dataesr/scientific-paragraphs-categorization huggingface dataset:
Functional annotation enrichment for Gene Ontology (GO) terms were realized using Flymine database [http:// www. flymine. org/]  16. Benjamini-Hochberg corrected P values of less than 0. 05 were considered significant. We also used i-cisTarget tool  17  to look for enrichment in TF (TF) position weight matrices and potential binding sites in the regulatory regions of co-expressed genes. i-cisTargetX computes statistical over representation of DNA motifs and ChIP-seq peaks in the non-coding DNA around sets of genes  17. The enrichment was considered significant when the Normalized Enrichment Score (NES) was higher than 5. Validation of RNA-seq data using RT-qPCR. To confirm RNA-seq results, we have selected 4 differentially expressed genes (DEGs) known to be involved in the JNK pathway (Hsromega  43  , Cabut  44  , Puckered  45  and Jra/dJjun  46  ) and 4 DEGs known to be targets of the CrebA transcription factor (TRAM, CG5885, Spase25 and Sec.
61beta)  23. RT-qPCR was performed to confirm the gene expression changes of these 8 genes in our 3 experimental conditions (Control, SH and DH). Since, when relaxing the stringency of the analysis to edgeR results, CrebA gene was retrieved as differentially expressed, RT-qPCR was also performed on this gene. RNA extraction from flies was performed with TRIzol ™ Reagent according to the manufacturer's instructions. Then total RNA was reversely transcribed with the Invitrogen ™ SuperScript ™ IV VILO ™ Master Mix according to the manufacturer's instructions. The resulting cDNA was then used as a template for qPCR. Gene-specific primers were designed using Primer 3 software (see Supplementary Table  S6 ), while the rp49 gene was used as the internal control. Reactions were performed using the Applied Biosystems ™ QuantStudio ™ 6 Flex Real-Time PCR System with Power SYBR ® Green PCR Master Mix.
The qPCR program began at 95 °C for 10 min, followed by 40 cycles of 95 °C for 15 s and 60 °C for 1 min. Fluorescent signals were collected at each polymerization step. Melting curve analysis of amplification products was performed at the end to confirm that a single PCR product was detected. Samples were assayed in triplicate and PCR reactions without the template were performed as negative controls. The comparative Ct method for relative quantification was used to analyze the data  47.
1A ), for which TaqMan chemistry was used. Primers used are listed in SI Appendix, Table  S3. H3K36me3-immunoprecipitated chromatin from H1 hES cells was prepared as described above. ChiP-sequencing (ChIP-Seq) libraries were prepared using the NEBNext Ultra DNA Library Prep Kit for Illumina (E7370S; New England BioLabs) and sequenced on a NextSeq 500 sequencing system. The ChIP-Seq data were analyzed using an in-house pipeline that automatically assesses the quality of data, trims adaptors, merges short reads, maps reads to the reference genome (hg19), filters data for duplicates, and performs peak calling. The data were visualized in the UCSC Genome Browser. RT-PCR. RNA was isolated using TRI Reagent (T9424; Sigma-Aldrich) and subsequently DNase-treated using a DNA-free DNA Removal Kit (AM1906; Ambion).
Samples were sequenced on the NextSeq 500 sequencing system. CapSeq data were aligned to build hg19 using STAR and visualized in the USCS Genome Browser. 5′ RACE. A 5′ RACE assay was performed on total DNase-treated RNA using the 5′ RACE System for Rapid Amplification of cDNA Ends (18374-058; Invitrogen). Briefly, first-strand cDNA was synthesized using strand-specific primers to hRHBDF1, and mGapdh was used as an internal control. Actinomycin D was added to prevent second-strand cDNA synthesis. The cDNA was then cleaned up using a S. N. A. P. column (Invitrogen), TdT tailing was performed, and the dC-tailed cDNA was amplified using nested strand-specific hRHBDF1 and mGapdh primers in combination with the provided abridged anchor primer. Following amplification, the cDNA was quantified by real-time PCR using SYBR Green chemistry.
The small RNA-Seq data were trimmed with an in-house Perl script to 25-base-long reads to remove sequencing adaptors. Reads were mapped to both mm9 and hg19 genomes using STAR (allowing each pair to map a maximum of two times to the genome). Read pairs per million mapped read pairs were calculated within the elements of the ZFαAS constructs [HS-40 enhancer (chr16:163249-164691), HBA2 gene (chr16:222845-223709), part of LUC7L gene (chr16:277024-282124)], and miR16 as a positive control (chr14:62250772-62250794 and chr3:68813839-68813861) using samtools. Reads that mapped to hg19 and mm9 within the ZFαAS constructs were filtered out using an in-house Perl script (only a few double-mapped reads were reported). The data were expressed as reads per million normalized to mouse mapped reads and visualized in UCSC using bedtools and ucsctools.
Heat map plots for promoter and intragenic CGIs in hES H1 cells were generated for CGIs with >60% coverage using datasets either publicly available [bisulfite sequencing (BS-Seq) (GSM429322)  (53) , RNA-Seq (GSM958733)  (54) , H3K4me3 (GSM733657), H3K27me3 (GSM733748), Pol2 MMS-126R (GSM803366), input control for H3K4me3 and H3K27me3 (GSM733770), Pol2 (GSM803364)] or generated in-house (H3K36me3). The input was subtracted from the ChIP data. CGIs were sorted in descending order based on the DNA methylation level or differential Pol2 binding within ±2 kb from the middle of CGI, and enrichment for H3K36me3, RNA expression, H3K4me3, and H3K27me3 reads was displayed using the in-house Perl script and visualized in R. Other publically available datasets used to determine RHBDF1 DNA methylation levels and expression were as follows: Bio-CAP-Seq: testes (GSM1064675), liver (GSM1064676), input control (GSM1064674)  (55) ; BS-Seq: hES (GSM429322); and RNA-Seq: hES (GSM958733), liver (GSM752705)  (56).
RNA-Seq, ChIP-Seq, and CAP-Seq datasets produced in the course of this study have been submitted to the Gene Expression Omnibus with superseries accession no. GSE84355. Motif enrichment was conducted using Homer v4. 9  (57). Statistical Analyses. Statistical significance was calculated by a two-tailed t test using Graphpad Prism 6, R, or Excel on data obtained by analyzing in triplicate a minimum of two biological replicates.
ACKNOWLEDGMENTS. We thank  Rob Klose  and  Skirmantas Kriaucionis  for critical reading of the manuscript,  Thomas Jenuwein  for H3K9me3 antibodies,  Sue Butler  and  Jackie Sloane Stanley  for tissue culture,  Nick Proudfoot  for donating the β-globin terminator,  Nicki Gray  for help with drawing the model, and  Felix Krueger  for help with analysis of the bisulfite sequencing data. This work was funded by the  Medical Research Council (MRC) ,  R. J. S. M. was supported by an  MRC   Capacity Building Studentship , and C. T. was supported by a  Royal Society Dorothy Hodgkin Fellowship.
Phylogenetic analysis. A phylogenetic analysis was performed in PAUP* 4. 0b10  22  and TNT software package  23  using a data set based on Grande  11. The inclusion of Nhanulepisosteus did not change the interrelationships among the major clades of lepisosteoids  11  obtained in that previous study. We obtained 176 most parsimonious trees. The strict consensus tree hypothesizes the presence of two well resolved clades of gars among the Lepisosteoidea: Lepisosteidae and Obaichthyidae. Nhanulepisosteus falls as the sister taxon of the rest of the Lepisosteidae (Fig. 3  and Supplementary Fig. 2, 3 ).
Among the holosteans, the ginglymodians are confirmed as monophyletic. The macrosemiids (Macrosemius) diverge earliest, followed by Semionotus being the sister group of a monophyletic Lepisosteoidea, in which the early Cretaceous Obaichththyidae is the sister taxon of the Lepisosteidae  11. Bootstrap values were calculated in PAUP. Bremer Decay values were calculated in TNT software package  23  (Supplementary Fig. 2 ). Histological preparation. Ground cross sections were made using the methodology of Matrajt et al. 30  , modified by Meunier et al. 31. Nomenclatural act. This published work and the nomenclatural act it contains have been registered in ZooBank, the proposed online registration system for the International Code of Zoological Nomenclature (ICZN). The ZooBank LSID (Life Science Identifier) can be resolved and the associated information viewed through any standard web browser by appending the LSID to the prefix 'http://zoobank.
Acknowledgements The manuscript greatly benefited from critical comments by  Gael Clément ,  Vincent Dupret ,  Camila Cupello ,  Kleyton Cantalice ,  Pierre Gueriau ,  Véronique Barriel , and  Lúcio Machado. We also wish to express our gratitude to  David Martill  for his comments and English editing of the manuscript as well as to  Juan Miguel Contreras-Almazán  ( UNAM ) for the photographs and to  Gerardo Alvarez Reyes ,  Jair Barrientos Lara , and  Jésus Flores Cisneros  for assistance in the field work, and  Vincent Rommeveaux  ( MNHN ) for technical assistance with the ground sections. PMB was partially supported by the  Conselho Nacional de Desenvolvimento Cientifico e Tecnológico (CNPq). JAO was supported by the project  PAPIT-IN 209017 (UNAM).
Collaborative collection of comprehensive data The establishment of a DIPG registry was set as first project of the Network, with the purpose to include clinical, biological and centrally reviewed radiology data of patients with DIPG, both in-and outside clinical trials. The SIOPE DIPG Registry is composed of an online web application and database for clinical data, and an Imaging Repository for radiological data (Fig. 1 ). In parallel, an International DIPG Registry was initiated and developed, which includes patient data from the USA, Canada, Australia and New Zealand. To allow for the inclusion of uniform data, standardized electronic Case Report Forms (e-CRFs; Fig. 2 ) were developed by the SIOPE DIPG Network, in coordination with colleagues from the International DIPG Registry. The online e-CRFs collect  data on demographics, medical history and physical exam at time of diagnosis together with the results from radiological and pathological review by the local hospital, treatment data (including radiotherapy, chemotherapy, surgery and supportive care such as steroids), data on clinical and radiological follow up, and last known status of the patient (see Data Entry Manual; Supplementary material 1).
Data collection Each country represented in the SIOPE DIPG Network is committed to delivering data to the SIOPE DIPG Registry and Imaging Repository. After subscription to the Network, the approved Network member receives a username and password to enter data into the Registry. Data collection covers both retrospective and prospective registration. Retrospective data will be collected from local hospitals, national registries and clinical trials. For prospective registration, Network members are encouraged to inform their patients about the existence of the SIOPE DIPG Registry followed by the informed consent procedure. In case of decline, the e-CRFs will be left blank, but a unique Registry number is created, which will only be used for epidemiologic studies. To describe data retrieval, as well as responsibility and ownership of the data, uniform international agreements for collaborative research purposes were created (see Legal aspects).
Data storage and safety Based on the e-CRF's, an optimized relational database was constructed. The database along with the web application is hosted on a dedicated server where the web application is the single point of contact with the database. All end-user connections use the secure HTTP (HTTPS) protocol to ensure protection of the privacy and integrity of the exchanged data. The server is placed within a Virtual Private LAN protected by a dedicated firewall ring. For server maintenance purposes direct access to the server is only possible through a restricted virtual private network (VPN) connection. The DIPG Registry is built on a generic framework in which presentation, logic and data layer are separated. The framework was designed with several active protection features to prevent unsolicited use of the application such as user/role/session validation, the use of antiforgery tokens and brute force protection.
To ensure data safety, database input controls and extensive audit trailing are used. Every action within the system and the database is logged. The server, application and database are monitored 24h/7days and backups are made and stored daily on a different server in order to provide a disaster recovery scenario. The SIOPE DIPG Registry framework herewith provides a stable, secure and generic basis in any of its products. A penetration test (black box approach) was performed to validate the effectiveness of the (visible) security implemented on the SIOPE DIPG Registry and Imaging Repository. This test will be repeated on a regular basis.
Legal aspects The daily and financial management, and hosting of the SIOPE DIPG Registry is carried out by the Dutch Childhood Oncology Group (DCOG), a National Paediatric Haematology-Oncology Society (NaPHOS) member of SIOPE. DCOG is mandated by the Executive Committee of the DIPG Network to act as a legal entity on its behalf in matters concerning the DIPG Registry, by a letter of mandate. The construction of a collaborative research infrastructure, with geographical differences in health care structures and legislation faces considerable challenges. Experts in the field of sensitive data transfer and access rights have been consulted to certify issues concerning data anonymization, -collection, and -safety. To meet multinational standards, two legal documents have been drafted, abiding to EU law and taking into account SIOPE DIPG Network members' national laws.
The first contains the SIOPE DIPG Network Bylaws (Supplementary material 3), that describe the mission, aims, core values and structure of the SIOPE DIPG Network as well as terms and conditions for submitting, reviewing and approving proposals for research projects using data from the SIOPE DIPG Registry. Furthermore, the Bylaws provide a Scientific Advisory Agreement for consultation of experts outside the SIOPE DIPG Network, such as specialised neuroradiologist for central radiology review. Second is the SIOPE DIPG Registry and Imaging Repository Regulatory Document (Supplementary material 4), describing the terms and conditions for management, maintenance of and access to the DIPG Registry and Imaging Repository.
Use of data For strategic decisions concerning novel collaborative clinical and biological research projects in the field of DIPG, NCs meet or consult several times a year. In this way the SIOPE DIPG Network itself is responsible for the optimal use of obtained data. Data from the SIOPE DIPG Registry and Imaging Repository are available to researchers for collaborative, interdisciplinary, and translational studies. For use of the data from the Registry, the researcher must be a member of the SIOPE DIPG Network. The availability of data to the researcher is conditional to obtained approval from the Executive Committee, after submission of a project proposal, and permits and licenses required by the researcher's national law. The Executive Committee may set additional conditions to a specific project and stipulates the general terms and conditions with regard to receipt and use of data.
Subsequently, only requested, relevant data are selected from the DIPG Registry and made available to the researcher. The researcher owns results of a research project, including the intellectual property rights thereto. Publication of results generated with data from the SIOPE DIPG Registry requires to comply with rules concerning authorship, as defined by the International Committee of Medical Journal Editors (ICMJE). Each year, the Executive Committee sends a report to the members of the SIOPE DIPG Network on the number of approved, performed and rejected projects.
International collaboration in DIPG research Since its inception in 2011, the SIOPE DIPG Network has expanded each year. Currently, 27 countries (Austria, Belgium, Croatia, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Lithuania, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, The Netherlands, United Kingdom, Turkey, Russia, and Mexico; Supplementary Fig. 2 ) have committed to the SIOPE DIPG Network and Registry. There is also a close collaboration with the International DIPG Registry, which represents the collaborative efforts of physicians and researchers from North America, Canada, Australia and New Zealand (Supplementary Fig. 2 ). To coordinate similar data collection, there are frequent telephone conferences and annual working visits between the SIOPE DIPG Network chair, the SIOPE DIPG Registry coordinator and International DIPG Registry team stationed at the Clinical Management and Research Support Core (CMRSC) at Cincinnati Children's Hospital Medical Center.
SIOPE DIPG registry and imaging repository Currently, as a prerequisite to start prospective patient inclusion in the SIOPE DIPG Registry, members of the SIOPE DIPG Network are in the process of Medical Ethical Committee and IRB review, with some countries already including patient data upon approval. As of April 2016, six countries have submitted retrospective data of 694 patients to the SIOPE DIPG Registry and Imaging Repository. Data were retrieved from three national registries, two local hospitals, and one clinical trial. Figure  3  shows the age distribution of patients included in the SIOPE DIPG Registry, with a median age of 7 years (standard deviation (SD) ± 3. 5). Table  1  shows the patient characteristics, clinical, radiological and biological disease characteristics, and treatment details of the total cohort.
Discussion A first step is made to improve the infrastructure of research into DIPG. This was done by (1) the establishment of the SIOPE DIPG Network, and (2) the development and initiation of the SIOPE DIPG Registry and Imaging Repository. This initiative, enabling collaborative research, is seen as major first step towards improving care and (ultimately) cure for children with DIPG. Collaboration is pursued to overcome the factors hampering research into DIPG. This paper is the first to publish pooled patient data of almost 700 DIPG patients collected from national registries, local hospitals and clinical trials. To date, published patient data are largely from phase I/ II trials, which cover only a small percentage of the actual population diagnosed with DIPG. This possibly results in publication/selection bias.
Future registration of all DIPG patients, both in-and outside trials, will give the opportunity to analyze 'real-life' DIPG patient data resulting in better description of incidence, characteristics and survival of DIPG patients. Also, it will generate a representative reference cohort, which may be used as historical control in any future study. With the SIOPE DIPG Network and SIOPE DIPG Registry/Imaging Repository, an infrastructure has been created that allows for research transparency, international collaboration and the elimination of duplication of research efforts. Already two international studies were published by the SIOPE DIPG Network, concerning palliative care and end-of-life decisions  [18]  and steroid use  [19]  in DIPG patients. The first large-scale international study including all patients registered in the SIOPE DIPG Registry and International Registry, with an estimated total of >1000 DIPG cases, is currently being conducted.
This study will evaluate the characteristics of long-term surviving patients in comparison to the total group of patients. The preliminary patient data of the 694 patients currently included in the SIOPE DIPG Registry, shows an equal gender distribution, rapid onset of symptoms prediagnosis (86% <12 weeks of which 66% within 6 weeks), a clinical presentation including cranial nerve palsy in the majority (85%) of patients, and two-third of patients showing gadolinium contrast enhancement on the diagnostic MRI, of which 57% (39% of the total cohort) showed partial ring-like enhancement suggestive for necrosis. At time of diagnosis, only 1% of the diagnostic MRIs showed metastasis in the brain, and 2% in the spine. Eighteen percent of patients present with hydrocephalus. Biopsy was performed in one-third of the patients, showing a range of WHO grades.
The recent WHO re-classification, however, may imply that the inclusion criteria for the SIOPE DIPG Registry need to be adjusted to also include patients with non-pontine diffuse midline gliomas in the future. Dependent on the extent to which biopsies and autopsies will be (re-)introduced for DIPG, data on biological characteristics will gradually increment in the Registry, which will increase the knowledge on DIPG etiology, pathogenesis, possible drug targets and the mechanisms that contribute to the observed resistance to treatment. Furthermore, big-data analysis of aggregated clinical, radiological and especially biological data facilitates the discovery of patterns that indicate patient subgroups, which enables consensus formation on classification, in-/exclusion and response criteria, and improves the quality and comparability of future trials.
Moreover, joining forces within an international research-infrastructure will stimulate the initiation of, and active accrual in, international multicenter trials, with sufficient power to address the many unanswered research questions. This, together with the recent evolution of ideas concerning therapeutic strategies  [21] [22] [23] [24] , should facilitate the identification and selection of novel tolerable and effective therapies. Data collection in the Registry will have some (initial) limitations. Due to the former lack of local hospital-and national registrations, lack of specific ICD-codes 1 , and due to a presumed limited documentation of clinical, radiological and pathological data, retrospective data collection will very likely be incomplete. Based on data from the Dutch retrospective study  [10] , and included parties in the SIOPE DIPG Network (with a total number of about 600 million residents aged 0-19 years; April 2016) it is estimated that over 350 children are eligible for prospective registration in the SIOPE DIPG Registry each year.
It is expected that annually about 200 patients (60%) will be registered in the first years, and that this number will increase when the SIOPE DIPG Network expands, resulting in higher data completeness per country over time. Recent publications in DIPG literature have shown that coupling genetic data to clinical data will become increasingly important to understand and/or predict the clinical behavior of the disease  [9, 14]. Therefore, as for now, data of the most common genetic aberrations are entered in the Registry via a 'Biopsy/Autopsy e-CRF'. A next step of the SIOPE DIPG Registry is to establish a (virtual) biobank of DIPG material, linked with the DIPG Genomics Repository at Progenetix (dipg. progenetix. org), a cancer genome database  [25]. Ideally, the increased availability of DIPG tumor tissue will lead to generally available, representative, and possibly even patient subgroup-specific cell cultures and xenograft models, which enable thorough basic research and high-throughput screening of candidate therapies.