dataesr/scientific-paragraphs-categorization huggingface dataset:
Reactome pathways highlighted in our enrichment analysis included broad classifications at the nucleotide level such as nucleotide excision repair, as well as more specific processes including SMAD signaling proteins (fold enrichment = 56. 11, p = 1. 65 × 10 -3 ), NOTCH (fold enrichment = 66. 75, p = 9. 56 × 10 -7 ), and Activin (fold enrichment = 74. 46, p = 1. 79 × 10 -2 ) (summarized in Table  2 , full results in Supplementary Table  S4 ). Our second svPPA ontological pathway analysis -through the W-PPI-NA pipeline -enabled the independent topological characterization of our 64 svPPA network genes. Provided that one svPPA network risk gene -TH1L -did not survive after applying the W-PPI-NA method, the (second) network was ultimately generated using 63 proteins as seeds. We merged the annotations reported in multiple protein-protein interaction (PPI) databases within the IMEX consortium  17.
S2 ). The core of the network was made of 37 nodes (7 IIHs and their interactors) and 93 edges. These were strongly interconnected (average number of neighbors = 4. 7). We next functionally annotated the interactomes, focusing on GO-BPs (biological processes) using g:Profiler. The first functional enrichment aforementioned in this paragraph was followed by a second iteration of the same procedure but only applied on the densely connected core of the network (Fig. 2D ). Our results (Supplementary Data S1) indicated a list of semantic classes that were a subset of the former. Interestingly the subset terms (percentage of retention >12%, i. e. an arbitrary yet robust threshold that takes into account the functions containing the largest number of replicated BP terms in our experimental setting (Fig.
Unfortunately, the results of our VEGAS analyses do not facilitate the calculation of each gene's, or the overall network's, percent contribution to svPPA risk. Further molecular and model-organism studies will be required to validate and prove the importance of our svPPA network genes as modifiers of disease risk in svPPA and other TDP-43 proteinopathies. We attempted to replicate the protein interaction network results from our VEGAS analysis using differential expression data from GSE13162. The network generated using differential expression from GSE13162 was not significant after multiple testing correction (data not shown). This study focused on one of the FTLD phenotypes. Ongoing work in our group focuses on the other IFGC phenotypes  30  as well as the work of other groups which will help to elucidate the genetic and biochemical pathways that make svPPA distinct from the other FTLD phenotypes and may further highlight which processes are shared across FTLD subtypes.
Methods Ethics, consent and permissions. This study was performed in accordance with the guidelines set forth by the University of California, San Francisco Human Research Protection Program Institutional Review Board. The data collection from the original GWAS used in this analysis was overseen by the relevant institutional review boards, and ethics committees approved the research protocol of all individual studies used in the current analysis. Participants of those studies provided written informed consent. svppA gene network generation. To generate the svPPA network, we first calculated gene-level significance values using VEGAS  10. This tool uses location information from the UCSC Genome Browser (hg18) assembly to assign individual SNPs to their respective gene. Gene boundaries were defined as 50 kb beyond the 5′ and 3′ UTRs of each gene to ensure we captured the effects of regulatory regions and SNPs in linkage disequilibrium (LD).
VEGAS accounts for background LD patterns between markers within a gene using data from individuals of northern and western European descent (HapMap2 CEU)  31. Monte-Carlo simulations use these LD patterns to generate a multivariate normal distribution which is used to calculate an empirical p-value for each gene. For additional details on VEGAS, please see Liu et al. and Baranzini et al. 10, 32. We derived PINs from the iRefIndex database, a collection of 15 human PIN data sets from different sources  33. The combined dataset from these PINs contained over 400,000 interactions among approximately 25,000 proteins. To minimize the number of false positives in our PIN, we limited our PIN to interactions described in at least two independent publications. The resulting network used as a background network in our analyses contained 8,960 proteins and 27,724 interactions.
Gene expression in pathologically confirmed FTLD cases. We hypothesized that genes from our network analysis would be dysregulated in pathologically confirmed cases of FTLD as compared to controls. Given that svPPA is primarily associated with ubiquitinated inclusions composed of TDP-43, we chose to use a publicly available dataset of individuals diagnosed with FTLD with ubiquitinated inclusions and comparable control cases. Ten of the participants were pathologically diagnosed with sporadic FTLD and 11 diagnosed as controls (Gene Expression Omnibus (GEO) dataset GSE13162)  35. In linear regression models we controlled for sex, post mortem interval, and age. svppA biological pathway enrichment analysis. We performed enrichment analyses on our genes of interest using the Reactome and GO annotation databases.
Acknowledgements Primary support for data analyses was provided by the  Radiological Society of North America (RSNA)   RMS1741  (LWB),  Larry L. Hillblom Foundation   2016-A-005-SUP (JSY ),  AFTD Susan Marcus Memorial Fund Clinical Research Grant (JSY) ,  NIA   K01 AG049152  (JSY),  Bluefield Project  to  Cure FTD  (JSY),  Tau Consortium (JSY) ,  NIA   K01 AG046374  (CMK), U24DA041123 (RSD),  National Alzheimer's Coordinating Center  ( NACC) Junior Investigator Award (RSD), RSNA Resident/Fellow Grant  (RSD),  Foundation of ASNR Alzheimer's Imaging Grant (RSD) , and  Alzheimer's Society  Grant  284  (RF). Additional support was provided by an  MRC   Programme grant  ( MR/N026004/1 ; JH and PAL) and a  MRC New Investigator Research Grant  ( MR/L010933/1 ; PAL). PAL is a Parkinson's  UK research  fellow (grant  F1002 ).
Homo sapiens annotations and ran the statistical enrichment tests for biological pathways under the default settings (which corrects for multiple testing using the Bonferroni technique). To replicate the findings of our primary ontological analysis, we next applied the recently developed W-PPI-NA pipeline 15 to increase resolution on the candidate proteins isolated by PINBPA. Specifically, we generated a second independent network using the svPPA genes prioritized by the PINBPA analysis by extracting ( 12 May 2017 ) their protein interactors (PPIs) from the following databases within the IMEX consortium 17 :  APID Interactomes, BioGrid, bhf-ucl, InnateDB, InnateDB-All, IntAct, mentha, MINT, InnateDB-IMEx, UniProt , and MBInfo by means of the "PSICQUIC" R package (version 1. 15. 0 by  Paul Shannon , http://code.
google. com/p/psicquic/). PPIs were harmonized by converting  Protein IDs  to UniProt and  Entrez IDs  thus allowing merging of all databases. We removed TrEMBL, non-protein interactors (e. g. chemicals), obsolete  Entrez , and Entrez matching to multiple Swiss-Prot identifiers. All PPIs underwent quality control and filtering leading to removal of: i) all the non-human taxid annotations, and ii) all the annotations with multiple or no PubMed identifiers or no description of Interaction Detection Method. The interactions were then scored as follows: (i) evaluation of the number of different publications reporting the interaction and (ii) evaluation of the number of different methods reporting the interaction. All the interactors with a final score ≤2 were discarded to reduce false positive rate.
Data Availability Requests for GWAS metadata should be directed to the International FTD-Genomics Consortium. The PINBPA package is available through Cytoscape (www. cytoscape. org). Reactome data is available at www. reactome. org. PANTHER data is available at www. pantherdb. org. The "PSICQUIC" R package (version 1. 15. 0 by Paul Shannon) is available at (http://code. google. com/p/psicquic/). g:Profiler is available at(g:GOSt,http://biit. cs. ut. ee/gprofiler/).
The co-primary endpoints were overall survival and failure-free survival. Secondary endpoints of vaginal, pelvic, and distant recurrence were analysed according to the first site of recurrence. Survival endpoints were analysed by intention-to-treat, and adjusted for stratification factors. Competing risk methods were used for failure-free survival and recurrence. We did a post-hoc analysis to analyse patterns of recurrence with 1 additional year of follow-up. The study was closed on Dec 20, 2013; follow-up is ongoing. This study is registered with ISRCTN, number ISRCTN14387080, and ClinicalTrials. gov, number NCT00411138. Findings Between Nov 23, 2006, and Dec 20, 2013, 686 women were enrolled, of whom 660 were eligible and evaluable (330 in the chemoradiotherapy group, and 330 in the radiotherapy-alone group).
Randomisation and masking Patients were randomly assigned (1:1) to open-label treatment groups with chemoradiotherapy or radiotherapy alone, by use of a biased-coin minimisation procedure ensuring balance overall and within each stratum of the stratification factors (participating centre, lymphadenectomy [yes vs no], FIGO 2009 stage of cancer [IA vs IB vs II vs III]), and histological type [endometrioid carcinoma vs serous or clear cell carcinoma]). Patients were registered and randomly assigned by the data centres of the participating groups and treatment was assigned with a web-based application. Participants, physicians, and investigators were not masked to treatment allocation.
Final database lock was on Nov 29, 2018. We did statistical analyses using SPSS, version 23. 0. 0. 2, and R, version 3. 5. 1. All analyses were done by intention to treat, excluding ineligible patients and those who immediately withdrew informed consent after randomi sation. Differences in relapse and survival rates between the groups were tested with the log-rank test and Cox regression analysis. The analysis of the primary endpoints was adjusted for the stratification factors (participating group, lymphaden ectomy, stage of cancer, and histological type), since a stratified minimisation procedure was used at randomi sation. 15, 16 or the adjusted analysis, stratification factors were included as covariates in the Cox model. The proportional hazards assumption for treatment was checked by use of Schoenfeld residuals for overall survival and failure-free survival, and was not found to be violated.
17  methods were used for analysis of failure-free survival and recurrence, by calculating cumulative incidences and Fine-Gray regression. 18 For failure-free survival, inter current death was used as a competing risk. For the first failure analysis of recurrences, all other recurrences and death were used as competing risks. Median survival after recurrence was calculated as the first timepoint at which the Kaplan-Meier curve was below 50% survival. The IQR was calculated similarly. In the multivariable analysis, the following covariates were included together with treatment: stage, histological type and grade, type of surgery, participating groups, lymphovascular space invasion, and age. The median follow-up and IQR was estimated with the reverse Kaplan-Meier method. This study is registered with ISRCTN, number ISRCTN14387080, and ClinicalTrials.
Vaginal brachytherapy was given to 309 (47%) of 660 patients: 151 (46%) of 330 patients on chemoradiotherapy and 158 (48%) of 330 on radiotherapy alone. In the chemoradiotherapy group, concurrent cis platin was completed by 304 (92%) of 330 women, adjuvant carboplatin by 262 (79%), and adjuvant paclitaxel by 233 (71%). At least one dose reduction of cisplatin (to 40 mg/m²) was recorded for five (2%) patients, of carboplatin (from AUC5 to AUC4) for 36 (11%) patients, and of paclitaxel (from 175 mg/m² to 135 mg/m²) for 50 (15%) patients. At the final database lock (Nov 29, 2018), 150 patients had died (65 in the chemoradiotherapy group and 85 in the radiotherapy alone group) and 189 patients had a failure-free survival event (84 in the chemoradiotherapy group and 105 in the radiotherapy alone group).
Application of this principle implies that the treatment effect for overall survival can be considered significant. Better selection of women for adjuvant treatment might be achieved by integration of molecular characteristics. For intermediate-risk endo metrial cancer, an improved risk assessment was reported with an integrated profile of clinicopathological and molecular risk factors. 30 This approach is currently being tested in the randomised PORTEC-4a trial (NCT03469674). A pilot study of the TransPORTEC consortium showed that determination of the molecular subgroups as described by the Cancer Genome Atlas Group 27 also improved risk assessment in high-risk endometrial cancer. Translational research is being done on tumour tissue samples donated by PORTEC-3 participants as part of an international collaboration.
Acknowledgments The  PORTEC-3 study  was supported by a grant from the  Dutch Cancer Society  ( UL2006-4168/CKTO 2006-04 ), the  Netherlands. PORTEC 3 was supported in the UK by  Cancer Research UK  ( C7925/A8659 ). Participation in the PORTEC-3 trial by the  Australia and New Zealand Gynaecologic Oncology Group (ANZGOG)  and the  Trans-Tasman Radiation Oncology Group (TROG)  were supported by the  NHMRC  Project Grant  570894 (2008 ) and by a  Cancer Australia  Grant (awarded through the  2011 round of the priority-driven Collaborative Cancer Research Scheme  and funded by  Cancer Australia ). Participation by the  Italian MaNGO group  was partly supported by a grant from the  Italian Medicines Agency AIFA  ( FARM84BCX2 ). Canadian participation in the PORTEC-3 trial was supported by the  Canadian Cancer Society Research Institute  (grants # 015469  and # 021039 ).
Patient Selection Clinical data and samples from patients with nsCLP and their family members were collected in collaboration with the Centre Labiopalatin, Cliniques Universitaires St Luc, Brussels, Belgium and Amiens-Picardie Hospital, France. Informed consent was signed by each participant prior to conducting the study, as approved by the institutional review board. For each patient, a standardized questionnaire was filled in, notably detailing family history and clinical phenotype. The CLP phenotyping was based on clinical examination by the plastic surgeon while evaluating the infant before surgery and follow up, and on the questionnaire. Eight patients who met the clinical diagnosis of non-syndromic discontinuous CLP were selected and included in the study. This comprises 6 sporadic cases and 1 with a familial history of CL/P (Table  1 ).
Whole Exome Sequencing DNA was extracted from blood samples using the Wizard®Genomic DNA Purification Kit (Promega). WES was carried out using 1 µg of genomic DNA per sample. Exomes were captured using a commercial enrichment kit (Agilent SureSelectXT Human All Exon KitV5) and enriched libraries were sequenced on an Illumina Hiseq2000. Generated reads were aligned to the human genome build hg19 using Burrows-Wheeler Aligner (BWA) 0. 7. 15. Data processing and variant calling were performed with Picard 1. 107, Genome Analysis Toolkit 3. 3 package (GATK), respectively. The generated variant files (. vcf) were imported into a database and further analyzed using Highlander 14. 10. 3, an in-house bioinformatic framework for variant annotation, filtering, and visualization  [10]. We considered rare variants as those with a frequency below 0.
5% in public databases: Genome Aggregation Database (gnomAD)  [11] , Exome Aggregation Consortium database (ExAC)  [12] , 1000 Genomes  [13]  and Genome of the Netherlands (GO-NL  [14] ) and in our in-house control database. As "likely pathogenic" variants, we considered those with a high impact (canonical splice-site variants and those generating a premature termination codon = PTC (Premature Termination Codon: out-of-frame indels and nonsense variants), or a moderate impact (non-synonymous), as annotated by SnpEff 4. 1 and a combined annotation dependent depletion (CADD) PHRED score >15. Missense variants were considered as possibly pathogenic only if predicted to be possibly/probably damaging in at least three out of seven in silico variant classifiers (Sift, Polyphen, Likelihood Ratio Test (LRT, Mutation Taster, Mutation Assessor, Functional Analysis through Hidden Markov Models (FATHMM, DEOGEN (a variant effect predictor that could handle both missense SNVs and in-frame INDELs)).
Patient F1-3 The proband is the only child of an unrelated Caucasian couple with an unremarkable family history. She was born at 37 weeks of gestation (WG) with birth weight BW = 3070 g and birth height BH = 47 cm. She had a right labioalveolar cleft lip associated with a submucous cleft. At 11 years and 3 months of age, she has had no specific follow-up, and thus undetermined reproductive axis and olfactory clinical status. We identified a 2 bp insertion (c. 1711_1715delinsTACT: NM_023110. 2) in the FGFR1 gene. This variant was not found in her mother, and DNA from the father was not available (Figure  2  F1 ). This variant leads to a frameshift and a premature termination codon (PTC) at position 571 (p. Glu571Tyrfs*61: NP_075598). This insertion is not known in gnomAD v2. 1. 1  [11]. The gene is intolerant for loss of function (LoF) mutations, evidenced by a probability of being Lof intolerant (pLI) value of one, with four unique predicted truncating alleles out of the 258,000 in the database.
Acknowledgments: We are grateful to all the family members for their invaluable contributions. The authors thank  National Lottery, Belgium and the Foundation against Cancer  ( 2010-101 ),  Belgium  for their support to the  Genomics Platform of University of Louvain and de Duve Institute , as well as the  Fonds de la Recherche Scientifique -FNRS Eguipment Grant  U. N035. 17 for the «Big data analysis cluster for NGS at UCL». We also thank la  Biobanque de Picardie  - BB-0033-00017 -and the  Facing Faces Institute.
In contrast, dv/v calculated in the 0. 1-0. 4 Hz frequency band reaches a maximum around June (around 6 weeks later than for the high frequencies), decreases over ~6 weeks, and then stays low before starting to increase in November. These patterns are generally consistent across the entire Northern Volcanic Zone, although in the south of the region-around the Vatnajökull ice cap, and close to the coast-trends are more varied (fig. S9 ). To investigate the seasonal pattern in dv/v, we compare to weather data from the Icelandic Meteorological Office's (IMO's) reanalysis using the numerical weather prediction (NWP) model HARMONIE-AROME for the period August 2008 to June 2017  (25). This is downscaled from the ERA-Interim reanalysis, a global dataset of atmospheric parameters updated in real time.
Measuring dv/v We used data from 51 broadband, three-component seismometers across the Northern Volcanic Zone: 35 stations from the University of Cambridge's network, 18 stations from the national network of the IMO, 2 from University College Dublin, and 1 from the British Geological Survey. The average station elevation is 700-m above sea level. The data were stored in day-long miniSEED files at 50 or 100 Hz. We used the program MSNoise to measure dv/v in five frequency bands: 0. 1-0. 4 Hz, 0. 4-1. 0 Hz, 1-2 Hz, 2-4 Hz, and 4-16 Hz. Before filtering, the data were preprocessed by resampling to 10 Hz for the four lower frequency bands and 50 Hz for the higher frequency band. Here, we calculated NCFs between the different components at the same station ["single-station cross-components," east-north (EN), east-vertical (EZ), and north-vertical (NZ)].
Acknowledgments: We thank  S. Steinþórsson ,  B. Brandsdóttir , and others who assisted with fieldwork in Iceland, and  D. Egilson ,  G. Olivier ,  T. Lecocq ,  J. Smith ,  T. Hudson ,  O. Volk ,  R. Green , and others for the helpful discussions. Software used includes MSNoise (msnoise. org),Coulomb 3. 3 for strain modeling, SWAMI codes ( Rix & Lai ) for calculating phase velocities of surface waves, and  Computer Programs in Seismology (Hermann)  for calculating depth.
InDeal is a project funded by the Horizon 2020 Framework Program (topic: H2020-EE-2015-2-RIA) of the European Union under grant agreement no. 696174. The project brings together a number of organizations from different sectors (Table  1 ), such as research organizations with expertise in control, machine learning, materials and energy harvesting, industrial partners with wide experience in software development, smart meters and system integration, as well as district heating and cooling services providers. Real case studies will be hosted by two network operators in France and Slovenia in order to test the sub-systems and the final system of InDeal under operational conditions. A number of recent studies  [6] [7] [8]  emphasize that Europe's district heating and cooling systems must undergo a radical change into low-temperature district heating networks interacting with low energy buildings, as well as becoming an integrated part of smart energy systems.
Web-Based Platform Net Technologies (NET) presented the progress over the development of the Central Monitoring and Control web Platform (CMCP) which hosts and visualizes all the different subtools and systems developed within the project. The goal of the CMCP is to offer a unique user environment which will not only present the measurable parameters of the DHCS but will also act as a transfer mechanism between the InDeal technical solutions for energy efficiency improvements. The proposed CMCP enables the end users to clearly evaluate the benefits of adopting InDeal design and innovations into their DHC networks. The main characteristics of the CMCP are summarized, as follows: (i) It has a scalable architecture, independent of any operating and database manager system; (ii) CMCP does not depend on the end user hardware/software (computer, laptop, smart phone); (iii) it enables web based access which allows connectivity anytime anywhere; (iv) it provides notification and alarming functionalities based on user needs and user access rights; (v) it integrates statistical and reporting functionalities and (vi) it is based on a security-enabled and privacy-enabled design in order to guarantee the confidentiality of the access and data within the platform.
Life Cycle Analysis IZNAB performed a life cycle assessment (LCA) study in order to provide detailed data about the environmental, economic and social impact of the InDeal project's solutions. The impact assessment was divided in two parts: (i) Analysis of the environmental and economic impact comparing the new cellulose nano-fiber insulation material with the most commonly used PUR insulation and (ii) analysis of the environmental, economic and social impact of DHC plants (in Vransko and Montpellier). To assess the impact of DHC plants' data with respect to emissions, used fuels, distributed H&C power were provided by the plants' operators (ENERGETIKA and SERM) and further analyzed by IZNAB using specialized LCA software-SimaPro  [14]. The comparison was performed with the data obtained before and after the implementation of the InDeal solution in both real case study plants.
Regarding the insulation material NAITEC, that is responsible for its development and testing, provided data about the materials and the energy used in the production process, their cost, as well as information about the waste generated during the production. IZNAB analyzed the data and compared it with the production process of PUR materials for pre-insulated pipes also using the SimaPro software. The social impact assessment of the InDeal system was carried out focusing on three stakeholder categories: Workers, value-chain actors, and local communities. The analysis for Vransko and Montpellier case-studies revealed that the risk of undesired impact is low (or even very low) and that the impact of the InDeal technology may be further strengthened in the future to achieve higher levels of energy efficiency.