dataesr/scientific-paragraphs-categorization huggingface dataset:
2a ). A similar activation of an adjacent rif (Pf3D7_1149800) was also seen in the case of the stevor-activated parasite line (Fig. 3c ). In order to verify the microarray data and show that the expression remains stable we performed qRT-PCR on 15 different multigenes (5 var, 5 rifin, 5 stevor) 6 weeks after the microarray analysis (Fig. 3d ). RNA was harvested in triplicates grown in the blood of three different donors 18 hpi from all three knock-in cell lines. Relative expression was calculated by normalization to seryl-tRNA synthetase. The expression patterns remained constant when compared to the microarray analysis. None of the multigene families, whether they have been selected for expression or not, showed drastic changes in expression pattern. Despite keeping all three cell lines under the same drug pressure throughout the duration of the experiment, total mRNA levels remained different between all three multigene families.
Our results also clearly indicate that the SLI approach allows the activation of a defined yir from its own promoter and are consistent with reports that YIRs have different localization during parasite development  50. Transcriptional co-regulation of yir genes. The endogenously tagged PYYM_0017400. GFP cell line now provides an ideal opportunity to study co-regulation of yir expression in P. yoelii. For this, triplicates of RNA extracted from trophozoite-stage wild-type PYYM as well as 2 clones of PYYM_0017400. GFP were analysed by RNA sequencing. To avoid missing any yir genes in our downstream analysis, the RNA seq raw data was mapped to the reference genome of P. yoelii 17X due to the larger number of yir gene annotation in PlasmoDB (the ID of PYYM_0017400 in the P. yoelii 17X annotation is PY17X_1100077).
The blue arrow points to the gene that was tagged in this transfected cell line. Orange arrows point to the genes selected for qRT-PCR validation. b Expression of yirs in each group were validated using qRT-PCR and results are in line with RNA sequencing results. All data are presented as mean ± standard error of the mean (SEM). the parasites. Removal of the drug led to a slow decrease of gene expression in a subpopulation of parasites up to the point where detection by Western blot and qRT-PCR was not possible anymore (parasites were validated approximately 20 cycles after drug removal). The locus was re-activated by addition of the drug to the culture medium. Even though all cell lines were kept under the same drug pressure, relative mRNA levels differed between them. This might be either due to variances in expression timing (RNA was harvested at 18 hpi in all cell lines) or differences in total mRNA transcription.
We performed the RNAseq analysis using Kallisto to map the reads against the annotated PY17X1. 1 index file with boostrap 100 and thread 4 to obtain the transcript per million (TPM) count. Differential gene analysis was done by sending the TPM from Kallisto into DEseq2 software. Whole genome sequencing and analysis. Genomic DNA of two clones of all three P. falciparum cell lines was extracted using phenol:chloroform:isoamylalcohol (25:24:1, Invitrogen) followed by ethanol precipitation as per manufacturers protocol. All following steps were performed by the Genome Institute of Singapore. DNA libraries were prepared by 1D native, PCR free barcode ligation. Multiplexed libraries were sequenced on an Oxford Nanopore GridION platform release 19. 12. 6 on a single flowcell (Basecalling/mode: Guppy 3.
Acknowledgements The authors would like to thank  Professor Marek Mutwil  and  Dr Devendra Shivhare  for their valuable input in the Kallisto workflow. We would like to thank  Anthony Holder  for his kind gift of the Gap45 antibody. Special thanks to  Tobias Spielmann  for sharing of the plasmids and information about the SLI system before publication. Han Ping Loh was funded by  A*STAR Graduate Academy  (AGA). Radoslaw Igor Omelianczyk was supported by  SINGA. This work was funded by the  Singapore Ministry of Health's National Medical Research Council  under its  Cooperative Basic Research Grant  ( NMRC/CBRG/ 0040/2013 ) and  Open Fund Individual Research Grant  ( NMRC/OFIRG/0058/2017 ). M. C. J. C. and P. R. P. were partially supported by the  National Research Foundation of Singapore  through the  Singapore-MIT Alliance for Research and Technology's (SMART) Interdisciplinary Research Group in Infectious Disease and Anti-Microbial Resistance Research Programs.
Data availability All relevant data are within the paper and its Supporting Information files are available from the authors upon request. The microarray and RNA sequencing data discussed in this publication have been deposited in NCBI's Gene Expression Omnibus  87  and are accessible through GEO Series accession number GSE128123 and GSE152162, respectively. The whole genome sequencing data have been deposited with links to BioProject accession number PRJNA637985 in the NCBI BioProject database (http:// www. ncbi. nlm. nih. gov/bioproject/637985). Source data underlying the plots shown in figures are provided in Supplementary Data 1.
Statistical analysis This non-inferiority crossover trial compared two ventilation strategies administered to all newborns in random order. The study was adequately powered; it was possible to explore the non-inferiority of nHFPV compared to nCPAP in terms of the mean rScO 2 over the last 5 min of either modality. The literature  [8, 9]  indicated that the mean rScO 2 observed in such patients is approximately 80%, with a standard deviation (SD) of 10%. We defined nHFPV as being noninferior to nCPAP if the lower boundary of the bilateral 95% CI for the difference (nHFPV minus nCPAP) was less than -5%; otherwise, the new ventilation would be poorer than the reference ventilation. Our sample size of 80 patients afforded a power of 80% in terms of revealing non-inferiority of the new regimen, assuming a non-inferiority margin of -5 (nQuery software ver.
6. 0). The results are expressed as means with 95% confidence intervals (CIs) or SDs for continuous variables, and as frequencies for categorical variables. We used a linear regression model to assess the effects of treatment, treatment period (first or second), and treatment-period interactions. The latter exploration checked for the absence of a carryover effect, which would have compromised the analytical validity of the data from the second treatment period. All statistical analyses were conducted by a biostatistician from our Clinical Epidemiology Unit using SAS software ver. 9. 4 (SAS Institute Inc. , Cary, NC, USA). We performed intention-to-treat analyses. Primary outcome analysis featured replacement of missing rScO 2 data by the poorest sample value. Sensitivity analyses were performed on all available data.
Discussion nHFPV was well-tolerated and non-inferior to nCPAP as measured by rScO 2 levels when used to manage respiratory distress at birth in newborns of GA ≥ 33 weeks. Sensitivity analyses confirmed this, except when replacing missing rScO 2 values by the worst observed value under nHFPV and the best observed value under nCPAP. However, it is unlikely that all nCPAP rScO 2 data would be compatible with the 55% value under nHFPV. Indeed, most of the missing data were attributable to signal loss (contact issues between the sensor and forehead); all other vital parameters (SpO 2 , HR, and RR) collected at the same time were within normal ranges. If respiratory distress is evident, PEEP improves alveolar recruitment and limits alveolar collapse at the end of expiration, increasing residual functional capacity and decreasing breathing effort.
FUNDING This research was conducted under the auspices of the  CASCADE  Project that is funded by the  European Commission   FP7 program , ENV. 2011. 2. 1. 4-2-'Behavior of ecosystems, thresholds and tipping points, '  EU  Grant agreement:  283068. This manuscript synthesizes our findings from across this project and in doing so draws heavily on our final report to the  EU , which is archived at: https://library. wur. nl/WebQuery/wurpubs/fulltext/441608. SV and JK also thank  FCT/MCTES  for the financial support to CESAM ( UIDP/50017/2020 + UIDB/50017/2020 ), through national funds. SB also thanks the  Spanish Ministry of Science and Innovation for financial support  ( CGL2017-89804-R ).
Introduction Proteotyping is a typing method for taxonomic identification of organisms according to their specific protein profile acquired by mass spectrometry  [1]. Proteotyping can be performed by whole cell matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry, an established technique for the identification of microorganisms based on the molecular mass profile of their low molecular weight and basic proteins. The technique is designed to query the mass spectrum acquired directly on the sample against a database containing profiles of thousands of previously recorded microorganisms  [2]. The approach enables the rapid and confident identification of, for example, bacterial pathogens for clinical diagnostics at low cost  [3] , and can be used for discriminating subspecies as illustrated for Francisella tularensis  [4]  or Campylobacter coli  [5] , and for identifying antibiotic resistance in specific cases  [6].
Data interpretation For the Mix3* digests, MS/MS spectra were assigned to peptide sequences using a database comprising the polypeptide sequences from the annotated genomes of B. subtilis subsp. spizizenii ATCC6633, E. coli BL21-Gold (DE3) pLysS AG and S. cerevisiae S288C strains. The database contains 43,774 polypeptide sequences and 15,766,031 amino acid residues. The interpretation was performed using Mascot Daemon software version 2. 6. 1 (Matrix Science) with the following parameters: 5 ppm peptide tolerance, 0. 02 Da MS/MS fragment tolerance, 2+ or 3+ peptide charges, a maximum of two missed cleavages, carbamidomethylation of cysteine as fixed modification, oxidation of methionine as variable modification and trypsin as proteolytic enzyme. Microorganism proteotyping was performed by assigning MS/MS spectra against the NCBInr database (downloaded on 01/03/2018) comprising 108,307,546 protein sequences, using Mascot with the same parameters as above except that only one missed cleavage was allowed, and a p-value below 0.
MS spectra were recorded using an Autoflex III MALDI-TOF/TOF mass spectrometer (Bruker Daltonics, Bremen, Germany) equipped with a 200-Hz Smartbeam laser. Spectra were recorded in the linear, positive mode from 2,000 to 20,000 m/z, cumulating 500-1,000 shots from different positions of the target spot. The Ion source 1, Ion source 2, Lens and the extraction delay time were set at 20. 07 kV, 18. 60 kV, 7. 50 kV, and 200 ns, respectively. Each spectrum was the merged signal from 500-1,000 shots from different positions of the target spot. Calibration was performed externally using the Bruker Bacterial Test Standard (Escherichia coli protein extract including the additional proteins RNase A and myoglobin). Spectra were recorded with the flexAnalysis software (v3. 4, Bruker Daltonics) and interpreted with the Biotyper software (v3.
1, Bruker Daltonics) and the biotyper spectral database v7 which contains spectra profiles for 7,311 reference microorganisms. The proteotyping confidence is based on a score analysis as recommended by the manufacturer: i) a score > 2. 3 was considered highly probable species identification, ii) a score between 2. 0 and 2. 3 was considered a secure genus identification and probable species identification, iii) a score between 1. 7 and 1. 999 was considered as a probable genus identification, iv) a score < 1. 7 was considered as not a reliable identification.
Similarly, 70 of the 87 specific proteins presents in the 96-wells dataset are also found in the in-tube results with a unique peptide. As expected, experimental and analytical variability observed at the peptide level influenced the validation of a few number of proteins. However, these results demonstrate that such variability does not significantly change the confidence of the proteotyping analysis. Also, their proteotyping values were equivalent, as the number of peptides assigned to each microorganisms were comparable between the 96-well format (Table  S3 ) and the in-tube format (Table  S1 ): 665 and 791 for S. cerevisiae, 3671 and 4157 for E. coli, and 11542 and 12348 for B. subtilis.
After plate processing, the resulting 36 digests were subjected to nanoLC-MS/MS and proteotyping identification. The detailed proteotyping data are detailed in Supplementary Table  S6. The 36 samples were accurately identified at the species level by 1,026 (±3%) PSMs and 10 (±13%) assigned specific peptides for A. baumanii, and 1,273 (±2%) PSMs and 2 (±20%) assigned specific peptides for E. coli. The presence of E. coli in A. baumanii samples, or the reverse, was not detected through PSMs or specific peptides. These results demonstrate that sample homogenization, liquid disposal, reagent removal and incubation steps during the protocol do not have any impact on the purity of samples. Thus, the method can be easily applied to a microplate platform without any risk of cross-contamination.
Thus, the former approach is more discriminant than the latter as confirmed with the comparison carried out in the present study. The MS/MS spectra were recorded using a mass tolerant precursor of 5 ppm, a mass fragment ion of 0,02 Da and an isolation window of 1. 6 m/z. These values recommended by Thermo Scientific for measuring MS/MS spectra should be used for interpreting MS/MS proteotyping results. Because of the extra-large database used, appropriate control of the FDR is key for avoiding false-positive identification of microorganisms. Noteworthy, the additional signals recorded by MS/MS could increase the sensitivity of strategies related to high throughput dereplication of isolates  [38]  and could improve discrimination of strains at taxonomic ranks below the species level  [39]. Therefore, tandem mass spectrometry proteotyping could be used for systematically characterizing clinical isolates as a performant first-line epidemiological tool.
The 96-well plate format developed here is perfectly adapted for such an objective. The lack of reference spectra for most environmental bacteria and uncultivable microorganisms is another drawback of whole-cell MALDI-TOF mass spectrometry  [1]. As shown here for dental isolates, tandem mass spectrometry proteotyping is applicable to any microorganism and, based on the generalist database, can be used to ascertain the phylogenetic lineage of the isolate. Whole-cell MALDI-TOF mass spectrometry is not reliable for characterizing samples containing multiple microorganisms  [10]. Here, we confirmed that tandem mass spectrometry proteotyping can be applied to samples containing several microorganisms; indeed, complex mixtures can be characterized in terms of taxa present, but also in terms of biomass contributions  [14, 40].
Acknowledgements KH thanks the  Région Occitanie  for supporting part of his PhD fellowship. This work was funded in part by the  French joint ministerial program  of R&D against CBRNE threats and the  ANR program  " Phylopeptidomics " (grant number  ANR-17-CE18-0023-01 ). The authors are indebted to  Rosa Maria Gomila Ribas  ( Universitat de les Illes Balears, Serveis Cientificotècnics, Palma ) for performing the MALDI-TOF measurements in a contractual service mode and  Sebastian Alberti  ( Universitat de les Illes Balears ) for implementing an excellent technical platform.
Genetic diversity and inbreeding analyses We tested whether CP present a decrease in genetic diversity and an increase in inbreeding from the adult to the seed cohort stages (whereas no effect was expected for NCP). To this purpose, we estimated the following genetic diversity variables per population and per cohort in each population using the program SPAGeDi 1. 4  (Hardy and Vekemans, 2002) : number of observed alleles (NA), effective number of alleles (NA E ) following  Nielsen et al. (2003) , rarefied allelic richness (A R ) expressed as the expected number of alleles based on a minimum subsample size of k gene copies, expected heterozygosity (often called gene diversity) corrected for sample size (H E )  (Nei, 1978) , observed heterozygosity (H O ), and individual inbreeding coefficient (F).
We tested the significance of inbreeding coefficients using 10000 gene copy permutations. The presence of null alleles causes a bias in the proportion of heterozygosity and consequently affects the estimates of inbreeding coefficients within a population  (Chybicki and Burczyk, 2009). Therefore, we calculated the null allele frequencies per locus and the inbreeding coefficients accounting for null alleles in each cohort, using the population inbreeding model (PIM), a maximum likelihood approach implemented in the INEST 2. 2 software  (Chybicki, 2017). The inferred data of genetic diversity (NA E , A R , H E , H O , F) per locus and cohort in each population, clustered in two groups (NCP and CP), were used for statistical analyses, using an analysis of variance procedure in R (  R Core Team, 2013).
Mating system analyses Mating system parameters were estimated using the mixed mating model as implemented in the software MLTR 3. 4  (Ritland, 2002). Multilocus outcrossing rate (t m ) and single-locus outcrossing rate (t s ) were calculated from progeny arrays using known maternal parents and the Newton-Raphson estimation procedure. Selfing rate (s) was also assessed by NMπ software  (Chybicki, 2018). The standard error of mating system estimates was evaluated using 1000 bootstraps. The difference between t m and t s gives an indirect estimation of the presence of biparental inbreeding. The difference in means of mating system parameters between CP and NCP was assessed using a bootstrap procedure for independent samples in SPSS with the same parameters set above.
Pollen-mediated dispersal characteristics We relied on different methodologies to compare patterns of pollen-mediated gene flow between CP and NCP. Pollen dispersal parameters were first inferred through an indirect procedure using KINDIST and TWOGENER programs, as implemented in POLDISP software  (Robledo-Arnuncio et al. , 2007)  From the within-sibship-correlated paternity (r p , which is the probability of sharing the same father within a maternal sibship), we calculated the mean effective number of pollen donors that participate in cross-pollination as N EP = 1/r p. We tested whether the among-sibship-correlated paternity is inversely correlated with the distance between mother trees using a Mantel test procedure as implemented in the zt software  (Van de Peer, 2002). For each population, the slope was negative and significant.
The different pollen dispersal distribution models available in POLDISP (normal, exponential, exponential power, geometric, 2Dt) were then tested for each population. Reference threshold distances were set to 50, 200, 275, and 300 m in Saki, Cassou, Walley, and Vouza, respectively, as there was no decrease of the among-sibship correlated paternity beyond these distances. Second, we used the TWOGENER program to estimate pollen dispersal parameters using an exponential-power dispersal distribution as the assumed dispersal kernel because it provided a better fit to data as demonstrated by least-square residual values. The effective male population density (D EP ) was estimated with TWOGENER using as input the scale parameter of the dispersal distribution (a) as estimated with KINDIST (Appendix S5).
e. , fathers outside the plot); (4) mean distance of pollen dispersal (d p ); (5) shape parameter of pollen dispersal kernel (b p ) (b < 1 for a fattailed distribution, b = 1 for an exponential distribution, b = 2 for a Gaussian distribution); and (6) the effect of DBH on male reproductive success. For each population, analyses were run on two data sets: (1) all adults from the plot only (used to estimate m p ); (2) all adults from the plots and the transects (used to estimate other characteristics of the pollen kernel, notably the shape parameter that is more accurately estimated using the whole data set). Finally, we estimated the male reproductive success by studying the relationship between the number of times an individual has been identified as a male tree by paternity analysis (number of pollination events it has contributed to) and its diameter at breast height (DBH).
To this aim, we used a generalized linear model (GLM) with negative binomial distribution and log-link. Covariates were the DBH, its quadratic term and the interaction with the respective tree population. The DBH has been centered to its sample mean value (48. 7). To test differences in mean values of pollen dispersal (r p , N EP , δ p ) between CP and NCP, we performed a bootstrap procedure for independent samples using SPSS as above based on pollen dispersal data inferred per maternal trees in each population from KINDIST and CERVUS.
ACKNOWLEDGMENTS The present study is part of the Ph. D. thesis of D. L. at the  University of Natural Resources and Life Sciences, Vienna, Austria. This article has been made possible thanks to financial support from the  Austrian Development Agency  for the project " Threats to food tree species in Burkina Faso " led by  Bioversity International (now "The Alliance" of Bioversity International and CIAT)  and to additional support through the  CGIAR Research Program on Forests, Trees and Agroforestry. We also thank colleagues and technicians from the  Centre National de Semences Forestières of Burkina Faso (CNSF)  for field assistance, including fruiting surveys and collection. We thank  Olga Spellman  ( Bioversity ) for her help in editing the manuscript and two anonymous referees for helpful comments on earlier drafts of the manuscript.
Since the recent Divisions started in 2012, the numbers above are the total numbers of members registered in the database between 2012 and now, without taking in account if a member is still active today. Moreover, they cover all IAU's Member States and are not limited to ESA's Member States. Finally, it is important to notice that not all planetary scientists in Europe are members of IAU, therefore most probably these values underestimate the number of women in the field. Comparing the data for 2010 and 2014 shows that in most staff grade the proportion of staff who are female has risen  (Massey, 2015). 26 % of IAU members in France are women. We have also tried to estimate the percentage of women in planetology in France relying in particular on the statistics made by the National Planetology Program (PNP, Programme national de planétologie: Alessandro Morbidelli, personal communication, 2018).
Acknowledgements. We would like to thank  Robert Massey  and an anonymous reviewer for their comments that greatly improved the manuscript. We are also immensely grateful to the  IAU , and in particular to  Madeleine Smith-Spanier , to  Gonzalo Tancredi  and to  Sarah Gibson  for their precious help to provide us IAU statistics. We thank the  Programme national de planétologie  for giving us access to their statistics. Finally, we would like to thank everyone who helped us both by providing useful information as well as fruitful and encouraging discussions. Review statement. This paper was edited by  Chiaki Oguchi  and reviewed by  Francesca Matteucci ,  Robert Massey , and one anonymous referee.
Single-cell qRT-PCR Gene expression analysis in single cells was measured using the C1 Single-Cell Auto Prep System coupled with the real-time PCR reader BiomarkHD (Fluidigm, CA) according to Fluidigm recommendations in untreated cells and in cells treated with 50 µM TMZ for 4, 9, 12, and 16 days. Single-Cell PreAmp IFC 10-17 and 17-25 µM were used, respectively for U251 S , U251 R , and U251 TR(D4, D9, D12). Results were analyzed using the Singular Analysis Toolset Software provided by Fluidigm. The list of primers is given in Supplementary Table  1.