dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgments This material is based upon work supported by the  National Center for Atmospheric Research , which is a major facility sponsored by the  National Science Foundation  under Cooperative Agreement no. 1852977. Support by the  Centre of Excellence ESiWACE  is acknowledged. ESiWACE has received funding from the  European Union 's  Horizon 2020 research and innovation programme  under grant agreement numbers  675191  and  823988. The authors thank the  German Climate Computing Center  for hosting, providing access to and supporting the evaluation of the DYAMOND data sets. We acknowledge high-performance computing support from  Cheyenne  (doi: 10. 5065/D6RX99HX )provided by  NCAR's Computational and Information Systems Laboratory , sponsored by the  National Science Foundation. RS, MS, MN and CK were supported by the  FLAGSHIP2020  within the priority study 4 (Advancement of meteorological and global environmental predictions utilizing observational "Big Data") and the  Integrated Research Program for Advancing Climate Models (TOUGOU)  grant number  JPMXD0717935457  from the  Ministry of Education, Culture, Sports, Science, and Technology of Japan.
The NICAM simulation was performed on the Earth Simulator of the  Japan Agency for Marine-Earth Science and Technology. MR, PLV , and BV acknowledge funding from the  EU H2020   PRIMAVERA  project under grant agreement no. 641727. MK was supported by the  NSF  Grant  AGS1418309  to  Stony Brook University , and by the  NCAR-Wyoming Supercomputing Center , where the SAM simulation was performed. The authors would also like to thank  David Ahijvevych  for his assistance with the GFDL tracker, and  Daniel Stern ,  William Komaromi , and  Kevin Hodges  for valuable comments. The comments from two anonymous reviewers and three editorial members of this journal also helped in improving the manuscript.
(  4 ) to be small for the series to be convergent but, the three skew-spectra can also be used as independent estimators of non-Gaussianity and a method of effective data compression in their own right. This makes them attractive even when the series in Eq. (  7 ) is divergent at smaller angular scales. The convergence of the series expansion and its implications were considered in  (Petri et al. 2013 ) to some extent. However, a detailed study is needed for a realistic assessment as a function of various survey parameters. (ii) Skew-spectra from CMB maps: In The important difference of the CMB skew-spectra with the ones at lower redshifts is the significance of post-Born correction in modelling of non-Gaussianity. The post-Born correction is non-linear and it is known to generate a non-negligible bispectrum of the convergence  (Marozzi et al.
ACKNOWLEDGMENT DM is supported by a grant from the Leverhume Trust at MSSL. DM would like to thank Chiaki Hikage and Geraint Pratten for useful discussions during the initial phase of this project. DM would also like to thank the members of Euclid Forward Modelling Working group including Benjamin Wandelt, Adam Amara and Martin Kilbinger for critical comments. We would like to thank Peter Taylor for providing us his code to generate the Euclid type mask used in our study.
Source selection from AGN KSP As noted in the introduction, the CTA Consortium has prepared a program of KSPs, which are intended to cover ∼ 40 % of the available observing time in the first ten years of CTA operations. The KSP dedicated to AGN involves three different observing programs: the long-term monitoring program, the search for and follow-up of AGN flares, and a program devoted to establishing high-quality spectra of selected AGN, with a systematic coverage of redshift and AGN type. These observations will provide a rich database of VHE spectra that can be used to study the physics at play in the γ-ray sources and the effects of γ-ray absorption. While a detailed evaluation of the live time allocated to each KSP remains to be established upon commissioning of CTA, we propose in the following sub-sections (Secs.
Flare sample The AGN-flare program has been devised to search for and follow-up VHE flares from AGN, triggered either by external facilities or internally by the monitoring program performed with CTA. On the basis of the results of present-day facilities (mainly Fermi and Swift), about 25 alerts per year are expected, 10 -15 of which would be followed with CTA. The time budget proposed for the follow-up program of AGN flares is about 700 hours for the northern CTA site and 500 hours for the southern CTA site. We base the simulations on two different samples of observed elevated-flux states. The first sample, consisting of 14 AGN, exploits observations during flaring states by VHE groundbased instruments, as listed in Ref. [15]. Intrinsic spectra are derived, as for the long-term monitoring sample, by fitting a spectral model accounting for absorption on the EBL to the VHE data  [8].
For lower and higher masses, ALP-induced oscillations occur above and below the CTA energy range, respectively. Couplings g aγ > 6. 6 × 10 -11 GeV -1 are excluded by the CAST experiment  [160]  and observations of globular clusters  [161]. We do not expect the oscillations to be detectable for couplings smaller than the minimum value tested, since the median survival probability (median with respect to the magnetic-field realizations) alters the intrinsic spectrum by less than 1 % below 1 TeV. In order to minimize the computational time to scan the parameter space and magnetic-field configurations, we opt for the use of the Asimov data set  [162] , in which the observed number of counts is set equal to the number of expected counts. We checked that the results derived from an Asimov data set are representative of the mean results of Monte-Carlo realizations.
The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreements No 262053 and No 317446. This project is receiving funding from the European Union's Horizon 2020 research and innovation programs under agreement No 676134. The research leading to these results has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement GammaRayCascades No 843800.
Acknowledgments We gratefully acknowledge financial support from the following agencies and organizations:  State Committee of Science of Armenia, Armenia ;  The Australian Research Council ,  Astronomy Australia Ltd, The University of Adelaide, Australian National University, Monash University, The University of New South Wales, The University of Sydney, Western Sydney University, Australia ;  Federal Ministry of Education, Science and Research, and Innsbruck University, Austria ;  Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) ,  Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) ,  Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) ,  Ministry of Science, Technology, Innovations and Communications (MCTIC), Brasil ;  Ministry of Education and Science, National RI   Roadmap  Project  DO1-153/28.
Moreover, an interaction between a terminating ribosome and a specific messenger ribonucleoprotein (mRNP) structure localized 3 to the stop codon is required for proper termination  [44, [65] [66] [67]. The 'faux 3 -UTR' model also suggests that the proximity of the PAB1 to the PTC is essential for NMD activation  [31, 44, 68, 69]. [40]  with the poly(U) mRNA motif, constructed based on the pdb (protein data bank) id: 2wjv  [67]  and 2xzo  [37]. The crystal structure of UPF1 (pdb id: 2wjv  [67] ) is with the UPF2 protein, but since UPF1 adopts a different conformation when bound with UPF2, we removed it from the presentation. In addition, the poly(U) mRNA motif has been inserted into the structural representation (from pdb id: 2xzo  [37] ) as a reference since it is not present in the original crystal structure (pdb id: 2wjv  [67] ).
(b) Isoform_1 structure of the UPF1 (build considering the pdb id: 2wjv  [67] ) protein, with the 11 aa (amino acids) insertion (353-GNEDLVIIWLR-363) in the 'regulatory loop'. These 353-GNEDLVIIWLR-363 residues are highlighted over the protein structure in blue color. This UPF1 isoform_1 structure with inserting 11 aa was modeled considering the isoform_2 crystal structure as the template (pdb id: 2wjv)  [67]. (c) In the NMD pathway, recognition of PTC-containing mRNA transcript requires UPF1, UPF2, and UPF3 proteins as the core machinery, along with various suppressors with morphogenetic effect on genitalia (SMG) proteins  [7, 61]. There is a general agreement that NMD substrate recognition relies upon differences in mRNA ribonucleoprotein (mRNP) composition between normal mRNAs and PTC-containing mRNA transcripts.
Concerning the dynamics of NMD components, the binding of UPF2 with UPF1 causes a large conformational change in the UPF1 CH-domain (cysteine-histidine-rich domain), which triggers the UPF1 helicase activity. Furthermore, within the resulting decay-inducing complex (DECID), the SMG1 protein phosphorylates UPF1 that inhibits further translation termination initiation at the AUG codon  [56]. The UPF1 protein is a key component in the NMD pathway, also termed as the master regulator. Deletion of UPF1 in yeast not only stabilizes the nonsense-containing mRNAs but also enhances nonsense codon read-through as well and inhibits degradation of prematurely terminated polypeptides  [36, 37, 39, 46]. Moreover, the work by Chan et al. [70] has shown that deletion of UPF1 induces the production of (approximately6-to 8-fold   [40]  with the poly(U) mRNA motif, constructed based on the pdb (protein data bank) id: 2wjv  [67]  and 2xzo  [37].
The crystal structure of UPF1 (pdb id: 2wjv  [67] ) is with the UPF2 protein, but since UPF1 adopts a different conformation when bound with UPF2, we removed it from the presentation. In addition, the poly(U) mRNA motif has been inserted into the structural representation (from pdb id: 2xzo  [37] ) as a reference since it is not present in the original crystal structure (pdb id: 2wjv  [67] ). (b) Isoform_1 structure of the UPF1 (build considering the pdb id: 2wjv  [67] ) protein, with the 11 aa (amino acids) insertion (353-GNEDLVIIWLR-363) in the 'regulatory loop'. These 353-GNEDLVIIWLR-363 residues are highlighted over the protein structure in blue color. This UPF1 isoform_1 structure with inserting 11 aa was modeled considering the isoform_2 crystal structure as the template (pdb id: 2wjv)  [67].
GC-and AU-Rich mRNA Motifs Binding Pattern with UPF1 Isoforms PTC-containing mRNAs are rapidly degraded via the NMD pathway (Figure  1 ), and it has been proposed that UPF1 (the master regulator) is often associated with these mR-NAs  [74, 78]. In addition, the CLIP-Seq studies suggest that UPF1 binds mRNA rather non-specifically, but tends to accumulate in GC-rich motifs of 3 UTRs  [17] [18] [19]. Therefore, to investigate the binding pattern and selectivity of UPF1 with different mRNA motifs, we performed MD simulations on different GC-rich mRNA motifs with the UPF1protein, as well as made a comparative analysis with AU-rich sequences. For constructing different GC-and AU-rich mRNA motifs, model structures for the MD simulations with UPF1, the poly(U) mRNA (5 -UUUUUUU-3 ) from the X-ray structure with UPF1 (pdb id: 2xzo  [37] ), was considered as the template.
Materials and Methods Systems Build-Up for Different mRNA Motifs with UPF1 Different structures of UPF1 with ATP or mRNA are available in the Protein Data Bank database (pdb; http://www. rcsb. org/pdb; accessed on March 2021); however, the majority of them lack the CH domain, which is crucial for the proper functioning of the UPF1 protein. Therefore, in this study, we used the complete optimized UPF1structure (pdb id: 2wjv  [67] ) retrieved from our previous study  [40]. The UPF1 (pdb id: 2wjv  [67] ) is an isoform_2 crystal structure having 11 aa less (353-GNEDLVIIWLR-363) in the 'regulatory loop' compared with the isoform_1 (http://www. rcsb. org/pdb; accessed on March 2021). The UPF1 isoform_1 structure was modeled by considering the isoform_2 crystal structure as the template (pdb id: 2wjv  [67] ; Figure  1a, b ).
The missing amino acids in the tertiary structures of UPF1 in both isoforms were built using the Swiss model, as well as using the 'prepare protein' protocol implemented in the macromolecules module of the BIOVIA Discovery Studio Client v18. 1 (Dassault Systèmes, BIOVIA Corp. , San Diego, CA, USA) program  [41, 80]. Superimposing both UPF1 isoform modeled structures (build based on the pdb id: 2wjv  [67] ) with different structures available (UPF1 isoform_2 (pdb id: 2xzp  [37] ) and UPF1_isoform_1 (pdb id: 6ej5  [71] )) suggests a strong correlation between conformations (Figure  S1 ). The UPF1 crystal structure containing the CH domain (pdb id: 2wjv  [67] ) lacks the mRNA, and therefore, the position of the poly(U) mRNA motif was used from the pdb id: 2xzo X-ray structure (UPF1 without the CH domain)  [37].
Using the 'superimpose module' in BIOVIA Discovery Studio v18. 1 package, the position of poly(U) mRNA with both UPF1 isoforms was defined. The minimization of the modeled UPF1-poly(U) mRNA systems were performed using the 'smart minimizer' algorithm and applying the CHARMm (Chemistry at Harvard Macromolecular Mechanics) forcefield [81], with other parameters set as default in the BIOVIA Discovery Studio v18. 1 package. Systems for the MD simulations of UPF1 with GC-rich (5 -CCUGGGG-3 , 5 -CCUGGGA-3 , 5 -CCUGGAA-3 , and 5 -CCUGAGA-3 ) and AU-rich (5 -UUUUUUU-3 , 5 -UUAAUUU-3 , 5 -UUAGUUU-3 , and 5 -UUGAUUU-3 ) mRNA motifs were generated using the Molecular Operating Environment (MOE; Chemical Computing Group Inc. , Montreal, QC, Canada) package. A similar position as that of the poly(U) mRNA motif with UPF1 from the X-ray structure (pdb id: 2xzo)  [37]  was used for these GC/AU-rich mRNA-UPF1 systems.
Subsequently, the UPF1 protein with different mRNA motifs were optimized in the MOE package applying the CHARMM27 forcefield  [82]. The cancer mutations retrieved from the cancer genomics database cBioPortal  [79]  were inserted in the UPF1 structure using the MOE modules. Tertiary coordinates of mRNA as input parameters for the GRO-MACS 4. 6. 5 package  [83]  were retrieved using the CHARMM-GUI server  [84]. Applying CHARMM27 forcefield, the following 21 different protein-RNA systems were simulated using GROMACS 4. 6. 5  [85] : UPF1 isoform_1 apo-form and with poly(U) mRNA; UPF1 isoform_2 apo-form and with poly(U) mRNA; UPF1 isoform_1 and isoform_2 with GC-rich mRNA motifs (5 -CCUGGGG-3 , 5 -CCUGGGA-3 , 5 -CCUGGAA-3 , and 5 -CCUGAGA-3 ); UPF1 isoform_1 with AU-rich mRNA motifs (5 -UUAAUUU-3 , 5 -UUAGUUU-3 , and 5 -UUGAUUU-3 ) and the mutated UPF1 isoform_1 (A839T, P533L, or P533T) apoform and with poly(U) mRNA.
Figure1. The master regulator of the NMD (nonsense-mediated mRNA decay) pathway: UPF1 (UP-frameshift 1). (a) Optimized UPF1 isoform_2 model structure [40]  with the poly(U) mRNA motif, constructed based on the pdb (protein data bank) id: 2wjv [67]  and 2xzo [37]. The crystal structure of UPF1 (pdb id: 2wjv [67] ) is with the UPF2 protein, but since UPF1 adopts a different conformation when bound with UPF2, we removed it from the presentation. In addition, the poly(U) mRNA motif has been inserted into the structural representation (from pdb id: 2xzo [37] ) as a reference since it is not present in the original crystal structure (pdb id: 2wjv [67] ). (b) Isoform_1 structure of the UPF1 (build considering the pdb id: 2wjv [67] ) protein, with the 11 aa (amino acids) insertion (353-GNEDLVIIWLR-363) in the 'regulatory loop'.
These 353-GNEDLVIIWLR-363 residues are highlighted over the protein structure in blue color. This UPF1 isoform_1 structure with inserting 11 aa was modeled considering the isoform_2 crystal structure as the template (pdb id: 2wjv) [67]. (c) In the NMD pathway, recognition of PTC-containing mRNA transcript requires UPF1, UPF2, and UPF3 proteins as the core machinery, along with various suppressors with morphogenetic effect on genitalia (SMG) proteins [7, 61]. There is a general agreement that NMD substrate recognition relies upon differences in mRNA ribonucleoprotein (mRNP) composition between normal mRNAs and PTC-containing mRNA transcripts. In mammalian cells, an exon-exon junction complex (EJC) of proteins deposited at exon-exon boundaries during pre-mRNA splicing is considered to be a primary determinant of NMD [62].
RNA-seq analysis RNA was extracted using the Nucleospin RNA XS Micro kit from Macherey Nagel (Hoerdt). Libraries were prepared using the SMARTer ® Low Input RNA kit (Takara). All libraries were sequenced on an Illumina Hiseq2500 platform. Data normalization and differential gene expression were performed with the DESeq2 v1. 26. 0 R package. Significant genes were defined as P< 0. 05 after adjustment for multiple testing by False Discovery Rate (FDR) correction and used in downstream analysis. Principal Component Analysis was visualized using the Factoextra v1. 0. 7 R package. Gene Set Enrichment Analysis (GSEA version 4. 1. 0) was used for the analysis of DOHH2 and HLY1 gene expression profile (GEP) to identify the gene sets that were enriched between two conditions. Results were then compared to those obtained by comparing the GEP of purified FL B cells and purified centrocyte (Affymetrix ACCEPTED MANUSCRIPT -CLEAN COPY 10 microarrays, purified centrocytes, GSE136248, n=5; purified FL B cells, GSE85233, n=10)  26  after Limma analysis with a FDR of 5% and an absolute fold change>1.
ACKNOWLEDGMENTS This work was supported by  INSERM, University of Bordeaux, Ligue Régionale contre le Cancer  ( comités de Gironde, Charentes, Pyrénées, Landes ), the  Fondation ARC pour la Recherche sur le Cancer  (Grant  PGA1 RF20170205386 ), the  Institut National du cancer (INCA AAP   PNP-19-009 ),  Emergence GSO Cancéropole , and SIRIC BRIO. S. L. is supported by  Ligue Nationale contre le Cancer  and C. L. is a recipient of a doctoral fellowship from the  FHU CAMIn and LBB (Léa Broca-Brisson)  of a master fellowship from  CNRS GDR Imabio. J. S. V. is funded by the  Infrastructure eCellFrance  ( ANR-11-INSB-005 ). The 3D capsules were obtained from the  VoxCell Organoïds Plateform , a service of the  CNRS-INSERM and Bordeaux University -UMS TBMCore 3427. We thank  Stéphanie Durand-Panteix  for her technical support with transduction experiments.
We thank  Atika Zouine  and  Vincent Pitard  for technical assistance at the  Flow cytometry facility ,  CNRS UMS 3427 ,  INSERM US 005 ,  Univ. Bordeaux, F-33000 Bordeaux, France. We acknowledge the  Bordeaux Imaging Center , a service unit of the  CNRS-INSERM and Bordeaux University , member of the national infrastructure  France BioImaging  supported by the  French Research Agency  ( ANR-10-INBS-04 ). Cell sorting was performed at the  Biosit Flow Cytometry  and  Cell Sorting Facility CytomeTRI  ( UMS 6480 Biosit, Rennes, France ). High-throughput sequencing has been performed by the  ICGex NGS platform of the Institut Curie  supported by the grants  ANR-10-EQPX-03  ( Equipex ) and  ANR-10-INBS-09-08  ( France Génomique Consortium)  from the  ANR , by the  ITMO-CANCER , and by the  SiRIC-Curie program  ( SiRIC Grant INCa-DGOS-4654 ).
Background & Aims: Fibrosis is the strongest predictor for long-term clinical outcomes among patients with non-alcoholic fatty liver disease (NAFLD). There is growing interest in employing non-invasive methods for risk stratification based on prognosis. FIB-4, NFS and APRI are models commonly used for detecting fibrosis among NAFLD patients. We aimed to synthesize existing literature on the ability of these models in prognosticating NAFLD-related events. Methods: A sensitive search was conducted in two medical databases to retrieve studies evaluating the prognostic accuracy of FIB-4, NFS and APRI among NAFLD patients. Target events were change in fibrosis, liver-related event and mortality. Two reviewers independently performed reference screening, data extraction and quality assessment (QUAPAS tool).
| Inclusion and exclusion criteria We searched for studies published in peer-reviewed journals that had assessed the prognostic accuracy of at least one of the biomarkers of interest (FIB-4, NFS, APRI) in predicting future liver-related events, or changes in fibrosis stage at future biopsies. Publications in any language were eligible for inclusion. Studies that included adults (≥18 years) diagnosed (based on liver histology) or clinically suspected with NAFLD, and data on either FIB-4, NFS, or APRI were eligible. Studies in a mixed cohort of conditions (eg NAFLD and viral hepatitis patients) were only included if outcomes were separately reported for NAFLD patients. The target events of interest were the following: • worsening (or improvement) of fibrosis stage, evaluated preferably by using the NASH CRN score  14  and the EPoS staging system  15  for all stages of fibrosis or any dichotomized fibrosis status (eg F0-F2 vs F3-F4); • other liver-related outcomes of interest, including model of end stage liver disease (MELD) score ≥15; liver transplant; HCC; large oesophageal/gastric varices; ascites; increase in hepatic venous pressure gradient (HVPG) >10 mm Hg; histological progression to cirrhosis; hospitalization (as defined by a stay of ≥24 hours) for onset of: variceal bleed, hepatic encephalopathy, spontaneous bacterial peritonitis; • mortality (liver-related or all-cause).
| Data extraction and quality assessment The following data were extracted from each included study: study characteristics, clinical characteristics, index test features, target event features (if applicable) and overall performance of the test in terms of AUC or C index. Data were independently extracted and cross-checked by a second reviewer (JL and YV). The Quality Assessment of Prognostic Accuracy Studies (QUAPAS) tool was used to assess the methodological quality and risk of bias in the included studies. 16 In short, QUAPAS is a modification of the existing Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool, 17 revised to account for items unique to prognostic accuracy study designs. QUAPAS follows the same domain-based framework as QUADAS-2. Two independent reviewers (JL and YV) evaluated risk of bias and concerns for applicability using the five domains (participant recruitment, index test, target event, study flow, analysis), assigning each study with a judgement of 'low', 'high', or 'unclear' risk.
Here we explore a novel way of measuring β diversity in marine fish communities using environmental DNA and compare it to traditional visual long-term surveys. Environmental DNA (eDNA) is shed by aquatic organisms via many sources including fecal matter, mucus, or skin, forming a suspended biodiversity database. Sampling eDNA and sequencing it using high-throughput methods can reveal the presence of a wide spectrum of species without direct observations or sampling of whole organisms  [21] [22] [23] [24]. In aquatic ecosystems, eDNA metabarcoding of water samples may detect more species and avoid some sources of bias inherent to traditional surveys  [25] [26] [27] [28] [29]. While eDNA has been successfully used to capture regional diversity in a variety of systems  [25] [26] [27] [28] [29]  , recent studies have revealed that eDNA can also be used to describe spatial patterns of biodiversity and species composition at relatively fine scales (< 1 km) across natural marine landscapes  27, [29] [30] [31] [32] [33].