dataesr/scientific-paragraphs-categorization huggingface dataset:
We estimated parameters between the two Cape Verde islands and between CVI and Morocco using four demographic models. For each model and population pair, we conducted the analysis 1000 times with up to 50 iterations to infer confidence intervals. We used three complementary approaches to model the demographic history within the archipelago including the timing of colonization and severity of the associated bottlenecks. First, we RELATE  34  and COLATE  36  under a haploid model using the module 'EstimatePopulationSize' to reconstruct N e over time based on inferred coalescence events within each island population. In addition, we fit a model to the data using forward-in-time, individual-based simulations from Slim3  21. We also conducted inference based on phylogenetic analysis of the nonrecombining chloroplast locus to check for agreement at this locus.
Niche modelling. We performed niche modeling in Maxent  37  based on the bioclimatic variables described in Supplementary Table  1. We used standard default parameters with jackknife resampling to estimate the importance of each variable on the model. We built a model to predict the suitability across the Cape Verde archipelago for colonization by A. thaliana from the Moroccan range, and to identify the regions within Cape Verde that are most similar to the Moroccan habitat (Supplementary Method 9). Testing for evidence of adaptive evolution. We used custom scripts (https:// github. com/HancockLab/CVI) to compute the d sel /d neu ratio, defined as the rate ratio of 0-fold nonsynonymous to 4-fold synonymous substitutions, scaled by the number of sites at risk for each category. Genome-wide, after discounting sites with more than 5% missing data, the number of sites at risk for 0-fold and 4-fold mutations were respectively 5967270 and 1332660.
Trait mapping. We conducted genome-wide association analysis (GWAS) using a univariate linear mixed model while accounting for population structure with a mean-centred kinship matrix <-gk 1> using the flag <-lmm 4> in GEMMA  99. Input files for this analysis were generated on GATK genotypes, which included indel calls, using VCFtools 107 and PLINK  104. Mapping was conducted based on the median phenotype across replicates per genotype (https://github. com/ HancockLab), since no block effect was detected across the chamber (Supplementary Method 12). For bulked segregant analysis, we propagated an inter-island F2 population (S5-10 x F13-8, n = 488), in which the ancestral allele FRI K232 was fixed), under simulated CVI conditions. Because early flowering segregated at an approximately 1:3 ratio (indicating a single recessive locus), we sampled leaf tissue from the 25% early tail of the F2 (n = 108).
We extracted DNA using a DNeasy Plant Mini kit (Qiagen), assessed DNA quality and quantity with Qubit and Nanodrop (Thermo Fisher Scientific), prepared a single library using NEBNext Ultra II FS DNA Library Prep Kit (New England Biolabs) and sequenced it to 50x coverage using the Illumina HiSeq3000 platform. We called variants against the TAIR10 reference assembly using a GATK pipeline  108  (https://github. com/HancockLab/CVI), retaining only biallelic variants. We identified window(s) where the median allele frequency dispersion was greater than 95% and annotated variants within candidate region(s) using SnpEff v. 3. 0  109. These are listed in Supplementary Data 6. Functional validation. We measured FLC expression in a representative set of eight Cape Verdean and six Moroccan lines as well as in the Col-0 reference line, a modified Col-0 with a functional FRI introgressed (Col-0 FRI-Sf2, shown as Col-0 FRI + FLC + ), since FRI affects FLC mRNA levels  71, 72  , and Col-0 FRI-Sf2 with an FLC knock-out (Col-0 FRI-Sf2 flc-3, shown as Col-0 FRI + FLC -)  61.
From these, we calculated the proportion of runs where populations adapted, the proportions of potentially adaptive variants that are lost or fixed in all runs, and the times to fixation or loss. Statistical analyses. For the comparison of climate variable distributions in Morocco and CVI, differences in the distributions were evaluated using two-tail Wilcoxon rank sum tests/Mann-Whitney U tests (hereafter MWW test) with the wilcox. test() function in R (https://github. com/HancockLab/CVI). We computed the d sel /d neu ratio and the distribution of fitness effects (DFE) with polyDfe v. 2. 0  109  for the two CVI island populations and Morocco. To estimate uncertainty around these parameters, we bootstrapped frequency spectra 500 times with polyDfe and calculated an empirical p-value for the d sel /d neu ratio and the discretized DFE categories based on the bootstrapped data.
The large variance in the bootstrapped data stems from the low number of variants segregating in CVI. To assess fitness effects, we tested deme, habitat and deme x habitat interaction effects of Moroccan and CVI lines in the CVI and Moroccan-simulated environments. To correct for overdispersion, we employed a negative binomial transformation using the glm. nb() function from the package MASS v. 7. 3-51. 4 in R (https://github. com/HancockLab/CVI). To compute the proportion of private variants we counted the mutations that distinguish Cvi-0 from Ler-0 and calculated the proportion which are private to Santo Antão and segregating there. This calculation was repeated for the whole genome, QTL and candidate genes. Because functional variants represent single mutations, in this case each variant was either fixed in CVI and denoted with 0% private, or segregating in Santo Antão and denoted with 100% private.
1>) and conducted stepwise regression on each of these sets, exactly as we had done on the seven functional variants. We obtained an empirical p-value by comparing the observed R 2 to the resampled null distribution (https://github. com/HancockLab). We tested for differences in the distributions of bolting time between CVI and Moroccan populations using two-tail MWW tests on the medians per genotype with the wilcox. test() function in R (https://github. com/HancockLab/CVI). 95% confidence intervals were calculated using function ci() implemented in the R package gmodels v. 2. 18. 1  115. To determine whether there was transgressive segregation in inter-island crosses, we tested each F2 population against their corresponding parental lines. Each parental line was grown in 12 replicates, except for Cvi-0 and F9-2 (4 replicates per lines), and the F2s had 488, 598, and 636, respectively for the crosses S5-10 x F13-8, Cvi-0 x F9-2, and S15-3 x F3-2.
We used Dunnett's tests on each individual cross, using the DunnettTest function implemented in the R package DescTools 110 (https://github. com/HancockLab), and a Fisher's combined p-value test on the set of crosses, using the function fisher. method implemented in the R package metaseqR 111 (https://github. com/HancockLab). We conducted genome-wide association studies (GWAS) using likelihood ratio tests in GEMMA  112  to test associations between markers and the median bolting time per natural line. Manhattan plots show p-values -log 10 transformed on the y-axis. We tested the difference in FLC expression and bolting time between genotypes with the Kruskal-Wallis method implemented in the R package agricolae (https:// github. com/HancockLab). We applied the 2 -ΔΔCt (Applied Biosystems) on the median across three technical replicates per genotype.
For the FLC complementation test, we tested phenotypic complementation of F1 hybrids by their phenotypic distributions to parental lines using the wilcox. test() function implemented in R (https://github. com/HancockLab), on four replicates of each of the parental lines and eight replicates of each F1 line. We tested for phenotypic complementation of Col-0 background F1 hybrids by comparing their phenotypic distribution to Col-0 FRI-Sf2 flc-3 (FRI + FLC -) and Col-0 FRI-Sf2 (FRI + FLC + ) using the wilcox. test() function implemented in R (https://github. com/HancockLab/CVI).
Acknowledgements The authors thank  Martin Koornneef ,  Nick Barton ,  Christian Brochmann , and  George Coupland  for valuable discussions and comments, and we thank  Wolfram Lobin  for sharing herbarium records. Logistical support in the field, field assistance and advice were provided by  Natural Parks in Santo Antaõ and Fogo ,  A ̂. Moreno  and  S. Gomes  at the  Instituto Nacional de Investigacaõ e Desenvolvimento Agraŕio (INIDA) ,  Cape Verde , and  Arlindo Martins. The project was supported by the  Marie Curie CIG 304301, Vienna International Postdoctoral Program for Molecular Life Sciences (VIPS) ,  NSF   IRFP  ( 1064766 ),  Max Planck Society Funding , and  ERC   CVI_ADAPT 638810  to A. M. H. , FWF DK  W1225-B20  (A. F. ),  Laboratoire d'Excellence (LABEX)  entitled  TULIP  ( ANR-10-LABX-41 ) to F.
Data availability All data generated in this study are included in this article and its Supplementary Information files. The raw sequencing read data generated in this study have been deposited in the European Nucleotide Archive (ENA) under accession code PRJEB39079. In addition, previously published sequence data were used from ENA project ID PRJEB24044 and ENA project ID PRJNA273563. All sequences were aligned against the Arabidopsis TAIR reference assembly GCA_000001735. 1. The genomic variant calls have been deposited in the European Variation Archive (EVA), under project accession number PRJEB44201. Source data are provided with this paper.
We focused on four main topics, including: (1) indications and patient selection methods; (2) reimbursement; (3) clinical and pre-clinical on-going or planned studies; and (4) the number of patients treated with PT per year. The questionnaire was developed as a web-based application within a free software tool: Google forms (https://www. google. com/forms). Eight links were provided for each tumour site separately, to enable the survey to be completed by different personnel from a centre. Using this web-based system, participants could enter data or select appropriate answers from a list of predefined answers. The questionnaire was first evaluated by colleagues with expertise in radiotherapy of a given tumour site and based on their comments, adjustments were made accordingly before distributing the questionnaires across the PT centres.
In June 2020, the first electronic invitation was sent to all 22 European PT centres in thirteen different countries. Centres treating intra-ocular tumours only were not included into the study. First and second reminders were sent in September 2020 and January 2021, respectively. The survey was closed in March 2021. Number of patients treated with PT in 2020 were obtained from participating centres in June 2021. Collected data were evaluated per centre and statistics were performed for all centres together.
Discussion The survey presented in this paper revealed various policies and methods for the application of PT in adult patients across European centres. Of the 22 centres invited, 19 (86%) completed the survey. In addition, each of the 13 countries that provide PT was represented by at least one centre. To our knowledge, there is no study comparing the patients' access to PT in Europe and other part of the world. However, a rough estimation can be obtained about it, using the data regarding the number of patients treated with PT annually, which was provided by several PT centres to the PTCOG central database. Based on that, including both adult and paediatric patients, a total of 22,012 patients were treated in 92 PT centres worldwide during 2020. Fifty-eight percent of these patients were treated in PT centres located in North America, 33% in Europe and 9% in Asia  [19].
The model-based approach has been adopted in the Netherlands, Denmark, France, Germany, Italy, and Spain for a number of tumour sites including GI, breast and HNC. Furthermore, a web-based software tool, ReCompare (REmote COMparison of PAR-ticlE and photon treatment plans), was developed by researchers from Germany to facilitate remote treatment plan exchange between photon and PT centres for comparison and patient selection  [33]. In addition, in a recent report from the PT Clinical Trial Strategy Group of the United Kingdom, it was promoted to design and participate in PT clinical trials, to advance quality assurance, methodology, interpretation of the results and the consistency of reporting of clinical trials for PT  [34]. A notable finding of the current study was that reimbursement was provided by national health care systems for the majority of commonly treated tumour sites.
Acknowledgements The work described in this paper has been funded by the  European Union  (Project number: 730983: INSPIRE-project). We would like to thank to  Liesbeth Boersma ,  Karen Kirkby ,  Ta Bastiaan ,  Loïc Feuvret ,  Jeroen Buijsen ,  Judith van Loon ,  Kenneth Jensen ,  CJS Kronborg ,  Michiel Kroesen ,  Stefan Hutschemaekers ,  Hanna Mortenson ,  Yvonne Klaver ,  Myra Rodrigues ,  Ben Vanneste  and  Rita Engenhart-Cabillic  for their contributions to this study.
ANIPHI was developed in collaboration with Decision Eyes, a Portuguese Start-up responsible for the development of WELPHI, a software solution on top of which ANIPHI was developed (for further information, see http://www. welphi. com/). Decision Eyes will keep assisting the authors in maintaining the database, fixing bugs, and modifying the platform if needed. Educators using ANIPHI can analyze, delete and export data collected in all rounds. All the information collected is stored following WELPHI's Privacy Policy which can be found at https://app. welphi. com/welphi/TermsAndConditions/Anicare/TermsEN. pdf. The platform is available in the English, French, Portuguese and Spanish languages at http://app. welphi. com/ welphidev/Pages/LoginPage. aspx. In the next section, we present the ANIPHI platform architecture organization so that educators can understand how to implement the ANIPHI design and provide user interface guidance on how to use the platform to support SAQ-like debates.
The ANIPHI platform architecture organization The ANIPHI platform is a free-to-use web-based application developed using the. NET framework connected to an SQL Server 2014 database and accessible through the Internet. In terms of its architecture, ANIPHI is organized into 14 pages: (1) create login, (2) process overview, (3) round details management (round 1 and 4), (4) round details management (round 2 and 3), (5) process details management, (6) edit and manage round 1 info,  (7)  edit and manage round 2 and 3 info, (8) edit and manage round 4 info, (9) edit messages,  (10)  add and manage proposals/arguments, (11) add and manage participants,  (12)  add and manage scale level,  (13)  proposals/arguments statistics, and (  14 ) participants statistics. In this section, we will present screenshots of ANIPHI to illustrate the platform architecture organization: selected screenshots reference the case study presented in the next section.
Acknowledgments The authors would like to thank  WELPHI Decision Eyes , namely  João Bana e Costa  and  Fabio Martins , for all the knowledge and support provided during the development of the ANIPHI platform. The authors would also like to thank all the ANICARE researchers for stimulating and continuous discussions around the development of the  ANIPHI platform. Namely, Dantas, M. (Coopalima, Portugal), Martins, E. (EUVG, Portugal ), Salgado,  M. ( Instituto Superior Tecnico, Universidade de Lisboa ), Magalhães-Sant'Ana M. and Stilwell, G. (CIISA-FMV-UL), Facorro, J. G. and  Leis, R. (Federacion EFA Galicia, Spain) ,  Girard , B. and Raballand,  N. ( EPLEFPA de La Cote Saint Andre, France ), Lanssens, M. and  Bredow, F. (Montpellier SupAgro, France) ,  Ilmonen ,  J (Omppu Tonttu Luomutila , Finland).
We acknowledge the financial support from The  National Agency Erasmus+ France/ E ´ducation Formation (Bordeaux)  under grant number:  ANICARE n˚2017-1-FR01-KA202-037287. A. C. L. V. and M. D. O. received support from  CEG-IST, FCT -Foundation for Science and Technology, I. P. , under the project  UIDB/00097 / the ANICARE consortium have already successfully tested the ANIPHI platform for different farm animal welfare topics. life educational context, where we discuss some aspects of the design and use of our pedagogical platform. 2020. A. C. L. V. work was also supported by the  MEDI-VALUE  project supported by the  Portuguese Foundation for Science and Technology  (Grant no. PTDC/EGE-OGE/29699/2017 ) where the use of the Delphi method is explored within collaborative decision-making processes.
67 e then designed a series of derivatives (Figure  3 ) incorporating the 4-hydroxy-2-naphthoic group bridged by an amide or urea group with an arginine surrogate (arginine mimetic moiety). The effect of the introduction of a methionine was also explored. The compounds (5-11, Table  1 ) were synthesized and, at first, analyzed for known classes of assay interference compounds. 68 All derivatives were not recognized as PAINS according to the SwissADME web tool (http://www. swissadme. ch),  69 the Free ADME-Tox Filtering Tool (FAF-Drugs4) program (http://fafdrugs4. mti. univ-paris-diderot. fr/ ),  70  and the "False Positive Remover" software (http://www. cbligand. org/PAINS/)  71 nor as aggregators according to the software "Aggregator Advisor" (http://advisor. bkslab. org/). 72 hen, we resolved to determine their effect on the catalytic activity of human recombinant PRMT1, chosen as representative of class I PRMTs.
After an incubation of 60 min, 10 μL of streptavidin donor beads (PerkinElmer, #6760002) diluted in Epigenetic Buffer 1X was added in each well (final concentration, 20 μg/mL). After an incubation of 30 min, signals were read in Alpha mode with a PerkinElmer EnSight multimode microplate reader (excitation at 680 nm and emission at 615 nm). For each incubation step, the OptiPlate was sealed with protective foil to prevent evaporation and contamination. Donor and acceptor beads were added in subdued light. The 100% activity (positive control) was reached using the vehicle (DMSO) while the 0% activity (negative control) was obtained without the protein. Data were analyzed using Excel software. Values obtained for each compound are mean ± SD determined for three separate experiments. Radioisotope-Based IC 50 Profiling against PRMTs.
The effects of compounds 12a-12h on the catalytic activity of PRMT1, PRMT3, PRMT4, PRMT5, PRMT6, PRMT7, and PRMT8 were determined with a HotSpot PRMT activity assay by Reaction Biology Corporation (Malvern, PA) according to the company's standard operating procedure. 119, 120 Briefly, the full-length human recombinant proteins PRMT1 (residues 2-371, C-terminus; with an N-terminal GST-tag; MW = 68. 3 kDa; Genbank Accession # NM_001536) or PRMT3 (residues 2-531, C-terminus; with an N-terminal His-tag; MW = 62. 0 kDa; Genbank Accession # NM_005788), or PRMT4 (residues 2-608, C-terminus; with an N-terminal GST-tag; MW = 91. 7 kDa; Genbank Accession # NM_199141), or PRMT5/MEP50 complex  121, 122  (residues PRMT5 2-637, C-terminus, and MEP50 2-342, C-terminus; with an N-terminal FLAG-tag, PRMT5, or His-tag, MEP50; MW = 73.
7/39. 9 kDa; Genbank Accession #NM_006109, #NM_006109), or PRMT6 (residues 2-375, C-terminus; with an Nterminal GST-tag; MW = 67. 8 kDa; Genbank Accession # NM_018137), or PRMT7 (residues 2-692, C-terminus; with an Nterminal His-tag; MW = 81. 7 kDa; Genbank Accession # NM_019023), or ΔN(1-60)-PRMT8  123  (residues 61-394, Cterminus; with C-and N-terminal His-tags; MW = 43. 2 kDa; Genbank Accession # NM_019854) were added to a solution of the proper substrate (histone H4 for PRMT1, PRMT3, and PRMT8; histone H3. 3 for PRMT4; histone H2A for PRMT5/MEP50; GST-GAR for PRMT6 and PRMT7; final concentration 5 μM) in freshly prepared reaction buffer (50 mM Tris-HCl (pH 8. 5), 5 mM MgCl 2 , 50 mM NaCl, 1 mM DTT, 1 mM PMSF, 1% DMSO) and gently mixed. The proper solution of compounds 12a-12h in DMSO was delivered into the PRMT reaction mixture by using an Acoustic Technology instrument (Echo 550, LabCyte Inc.
Sunnyvale, CA) in the nanoliter range and incubated for 20 min at room temperature. Then, 3 H-SAM (final concentration 1 μM) was delivered into the reaction mixture to initiate the reaction. After incubation for 60 min at 30 °C, the reaction mixture was delivered to filter paper for detection (as assessed by scintillation). Data were analyzed using Excel and GraphPad Prism 6. 0 software (GraphPad Software Inc. , San Diego, CA) for IC 50 curve fits using sigmoidal dose vs response-variable slope (four parameters) equations. Selectivity Assay against KMTs. The effects of compound 12h on the catalytic activity of ASH1L/KMT2H, EZH2/KMT6, MLL1/ KMT2A, SET7/9/KMT7, SETD8/KMT5A, SUV39H2/KMT1B, SUV420H1/KMT5B, and DOT1L/KMT4 were determined with a HotSpot KMT activity assay by the Reaction Biology Corporation (Malvern, PA) according to the company's standard operating procedure.
119, 120 Briefly, the human recombinant ASH1L (residues 2046-2330, with an N-terminal His-tag; MW = 35. 4 kDa; Genbank Accession # NM_018489), or the human recombinant EZH2containing five-member polycomb repressive complex 2 (including EZH2 residues 2-746, AEBP2 2-517, EED 2-441, RbAp48 2-425, SUZ12 2-739; all full-length; with N-terminal Flag-tag on EED and Nterminal His-tag on all others; MW = 333. 8 kDa; Genbank Accession # NM_001203247, NM_001114176, NM_003797, NM_005610, ChemAxon (https://www. chemaxon. com). Stereochemical restraint dictionaries for all compounds have been produced using the grade Web Server (http://grade. globalphasing. org). PRMT6 Cloning, Expression, and Purification. The Mus musculus PRMT6 gene sequence (UNP Q6NZB1) corresponding to the residues 34-378 of the protein was cloned in the pnEA-vHis or pnEA/vHis vector (TEV protease cleavable hexahistidine tag at the amino-or carboxy-terminus of the recombinant protein, respectively)  132  between the NdeI and XhoI restriction sites and used to transform Escherichia coli BL21 (DE3) cells.
Data sets were all collected on an in-house RIGAKU FR-X diffraction source, using a PILATUS 4 M detector (Dectris), and processed with XDS. Three structures of mmPRMT6 have been solved and refined. The crystals belong to the P2 1 space group with two mmPRMT6 molecules in the asymmetric unit. The structures were solved by molecular replacement using previously solved mmPRMT6 structures as the search model (PDB ID 4C03). 107 Iterative cycles of model building and refinement were carried out using Coot, PHENIX, and Buster. A summary of the data statistics for the two solved and refined structures is provided in Table  5. The atomic coordinates and experimental data (PDB ID 7NUD, 7NUE, and 7P2R) have been deposited in the Protein Data Bank. Parallel Artificial Membrane Permeability Assay (PAMPA).
Accession Codes The atomic coordinates and structure factors of PRMT4 in complex with 12a-c and 12f-h in space group P2 1 2 1 2 (PDB ID: 7PV6, 7PPY, 7PPQ, 7PU8, 7PUQ, 7PUC) and of PRMT6 in complex with 12a, 12c, and 12f in space group P2 1 (PDB ID: 7NUD, 7NUE, and 7P2R) have been deposited in the Protein Data Bank, and authors will release the atomic coordinates and experimental data upon article publication.
Compounds were tested at a 100 μM fixed concentration. c Enzyme residual activity percentage calculated with respect to DMSO. d Compounds were tested in 10-concentration IC 50 mode with threefold serial dilutions starting at 100 μM. Data were analyzed with GraphPad Prism software (version 6. 0) for IC 50 curve fitting. e Ligand efficiency (LE) calculated from IC 50 as a surrogate for K D. f ND, not determined.
b Compounds were tested at a 100 μM fixed concentration. c Enzyme residual activity percentage calculated with respect to DMSO. d Compounds were tested in 10-concentration IC 50 mode with threefold serial dilutions starting at 100 μM. Data were analyzed with GraphPad Prism software (version 6. 0) for IC 50 curve fitting. e Ligand efficiency (LE) calculated from IC 50 as a surrogate for K D. f ND, not determined.