dataesr/scientific-paragraphs-categorization huggingface dataset:
Data analysis The p T balance of dijets is measured using the leading and subleading jets. This balance is quantified by the ratio of the subleading to leading jet p T , denoted x J. Dijets are selected from the two highest p T jets within a window of |η| < 1. 5. The p T of the leading and the subleading jets are required to be above 100 and 40 GeV, respectively. This asymmetric p T selection is chosen to ensure sensitivity to quenching effects. The subleading jet threshold of 40 GeV is chosen to keep the subleading jet-finding efficiency reasonably high, as will be described below. The leading jet threshold of 100 GeV is a compromise between statistical precision, on one hand, and maintaining a large lever-arm with the subleading jet, on the other. For the case of b dijets, the leading and subleading jets are chosen prior to b-tagging selection.
Corrections are derived from simulation for both the leading and subleading jet. We also correct for the variation of the b tagging efficiency within the centrality selections presented in this analysis. f (p T ) = exp[b exp(cp T )], In order to probe for quenching or other nuclear effects on the balance distributions, a baseline is constructed using pp data as a reference. Since the deterioration of the jet p T resolution with increasing collision centrality introduces an additional imbalance in the x J distributions, a direct comparison of PbPb and pp measurements does not solely reflect the nuclear modifications. This issue is addressed by smearing the transverse momentum of the jets in pp data by the amount that corresponds to the additional underlying event fluctuations estimated from HYDJET simulations that have been tuned to match the underlying event density in PbPb data.
Jet energy resolution The uncertainly from the jet resolution is propagated by varying the resolution parametrization in Eq. 2. The effect on the x J distribution is evaluated by applying these alternate smearing parametrizations to particle-level jets. In pp collisions, the C and S parameters are varied by 0. 02 and 0. 2 √ GeV, respectively. For PbPb collisions, in addition, the N term is varied by 2 GeV, which covers the difference in underlying event between data and simulation, and the variation of the resolution within the wide centrality bins. Although the results are not unfolded for the resolution effects, the uncertainty is fully included in the data points in order to correctly evaluate any theoretical models that fold in the resolution effects for comparison.
The reweighted distribution is also shown in  Fig 4. Finally, the data are also compared to simulations based on next-to-leading order matrix elements, as encoded in the hvq package  [26]  of the POWHEG BOX  [27]  (v2) generator. Hadronization in the POWHEG method  [28, 29]  is performed by matching the matrix elements to parton showers, which in this case are generated with PYTHIA 8. 212  [30] , tune CUETP8M1  [31]. The POWHEG + PYTHIA 8 simulations are found to give a good description of the b dijet data. Figure  5  shows the x J distributions for inclusive dijets and b dijets for three different centrality selections of PbPb collisions. Here the data are compared to the reference obtained from pp data by smearing the p T of each jet according to a parametrization of the resolution for the given centrality class.
2a ). CO1 sequences were deposited in Genbank (accession numbers MK033247-MK033269, Supplementary Table  S1 ) including the first CO1 sequences for Ad. madagascarica, and two Uranotaenia species from Madagascar, as well as the first Cx. decens sequences covering this region of the CO1 gene. Surprisingly, we found no evidence of resident Wolbachia strains in members of the Cx. pipiens complex indicating the absence of the wPip strain which is usually ubiquitous in Cx. pipiens pipiens and Cx. pipiens quinquefasciatus sibling species  42. As species within the Cx. pipiens complex are morphologically indistinguishable, we selected a sub-sample of individuals from different collection sites to determine the species using both species-specific PCR analysis and sequencing targeting a CO1 gene fragment that discriminates species within the Cx.
2b ). We also analysed three females that were morphologically identified as Cx. pipiens complex individuals but did not result in any species confirmation through PCR (Fig. 2b ). CO1 sequencing indicated these individuals were genetically diverse and, with the sequences currently available for comparison, were most closely related to Cx. rima and sequences named Cx. sp. GP-A from Kenya -Genbank accession number KU380413. 1 (94% nucleotide identities, but only 89-94% coverage to the gene fragment amplified), suggesting the possibility of unknown Culex species present in Madagascar. We also screened individuals from all mosquito species for Asaia and detected the presence of this competing bacteria in 13 of 17 species (Table  2 ). Variable prevalence rates were observed and we detected co-infections of Wolbachia and Asaia in Ad.
MLST resulted in successful sequencing of the majority of gene loci, although we were unable to amplify hcpA from wUnif-Mad despite using alternative protocols with degenerate primers (Table  3 ). ftsZ universal primers  47  were also needed to obtain a sequence for wMad. Each of the wMad gene sequences produced an exact match to alleles already present in the database, with the resulting allelic profile producing an exact match with strain type 125. This allelic profile matches four isolates currently present in the MLST database, detected in three Lepidopteran species, from French Polynesia, India, Japan and Tanzania (Isolate numbers 40, 247, 270 and 322 respectively), but no isolates from mosquito or other Dipteran hosts. The remaining strains had new alleles for at least one of the MLST gene loci (sequences differed from those currently present in the database by at least one nucleotide difference per locus), resulting in new allelic profiles highlighting the diversity and novelty of these resident strains.
Wolbachia gene sequences were deposited in GenBank (accession numbers MK026554-MK026563 and MK033270-MK033320, Supplementary Table  S2 ). The phylogeny of these novel strains based on concatenated sequences of all five MLST gene loci (where possible) (Fig. 5 ), or four MLST gene loci for analysis of wUnif-Mad (hcpA sequence not available) alongside the other strains (Fig. 6 ), also reveals significant strain divergence. As expected, due to the general incongruence between host phylogenetic relationships and their resident Wolbachia strains  48, 49  , the majority of the novel Wolbachia strains in our study provide no evidence for clustering with other strains that infect mosquitoes. One exception is the wMad strain which, although distinct, appears closely related to wPip (the resident strain normally present in the Cx.
95), comprising 26 nucleotide sequences. There were a total of 669 positions in the final dataset. (b) Maximum Likelihood phylogenetic analysis for selected Culex mosquito species targeting a second CO1 gene fragment  43  showing a tree with the highest log likelihood (-2078. 87), comprising 22 nucleotide sequences. There were a total of 638 positions in the final dataset. Wolbachia-infected = (W+), Wolbachiauninfected = (W-), Rift Valley fever virus-infected = (RVFV+). abundant in the central domain  50. In Madagascar, this species was previously shown to be infected with WNV and Babahoyo virus  50  and in mainland Africa has been shown to be infected with additional arboviruses including Moussa virus  51. The wMad strain was found in all Ad. madagascarica individuals we collected from Tsaramandroso.
In our study, Asaia was also detected in the single Wolbachia-infected Cx. antennatus individual so further studies should be undertaken to determine the dynamics of these microbes within wild mosquito populations. The prevalence of Asaia is highly dependent on the environment given this Figure  6. Maximum Likelihood phylogenetic analysis from concatenation of four MLST loci (coxA, fbpA, ftsZ and gatB). The tree with the highest log likelihood (-7114. 64) is shown incorporating 75 nucleotide sequences. There were a total of 1624 positions in the final dataset. Concatenated sequence data from Wolbachia strains downloaded from the MLST database for comparison are shown in teal (mosquito strains) and black (all other host strains), with isolate numbers from the MLST database shown in brackets.
Concatenated Ma. uniformis sequence data from Kenya 60 (Isolate number 500) downloaded from the MLST database is highlighted in teal and denoted with a clear circle, for comparison with the wUnif-Mad strain (blue with filled circle) detected in this study. Other novel resident strains discovered and characterised in our study are highlighted in colour and denoted with filled circles. bacterium can be acquired through various routes including from males to females during mating and from both larval and adult mosquito sugar feeding  73. For example, prevalence rates of 46% were seen in field-caught Ae. albopictus from Madagascar 74 but the overall composition and diversity of the mosquito microbiota in field populations of Ae. aegypti and Ae. albopictus in Madagascar is also highly dependent on environmental factors  75, 76.
Amplification was followed by a dissociation curve (95 °C for 10 seconds, 65 °C for 60 seconds and 97 °C for 1 second) to ensure the correct target sequence was being amplified. PCR results were analysed using the LightCycler ® 96 software (Roche Diagnostics). Asaia detection was also undertaken targeting the 16S rRNA gene  73, 81. Wolbachia MLST. Multilocus sequence typing (MLST) was undertaken to characterize Wolbachia strains using the sequences of five conserved genes as molecular markers to genotype each strain. In brief, 450-500 base pair fragments of the coxA, fbpA, hcpA, gatB and ftsZ Wolbachia genes were amplified from one individual from each Wolbachia-infected mosquito species using previously optimised protocols  45. A Culex pipiens gDNA extraction (previously shown to be infected with the wPip strain of Wolbachia) was used a positive control for each PCR run, in addition to no template controls (NTCs).
ZIKV screening was undertaken using a Taqman probe-based assay using 5 µl of Qiagen QuantiTect probe master mix, a final concentration of 1 µM of each primer, 1 µl of PCR grade water and 2 µl template cDNA, to a final reaction volume of 10 µl. PCR results were analysed using the LightCycler ® 96 software (Roche Diagnostics). Synthetic long oligonucleotide standards (Integrated DNA Technologies) of the amplified PCR product were generated in the absence of biological virus cDNA positive controls and each assay included negative (no template) controls.
Acknowledgements We would like to thank all the villagers who participated in the fieldwork. Funding was provided by the  London School of Hygiene and Tropical Medicine ,  Bayer Pharmaceuticals  and a  Wellcome Trust/Royal Society  grant awarded to TW ( 101285/Z/13/Z ): http://www. wellcome. ac. uk; https://royalsociety. org. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
The tree with the highest log likelihood (-681. 38) is shown, comprising 17 nucleotide sequences. There were a total of 335 positions in the final dataset. Resident Wolbachia strains detected in our study are highlighted in colour, denoted with circles and multiple 16S rRNA sequences from individuals of the same species are included where possible. For comparison, a diverse range of strains available from GenBank were included (shown in black, with accession numbers included).
In order to increase the robustness we used pre-exposure RNA samples from other baboons than the RNA samples taken after irradiation (Table  1 ). The sample number Continued for screening purposes taken after irradiation was higher (seven instead of five), because of their higher yield of RNA per sample, which were not used in previous examinations and, therefore, more RNA remained for this analysis on persistent gene expression over time. We used the Agilent oligo microarray GE 8 × 60 K (Agilent Technologies, Waldbronn, Germany) combined with a one-color based hybridization protocol of GeneSpring GX12 software for data analysis as described in detail elsewhere  22. We analyzed gene expression by quantile normalized log 2 -transformed probe signals as an outcome. We used the non-parametric Mann Whitney (MW) test to compare gene expression across the different time points using the unexposed group as the reference (control).
Gene expression data presented in this publication have been deposited at the NCBI's Gene Expression Omnibus (GEO accession number GSE77254). Stage II: Validation of stage I candidate genes via qRT-PCR. For validating the mRNA candidate genes from stage I (screening) using remaining RNA samples, we used a custom LDA and TaqMan chemistry (order IDs for the examined genes are provided in Table  2 ). A 1 µg RNA aliquot of each RNA sample was reverse transcribed using a two-step PCR protocol (High Capacity Kit). 400 µl cDNA (1 µg RNA equivalent) was mixed with 400 µl 2 x RT-PCR master mix and pipetted into the 8 fill ports of the LDA. Cards were centrifuged twice (1,200 rpm, 1 min, Multifuge3S-R, Heraeus, Germany), sealed, and transferred into the 7900 qRT-PCR instrument. The qRT-PCR was run for two hours following the qRT-PCR protocol for 384-well LDA format.
Cards were centrifuged twice (see above), sealed, transferred into the 7900 RTQ-PCR instrument and again the 384-well LDA RTQ-PCR protocol was run over two hours. For the custom LDA, threshold cycle (CT) values were normalized relative to the 18S rRNA measured in an aliquot of the RNA samples using a 96-well-format TaqMan qRT-PCR platform. We have found that this approach to normalization was more robust compared to the use of the internal control (GAPDH and 18 S rRNA) spotted on the LDA. For the commercial miRNA LDAs type A and B we used the median miRNA expression on each LDA for normalization purposes, because this proved to be more robust and a slightly more precise method compared to a normalization approach using a housekeeping miRNA species provided on the LDA (data not shown). The CT-values of the housekeeping gene was subtracted from the CT-value of each of the spotted genes, following the ∆CT-quantitative approach for normalization purposes.
Finally, we made comparisons on how the various categories of predictor variables were associated with newborn WAZ or LAZ. We imputed missing data for predictor variables and intermediary variables as well as outcome variables that were measured after 6 weeks from delivery. We used multiple imputed data (50 imputations) based on chained equation methods, for all ordinary leastsquares regression and logistic regression analyses. Among the included participants for regression analyses, the number of originally missing values that were substituted with values obtained by multiple imputation ranged from 0 to 480 (0. 0% to 34. 8%) per variable (Supplementary Table  1 ). We estimated regression coefficients for continuous variables and odds ratios for dichotomous variables when estimating associations between variables in bivariate and multivariable models.
We considered p values below. 05 indicative of statistical significance also in SEM. Because we could not estimate parameters for pathways leading to the dichotomous variables (maternal malaria, HIV, and primiparity) with SEM, we established the direction of association from regression models and indicate the associations with dashed lines in the pathway graphs. As a sensitivity analysis to SEM, we used random forest modelling and forest plots (R Version 3. 2. 1, number of trees to grow 1,000). We imputed missing values in predictor data using R software's command rfImpute in random forest and regressed WAZ and LAZ against all the tested predictor and intermediate variables and calculated raw variable importance for all predictor and intermediate variables. All statistical analyses were done with either Stata Version 13.
| RESULTS Of the 1,391 women who were enrolled into the iLiNS-DYAD-M study, 1,379 (99. 1%) provided data for analyses with predictor and intermediary variables and 1,179 (84. 8%) provided data for the analyses also with child anthropometrics. The reasons for exclusion were twin pregnancy (12 subjects) and lack of any anthropometric information for the infant (because of loss of pregnancy, death, or drop-out; 200 subjects). The included women were less often primiparous than the excluded ones (19. 5% vs. 35. 1%). For other baseline characteristics, there were some statistically significant but clinically nonsignificant differences between the included and excluded participants (Table  1 ). Of the newborns, 91 (7. 8%) had either length or weight values estimated by multiple imputation, because the actual values were collected only after 6 weeks of age.
ACKNOWLEDGMENTS We thank the study participants, the local communities, the health service staff, and our research personnel at the study sites as well as members of the trial's data safety and monitoring board, the iLiNS extended research team, and the iLiNS-Project  Steering Committee  (http://www. ilins. org/)for their positive attitude, support, and help in all stages of the study. We particularly thank  André Briend  for trial conceptualization and  Mary Arimond  for iLiNS-Project management.
respondents/sample US participants were recruited through the KnowledgePanel ® maintained by GfK Custom Research, LLC, USA. UK participants were recruited through MrOps (London, UK; see Supplementary materials for further details). Both market research panels required consent from each member when joining, with the expectation that they would participate in surveys and their anonymized data could be used in publications. Each participant also signed an online consent form to participate in this study. Due to the nature of the study, which involved market research panels with informed consent, ethical approval was not required (for further information see Supplementary materials). The medical history and demographic characteristics of the panel members were documented in advance of the study.
Data collection Data were collected using the self-administered online survey. Respondents in the MDD and general population samples completed the PHQ-9 at screening and the remaining survey questions at baseline. Only respondents in the MDD population were invited to complete the survey again at 6 weeks (±7 days) after baseline (Figure  1 ). To prevent long delays in completing items in the survey, potential respondents were asked to complete the surveys online at their selected location within a 24-hour window. If a respondent failed to complete the baseline survey within 24 hours of starting, their data were excluded from the study analyses. Before the study, the survey was pre-tested using 30 respondents each from the US and UK samples who met all MDD inclusion criteria and none of the exclusion criteria.
analyses It should be noted that the study was not an opinion poll survey where the objective is to extrapolate to a specific target population via weighting of observations. As a consequence, no weighting was applied to the patient observations. Analyses conducted included assessment of internal consistency reliability, convergent validity, known-groups validity, responsiveness to change, and CFA. With the exception of the known-groups validity, responsiveness to change analyses, and the CFA, all analyses were conducted using baseline PDQ-D scores from the MDD samples only. With the exception of the CFA, all analyses were conducted separately for the US and UK samples. The CFA sample included respondents from both MDD and general population samples pooled across both countries. Data were analyzed using Statistical Analysis Software (SAS ® ; SAS Institute Inc.
, Cary, NC, USA) Version 9. 2, Statistical Package for the Social Sciences (SPSS ® ; SPSS Inc. , Chicago, IL, USA) Version 17. 0, or MPlus ® (Muthén & Muthén, Los Angeles, CA, USA) Version 5. No missing-data imputation methods were used. Patient-reported instrument scores were only calculated for respondents who completed all constituent items. Descriptive statistics, including median, mean, and SD of observed values and percentage of respondents with missing scores, were determined for each item, subscale, and the total score of the PDQ-D at baseline for the US and UK MDD samples. To determine any potential differences between sample populations, sex distributions of the US and UK MDD samples were compared using Fisher's exact test, and mean age and mean scores of all patient-reported measures were compared using independent-sample t-tests.
ethics approval Data were collected by survey companies through their existing approved market-research panels, following their own procedures. When subjects are enrolled in such panels, they provide the panel owners with written informed consent, and agree to be contacted for participation in online surveys. For this survey, we ensured that the participants signed an additional informed consent form to participate. In the US, this type of survey is exempt from Institutional Review Board approval according to guidelines from the US Office for Human Research Protections which stipulate that research involving the use of educational tests (cognitive, diagnostic, aptitude, achievement), survey procedures, interview procedures or observation of public behavior, are exempt unless: 1. Information obtained is recorded in such a manner that human subjects can be identified, directly or through identifiers linked to the subjects; and 2.
Acknowledgments The authors thank  Jakob Bjorner, MD, PhD , of  Optum, Inc. , who assisted with some of the data analyses and interpretation (particularly the CFA). Editorial assistance was provided by  Julie Adkins  of  Anthemis Consulting Ltd  and funded by  Lundbeck SAS. The study and editorial assistance in preparing the paper were funded by  Lundbeck SAS. Lundbeck personnel were involved in the study design, in the collection, analysis, and interpretation of data, in the writing of the report, and in the decision to submit the article for publication. Preliminary results were presented at the 16th Annual European Congress of the  International Society for Pharmacoeconomics and Outcomes Research (ISPOR)  as a poster presentation. November 2-6, 2013 Dublin, Ireland. The poster's abstract was published in "Poster Abstracts" in Value in Health (Value in Health 2013;16: A330 ).
no. 554723). Subsequently, cells were resuspended in 50 µl of 1× Perm/Wash Buffer and stained with a rabbit polyclonal anti-LRBA antibody (Sigma; cat. no. HPA023597 or HPA019366, dilution 1:400) for 30 min at 4°C. A secondary antibody F(ab′)2 donkey anti-rabbit IgG-PE (BD; cat. no. 558416, dilution 1:25) was added and incubated at 4°C for 30 min. Cells were then washed and acquired on a FACS Canto II (BD). Data analysis and calculation of the geometric mean fluorescence intensity (MFI) were performed using FlowJo TM 7. 6. 5 software (TreeStar Inc. , Ashland, OR, USA). Gating strategy was done as follows: cells were first gated for mononuclear cells (SSC-A vs. FSC-A) and singlets (FSC-H vs. FSC-A). Then, living mononuclear cells were gated based on the negative staining for the FVD and separated in cell subsets according to their extracellular markers.
Western Blotting Protein lysates were size-fractionated by SDS-PAGE (12, 8, and 4% gradient gel), electrotransferred to a PVDF membrane for 1. 5 h at 45 V and immunodetected with a rabbit polyclonal anti-LRBA antibody (Sigma-Aldrich; cat. no. HPA023597). The specific binding of the antibody to the LRBA protein was detected with a secondary HRP anti-rabbit IgG (Cell signaling; cat. no. 7074) as a band of ~319 kDa. Tubulin (Abcam; cat. no. 4074) was used as protein loading control, and was detected as a band of ~50 kDa.