dataesr/scientific-paragraphs-categorization huggingface dataset:
In Silico Analyses/Bioinformatics To identify peroxins in the genome data of the cryptophyte Guillardia theta, the following in silico analyses were performed: 1) Kyoto Encyclopedia of Genes and Genomes (KEGG; http://www. genome. jp/kegg/; last accessed June 5, 2018) analysis with G. theta proteins (Guith1, gene catalog, best model proteins, 24,840;  Curtis et al. 2012 ) and screening of classification category "peroxisome" for annotated peroxins; 2) BlastP with known Pex protein sequences from yeast (Saccharomyces cerevisiae) and Arabidopsis thaliana (NCBI) against the JGI G. theta all model proteins database (https:// genome. jgi. doe. gov/Guith1/Guith1. home. html; e-value cutoff: e-4; last accessed June 5, 2018) and for some peroxin queries (Pex3, Pex13, Pex24): local HMMER search  (Eddy 1998)  with HMMER profiles build from "seed" and "full" Stockholm alignments extracted from the Pfam database (http://pfam.
xfam. org/; last accessed June 5, 2018) against a G. theta protein database consisting of sequences extracted from NCBI (51,636; https://www. ncbi. nlm. nih. gov/protein/? term¼Guillardiaþtheta; last accessed June 5, 2018); 3) screening of the G. theta JGI genome database via keyword search for "peroxin," "pex," "peroxisomal," and "peroxisome"; 4) extracting the genomic and transcript information from the individual gene models and BlastN versus all_model_transcripts and the three EST databases included in the G. theta JGI genome database (see above) as well as the G. theta CCMP2712 transcriptome reads (SRR747855) (https://trace. ncbi. nlm. nih. gov/Traces/sra/? run¼SRR747855; last accessed June 5, 2018) and the G. theta EST databases at NCBI (rna_refseq and est) and the MMETSP  (Keeling et al.
2014) ; 5) manual inspection of each individual gene model using the software tool Sequencher (Genecodes); 6) validation of hits via reciprocal BlastP analysis of sequences against the NCBI nr database (https://blast. ncbi. nlm. nih. gov/Blast. cgi; last accessed June 5, 2018) and identification of conserved domains with NCBI Conserved Domain Search (CDS; https:// www. ncbi. nlm. nih. gov/Structure/cdd/wrpsb. cgi; last accessed June 5, 2018). For the identification of peroxins in other "chromalveolates," sequences of G. theta and the diatom Phaeodactylum tricornutum  (Gonzalez et al. 2011)  were used in addition to queries from yeast and Arabidopsis (NCBI) for BlastP analyses (e-value cutoff: e-4) against the genome data of: Emiliania huxleyi (https://genome. jgi. doe. gov/Emihu1/Emihu1. home.
Gene Sequence Amplification, Plasmid Construction, and Transformation Genes for localization studies were amplified via standard polymerase chain reaction (PCR) using the PHUSION High Fidelity DNA polymerase (Finnzymes) and gene-specific oligonucleotides synthesized by Sigma-Aldrich usually equipped with terminal restriction sites (see Supplementary Material online for primer sequences). PCR amplified fragments were cloned into pJet1. 2/blunt via the CloneJET PCR Cloning Kit (Thermo Fisher Scientific), sequenced (Macrogen), and cloned together with the gene encoding the enhanced green fluorescent protein (egfp) into the pPha-NR plasmid (GenBank: JN180663). Prior to biolistic transformation of diatoms, generated plasmids were isolated from a 50-ml E. coli culture using the Qiagen QIAfilter Midi/Maxi Kit and again verified by sequencing.
Phylogeny For phylogenetic analyses, we used a set of the protein sequences from cryptophytes, apicomplexans, and dinoflagellates identified here and previously to perform BLAST analyses against a local database containing sequences compiled from different sources (e. g. , MMETSP, NCBI, JGI) without applying any filters or clade preferences. We aligned all sequences selected with an E-value less than 1e-10 using MAFFT with high speed settings  (Katoh and Standley 2013). Preliminary trees were generated with Fasttree  (Price et al. 2010 ) after using BMGE (Criscuolo and Gribaldo 2010) with a block size of 4 and the BLOSUM30 similarity matrix. We applied a "dereplication" step with TreeTrimmer  (Maruyama et al. 2013) , sizing down robustly supported monophyletic clades in order to reduce sequence redundancy.
Results Peroxins in G. theta and Other "Chromalveolates" The presence of genes encoding peroxins was first investigated in the genome of the cryptophyte G. theta via BLAST and HMMER searches as well as by screening genome annotation data using the KEGG (Kyoto Encyclopedia of Genes and Genomes) pipeline (see Materials and Methods). Our survey led to the identification of a set of 16 peroxins (including two isoforms of two components, respectively; table 1) most likely sufficient for peroxisome biogenesis, division, and maintenance in the cryptophyte. The set includes the two receptors for PTS1 and PTS2, Pex5 and Pex7, the docking complex component Pex14, the RING-finger complex factors Pex2, Pex10, and Pex12 as well as the ubiquitin-conjugating enzyme Pex4, its membrane anchor Pex22, and the two AAA-type ATPases Pex1 and Pex6 for receptor recycling (table  1 ).
Though a putative TMD was identified by TOPCONS and TMHMM (see supplementary table  S2 , Supplementary Material online). The two Pex19 proteins found in G. theta both contain a conserved Pex19 domain within their C-terminal sequence part. TMHMM and TOPCONS predicted a putative TMD for one of the isoforms (Gt_Pex19-1). For the putative Gt_Pex3, which was initially identified with HMMER, a potential Pex3 domain was predicted via NCBI conserved domain search, although clear database hits (NCBI nr) were scarce when using the primary sequence as a query. In contrast, the putative PTS2 receptor Gt_Pex7 was found to possess a highly conserved primary sequence with the typical WD40 repeats (six in total) known to play a role in protein-protein interaction (see supplementary fig. S1 , Supplementary Material online).
1B  and supplementary fig. S2A , Supplementary Material online). Although the sequence shows a high degree of conservation at the N-terminus and especially the C-terminal part (TPR motifs) when aligned with Gt_Pex5, a whole region of $70 amino acids is missing in Eh_Pex5 (ID: 449555) that has been identified via BlastP in the E. huxleyi genome database. In the comparable sequence part of Gt_Pex5, this is exactly the region where the potential Pex7 interaction site is located (supplementary fig. S2A , Supplementary Material online). It has to be noticed though, that the EST coverage for E. huxleyi pex5 gene is incomplete, which does not allow us to preclude that the analyzed gene model detected in the genome database of the haptophyte is completely authentic. However, even after including transcript data information of several other E.
huxleyi strains from the MMETSP project  (Keeling et al. 2014)  to clarify the eh_pex5 gene model situation, a potential Pex7-binding motif could not be identified in the resulting translated Eh_Pex5 amino acid sequences (not shown). In addition to that, screening of another haptophyte, C. tobin CCMP291, genomic data also did not result in the detection of a Pex7 ortholog, which further speaks for the absence of a PTS2 pathway in haptophytes. As several other Pex factors (including Pex5) have also not been detected in this particular screening (see table 1), the genome data of C. tobin might be rather fragmentary. Thus, the observations made for this haptophyte have to be interpreted with caution and may not be entirely representative for haptophytes in general (see E. huxleyi, table 1). However, we detected putative Pex5 sequences in the transcriptomes of two other haptophytes, Chrysochromulina rotalis (CAMPEP_0115884546) and Phaeocystis antarctica (CAMPEP_0172982558) (MMETSP database;  Keeling et al.
2B ) and work recently published by  McCarthy et al. (2017). Next, we wanted to assess the phylogenetic history of at least a subset of the detected peroxins in G. theta and other chromalveolates to gain more knowledge about their evolutionary past. We used the MMETSP as well as the NCBI (nr) database as a basis for our calculations (see Materials and Methods). Particularly, the MMETSP database is a resource of transcriptome data for many organisms for which a genome sequence is not yet present  (Keeling et al. 2014). However, since the MMETSP data is not free of contamination, the results have to be evaluated with caution. Two peroxins were in the focus of our phylogenetic analyses: (i) the putative receptor of the prevailing PTS1 import pathway, Pex5, which was identified in all major "chromalveolate" groups (table 1), and (ii) the potential ubiquitin conjugating E2 enzyme Pex4, which is present in all "chromalveolates" investigated in this study, even in those most likely lacking peroxisomes (noncoccidian apicomplexan parasites such as Plasmodium), making this factor particularly interesting.
Acknowledgments We would like to thank  Uwe Maier  for the broad support of the work, helpful discussions, and critically reading of the manuscript. We are grateful to  Marion Debus  for technical assistance with sample preparation for electron microscopy. We also like to thank  Larissa Kolesnikova  from the  EM facility of the Institute of Virology, Philipps University Marburg , for access to their electron microscopic facility and for taking pictures for us, which are part of this work, during times we had technical issues with our system. This work is funded by the  Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)-409750538.
Data for Cv, Tg, and Pf were already published inMoog et al. (2017), in which the presence of peroxins in apicomplexans was studied in more detail. According to transcript data (MMETSP database; Keeling et al. 2014) present in other haptophytes: Chrysochromulina rotalis (CAMPEP_0115884546) and Phaeocystis antarctica (CAMPEP_0172982558). nd c a Organism name (and strain) abbreviations: Gt, Guillardia theta CCMP2712; Eh, Emiliania huxleyi CCMP1516; Ct, Chrysochromulina tobin CCMP291; Pt, Phaeodactylum tricornutum CCAP 1055/1; Tp, Thalassiosira pseudonana CCMP1335; Aa, Aureococcus anophagefferens clone 1984; Ng, Nannochloropsis gaditana; Es, Ectocarpus siliculosus Ec 32 CCAP 1310/04; Cv, Chromera velia CCMP2878; Tg, Toxoplasma gondii ME49; Pf, Plasmodium falciparum 3D7; Sm, Symbiodinium microadriaticum CCMP2467.
b As shown in Moog et al. (2017) a Pex19 candidate was detected in a related chromerid species, Vitrella brassicaformis CCMP3155 (NCBI accession number: CEL92557. 1). c According to Ludewig-Klingner et al. (2018) present in other dinoflagellates. d e Cr. , cryptophytes; Ha. , haptophytes; þ, Ortholog present; 2, two potential orthologs identified; ?, Orthology status unclear; nd, not detected. See supplementary table S1, Supplementary Material online, for protein identification numbers.
2), sterilized by filtration on a 0. 2-lm membrane (Nalgene; Nunc International, Naperville, IL, USA), aliquoted, and stored at 48C for up to 1 year. MAb concentrations were determined by absorbance at 280 nm (Nanodrop 2000; ThermoFischer Scientific) and their specific mass extinction coefficients, by using the Protparam software (Swiss Prot; provided in the public domain by Swiss Institute of Bioinformatics, Geneva, Switzerland, http://www. expasy. org/). Endotoxin contamination was verified by using a limulus amebocyte lysate test (Endosafe PTS; Charles River, Ecully, France). The sequence and molecular integrity of different anti-CD160 mAbs batches were controlled by enzymatic treatment of mAb followed by mass spectrometry analysis of the peptides generated (at the Laboratoire de Spectrométrie de Masse Bio-Organique, UMR 7178 CNRS/ University of Strasbourg, France).
CNV Measurements. CNV was graded on a 0-to-4 scale as based on the length of the neovessels formed between the limbus and the lens (see Fig. 1D ). CNV was photographed (Canon 550D on binocular microscope, 320; Canon France, Courbevoie, France) on D1, D3, and D7 or on D6, D8, and D12 to assess the impact of the early and late treatments, respectively. CNV on corneas was manually measured and analyzed by image processing using MorphoExpert software (Explora Nova, La Rochelle, France) to allow quantitative analysis of corneal neovessel length (mm) and count individual neovessels, as well as determining NV area (mm 2 ) (representative images are shown in Fig. 1C ). Evaluation of Additive Effect of CL1-R2 and Anti-VEGF Antibody on Inhibition of CNV in Rabbit. The potential additive effect of combining CL1-R2 and bevacizumab therapy was determined for several groups of rabbits by using the same CNV model.
Statistical Analysis Statistical analyses were performed by using GraphPad Prism software (version 6; GraphPad, San Diego, CA, USA). Differences in NV grades, length, and area between the experimental and control groups were analyzed by using Mann-Whitney tests. Results are presented as mean 6 SD. The threshold for statistical significance was set at 0. 05. The significance of P values is indicated in all figure legends. To determine the statistical significance of percentage differences of clinically relevant lesions between the vehicle control group and ELB01101 in the ChNV NHP model, a v 2 test was performed.
Acknowledgments The authors thank  Maryse Aguerre-Girr ,  Marie-Andrée Daussion ,  Jeanine Boyes ,  Benjamin Gil , and  Julie Tabiasco  for their assistance in preparing and contributing to some of the experiments and various aspects of this study, and  Pascal Clerc  for assistance with analysis of MorphoExpert data. The English language was edited by  Maighread Gallagher, PhD  ( TWS Editing ). Supported in part by  INSERM ,  CNRS ,  Toulouse III University, Association Valentin Haüy , and through Grant  ANR-12-RPIB-0009  from the  French National Agency for Research. The funders played no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Disclosure:  T. Menguy ,  Elsalys Biotech  (E), P;  A. Briaux , None;  E. Jeunesse , None;  J. Giustiniani , None;  A.
Dose rate calculations Evaluation of internal β-particle dose rates resulting from the tritium treatments were derived from the data obtained in separate experiments designed to measure uptake and retention of tritium  [63]. Tritium concentration in mouse tissues were measured at time points of 0, 1, 7, 15, 21 and 30 days and percentage (P) of the input tritium concentration in drinking water was calculated for each time period using trapezoid areas of the biokinetics curves. Then dose was evaluated using the following formula: Xt = D × P × b × E × T, where Xt is dose to mouse in Gy per a time period t, D is drinking water tritium concentration in Bq/L, P is percentage of tritium tissue concentration relative to that in drinking water over a time period t, b is mean energy of a b-particle and equals to 5.
The significance of the dose-dependent terms in the models (1) and (2) was investigated using a permutation test  [65, 66]. We compared the goodness of fit on the proposed model (2) vs. the linear model using the Akaike information criteria (AIC)  [67] , which penalizes the likelihood of the models by their numbers of explanatory variables in order to obtain the most parsimonious one. Lower AIC values indicate better fit and differences in AIC above 4 may be considered as significant. We carried out all calculations for the dose-response analysis with MATLAB Version: 8. 2. 0. 701 (R2013b).
ACKNOWLEDGMENTS This study was conducted under the auspices of a research collaboration between  Canadian Nuclear Laboratories  ( CNL; Chalk River, Canada ) and the  Institut de Radioprotection et de Sûreté Nucléaire (IRSN; Paris, France). The authors are thankful to  Jovica Atanacovic  and  Bruce Heinmiller  for providing dosimetry guidance for the shielded 60 Co source, to  Dr. Aurélie Desbrée  for providing advice for tritium microdosimetry, to  Dr. Candice Didychuk  and  Dr. Céline Baldeyron  for reading this manuscript and providing helpful comments.
In addition, the actual parameterization of NH3 exchange models requires large databases accounting for the variability of χs. To our knowledge, there is only one process-based model developed by  Riedo et al. (2002)  for grasslands which accounts for the plants N nutrition and growth stage in calculating χs. However, as χs is not only driven by N input to the ecosystem and plant growth stage, it may be a strongly regulated process that depends on environmental changes such as elevated ground-level O3. Ground-level O3 can be considered as the most phytotoxic air pollutant due to visible injury to a variety of plants and the rising concentrations in different regions of the world  (Cooper et al. , 2014; Feng et al. , 2014). It affects photosynthetic parameters (e. g. , stomatal conductance (gs), light-saturated CO2 assimilation rate (Asat), intercellular CO2 concentration (Ci) and chlorophyll (Chl) content) of forest species to a varying extent  (Li et al.
Statistical analysis Data of each investigated variable from three plants per OTC were averaged and then used as the statistical unit (N=3). Prior to analysis, all data were tested for normality using the Shapiro-Wilk's W-test and for homogeneity of variance using Levene's-test to determine whether data should be transformed to be satisfied in application. A three-way analysis of variance (ANOVA) with a mixed linear model was then conducted to examine the effects of O3, N, measurement dates and their interactions on physiological parameters and χs as well as other parameters using JMP software (SAS Institute, Cary, NC, USA). Tukey's Honestly Significant Difference (HSD) test was applied to examine the significant differences. Analysis of covariance (ANCOVA) was performed to test the significance of difference in the slopes of the linear relationship between χs and physiological parameters using SPSS software (version 11.
Study setting A collaborative, international, multicenter, prospective, observational cohort study was conducted according to a pre-speciied, published protocol (ClinicalTrials. gov identifier: NCT02179112)  [12]. The collaborative network methodology has been described elsewhere  [13]. Briely, the study was conducted by teams of local investigators coordinated by a national lead investigator. Investigators were recruited via the GlobalSurg network and through dissemination on social media and other personal contacts. Consecutive sampling of patients undergoing emergency abdominal surgery was undertaken during 2-week periods within a 6-month study window. Investigators in a hospital could choose one or multiple 2-week periods. There was an absolute requirement for all cases in the chosen period(s) to be included, but no minimum number set to avoid bias against smaller centers.
A UK National Health Service Research Ethics review considered this study exempt from formal research registration (South East Scotland Research Ethics Service, reference NR/1404AB12); individual centers obtained their own audit, ethical or institutional approval. This study is reported according to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines  [14]. Pre-speciied sub-group analyses included the examination of patients undergoing appendectomy as compared with other abdominal surgical procedures. At each participating center, data collection was performed by teams following the same standardized protocol  [12].
Once vetted, the record was accepted into the dataset for analysis. Patient variables included age, gender, American Society of Anesthesiologists (ASA) physical status classiication system, diabetes history, smoking and diagnostic category. Service variables included use of the WHO surgical safety checklist, the experience of surgeon/anesthetist, and compliance with selected evidence-based standards. Prophylactic antibiotic use was deined as antibiotics administered either at induction, or during surgery but before opening of a contaminated space.
6%) compared with high-HDI countries (11. 2%)]. This translates to a NNT with laparoscopic rather than open surgery of 6 to prevent one SSI in low-HDI countries managing perforated appendicitis. Moreover, in the absence of CT imaging, diagnostic laparoscopy can provide an efective way to investigate patients with acute abdominal pain short of the requirement for a full laparotomy. The major strength of this study is the collection of patient-level prospective data from 52 countries. This unique dataset allows comparison across the HDI spectrum which is rarely possible. A published, detailed protocol translated into major languages ensured consistent data collection across varying regions without the burden of communication barriers. Local validation by leads ensured data accuracy and completeness was high.
Acknowledgements Organizations assisting in dissemination (alphabetical): Asian Medical Students' Association (AMSA), Association of Surgeons in Training (ASiT), College of Surgeons of East, Central & Southern Africa (COSECSA), Cutting Edge Manipal, Egyptian Medical Student Research Association (EMRA), International Collaboration For Essential Surgery (ICES), International Federation of Medical Student Associations (IFMSA), Lifebox Foundation, School of Surgery, Student Audit and Research in Surgery (STARSurg), The Electives Network, United Kingdom National Research Collaborative, World Korean Medical Students Association (WKMSA), World Society of Emergency Surgery (WSES), World Surgical Association (WSA). Individuals assisting in dissemination (alphabetical): Douglas.
Acknowledgments This work was carried out in the framework of the public procurement " Determination of Chemical Composition of Atmospheric Gases and Aerosols in Estonia" of the Estonian Environmental Research Centre  (Reference number:  146623 ), funded by the  Estonian-Swiss cooperation program  " Enforcement of the surveillance network of the Estonian air quality: Determination of origin of fine particles in Estonia ". The authors would like to thank  Picarro Inc. , particularly  Mr. John Hoffnagle  and  Mr. Derek Fleck , for the detailed information regarding possible interferences in the NH 3 analyzer. We also acknowledge the support of the  Swiss National Science Foundation  ( IZERZ0 142146 ) and the funding for the measurements in Zurich by the  Federal Office for the Environment (FOEN) in Switzerland.
The following prior distributions for the parameters of P1, L2, L2R models θ 0 ,Γ 5:5; 3 ð Þ and logðθ 1 Þ; logðθ 2 Þ ð Þ ,N log 0:08 0:92 À 0:75; 0:675 T ; 1:5 0 0 0:75 ! ! are chosen to satisfy two conditions on d0 and d1 formulated above. The characteristics of all the models compared are evaluated in R (R Core Team, 2015) using the bcrm-package by  Sweeting et al. (2013). To accommodate the randomization to the control group and the Emax model corresponding modifications to the package were made. The code is available online at https://github. com/dose-finding/Randomised-bcrm.
Acknowledgments The authors acknowledge the insightful and constructive comments made by two reviewers. This project has received funding from the  European Union 's  Horizon 2020 research and innovation program  under the  Marie Sklodowska-Curie  grant agreement No  633567. Xavier Paoletti  is partially funded by the  Institut National du Cancer (French NCI ) grant SHS-2015 Optidose immuno project. This report is independent research arising in part from  Prof Jaki 's  Senior Research Fellowship  ( NIHR-SRF-2015-08-001 ) supported by the  National Institute for Health Research. The views expressed in this publication are those of the authors and not necessarily those of the  NHS , the  National Institute for Health Research  or the Department of Health.