dataesr/scientific-paragraphs-categorization huggingface dataset:
In the current study, data on laboratory measures were collected at baseline and at 2-week intervals thereafter up to 16 weeks (for FGF23, data were available at baseline and 8 and 16 weeks). Thus changes up to 14 weeks, which represent cumulative changes from baseline over the entire 14-week period, were used to assess the influence of earlier temporal changes in serum phosphate or TSAT on later changes in FGF23 outcomes at 16 weeks. A structural equation path analysis model was specified (Figure  1 ). In the model, if the regression pathway coefficient (c) is significant and the products of both indirect pathway coefficients, (a Â b) and (d Â e), are not significant, then this could represent either a direct effect of treatment on the change in FGF23 or an indirect effect by unknown/unmeasured mechanisms.
Results were neither dependent on the analytic method nor the method's means of handling missing data. We believe that the complexity of the relations between these biological processes lends itself well to path analyses, which have not yet been widely used in the nephrology literature. The baseline characteristics of the trial population suggest that the findings are generalizable to patients with CKD Stages 3-5 seen in general nephrology outpatient practices. Limitations were the post hoc exploratory nature of these analyses, the relatively short 16-week randomized study period and the lack of measures of vitamin D and urinary phosphate. Longer trials, such as the 48-week COMPASS trial (ClinicalTrials. gov identifier: NCT03236246) may be useful for assessing the long-term effect of ferric citrate on FGF23 or serum phosphate and on clinical outcomes, including cardiovascular events, among patients with NDD-CKD and IDA.
Study design and participants The study protocol was approved by the participant hospitals' institutional review boards. Signed informed consent was obtained from each patient. This study-the ONCOTHROMB12-01 study (Clinicaltrial. gov indentifier: NCT03114618)-is an observational cohort study involving an 18 month monitoring period with analysis at 6, 12, and 18 months. This paper presents the results for the first 6 months. Selection criteria were as follows: • Over 18 years of age.
ACKNOWLEDGEMENTS The authors thank the  Sociedad Española de Oncología Médica , the  European Society of Cardiology , the  Fundación Josep Carreras contra la Leucemia , the  Sociedad Española de Trombosis y Hemostasia, CERC Programme/Generalitat ,  Ferrer inCode , and  Leo-Pharma  for funding and institutional support. The authors thank  Adrian Burton  (www. physicalevidence. es) for editorial assistance. The study has been presented in part in: ISTH congress (Toronto-2015), ICTHIC congress (Bergamo-2016), SEOM congress (Madrid-2016), WHITH congress (Barcelona-2017), and  ISTH  ( Berlin-2017 ).
, 1978). The higher the value of the index, the greater the functional role played by branches. We built a single integrative branching index that expresses the architectural gradient by combining these two variables using Principal Component Analysis (correlation between photosynthetic and exploration branching indexes: rho = 0. 86) employed in the ade4 package for R  (Dray and Dufour, 2007). Species were segregated into three architectural classes (Monocaulous, Intermediate, and Branched) using Wilcoxon signed-rank tests that enable detection of breaks in the distribution of the integrative branching index. Using morphological criteria reviewed by  Barthélémy and Caraglio (2007) , we then described main traits commonly used in architectural analyses (growth process, branching pattern, position of reproductive structures, etc.
Phylogenetic Signal We assessed phylogenetic independence of measured traits  (Felsenstein, 1985)  using two complementary statistics calculated under a Brownian Motion (BM) model of evolution. Pagel's Lambda  (Pagel, 1999; Freckleton et al. , 2002)  is widely used for low rates of type I error and robustness, even for poorly or moderately informative phylogenies  (Freckleton et al. , 2002; Münkemüller et al. , 2012). Because this statistic loses statistical power when used on small phylogenies (<30 terminals,  Freckleton et al. , 2002) , we also used Blomberg's Kappa  (Blomberg et al. , 2003; Kembel, 2009)  that is less robust but more appropriate for small taxonomic sampling (until 20 taxa,  Kamilar and Cooper, 2013). Both statistics were calculated considering intraspecific variation using the phytools package for R  (Revell, 2012).
Trait Correlations and Functional Characterization We used phylogenetic regression based on the method proposed by  Ives et al. (2007)  and implemented in the phytools package for R  (Revell, 2012)  to test whether architectural variation was correlated with functional specialization. Using maximum likelihood, this method fits bivariate models taking into account both phylogenetic framework and intraspecific variation. The response variable was the integrative branching index, and the explanatory variables were all other functional traits (Table  1 ). Significance of relations was tested using a likelihood ratio test between the model and a model constrained with a slope of zero. To characterize the functional space of each architectural classes, we performed a Principal Component Analysis.
Trait Based Diversification To test whether one of the architectural classes has contributed more than the others to the diversification of New Caledonian Atractocarpus (by increasing speciation rates and/or decreasing extinction rates), we used the Multiple State Speciation Extinction (MuSSE) framework  (Fitzjohn et al. , 2009)  as implemented in the diversitree package for R  (Fitzjohn, 2012). For this analysis, outgroups were dropped from the phylogeny to consider only the 27 rainforest Atractocarpus species. Fifteen models of diversification were used, each differing in whether or not of speciation, extinction and transition rates were equal between classes (Table  2 ). Model selection was done according to AICc.
DATA AVAILABILITY STATEMENT All datasets generated for this study are included in the manuscript and the supplementary files. Data concerning the phylogenetic tree was obtained from Mouly et al. (under  review)  and genetic sequences are available in the European Nucleotide Archive (accession numbers on Appendix 2 in Supplementary Material). Information about study sites (habitat characteristics. ) is available through the voucher specimens of which duplicates have been deposited in various herbaria.
3%), trastuzumab was withheld because of other patient-related factors (eg, loss to follow-up, general frailty/poor performance status) or disease characteristics (Table  1 ). 23, 25, 36, 37, 40  Percentages of patients who received trastuzumab was calculated using drug sales data received from the Retail Drug Supplier in SE, treatment recommendations by the Swedish Breast Cancer Group, cancer and death statistics received from the National Board of Health and Welfare, general statistics (eg, population) obtained from Statistics Sweden, an estimated frequency of HER2 positivity of 25%, a treatment duration of 38 weeks, and an estimated use of 1 unit of trastuzumab per patient per week.
Approved by EMA, 2018 87 ; submitted to MHLW in Japan, 2017 88 ; submitted to FDA, 2017 80 Trast and Doc / Trast and F and  Epi and Cy pCR  ( 95% CI): 50. 4% (44. 1-56. 7)ORR (95% CI): 89. 5% (85. 0-92. 9 )!1 Treatment-emergent SAE: 11. 9% Withdrew treatment because of significant LVEF decrease: 3 patients IRR: 10. 4% pCR treatment difference (95% CI):  À0. 0362  ( À0. 1238 to 0. 0516 ) c ORR treatment difference (95% CI):  À0. 0115  ( À0. 0990 to 0. 0764) HER2 þ MBC CT-P6  and  Pac ORR Safety  and efficacy NCT01084876 ORR: 57% Median TTP: 11. 07 mo Median TTR: 1. 38 mo SAEs: 13. 5% IRR: 15. 6% Cardiotoxicity: 3. 3% Trast and Pac ORR: 62% Median TTP: 12. 52 mo Median TTR: 1. 38 mo SAEs:  12. 1% IRR: 26. 0%Cardiotoxicity: 4. 3% ORR treatment difference (95% CI):  5%  (e0. 14 to 0. 04) c TTP; P ¼.
0%) Epi and Cy / Trast and Pac pCR, local review: 40. 5% RD (90% CI): 7. 3% (1. 2%-13. 4%) a RR (90% CI): 1. 19 (1. 033-1. 366) a pCR, central independent review: 41. 8% RD (90% CI): 5. 8% (À0. 5% to 12. 0%) b RR (90% CI): 1. 14 (0. 993-1. 312) b !1 AE: 79. 5% Grade 3þ AE: 14. 1% Most common AEs were arthralgia (15. 2%), asthenia (16. 3%), neutropenia (12. 5%), peripheral neuropathy (11. 9%), and anemia (10. 2%) BCD-022 (Biocad, HER2 þ MBC BCD-022 and Pac ORR, PK CR, PR, stabilization NCT01764022 ORR (95% CI): 53. 57% (40. 70-65. 98) Saint-Petersburg, (first-line) rate, progression rate, CR: 5. 36% Russia) 81,82 AEs, CTX cycles PR: 48. 21% postponed because of SD: 25. 0% AEs, DC due to AEs, Progression rate: 21. 43% ADA, PK NAb: 1 patient Trast and Pac ORR (95% CI): 53. 70% (40. 60-66. 31) CR: 3.
Data collection and classification Data were collected from the French PH registry or from routinely performed assessments in clinical practice. Predefined clinical, functional, hemodynamic and therapeutic data were collected using a standardized case report form. The period of observation was from the date of PEA until time of death or date of last known contact. Data were categorized into five sets of parameters: (1) clinical (age, gender, smoking, history of acute pulmonary embolism, associated medical conditions); (  2 ) therapeutic (delay between first assessment and PEA, use of pulmonary arterial hypertension (PAH) targeted treatment before PEA, duration of treatment before PEA); (3) functional (New York Heart Association [NYHA] functional class and 6-minute walk distance [6MWD]); (  4 ) spirometric (TL CO expressed as % of the predicted value); and (  5 ) hemodynamic (PVR expressed in dyn.
25 mm film thickness (J&W Scientific, Rancho Cordova, CA, USA) at a constant helium flow rate of 1. 0 mL/min. Samples (1. 0 μL) were injected in a splitless mode for 0. 5 min at 250 °C. The temperature program started at 35 °C that was held for 2 min, followed by an increase to 140 °C with a 15 °C/min temperature gradient. The last step was an increase to 320 °C with a 10 °C/min temperature gradient, held for 10 min. The total run time was 37 min. The transfer line temperature was set to 280 °C. The MS data were acquired in the full scan mass range of 43-500 m/z using an electron ionization (70 eV). Quantifications were done using eight-point calibrations with the corresponding standard quantification ions listed in Additional file 1: Table  S1. For compounds for which standard were not available the nearest isomeric standard was employed.
Gene expression analysis by real-time RT-PCR RNA was isolated using NucleoSpin RNA Plus (Macherey-Nagel; Düren, Germany) or RNeasy from Qiagen (Qiagen, Germantown, MD), and reverse transcribed to cDNA on a PCR System 2400 (PerkinElmer, Waltham, MA, USA) using a High Capacity cDNA Archive Kit (Applied Biosystems, Foster City, CA, USA). Real-time PCR was performed using pre-designed TaqMan Gene Expression Assays and TaqMan Universal PCR Master Mix and run on Applied Biosystems 7500 fast software. Gene expression of induced IL-1α (Hs00174092_m1), IL-1β (Hs01555410_m1), IL-6 (Hs00174131_m1), CXCL8 (Hs00174103_m1), COX-2 (Hs00153133_m1), MMP-1 (Hs00899658_m1), HO-1(Hs01110250_m1), PAI-2/SERPINB2 (Hs01010736_m1), CYP1A1 (Hs00153120_m1) and Cyp1B1 (Hs02382916_s1) were normalized against GAPDH (Hs02758991_g1) and expressed as fold change compared to untreated control as calculated by the ΔΔCt method (ΔCt = Ct.
Statistical analysis Statistical analysis was performed by ANOVA with Holm-Sidak post-test for multiple comparisons. As ANOVA cannot be performed on normalized data, the gene expression data were analyzed using the deltaCTvalues from the q-PCR measurements. All calculations were performed using GraphPad Prism 7 software (GraphPad Software, Inc. , San Diego, CA). the data analysis and statistics. PHEC were isolated and cultivated by KZ and MHR. KK and AK performed the OC-extraction and chemical characterization. JØ conceived and coordinated the study, with support of JAH. BB and JAH drafted the first versions of the manuscript and wrote the final version in collaboration with JØ. All authors read, commented and approved the final manuscript.
Acknowledgements We thank  E. Lilleaas  and  HJ. Dahlman  ( Norwegian Inst. of Public Health, Oslo, Norway ) for technical assistance throughout the study. The contribution of EM and ACG was performed in the framework of the internally funded " In vitro models for the prediction of respiratory irritation and sensitization -IMPERIS " project (LIST). BC Brinchmann was supported by a travel exchange grant from  Rennes Métropole , to realize part of his PhD in Rennes, France. The work at  NIPH , including two travel grants were supported by the  Research Council of Norway , through the  Environmental Exposures and Health Outcomes-program  (grant no. 228143 ).
* S Supporting Information The Supporting Information is available free of charge on the ACS Publications website at DOI: 10. 1021/acsmacrolett. 8b00418. Experimental procedures, materials used, characterization details, 1 H NMR spectra, FTIR spectra, GPC eluograms, POM images, and the SAXS, WAXS, and TEM data for PtBA 0.
For the explosive disintegration of heterogeneous droplets to happen, the temperature at the interface must reach that of water boiling. A non-contact method, planar laser-induced fluorescence (PLIF), made it possible to establish that the temperature near this interface reached 100-120 • C before disintegration. The authors determined the threshold temperatures at the onset of this effect for a group of solid and liquid organic additives (slurry and emulsion components). As a result of the explosive fragmentation of multi-component droplets, the evaporation surface area increases up to 15 times. It is important to expand the experimental database with the evaporation characteristics of typical sewage and service water compositions to improve their treatment. The most popular approach to the experimental research into the breakup of boiling liquid, solution, emulsion, and slurry droplets is placing them on a holder into a heated gas flow (e.
Review of Time Ranges of Droplet Breakup through Microexplosion This subsection presents a review of the time ranges of droplet breakup through microexplosion. We considered the experimental results of microexplosion times published in studies  [30] [31] [32] [33]. Table  1  contains the main suitable data from these papers. A droplet is placed on the holder inside the combustion chamber with a temperature of 30 • C. After that, the droplet ignites by an electrically heated wire. The temperature of the droplet is measured by the Pt-PtRh thermocouple. A video camera records the microexplosion process. The fall process lies in the simultaneous motion of the chamber and the droplet during ~1 s.
[28,29] Sunflower oil, distilled water, non-ionic surfactant SPAN 83 K-type thermocouple (Nickel-Chromium, Nickel-Alumel) (0. 9-1. 3 s) A bare K-type thermocouple (wire diameter 76. 2 µm) is heated from below by the means of a highly resistive coil with its asymptotic temperature of 350 • C. The emulsion drop is maintained on the thermocouple junction by interfacial tension. The thermocouple signal is acquired by an oscilloscope, and the shadowgraph frames are visualized using a high speed camera (10,000 fps). An analysis of data presented in Table  1  enables the conclusion that when using the different holders examined in the study, the explosive breakup times of the droplets are the upper estimates of Energies 2018,  11, 3307  the actual values in the practical applications. Therefore, the values presented in the research can be used to predict the maximum possible times of heating until droplet breakup.
We recorded the heating, boiling, and disintegration of two-component droplets by a high-speed video camera. The recordings were processed using the Tema Automotive and ActualFlow software packages for the continuous tracking of moving objects. In the course of processing, we determined the initial droplet radius R d and the total liquid evaporation surface area, S. The video recordings Energies 2018, 11, 3307 6 of 17 were processed in two stages. At first, we tracked how the frontal cross-sectional area S m of an evaporating and deforming droplet changed until it finally broke up (Figure  2c ). Using the Airbag and Advanced Airbag tracking algorithms, we observed the changes in the shape of an evaporating droplet. After that, the frontal cross-sectional area of a droplet was calculated, and the curves S m (t) were plotted.
The droplet was assumed to be spherical and its frontal cross-sectional area to be a circle. Using the formula R d = (S m /π) 0. 5 , we calculated the average droplet radius R d. The errors of the R d calculation did not exceed 2. 5%. After that, the total area of the droplet evaporation surface was calculated using the formula S = 4πR d 2. Video recordings following the explosive breakup of the heterogeneous droplet into separate smaller fragments were analyzed at the second stage. A polydispersed aerosol was usually formed. The shadow image was analyzed using the Actual Flow software to determine the location, boundaries, and dimensions of separate droplets. Median, Low Pass, and Average software filters were used to screen off the noises, and Laplace Edge Detection was used to determine the boundaries of droplet surface.
Genome project history The project information and associated MIGS (Minimum Information about a Genome Sequence) 2. 0 compliance  [21]  are summarized in Table  2. This bacterium was selected for sequencing as it was determined to be one of the most promising strains for discovery of compounds with strong antibacterial (Fig. 1d ), antifungal and biosurfactant abilities (Additional file 1: Figure  S1 ). The availability of the draft genome of DNG9 may contribute to the evolution and comparative genomics studies of the B. cereus sensu lato group. Furthermore, future investigations on its genome-encoded bioactive metabolites may be pursued. This work provided a standard draft genome and the assembled contigs have been deposited in public repositories. The PGAP-and JGI-IM-annotated genomes were deposited to the DDBJ/ENA/GenBank  Phylum Firmicutes TAS  [16]  Class Bacilli TAS  [54, 55]  Order Bacillales TAS  [42, 56]  Family Bacillaceae TAS  [42, 57]  Genus Bacillus TAS  [41, 42]  Species Bacillus thuringiensis TAS  [42, 58]  Strain DNG9 Evidence codes: IDA Inferred from Direct Assay, TAS Traceable Author Statement (i.
e. , a direct report exists in the literature), NAS Non-traceable Author Statement (i. e. , not directly observed for the living, isolated sample, but based on a generally accepted property for the species, or anecdotal evidence). These evidence codes are from the Gene Ontology project  [61]  Fig. 2  Maximum likelihood phylogeny of Bacillus thuringiensis DNG9 16S rRNA gene isolated from Algerian soil-oil slough. Nucleic acid sequences were aligned using Geneious and the tree compiled using RaxML. Numbers above the branches refer to bootstrap values. The tree was rooted using Bacillus subtilis subsp. subtilis ATCC 6051 T. Type strains are indicated with T. All strains represent sequenced genomes. Scale bar indicates 2 nucleotide substitution for each 10 nucleotide sequences. Accession numbers of publicly available sequences are given in brackets databases under accession numbers MSTN00000000 and Ga0180945, respectively.
Genome sequencing and assembly The genome of Bacillus thuringiensis DNG9 was sequenced at The Applied Genomic Core, Department of Biochemistry, University of Alberta using Illumina paired-end sequencing platform and Nextera XT DNA library kit (Illumina, USA). Whole genome sequencing was performed in duplicates using the MiSeq Reagent kit v2. Sequencing of 250 bp paired-end modules gathered 3. 69 M reads, which provided an average coverage of 317× resulting in 38 contigs. De novo assembly of the 6,057,430 bp paired-end sequences was created using CLC Genomics Worksbench v 7. 5. 2. (CLC bio, Aarhus, Denmark).
Acknowledgements The authors acknowledge the help of Georgina Mcintyre from The  Applied Genomic Core, University of Alberta  for genome sequencing and  Arlene Oatway  from the  Advanced Microscopy Unit, Department of Biological Sciences, University of Alberta  for electron microscopy analyses. Funding MSD was funded by  Agence Universitaire de la Francophonie ,  France. MSD, MD , FN and SKG were supported by the  National Fund for Scientific Research of Algeria. JCV was funded by the  Natural Sciences and Engineering Research Council of Canada. JZA was funded by  Alberta Innovates-Health Solutions. ARRR was funded by  Alberta Innovates-Technology Futures  and  Vanier Canada Graduate Scholarship.
Statistical analysis Each experiment was performed in triplicates and the results were expressed as mean values. Linear regression analysis was used to calculate LC 50 values. Microsoft Excel® was used to enter and capture data. Various graphs and tables were extracted from this data. Data was then exported to SPSS for further analysis. The MIC for each microorganism was analyzed using one-way analysis of variance (ANOVA). P value < 0. 05 was considered as significant. SPSS 25. 0 was employed for statistical analysis.
fog05 is an OpenSource project that aims to provide an IaaS Software for MEC. Due to its fully distributed and pluggable architecture, it allows extensions on functionalities and on the information model, allowing to achieve all the requirements coming from ETSI MEC. The MEAO and the MEPM-V are developed as plug-ins on top of fog05 and leverage the fully distributed Pub-/Sub communication fabric provided by fog05 to communicate between each other, while the ME Platform is developed in a way that allows communication between different ME apps that expose services. More in detail the request of NS deployment will be send to the MultiLayer Orchestrator, that will operate a formal check on the NS descriptor. If MEC Application descriptor is present within the NS descriptor, the MultiLayer Orchestrator will originate two parallel work flows: (i) the first flow will consist in a ETSI NFV standard Network service deployment, where AppD are treated as standard VNFd (ii) the second flow consists in the interaction between MEAO, MEPM-V and ME Platform to enable MEC services consumed by an AppD.
NFV construct that corresponds to ME Host. In 5GCity an ME Host is mapped with the NFVI present in a cabinet, meaning that an NFVI-PoP correspond to a ME Host. MEC should be able to reuse such as NFVI-PoP (basically, a data centre) and Zone (a set of co-located and well-connected physical resources which is a subset of an NFVI-PoP). 12. ME App VNF Instance Relocation. The MEAO and the NFVO collaborate when it is time to relocate an ME App instance. This communication goes through a reference point separate from Mv1, because it is unrelated to Os-Ma-nfvo. Relocation is triggered by MEAO based on information coming from MEPM-V. 13. Application instantiation. Similarly to issue 12, ME app instantiation is triggered by the MEAO.
The cooling rate dT/dt was calculated from the formula:  (1)  where v is the head feed rate and dT/dx is the temperature gradient in the melted metal pool. The temperature gradient was determined using the thermal imager and ThermaViz 2. 0 software. The thermal images were obtained at different heights of the constructed elements for the zone at the ground, half of the height, and the top of the sample. The applied processing parameters and obtained cooling rates are listed in Table  1. Macrostructure observations were carried out with a Nikon Eclipse MA200 light microscope (Nikon Corporation, Tokyo, Japan). Prior to structural examinations, all of the samples were subjected to the following metallographic preparation procedure: grinding on SiC papers with the granulation in the sequence of 120, 240, 500, 1200, and 2400; polishing with diamond suspensions (3, 1, and 0.