dataesr/scientific-paragraphs-categorization huggingface dataset:
Discussion We have set-up a unified genomic platform, available at https://bigsdb. pasteur. fr/bordetella/, by merging the data from the two previously existing PubMLST and Pasteur BIGSdb-Bordetella databases. This merger has enabled allelic nomenclature unification and has led to reassemble on the same platform, genotyping schemes that will facilitate the study of Bordetella diversity at different phylogenetic breadths. We have also expanded the genomic library with public sequences and sequenced genomes from the French NRC. The resulting unified platform for Bordetella genotyping will ease the future curation and expansion of Bordetella genomic data by a community of users and curators. Two complementary cgMLST schemes are available on the genomic platform. While the cgMLST_genus scheme should be preferred for genus-wide phylogenetic analyses and within individual species including B.
Regarding the phylogenetic structure of Bordetella, we provide a complete picture of the relationships among the 16 Bordetella species that have current standing in the Prokaryotic taxonomy, and confirm the existence of approximately the same number of additional putative species (  [21] ; PRJNA385118). This work shows that the taxonomy of the Bordetella genus will need future updates, and the unified Bordetella genomic library should facilitate the recognition of strains belonging to the same putative novel Bordetella taxa, thereby enhancing knowledge of their microbiological, ecological or pathogenic properties. An important finding of this work is the identification of a novel B. bronchiseptica lineage, which we provisionally named Bbs lineage II. This lineage is clearly distinct from the classical Bordetella, which we therefore propose to define strictly as the BbGS, i.
This scheme thus provides a convenient way to distinguish 'out of China' dissemination of the fhaB3 sublineage, from parallel evolution of macrolide resistance in other locations. An important current limitation of the genomic library is its contents imbalance towards genomic sequences from acellular vaccine-using high-income countries, as observed for other pathogens  [62] : our database contained only few genomes from Africa (0. 2 %), Asia (1. 9 %) or Oceania (2. 1 %) as compared to those from North America (13. 6 %) or Europe (58. 7 %). In the future, efforts should be made to generate and incorporate more genomic sequences from world regions that are currently underrepresented. In conclusion, the unified Bordetella genomic library was built with the intention to facilitate and harmonize the genotyping of strains of this important bacterial genus, and should represent a useful tool even for genomic epidemiology consortia unfamiliar with genomic analyses.
Leaves are labelled with the identifier of the strain in the BIGSdb database, followed by the strain name. The analysis was performed with 186 B. bronchiseptica genomes, and representatives of the phylogenetic diversity of B. pertussis (9 genomes) and B. parapertussis (9 genomes). The recombination-purged concatenated multiple sequence alignment of 1,415 core gene loci (cgMLST_genus scheme) was used. The tree is rooted on lineage II, which is the most divergent clade. Branch lengths were not used in order to ease readability of groups and isolates; see Figure  S5  for the corresponding phylogram. For each isolate, the host is represented using a leaf symbol, where available (see key in Figure  S5 ). The numbers corresponding to T3SS sequence types are indicated along the external circle around the tree; only the identifiers of main T3STs are indicated.
Funding information This work was supported financially by the  French Government 's  Investissement d'Avenir program Laboratoire d'Excellence "Integrative Biology of Emerging Infectious Diseases"  ( ANR-10-LABX-62-IBEID ). BIGSdb development is funded by a  Wellcome Trust Biomedical Resource  grant ( 218205/Z/19/Z ). This work used the computational and storage services provided by the  IT department at Institut Pasteur. The National Reference Center for  Whooping Cough  and other Bordetella Infections is supported by  Institut Pasteur and Santé publique France (Public Health France ).
All temperatures given in this paper are the sample temperatures, i. e. , the temperature measured on the graphite matrix plus 60 • C  [15]. The microstructures were studied by means of scanning electron microscopy (SEM) using back-scattered electron (BSE) imaging (FEI, Hillsboro, OR, USA) and in transmission electron microscopy (TEM) (JEOL, Tokyo, Japan). Quantitative microstructural data were extracted from SEM micrographs by using the ImageJ software. The grain size was evaluated by considering the diameter of a circle with the same area as the grain. TEM thin foils were prepared by standard jet polishing using the A3 electrolyte commercialised by Struers, Cleveland, OH, USA, at -10 • C with a current of 500 mA and a voltage of 90 V. TEM investigations were performed on a JEOL 2010 operating at 200 keV.
Local chemical compositions were measured by energy-dispersive X-ray spectroscopy (EDS) in the SEM and TEM (using the STEM mode for Scanning Transmission Electron Microscopy) and will be given in at. % in the following. X-ray diffraction (XRD) measurements were conducted on an AXS D8 advance diffractometer from Bruker, Billerica, MA, USA, using CuK α radiation. From these measurements, the volume fractions of the occurring phases were determined by Rietveld analysis utilizing the software MAUD (version 2. 97)  [26]. In order to determine the microstructural evolution during the SPS densification of the TNM + alloy, heat treatments were performed on a dilatometer of type 805A/D from Thermo Fisher, Waltham, MA, USA. This was carried out to precisely control the sample temperature in accordance with the temperature profile of the SPS process, as well as to quench the sample to room temperature to preserve the high-temperature microstructure.
Three test specimens, suitable for tensile tests at room temperature and at 800 • C (strain rate 10 -4 s -1 ) as well as for creep experiments, were machined from each SPS processed billet. Concerning the tensile tests at room temperature, the following data were extracted from the curves of the true stress as a function of the true elongation: -Yield strength: stress at which plastic deformation starts and defined as the stress at 10 -3 % plastic elongation; -R0. 2: the tensile stress at 0. 2% plastic elongation; -UTS: ultimate tensile stress; and -A: plastic elongation at rupture. The cross-sections of the fracture surfaces of the specimens broken during tensile tests were analysed by SEM. To observe the dislocation microstructures present in these samples, TEM thin foils were extracted from disks cut perpendicularly to the tensile axis.
However, in the case of the TNM alloy densified at 1300 • C, β o phase is only present in a few specific parts of the microstructure, arising from heterogeneities in the powder particles (Figure  1a ). the γ lamellae can be found in one lamellar grain and that one of them appears to be largely predominant, as a result of the lamella precipitation process  [28]. Three test specimens, suitable for tensile tests at room temperature and at 800 °C (strain rate 10 -4 s -1 ) as well as for creep experiments, were machined from each SPS processed billet. Concerning the tensile tests at room temperature, the following data were extracted from the curves of the true stress as a function of the true elongation: -Yield strength: stress at which plastic deformation starts and defined as the stress at 10 -3 % plastic elongation; -R0.
Introduction Maternal mortality, a key indicator of the quality of maternal healthcare, is at historic lows in high income countries. 1 Most of these countries seem to be in stage IV or V of the obstetric transition, in which maternal deaths are mostly due to extra-obstetrical conditions. 2  International comparisons of maternal mortality are important as they can highlight national similarities or differences, both of which are valuable for determining priorities in maternal health. Cause specific profiles of doi: 10. 1136/bmj-2022-070621 | BMJ 2022;379:e070621 | the bmj maternal mortality provide warnings about the quality of maternal care in particular conditions. ] [5]  Historically, cross country comparisons of maternal mortality have been based on data from vital statistics offices, based on death certificates.
2] [13]  For example, because countries with the least advanced case ascertainment methods are likely to miss the most cases, they may paradoxically seem to have the lowest maternity mortality ratios. 6 7 n response to these major limitations, several countries have implemented enhanced surveillance systems for maternal mortality to optimise and standardise the successive steps of identifying, documenting, classifying, and learning lessons from every maternal death. 14 We hypothesised that these enhanced systems ensure that intercountry variability of maternal mortality is not due to differences in data collection methods and that they provide reliable and comparable data. The International Network of Obstetric Survey Systems (INOSS), an international collaboration of researchers and clinicians collecting population based data on severe maternal complications and rare diseases in pregnancy, offered the opportunity to gather and compare such data.
Methods study design and data sources Eight countries collaborating in the INOSS and using enhanced surveillance systems for maternal mortality participated in this descriptive population based study: Denmark, Finland, France, Italy, the Netherlands, Norway, Slovakia, and the UK. 15  We defined enhanced surveillance systems as those with specific prerequisites for the three essential steps of this process: the identification, documentation, and review of maternal deaths. For the first step, completeness of case identification must be ensured by at least one type of linkage between the death register and one of the following: birth register, pregnancy loss register, and hospital discharge database. We considered the Dutch system to be enhanced despite the lack of linkage for the identification of women who died (prevented by data privacy regulations).
Because the Netherlands is a relatively small country where reporting of maternal deaths up to one year after the end of pregnancy is mandatory, we considered its maternity mortality surveillance system "possibly enhanced" and included its data in this analysis. The   1  describes the main features of the enhanced surveillance system in each participating country. Full protocols are published elsewhere. 5 16-21 llected data We collected the most recent aggregated and complete dataset available at the time of the study design from a time period that varied according to the number of births in each country: a three year period for France, Italy, and the UK and a five year period for Denmark, Finland, the Netherlands, Norway, and Slovakia. The Finnish data cover deaths from 2008 to 2012, and the other countries provided data from 2013 and after (table  2 ).
We also calculated maternal mortality ratios up to one year for countries where enhanced surveillance of maternal mortality was conducted for late deaths. We calculated age specific maternal mortality ratios and those for women with migrant or minoritised ethnic backgrounds (based on current citizenship, country of birth, or ethnicity) for each country. For age, we also calculated the pooled relative risks and 95% confidence intervals of death by maternal age group, including data from all the countries that used linkage for case identification, with women aged 20-29 as the reference group, using a random effects meta-analysis model with inverse variance weighting and the DerSimonian and Laird method. 24 inally, in each country, we calculated the proportion of each cause among all maternal deaths, as well as the cause specific maternal mortality ratios per 100 000 live births.
Data availability Data on the citizenship of women who died and the number of live births according to citizenship were available for five countries: Finland, France, Italy, Norway, and Slovakia (appendix 2). The country of birth of women who died and the number of live births according to country of birth were available for six countries: Denmark, Finland, France, Norway, Slovakia, and the UK. Maternal ethnicity of women who died and the number of live births were available for two countries: the Netherlands (ethnicity reported by healthcare providers) and the UK (self-reported ethnicity).
4. Cultivation  [48, 52, 53]. Natural samples (e. g. , shell fragments, ooids) harboring euendoliths are used to inoculate agar plates containing a chemically defined culture medium. Once single colonies grow enough to be mechanically isolated, each colony is transferred into a liquid medium and stored under specific environmental conditions. While cultivation selects heavily for fast-growing microorganisms, it is a valuable tool to confirm taxonomic identification and to investigate the life history and physiology of euendoliths  [44, 45, 54]. Cultivation also represents a necessary step to build the databases used for the identification of environmental DNA sequences  [52].
g. , species composition, abundance, biomass), and the prevalence and severity of euendolithic infestation in less-investigated marine calcifiers (e. g. , brachiopods, barnacles, limpets, snails), under different environmental conditions and timescales, and using a combination of approaches; 4. Develop a standardized experimental framework, including ex situ and in situ experiments, to evaluate and compare the modalities of euendolithic infestation and how infestation may be influenced by various abiotic and biotic parameters (e. g. , nutrient concentrations, light availability, presence of grazers and predators); 5. Determine the detrimental and beneficial effects of euendolithic infestation on live marine calcifiers, using manipulative experiments when possible; 6. Centralize available information on euendoliths (including heterotrophs) in a publicly accessible database (e.
As part of the technical validation study a series of semi structured interviews have been carried out with patients from all 4 cohorts, addressing issues such as their perceptions on the meaningfulness of mobility in their lives and the use of digital strategies to measure their mobility performance. Data from these interviews are currently being analyzed. In ongoing work multiple methods are being used, including literature reviews, focus groups, semi structured interviews, and surveys to develop a robust Conceptual Framework to support the quantitative clinical validation plan. We also intend to adopt relevant CTTI recommendations , and the approach proposed by Manta et al. (14).
Funding This work was supported by the  Mobilise-D  project that has received funding from the  Innovative Medicines Initiative 2 Joint Undertaking (JU)  under grant agreement No. 820820. This JU receives support from the  European Union 's  Horizon 2020 research and innovation program  and the  European Federation of Pharmaceutical Industries and Associations (EFPIA). Content in this publication reflects the authors' view and neither IMI nor the  European Union ,  EFPIA , or any Associated Partners are responsible for any use that may be made of the information contained herein. CM was supported by the  NIHR Sheffield Biomedical Research Center (BRC).
The first step of the screening approach consists of sorting the data and keeping only emission contributions that are relevant enough. In a second step, the method identifies, among those significant differences, the most important ones that provide evidence of methodological divergence and/or errors that can be found and resolved in at least one of the inventories. The approach has been used to compare two versions of the CAMS-REG European-scale inventory over 150 cities in Europe for selected activity sectors. Among the 4500 screened pollutant sectors, about 450 were kept as relevant, among which 46 showed inconsistencies. The analysis indicated that these inconsistencies arose almost equally from large-scale reporting and spatial distribution differences. They mostly affect SO 2 and PM coarse emissions from the industrial and residential sectors.
). Various sources of proxies are reported to create very-high-resolution inventories at the urban scale  (Zheng et al. , 2021; Geng et al. , 2017; Ramacher et al. , 2021). One of the most important challenges in compiling localscale emission inventories is remaining consistent with data provided by national inventories while providing satisfactory accuracy at all locations and times. For all these reasons, compiling emission inventories can lead to different results depending on the methods and data used. In previous work,  Thunis et al. (2016)  proposed a methodology to compare two emission estimates over a given area based on a limited input, i. e. , the total emission per pollutant and macro-sector. With this method, the differences between the total emissions of the two inventories are apportioned in terms of emission factors and activity differences.
Input data Based on a 0. 1 × 0. 1 • gridded emission inventory detailed in terms of emitted pollutants (denoted as "p") and sectors of activity (denoted as "s"), the data required for each pollutant and sector (denoted as a [p, s] couple) are twofold and consist of: -Emission totals aggregated over specific areas of interest (e. g. , urban areas, agriculture-intensive areas, industrial areas, etc. ). These areas, referred to as focal areas, can be freely selected and represent locations where we wish to assess the consistency of the inventory. The associated emissions are denoted by a lowercase notation e p,s. -Emission totals aggregated over larger areas (e. g. , country, regions, modeling domains, etc. ). In general, these areas correspond to the larger scale at which data are reported. For example, "country" is the scale of interest for EU-wide inventories, as this is the scale at which national emission totals are typically reported or estimated.
Exclusion of non-relevant emissions Not all emission data (E and e for all pollutants and sectors) are kept for the analysis. Emissions that are smaller for a given pollutant and sector are disregarded, even though differences might be large between emission estimates for those emissions. For the exclusion, we proceed as follows: for each [p, s] and each inventory, we calculate the ratio between the focal area emission (e p,s ) and its respective larger-scale pollutant total, i. e. , E p : For each [p, s] couple, the maximum values of the two inventories is then normalized by the maximum obtained over all [p, s] and over the two inventories for a given focal area: X p,s = max {inv} e p,s E p. (1) γ p,s = X p,s max p,s {X p,s }. ( 2 ) This final ratio informs on the relative importance of each [p, s] couple.
In practice, reported data were found fit for purpose for EU member states and the UK, Norway, Iceland, and Switzerland, while for other countries, alternative emission estimates were used. In addition, some further modifications were made to the dataset for which we refer to  Kuenen et al. (2022). This results in a complete emission inventory for all countries, which is then spatially distributed at high resolution using a consistent methodology over the whole domain. For the comparison presented in this paper, we use two versions of the CAMS-REG inventory for the same year, i. e. , 2015: -CAMS-REG v2. 2. 1: a version covering the years 2000-2015, based on the official reported data of air pollutants and greenhouse gases in the year 2017. -CAMS-REG v4. 2: this version covers the years 2000-2017, based on the official reported data of air pollutants and greenhouse gases in the year 2019.
2 contains, among other things, an improved split in road transport emissions between urban, rural, and highway shares, and agriculture (new proxies for manure spreading, fertilizer application based on the JRC CAPRI model;  Britz and Witzke, 2015). It also uses a new approach for agricultural waste burning, improves the pointsource database, and uses updated harmonized inland and sea shipping based on the FMI STEAM model  (Jalkanen et al. , 2009). Further details on these changes are provided in  Kuenen et al. (2022). It is important to stress that the proposed screening methodology assesses the overall consistency of the two inventory versions, i. e. , it covers the consistency of the inventory compilation itself but also the consistency of its input data (in this case, country-reported emissions).
Focal areas are defined as the functional urban areas (FUA; OECD 2012) for which emissions (e p,s ) are obtained by aggregating grid cell values. The FUA is composed of a core city plus their wider commuting zone, consisting of the surrounding travel-to-work areas. As depicted by blue shading in Fig. 3 , 150 FUAs across Europe were selected for this screening. Details on these cities are provided in  Thunis et al. (2018). The larger-scale emissions (E p,s ) are defined at country level, the level at which CAMS-REG takes the official reported data as input. In terms of pollutants, E p,s and e p,s include the following: NO x , NMVOC, PM 2. 5 , PM CO (coarse PM, calculated as the difference between PM 10 and PM 2. 5 emissions from CAMS-REG), SO 2 , and NH 3 , whereas sectors are based on the Gridded Nomenclature For Reporting (GNFR) classification.
Given the large and possibly overwhelming amount of data to analyze (many pollutants, activity macro-sectors, and cities), the first step of the screening approach consists of sorting the data for the comparison and keeping only emission contributions that are relevant enough. In a second step, the method identifies, among those relevant emissions, the most important differences that provide evidence of methodological divergence and/or errors that can be found and resolved in at least one of the inventories. Although this screen-ing does not allow checking of the quality of the inventories in an absolute way, the magnitude of the differences is often large enough to make it possible to identify one best value out of the two inventory estimates, even though the truth is unknown. The approach has been used to compare two versions of the CAMS-REG European-scale inventory over 150 cities in Europe for selected activity sectors.
Study population This retrospective study was approved by our institutional review board (CRM-1906-012). One hundred and one consecutive patients with primary glioblastoma were identified from our database over a 4-year period. They were included if they had undergone: (a) chemoradiotherapy (CRT) after surgical resection or biopsy, (b) 4 MRIs: an initial MRI at the time of the diagnosis, an immediate postoperative MRI 24-72h after surgery, an early follow-up MRI, performed in our centre 1 month after CRT completion (CRT+1) and a subsequent follow-up MRI, 3 months after CRT completion (CRT+3), (c) DSC-MRI on a 3T system, (d) progressive contrast-enhanced lesions on the CRT+1. Among these patients, 76 were excluded and the remaining 25 constituted our cohort (Fig  1 ). For each case, patient characteristics included age, gender, extent of resection, initial WHO performance status, initial tumour volume, irradiation dose, molecular markers (IDH, MGMT) and overall survival (referred as the time between the date of initial MRI and the date of death or date last known alive).