dataesr/scientific-paragraphs-categorization huggingface dataset:
Data collection, data monitoring and adverse events At each participating site, data are collected and entered into the web-based electronic case report form (eCRF) (Medsharing, Fontenay-sous-Bois, France) by trial or clinical monitors (clinical research associates) under the supervision of the site principal investigators. The trial database will be created from the eCRF. Trained research coordinators monitor data collection. The study collects demographic, baseline information at randomisation, intracerebral monitoring measured hourly on day 1 to day 5, extracerebral information on vital signs and therapies measured every 6 hours on day 1 to day 5, biological data measured every 12 hours on day 1 to day 5, adverse events during the ICU stay and functional outcome at 6 and 12 months. Several procedures to ensure data quality and protocol standardisation are in place to help minimise bias.
They include: (1) a full-day investigator meeting for all principal investigators and lead research coordinators prior to study commencement to ensure consistency in procedures; (2) a site initiation visit conducted prior to site activation to provide protocol training for all site staff; (3) if needed, training sessions in PbtO 2 management prior to site activation; (4) a detailed Oxy-TC operations manual provided for the investigators and research coordinators; (5) one or more visit as required from the project manager to each investigating site during the recruitment period to verify data sources and provide retraining as necessary; (6) centralised maintenance of the electronic database at Grenoble Clinical Research Centre and (7) for the MRI substudy, a validation of all participating sites including a quality check of MRI data, patient transport and MRI transfer procedures prior to site activation.
Statistical considerations According to the available literature,  1 23 24  including the most recent data,  25  the rate of unfavourable neurological outcome (death and severe disability) following severe TBI is 55% (ICP group). Assuming a two-sided alpha risk of 0. 05, the enrolment of two equally sized groups (148 patients per group) will have 80% power to detect a 30% reduction in relative risk of unfavourable neurological outcome at 6 months, that is, an absolute reduction of 17% in the rate of unfavourable neurological outcome. A total of 300 patients have to be recruited for the study. No interim analysis is planned. The full statistical analysis plan will be developed prior to database freeze. Data will be expressed as mean and 95% CIs, or median and IQRs where appropriate. Comparisons will be conducted on an intention-to-treat basis.
Study timescale 2014-2016: protocol design and approval from the Institutional Review Board and from the National Agency for Medicines and Health Products Safety (ANSM, Agence Nationale de Sécurité du Médicament et des produits de santé), eCRF and randomisation system building, and quality control for the MRI ancillary study. Please see administrative information in online supplementary file. 2016-2021: inclusion of patients. The first patient was recruited on 15 June 2016. 2022: 1-year follow-up of patients. 2023: cleaning and closure of the database, data analyses, manuscript writing and publication.
The usefulness of PbtO 2 monitoring in patients with TBI was recently demonstrated in a randomised trial (Brain Oxygen Optimization in Severe Traumatic brain injury, BOOST-2) where information provided by PbtO 2 appeared to help reduce the proportion of time spent with brain hypoxia. 18 Although that study was not powered for clinical efficiency, a trend towards lower mortality and better outcome was observed in the ICP + PbtO 2 group compared with the ICP group. These results prompted the authors to launch a phase III trial (BOOST-3; NCT03754114) that is open for recruitment since August 2019 using a similar methodological approach and primary outcome as the Oxy-TC trial. Both trials will provide evidence regarding the potential benefit or harm of invasive monitoring of brain oxygenation after severe TBI.
Background: Futibatinib is an oral, irreversible, highly selective fibroblast growth factor receptor (FGFR)1e4 inhibitor with potent preclinical activity against tumors harboring FGFR aberrations. This first-in-human, phase I dose-escalation trial (NCT02052778) evaluates the safety and pharmacokinetics/pharmacodynamics of futibatinib in advanced solid tumors. Patients and methods: Following a standard 3þ3 dose-escalation design, eligible patients with advanced solid tumors refractory to standard therapies received 8e200 mg futibatinib three times a week (t. i. w. ) or 4e24 mg once daily (q. d. ). Results: A total of 86 patients were enrolled in the nine t. i. w. (n ¼ 42) and five q. d. cohorts (n ¼ 44); 71 patients (83%) had tumors harboring FGF/FGFR aberrations. Three of nine patients in the 24-mg q.
Study design, patients, and treatment This open-label, multicenter, phase I study (NCT02052778) enrolled patients with histologically/cytologically confirmed advanced metastatic solid tumors with any number of prior therapies. Enrollment was planned to be restricted to patients with FGF/FGFR aberrations (screened locally) from dose level 5 of both dosing schedules [56 mg three times a week (t. i. w. ); 36 mg once daily (q. d. )]. An intermediate 20-mg q. d. dose cohort enrolling patients with tumors harboring FGF/FGFR aberrations was added per a protocol amendment dated 15 May 2017. Additional eligibility criteria included an Eastern Cooperative Oncology Group performance status of 0 or 1, adequate alanine aminotransferase (ALT) and aspartate aminotransferase [AST; 3Â upper limit of normal (ULN); 5Â ULN if liver metastases were present], and adequate total bilirubin ( 1.
17 n summary, this phase I dose-escalation trial demonstrated tolerability, PD activity, and preliminary antitumor activity of futibatinib in heavily pretreated patients with advanced solid tumors. Safety and PK data supported 20 mg futibatinib q. d. as the RP2D. On the basis of these results, futibatinib has been evaluated in the phase I doseexpansion portion of this study in multiple tumor types (recently completed) and in a phase II registrational trial (NCT02052778) in iCCA with FGFR2 fusions/rearrangements. The phase II trial has completed recruitment, and results of interim analyses are expected in 2020. In addition, recruitment is ongoing in other phase II [NCT04024436 (breast cancer)] and phase III [NCT04093362 (iCCA)] trials.
ACKNOWLEDGEMENTS Medical writing and editorial assistance were provided by  Vasupradha Vethantham, PhD , and  Jennifer Robertson, PhD , of  Ashfield Healthcare Communications (Lyndhurst, NJ, USA ) and funded by  Taiho Oncology, Inc. Biotech Inc. ,  Kolon Life Science, OrigiMed, Sumitomo Dainippon Pharma Co. , Seattle Genetics Inc. , DebioPharm, Dialectica ,  Piers Pharmaceuticals , Xencor, and  Tyra Biosciences ; and has received fees/honoraria from  Chugai Biopharmaceuticals, Dialectica, Mayo Clinic , and  Sumitomo Dainippon Pharma. LG has a consulting/advisory role for Debiopharm,  H3 Biomedicine, Incyte, QED, Alentis, Pieres, Agios , and  Sirtex ; serves on the  IDMC for AstraZeneca ; has received research funding from  Taiho ; and has received reimbursement for travel, accommodation, and other expenses from  Taiho.
Sequence and phylogenetic analyses We used an in-house bioinformatic pipeline to process raw sequences. Paired-end reads were merged with FLASH  (Magoc and Salzberg, 2011)  under strict criteria and assigned to specific samples based on their MIDs. MID and primer sequences were trimmed using CUTADAPT  (Martin, 2011). Cleaned merged reads were next dereplicated to unique sequences using VSEARCH  (Rognes et al. , 2016) , which was also used to detect and eliminate potential chimeras. Non-chimeric sequences from all samples were pooled together to define operational taxonomic units (OTUs) at a conservative threshold of 95% identity for 18S rRNA genes using CD-HIT-EST  (Fu et al. , 2012)  and SWARM  (Mahe et al. , 2015). Singletons were excluded from subsequent analyses. OTUs were assigned to taxa based on their similarity with a local 18S rRNA database build from SILVA v128  (Quast et al.
, 2013 ) and PR2 v4. 5  (Guillou et al. , 2013). OTUs less than 80% identical to their best environmental hit were blasted against the GenBank nr database (https://ncbi. nlm. nih. gov/) and assigned manually by phylogenetic placement analyses. Briefly, the closest hits to our OTUs in SILVA and PR2 were aligned with full 18S rDNA reference sequences covering the eukaryotic diversity using MAFFT  (Katoh and Standley, 2013). After removal of uninformative sites with trimAl  (Capella-Gutierrez et al. , 2009) , we built a tree with full reference sequences with IQ-tree  (Nguyen et al. , 2015)  under a GTR-+G+I sequence evolution model. OTU sequences were aligned to the reference alignment and then placed in the reference phylogenetic tree using EPA-ng  (Barbera et al. , 2019). OTUs with no reliable affiliation were maintained as 'Unclassified'.
, 2009; de Vargas et al. , 2015)  were identified in deep freshwater lakes  (Yi et al. , 2017; Mukherjee et al. , 2019). Likewise, Syndiniales, a clade of parasitic alveolates (often parasitizing their dinoflagellate relatives) widely distributed in oceans  (López-García et al. , 2001; Guillou et al. , 2008) , were recently identified in Baikal surface plankton  (Annenkova et al. , 2020). We identified members of all these lineages in our large Lake Baikal plankton dataset, albeit mostly in low proportions (Fig. 2A ; Table  S3 ). Bolidophytes and, collectively, MAST clades were nonetheless relatively abundant in the lake. However, MAST clades are not monophyletic and they exhibited different abundance patterns. Clades previously detected in freshwater systems, MAST-2, MAST-6, MAST-12 and to a lesser extent MAST-3, were relatively abundant.
Acknowledgments We thank the crew of the R/ V G. Titov  for their professionalism and efficiency onboard, the director of the  Limnological Institute at Irkusk  for logistical assistance and  Philippe Deschamps  for technical bioinformatic support. This research was funded by the  European Research Council  Grants ProtistWorld (322669, PL-G) and PlastEvol (787904, DM) as well as the  Russian State grant   0345-2016-0009  (NVA).
85m 85 BK02 BK02. 5m 5 28. 06. 2017 52°15'70" N 106°02'90" E BK26. 5m 5 BK26. 25m 25 BK26. 50m 50 BK26. 100m 100 BK26. 200m 200 BK26. 500m 500 BK26. 1000m 1000 BK26. 1350m 1350 BK28. 5m 5 BK28. 25m 25 BK28. 50m 50 BK28. 100m 100 BK28. 200m 200 BK28. 500m 500 BK28. 1000m. CT 1000 BK28. 1300m. CT 1300 BK28 06. 07. 2017 51°47'817" N 104°46'449" E South BK26 05. 07. 2017 51°52'638" N 105°15'294" E BK01 28. 06. 2017 52°15'70" N 106°02'90" E Central BK03 28. 06. 2017 52°41'401" N 106°44'208" E BK22 04. 07. 2017 53°23'524" N 107°53'094" E BK05 29. 06. 2017 53°31'096" N 108°24'583" E North BK20 03. 07. 2017 54°08'361" N 108°30'613" E BK16 02. 07. 2017 55°06'259" N 109°16'104" E BK06 30. 06. 2017 53°50'658" N 108°40'195" E Not connected Connected Bottom depth (m) 36 129 13 13 10 NA 35 10 1408 1381 1083 105 156 592 1512T 846 896 Functional classification Autotrophs 69 45 Heterotrophs 35 51 Parasites 5 1 Phylogenetic ascription Apicomplexa 1 0 Apusozoa 0 0 Bicoecea 2 1 Centroheliozoa 0 0 Cercozoa 13 9 Chlorophyta 9 2 Choanoflagellida 0 2 Ciliophora 11 33 Conosa 0 0 Cryptomycota 3 0 Cryptophyta 11 3 Figure S9.
Next generation sequencing, phylogeny and identification of contaminant DNA A slice of flesh from specimen MNHN JL305 was sent to the Beijing Genomics Institute (BGI) in Shenzhen, which provided DNA extraction and sequencing. Sequencing was performed on a DNBSEQ platform. A total of ca. 60 million clean paired-end reads were obtained. Reads were assembled using SPAdes 3. 14. 0 (Bankevich et al. , 2012)  with a k-mer of 85. Contigs corresponding to the mitogenome and the nuclear ribosomal RNA genes were retrieved by customized blastn command line analyses, using already available sequences downloaded from GenBank as a custom database; ribosomal RNA genes (not used in this article), were deposited into GenBank as MT860713 (18S) and MT860719 (partial 28S). In addition to the sequences related to A.
expatria, other positive matches belonging to contaminant DNA were obtained as explained in the results. tRNA were identified using tRNA-scan  (Lowe & Chan, 2016). The mitogenome was verified using the Consed package  (Gordon, Abajian & Green, 1998) , and gene identification was performed using MITOS  (Bernt et al. , 2013). The genomic map was drawn using OGDRAW  (Lohse et al. , 2013). Amino acid sequences of the protein coding genes were concatenated following a protocol already described  (Gastineau & Justine, 2020; Gastineau et al. , 2019 Gastineau et al. , , 2020)) , and aligned with corresponding sequences from other species using MAFFT  (Katoh & Standley, 2013) ; we used the command-line version of MAFFT, with the option "G-INS-I". A maximum likelihood phylogeny was inferred from this alignment using RaxML version 8.
Mitogenome The mitogenome (Fig. 7 ) is 14,962 bp long (GenBank accession number: MT527191). It contains 12 protein coding genes, two ribosomal RNA genes and 22 transfer RNA genes. The mitogenome is completely colinear with that of O. nungara (KP208777)  (Solà et al. , 2015)  and similar in size (14,909 bp for O. nungara). A megablast query using the whole sequence of the mitogenome shows a global 83. 77% identity between these   ND3. It is worth mentioning that the impossibility to evidence a start codon for these genes was observed with O. nungara, but not for example with B. kewense, Pl. manokwari or Pa. ventrolineata. Unlike O. nungara, however, no overlap between the ND4L and ND4 genes was evidenced. In the tree representing a maximum likelihood phylogeny of amino acid sequences of protein coding genes, A.
ACKNOWLEDGEMENTS A complete French translation of the article is available as a Supplemental File / Une traduction française intégrale de l'article est disponible comme fichier supplémentaire: Le Plathelminthe terrestre Amaga expatria (Geoplanidae) en Guadeloupe et Martinique: nouveaux signalements et caractérisation moléculaire, dont le mitogénome complet. We are grateful to all non-professionals and professionals who provided records and specimens; they are listed in Table 1. All individuals listed in Table 1 kindly agreed to have their photographs published in this paper. François Meurgey  and  Laurent Charles  kindly communicated some field observations;  Laurent Charles  provided information about the status of Subulina octona; they both agreed to have their information communicated here.
Data Availability The following information was supplied regarding data availability: All data are available in the Supplemental Files and from GenBank: MT602619-MT602626. The complete mitogenome is available at GenBank: MT527191. SSU and LSU partial sequences are available at GenBank: MT860713 and MT860719. All specimens have been deposited in the official collection of the Muséum National d'Histoire Naturelle (MNHN), Paris, France, under registration numbers MNHN JL146, MNHN JL216, MNHN JL217, MNHN JL262, MNHN JL289, MNHN JL305, MNHN JL310 and MNHN JL319.
Nevertheless, there is still a great need to provide more data that will allow the development of methods for designing geopolymers. The geopolymerisation process is strongly dependent on the source, composition and particle size of the aluminosilicates; thus a database on the chemistry, reactivity and dissolution mechanisms of various precursors must be completed  [5]. There are many examples of geopolymer mixes and alkali-activated materials (AAM) in the literature. The properties of those binders depend on the chemical composition of the source material. Aluminosilicate systems based on FA with low calcium content required a heat treatment curing cycle that makes this material well suited for prefabrication and precast manufacturing processes  [7, 8, 9, 10]  but they jeopardize their sustainable character because they require a significant amount of thermal energy to set and harden.
► To allow for comparability across populations and minimise the risk of outliers, our study focused on Organization for Economic Cooperation and Development countries, which are mostly highincome countries. ► Data on the prevalence of 10 mental issues were obtained from the Institute for Health Metrics and Evaluation's Global Burden of Disease study 2017, from which an increasing number of high-impact epidemiological studies has already been published. ► Our analysis took into account overall healthcare spending and potential outlier countries. ► The ecological design was necessary because our research questions were directly related to the association of national-level mental health prevalence and socioeconomic indicators; however, there is no possibility to make inferences about individuals from this dataset.
AbStrACt Objectives Recent studies have demonstrated worsened mental health in relatively highly developed countries impacted by social inequalities and unemployment. Here, we investigate (1) whether mental health issues are differently or similarly affected by these social factors and (2) whether their effects on mental health are related or unrelated to each other. Setting Analysis at the country level among Organization for Economic Cooperation and Development (OECD) countries (n=36). Data on social indicators were collected from OECD and the United Nations Development Programme databases. Data on the prevalence of mental issues were obtained from the Institute for Health Metrics and Evaluation's Global Burden of Disease study 2017. Participants No involvement of participants. Primary and secondary outcome measures Using linear regression models, we investigated the relative contribution played by human development (as measured by the Human Development Index (HDI)), social inequalities (Gini index) and unemployment (unemployment rate) on the prevalence of 10 mental health issues.
Dependent variable Prevalences of mental health issues across OECD countries were collected from the IHME's GBD project database,  19  where data are estimated from a combination of surveys, medical and epidemiological data, as well as metaregression models. Data from the GBD study 2017 were released in November 2018 and concern years 1990-2017. The GBD study 2017 defines prevalence as the proportion of people in a population who are a case of a disease, injury or sequela. All results in GBD refer to point prevalence. Data were extracted for year 2017 for a combination of mental health disorders and the specific following issues: depressive disorders, anxiety disorders, schizophrenia, bipolar disorders, eating disorders, alcohol use disorders, ADHD, autism spectrum disorders and suicide (table  1 ).
Independent variables Each country's level of human development was measured with HDI (range: 0 to 1). The HDI summarises life expectancy, a combination of adult literacy rate and school enrolment rate, and gross domestic product per capita at purchasing power parity. 20 or each country, income inequality was measured using the Gini index (range: 0 to 1), which intends to represent a nation's income distribution. 21 A Gini coefficient of 0 means that the country income is perfectly equally distributed. A Gini coefficient of 1 means that all the country's income is received by just one person. Our third socioeconomic indicator was unemployment rate, which measures the rate of unemployment as a percentage of the labour force. 22 ata for the three predictors were collected from the OECD database except for HDI, which was retrieved from the United Nations Development Programme database (table  1 ).
Data were extracted for year 2016, except when unavailable, in which case data were extracted for the closest year previous to 2016 (year range for data collection: 2014 to 2016). Source data for all 36 OECD countries is available at https:// data. mendeley. com/ datasets/ xcycfh96x5/ 1. There was no missing data. For each indicator (dependent and independent variables), atypical countries were defined as having a z-score greater than 3 or below -3 (table  1 ).
For our data, Pearson's r between combined mental health disorders prevalence and healthcare spending as measured by price per capita at purchasing power parity (obtained from the OECD database  24  ) was of 0. 58 (p<0. 001). To check that our results were not impacted by overall healthcare expenditures, we decided to regress out the influence of healthcare spending on the prevalence of each mental health issue and to rerun our analysis using the residuals as dependent variables. Finally, to check that our results were not too influenced by outliers, we also ran our analysis using robust regression methods. To run these analyses, we used R V. 3. 6. 1.
16S rRNA PHYLOGENY For phylogenetic analysis, 16S rRNA gene sequences were obtained from both strains (RB29 T and RB68 T ) by PCR amplification  [17]  and additionally extracted from genomic data (vide infra Genomic Features) using Artemis  [21]. blast analysis was performed using the NCBI database and 16S rRNA gene sequences of nearly all published Actinomadura reference strains downloaded from the LPSN database  [22]. Pairwise sequence similarities were calculated using the method recommended by Meier-Kolthoff  [23]  on the GGDC web server available at http:// ggdc. dsmz. de/ (Tables  S1  and S2 , available in the online version of this article). Sequences were aligned with the sina sequence alignment service  [24]. Phylogenetic trees were reconstructed with the neighbour-joining  [25]  and maximum-likelihood algorithms  [26]  in mega software (version 7.
GENOME FEATURES Extraction of genomic DNA, PCR amplification/sequencing of the 16S rRNA gene and genome sequencing of strains RB29 T and RB68 T have been described previously  [17, 30]  and genome data have been deposited at NCBI under NZ_MTBP00000000. 1 [RB29 T (alias 5-2)] and NZ_WEGH00000000. 1 (RB68 T ). Additionally, the genome of A. rayongensis DSM102126 T was sequenced (Genewiz) and genome data were deposited at NCBI (NZ_WUTW00000000. 1, Table  S4 ). The genomic DNA G+C content was determined from whole genome sequence data of strains RB29 T and RB68 T  [31] [32] [33]. Digital DNA-DNA hybridization (dDDH) analysis was performed using the GGDC web service at http:// ggdc. dsmz. de  [32]  and compared with other available published genomes of their corresponding genus. Additionally, average nucleotide identity (ANI) was calculated using the web services available at JSpeciesWS (http:// jspecies.
hibisca DSM 44148 T. All data were acquired in this study. nt, Not tested. Utilization tests were analyzed as follows; +, grows like positive control (basal medium with glucose); (+), better than negative control but not like positive control; -, not better than negative control (basal medium with water). All strains were positive for utilization of d-glucose and negative for utilization of d-arabinose, d-xylose, d-mannitol, raffinose and cellulose NaCl tolerance (%, w/v) 0-4 0-3 0-4 0-4 0-4 Optimum NaCl (%, w/v) 0-1 0-1 0-1 0-1 0-1   S3 ). Straight chains of two, three and rarely four cylindrical spores with a smooth shape are formed on the tip of sporulating aerial mycelium on ISP2 (Fig. 3a, c ).
3b, d ). Overall, strain RB68 T exhibited several different phenotypic characteristics from the reference type strain A. hibisca DSM 44148 T (Tables  1  and S5 ), which clearly supported its status as representing a novel bacterial species. The type strain is RB29 T (=CCUG 72668 T =NRRL B-65537 T ), which was isolated from the gut of the termite Macrotermes natalensis (major worker). The DNA G+C content of the type strain is 73. 1 mol%. The GenBank/EMBL accession number for the partial 16S rRNA gene sequence of strain RB29 T (alias 5-2) is KY312019. 2. The whole genome shotgun (WGS) project has project accession NZ_MTBP00000000. Raw sequencing data have been deposited under accession number SRR11565158.