dataesr/scientific-paragraphs-categorization huggingface dataset:
Website To make this resource readily available to the scientific community, we created the covid19interactome. org, a website that can be used to explore the virus-host proximity interactome dataset. Users can explore the website from the point of view of a viral protein with a detailed report on proximity interactions for the WT or mutant variants, or by searching for a specific host prey protein, which will retrieve baits that identify the prey and offer a heat map profile view across the data set. A network exploration tool is also available that displays up to 25 of the most abundant preys (length Samavarchi-Tehrani et al. , SARS-CoV-2 proximity interactome page 5 normalized spectral counts) for each bait (Fig. 1f ; Supplementary Table  4 ). Examples of the functionality of the website are shown in Extended data Fig.
Discussion Here we report the proximal proteome of SARS-CoV-2 proteins, profiled as both N-and C-terminal fusions with the fast acting miniTurbo enzyme, in A549 cells, a widely used model system in coronavirus biology  [50] [51] [52]. We present the dataset as a resource accompanied by a user-friendly website (covid19interactome. org), and apply immunofluorescence microscopy, term enrichment and bait similarity profiling to assign each bait to a specific subcellular location. The resulting dataset identifies a number of new and confirmatory proximity interactions, and can be mined to shed light on the viral life cycle and to identify virus-host interactions that could represent important therapeutic targets. A major challenge in the interpretation of proximity-dependent biotinylation is the complexity of the data that it generates  9.
Several recent AP-MS studies have identified biochemically-stable interactions for SARS-CoV-2 proteins. As with previous comparative studies  11, 12, 15  , the overlap between the AP-MS and BioID datasets varies depending on the bait. This is not surprising, as, in addition to major differences in methodologies, BioID is a proximity-dependent detection method, and thus simply captures proteins in the same local environment as the bait. AP-MS conducted under standard, gentle lysis conditions is not optimal for the capture of labile protein-protein interactions, or proteins associated with membranes. Post-lysis artefacts, or in some cases associations that result from the extreme overexpression of transient transfection, can also explain some of the interactions captured by published AP-MS studies that are not recapitulated here.
DAPI (Sigma Aldrich, 20 mg/ml, used at 1:10,000) was used as a nuclear counterstain. Slides were mounted in ProLong Gold AntiFade (Molecular Probes, ThermoFisher Scientific, Cat# P36930) and imaged on a Nikon A1R+HD confocal scanner attached to an Eclipse Ti2-E inverted microscope. Confocal scanning was performed with a resonant scanner and 60x/1. 4 CFI Plan Apo lambda oil objective. NIS-Elements software was used for image acquisition and processing with Denoise. AI and 3D deconvolution. Images were processed using Volocity software V6. 2 (PerkinElmer, Waltham, MA).
Peptide and Protein Identification Raw files (. WIFF and. WIFF. SCAN) were converted to an MGF format and to an mzML format using ProteoWizard (v3. 0. 4468) and the AB SCIEX MS Data Converter (V1. 3 beta), as implemented within ProHits  69. For human samples, the database used for searches consisted of the human and adenovirus sequences in the RefSeq protein database (version 57). The database was supplemented with SARS-CoV-2 protein sequences, "common contaminants" from the Max Planck Institute (http://141. 61. 102. 106:8080/share. cgi?ssid=0f2gfuB) and the Global Proteome Machine (GPM; http://www. thegpm. org/crap/index. html), and with commonly used epitope tags. The search databases consisted of forward and reverse sequences (labeled "gi 9999" or "DECOY"); in total, 72,226 entries were searched for the human database.
Spectra were analyzed separately using Mascot (2. 3. 02; Matrix Science) and Comet  70  [2012. 01 rev. 3] with trypsin specificity and up to two missed cleavages; deamidation (Asn or Gln) and oxidation (Met) were selected as variable modifications and carbamidomethylation of cysteine residues was selected as a fixed modification. The fragment mass tolerance was 0. 15 Da, and the mass window for the precursor was ±40 ppm with charges of 2+ to 4+ (both monoisotopic mass). The resulting Comet and Mascot results were individually processed by PeptideProphet  71  and combined into a final iProphet  72  output using the Trans-Proteomic Pipeline (TPP; Linux version, v0. 0 Development trunk rev 0, Build 201303061711). TPP options were as follows: general options were -p0. 05 -x20 -PPM -dDECOY, iProphet options were -pPRIME, and PeptideProphet options were -pPAEd.
Enrichments Gene Ontology (GO) enrichments were performed using g:Profiler's Python client  74  (database version e100_eg47_p14), with the g:SCS multiple testing correction method, a significance threshold of 0. 01, our defined A549 custom background set and with no electronic annotations. The A549 background set included all proteins defined in the SAINT report or those found in A549 cells in ProteomicsDB  75  with an MS1 intensity > 0 (Supplementary Table  5 ). Protein domains and regions were retrieved from Pfam 76 and enrichments were calculated for each bait using Fisher's exact test using the A549 background. The FDR was controlled by using the Benjamini-Hochberg procedure for an FDR of 1%. Domains had to be found in at least three preys to be considered as enriched. Allowable regions included coiled_coil, sig_p and transmembrane.
a, Schematic of the virus proteins profiled in this study, mapped on the genomic viral RNA (*profiled in wild type and mutant forms; **not profiled). b, Representative immunofluorescence images demonstrating miniTurbo-tagged SARS-CoV-2 proteins targeting to different subcellular compartments and miniTurbo-tagged LMNA as a representative host protein (also see Extended data Fig. 2a  and b ). c, Summary of immunofluorescence data (number of baits in each category indicated in parentheses; see Supplementary Table  1  and Extended data Fig. 2a  and b ). d, Overview of the dataset. e, Overlap of the proximity interactions reported here with previously reported interactions for SARS-CoV-2 or any coronavirus (see Supplementary Table  3  and Extended Data Fig. 3 ). f, Cytoscape representation of the most abundant (length normalized spectral counts; up to 25 are shown) proximity interactors for each viral bait (See Supplementary    5  for full list of terms).
Also see Extended Data Extended Data Fig. 1. Expression of the bait proteins in A549 cells. a-b, Protein expression in the indicated transduced cells was induced with doxycycline (24 hours). Biotin (50 µM) was added to the culture media (15 minutes) and cells were harvested as detailed in methods. Proteins were resolved on SDS-PAGE and blotted with anti-FLAG. Beta-actin was used as loading control (a). Membranes were quenched using NaN3 and reprobed for biotinylated proteins using HRP-conjugated streptavidin (b). Samavarchi-Tehrani et al. , SARS-CoV-2 proximity interactome page 31 Extended Data Fig. 2a, b : Bait protein localization and proximal labeling. A549 cells were transduced with lentivirus to deliver the specified bait protein. Bait expression was induced as above. Cells were fixed and stained for bait protein using anti-FLAG antibody and for biotinylated proteins using Alexa-594 conjugated streptavidin.
The Golgi and nucleus were counterstained using anti-Giantin antibody and DAPI, respectively. Staining controls (for host bait PDIA4) included omission of doxycycline or biotin. Due to variability in expression levels between different baits, exposure settings and image brightness were adjusted to enable visualization of all baits shown, and is not intended to be quantitative. Images for NSP1, NSP3 NSP14_Ct and ORF14_Ct were not acquired (ND) due to low expression levels. Extended data Fig. 3 : Overlap with previously reported interactions by bait (supports Fig. 1e ). Percentage of previously reported interactions that were recovered by each bait in BioID, and the percentage of BioID proximity interactions that have been previously reported (See Supplementary Table  Extended Data Fig. 4. SARS-CoV-2 website.
b, Condition comparison plots can be viewed by selecting two conditions from (1). This will display all preys that pass the filter criteria for at least one bait. Preys will be displayed by spectral count of one bait versus the other. Options for filtering and interactivity are as described for panel a. Extended Data Fig. 7. Specific interactors for NSP6_Nt (supports Fig. 3e ). Spectral counts (xaxis) versus quantitative enrichment (i. e. specificity, y-axis) for preys in the NSP6_Nt BioID. Selected preys are indicated. Extended Data Fig. 10. Co-localization of N in G3BP1-stress granules upon overexpression of exogenous G3BP1 (supports Fig. 4c ). Using a lentivirus delivery system, mCherry-N and/or EGFP-G3BP1 were introduced into A549 cells under the control of a doxycycline inducible promoter.
Funding: This project was generously funded by a  Fast Grant  from the  Thistledown Foundation (Canada)  to BR,  FPR  and  ACG. This work was also supported by a  Canadian Institutes of Health Research Foundation  Grant ( CIHR FDN 143301  to ACG), and a  Natural Sciences and Engineering Research Council of Canada (NSERC ;  RGPIN-2014-06434  to ACG). Proteomics work was performed at the  Network Biology Collaborative Centre at the Lunenfeld-Tanenbaum Research Institute , a facility supported by  Canada Foundation for Innovation  funding, by the  Government of Ontario  and by  Genome Canada  and  Ontario Genomics  ( OGI-139 ). Work in the BR lab was also supported by the  Canada Foundation for Innovation (CFI) , and The  Princess Margaret Cancer Foundation. ACG is the Canada Research Chair (Tier 1) in Functional Proteomics.
Randomization The randomization will be centralized and stratified by center and parity and will be performed according to a 1:1 ratio. The randomization will be performed by nonvarying size block. A computer-generated randomization list will be carried out by a statistician before the study begins. Once a woman has been included through the filing of an electronic case report form (eCRF) directly via the internet (Clinsights software; Glassbeam, Santa Clara, CA, USA), she will retain her randomization number (if it has been assigned to her) even if she withdraws from the study or refuses randomization afterward. Women will be randomized after episiotomy and before the beginning of the suture to receive either 75 mg of ropivacaine (Fresenius Kabi, Sèvres, France; marketing authorization number 3400957740832 [2009, RCP rev.
Study assessments A summary of the study timeline and investigations is presented in Fig. 1. Randomized women are provided with a study calendar to assist them to prospectively record data relevant to the study questionnaires. Research staff members are trained in standardized administration of all study questionnaires and data collection procedures. Midwives collecting data for the ROPISIO study during the postpartum period (H12, H24, H48, D7, M3, and M6) are blinded. Indeed, the patient medical record does not contain the result of the randomization.
Statistical analysis Both intention-to-treat and per-protocol analyses will be conducted, following the Consolidated Standards of Reporting Trials (CONSORT) guidelines for randomized controlled trials and will be conducted with the statistician and researchers blinded to group status. The two groups will be described for demographic characteristics and risk factors for perineal pain after episiotomy. The existence of a "ropivacaine effect" (i. e. , a difference between the two groups for the primary outcome measure and the secondary outcome measures) will be analyzed. In case of missing data for the primary endpoint, two types of imputation will be realized (multiple imputation and worst case imputation): NPRS strictly superior to 3/ 10 on the perineal repair area. The percentage of patients with an NPRS strictly superior to 3/10 on the perineal repair area at D7 will be compared between groups (ropivacaine versus placebo) by a mixed effects logistic model in order to take into consideration parity, center, and group as fixed effects.
Data management The clinical research technician will complete data throughout the trial with Ennov Clinical software (Ennov, Paris, France) under the responsibility of each investigator. The eCRF for each woman will contain the following: One file completed by the clinical research technician concerning the maternal and obstetrical characteristics: woman's characteristics, course of the pregnancy, labor, and delivery One file completed by the clinical research technician about the postpartum events after leaving the delivery room and the results of NPRS in the immediate postpartum period H12, H24, and H48 Questionnaires on D7, at M3 and M6 postpartum, about perineal pain (NPRS), pain characteristic (DN4), quality of life (SF-36), sexual function (FSFI), and psychological status (EPDS) sent by the technician to the women by email and completed by the women in the electronic file.
In case the patient does not answer the survey at D7, they will be called by phone at D10. An email will be sent 1 day before M3 and M6. In case the patient does not answer, 7 days afterward, a second reminder will be sent by email. Data on D7 can be collected until D10 for analysis. Data at M3 and M6 will be accepted until 15 days after M3 and M6. During the research, all the patient data will be anonymized and provided by the investigator to the promoter. Patients' names and addresses will never appear in the eCRF. Only the first letter of the first name and the surname and the month and year of birth will be recorded with the randomization number. The email address will be collected by the medical team at the time of inclusion and will be registered in a specific database that will not be connected to the data accessible by the promoter.
A final report will be prepared for the funding body, and article will be prepared for publication with national and international dissemination. In case of protocol amendments, the investigators will be informed by a newsletter and an email including all the specific modifications and the updated documents (e. g. , protocol, patient information, and consent form). If several modifications are presented, a comparative table of the old and new document versions will be produced. All the amendments will be carried out by the promoter in the clinical trial database. Only the study promoter will have access to the complete final trial dataset. At the end of the study, each investigator will receive a copy of the data from the women include in his center.
Trial status Enrollment having started on 24 October 2017. As of 10 May 2020, all the 272 patients were included in the ROPISIO trial and the follow-up will last until October 2020. Three data safety and monitoring committees have confirmed the continuation of the study, in January 2018, February 2019 and March 2020 respectively. The current protocol version used for ROPISIO study is 8. 0, dated 22 February 2019. Enrollment was completed in April 2020. The total duration of the trial will be 43 months, including 37 months of inclusion and 6 months of follow-up in the postpartum period (assessment of quality of life, pain characteristics, sexual function, and postpartum symptoms of depression).
Acknowledgments:  Thai Q. D. (Pronovalg)  is acknowledged for providing the Cry reference sample and  Elie Duran  ( Onco-Hélios Therapeutix SAS ) for providing Nostoc sp. ATCC ® 53789™ strain and some culture equipment. Valerie Dias ,  Faculté de Pharmacie de Paris ,  Université de Paris , English Associate Professor for English improvement.
High-level ab initio calculations were performed to assist the analysis and to obtain reliable estimates for an extended set of spectroscopic quantities. We have searched for propargylimine at 3 and 2 mm in the spectral survey of the quiescent giant molecular cloud G+0. 693-0. 027 located in the "Central Molecular Zone", close to the Galactic Centre. Results. About 1000 rotational transitions have been recorded for the E-and Z-propargylimine, in the laboratory. These new data have enabled the determination of a very accurate set of spectroscopic parameters including rotational, quartic and sextic centrifugal distortion constants. The improved spectral data allow us to perform a successful search for this new imine in the G+0. 693-0. 027 molecular cloud. Eighteen lines of Z-propargylimine have been detected at level > 2.
For these data, the contributions due to the nuclear quadrupole coupling were neglected, and the measured frequencies were assigned to the corresponding pure rotational transitions. For each isomer, lines with or without resolved hyperfine structure have been given the same assumed uncertainty and have been analysed together in a global least-squares fashion. In total, our data sets comprise 531 lines for Z-PGIM and 545 lines for E-PGIM. They also included 50 and, respectively, 47 cm-wave transitions taken from the literature  (Sugie et al. 1985; McNaughton et al. 1988). Different statistical weights w = 1/σ 2 were given to the data of the various subsets to take into account the different measurement precision (σ). For the lines measured by  Sugie et al. (1985)  we retained the same weighting scheme of the original paper, while 50 kHz was given to the few transitions of the Z isomer reported by  McNaughton et al.
To evaluate the overall precision of our spectral computations, we have chosen a subset of transitions having K a = 0, 1, 2, 3 and lower level energy, E/k < 200 K. Then, we further singled out all the lines having integrated intensity of at least 1/10 of the maximum computed at 50 K. These selections constitute the most critical spectral data for an effective search of the PGIM isomers in astrophysical sources. They contain 159 lines in the 54-265 GHz range for Z-PGIM, and 247 lines in the 66-551 GHz range for the E-PGIM. The maximum 1σ errors are 1. 9 kHz and 4. 7 kHz, respectively, which correspond to radial equivalent velocity uncertainties in the ranges 0. 8 -2. 0 × 10 -2 at 3 mm, and 0. 3 -0. 8 × 10 -2 at 1 mm regime. As electronic supplementary information, we provide a set of spectral catalogues for PGIM isomers directly obtained with the SPCAT program  (Pickett 1991)  without any further editing.
Data analysis and results The two intervals of frequency covered by the survey are 71. GHz. During the observations, the pointing was checked every 1-1. 5 h on nearby planets, QSOs or bright H ii regions, and the telescope focus was checked at the beginning of the observations and after sunset and sunrise. The half-power beam width (HPBW) of the telescope at the observed frequencies is 14 -33. The observations were centred at the coordinates of G+0. 693: α(J2000) = 17 h 47 m 22 s and δ(J2000)= -28 • 21 27. The position switching mode was used in all the observations, with an off position of  (-885 , 290 ).
Discussion To the best of our knowledge, the formation of PGIM in the ISM has never been investigated to date, thus there are no chemical pathways included in astrochemical databases such as KIDA 7   (Wakelam et al. 2012)  or UMIST 8 (McElroy et al. 2013). In the following, we formulate and discuss a few possible PGIM formation mechanism based on the results of theoretical and experimental studies on detected imines (e. g. Lovas et al. 2006; Theule et al. 2011; Krim et al. 2019   The schematic reactions are illustrated in Fig. 6. As shown in Table  5 , all the proposed processes involve molecular precursors that are significantly more abundant than PGIM (although propynal only marginally), therefore it is not unlikely that one (or several) of these mechanisms might be able to account for the presence of this imine in G+0.
Conclusions This paper presents an extensive theoretical and laboratory study of the rotational spectrum of PGIM in its vibrational ground state, extending the earlier, very limited knowledge on the spectroscopic properties of this simple imine. The recordings have been performed in selected frequency intervals spanning the 83-500 GHz range, collecting some 500 lines for each of the two E and Z geometrical isomers. These experimental data were fitted to the coefficients of the S -reduced rotational Hamiltonian, providing a very precise set of rotational, quartic, and sextic centrifugal distortion constants. Many transitions, especially those of b-type dipole, show a resolvable hyperfine patterns due to the quadrupole coupling of the 14 N nuclei. For these transitions, 357 separate components were accurately measured and analysed to determine the corresponding hyperfine coupling coefficients.
The optimised values of all the spectroscopic con-stants are in excellent agreement with the results of high-level theoretical calculations, which were performed to assist the analysis of the laboratory data. The newly obtained set of spectroscopic parameters (Tables 2) allowed to generate a highly precise set of restfrequencies for E-and Z-PGIM at mm regime. With these data we have searched for PGIM in a spectral survey of the molecular cloud G+0. 693 located in the "Central Molecular Zone". We have detected 18 transitions of Z-PGIM, the lowest energy isomer, for which a column density of N = (0. 24±0. 02)×10 14 cm -2 was derived. The higher-energy E-PGIM isomer was not detected in the data, setting an upper limit of N < 1. 3 × 10 13 cm -2 from the two strong spectral features which show no contamination from other species.
2001) , we may estimate an overall accuracy of 2-3×10 -3 Å for bond distances. For comparison, the bond lengths reported by  Sugie et al. (1985)  listed in Table  A. 1 are generally shorter, while the ones computed by  Osman et al. (2014)  (listed in the same Table) are generally longer. These discrepancies are due to the low level of theory used in these earlier studies. As a matter of fact, the accuracy of molecular equilibrium structures is strongly dependent on the wave func-10 CFOUR, Coupled-Cluster techniques for Computational Chemistry, a quantum-chemical program package written by J. F. Stanton, J. Gauss, L. Cheng, M. E. Harding, D. A. Matthews, P. G. Szalay et al. , and the integral packages MOLECULE (J. Almlöf and P. R. Taylor), PROPS (P. R. Taylor), ABACUS (T. Helgaker, H. J. Aa.
Acknowledgements. We thank the  IRAM-30m  staff for the precious help during the different observing runs. A. P. C. gratefully acknowledges financial support by  University Cà Foscari Venezia  (ADiR funds) and the super-computing facilities of  CINECA  (project " CINEMA ", grant  HP10C2QE6F ) and SCSCF (" Sistema per il Calcolo Scientifico di Cà Foscari ", a multiprocessor cluster system owned by  Università Cà Foscari Venezia ). V. M. R. has received funding from the  European Union 's  Horizon 2020 research and innovation programme  under the  Marie Skłodowska-Curie  grant agreement No  664931. I. J. -S. and J. M. -P. have received partial support from the  Spanish FEDER  (project number  ESP2017-86582-C4-1-R ), and  State Research Agency (AEI)  through project number  MDM-2017-0737   Unidad de Excelencia María de Maeztu-Centro de Astrobiología (INTA-CSIC ).