dataesr/scientific-paragraphs-categorization huggingface dataset:
Of the nine parameters, minimum peak height and minimum peak size were determined by examining the negative control profile for a sample lacking DNA. The minimum peak height was set slightly above the highest value seen in the negative control profile, while minimum peak size was designated as bands showing at least 3-fold increase in signal to noise ratio relative to the negative control. Peaks ranging from 48 bp to a maximum of 350-500 bp, depending on the primer pair, were included in the analysis. tinyFLP  (Arthofer, 2010)  generates statistical data for all the bands allowing the user to identify: 1) samples with poor performance; 2) monomorphic bands that are present in all the samples and have no phylogenetic value, and 3) artifacts e. g. , bands that appear in only one sample. Bins with rare alleles present only in one sample, as well as monomorphic bands that lack phylogenetic information, were removed from further analysis.
tinyCAT was used to concatenate the binary allele matrices (BAM) for each sample, using the 6 different primer combinations, into one combined matrix  (Arthofer, 2010). This combined BAM was used in all subsequent applications for phylogenetic analysis  (Arthofer et al. , 2011). A network tree containing 37 strains was generated using the program SplitsTree 4  (Huson and Bryant, 2006 ) by using Neighbor-net from 411 data points i. e. , AFLP peaks  (Bryant and Moulton, 2004). Validation of the AFLP data and the phylogenetic tree derived by combined analysis using 6 primer pairs was carried out by bootstrapping  (Holland et al. , 2008). The reliability of AFLP markers was assessed by the error rate, which is the ratio of the number of mismatched loci to the total number of loci  (Bonin et al.
S1 , panel B). S2 ) was performed on 36 L. donovani strains from SD and Ethiopia, and L. major included as an outlier. These primer pairs were chosen because they gave the most intense PCR products and widest molecular weight range of products of all the 12 primer pairs examined in initial AFLP runs on six of the strains. Of the 456 AFLP alleles included in this study, 45 alleles (~10%) were monomorphic while the remaining 411 (90%) were polymorphic. A Neighbor-net network (Fig. 2 ) was built using the 411 polymorphic data points i. e. , AFLP peaks. Strains GR353 (NE2a and NE2b) and LEM3459 (SD8a and SD8b) were used as internal controls. The selective PCR was performed in duplicate using the same pre-selective PCR product giving essentially identical replicates. As can be seen in Fig. 2  strains from Southern Ethiopia (SE) group separately from the Northern Ethiopian and Sudanese (NE/SD) strains.
, 1992). Thus, the finding that L. donovani skin isolates have lower number of polymorphic AFLP fragments than non-skin isolates warrants further investigation. kDNA minicircle sequencing was also used to examine genetic diversity of all the East African L. donovani strains. A high degree of polymorphism was observed using this approach where the isolates Fig. 5. Phylogenetic tree of East African Leishmania donovani strains based on analysis of kDNA minicircle sequences. The sequences (GeneBank accession numbers KY950645 to KY950679) were aligned using Muscle algorithm with gaps, and the phylogenetic tree was built using the Maximum Likelihood method based on the Hasegawa-Kishino-Yano model  (Hasegawa et al. , 1985)  using MEGA7  (Kumar et al. , 2016)  as described in Material and Methods.
Acknowledgements All 'LEM' strains from Sudan were isolated by  Dr. Jacques Dereure  ( French National Reference Center for Leishmanioses, Montpellier, France ). This work was supported by grant  OPPGH5336  from the  Bill and Melinda Gates Foundation  to A. H. and C. L. J. The authors would like to thank  Dr. Wolfgang Arthofer ,  University of Innsbruck, Innsbruck, Austria  for his help and useful discussion regarding the programs optiFLP, tinyFLP, and tinyCAT. C. L. J holds the  Michael and Penny Feiwel Chair of Dermatology.
1 ). A previously predicted CDP-diacylglycerol (DAG)-dependent PSS enzyme (  7 ) has now been reannotated as a phosphatidylglycerolphosphate synthase (PF3D7_0820200) in the Plasmodium database (www. plasmodb. org). In the present study, we determined the contribution of the different pathways to the biosynthesis of PC, PE, and PS, and we analyzed their regulation. To this purpose, we undertook a lipidomic analysis of P. falciparum-iRBCs using deuterium-labeled Cho, Etn, and Ser as tracers to follow the different PL pathways (supplemental Fig. S1 ). We identified the reaction intermediates and the final PL products of each pathway by LC/MS/MS and quantified the relative contribution of each pathway to the biosynthesis of the three main PLs. When we started our study, Cho from serum (10-15 µM) (Human Metabolome Data Base, http:// www.
Characterization of PL species by shotgun-mass spectrometry Shotgun-mass spectrometry analysis by ESI was carried out according to the protocol previously described  (34). Dried PL extracts were dissolved in 500 µl of a mixture of chloroform/ methanol (2/1: vol/vol) containing 7. 5 mM ammonium acetate. Each sample was infused into the TurboV electrospray source of a QTRAP 5500 mass spectrometer (AB Sciex, Concord, Canada) at a flow rate of 7 µl•min 1 , with fast polarity switching (50 ms) at a scan rate of 200 Da/s. ESI-MS/MS experiments in precursor ion scan were performed in negative ion mode to screen for PE and PS and led to 53 precursor ion scans. In positive ion mode, one precursor ion scan allowed screening for PC. PL species were identified using Lipid View software (version 1. 2, AB Sciex).
At the liver stage, Plasmodium seems to rely on PC taken up from the hepatocyte host cell  (38). However, KO of host CT (CCT) did not affect parasite growth or merozoite formation, but impaired parasite survival, suggesting that Plasmodium is able to produce its own PC at this stage  (38). PE was synthesized about equally from Etn (43%) and from Ser (57%). Increasing the Etn-d 4 concentration in the culture medium induced a sharp decrease of PE synthesized from Ser. The incorporation of Ser into PE is possible via two pathways: decarboxylation of PS or decarboxylation of the precursor Ser and synthesis via the CDP-Etn-dependent Kennedy pathway (Fig. 1 ). PSD activity has been demonstrated for Plasmodium  (24) , and a PSS-base-exchange enzyme (PSS2) is annotated in the genome database. Direct decarboxylation of Ser has been described in plants  (23) , and Ser decarboxylase catalytic activity has been suggested in P.
•GWAS and data computing of heritability indice To calculate heritability, we estimated variance components using a random effects model using the lme4 R package  [27]. Strain and experiment date were treated as random effects, and the heritability was calculated as VA/(VA+VD+VR), where VA is the additive genetic variance, and is equal to twice the Strain variance, VD is the experiment date variance, and VR is the residual variance. For the GWAS, we used the online tool specifically designed for the DGRPs (http://dgrp2. gnets. ncsu. edu/) [28, 29]. The Manhattan and QQ-plots were generated using R.
RNA-sequencing: We prepared the libraries using the BRB-seq protocol and sequenced them using an Illumina NextSeq 500  [11]. Reads from the BRB-seq protocol generates two fastq files: R1 containing barcodes and UMIs and R2 containing the read sequences. R2 fastq file was first trimmed for removing BRB-seq-specific adapter and polyA sequences using the BRB-seqTools v1. 0 suite (available at http://github. com/DeplanckeLab/BRB-seqTools). We then aligned the trimmed reads to the Ensembl r78 gene annotation of the dm3 genome mixed with the Lactobacillus Plantarum WJL genome using STAR (Version 2. 5. 3a) [30] , with default parameters (and extra "--outFilterMultimapNmax 1" parameter for completely removing multiple mapped reads). Then, using the BRB-seqTools v1. 0 suite (available at http://github.
com/DeplanckeLab/BRB-seqTools), we performed simultaneously the sample demultiplexing, and the count of reads per gene from the R1 FASTQ and the aligned R2 BAM files. This generated the count matrix that was used for further analyses. Genes were retained in the analysis if they had more than 10 reads in more than 50 samples. The data was subsequently transformed using the voom method. Differential expression was performed using the R Limma package  [31, 32]. Genes with a log 2 fold change greater than 2 and a Benjamini-Hochberg adjusted P-value less than 0. 05 were considered differentially expressed. Since the library preparation was performed in two plates, hence introducing a batch effect, we used the duplicateCorrelation function and included the batch as a blocking variable. Prior to PCA analysis and standard deviation calculations, we removed the batch effect using the removeBatchEffects function and then used the princomp function.
We used the cluster profiler package to perform GSEA analyses. The gmt file containing the gene ontology annotations was obtained from GO2MSIG data. Specifically, we used the high quality GO annotations for Drosophila melanogaster. For each GSEA analysis, we used 100,000 permutations to obtain adjusted p-values and only included gene set sizes to between 6 and 1000 genes. The raw expression data has been deposited in ArrayExpress (accession number: E-MTAB-6518) RNA-sequencing: We prepared the libraries using the BRB-seq protocol and sequenced them using an Illumina NextSeq 500  [11]. Reads from the BRB-seq protocol generates two fastq files: R1 containing barcodes and UMIs and R2 containing the read sequences. R2 fastq file was first trimmed for removing BRB-seq-specific adapter and polyA sequences using the BRB-seqTools v1.
0 suite (available at http://github. com/DeplanckeLab/BRB-seqTools). We then aligned the trimmed reads to the Ensembl r78 gene annotation of the dm3 genome mixed with the Lactobacillus Plantarum WJL genome using STAR (Version 2. 5. 3a) [30] , with default parameters (and extra "--outFilterMultimapNmax 1" parameter for completely removing multiple mapped reads). Then, using the BRB-seqTools v1. 0 suite (available at http://github. com/DeplanckeLab/BRB-seqTools), we performed simultaneously the sample demultiplexing, and the count of reads per gene from the R1 FASTQ and the aligned R2 BAM files. This generated the count matrix that was used for further analyses. The data was subsequently transformed using the voom method and analyzed using the R Limma package  [31, 32]. The raw expression data of BRB-Seq has been deposited in ArrayExpress (accession number: E-MTAB-6518) •The making and maintenance of germ-free flies Axenic flies were generated by dechorionating embryos with 50% household bleach for five minutes; eggs were then washed in successive 70% ethanol and sterile distilled water for three minutes each.
•Larval Length Measurement All live Drosophila larvae were collected from each nutritive cap containing low yeast diet by temporary immersion in sterile PBS, transferred on a microscopy slide, killed with a short pulse of heat (5 sec at 90°C), mounted with 80% glycerol/PBS. The images were taken with the Leica stereomicroscope M205FA and the lengths of individual larvae were measured using ImageJ software  [33]. For each DGRP strain and each cross and/or condition, at least three biological replicates were generated.
All images were taken measured using ImageJ software •Bacteria culture and mono-association For each mono-association experiment, Lp WJL  [34]  was grown in Man, Rogosa and To contaminate the garden-collected flies with their own microbiota, eggs were dechorionated and directly seeded onto appropriate food caps. Sterile PBS was used to wash the side of the bottles where the adult wild flies were raised to recover more fecal content, and 300 ul of the wash was inoculated to the dechorionated eggs. For GF control, 300 ul of sterile PBS was used to inoculate the dechorionated eggs. The microbial composition of this microbiota can be founded here  [15].
•Statistical Analysis and data representation GraphPad Prism software version 6. 0f for Macintosh (GraphPad Software, La Jolla California USA, www. graphpad. com) was used to compare GF and Lp WJL -associated conditions for larval length, developmental timing, adult emergence, allometry and linear regression analysis for the buffering effect. For small samples with less than 10 data points, nonparametric analysis was conducted. R-studio was used to conduct Levene's test and multivariate analyses. For all experiments, the p-values were reported on the corresponding figure panels only when inferior to 0. 05. Observed -log (p) Three different control knockdowns were used: one control fly strain recommended by VDRC for RNAi constructs obtained from VDRC, one control strain (against mCherry) recommended by the Harvard TRiP collection, and the y,w strain from Bloomington.
Acknowledgments We would like to thank  Benjamin Prud 'homme and colleagues at  ENS de Lyon  for their critical reading of the manuscript and valuable suggestions, the  Arthro-Tools platform the SFR Biosciences  ( UMS3444/US8 ) for the fly equipment and facility, the  Bloomington Stock Centre and VDRC  for fly lines. This work was supported by an international collaborative grant through the  French "Agence Nationale de la Recherche " and the " Fond National Suisse pour la Recherche " ( ANR-15-CE14-0028-01 ) awarded to F. L and B. D. , an  ERC  starting grant ( FP7/2007-2013-N_309704 ) awarded to F. L. , a  SystemsX. ch(AgingX)  Grant awarded to B. D and Institutional Support by the  EPFL  (B. D. ). CEI was funded by a  Ph. D. fellowship from the  Rhone-Alps region. F. L is supported by the  FRM/FSER foundation , the FINOVI foundation and the  EMBO Young Investigator Program.
Field activities The serological and oocyst data were collected through a longitudinal study on the infectious reservoir  [11]. Data are deposited in the Dryad repository: (http://dx. doi. org/10. 5061/dryad. v60jk42)  [52]. The study design and procedures for data analysis and modeling are summarized in Fig  1 ; clarifying where conventional statistical models were used to present and analyze study data and where data were incorporated into the EMOD malaria model to simulate their impact on malaria transmission and the human infectious reservoir for malaria. Study participants of all ages living in a hyper-endemic and seasonal malaria transmission setting of Burkina Faso were randomly recruited from four age groups (< 5 years, 5-14 years, 15-30 years and above 30 years of age) in proportions that reflect local demographic proportions (20%, 30%, 25% and 25% respectively).
Data analysis using statistical models All statistical analyses were performed in R version 3. 3. 1. Gametocyte positive samples in the Pfs25 mRNA QT-NASBA were considered submicroscopic if negative by microscopy. Median densities (optical density) of Pfs230 and Pfs48/45 antibodies were categorized by age group (1-4, 5-14 or 15+ years), season (start-wet, peak-wet or dry) and gametocyte density (sub-microscopic or microscopic) to describe antibody density dynamics. The proportion of seropositive individuals and infected mosquitoes were categorized by age group (1-4, 5-14, 15-30 and 30+ years) to describe antibody prevalence and mosquito infection dynamics. A Wilcoxon rank sum test was used to compare the mean oocyst density between samples seronegative versus seropositive to Pfs48/45 and Pfs230 antigens at different gametocyte densities (Submicroscopic, 0.
01-16, 17-100, !100 gametocytes/μL). A statistical test was considered significant if p 0. 05. A generalized linear mixed effect model (GLMM) was used to assess the impact of P. falciparum sexual stage immunity on oocyst intensity. The intensity of P. falciparum oocysts per individual mosquito midgut and per participant was used in this model as a proxy of humanto-mosquito transmission capability. Because natural malaria infections in endemic areas are unique to individuals, sophisticated regression analyses that account for confounding factors are required to isolate the effect of specific immune factors on malaria transmission. The GLMM grounded in R software AD Model Builder framework accounting for zero inflation, over-dispersion and repeated measurements was used to estimate the effects of anti-Pfs48/45 and Pfs230 antibodies on oocyst intensity assuming a negative binomial distribution of oocysts counts in the mosquito population.
Results One hundred and twenty-eight study participants with both P. falciparum sexual stage immunity and mosquito's feeding data were included in the data analysis. On the three occasions of seasonal sampling time points, 66 of the study participants were visited on three occasions, 31 twice and 31 once resulting in a total of 291 blood samples. NANP 6 antibody density and parasite density by QT-NASBA were obtained from 284 and 285 respectively of the 291 blood samples.
Acknowledgments We thank the  communities of Laye and Dapelogo (Poedogo, Niandeguin, Tanghin)  for their cooperation, the  Ministry of Health of Burkina Faso  for providing local staff support and operational logistics. We are grateful to  Jaline Gerardin ,  Caitlin Bever ,  Milen Nikolov ,  Hil Lyons  and  Min Roh  for helpful discussions.
In this study, the determinants of T. gondii seroconversion dynamics (used as a proxy of primo-infection dynamics) were investigated in five farm cat populations based on data from a two-year survey. Blood samples were collected and tested every three months to detect specific antibodies against T. gondii. Seroconversion rates were estimated in relation to the cats' age and gender and to the season using multi-event capture-markrecapture (CMR) to account for the uncertain age and serological status of cats that were not captured and not tested for T. gondii antibodies. The probabilities of misclassifications in the assignation of serological status (i. e. apparent false-negative and false-positive results) was also estimated since multi-event CMR models do not require a one-to-one correspondence between a test result and the serological status, but rather estimate the probabilities of each test results conditional on each serological status (e.
Three age classes were considered: 'kittens' , from two to three months-old; 'juveniles' , from four to six months-old; and 'adults' , over 6 months-old. The age class was estimated based on birth observation or other information collected from farm owners and/or on teeth development  [38]. Cat sociability towards humans was also recorded: 'easy to catch by hand' or 'need trap to be caught'. Lastly, information on cat mortality events was also collected from farm owners to complement the dataset.
Multi-event capture-mark-recapture modelling Because unsociable cats were not captured during some sampling sessions, we performed analyses under the general framework of multi-event capture-mark-recapture models (CMR) accounting for uncertainties about state of some individuals (sensu 'partial observations') and for heterogeneity in capture rates between sociable and unsociable cats. Two sources of uncertainty in state assessment were observed in the dataset and considered in the models: (i) uncertainty about the serological status of some re-sighted individuals whose blood was not collected and thus not tested for the presence of T. gondii antibodies; and (ii) uncertainty about the age class of some individuals due to incomplete information about birth date and teeth. These uncertainties were considered explicitly in the capture histories by taking into account 15 events defined as follows: 0, not detected; 1, kitten tested with titre = 0; 2, kitten tested with titre ≥ 25; 3, kitten detected but not tested; 4, juvenile tested with titre = 0; 5, juvenile tested with titre ≥ 25; 6, juvenile detected but not tested; 7, adult tested with titre = 0; 8, adult tested with 0 < titre < 25; 9, adult tested with titre ≥ 25; 10, adult detected but not tested; 11, individual of undetermined age tested with titre = 0; 12, individual of undetermined age tested with titre ≥ 25; 13, individual of undetermined age detected but not tested;14, cat recovered dead.
Goodness-of-fit tests and model selection No specific test exists to detect a structural lack of fit of multi-event models to data  [9]. In this study, the goodness-of-fit of the multi-event model was assessed after pooling all 'detected alive' events, resulting in a multi-state dataset containing only alive and dead encounters and ignoring uncertain states. The goodnessof-fit for the fully time-dependent Jolly-Move (JMV) multi-state model  [53]  was then applied using the U-CARE program version 2. 3. 2  [54]. Multi-event models were fitted using the E-SURGE program version 1. 9. 0  [55]. The model selection procedure was performed following a bottom-up approach (see Additional file 1: Table  S1  for details on the starting model and the selection procedure). First, the best structure for initial states, i.
53% of the kittens born during the study on this farm). Based on a cut-off value of titre = 25, the estimated seroprevalence over the study period varied from 15. 38% in farm T to 73. 08% in farm F (see Table  2 ). When a cut-off value of titre = 10 was considered, seroprevalence varied from 29. 63% in farm B to 73. 08% in farm F (Table  2 ). ). An effect of sociability on detection rate was thus considered in the starting model. Cat age was also a variable which may favour the detection of heterogeneity in our dataset, since cats ≤ 6 months were almost systematically detected at each occasion contrary to adults. This effect was taken account in the models and tested on each parameter.
Acknowledgements The authors would like to thank all the farm owners who permitted access to their properties and their cat populations and who provided very useful information on cat population dynamics. The authors also warmly thank the two anonymous referees for helpful comments on the previous version of the article. All authors are grateful to  Alain Simon ,  Pierre Belle-Isle ,  Marion Dellinger ,  Sabine Kurdzielewicz ,  Céline Sakonda ,  Candice Gagnaison  and  Marie Bonneric  for their assistance in the field work.
The baseline demographic characteristics of the three PvDBPII dose groups and GeneVac-B control vaccine group were comparable (Table  1 ). There was no significant difference between the test and control groups with respect to weight, height and age across all doses. The first subject was enrolled in October 2016 and the last subject completed the protocolspecified last visit, i. e. , day 180 after first vaccination in July 2017. The study was stopped after the last subject successfully completed the last follow-up visit. Subjects in higher PvDBPII dose cohorts were immunized with an escalated vaccine dose only after review and receipt of written recommendation from an independent Data Safety Monitoring Board (DSMB), overseeing the trial as per the predefined DSMB charter. One subject each in cohorts 1 and 2, respectively, dropped out of the study before the second immunization visit.
3. Although the qualitative IFA results support the ELISA data and confirm seroconversion to PvDBPII vaccine, the observed low level nonspecific reactivity of some Day 0 sera with parasites makes it difficult to draw any specific conclusion about end point titres for IFA reactivity. PvDBPII-specific antibodies block binding of PvDBPII with DARC Next, to determine whether anti-PvDBPII antibodies in serum samples were able to block interaction of PvDBPII with its receptor DARC, Day 0, 84 and 180 serum samples were tested in an ELISAbased binding-inhibition assay (BIA). Sera were tested at different dilutions from 1:10 to 1:10,000, with percentage binding inhibition calculated for each dilution. Fifty percent binding-inhibition titres were determined from percent inhibition vs dilution curves.