dataesr/scientific-paragraphs-categorization huggingface dataset:
0 in a Synergy HT multimode microplate reader in continuous mode at 550 nm over 24 h (extinction coefficient of phenol red, 8,450 M 21 cm 21 ). The acid produced after ester bond cleavage by the hydrolytic enzyme induced a color change in the pH indicator that was measured at 550 nm. The experimental conditions were as detailed previously  (35) , with the absence of activity defined as at least a 2-fold background signal. Briefly, the reaction conditions for 384-well plates (catalog no. 781162; Greiner Bio-One GmbH, Kremsmünster, Austria) were as follows: protein, 0. 2 to 2. 0 mg per well; ester, 20 mM; temperature (T), 30°C; pH, 8. 0 [5 mM 4-(2-hydroxyethyl)-1-piperazinepropanesulfonic acid (EPPS) buffer, plus 0. 45 phenol red]; reaction volume, 40 mL. The reactions were performed in triplicate, and data sets were collected from a Synergy HT multimode microplate reader with Gen5 2.
2 mL of a mixture of protein (1 mL, 24 mg Á mL 21 ) and seeds (0. 2 mL, 1:100) with guanidine hydrochloride (0. 2 mL, 0. 1 M) and reservoir (0. 5 mL, 11% polyethylene glycol 8000, 100 mM Bis-Tris, pH 5. 5, 100 mM ammonium acetate). For data collection, crystals were transferred to cryoprotectant solution consisting of mother liquor and glycerol (20% [vol/vol]) before being cooled in liquid nitrogen. Diffraction data were collected using synchrotron radiation on the XALOC beamline at ALBA (Cerdanyola del Vallés, Spain). Diffraction images were processed with XDS (46) and merged using AIMLESS from the CCP4 package  (47). The crystal was indexed in the P2 1 2 1 2 1 space group, with two molecules in the asymmetric unit and 62% solvent content within the unit cell. The data collection statistics are given in Table  S4.
The structure of EH 0 was solved by molecular replacement with MOLREP (48) using the coordinates from Est8 as a template (PDB code 4YPV). Crystallographic refinement was performed using the program REFMAC (49) within the CCP4 suite, with NCS (noncrystallography symmetry) medium restraints and excluding residues 17 to 36. The free R factor was calculated using a subset of 5% randomly selected structure-factor amplitudes that were excluded from automated refinement. Subsequently, heteroatoms were manually built into the electron density maps with Coot8 (50), and water molecules were included in the model, which, combined with more rounds of restrained refinement, reached the R factors listed in Table  S4. The figures were generated with PyMOL. The crystallographic statistics of EH 0 are listed in Table  S4.
ACKNOWLEDGMENTS This study was conducted under the auspices of the  FuturEnzyme  Project funded by the  European Union 's  Horizon 2020 Research and Innovation Programme  under grant agreement no. 101000327. We also acknowledge financial support under grants  PID2020-112758RB-I00  (M. F. ),  PDC2021-121534-I00  (M. F. ), and  PID2019-105838RB-C33  (J. S. -A. ) from the  Ministerio de Ciencia e Innovación ,  Agencia Estatal de Investigación (AEI)  (https://doi. org/ 10. 13039/501100011033 ),  Fondo Europeo de Desarrollo Regional (FEDER) , and the  European Union  (" NextGenerationEU/PRTR "), and grant  2020AEP061  (M. F. ) from the  Agencia Estatal CSIC. C. Coscolín  thanks the  Ministerio de Economía y Competitividad and FEDER  for a Ph. D. fellowship (grant  BES-2015-073829 ). P. N. G. acknowledges the Sêr Cymru Programme partly funded by  ERDF  through the  Welsh Government  for the support of the project  BioPOL4Life , the project ' Plastic Vectors ' funded by the  Natural Environment Research Council UK (NERC) , grant no.
Results In this document, the detection probability is the probability to detect at least one mosquito of a given species during a 24-h trapping session, given the known presence of this species in the study area. The apparent density is the mean number of individuals of given species and sex caught during a 24-h trapping session. Overall, 951 Ae. aegypti, 618 Ae. albopictus and 737 Cx. quinquefasciatus were identified out of a total of 2306 catches. On a few occasions, one of the traps failed (lack of CO 2 , or defective battery). The design was therefore slightly unbalanced. However, the missing data were independent of the response, and the maximum-likelihood estimates of the model coefficients were therefore unbiased. In total, results from 89 trapping sessions were available, whereas the expected total was 96 (92.
The environmental effects controlled by the Latin square design were trapping date (proxy for air temperature, relative humidity, wind speed and direction) and trapping site (proxy for habitat type, distance to breeding and resting sites). At the end of each 24-h trapping session, mosquitoes were collected from each BG-Sentinel trap and frozen at -20 °C to kill them. They were then poured into Petri dishes for identification using a binocular and a morphological key adapted to local mosquitoes 2. Individuals of Ae. aegypti, Ae. albopictus, and Cx. quinquefasciatus were counted by species and sex. Data were entered and stored in a relational database management system. Data analysis. Separate analyses were done for each mosquito species. To assess the effects of trapping strategies, we chose a hurdle model jointly accounting for the detection probability of the mosquitoes, and their apparent density  38.
This model was made of two sub-models which were jointly fitted: (i) a logistic Bernoulli model for the presence data (detection probability), and a zero-truncated negative binomial model for the apparent-density counts. The same covariates were used to model the detection probability and the apparent density. The latter was chosen to account for the large variance met in this dataset-related to the peculiarities of Aedes mosquitoes ecology. Indeed, males of Ae. aegypti sometimes aggregate in swarms of thousands of insects, triggered by aggregation pheromones  39. Females are also attracted by these swarms, as well as mosquitoes from other species. When such a swarm met a trap, hundreds of mosquitoes were caught during a single trapping session. This happened several times during the experiment.
We did not discard the corresponding data because they are an important feature of Aedes ecology. Therefore, we did not expect to select a single best model adapted to an unrealistic average situation. Instead, we adopted a multi-model averaging approach, well adapted when there is not a single plausible model with respect to the available data  40. A "full" model was defined, representing the most complex structure expected in the dataset. From this full model, a set of nested, plausible sub-models was defined, and all these models were fitted using a maximum-likelihood method. They were ranked using AICc, the small-sample version of the Akaike information criterion. The AICc difference between consecutive models was computed, and divided by the AICc difference between the first and last models.
This quantity is the Akaike weight. It was used as a relative model plausibility indicator, and to compute weighted means of the fitted values from each compared model, i. e. , multi-model averaging (MMA). We applied the approach on each bootstrapped dataset to compute 95% credible intervals for the MMA-fitted values. To estimate the 95% credible intervals of observed and fitted values, we used a bootstrap resampling procedure of the observed dataset  41. The combination of sites and dates (two sites, four dates by replicate, and three replicates) was taken as the 24 resampling units of four trapping sessions each (i. e. , the four dates). A random sample of these units was drawn with replacement in the initial data set, with the same size in sampling units. It was used to compute the simulated means.
The process was iterated 200 times. The 2. 5% and 97. 5% quantiles of the empirical distributions of each simulated mean were used as the 95% credible interval of population means. The R software and computing environment  42  was used for data analysis, in particular statistical packages pscl for hurdle models  38  , and MuMIn for multi-model averaging and inference  43  , implementing the methods described in Burnham & Anderson  44. Throughout this document, α was set to 0. 05.
Acknowledgements This research work was partially funded by the  European Union, (i) European Research Council , Grant Agreement No. 682387-REVOLINC , and ( ii) Horizon 2020 program , Grant Agreement No. 874850-MOOD , both in the framework of the  One Health Indian Ocean partnership network  (www. onehe alth-oi. org). It is cataloged as MOOD044. The contents of this document are the sole responsibility of the authors and don't necessarily reflect the views of the  European Commission. We are grateful to  Agence Régionale de Santé La Réunion -in particular its vector control department, for their support and fruitful discussions. We thank  Dr. Marc J. B. Vreysen ,  Head of the FAO-IAEA Insect Pest Control Laboratory (Vienna, Austria ), for his comments on the draft version of this paper.
Data availability Data and R code needed to run the analysis are available in a master R Markdown document  45  named bgtrap. Rmd containing the dataset-as an R object named tab, and the master R code. Most of the work is done by R functions automatically sourced in the running R session from an external file called functions. R. The list of add-on R packages needed to run the analysis, as well as some code to install-and possibly update them, are available in an R file called packages. R, also automatically sourced in the R session. All these files are available in the section Supplementary Information containing further instructions.
In line with the Journal's conflict of interest policy, this paper was handled by Jeroen Hendriks. The congenital heart disease (CHD) population now comprises an increasing number of older persons in their 6th decade of life and beyond. We cross-sectionally evaluated patient-reported outcomes (PROs) in persons with CHD aged 60 years or older, and contrasted these with PROs of younger patients aged 40-59 years and 18-39 years. Adjusted for demographic and medical characteristics, patients ≥60 years had a lower Physical Component Summary, higher Mental Component Summary, and lower anxiety (Hospital Anxiety and Depression Scale-Anxiety) scores than patients in the two younger categories. For satisfaction with life, older persons had a higher score than patients aged 40-59 years. Registration: ClinicalTrials.
10, 11 he study was approved by the Institutional Review Board of the University Hospitals Leuven/KU Leuven Belgium (coordinating centre) and by the local institutional review boards of the participating centers (when required). Informed consent was obtained from each participating patient. The study protocol was registered at ClinicalTrials. gov: NCT02150603. Demographic data were collected through self-report questionnaires. In line with a prior study on older persons with CHD,  6  we categorized patients into three age cohorts: ≥60 years; 40-59 years; and 18-39 years. We assessed three domains of PROs using valid and reliable self-report questionnaires: (i) perceived physical and mental health status using the 12-item Short Form Health Survey (SF-12)  12  and the EuroQOL-5D Visual Analog Scale (EQ-VAS);  13  (ii) psychological distress using the Hospital Anxiety and Depression Scale (HADS); 14 and (iii) quality of life using a Linear Analogue Scale (QOL-LAS)  15  and the Satisfaction With Life Scale (SWLS).
16 Expanded definitions of the domains and the interpretation of scores of the questionnaires are provided in Supplementary material online, Table  S1. Eligible patients were mailed a questionnaire package or completed surveys during an outpatient visit. Data collection ran from April 2013 through March 2015. Data analysis was performed using IBM SPSS Statistics for Windows, version 28 (IBM Corp. , Armonk, NY, USA). Patient-reported outcome scores were expressed as means and standard deviations. Demographic and medical background variables were compared across the age cohorts using the χ 2 test. Differences in PROs across the age cohorts were tested through multivariable general linear mixed models, adjusted for sex; educational level; employment status; marital status; patient-reported NYHA status; and complexity of the heart defect.
29  related concept is frailty, which is defined as 'a significant decline in functional reserve, resistance, and resilience of multiple organ systems, and the resultant extreme vulnerability of the individual to endogenous and exogenous stressors (such as infection, injury or surgery, or some medicines), leading to a higher risk of accelerated functional decline and adverse health-related outcomes'. 30 To date, frailty has not been comprehensively investigated in CHD. However, in the international APPROACH-IS II project that is currently underway, frailty is being assessed in patients with moderate or complex CHD aged 40 years or older (https://clinicaltrials. gov/ct2/show/NCT04902768). The APPROACH-IS project had several methodological strengths. More than 4000 patients from 15 countries were included; there was a high degree of complete data; and we used valid and reliable PRO instruments.
Study Population All subjects were enrolled in our Fetal Medicine Unit at Necker Hospital (AP-HP hospitals of Paris and Paris-Cité University) between December 2011 and December 2017. Patients provided written informed consent, and studies were approved by the local ethics committee and registered in the clinicaltrial. gov website as NCT03090841 (BiocCMV) and NCT01651585 (CYMEVAL2). According to the study protocol, amniotic fluid that was not used for clinical management-related investigations was stored for research purposes. The women included were referred following maternal primary infection (MPI) within 2 months prior to conception or in the first trimester of pregnancy. They underwent amniocentesis to diagnose cCMV infection. For each infected fetus, a negative control with a non-infected and euploid fetus was included and matched accordingly to fetal gender and gestational age at amniocentesis.
Beads were resuspended in PBS and read on a Luminex 200 analyzer (Luminex Corporation) with acquisition of 100 beads for each region and analyzed using Bioplex Manager software (Bio-Rad Laboratories, Hercules, CA, USA). Analyte concentrations (pg/mL) were determined using five parameters regression algorithms and expressed as the mean pg/mL ± S. E. Concentrations were corrected for dilution by ExoQuick-TC™ or Triton™ X-100. Extracellular vesicle luminal content ('internal fraction') was calculated as [analyte content of lysed vesicle] -[analyte content of intact vesicles ('surface fraction')].
Cytokines Profiling in Amniotic Fluid of Symptomatic Newborns Concentrations of relevant cytokines and comparison between symptomatic and asymptomatic newborns are summarized in Table  3  (full dataset in Supplementary Table  S2 ). Twelve proteins were significantly correlated to a symptomatic status at birth in the univariate analysis: four were soluble proteins (IP-10, IL-18, TRAIL, and CRP) and eight were associated with EV, mostly located within the EV (IP-10, IL-6, MCP1, MIG, and RANTES). Five cytokines were previously associated with fetal infection (IP-10 internal , IP-10 surface , IP-10 soluble , IL-18 soluble , and TRAIL soluble ) (Figure  2 ). A pattern with a specific increase in cases of severe symptomatic infection was identified for six proteins (IL-18 soluble , TRAIL soluble , CRP soluble , TRAIL surface , MIG internal and RANTES internal ).
Morphological Traits In order to estimate the reach of a searcher shoot, we measured in situ the distance in a straight line from the base to the apex of the searcher shoot (here called the "reach"). Searcher shoots were cut at the base and temporary stored in a plastic bag before measurements. In our field laboratory, all the leaves were removed by cutting the petiole/rachis as close as possible to the insertion point with the lamina(s). Laminae were digitised using a 300 dpi-imaging scanner (Epson Perfection V800; Epson America Inc. , Long Beach, CA, United States and Canon CanoScan LiDE 400; Canon Japan Inc. , Tokyo, Japan), and areas were extracted using the leafarea R package  (Katabuchi, 2015). Fresh masses of the searcher stem and all appendages (branches, petioles, and laminae) were measured within 3 h after the shoot was sampled.
, 2019). We therefore prepared longitudinal sections on one individual per species to distinguish fibres from sclereids  (Lehnebach et al. , 2020)  and thus interpret their putative mechanical significance to stem stiffness. To characterise anatomical organisations of different species, we distinguished up to 9 types of tissue per species from the following tissue categories: (i) medullary parenchyma, (ii) medullary fibres, (iii) xylem (including primary and secondary xylem), (iv) phloem (including primary and secondary phloem), (v) cortical parenchyma, (vi) cortical sclereids, (vii) cortical fibres, (viii) cortical collenchyma and (iv) periderm. We manually delineated tissues from digitised cross-sections with a graphics tablet and created layers with the GIMP software (version 2. 10. 12 1  ).
Masks of layers were used to calculate cross-sectional areas and second moments of the entire stem and each area of each tissue with a customised macro using ImageJ software (v. 1. 43u 2 ). The orientation of the cross-section is critical for calculating the second moment of area of the entire stem and tissue proportions. An oval cross-section positioned with its long axis in the vertical plane would have a higher second moment of area than if it would be placed in the horizontal plane. We therefore aligned each cross section and its masks with the longaxis of the stem arranged vertically. We then measured the second moment of area in this vertical position (I x ) and at 90 • (I y ) to it for both the entire section and the individual tissues. We then calculated proportions of each tissue in terms of second moment of area based on the mean values calculated from the vertical and horizontal orientations.
Statistical Analysis All statistical analyses and data graphics were performed with R software 3. We applied a one-way ANOVA on a subset data frame with 170 searcher shoots accounting for 22 species represented by at least 3 replicates to test how reach capacity varies between species. We used standardised major axis regression (SMA) via the SMATR package  (Warton et al. , 2012)  to observe absolute and relative changes of mechanical properties, anatomical organisations, and functional traits with reach capacity. Since power functions were linked to most traits and reach capacity, we used log-log graphs to plot the data and log-transformed the data via the sma function. The assumptions of linearity and equal variance of all fitted values and assumption of normally distributed residuals were graphically checked for all variables.
FUNDING This project has received funding from the  European Union 's  Horizon 2020 research and innovation program  under Grant Agreement No. 824074  (GrowBot) and an " Investissement d'Avenir " grant from the  Agence Nationale de la Recherche  ( CEBA :  ANR-10-LABX-0025 ;  ARBRE ,  ANR-11-LABX-0002-01 ). TH was supported by a doctoral fellowship from the  CEBA.
The top surface of the cube was scanned by the SEM to acquire an image with resolution 50 nm per pixel (4000 x 4000 pixels). Then, a microtome shaved a 50 nm thick layer from the top of the specimen, and the new top surface was scanned. This process was repeated until 4000 images were obtained so that the data cube had equal resolution in , , dimensions. Custom image analysis scripts were written for the SEM datasets. First, a local adaptive threshold was used to binarize the image. A distance transform was used to identify the center of each cell slice in a particular 2d image. A watershed algorithm was then seeded with the cell slice centers, followed by a particle tracking algorithm to label cells across image slices. After labeling, the boundary for each cell was found, resulting in a point cloud of the exterior of each cell.
Bud scar size We next measured the typical size of bud scars on the surface of Y55 yeast cells. Single cells were stained with calcafluor to highlight the chitinous bud scars (Figure  1 -Figure  Supplement 1 ). Confocal -stacks were obtained on a Nikon A1R confocal microscope equipped with a 40× oil immersion objective. These images were visualized using the image processing software FIJI, and the 3d volume viewer plugin. To track the location and size of bud scars, a custom MatLab script was written to map the strongest calcafluor signals, since calcafluor makes bud scars brighter than other portions of the cell wall. Brightness isosurfaces then isolated the bud scars from the cell wall. Next, the isosurface points were rotated to theplane by finding its principal components in a principal component analysis.
Registration of cell positions Positions of cells were registered based on fluorescence intensity using custom Matlab scripts. This was achieved by carrying out a 2D convolution of each frame of the -stack with a basic kernel modelling the appearance of a cell -this was set to be an asymmetric double sigmoidal function. Cell segmentation was corrected manually. -stacks taken from different angles were roughly aligned using Fiji and the Matlab function fminsearch to minimise distances between the reproductive cells. This alignment was used as starting point for alignment of the somatic cells again using fminsearch. The positions of somatic cells were merged and averaged.
3D Voronoi Tessellations First, we computed 3D Voronoi tessellations within a defined boundary. These tessellations were performed for experimental snowflake yeast data from the SEM and simulations of 3D groups using the open-source Voronoi code Voro++  (Rycroft, 2009) , wrapped in a custom MatLab script. Voro++ takes as input the Cartesian coordinates of the cell centers and the boundary of the shape within which to compute the tessellation. Without a boundary, all of the Voronoi cells located on the periphery would extend to infinity. We started the tessellation process by setting the input boundary to be a sphere; the Voronoi algorithm tessellated space within the spherical boundary. Then, pieces of the sphere were pared away until a Voronoi tessellation within the group's convex hull was obtained, as described in the next paragraph.
Volvox Along the surface of the Volvox organisms, there are gaps between some of the somatic cells due to the Gonidia that lie beneath, but near the surface of the organism. These Gonidia effectively occupy space on the surface, making it inaccessible to somatic cells. We excluded all Voronoi cells that intersected these Gonidia gaps. We identified gaps in the soma cells by flagging Delaunay triangles with exceptionally high aspect ratios. Any Voronoi polygons that intersect the flagged Delaunay triangles were then flagged and later excluded from the dataset. The polygons were generally spatially clustered, indicating that the Gonidial gaps were being correctly isolated. Roughly 90 polygons were excluded from each organism. In Volvox organisms, each cell is surrounded by extracellular matrix, so cells do not contact each other.
Acknowledgments Core Facilities at the  Carl R. Woese Institute for Genomic Biology. W. C. R. was supported by  NIH  grant  1R35GM138030. This work was funded in whole, or in part, by the  Wellcome Trust  (Grant  207510/Z/17/Z ; REG & SSH). For the purpose of open access, the authors have applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission. This work was also supported in part by  Established Career Fellowship   EP/M017982/1  from the  Engineering and Physical Sciences Research Council (REG).