0. 76% agarose layer. An additional top-agar layer was added after one week. After 14 days, pictures were taken with a Leica DC300F digital microscope camera using XnView software, and colonies were counted with Volocity. Experiments were performed in duplicate and the mean value was used for further analysis.
Data Rams were genotyped with the OvineSNP50 Bead-Chip (Illumina Inc. , San Diego, CA). Supplemental  Figure S1 (https: / / doi. org/ 10. 3168/ jds. 2018 -15405)  shows the distribution of progeny-tested rams genotyped per year of birth. The genotyped animals in the BB breed were born between  1999 and 2008; in the MTN breed between 1996 and 2007; in MTR breed between 1999 and 2009; in the LACCon subpopulation between 1996 and 2012; and  in the LACOvi subpopulation between 1999 and 2012. The SNP quality control included the absence of parent-offspring Mendelian segregation incompatibilities (<3%), SNP call rate >97%, and large deviations from Hardy-Weinberg equilibrium [SNP with P < 10 -6 were discarded; see  Baloche et al. (2014)  and  Legarra et al. (2014)  for more details]. The final data set included 38,287 autosomal SNP and 8,700 genotyped animals.
Pedigree-Based Inbreeding Estimates The pedigree-based inbreeding estimates (F PED ) of the genotyped individuals were obtained using the software PEDIG  (Boichard, 2002)  with the option that implements the algorithm of  Meuwissen and Luo (1992). The generation interval was also calculated us-ing PEDIG and was 4. 95, 4. 51, 4. 20, 3. 61, and 3. 55  for BB, MTN, MTR, LACCon, and LACOvi, respectively, in accordance with previous estimates  (Larroque et al. , 2014).
ROH-Based Inbreeding Estimates Runs of homozygosity are long, uninterrupted stretches of homozygous genotypes  (McQuillan et al. , 2008). More specifically, the inbreeding estimator (F ROH ), is the proportion of the genome that is in ROH. For individual i, F ROH i was calculated as F l l ROH ROH k n g i ik ROH i = = ∑ 1 , where n ROH i is the total number of ROH in individual i, l ROH ik is the length of the kth ROH in individual i in base pairs, and l g is the length of the genome in base pairs (which was 2,438,309,318 bp in the data set analyzed in the present study). An example of ROH is shown in Figure  1. The first allele is indicated by 1 and the second allele is indicated by 2 within the circles. The minimum length that constituted a ROH was 4 Mb, the minimum number of SNP was 10, the minimum density was 1 SNP per 10 kb, the maximum distance allowed between 2 consecutive homozygous SNP in a run was 1 Mb, a maximum of 2 missing genotypes were allowed (empty circles,) and 1 heterozygous genotype within a particular ROH was permitted (alleles indicated in black).
ACKNOWLEDGMENTS We thank  Carole Moreno  ( INRA, Castanet Tolosan, France ) and 2 anonymous referees for useful suggestions on the manuscript. This project has received funding from the  European Unions '  Horizon 2020 Research & Innovation programme  under grant agreement no. 772787 -SMARTER  ( Small Ruminants Breeding for Efficiency and Resilience, Castanet Tolosan, France ). This work was also supported by  ARDI (Research, Development and Innovation, Vitoria, Spain ; grant agreement  EFA 208/16 ) from POCTEFA funds, and  GDivSelGen  ( Efficient Use of Genetic Diversity in Genomic Selection, Paris, France) action (INRA Sel-Gen metaprogram ). Authors are also grateful to the  GenoToul bioinformatics platform Toulouse Midi-Pyrenees  ( Castanet Tolosan, France ) for providing computing and storage resources.
Pressure was measured before and after each data collection. The sample-to-detector distance was 279. 88 mm and calibrated, along with the wavelength, using Si standard and Fit2D software  [25]. The same synthetic sample of galenobismutite used in Olsen et al 2007 was selected to collect the present set of measurements, to avoid differences in compressibility ascribable to different chemical compositions in the samples. The X-ray beam was monochromatized to a wavelength of 0. 41125 Å and focused down to 10×10 µm area. Data were collected with a DAC rotating 64° around the ω-axis (from -32 to +32°) with angular step of 0. 5° and counting time of 1s per step. The scattered radiation was collected by a MAR555 flat panel detector, with 430 × 350 mm (555mm diagonal) active area. The extraction and correction of the intensity data, merging of reflections, and the refinements.
Pressure was measured before and after each data collection. The sample-to-detector distance was 279. 88 mm and calibrated, along with the wavelength, using Si standard and Fit2D software  [25]. The same synthetic sample of galenobismutite used in Olsen et al 2007 was selected to collect the present set of measurements, to avoid differences in compressibility ascribable to different chemical compositions in the samples. The X-ray beam was monochromatized to a wavelength of 0. 41125 Å and focused down to 10 × 10 µm area. Data were collected with a DAC rotating 64 • around the ω-axis (from -32 to +32 • ) with angular step of 0. 5 • and counting time of 1s per step. The scattered radiation was collected by a MAR555 flat panel detector, with 430 × 350 mm (555mm diagonal) active area. The extraction and correction of the intensity data, merging of reflections, and the refinements of the crystal lattice parameters were done by means of the CrysAlis software (Agilent technologies)  [26].
Measurements were performed at different pressures from 0. 5 to 20. 9 GPa on increasing pressure, and at 16. 43, 8. 12, and 2. 1 GPa on decreasing pressure to evaluate the reversibility and hysteresis phenomena of structural changes. The absorption correction was applied by means of ABSORB-7 software  [27]. The structure refinements were carried out with ShelXle  [28]  on F 2. Scattering curves for neutral atoms were used. Table  1  summarizes details of data collection and structure refinements up to 20. 9 GPa. Final atomic coordinates and isotropic displacement factors are listed in Table  2. Bond lengths, polyhedral volumes and polyhedral distortion parameters at different pressures, are reported in Table  3. Cif files with the hkl, i. e. , the Miller indices of the collected reflections, of individual refinements are in Table  S1  (deposited).
Compressibility The evolution of the unit-cell of galenobismutite with pressure is reported in Figure  2  and in Table  1. The behavior of the cell parameters shows no discontinuities in the investigated pressure range and indicates that no phase transition occurs in galenobismutite structure up to 20. 9 GPa. The volume-pressure data were fitted with a third-order Birch-Murnaghan equations-of-state, using the EOSFIT7-GUI software  [29] , as suggested by f E -F E , namely the "Eulerian finite strain" versus "normalized stress" plot  [30] , (Figure  3 ). The third order Birch-Murnaghan Equation of State (EoS) fit yields V 0 = 697. 4(8) Å 3 , K 0 = 51(1) GPa and K' = 5. 0(2). The bulk modulus and the first derivative values were in good agreement with the values obtained from the f E -F E plot  [30].
The intercept value and the slope obtained by a linear regression give F E0 and K' values equal to 51(1) GPa and 4. 8  (8) , respectively. The evolution of the unit-cell of galenobismutite with pressure is reported in Figure  2  and in Table  1. The behavior of the cell parameters shows no discontinuities in the investigated pressure range and indicates that no phase transition occurs in galenobismutite structure up to 20. 9 GPa. The volume-pressure data were fitted with a third-order Birch-Murnaghan equations-of-state, using the EOSFIT7-GUI software  [29] , as suggested by fE-FE ,namely the "Eulerian finite strain" versus "normalized stress" plot  [30] , (Figure  3 ). The third order Birch-Murnaghan Equation of State (EoS) fit yields V0 = 697. 4(8) Å 3 , K0 = 51(1) GPa and K' = 5. 0(2). The bulk modulus and the first derivative values were in good agreement with the values obtained from the fE-FE plot  [30].
The intercept value and the slope obtained by a linear regression give FE0 and K' values equal to 51(1) GPa and 4. 8(8), respectively. EOSFIT7-GUI software  [29] , as suggested by fE-FE ,namely the "Eulerian finite strain" versus "normalized stress" plot  [30] , (Figure  3 ). The third order Birch-Murnaghan Equation of State (EoS) fit yields V0 = 697. 4(8) Å 3 , K0 = 51(1) GPa and K' = 5. 0(2). The bulk modulus and the first derivative values were in good agreement with the values obtained from the fE-FE plot  [30]. The intercept value and the slope obtained by a linear regression give FE0 and K' values equal to 51(1) GPa and 4. 8(8), respectively. were the most and the least compressible lattice parameters, respectively, with the anisotropic ratio M 0a :M 0b :M 0c = 1. 55:1:1. 84. Density of galenobismutite changed from 7.
Discussion and Conclusion The comparison of data collected at different pressures on galenobismutite allows the following conclusions: a) The structural evolution is completely reversible with pressure increase up to 20. 9 GPa. The same values were measured increasing and decreasing the pressure and the same equation of state is measured by using values collected increasing or decreasing pressure. No evidence of hysteresis in the changes were observed, meaning that the changes are completely elastic. b) The change in atomic coordinations bring the M3 coordination polyhedron closer to the shape observed in other members of the CF structural family (from CN7+1 to CN8). However, unlike other CF crystal structures, M2 keeps and even equalizes its seven-fold coordination with increasing pressure.
Discussion and Conclusion The comparison of data collected at different pressures on galenobismutite allows the following conclusions: (a) The structural evolution is completely reversible with pressure increase up to 20. 9 GPa. The same values were measured increasing and decreasing the pressure and the same equation of state is measured by using values collected increasing or decreasing pressure. No evidence of hysteresis in the changes were observed, meaning that the changes are completely elastic. (b) The change in atomic coordinations bring the M3 coordination polyhedron closer to the shape observed in other members of the CF structural family (from CN7+1 to CN8). However, unlike other CF crystal structures, M2 keeps and even equalizes its seven-fold coordination with increasing pressure.
Cryo-EM data acquisition and processing. Grids were imaged using two 300-keV Titan Krios (FEI) equipped with a K2 Summit direct electron detector (Gatan) at ESRF (France) and at the Diamond Light Source (eBIC, UK) producing the SpeFL-ESRF and SpeFL-DLS datasets, respectively. Images were recorded with EPU in counting mode with a magnified pixel size of 1. 067 Å (Supplementary Table  3 ). 30 frames were collected to have a total accumulated dose of 30 electrons per Å 2. Data were processed in Relion 2. 1 41 , Relion 3. 0 42 and Cryosparc 0. 6 43 according to the scheme presented in Supplementary Figure  6. Briefly, MotionCor2 44 was used for movie alignment, Gctf 45 for Contrast Transfer Function (CTF) estimation and either Relion 2. 1 or Cryosparc for 2D classification of the particles obtained by automated picking in Relion 2.
1. The csparc2star. py and star. py scripts 46 were used for exporting particles selected in Cryosparc back into Relion. 3D classification was performed in Relion 2. 1 in three steps: (i) unsupervised classification with 4 times downsized particles, (ii) focused classification on all 3 tRNA sites with background subtraction and 3 times downsized particles, and (iii) focused classification on the P-site tRNA with background subtraction and 2 times downsized particles. Classes containing a single P-tRNA or both P-and E-site tRNAs were combined after ensuring that each class contained a peptide with the same conformation in the ribosomal exit tunnel when refined individually. Movie refinement and particle polishing were first performed with Relion 2. 1. Refined particle coordinates were then used to re-extract particles in Relion 3.
5 mM X-Gal in the absence (-) or presence (+) of 3 µmol ornithine or 20 µg bicyclomycin. Blue cells express the speF 1-3 -lacZα translational fusion. d, Model of speF induction following the ornithinedependent stalling of ribosomes translating speFL. The speFL open reading frame is boxed and shown partly in turquoise, with the overlapping rut site in yellow. Consecutive rare arginine codons R12 and R13 are shown in red letters. The leading ribosome on speFL is outlined in black while the second and third ribosomes are outlined in gray. The SpeFL peptide is in turquoise. e, Codon frequency at each position of speFL in E. coli (red line) and in the Enterobacteriales order (n species =10 (see Supplementary Fig. 1); mean -blue lines; ± standard deviation (SD) -light blue boxes). Codon usage values were obtained from the Codon Usage Database (NCBI-Genbank Flat File Release 160.
Acknowledgements A. H. V. is funded by a doctoral grant from the  French Ministère de l'Enseignement Supérieur et de la Recherche. C. A. I. , B. S. and G. S. have received funding for this project from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation program  (Grant Agreement No. 724040 ). C. A. I. is an  EMBO YIP  and has received funding from the  Fondation Bettencourt-Schueller. I. C-M. is funded by  Inserm  and A. C. S. is funded by a joint doctoral grant from  Inserm  and the  Aquitaine Regional Council. We acknowledge Diamond for access and support of the Cryo-EM facilities at the  UK  national electron bio-imaging centre (eBIC), (proposal EM 19716-1), funded by the  Wellcome Trust ,  MRC  and  BBSRC , and  Sarah Neumann ,  Andrew Howe  and  James Gilchrist  for assistance.
We also acknowledge the  European Synchrotron Radiation Facility  for provision of microscope time on CM01 30 and we thank  Michael Hons  for his assistance. This work has been supported by iNEXT, grant number  3901 , funded by the  Horizon 2020 program  of the  European Union. We thank  Isabelle Iost  for help with gradient fractionation,  Yaser Hashem ,  Armel Bezault  and  Marion Decossas  for help with grid preparation and screening,  Rémi Fronzes  for access to the GPU cluster,  Chiara Rapisarda  for help with cryo-EM data processing and  Nora Vazquez-Laslop  for providing the E. coli TB1 strain and pErmZα plasmid for the in vivo lacZ assay.
Clinical Trial Registration: NCT01876082 Findings: From December 2012 to August 2017, 72 patients were recruited (pazopanib arm: 48; MV arm: 24). The median follow up was 23. 4 months [95% CI: 20. 5-24. 2]. Forty-six in the pazopanib arm and 20 in the MV arm were assessable for efficacy. In the first 43 patients assessable for the primary endpoint in the pazopanib arm, the 6-month NPR was 83. 7% [95% CI: 69. 3-93. 2]. It was 45% [95% CI: 23. 1-68. 5] in the MV arm. The most common grade 3 or 4 adverse events in the pazopanib arm were hypertension (n=10, 21%) and diarrhea (n=7, 15%) in the pazopanib and neutropenia (n=10, 45. 5%) and liver transaminitis (n=4, 18. 5%) in the MV arm, respectively. Eleven patients (22. 9%) and 6 patients (27. 3%) had at least one serious adverse event related to study treatment in the pazopanib and MV arms respectively.
Randomization and masking Eligible patients were randomly assigned using a 2:1 ratio to receive either pazopanib or a regimen combining methotrexate-vinblastine, respectively. Upon investigator's request and after confirmation of all eligibility criteria, eligible patients were randomly assigned between the two arms of treatment by a web-based randomisation system (TenAléa software, https://prod. tenalea. net/gso/dm/) centralized at the sponsor site. Once the randomization was completed, the investigator received an automatic confirmation by email with the arm of treatment allocated. Randomization was stratified according to inclusion center and tumor location (limbs and girdles versus other). A minimization randomization method has been used to avoid significant imbalance between the arms.
Exploratory post-hoc proteomic analyses of pretreatment tumor samples were performed in line with previous work from Kim et al. 22  (Webappendix pages 1) with the aim to identify a proteomic signature predictive of response to pazopanib. Statistical analyses were performed using SAS version 9. 2 software (SAS Institute, North Carolina, USA). This study was registered with ClinicalTrials. gov number NCT01876082.
Role of the funding source The study was sponsored by Institut Bergonié (Bordeaux, France). The data were collected using the sponsor data-management system and were analyzed and interpreted by representatives of the sponsor in collaboration with the investigators. MT, MP, CB and AI had access to the raw data. All the authors contributed to and reviewed the data reported, verified that the study was conducted in fidelity to the study protocol, edited and approved the final manuscript submitted for publication, and vouched for the completeness of the data set and integrity of the analysis. The funding sources (GlaxoSmithKline and Novartis) played no role in the design of this study and did not play any role during its execution, analysis, interpretation of the data, or decision to submit results.