dataesr/scientific-paragraphs-categorization huggingface dataset:
During geometry optimization procedure constraints were imposed on all of the atoms replacing or constituting protein backbone atoms. Four mentioned models differ only in the manner of protonation of pyrophosphate anion and His292. The protonation mode of protein residues and molecules covered by the models was assigned based on the results from the Propka 3. 1 program and visual inspection  [41, 42]. For the model without Mg 2+ Propka 3. 1 suggested double protonation of pyrophosphate (in model with Mg 2+ bound according to Propka. 3. 1, pyrophosphate should not be protonated -charge -4) and neutral charge of His292. Therefore, for pyrophosphate two possible protonation states were considered, compare models 1 and 3 (pyrophosphate protonation labeled as v1) with models 2 and 4 (pyrophosphate v2) in Figs.
MD Methods MD simulations were performed for the ATPS-APS-Mg 2+pyrophosphate complex in order to model the structure with bound magnesium ion, and check its coordination mode in the enzyme active site. The starting structure of ATPS hexamer was build with the help of the PISA server, based on the 1G8H crystal structure solved for ATPS dimer, as it was suggested by Ullrich et al. [22]. Lacking Met1 residue in each subunit was modeled with Modeller program  [43, 44]. Protonation states of residues of hexamer were evaluated using Propka 3. 1 program and visual inspection  [41, 42]. Parameters for all protein residues were applied from the AMBER FF03 force field, using AMBER 12 package  [45, 46]. Parameters missing in the AMBER force field were derived from QM calculations. In APS molecule, only phosphosulfate moiety was parametrized completely, while for adenine and ribose groups all parameters besides partial charges were taken from parameters available in the AMBER force field for ATP molecule.
Figs. 10, 11 and 12 present fragments of studied models with denoted distances and angles critical for the reaction. In the optimized structure of ATPS-APS-PPi complex the O1-P1-OH1 angle equals 57. 0 ∘ , 81. 7 ∘ and 79. 2 ∘ , in models MG, 1 and 2, respectively. In the crystal structure (PDB code: 1G8H), the O1-P1-OH1 angle equals 80. 15 ∘ , revealing much better agreement with the corresponding angle in models 1 and 2 than in model MG. However, in all studied models the angle between the atoms directly involved in the SN-2 reaction of cleavage of O1-P1 and formation of P1-OH1 bond remains rather far from the most favorable straight angle. The conformation of APS, similar in each model, causes formation of highly energetic hypervalent structure in the ATPS-TS2 transition state complex. In the ATPS-TS2 optimized geometries (Figs.
Moving along the reaction coordinate, the first shell ligands of Mg 2+ change its geometry from trigonal bipyramid (Mg 2+ coordinated by O7, O9 and O11 ATP phosphate oxygen atoms, Asn198 and water molecule) in E-S, via distorted trigonal bipyramid (Mg 2+ coordinated by O7, O11, O13 phosphate oxygen atoms, Asn198 and water molecule) in E-TS1 to tetragonal bipyramid (Mg 2+ coordinated by O7, O9, O11, O13 phosphate oxygen atoms, Asn198 and water molecule) in E-P complex (Fig. 6 ). Such a rearrangement around magnesium ion is presumably responsible for the high energy barrier of 48. 3 kcal/mol obtained for this process. Since the studies performed for model of active site binding Mg 2+ revealed that magnesium ion might rather inhibit than catalyze ATPS reaction, the work was extended to four models deprived of Mg 2+ , constructed based on the crystal structure solved for ATPS complex with APS and PPi, where the magnesium was not observed in the active site (PDB code: 1G8H,  [22] ).
Dryline climatologies (i. e. , the study of their frequency, spatial distribution, relation to diurnal and seasonal cycles, and associated synoptic conditions) have also been studied over different regions using different datasets and detection criteria. Usually, a conservative moisture variable is utilized to identify the dryline-either specific humidity or mixing ratioalthough some works use near-surface dewpoint temperature. In addition, conditions over the temperature field are often included to eliminate surface fronts, and on occasions, a wind shift across the dryline is required. Some studies  (Owen 1966; Hoch and Markowski 2005; Schultz et al. 2007 ) use surface observations to manually detect drylines. Based on this approach they found that drylines are observed over the U. S. Great Plains on 32%-45% of the spring season days (April, May, and June).
a. Data This study uses the ERA-Interim reanalysis over the period 1979-2016  (Dee et al. 2011). Reanalysis data are chosen in the present work due to the lack of a dense surface observation network over the area of interest. ERA-Interim incorporates satellite data with a high spatial and temporal resolution, allowing a good representation of the atmospheric state, even over conventional data scarce areas. The reanalysis data are available at 6-h intervals in 27 pressure levels ranging from 1000 to 100 hPa, and in a horizontal grid spacing of 0. 58. Data for surface heat and moisture fluxes are taken from the 6-h forecasts verifying at the same time as the analysis. ERA-Interim assimilates surface observations of temperature, humidity and pressure over land making it particularly attractive for the representation of nearsurface processes like those associated with the development of drylines.
Acknowledgments. The authors thank the editor, two anonymous reviewers and  Rene Garreaud  for their constructive and insightful suggestions to improve the manuscript. This research was supported by the  PICT 2013-1299 ,  PICT 2014-1000 ,  PICT 2017-0221 ,  PICT 2017-2233 ,  UBACyT   20020130100618BA ,  UBACyT   20020170100164BA , and  UBACyT20020170100504BA  projects.
, 2018). The results of our participation are quite encouraging. Regarding the Relaxed Partial metric, our run achieves 80. 26% in average for the four languages and the two topics that compose the test collection. In order to present comparative results against the state of the art, we run experiments using two extra datasets under the standard CoNLL evaluation setup. The remainder of this paper is organized as follows: Section 2 introduces the related work while Section 3 presents the proposed multi-lingual model. Section 4 presents the results while conclusions are drawn in Section 5.
Experimental Setup We follow the configuration setup proposed by the task organizers. Two topics, "nord stream" and "ryanair", were used to test our models. These topics include 1100 documents in the four languages. Further details can be found in the 2019 shared task overview paper  (Piskorski et al. , 2019). For training, we have used the documents provided for the task but also the ones in Czech, Polish, and Russian from the previous round of same task in 2017  (Piskorski et al. , 2017). We additionally added the training example form the CoNLL2003 (Sang and De Meulder, 1837) collection in English (13879 train, 3235 dev, and 3422 test sentences). Used metrics include the officially proposed metrics and standard metrics for the CoNLL2003 dataset (F1 metric).
Unofficial Results In order to compare our system to the state-of-theart, we have evaluated our architecture using the CoNLL2003 dataset. Our results using two and six layers are presented in Table  2. Note that English is not part of our target languages. So, an underperformance of 2. 5 is acceptable in our system 8. It is also worth nothing that the use of more BERT layers increases our results. However, the amount of memory used is also increased manifold. We set the number of layers (hyperparameter) to two layers due to our computation constraints despite the downgrading in performances for English. The number of epochs (hyperparameter) was set using the BSNLP2017 dataset (for ru, cs, and 7 6 out of 8, with differences smaller than 0. 4 points. 8 More experiments using BERT English-only model will be performed in our future work.
pl) combined with CoNLL2003 as a validation set of our final models. Results for these combined datasets are presented in Table  3. Surprisingly, our results seem very similar independently of the fastText embedding. It suggests that our architecture is able to generalize the prediction for several target languages. Note that the worst results are obtained by the Bulgarian model, but no test examples were included for this language. In contrast, we believe that the examples provided in other languages were rich enough to help the predictions (also in English).
While CAR T cells are rationally designed, targeted therapies, they nevertheless frequently induce life-threatening toxicities that can be mitigated by planning and proper hospital organization. Comprehensive training should be provided to all categories of personnel includ-ing scientists, nurses and physicians, and close collaboration with a range of other specialists, especially intensive care unit staff and the neurology/neuroimaging services, is required. 11, 12 s CAR T cells represent a novel class of therapy and as both of the currently available products have only been evaluated in phase II studies to date, close post-marketing surveillance is mandatory. The EMA has endorsed the use of the European Blood and Marrow Transplantation (EBMT) registry for the collection of 15-year follow-up data on treated patients in order to ensure that evaluation of the efficacy and safety of commercially available CAR T cells continues on an ongoing basis.
76 In March 2019, the EBMT received a qualification opinion from the EMA which found the cellular therapy module of the EBMT registry to be fit-for-purpose for the regulatory overseeing of pharmaco-epidemiological studies concerning CAR Tcell therapy. 77  modified version of the MED-A cell therapy form will be used for CAR T cells and other academic-or industrymanufactured cell therapies. The data submission time points are day 0, day +100, 6 months, and annually thereafter. This module has already proven to be effective in capturing basic data sets on academic and commercial CAR T-cell infusions, although the EMA has requested additional safeguards during data capture for regulatory purposes. However, the current minimal data set requested by the EMA for commercial products does not require detailed product information such as CD4 and CD8 ratios or transduction efficiencies, as companies consider these to be sensitive proprietary information.
Agreed access to a more detailed data set regarding products being evaluated in clinical trials might benefit all those working in the CAR T-cell research field. In the USA, the FDA has implemented product-specific Risk Evaluation and Mitigation Strategy (REMS) programs. In parallel, the National Cancer Institute-funded Moonshot Initiative program called Cellular Immunotherapy Data Resource, awarded to the CIBMTR in October 2018, will allow for the collection of real-world data. In recent years, the EBMT has worked with the CIBMTR to develop common data collection policies so the prospect of robust global datasets on the efficacy and safety of CAR T-cell therapies is on the horizon. It is expected that patients receiving CAR T-cell therapies in both investigator-led and pharma-sponsored trials might also have their follow-up data collected in the EBMT registry.
In order to address concerns that pharmaceutical companies may have about the confidentiality of commercially sensitive clinical data, trial data reported to the EBMT registry can be embargoed until investigating centers decide to make such data accessible to the public. Early data collection might also create a virtuous circle whereby knowledge of increased activity might help those lobbying for an improved infrastructure for CAR Tcell therapies across Europe in terms of funding opportunities, regulatory frameworks, and, ultimately, commercial drug approval. EMA approval for the use of the EBMT registry also places certain responsibilities on the EBMT. As a formal data controller, the EBMT will need to guarantee a fair and transparent mode of data sharing in order to improve the assessment of the many different agents and ultimately to improve our knowledge on how best to use CAR T-cell therapies.
loa counts of 50 000 mf/mL  [3]. As the benefits of treatment were considered to outweigh the risk of SAEs, coendemic areas with high onchocerciasis prevalence were nevertheless targeted for MDA with ivermectin, although fear for SAEs sometimes resulted in low treatment coverage  [6]. However, coendemic areas with low onchocerciasis prevalence have remained untreated to date and might be in need of alternative strategies. To understand the need for and feasibility of alternative strategies for onchocerciasis elimination in loiasis-endemic areas, we assessed the extent of coendemicity and estimated the number of coinfected individuals, including people with such high L. loa mf intensity levels that ivermectin treatment is considered unsafe. We combined empirical data using multiple sources with statistical and mathematical models to estimate how the number of onchocerciasis, loiasis, and coinfection cases change over time since precontrol levels up to 2025.
2017; Hartmann, Rodr ıguez de la Vega, et al. 2018; Mohd-Assaad et al. 2018; Schirrmann et al. 2018) , which points to particularly strong and recurrent selection events in the inversion regions. In conclusion, our study provides important insights into the process of ecological divergence showing lower gene flow and more selection footprints in autosomal inversions, suggesting a role of rearrangements in protecting from recombination beneficial combinations of alleles. The most exciting finding was the unexpected higher gene flow on mating-type chromosomes, in striking contrast with the consistent and widespread opposite patterns found in sex chromosomes of plants and animals. The higher gene flow on mating-type Higher Gene Flow in Sex-Related Chromosomes. doi:10. 1093/molbev/msz252 MBE evidence of the history of gene flow between strains, we used the program SplitsTree  (Huson 1998; Huson and Bryant 2006)  that performs a neighbor-net tree.
Comparison of Diversity and Divergence between Autosomes and Mating-Type Chromosomes To compare diversity and divergence statistics from SNP data between autosomes and mating-type chromosomes, we used only strains with haploid sequenced genomes (i. e. , genomes of one single mating type) and performed SNP calling separately for a 1 and a 2 mating-type genomes using the MvCa-1250 reference genome of the corresponding mating type. Using only haploid genomes limits SNP quality bias and the need of genome phasing on the highly dimorphic and heterozygous mating-type chromosomes, in contrast to the highly collinear and homozygous autosomes. For the a 1 mating type, we studied 11 individuals having their a 1 haploid genome sequenced (supplementary table S1, Supplementary Material online) and performed read mapping and SNP calling against the MvCa-1250-A1 genome.
To compare mutation rates on autosomes and mating-type chromosome, we computed pairwise values of nonsynonymous divergence (d N ) and synonymous (neutral) substitution rate (d S ) between orthologous gene sequences of either the MvCa-1250 or the MvCa-Vir-1441 strain on the one hand, and the MvSv-1253 M. lagerheimii strain on the other hand, with the latter species having mostly recombining matingtype chromosomes  (Branco et al. 2017 , 2018 , Carpentier et al. 2019). We focused on the a 1 mating-type chromosome and therefore used the a 1 haploid genome assemblies for the three studied strains (MvCa-1250-A1, MvCa-Vir-1441-A1, and MvSv-1253-A1). We aligned orthologous gene sequences using the codon-based approach implemented in translatorX with default parameters  (Abascal et al. 2010 ) and used the nucleotide alignment as input in the yn00 program in the PAML package  (Yang and Nielsen 2000; Yang 2007 ).
We studied only orthologous groups with a single gene copy in each of the three studied genomes. We computed 6, 535 (resp. 6, 531)  pairwise values for the MvCa-1250-A1 versus MvSv-1253-A1 (resp. MvCa-Vir-1441-A1 vs. MvSv-1253-A1) comparisons. We computed the RND  (Feder et al. 2005; Rosenzweig et al. 2016) , a statistics allowing mitigating the potential confounding effect of different mutation rates on mating-type and autosomal chromosomes, by comparing the divergence between clusters to the distance to an outgroup. To compute RND, we used a customized script and as outgroup the a 1 or a 2 haploid genome assemblies of MvSv-1253 M. lagerheimii strain. For each strain of the MvCa and MvVi genetic cluster, we computed the absolute distance with the outgroup using the dist. dna() function and the F84 model in the R package {ape}  (Paradis et al.
Acknowledgments We are grateful to  Mike Perlin  and  Janis Antonovics  for providing anther-smut fungal strains and the Genotoul platform for sequencing. We thank  Antoine Branca ,  Jeanne Ropars , and  Quentin Rougemont  for help with analyses and  Alodie Snirc  for providing assistance in the laboratory. Janis Antonovics ,  Higher Gene Flow in Sex-Related Chromosomes. doi:10. 1093/molbev/msz252MBE.
RESULTS Study population included 404 840 people (mean age 45. 5 years, 57. 7% women) who were initially free of dementia, had a measurement of physical inactivity at study entry, and were linked to electronic health records. In 6. 0 million person-years at risk, we recorded 2044 incident cases of all-cause dementia. In studies with data on dementia subtype, the number of incident cases of Alzheimer's disease was 1602 in 5. 2 million person-years. When measured <10 years before dementia diagnosis (that is, the preclinical stage of dementia), physical inactivity was associated with increased incidence of all-cause dementia (hazard ratio 1. 40, 95% confidence interval 1. 23 to 1. 71) and Alzheimer's disease (1. 36, 1. 12 to 1. 65). When reverse causation was minimised by assessing physical activity ≥10 years before dementia onset, no difference in dementia risk between physically active and inactive participants was observed (hazard ratios 1.
3 and 2. 2 for diabetes, 2 and is 1. 3 for coronary heart disease 3 and 2. 2 for stroke  4  ). On the basis of this indirect evidence, the expected hazard ratio for the association of physical inactivity with dementia would be negligible, varying between 1. 05 and 1. 14 (see appendix, page 2). ] [10]  This means that physical inactivity assessment was undertaken during the preclinical or prodromal stage of dementia, which is characterised by a decline in physical activity. 11 12 o address these uncertainties, we investigated the association between physical inactivity and dementia using individual-level data from 19 cohort studies with long follow-up for morbidity and mortality. A standard method to reduce reverse causation is to exclude outcomes occurring in the initial follow-up period. Thus, we determined the association between physical inactivity and dementia for a population with physical activity measured a minimum of 10 years before dementia onset.
Cohort selection and data extraction We conducted an individual-participant meta-analysis according to PRISMA guidelines. The 19 prospective cohort studies for which relevant data on physical inactivity and dementia were available were identified using an electronic search of the Individual-Participant-Data Meta-analysis in Working Populations (IPD-Work) Consortium,  13  the Inter-University Consortium for Political and Social Research (www. icpsr. umich. edu/ icpsrweb/ICPSR/) and the UK Data Service (http:// ukdataservice. ac. uk/) (16 January 2018). Exposure search terms were "physical activity" and "exercise" and outcome search terms "dementia," "Alzheimer's disease," and "mortality. " For additional individuallevel data, we contacted principal investigators of the IPD-Work consortium. Inclusion criteria for cohort studies were: prospective cohort study with assessment of physical inactivity at baseline; >10 year follow-up for all-cause dementia or Alzheimer's disease; and incident dementia cases recorded both during the first 10 years of follow-up and, among those free of dementia at that point, incident cases of dementia during follow-up starting from year 10.
Patient involvement This is a secondary analysis of pre-existing datasets. No patients were involved in setting the present research question, the outcome measures, or in developing plans for recruitment, design, or implementation of the study. No patients were asked to advise on the interpretation or writing up of results. The dissemination plan targets a wide audience, including members of the public, patients, health professionals, and experts in the specialty through various channels: written communication, events and conferences, networks and social media.
The 10 year threshold was chosen because studies with repeat measurements suggest physical activity in people with dementia begins to decline approximately a decade before diagnosis. 12 For comparison, similar analyses were performed for each cardiometabolic disease. To examine the robustness of the findings, we performed pre-selected subgroup analyses by sex, age (threshold 60 years), study-specific physical inactivity prevalence (threshold 40%), and method used for outcome ascertainment (electronic records from morbidity registers, mortality registers, or both). Due to smaller sample sizes in these subgroups, the analyses were based on pooled data across all cohorts rather on 13 May 2019 by guest. Protected by copyright. http://www. bmj. com/ BMJ: first published as 10. 1136/bmj. l1495 on 17 April 2019.
To assess dose-response pattern, we used a three-level physical activity measure as the exposure. Finally, to assess the association of physical inactivity with dementia in relation to cardiometabolic disease (that is, having one or more of diabetes, coronary heart disease, and stroke), we created two dementia endpoints for participants with no cardiometabolic disease at baseline and no dementia at year 10: (a) incident cardiometabolic disease followed by incident dementia and (b) incident dementia without preceding cardiometabolic disease. We tested whether physical inactivity was differently associated with these outcomes using the χ 2 test (see appendix, pages 7-8). 35 n these analyses, pooled data were used. We used SAS (version 9. 4) to analyse associations between physical inactivity and health outcomes separately in study-specific data.
Results Of the 9741 studies identified in the three data sources, 35 had a measure of physical activity at baseline and follow-up for dementia (fig  1 ). In 19 of these studies, the length of follow-up and the number of incident dementia cases were sufficient for analysis of dementia risk within the first 10 years and from year 10 onwards. Fourteen studies used only death certificates to ascertain dementia, and five studies had dementia ascertainment based on electronic records from multiple registers including hospitalisations and medical prescriptions in addition to mortality records. Of the 404 840 participants included, 171 336 were men and 233 504 women. Mean age at study entry was 45. 5 years (range of mean ages across cohorts 36. 7 to 54. 3), and the prevalence of physical inactivity was 40.
In participants above 60 years of age (mean age 70. 8, standard deviation 7. 6), for example, we recorded 606 dementia cases during the first 10 years of follow-up and 889 cases from year 10 onwards. The mean age at diagnosis was 84. 8 years (standard deviation 6. 7) during the first follow-up period and 86. 7 years (SD 6. 3) during the later period, and the  The result was not affected by the method of dementia ascertainment (fig  4 ). With morbidity data (that is, ascertainment of dementia using linked records of hospitalisations and reimbursements for medical treatment of dementia), the hazard ratio for physical inactivity was 1. 51 (1. 07 to 2. 14) in the first follow-up period and 0. 97 (0. 76 to 1. 22) in the later period. The corresponding hazard ratios were 1. 41 (1. 18 to 1. 69) and 0.