dataesr/scientific-paragraphs-categorization huggingface dataset:
2% Triton X-100 in phosphate-buffered saline (PBS) (15 min), blocked with 1% bovine serum albumin in PBS for 1 h (blocking buffer), incubated with primary antibodies (diluted in blocking buffer) for 1 h in RT, followed by three PBS washes and then incubated in secondary antibodies (1 : 400 in blocking solution) for 1 h in the dark at RT followed by three PBS washes. Samples were mounted with VectaShield mounting medium containing 4′,6-diamidino-2-phenylindole (DAPI). Image acquisition was performed using Leica TCS SP2 confocal scanning microscope, equipped with a ×63/1. 4 numerical aperture (NA) objective. Single optical sections of the images or maximum projections (step size 0. 5 μm) were processed using ImageJ and smoothed to reduce the background noise. Quantification of nuclear morphology, YAP localization: images from random fields (upto 50) were acquired from coverslips stained with DAPI and Lamin or YAP on a UltraVIEW VoX spinning-disc confocal unit with Velocity software (PerkinElmer).
Briefly, an ultratome (LeicaEM UC7; Leica Microsystems, Vienna) was used to cut 60 nm serial thin sections and 200 nm serial semi-thick sections. Sections were collected onto 1% Formvar films adhered to slot grids. Both sides of the grids were labeled with fiduciary 10 nm gold (PAG10, CMC, Utrecht, The Netherlands). Tilt series were collected from the samples from ±65°with 1°increments at 200 kV in Tecnai20 EMs (FEI, Thermo Fisher Scientific, Eindhoven, Tthe Netherlands). Tilt series were recorded at a magnification of ×20,000 or ×60,000 using software supplied with the instrument. The nominal resolution in our tomograms was 4 nm, based upon section thickness, the number of tilts, tilt increments, and tilt angle range. The IMOD package and its newest viewer, 3DMOD 4. 0. 11, were used to construct individual tomograms and for the assignment of the outer leaflet of organelle membrane contours, and best-fit sphere models of the outer leaflet were used for vesicle measurements.
Videos were made in 3DMOD and assembled in QuickTime Pro 7. 5 (Apple) and the video size was reduced by saving videos at 480p in QuickTime. CLEM was performed exactly as described previously  59. FIBSEM: FIBSEM analysis was performed using a FEI Helios NanoLab 660 FEGSEM or G3 equipped with SEM Multi-Detector and ICD detector at accelerating voltage 2. 0 kV. Access to both of which was kindly provided by FEI, Co. (FEI, Thermo Fisher Scientific, Eindhoven, The Netherlands). For all highresolution EFSEM images, a primary beam energy of 2. 0 kV was used with a working distance of 1 mm, 3 ms dwell time, and tube bias of 140 V. An Auriga 60 FIB-SEM (Zeiss) microscope with Atlas3D software (FIBICS) was additionally used to collect the 3D data of two cells. Acquisitions were performed according to instructions of the manufacturers.
These cells were loaded onto the channels in the presence of ATR inhibitor or DMSO. Single stack image acquired for each field of view every 2 h for 10 h duration. Image acquisition parameters and analysis were similar to the above-mentioned experiment. FLIM-FRET analysis. For the acquisition, we used the Leica TCS SP8 confocal microscope with White light laser as excitation source tuned at 488 nm and HC PL APO CS2 ×63/1. 40 oil-immersion objective, everything managed by Leica Application Suite X software, ver. 3. 5. 2. 18963. For the lifetime measurements, the above system was implemented with PicoQuant Pico Harp 300 TCSPC module and picosecond event timer, managed by PicoQuant software (SymPho Time 64, ver. 2. 4). Data were imported and analyzed using in-house ImageJ macro. Micro-fabricated cell compression chamber.
Before the experiment, a cell compression device was capped and locked on the cell culture dish. Images were acquired using ×40 oil lens (NA = 1. 3) in PerkinElmer spinning disk microscope. Analysis of cell migration in micro-fabricated channels. We followed the protocol established previously  28  for PDMS channels preparation. Briefly, Polymer and crosslinking agent (RTV615 kit) (mixed in 1 : 10 ratio) was used to prepare PDMS channels. These are then plasma treated and embedded onto a glass-bottom dish or a two-chamber LAB-TEK II dish (Thermo Fisher). Then channels were fibronectin-coated and cells were loaded the day before the beginning of time lapse. We chose 15 μm-long, 4 μm-wide constriction for experiments involving HeLa and U2OS cell lines. Time-lapse images were acquired (every 10 or 15 min, with zstacks) on a UltraVIEW VoX spinning-disc confocal unit with Velocity software (PerkinElmer), equipped with an Eclipse Ti inverted microscope (Nikon) and a C9100-50 electron-multiplying CCD (charge-coupled device) camera (Hamamatsu) or Confocal Spinning Disk microscope (Olympus) equipped with IX83 inverted microscope provided with an IXON 897 Ultra camera (Andor) with OLYMPUS cellSens Dimension software, or on a DeltaVision Elite imaging system using ×40 oil-immersion (for 53BP1 foci counting) or ×20 dry objective for a duration of 18-24 h.
The images were processed using ImageJ and smoothed to reduce the background noise. All the quantifications were performed manually. Number of cells reaching the constriction within the experimental period was considered as a total cell number. Number of cell death and cell passing were counted per field to calculate the percentages. Fields with no cell migration or death were discarded from analysis. 53BP1 foci were counted manually using ImageJ. Difference was calculated by subtracting number of Foci before engaging the constriction from the number of foci present in the constriction. IP, MS, and data analysis. U2OS cells expressing GFP-ATR or GFP alone are cultured in SILAC medium containing light or heavy-labeled L-lysine and L-arginine for 5 days ensuring adequate incorporation of isotopes.
For label-free analysis, the procedure was the same but immunoprecipitated samples were kept separate and loaded separately, then digested and analyzed by MS. Proteins were identified using Mascot (v. 2. 3. 02) and quantification was done using Scaffold (v. 4. 3. 4). Exclusive unique peptide count was selected to evaluate changes in proteins abundance. For analysis, we pooled data from all experiments, selected candidates that were found as ATR-GFP interactors in at least two experiments, and which were significantly enriched (fourfold) over GFP control in at least one SILAC experiment. We performed Gene Ontology (GO) analysis using DAVID, to generate enriched terms for cellular compartments (GOTERM_CC) and biological processes (GOTERM_BP) (p-value with Benjamini correction < 0. 05). Revigo tool was utilized to simplify GO terms (resulting list size: 0.
7, database: Homo sapiens, semantic similarity measure: SimRel) and R Studio for plotting of Revigo output (size = log size, color = log10 p-value). Candidates where then manually curated to generate non-overlapping sub-categories of interest (for this study). A network was generated for each sub-category using STRING interaction analysis and the output was plotted using cytoscape. The MS proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE  65  partner repository with the dataset identifier PXD020622 (Project Name: ATR interactome in H. sapiens bone osteosarcoma U2OS cells). Files are named SILAC1, SILAC2, and SILAC3. Lipidomic analysis. (I) Lipid extraction: Nuclei were isolated according to the protocol  66. Nucleus and total cell samples were resuspended in 150 mM ammonium bicarbonate and passed through a 26 G syringe needle to fragment nucleic acids.
Acknowledgements We thank  O. Capetillo  ( CNIO, Spain ),  R. Tibbetts  ( Wisconsin ) for reagents,  Y. Schwab  and  J. M. Serra Lleti  ( EMBL, Germany ),  Letian Li  and  Anthony Burgess  ( Thermo Fisher Scientific, The Netherlands ) for assistance in EM analysis,  Michele Giannattasio  and the members of MF and GS laboratories for assistance and suggestions. We thank IFOM cell culture and imaging facility and Cogentech sequencing services for technical assistance. Work in MF's laboratory is supported by grants from  Associazione Italiana per la Ricerca sul Cancro, AIRC, Italy  ( 16770 ,  21416 ,  22759 ),  Association for International Cancer Research ,  AICR  (ref- 14-0338 ),  Telethon-Italy  ( GGP12171 ),  Centro europeo di Nanomedicina  (ref- EP002 ),  Ministero dell'Istruzione, dell'Universita e della Ricerca  ( MIUR-PRIN-2015SJLMB9 ), and the  European Commission  (ref-316390).
G. R. K. is supported by  Marie Curie Initial Training Networks (ITN) , ( FP7  "aDDRess"; Project number:  316390 ) fellowship and  Italian Association for Cancer Research (AIRC)  fellowship (Ref. 19464). A. K. is supported by  Wellcome Trust/DBT India Alliance intermediate fellowship, SERB (Department of Science and Technology) , and  Department of Biotechnology, Government of India. J. B. by is supported by the  Danish Cancer Society , the  Danish Council for Independent Research , the  Novo Nordisk Foundation , the  Swedish Research Council , and  CancerFonden. S. P. receives support from Denovostem  ERC   670126  and  FARE-MIUR  grants. T. P. is a Cariparo-Foundation fellow.
RNA sequencing (RNA-seq) and data analysis RNA extraction and RNA-seq library preparation upon GFP and NCBP3 depletion were performed as described  (44). Total RNAseq of siNCBP3 depletion samples are first reported here, but were collected as part of the same experiment described in  (44, 45). Reads from siNCBP3 samples were processed in parallel with the siEGFP control and relevant depletions from GEO:GSE99059 were processed in parallel as described in  (46). In brief, raw reads were quality filtered and trimmed as described (29), using Trimmomatic (v 0. 32) and settings (PE ILLUMINACLIP:/com/extra/Trimmomatic/0. 32/adapters /TruSeq3-PE-2. fa:2:30:10 HEADCROP:12 LEADING:22 SLIDINGWINDOW:4:22 MINLEN:25). Cleaned reads were then mapped to GRCh38 with HISAT2 (v 2. 1. 0) (47) using default settings and the genome index 'H.
CLIP data analysis Processed CLIP data for NCBP3 and EIF4A3 were obtained from  (49). Data shown are from NCBP3 PAR-CLIP data processed with the PARalyzer tool and the EIF4A3 HITS-CLIP data was processed with Piranha  (49). NCBP2 CLIP data was from GSE94427 (13) and lifted to GRCh38. ALYREF CLIP data was from GSE113896  (24)  and lifted to GRCh38. Metagene plots for CLIP data were constructed using custom python and R scripts employing deeptools software (v3. 0. 2) (50) relative to GRCh38 annotations shipped with featureCounts used for RNAseq analysis. For T>C conversion positions, raw reads were obtained from SRA: SRR500480 and SRR500481  (51) , adapter sequences (TCTTTTATCGTA TGCCGTCTTCTGCTTG and TCTCCCATCGTATGCC GTCTTCTGCTTG), low quality and short reads removed using bbduk from the BBMAP software (v35.
It was also notable, that the EJC core component MLN51 was not identified in the NCBP3 IP-MS screening, yet it appeared in the IP-western validation (Figure  2B , lanes 7, 9 and 11). However, compared to the three other EJC core components, MLN51 was captured less efficiently. This finding might be explained by the largely cytoplasmic localization of MLN51, whereas the remaining EJC core components and NCBP3 mainly reside in the nucleus  (32, 55, 56). It is notable that NCBP3's interaction with the EJC components EIF4A3 and MAGOH was not sensitive to RNase treatment, whereas its interaction with RBM8A and MLN51 was. Finally, we also performed reverse-IP/western analysis using HeLa cells stably expressing HA-tagged EIF4A3 or LAP-tagged ALYREF. Both EIF4A3-HA and ALYREF-LAP IPs recapitulated previous data by co-purifying NCBP3 in an only mildly RNasesensitive manner (Figure  2C, D ).
We next interrogated the EJC core integrity-dependent NCBP3 interaction further, by conducting in vitro protein binding assays of recombinant EJC core proteins and NCBP3. Taking advantage of the affinity of NCBP3 to m 7 -GTP, we used m 7 -GTP Sepharose to purify NCBP3-bound proteins  (16, 32). This revealed that NCBP3 was unable to associate with either of the individual EJC core proteins   (23, 58). The full data set of significantly enriched proteins is provided in Supplemental Table  S2. (B) IP/western blotting analysis validating the interactions of NCBP proteins with the indicated EJC and TREX components. IPs were performed on extracts from control (CTRL-LAP), NCBP1-LAP, NCBP2-LAP and NCBP3-LAP HeLa cells with (+) or without (-) RNase A/T1 treatment. Bait proteins were detected with anti-GFP antibodies.
Hence, although MLN51 interaction with NCBP3 was less abundant compared to the other EJC core components (Figure  2B ), and appeared insensitive to EIF4A3 or RBM8A depletion (Figure  3A ), the protein was still required for EJC interaction with NCBP3 in vitro (Figure  3B , compare lanes 9 and 10) (see Discussion). We also performed pull down assays with an NCBP3 construct comprising only the aa1-128 N-terminal region, which harbors the RRM of the protein, conferring cap and ARS2 affinity  (16, 32). Although slightly less efficient than the full-length protein, this N-terminal fragment was also able to pull down the EJC core (Supplemental Figure  S3 ). Taken our data together, we conclude that NCBP3 binds to the EJC, but only when it is fully assembled, which suggests that the interaction occurs post-splicing.
This reinforced the association of NCBP3 with splicing and RNA export activities. We next investigated any preferential binding of NCBP3 to RNA by re-analyzing published CrossLinking and Im-munoPrecipitation (CLIP) data sets for NCBP3  (49, 51) , EIF4A3  (49, 63) , NCBP2  (13)  and ALYREF  (24). Despite these datasets being obtained by different laboratories employing different versions of the CLIP technique, we reasoned that comparison at the metagene level might still yield relevant insights. To this end, we first compared the binding profiles of these factors on exonic regions of protein coding transcripts. Unlike NCBP2, which displayed an expected cap-proximal peak, CLIP signals of NCBP3 traced further downstream into mRNA bodies, quite similar to EIF4A3 and less persistent than ALYREF (Figure  4B ).
This might also help explain why MLN51 is required for NCBP3-EJC interaction in vitro, which is not obvious in vivo, as the reconstituted environment lacking other proteins, such as RNPS1, that could influence EJC formation. Interactions with MLN51 notwithstanding, the association of the bulk of NCBP3 with EJC was also reflected by their similar RNA binding profiles derived from CLIP datasets; NCBP3 binds close to the splice junctions of multiexonic RNAs, showing two broad peaks at 10-20 nt and 25-35 nt upstream of exon-exon junctions (Figure  4C  and Supplemental Figure  S4C ). This would be consistent with binding around a deposited EJC, which covers around 6-9 nt and a prominent EIF4A3 cross-linking site at ∼27 nt upstream of the splice junction  (35, 42, 64, 73). Based on this, we speculate that the EJC may direct NCBP3 binding (see below).
ACKNOWLEDGEMENTS We thank the  National Center for Dynamic Interactome Research at the Rockefeller University  for facility support for the interaction screen,  Dr Ina Poser  and  Prof. Anthony A. Hyman  for providing the LAP-tagged cell lines, and  Dr Catherine-Laure Tomasetto  for providing the MLN51 antibody. Author contributions: Y. D. , T. H. J. , J. L. and H. L. H. designed the experiments. Y. D. , I. B. , H. J. , C. I. , K. R. M. , W. M. S. performed the experiments. Y. D. , M. S. and K. R. M. performed data analysis. M. S. , H. L. H. and S. C. provided critical input. T. H. J. and J. L. supervised the project. Y. D. and T. H. J. wrote the manuscript with input from all co-authors. FUNDING Work in the T. H. J. laboratory was supported by  European Research Council  Advanced Grant [339953];  Independent Research Fund Denmark  and the  Lundbeck Foundation ; Work in the J.
L. laboratory was supported in-part by  National Institutes of Health  [R01GM126170], and benefitted from the support of the  National Center for Dynamic Interactome Research  [ P41GM109824 ]; Work in the H. L. H. laboratory was supported by the  French Agence Nationale de la Recherche  [ ANR-13-BSV8-0023 ,  ANR-17-CE12-0021 ];  Centre National de Recherche Scientifique ;  Ecole Normale Supérieure  and the  Institut National de la Santé et de la Recherche Médicale, France. Funding for open access charge:  European Research Council  [339953].
11. 03, Nikon, Tokyo, Japan). For rat tissue analysis, we randomly took images under light microscopy at 20× (Olympus BX51, Olympus, Hamburg, Germany) equipped with a digital camera (Olympus DP50, Olympus, Hamburg, Germany) and CellSens Digital Imaging software (version 1. 9, Olympus, Hamburg, Germany). For cross-sectional area (CSA) determination, at least 100 muscle fibers from three different images per muscle were measured. The mean and area distribution for each animal was analyzed (n = 4 per group) using Image J software (version 1. 46; National Institutes of Health; available at http://rsb. info. nih. gov/ij/), and the minimum diameter and the circular area were calculated based on a ratio of calibrated pixels to actual size (mm). For immunofluorescence labeling, the slices were pretreated with 10 mg/mL NaBH 4 to reduce autofluorescence for 80 min at 4 • C.
Thereafter, cells were fixed using 4% tamponed formaldehyde for 30 min and then washed out with TBS for cytology observations. For immunoblotting, we added RIPA buffer (50 mM tris-HCl, 1% triton-X-100, 0. 5% Na-deaxycholate, 0. 1% SDS, 150 mM NaCl, and 2 mM EDTA) with inhibitor phosphatases 20× and inhibitor proteases 100× buffer to the cultured cells (n = 4-5). For the fiber diameter evaluation, we randomly took images under light microscopy at 20× (Olympus CKX41, model U-LH50HG) equipped with a digital camera (Olymus U-TV1x-2) and an Olympus DP20-5 device from three wells for each condition for at least 100 myotubes for each condition. The area distribution for each condition was analyzed (n = 3 per group) using Image J software (version 1. 46; National Institutes of Health), was calculated using the circle area equation and using the length between two points from the myotubes width below the nucleus using the "straight" tool based on a ratio of calibrated pixels to actual size (mm).
Statistics The normality and homoscedasticity of the data were studied for each parameter to apply the correct statistical method (parametric or nonparametric) using the Shapiro-Wilk test. For all the data, we performed an unpaired Student's t-test to compare two groups, one-way analysis of variance (ANOVA) to compare three or more groups, and two-way analysis of variance (ANOVA) to compare grouped data followed by Turkeys' multiple comparison test. Data are presented as means ± standard error of the mean (SEM). Statistical analyses were conducted using GraphPad Prism 8 software (San Diego, CA, USA). The myofiber and myotube distributions did not present normality, and we performed Kuskal-Wallis test with Benjamin, Krieger and Yekutieti post hoc. Data are presented as mean, and statistical analyses were conducted using GraphPad Prism 8 software.
Acknowledgments: We are sincerely grateful to  Diego Ruano  ( Universidad de Sevilla, Spain ) and  Dr. Alejandro Vaquero  ( IDIBELL, Barcelona, Spain ) for gifting us the UB k48, s5α and H4K16Ac antibodies. The 2E-8 antibody was obtained from the  Developmental Studies Hybridoma Bank developed  under the auspices of the  NICHD  and maintained by the  University of Iowa, Department of Biology.
Clinical scoring Dogs were clinically scored using the grid developed and validated in the laboratory for GRMD dogs  [49]. Seven LRMD dogs (three females, four males) underwent iterative clinical scoring from weaning (2 months of age) and throughout their life. The clinical scores were compared to the values obtained from an age-matched male GRMD population encompassing 21 animals, and statistical significance was assessed by means of t tests. The dispersion of the data obtained for each population was evaluated by calculating the coefficients of variation. Seven LRMD dogs (three females, four males) underwent clinical scoring at an adult age (mean 23. 6 months, SD 12. 0 months); animals scored at adulthood included 5 out of the 7 animals scored from 2 months of age. The data were compared to the data obtained from eleven adult male GRMD dogs (mean 23.
LTBP4 SNPs analysis The Ensembl genome browser was used to identify known polymorphisms in the 30 coding exons of the canine latent transforming growth factor beta binding protein 4 (LTBP4) gene. Genotypes at these variant sites were called from the RNA-seq data from 5 LRMD dogs (LRMD 8, 9, 10, 12 and 13) using the Genome Analysis Toolkit (GATK, https://software. broadinstitute. org/gatk) best practices workflow for SNP and indel calling on RNA-seq data. The known sites in LTBP4 ENSC AFG00000005133 included 4 missense SNP variants (Ensembl Variant ID: rs851496729:p. Pro425Thr, rs8510 16279:p. Ser439Pro, rs853156464:p. Pro545Ala and rs2195 4920:pAla668Thr) and 7 synonymous SNP variants (Ensembl Variant ID: rs851354589, rs21999801, rs2195 4918, rs853084197, rs851625070, rs852260326 and rs850 783330); no novel coding variants were observed from the LRMD RNA-seq data.
Most human cases of DMD due to large mutations, predominantly deletions, preferentially affecting the major mutation hotspot spanning exons 45 to 55 or to a lesser extent the minor hotspot (exons 2-20)  [63]. Duplications also account for a significant number of the identified disease-causing mutations; exon 2 duplications are particularly frequent  [63, 64]. The GRMD mutation is a splice site point mutation and is therefore not a model for the large mutations that are frequent in DMD patients. Splice site mutations however account for 3% of the DMD referenced mutations. The LRMD mutation is a gross rearrangement, but it should be mentioned that inversions are a rare cause of human DMD. Querying the Leiden Duchenne muscular dystrophy database provided 8 inversion entries  [65]  and 5 supplementary inversion reports have been found in the literature  [66] [67] [68] [69] [70].
Acknowledgements We are very grateful to  Prof. Glenn E. Morris  and the CIND to have kindly provided the anti-dystrophin monoclonal antibodies. We thank  Dr. Robinot  for referring the first cases, and the breeder of the first dogs for his kind collaboration. We thank  Prof. Alain Fontbonne  and the whole team of the  CERCA (Centre d'étude en reproduction des carnivores d'Alfort)  for their precious help with the reproduction management of the LRMD colony and semen cryopreservation. We thank  Mireille Dubord ,  Bodovoahangy Andriatiana  and  Priscille Hertault  from the  CAAST  in the Alfort school of veterinary medicine for the biochemical analyses. We thank  Prof. Valérie Chetboul  and  Dr. Vassiliki Gouni , as well as the cardiology unit team of the Alfort school of veterinary medicine for the echocardiographic measures.
Statistical Analysis The obtained results were analyzed with the use of the STATISTICA 12. 0 PL software (StatSoft Inc. , Tulsa, OK, USA). The distribution of the studied concentrations did not follow the normal distribution (X 2 -test), thus nonparametric statistical analyses were applied. The Mann-Whitney test was used in order to compare two independent samples. The X 2 -test with Yates correction was used to investigate whether patients were gender-matched and whether there were differences regarding risk factors present between them. Correlation coefficients were obtained by applying Spearman's rank correlation. Values for continuous variables are presented as median with the 25th and 75th percentiles. For the variables CSF and serum chemokines concentration, chemokines Quotients, age, sex, and brain aneurysm risk factors, a logistic regression model was sought.