dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgement This study is part of the  CryoWALL  project ( 243784/CLE ) funded by the  Research Council of Norway (RCN). Additional funding, both directly or indirectly, was provided by the  University of Oslo , the  Geological Survey of Norway  and the  Norwegian Water and Energy Directorate (NVE). Part of the work by the  Norwegian Meteorological Institute  was funded by the  Research Council of Norway  through the  Climate Research Programme KLIMAFORSK (ACHILLES , project no. 235574 ). Bas Altena ,  Thorben Dunse ,  Justyna Czekirda ,  Jaroslav Obu ,  Ove Brynildsvold  (all  University of Oslo ),  Joel Fiddes  ( SLF, Switzerland ),  Amund Mundhjeld  (Raubergstulen) and  Solveig Winsvold  (NVE) helped with either installing rock wall loggers or reading them out. C. Lussana  ( Meteorological Institute of Norway ) guided the processing of the SeNorge2 dataset.
This study will permit to validate or identify already suspected risk factors for sarcomas such as phenoxyherbicides, chlorophenol and to generate new hypothesis to increase our understanding about the genetic and environmental contributions in the carcinogenicity process. Ethics and dissemination The present study is promoted by the French National Institute of Health and Medical Research (identification number C17-03). This study received National French Ethic committee (CPP Sud Méditerrannée I) approval (identification number 18-31)  and French Data Protection Authority (CNIL) approval (identification number 918171). Results of this study will be published in international peer-reviewed journals. Technical appendix, statistical code and dataset will be available in the Dryad repository when collection data are completed.
IntroduCtIon Sarcomas are a heterogeneous group of rare malignant tumours of connective tissues. Besides multiple and complex histology strengths and limitations of this study ► All newly diagnosed patients will be ascertained through a systematic review of the diagnostic by an expert pathologist within French sarcomas networks. ► Prospective inclusion of >2000 population-based patients which will allow to perform analysis by histological subtypes. ► Collection of various exposure data using face-toface administered standardised questionnaire by trained interviewers. Additionally, saliva samples will be collected. ► Possible low participation rate of population controls. ► Retrospective collection of data and over a long period of time. Open access At the genetic level, sarcomas can be split into two large categories based on the rearrangement level of the genome.
Thus, to date, it is impossible to draw strong conclusions on the aetiology of sarcomas from existing studies. Indeed, there are some methodological considerations to explain discrepancies between studies: sample sizes are often limited leading to insufficient power to detect small but relevant increases in risk. As a consequence, sarcomas are studied as a single outcome and not by histological subtypes; at most they are segregated into bone sarcomas and soft-tissue sarcomas. Such analyses support the strong hypothesis that the same aetiology is shared between each subtype and each site. The inclusion periods of patients are usually old and ascertainment of patients may be incorrect. Indeed, a second expert review of diagnosis is essential to correctly classify sarcoma's tumours. 10 Diagnostic procedures have been refined in expert centres during the last several years with the inclusion of new genetic and molecular data leading to a better understanding and definition of tumours.
A multicentre case-control study in seven European countries specifically focused on bone sarcomas found increased risks among blacksmiths, toolmakers, machine-tool operators and construction workers. 26 esides occupational factors, few studies investigated other environmental factors related to lifestyle, including the potential role of female hormones, tobacco smoke, alcohol, nutrition, fluoride in drinking water and body mass index. These studies reported inconclusive or inconsistent results with the exception of viruses like the HIV and human herpes virus 8 for Kaposi's sarcoma. 1  Finally, while there is increased evidence regarding genetic determinants of sarcoma risk,  31  and growing evidence that gene × environment (G×E) interactions are determinants of development and progression of complex disease,  32  to date, there are no data related to such G×E interactions with regards to sarcoma risk.
34 The NetSarc clinical network for sarcoma is the clinical network of the French Sarcoma Group dedicated to clinical patient care. NetSarc is managed by three sites (Centre Leon Berard in Lyon, Institut Bergonie in Bordeaux and Institut Gustave Roussy in Villejuif) working closely with 25 expert regional centres, ensuring good coverage of the whole French territory. 35 Besides, the French population-based cancer registries are organised in a collaborative network named Francim. The main objectives of this network are to coordinate the 14 general cancer registries and 11 specialised cancer registries that exhaustively register all newly diagnosed and confirmed cancer patients according to international procedures, to harmonise patients registration and data quality, to provide epidemiological indicators (incidence, survival, prevalence) and to coordinate epidemiological and surveillance research on cancer.
Open access In total, 15 districts meet one of the four criteria, which represent 17 813 937 inhabitants, ~27% of the French population (2019 estimations from the national institute of statistics and economic studies, Insee). Eight districts meet criteria 1 (Gironde, Hérault, Haute-Vienne, Loire Atlantique, Calvados, metropolitan area of Lille, Bas-Rhin and Doubs), two districts meet criteria 2 (Rhône and Val-de-Marne); three districts meet criteria 3 (Isère, Haut-Rhin and Poitou-Charentes) and two districts meet criteria 4 (Manche, Vendée). Since sarcomas are rare tumours, this study has to be multicentric. Indeed, from general cancer registry data and RRePS overall incidence data, considering a patients' response rate of 70%, and considering that ~90% of newly diagnosed patients will benefit from a systematic secondary review of diagnosis, it is expected to include 718 incident patients per year from these 15 districts, corresponding to a total sample size of 2154 patients from a 3-year recruitment (table  1 ).
For each control agreeing to participate, an appointment will be made to collect written consent and to administer detailed questionnaire by a CRA. All participants will give their informed written consent to participation, in line with French ethical guidelines. data collection Data will be collected in a three-step procedure and from subjects themselves: (1) the interviewer will contact subjects by phone and ask them to participate in the study; (2) if the subject has agreed to participate, an appointment will be made and a consent form as well as a self-administered questionnaire will be sent by mail to each subject. This self-questionnaire will permit to gather the complete occupational history (for each job held for at least 6 months) and residential history (for each place occupied for at least 1 year); (3) during a face-to-face interview, the trained interviewer will check (complete if necessary) and supplement the self-administered questionnaire by a specific questionnaire with questions about demographic and socioeconomic characteristics, occupations of spouse and parents, leisure-time activities, reproduction, medical history, family history of cancer, diet, lifestyle factors such as tobacco smoking and alcohol consumption.
The specific questionnaire will also collect additional occupational and residential information such as work tasks, work places, materials handled for each job held for at least 6 months and description of the environment of each residence places. At the end of the interview, subjects (both patients and controls) will be invited to provide a saliva sample in order to obtain germline DNA. In case of refusal to participate and if the subject agreed, data on the last occupied job and educational level will be collected in order to assess the potential selection bias that might occur due to the specific profile of non-respondent subjects. To ensure consistency in data collection, all CRA will be trained in the completion of the questionnaire and will detain a field guide of completion. Additionally, phone meetings involving all CRA will take place each month in order to deal with recurring problems in the completion of the questionnaire and to ensure homogeneity in data collection between all CRA.
statistical analysis Relationship between patient/control status and each exposure variable and 95% CI will be individually estimated using conditional logistic regression models. If necessary, a multilevel logistic model will be implemented in order to take into account the data variability due to the multicentre design and the various CRA that will administer the questionnaires (even if each CRA will be trained to the administration of the questionnaires). As previously mentioned, previous case-control studies had limited sample sizes leading to insufficient power to detect small but relevant increases in risk. As a consequence, sarcomas were studied as a single outcome and not by histological subtypes; at most they were segregated into bone sarcomas and soft-tissue sarcomas. Such analyses supported the strong hypothesis that the same aetiology is shared between each subtype and each site.
A data manager will ensure that the study is conducted in compliance with the protocol. On a regular basis and as frequently as necessary, he/ she will assess the quality of the collected data using several indicators: the average time spent by the CRA at the subject's home, the degree of completeness of the questionnaires by CRA, the ratio of included patients to expected patients the average elapsed time between the identification of a patient and the interview, the average elapsed time between patient and control interviews and so on. Besides, the data manager will detect aberrant data, duplication, inaccurate and missing data. Every week, these data manager will refer to the head of the national coordination centre and report on the progress of the study. All collected data will be centralised in a single location, the University of Bordeaux.
These data will be informatised by a contractor specialised in health and exposure data coding (Centre de Recherche et de Développement en Informatique Médicale). Expected results, as well as possible spin-offs for them This research is an innovative study that will permit to improve scientific knowledge about the aetiology of sarcomas and we expect our results to contribute to better understand the causes of sarcomas. We will primarily address the question of environmental causes, which will permit to confirm or generate new hypotheses on the environmental risk factors of this disease. This study will also provide a unique platform with data that will permit to address several research questions other than environmental ones. This project will also contribute to increase the French expertise with regards to research and management of sarcomas and will reinforce existing collaboration at a national level between each team involved in this study.
The living tree sloths Choloepus and Bradypus are the only remaining members of Folivora, a major xenarthran radiation that occupied a wide range of habitats in many parts of the western hemisphere during the Cenozoic, including both continents and the West Indies. Ancient DNA evidence has played only a minor role in folivoran systematics, as most sloths lived in places not conducive to genomic preservation. Here we utilize collagen sequence information, both separately and in combination with published mitochondrial DNA evidence, to assess the relationships of tree sloths and their extinct relatives. Results from phylogenetic analysis of these datasets differ substantially from morphology-based concepts: Choloepus groups with Mylodontidae, not Megalonychidae; Bradypus and Megalonyx pair together as megatherioids, while monophyletic Antillean sloths may be sister to all other folivorans.
Results To address some of the questions raised in the previous section, as well as to add to the available molecular database for folivorans, we utilized proteomic data collected from fossil and living sloths to focus on three fundamental issues: (1) relationships of tree sloths to each other and to other folivorans; (2) composition of folivoran superfamilies Megatherioidea and Mylodontoidea; and (3) divergence dating of major sloth ingroups. Results were tested against datasets that additionally incorporated published genomic and phenomic information. Samples. A total of 120 xenarthran samples comprising 24 different genus-level taxa (see Supplementary information, Supplementary Table  1. ) were screened for protein survival using both amino acid racemization (AAR) and matrix-assisted laser desorption/ ionization-time of flight (MALDI-TOF) mass spectrometry.
00) consists of traditional mylodontoids plus Choloepus. Because the inclusion of Choloepus in this group contrasts markedly with results achieved using morphological datasets, we designate this clade as *Mylodontoidea. Here, Scelidotherium + Scelidodon is the earliest diverging branch and Choloepus is recovered as part of a clade (PP = 0. 83), consistent with accepted mylodontid interrelationships  16, 30, 56.
NATuRe eCology & evoluTIoN To further interrogate the reliability of our proteomic topologies, we concatenated our collagen sequences with previously published mitochondrial genome sequences (hereafter, proteomic + genomic data) for all extant folivorans (two species of Choloepus, four species of Bradypus), two extinct folivorans (M. darwinii and N. shastensis) and the two extant outgroup taxa  33, 34. Bayesian analysis (Supplementary Fig. 2 ) of the combined dataset yielded a topology almost identical to that recovered using proteomic data alone, but in this instance *Megatherioidea (including Bradypus) and *Mylodontoidea (including Choloepus) were unambiguously recovered as reciprocally monophyletic clades (PP = 1). Recovery of a paraphyletic Bradypus (with respect to Megalonyx) is almost certainly due to a long genomic branch and lack of proteomic data for Bradypus torquatus, combined with a comparable lack of genomic data for Megalonyx.
Molecular clock considerations and divergence time estimates. Incorporating time as an analytical component in analysis of the combined dataset yielded a well-supported and monophyletic Antillean clade (PP > 0. 99), although within-clade relationships were not satisfactorily resolved. More unexpectedly, in light of traditional taxonomic concepts, BEAST placed the Antillean clade as a well-supported sister to *Megatherioidea plus *Mylodontoidea (PP = 0. 97) rather than pairing it with one or the other. Support for megatherioid (PP > 0. 99) and mylodontoid (PP > 0. 99) monophyly remained strong, but variable for constituent sub-clades. The relatively permissive constraints employed for calculation of divergences make it difficult to draw detailed conclusions regarding the tempo of sloth diversification, although mean ages in the combined analysis are reasonably consistent with inferences based on both genomic  33, 34  and morphological 16 data (Fig.
Discussion In most respects, our higher-level results for Folivora are consistent with recently published morphology-only phylogenies, but the few ways in which they differ are critical because they have profound implications for macro-evolutionary and biogeographical inference. Harmonization of morphological and molecular datasets is complicated, as the molecular results imply that traditional clades exhibit a massive amount of unrecognized homoplasy-or equally unrecognized plesiomorphies, incorrectly interpreted as (syn)apomorphies. Molecular analyses are of course subject to the same challenges, especially in contexts like the present in which samples sizes and information content are limited. It is already widely appreciated that genomic information is exceptionally useful for testing phylogenetic hypotheses; so is proteomic information, especially when it can be shown to be highly congruent with genetic indicators of relationship  53.
1% formic acid, 95% acetonitrile) during online electrospray ionization-MS and MS/MS analyses with a Q-Exactive Plus mass spectrometer (Thermo Fisher Scientific). MS/MS analyses of the top 25 precursors in each full scan (300-1700 m/z) used the following parameters: resolution, 17,500 (at 200 Th); AGC target, 2 × 10 5 ; maximum injection time, 200 ms; isolation width, 2. 0 m/z; normalized collision energy, 24%. Protein sequence analysis. The LC-MS/MS raw files were converted to Mascot generic files using Proteowizard  72  and searched against a mammal collagen database that included common contaminants (http://www. thegpm. org/crap/) in PEAKS v. 7. 5. Mass tolerances were set at 0. 5 Da for the fragment ions and 10 ppm for precursor ions, and up to three missed cleavages were permitted. Searches allowed various post-translational modifications (PTMs) including oxidation of the amino acids methionine, histidine, and tryptophan (+15.
99), hydroxylation of proline (also +15. 99), deamidation of asparagine and glutamine (+0. 98), pyro-glu from glutamic acid (-18. 01) and carbamidomethylation (+57. 02) which occurs as part of the sample preparation. A maximum of three PTMs was allowed per peptide. Protein tolerances were set at 0. 5% false discovery rate, >50% average local confidence (de novo only) and -log 10 P score ≥ 20. Sequences of both COL 1A1 and COL 1A2 were concatenated using previously published mammal collagen consensus sequences derived from NCBI, including sequences for the xenarthrans Dasypus novemcinctus (nine-banded armadillo; GenBank, No. XP_004470764), Cyclopes didactylus (silky anteater; Uniprot, No. COHJP1/COHJP2) and Lestodon armatus (extinct mylodontoid sloth, ref. 44  ). Telopeptides very rarely survive in fossil samples and so these were removed from all sequences.
The amino acids isoleucine and leucine cannot be differentiated using low-energy tandem mass spectrometry and de novo sequencing, as both are isobaric. Therefore, the identification of leucine/isoleucine was consistent throughout the sequence analyses concatenated in this study. Our approach is in line with previous phylogenetic studies using collagen as probe  43  , under the assumption that MS/MS sequence variation is not interpreted as a major phylogenetic change (see Phylogenetic analyses, below). Once a potential collagen sequence was compiled for a given sloth taxon, the sequence was added to the collagen database and the sample was rerun through PEAKS to check for coverage and sequence substitutions. Any differences noted either in the consensus sequences or between different species of sloths were inspected manually.
We investigated this by replacing all peptides coded as leucine with ambiguous codings {IL} and repeating Bayesian estimation of topology and branch lengths using MrBayes. The resulting 50% majority rule consensus tree was identical across coding schemes, and comparison of branch length estimates among analyses showed no significant deviation from 1:1 (branch length Leucine = -0. 00009 + branch length ambiguous × 0. 96, R 2 = 0. 995, P « 0. 001), indicating that the use of leucine is appropriate. We repeated Bayesian analyses of the combined proteomic + genomic dataset using the same settings, but with partitioning schemes and substitution models for genetic data following ref. 34. We attempted to integrate our combined molecular dataset with a large, recently published morphological dataset (ref.
9 ). The resulting majority rule consensus tree (Supplementary Fig. 6 ) is congruent in some respects with our molecular topologies (for example, Choloepus was recovered as a mylodontoid and Bradypus as a megatherioid), but other results repeatedly found in molecular analyses were not obtained. In particular, we recovered a strong (PP = 1. 0) traditional Megalonychidae nested within Megatherioidea that included Antillean sloths minus Choloepus. Although the Antillean species were represented in the total dataset by proteomic sequences, genomic data were unavailable. This result suggests that the large number of morphological characters, some known to be highly homoplastic  54  , were able to swamp the signal arising from the smaller proteomic dataset. While combined analysis of morphological and molecular data will ultimately be necessary to fully resolve folivoran phylogeny, this exercise suggests that it is premature to consider such simultaneous analyses reliable at this point in time.
Our MrBayes analyses sample tree topologies with branch lengths in units of substitutions per site, and thus ignore temporal information inherent in phylogenetic analysis of non-contemporaneous tips or external information about relative branch lengths that can be provided by the fossil record. We therefore also performed a series of Bayesian tree searches assuming a molecular clock under the fossilized birth-death framework  [81] [82] [83]  , as implemented in BEAST v. 2. 5. 1 (ref. 84 ). Briefly, this framework allowed us to sample from the posterior distribution of time-scaled trees for taxa in our proteomic dataset, inferred using their sequences and stratigraphic ages, while using phylogenetically constrained fossil taxa that lack amino acid data able to provide additional information on relative branch lengths and divergence times.
5; origin, ~U (61. 5, 150), yielding a flat prior on ages older than 61. 5-150 Ma. In addition, the analysis was conditioned on the number of extant taxa sampled (ρ = 0. 129 in the xenarthran proteomic analyses, ρ = 0. 333 in the folivoran proteomic analyses, ρ = 0. 266 in the combined analyses). Based on comparisons of marginal likelihoods computed via path sampling (see Supplementary information and Supplementary Table  3 ), we employed a relaxed uncorrelated clock with log-normally distributed rates for proteomic and combined analyses, with an exponential prior (mean, 0. 1) placed on the mean of log-normal distribution and the default gamma Γ(0. 5396, 0. 3819) on the standard deviation. Two MCMC analyses were run for 10 million generations each, sampling every 1,000 generations, after which fossils without data were pruned from the trees, the first 20% of the retained samples were discarded as burn-in, the samples were combined and maximum clade credibility trees constructed using the tree annotator software accompanying the BEAST suite.
Acknowledgements We thank the curatorial staffs of the following museums and private collections for permission to sample specimens in their care:  AMNH-M, American Museum of Natural History (Mammalogy), New York, USA ;  AMNH-P, American Museum of Natural History (Paleontology), New York, USA ; CIV,  Iota Quatro  faunal collection, courtesy of  Lazaro Vinola ;  El Trebol  faunal collection, Bariloche, Argentina; FR,  Forest Reserve (Trinidad)  faunal collection currently housed in  Department of Mammalogy, AMNH, New York, USA; IANIGLA-PV, Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales, CCT-CONICET-Mendoza, Mendoza, Argentina ;  MACN-PV, Museo Argentino de Ciencias Naturales 'Bernardino Rivadavia' (Sección Paleovertebrados), Buenos Aires, Argentina; MAPBAR, Museo de la Asociación Paleontológica Bariloche (APB) , prov.
Data availability Mass spectrometry proteomics data have been deposited with the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD012859. Collagen sequences are available on the Uniprot website (https://www. uniprot. org/); the complete list can be found in Supplementary Table  5. Phylogenetic datasets have been deposited at DataDryad (https://doi. org/10. 5061/dryad. 7dd64gs).