dataesr/scientific-paragraphs-categorization huggingface dataset:
ChIP-seq and ATAC -seq data mining Allelic and global mm9 alignments for H3K27ac in frontal cortex were obtained from the datasets GSM751461 and GSM751462. These alignments were converted into coverages using a R script. (rtracklayer, GenomicRanges) and were visualized on UCSC. ATAC-seq data for ES and ES derived neural progenitor cells were obtained from Geo DataSets GSE155215. Paired-end reads were treated with trim_galore (--paired) and then were aligned on the mm39 genome using bowtie2 (--very-sensitive -X 1000). Only proper paired alignments were conserved with samtools (view -f 2) and alignments on mitochondrial and random chromosomes were excluded. PCR duplicates were removed using picard-tools( MarkDuplicates --REMOVE_DUPLICATES=true). The coverage was produced using bamCoverage ( --normalizeUsing RPKM --binSize 20) and was visualized on UCSC genome browser.
Reanalysis of HI-C HI-C data were obtained from Geo DataSets under the accession numbers: for ES cells (GSM2533818, GSM2533819, GSM2533820, GSM2533821) and for in vivo NPC (GSM2533835, GSM2533836, GSM2533837, GSM2533838). These paired end reads were processed with HiC-Pro  (Servant N et al, Genome Biology (2015) , 16:259) with the following parameters (MIN_MAPQ = 20, REFERENCE_GENOME = mm39, GENOME_FRAGMENT = DpnII_resfrag_hg19. bed, LIGATION_SITE = GATC, BIN_SIZE = 5000). The produced normalized contact matrix (iced) was used to generate the contact map with the HiTC Bioconductor package.
, 2017) , until some transcript dependent cue stabilises one complex over another to commit RNA metabolism in a specific direction. Concerning binary interactions with the CBC, including results presented here, notably the identification of a conserved Trp binding pocket on CBP80, five distinct, nonoverlapping interaction sites on the CBC have now been identified (Figures  7A  and 7B ). These include: (1) the proximal CBP20-CBP80 interfacial groove binding site, where at least NELF-E and ARS2 bind, each with a RxxxxY motif, (2) the distal groove site, where Cterminal peptides ending in phenylalanine (…xDxF-Cter) were shown to bind for ARS2, NELF-E and PHAX; (3) the tryptophan-helix binding site on CBP80, where at least NELF-E, NCBP3, PHAX and ZC3H18 interact, each with a conserved tryptophan bound in the same CBP80 pocket irrespective of the directionality of the helix; (4) the peroxisome proliferatoractivated receptor-γ coactivator 1α (PGC-1α) binding site on CBP80 (PDB code: 6D0Y)  (Cho et al.
, 2018; Rambout et al. , 2023)  and (  5 ) the Transcription elongation regulator 1 (TCERG1) binding site, where, in the human pre-Bact-1 spliceosome structure (PDB code: 7ABG), one of the FF domains binds to CBP80  (Townsend et al. , 2020). Concerning binary interactions with ARS2, the ARM, or 'EDGEI' motif, which binds to the effector domain of ARS2, has now been shown to be functionally important for a number of effectors  (Dobrev et al. , 2021; Foucher et al. , 2022; Kiriyama et al. , 2009; Melko et al. , 2020; Polak et al. , 2023; Rouviere et al. , 2023; Schulze et al. , 2018). Here, we identify a non-canonical, but functional, ARM at the N-terminus of human PHAX. We also report quantitative in vitro measurements of the affinity to ARS2 of seven different single ARMs occurring in productive factors and four different double or triple tandem ARMs found in degradative factors, showing that the latter are generally tighter binders.
Cryo-EM Data Collection and Processing The CBC-m 7 GpppG-NCBP3 560-620 dataset was acquired using Titan Krios CM01 (ESRF, Grenoble, France)  (Kandiah et al. , 2019)  operating at 300 keV, equipped with K2 Quantum detector (Gatan) and a GIF Quantum energy filter (Gatan). The CBC-capRNA-PHAX and CBC-m 7 GTP-ARS2 147-871 datasets were acquired on the same microscope but equipped with a K3 Quantum detector camera (Gatan). For the CBC-m 7 GpppG-NCBP3 560-620 complex, 9629 movies were collected at 165K magnification, corresponding to a pixel size of 0. 827 px/Å for a total dose of 40 e-/A 2. For the CBC-capRNA-PHAX complex, 6517 movies were collected at 165K magnification, with a pixel size of 0. 84 px/Å and a total dose of 41. 7 e-/A 2. For the CBC-m 7 GTP-ARS2 147-871 , 12228 movies were collected at 165K magnification, with a pixel size of 0.
84 px/Å and a total dose of 40 e-/A 2. For all datasets, movies were imported into CryoSPARC  (Punjani et al. , 2017)  and aligned and dose-weighted using Patch MotionCorr. CTF estimation was performed with Patch CTF and micrographs were manually curated according to CTF based estimated resolution (<10Å) and estimated ice thickness (<1. 1). Particles were firstly picked on 100-200 representative micrographs using Blob Picker or Topaz  (Bepler et al. , 2019)  and then extracted with a box size of 300x300 pixels (NCBP3) or 256x256 (PHAX and ARS2 datasets) (Figure  S2 ). The best particles were then used to generate a Topaz model or to create Templates for particles picking in the remaining micrographs. After extraction, 2D classification was applied to eliminate bad particles and to select 2D class averages with lower background noise and stronger features.
Model building and refinement Models were iteratively constructed using COOT  (Emsley and Cowtan, 2004)  and PHENIX real-space refinement  (Afonine et al. , 2018)  starting with the published CBC-mGTP-ASR2 structure (PDB: 5OO6). Refinement and validation statistics, obtained using the PHENIX validation tool are reported in Table  S1. For the CBC-capRNA-PHAX and CBC-m 7 GTP-ARS2 147-871 , model building was guided partly by the AlphaFold model (Figure  S6 ), which correctly predicted the PHAX Trp118 helix and extreme C-terminus binding. There is no clear density for the capped RNA apart from the m 7 GTP although there is unassignable density near the cap-binding site that could be RNA or another part of PHAX. Additional extra, but disjointed density close to CBP20 Y142 and Y149 and between CBP20 Y50 and CBP80 Y461 (the conserved arginine binding site for ARS2 and NELF-E) could not be interpreted.
Acknowledgements SC and JK were funded by  ANR   MTREC  ( ANR-21-CE11-0021 ). THJ was supported by the  Danish National Research Council  and the  Novo Nordisk Foundation [ExoAdapt  Grant  31199 ]. IBS acknowledges integration into the  Interdisciplinary Research Institute of Grenoble (IRIG, CEA). This work used the platforms of the Grenoble Instruct-ERIC center (ISBG ; UAR 3518  CNRS-CEA-UGA-EMBL ) within the  Grenoble Partnership for Structural Biology (PSB ), supported by  FRISBI  ( ANR-10-INBS-0005-02 ) and  GRAL , financed within the  University Grenoble Alpes graduate school  ( Ecoles Universitaires de Recherche)   CBH - EUR-GS  ( ANR-17-EURE-0003 ). We thank  Caroline Mas  for assistance with  ITC  and  Jean-Baptiste Reiser  for his help and assistance with SPR and BLI. We thank  Sarah Schneider  and  Romain Linares  for support in using the EM Facility at  EMBL Grenoble.
Data collection Grids were loaded into a 300-kV Titan Krios transmission electron microscope (Thermo Fisher Scientific) equipped with a K3 direct electron detector and a post-column GIF BioQuantum energy filter (Gatan). Micrograph movies were typically collected using the EPU software (Thermo Fisher Scientific) at a nominal magnification of either 105000x with a pixel size of 0. 85 Å using a defocus range of -0. 8 to -2. 6 μm (TRANSCRIPTION-PRIMING and TRANSCRIPTION-PRIMING (in vitro) structures) or a nominal magnification of 130 000x with a pixel size of 0. 67 Å using a defocus range of -0. 8 to -2. 4 μm (TRANSCRIPTION-EARLY-ELONGATION structure). The samples were exposed to a total dose of 50 electrons/Å 2. Recorded movie frames were fractionated into 50 frames. A summary of the key data collection statistics for the dataset used to determine each cryo-EM structure is provided in Supplementary Table  2.
Image processing All movie frames were imported in RELION 4. 0 (42) and motion corrected using its own implementation of MotionCor2  (43). Particles were picked automatically using the pretrained BoxNet2Mask_20180918 model in Warp  (44). Calculation of contrast transfer function (CTF) estimation and correction was done in RELION 4. 0 with CTFFIND4  (45). Picked particles were extracted and processed in RELION 4. 0. First, particles were subjected to 2D classification at 4x binned pixel size. Then, all non-junk particles were used for 3D classification in an iterative manner using a 40 Å low pass filtered map of the apo SFTSV L protein (PDB: 6Y6K)  (18). Incomplete, low resolution or 3D classes containing damaged particles were excluded from further data analyses. The remaining particles were re-extracted with the original pixel size value for further 3D classification and refinement.
Model building, refinement and validation The recently published SFTSV EARLY-ELONGATION structure (PDB: 8AS7) was used as the starting point for modelling of the structures published in this study  (19). These initial models underwent iterative rounds of model building in Coot  (46)  followed by real-space refinement in Phenix  (47). The comprehensive validation tool in Phenix was then used to assess model quality  (47, 48). Coordinates and EM maps are deposited in the PDB and EMDB databases, as indicated in Supplementary Table  2. Figures displaying the molecules have been generated using a combination of CCP4mg  (49) , Pymol (Schrödinger), and UCSF ChimeraX  (50).
DATA AVAILABILITY Coordinates and maps included in this paper have been deposited in the Worldwide Protein Data Bank (wwPDB) and the Electron Microscopy Data Bank (EMDB) with the following accession codes: SFTSV L protein in a transcription priming state with CBD bound to capped-RNA [TRANSCRIPTION-PRIMING] EMD-18967 PDB-8R6W; SFTSV L protein captured at early elongation following capped-primer incorporation [TRANSCRIPTION-EARLY-ELONGATION] EMD-18969 PDB-8R7Y; SFTSV L protein in a state reflecting cap-independent transcription priming [TRANSCRIPTION-PRIMING (in vitro)] EMD-18963 PDB-8R6U.
ACKNOWLEDGEMENTS We want to thank  Stephan Günther  for his support and helpful discussions throughout the project. We acknowledge support by  Carolin Seuring ,  Cornelia Cazey  and  Ulrike Laugks  for access to the CryoEM multi-user Facility at CSSB and providing time for sample preparation, screening, and data collection;  Wolfgang Lugmayr  for help and support in using the CSSB partition on the DESY computer cluster for cryo-EM data processing. We also want to thank  Lennart Sänger  for feedback on the manuscript. Finally, we thank the  Wilhelm und Maria Kirmser-Stiftung  for support.
In this paper, we derive exact expressions, as well as recurrence relations, for single and product moments of order statistics (OSs) and record values of the Topp-Leone Lomax (TLLo) distribution proposed by Oguntunde et al. [29] (Wireless Personal Comm. , 109,  349-360, 2019). Moreover, we study the L-moments of this distribution. Also, we estimate the parameters of the TLLo distribution through the L-moments and compare to other models. We fit flood level data to the TLLo distribution because Okorie and Nadarajah [30] (Wireless Personal Comm. , 115, 589-596, 2020)  have shown that the TLLo distribution may be used to model datasets other than airborne communication transceiver data used by Oguntunde et al. [29]. Finally, we reveal a relationship between the entropy and the upper and lower record values, as well as OSs.
( 2 ) The relation between the pdf and df can be seen as f T LLo (x) = 2 α β (1 + x) 2 β+1 [1 -(1 + x) -2 β ] F T LLo (x). (3) The Lomax, exponentiated Pareto, and standard Pareto distributions are special cases of the TLLo distribution at the different values of the parameters. Oguntunde et al. [29]  explored some particular properties of the TLLo distribution with considering the estimation issue of the model parameters, while Okorie and Nadarajah  [30]  have demonstrated that the TLLo distribution may be used to simulate datasets other than one utilised by Oguntunde et al. [29]. The earlier limitations of  [29]  motivate us to explore further properties for the TLLo distribution with fitting it to flood data. Due to several applications of the OSs and the record values, as stated below, we derive the exact expressions for the moments of OSs and record values that which show the charateristic of the TLLo distribution and find the information theory as entropy measure of OSs and record values.
Patients, sample qualification and molecular analysis The study was conducted at Centre Léon Bérard, was approved on 2/2/2018 by the institutional review board, and was conducted in compliance with the Declaration of Helsinki and Good Clinical Practice guidelines. We retrospectively selected 50 patients among the 2,579 patients included in the previously reported PROFILER molecular screening program (NCT01774409) who had no MBTR based on the TGP/aCGH during the course of the trial and for whom a fresh frozen tumor mirroring the FFPE sample together with germ line DNA were available in Centre Léon Bérard certified Biobank (BB-0033-00050)  [7]. Fresh frozen surgically resected tumor specimens mirroring the FFPE sample were evaluated by an experienced pathologist for tumor cell content ≥ 30% was required.
Discussion Molecular analysis by WES/RNA-Seq is now available in routine for diagnosis and theranostic purposes to increase the rate of MBTR for patients with advanced cancer. To our knowledge, this is the first report comparing the percentage of candidate patients for a MBTR using both TGP/aCGH and WES/RNA-Seq available in all patients. As expected, WES/RNA-Seq led to the identification of more molecular alterations but most were not used for MBTR in the absence of documented clinical significance. However, a numerically higher rate of MBTR was recommended compared to TGP/aCGH. The translation of these recommendations into clinical benefit for the patients remains to be determined. The prospective randomized trial PROFILER02 trial (NCT03163732) has been completed and compares the value of a narrow-vs.
This work was supported by funding from the  Integrated Cancer Research Site LYriCAN  ( INCa-DGOS-Inserm_12563 ),  NetSARC (INCA & DGOS) ,  InterSARC (INCA) ,  LabEx DEvweCAN  ( ANR-10-LABX 0061 ),  PIA Institut Convergence Francois Rabelais PLAsCAN  (PLASCAN,  17-CONV-0002 ),  Fondation ARC contre le Cancer, La Ligue contre le Cancer (Canopée) , and  EURACAN  ( EC 739521 ).
Example Figure  1  illustrates our procedure using a dataset from the CATALYST package as an example. There are four markers, HLA-DR (Yb171Di), HLA-ABC (Yb172Di), CD8 (Yb174Di), and CD45 (Yb176Di), that spill over into the target marker, CD3 (Yb173Di). The markers have two names: the first name is the protein name and the second name in brackets is the conjugated metal. There are bead experiments for each of the spillover markers. Panel A depicts the marker distributions from the beads experiment. We see that for this marker the bead experiments are high-quality as the target marker Yb173Di is concentrated around six, similarly to the experiment with real cells. This suggests that the spillover marker values can be transferred to the real experiments. Marker Yb172Di shows large spillover into Yb173Di, and suggests that the left tail of the first mode of the distribution may be attributed to that marker.
Real Data We compare our method to CATALYST on one of the example datasets in the CATALYST package. The dataset has an experiment with real cells and a corresponding bead experiment. The experiment on real cells has   (Bendall et al. , 2011). 5,000 peripheral blood mononuclear cells from healthy donors measured on 39 channels. The experiment on beads has 10,000 cells measured on 36 channels. They have single stained bead experiments. The number of beads per metal label range from 112 to 241. We compare the two methods on the same markers as in the original CATALYST paper  (Chevrier et al. , 2018)  in their Figure  3B. In the original experiment, they conjugated three proteins-CD3, CD8, and HLA-DR-with two different metal labels. They conjugated CD8 (first row in Figure  3 ) with Yb174Di (Yb is the metal and 174 is the number of neutrons of the isotope) and La139Di, and similarly for the other rows.
Acknowledgments We thank  EuroBioC2022  for awarding  Marco Guazzini  a travel award to present a preliminary version of spillR in Heidelberg. We thank  Antoine Chambaz  for his feedback on an earlier draft that substantially improved the paper. Alexander G. Reisach  received funding from the  European Union 's  Horizon 2020 research and innovation program  under the  Marie Skłodowska-Curie  grant agreement No  945332.
Search Strategy An experienced medical librarian (DAD) implemented a comprehensive literature search to identify English language papers on the influence of the design of RSA on axial rotation published between January 2010 and December 2019. To locate relevant studies, we queried PubMed, Embase, Scopus, the Web of Science, and the Cochrane Database of Systematic Reviews. Search terms included a combination of keywords and subject headings including "primary RSA, " "reverse shoulder arthroplasty, " "prosthetic, " "reverse shoulder replacement, " "cuff tear arthropathy, " "design, " "axial rotation, " "range of motion, " and "prosthesis" (see the Supplementary Material 1 or database-specific search strategies). In addition to limiting the results to English, they were limited to adults and the following publication types: randomized controlled trials, controlled clinical trials, clinical trials, evaluation studies, case-control studies, cohort studies, longitudinal studies, prospective studies, retrospective studies, follow-up studies, comparative studies, systematic reviews, and meta-analyses (Supplementary Material 1 for database-specific search strategies).
The MNIR has been previously reported to be 79° or the L3 vertebral level  [7, 47]. Meta-analysis was performed to compare the postoperative ER and pre-to  postoperative improvement in ER based on global implant design (lateralized vs. medialized) and further stratified based on management of the subscapularis (repair with any method versus no repair). We anticipated that the design of the included studies and methodology involved in data collection would result in substantial heterogeneity; thus, we elected to use a random-effects model a priori  [48]. The I 2 statistic was used to assess the heterogeneity of results. The true effect size in 95% of the population (95% prediction interval) was calculated using the variance of true effects (T2) and the standard deviation of true effects (T).
Future studies are needed to evaluate whether lateralized RSA without subscapularis repair provides optimal ER while maintaining a low rate of postoperative instability. Although at least 2 years of clinical follow-up was required, included studies had varying follow-up periods. Furthermore, publication bias is a potential limitation (Fig. 6 ). The assessment of ER was not uniform: 11 studies assessed ER with the shoulder adducted at the side, one study assessed ER at 90° of abduction, and the remainder of the studies did not specify the position of the arm. We were also unable to meaningfully analyze IR due to substantial heterogeneity in reporting; this is a known limitation that has previously been reported and remains controversial  [46]. Moreover, in our attempt to capture all relevant articles, we queried commonly used databases with broad search terms; however, despite these efforts, relevant articles may have been missed.
5, 6  Using an incorrectly classified variant for family cascade testing and the delivery of screening, treatment, or reproductive choices can have severe adverse consequences. Historically, disease genes were identified by linkage studies in large families,  7  often using polymorphic markers in close proximity to the gene responsible for the disease. Subsequently, candidate gene studies based on known or hypothesized disease mechanisms became commonplace. 8  Until as recently as 10 years ago, it was not fully appreciated that individually rare genetic variants are collectively extremely common. Exome sequencing typically yields 200 rare (gnomAD allele frequency <0. 1%) and a mean of 27 ± 13 novel (not present in population databases, number varies by ancestry) coding variants. 9  Many studies reported new gene-disease associations without adequately controlling for background genetic variation in the population: inadequately small control cohorts, often just 100 chromosomes, were used for assessment of novel disease genes and variants, and consequently both the literature and disease databases were flooded with assertions of gene-disease relationships and variant pathogenicity that have not proven robust over time.
[10] [11] [12]  Recent years have seen concerted efforts to correct this bias, using large, publicly available population databases, such as ExAC and later gnomAD,  13, 14  as control cohorts, and applying standardized approaches to reinterpret evidence for gene-disease relationships  5  and variant pathogenicity  2  Many groups are invested in curation of disease-gene validity, including academic and health care centers, private companies, and consortia. The Gene Curation Coalition (GenCC) is a coalition aiming to harmonize approaches among these entities to ensure gene-level curated resources are comparable and interoperable and to provide access to structured representations of consensus data. As a first undertaking, the GenCC developed a consensus term set for grading gene-disease validity and developed a unified database to display curated gene-disease validity assertions from its members (the Clinical Genome Resource [ClinGen], DECIPHER, Gene2Phenotype [G2P], Transforming Genetic Medicine Initiative, MedlinePlus Genetics, Genomics England PanelApp [PanelApp], PanelApp Australia, Online Mendelian Inheritance in Man [OMIM], Orphanet, Ambry Genetic, Illumina, Invitae, Mass General Brigham Laboratory for Molecular Medicine, Myriad Women's Health, HUGO Gene Nomenclature Committee, Franklin by Genoox, King Faisal Specialist Hospital and Research Center, and PharmGKB).
This database can be likened to a "ClinVar for genes" in that members can submit assertions of disease association but in this case for genes, not variants. The GenCC database provides a single route of access to comprehensive aggregated assertions (https:// search. thegencc. org)  15  and currently contains over 16,911 gene-disease assertions on 4704 unique genes from 12 submitters. OMIM will connect its large dataset to the GenCC in real time via a submission API being launched soon. Resolution of gene-disease validity discrepancy across GenCC submitters is ongoing using a manual review process. As the next step to facilitate harmonized gene-disease validity assessments and support variant classification within the ACMG/AMP framework, the GenCC has focused on developing standardized terminology for the characterization of disease mode of inheritance, allelic requirement, and disease-associated variant consequences.
Pilot curation working group A working group of clinical geneticists with experience in the identification and evaluation of variants in both the clinical and research settings was formed to pilot curation of the 59 genes (66 disease-gene pairs) included in the ACMG Recommendations for Reporting of Incidental Findings in Clinical Exome and Genome Sequencing version 2. 0  23  (current at the time of study) using the new terminology and variant consequence matrix. The templates supplied to curators in the pilot working group are available in Supplemental Information 1 & 2, and the final outputs are available online (github. com/ImperialCardioGenetics/ ACMGSF_pilot_curation/).