dataesr/scientific-paragraphs-categorization huggingface dataset:
Results The initial diagnosis of both patients was mycetoma caused by M. mycetomatis, which was based on the hairy aspect of the colonies isolated from the grains. Microscopically dark hyphae with chlamydospores and absence of conidia were noted. For verification, the isolates were tested using currently applied M. mycetomatis specific PCRs. 14 With primer pair 26. 1b and 28. 3b, a 370 bp amplicon was obtained for both Mexican isolates as well as for the two M. mycetomatis control isolates (Fig. 2a ). When primer pair 26. 1a and 28. 3a was used, a 640 bp amplicon was obtained, which was 150 bp larger than the expected 490 bp amplicon obtained with the two M. mycetomatis control isolates (Fig. 2b , Lanes 1-2). The 640 bp amplicon (GenBank: MN384980) had no homology to any known sequence. Partial ITS, BT and RBP2 genes were sequenced for identification.
All rights reserved. No reuse allowed without permission. The copyright holder for this preprint this version posted May 10, 2020. ; https://doi. org/10. 1101/2020. 05. 10. 087254 doi: bioRxiv preprint globin (Figure  3D ). While this downregulation of a-globin is likely to also arise indirectly due to the impaired differentiation, expression of a-globin was more affected than bglobin (where no binding of MAZ was observed in erythroid cells, see below), consistent with MAZ playing a direct regulatory role at the a-globin locus. Given these findings suggesting a previously unknown for MAZ during erythroid differentiation, we further investigated whether human genetic variants in the MAZ gene are associated with clinically important erythroid traits. We analysed the GeneATLAS database that reports associations between 778 traits and millions of DNA variants  17.
No reuse allowed without permission. The copyright holder for this preprint this version posted May 10, 2020. ; https://doi. org/10. 1101/2020. 05. 10. 087254 doi: bioRxiv preprint 10 While the majority of MAZ binding sites (65%) were located at promoter regions (Figure  4B ), the average MAZ enrichment was comparable for peaks in the promoter regions, intergenic, and genic regions (Suppl. Figure  5D ). Overall, MAZ was present at least at one TSS of 28% (5466/19646) of protein-coding genes. Comparison with published ChIP-and ATAC-seq datasets from erythroid cells  8, [18] [19] [20]  (Suppl. Table  6 ) revealed that MAZ binding sites are located in regions of high chromatin accessibility (as detected by ATAC-seq) that are enriched for activating histone modifications (H3K4me3, H3K27ac) and Pol II but depleted of the repressive histone mark H3K27me3 (Figure  4C ).
Taken together, these results indicate that MAZ is enriched around TSS of a large proportion of transcriptionally active genes in erythroid cells. In order to identify motifs contributing directly to MAZ binding, we used the MEME software suite  21  to discover de novo enriched sequence motifs among a training set consisting of the 500 highest ranked MAZ peaks  22. Overall, six enriched motifs were detected in the MAZ erythroblast training dataset (E-value <0. 01) (Figure  4D ). The most significant motif found, G3(C/A)G4, is contained within the 13/14 probe derived from the HBA promoter used to identify MAZ in the MS screen, and was similar to the published canonical MAZ motif G3AG3  23. This canonical motif was present in 92% of all MAZ peaks (see methods and Figure  4D ), and was the only enriched motif with a narrow unimodal central enrichment in the peaks and a large maximum site probability (Figure  4E ), suggesting that the vast majority of MAZ genomic binding in erythroblasts is due to direct DNA binding of MAZ to this canonical DNA sequence motif.
Consistent with this, Pearson correlation coefficients for these datasets indicated that MAZ exhibited globally distinct binding profiles in the different cell types (correlation coefficient < 0. 85 for all pairwise comparisons) (Figure  5B ). In particular, 18% of MAZ peaks observed in erythroid cells were not shared with other cell types (1780 peaks, termed "erythroid-specific peaks"). Comparison with gene expression profiles  20  revealed that MAZ binds 41% (218/528) (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint this version posted May 10, 2020. ; https://doi. org/10. 1101/2020. 05. 10. 087254 doi: bioRxiv preprint of promoters of genes with erythroid-specific expression. Gene ontology analysis revealed that genes with a TSS bound by MAZ in an erythroid-specific manner were significantly associated with erythroid differentiation and blood haemostasis functions (Figure  5C ) as well as phenotypes associated with haematological diseases (Figure  5D ).
Mass Spectrometry For proteomics analysis, the DNA baits corresponding to oligonucleotide 13/14 WT and 13/14 M3 with a TT/AA-overhang were annealed, phosphorylated, ligated and purified as previously described  12   The tryptic peptides were fractionated on an in-house packed 25 cm microcapillary column (Reprosil 3. 0 µm; Dr. Maisch GmbH) in a 125 minute gradient from 5 to 60 % acetonitrile. The MS measurement was performed on an LTQ Orbitrap XL (Thermo) with a top5 DDA method using CID fragmentation. The MS data was processed with.
All libraries received 12 cycles of PCR amplification in the final step before PCR clean-up using Ampure beads. Sequencing was carried out on the HiSeq 2500 using Illumina HiSeq Rapid Cluster Kit v2 -Paired-End for 100 cycles. RTA software version used was Illumina RTA 1. 17. 20 and the Pipeline software version was bcl2fastq-1. 8. 3.
21 The strength of enrichment in the IP was assessed plotting "fingerprints" using deeptools  48  and by calculating normalized strand cross-correlation coefficient (NSC) and relative strand cross-correlation coefficient (RSC) metrics using Phantompeakqualtools  49. Normalisation of the ChIP-Seq signal. Reads of the ChIP-Seq samples were first normalised to the input and then scaled to 1x sequencing depth using deepTools v. 3. 1. 3  50. Peak calling. Peak calling was performed using MACS2 2. 1. 1 with the minimum FDR (q-value) cutoff of 0. 01  51. The top 75% fold enriched peaks were selected for further analysis. For ENCODE datasets optimal IDR thresholded peaks provided by the ENCODE consortium have been used. Peak annotation was made with UCSC RefSeq gene annotation (GRCh38 genome version) using HOMER suite 4.
Correlation of the datasets. A clustered heatmap of correlation coefficients of bigwig signal was computed using the Pearson method; the bam signal combined from the replicates was plotted over 10 kb bins with DeepTools. Defining erythroid-specific MAZ signal. The peaks called on MAZ datasets were overlapped with the peaks from five MAZ ENCODE datasets with the minimum overlap (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprint this version posted May 10, 2020. ; https://doi. org/10. 1101/2020. 05. 10. 087254 doi: bioRxiv preprint 22 of 1 bp using BEDTools. The MAZ peaks without the overlap in any of the regions were assigned to "erythroid-specific peakset". Motif Analysis. To find the sequence motifs enriched in MAZ peaks, genomic sequences (from -50 bp to +50 bp around the centres of the top 500 MAZ peaks ranked on their q-values) were extracted (hg38) and used as input for MEME de novo motif discovery  54  with E-value cutoff 0.
01 and motif size defined as 6-30 bp. To calculate the presence of the motifs in a given peak, we used FIMO with the above defined motifs at a p-value threshold of 10 -4 55. Motif central enrichment analysis was performed using CentriMo  22  on regions from -250bp to +250 bp relative to the peak summits. Functional analysis of genes with erythroid-specific MAZ enrichment. g:Profiler 56 was employed to conduct Gene Ontology (GO) Biological Function and HP (Human Phenotype) gene annotations. Fisher's exact test was used to retrieve significantly enriched GO terms for genes marked with erythroid-specific MAZ signal. Functional categories are defined as those containing at least five genes and a minimum enrichment score of 1. 3 (p-value < 0. 05). GeneATLAS database  17  was used for mining MAZ variants associated with erythroid-specific traits (p-value < 10 -2 ).
NMR Analysis 1 H NMR spectra were achieved on a Bruker Fourier 300 (300 MHz) (Billerica, MA, USA) and calibrated with acetone-d 6 , with proton signals at δ 2. 05 ppm. Data are reported as follows: chemical shift (δ ppm), integration, multiplicity (s = singlet, d = doublet, dd = doublet of doublets), coupling constant (Hz), and assignment. 13 C NMR spectra were recorded on a Bruker Fourier 300 (75 MHz) (Billerica, MA, USA) and were calibrated with Acetone-d 6 , signals at δ = 206. 26 and 29. 84 ppm. Data are reported as follows: chemical shift (δ ppm) and attribution. NMR spectra assignments were achieved using COSY, HMBC, and HSQC spectra.
Antiradical Activities The determination of the radical scavenging activity of the diacids was determined via 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay. These tests involved adding potential antiradical molecule solution in ethanol at different concentrations to homogeneous DPPH solution. The study was performed under stirring for 7 h 25 min on the following concentration scale: 400, 200, 100, 50, 25, and 12. 5 µM. Every 5 min, the absorbance was measured at 520 nm. At the end, the percentage curves of %DPPH (blue) and %reduced DPPH (green) were plotted in Regressi ® software using an average of the last six points. The amount needed to reduce the initial number of DPPH free radicals by half, i. e. , EC 50 , was provided by the crossing point of %DPPH (blue) and %reduced DPPH (green).
Amplicon-Based Sequencing We sequenced amplicons from 3 samples following the protocol described by Quick et al. (12). We prepared sequencing libraries using the NEBNext Ultra II DNA Library Prep Kit for Illumina and barcoded with NEBNext Multiplex Oligos for Illumina (Dual Index Primers Set 1) (New England Biolabs for both). We sequenced prepared libraries on an Illumina MiSeq using MiSeq Reagent Kit v3 (600 cycles) at the Biomics platform of Institut Pasteur (Paris, France). We used Trimmomatic (http://www. usadellab. org) to remove adaptor and primer sequences (first 24 nt from 5′ end of reads, which is the maximum length of primers used for multiplexed PCRs). Then, we aligned reads to the complete genome sequence of a 2016 ZIKV isolate from the Dominican Republic (GenBank accession no.
KU853012) using the CLC Genomics Suite (QIAGEN). We used SAMtools (http:// samtools. sourceforge. net) to sort the aligned bam files and generate alignment statistics. We visually inspected ZIKV-aligned reads using Geneious version 9. 1 (https://www. geneious. com) before generating consensus sequences and required a minimum of a 5× read-depth coverage to make a base call. We deposited all sequences we obtained in GenBank (accession nos. MK241415-7).
Sequence Dataset Compilation To determine the origin of ZIKV in Cape Verde, we created a comprehensive dataset of all publicly available ZIKV sequences from GenBank. We then removed from this dataset all laboratory, patented, African genotype, and pre-2000 Asian genotype isolates. We concatenated all genome fragments of the same isolate to retain 1 representative sequence per isolate. For sequences with incomplete information on sampling time and location in GenBank records, we attempted to retrieve this information from published studies and other online resources. For cases in which the origin of the imported case of ZIKV infection was known, we set the sampling location as the location of origin. Last, we removed sequences that were not linked to a publication or associated with a known sampling time or location.
The tree base was removed for ease of presentation. Tips of tree are colored according to their sampling location and branches according to their most probable geographic location. Note that sequences from the 2016 Angola outbreak  (23)  were published during the later stages of preparation of this manuscript and therefore were not included in this Bayesian analysis. Scale bar indicates years. See Appendix Figure  1  (https://wwwnc. cdc. gov/EID/article/26/6/19-0928-App1. pdf) for fully annotated tree. B) Expansion of tree containing Cape Verde ZIKV sequences (bold). Clade posterior probabilities are shown at wellsupported nodes (>0. 9). GenBank accession number, country of origin, and sampling date are provided for each ZIKV sequence. only the Asian lineage of ZIKV had been found to be associated with neurologic and congenital afflictions.
Acknowledgements We thank 2 anonymous reviewers whose suggestions helped to improve this manuscript. This work was supported by  Institut Pasteur de Dakar. P. L. received funding by the  European Research Council  under the European Union's  Horizon 2020 Research and Innovation Programme  (grant agreement no. 725422-ReservoirDOCS ) and by the  Wellcome Trust  through project  206298/ Z/17/Z. S. L. and B. V. are supported by the  Fonds Wetenschappelijk Onderzoek (Belgium). E. S. -L. received funding from the  INCEPTION program  ( Investissements d'Avenir grant   ANR-16-CONV-0005 ) and  Institut Pasteur. F. G. -R. is part of the  Pasteur-Paris University International doctoral program ,  BioSPC doctoral school. E. C. H. is funded by an  Australian Research Council Australian Laureate Fellowship  ( FL170100022 ).
2, 3, 5 Such monitoring is necessary, both for assessing eligibility of patients for TKI discontinuation to enter treatment-free remission, and to ensure the early detection of subsequent disease recurrence. 3 MPLICITY (NCT01244750) is an ongoing observational study in seven countries (France, Germany, Italy, the Netherlands, Russia, Spain, and United States) of patients with CP-CML seen in routine clinical practice and receiving 1L TKI treatment (imatinib, dasatinib, or nilotinib). The primary objective of SIMPLICITY is to understand TKI use and management patterns in routine clinical practice and treatment-related outcomes. Previous analyses of SIMPLICITY have highlighted that National Comprehensive Cancer Network (NCCN)   and European LeukemiaNet (ELN) recommendations on response monitoring have not been consistently translated into routine clinical practice, and that intolerance is the most common reason for treatment interruptions, discontinuations, and switching.
Data were collected through completion of an electronic case report form. "Treatment interruption" was defined as a gap in treatment of >1 day before restarting the same TKI, from the day the TKI was temporarily discontinued and ending the day before restarting. "Treatment discontinuation" was defined as cessation of TKI treatment that did not qualify as a treatment interruption. "Treatment switch" was defined as discontinuation of index TKI, followed by the start of second-line (2L) TKI during the follow-up period; all patients who switched TKI were deemed to have discontinued treatment.
Introduction Key knowledge gaps remain to improve reproductive health outcomes for millions of women living with female genital mutilation (FGM). We aimed to update previous reviews and quantify more rigorously maternal and perinatal complications related to FGM across different settings. Methods In this systematic review and meta-analysis, we searched 15 electronic databases for studies published between 1 August 1995 and 15 March 2020, reporting on maternal and perinatal complications related to FGM. We included studies comparing women with and without FGM while accounting for confounders. Pooled relative risks (RR) were calculated, using fixed-effects and random-effects models, for a range of maternal and perinatal outcomes, adjusting for individual characteristics and according to delivery settings and study design.
Search strategy and selection criteria We searched 15 electronic databases (MEDLINE, POPLINE, Scopus, Cochrane Library, BMC, Web of Science, EBSCO Discovery Service, Science Direct, Global Index Medicus, Google Scholar, ScieLO, LILACS, LiSSA, Pascal Francis and RefDoc) for articles on maternal and perinatal consequences related to FGM. We searched for studies published in any language between 1 August 1995 and 5 July 2019. This search was updated on 15 March 2020. The research time span starting from 1995 was chosen as pertinent to the year WHO developed the first standardised classification of FGM,  1  which was used to define FGM in the current study (box 1). Search terms included "female genital mutilation", "female genital cutting", "female circumcision", "clitoridectomy", "infibulation", "sunna", "obstetric*", "gyn*", "reproductive health", "childbirth", "delivery", "neonatal" and "pregnancy", with no language restrictions.
BMJ Global Health We included studies providing primary quantitative data on any maternal and perinatal consequences of FGM, matching with the following criteria: (a) studies including women of reproductive age (between 15 and 49 years of age) with or without any type of FGM, (b) studies reporting estimates on complications of pregnancy, childbirth or the immediate postpartum period, including perinatal complications, (c) studies conducted in any country, (d) observational studies. In accordance with the aim of this study, we excluded studies with no comparison group (women without FGM). Furthermore, to minimise potential confounding bias, we excluded studies where comparison groups were not matched or for which analyses did not adjust for potential confounders. 8 ta extraction and quality assessment FS and AA extracted the following data from eligible studies: authors' names, date of publication, country where the study was conducted, study design, number of participants, mean age of participants, FGM type and method of assessment, outcome measures and method of assessment, matching criteria or list of confounders and level of specialisation of healthcare facilities where women delivered.
Characteristics of studies found in the literature We retrieved 300 articles in our initial search (figure  1 ). After removing duplicates (leaving 106 unique references) and excluding 34 articles based on titles and abstracts, we assessed the 72 full remaining texts. Sixty-one of these articles were excluded because they were descriptive (n=7), did not match nor adjust for    [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27]  Eight studies were conducted in Africa  19-21 23-27  and three in Europe. 17 18 22 Altogether, the studies included 111 558 participants, 61 218 of whom had undergone FGM. Across studies, sample sizes ranged from 232 to 103 095 women. Most studies were facilitybased,  17-19 21-26  one study was community-based  27  and one study consolidated data from 13 Demographic and Health Surveys.
Methods We conducted a prospective, observational, single-center study that compared 30 patients with septic shock to healthy volunteers included between June 2004 and April 2007. All individuals who performed the laboratory assays and the statistical analyses were blinded to the study group. The study was approved by the ethics committee of the Saint Germain-en-Laye Hospital and registered on ClinicalTrials. gov (NCT00684736). Written informed consent was obtained from the patients or relatives and from the healthy volunteers before study inclusion. The laboratory assays done to assess tryptophan pathways were the only procedures performed specifically for the study.
Statistical analyses The data were analyzed using SPSS 15. 0 (SPSS, Inc. , Chicago, IL). Data are presented as mean (standard deviation [SD]) for numeric variables and as frequencies and percentages for categorical variables. A Kolmogorov-Smirnov normality test was used to determine if variables were normally distributed. A chi-square (χ 2 ) test was used to compare categorical variables and frequencies. Continuous variables were expressed as mean (SD). Normally and abnormally distributed variables were analyzed. A Student's t-test and oneway analysis of variance with post hoc Duncan test was used to compare normally distributed variables between two and three groups, respectively. However, a Mann-Whitney U test or Kruskal-Wallis test was performed to analyze any abnormally distributed variables.
Acknowledgments. The authors thank  Sharon Grevet  for her English assistance, which was sponsored by research grants. Financial Support. This research was partially supported by grants  FIS PI14/02029  and  PI17/01433  (PI: P. A. S. ) from the  Instituto de Salud Carlos III ,  Spanish Ministry of Economy and Competitiveness , and  Fondos Europeos de Desarrollo Regional (FEDER) , by the  Government of the Principality of Asturias   PCTI-2018-2022 IDI/2018/235 , and by an  RYC fellowship  ( RYC-2013-12587 ) and an  I+D 2017 grant  ( SAF2017-85489-P ) to L. G. Finally, L. d. l. F. -T. and Á. V. received Severo Ochoa grants ( PA-17-PF-B16-179  and  PA-18-PF-BP17-177 , respectively) from the  Government of the Principality of Asturias. The funders played no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Flow Cytometry Analysis Flow cytometry staining was performed with panels of antibodies specific for activated/memory T cells (aCD3-Biotin, aCD4-FITC, aCD8-APCeF780, aCD62L-PeCy7, aCD44-APC; all from BioLegend) in PBS with 0. 5% FCS 2 mM EDTA for 15 min. For intracellular staining cells will be stimulated with a mix containing 10 µg/ml Brefeldin A (Sigma), 50 ng/ml PDBu (Sigma) and 500 ng/ml ionomycin (Sigma) in RPMI-1640 (PAN Biotech) plus 10% FCS (Biochrom) plus 1% penicillin/streptomycin (Lonza) plus 2 mM L-glutamine (Lonza) for 4 h. The cells were then formalin-fixed, permeabilized (0. 05% Triton X-100 in PBS) and stained for cytokines (aIL-2-PE, aIFNg-PeCy7), and transcription factors (aFOXP3-FITC) or perforin (aPerforin-APC) for 1 h. All antibodies were from Biolegend. Cells were analyzed with Gallios and Cytoflex S flow cytometers (Beckman Coulter) and FlowJo Software (Beckton Dickinson).
Statistics Statistical analysis was performed with GraphPad Prism 7 and R programming suite (version 3. 6. 3) with a tidyverse package bundle and ggplot2 graphics library. If not stated otherwise, data are plotted as mean with SEM presented as bars and whiskers and single animals/observations presented as points or symbols. Normality of variable distribution was assessed by Shapiro-Wilk test and visual inspection of the quantile-quantile plots. Statistical significance for two-group comparisons was determined by a two-tailed T-test for normally distributed variables and by the Mann-Whitney U test for non-normally distributed variables. Statistical significance for comparisons of more groups/factors was analyzed by one-or two-way ANOVA, as appropriate, with Tuckey post-hoc test. Differences in tumor growth rate (Figure  1 ) (1) between the untreated tumor bearers and treatment groups (iron alone, immunotherapy alone, and iron with immunotherapy) and (  2 ) between the immunotherapy-and immunotherapy/iron-treated animals were analyzed with separate mixed-effect multiple linear regression models (fixed effects: time point and therapy group: time point interaction, random effect: individual animal, R packages lme4 and lmer test).
After wine treatment for 24 hours at 30°C, the level of resveratrol had decreased by almost 50%, while the amount of δ-viniferin had increased by 5-fold bringing it from 20 to 100 μg/L. In addition, the formation of oxistilbenin G was observed in red wine after the heat treatment. This compound was specifically formed after oxidative coupling of two resveratrol units in ethanol. The δ-viniferin was the main compound formed in red wine followed by oxistilbenin G, in agreement with the rate observed in the reaction between resveratrol and metals in ethanol (Table  1 ). All these data have confirmed that resveratrol could be transformed by oxidative coupling during wine aging providing oligomers. The difference between the total stilbene content before and after treatment (1. 50 and 0. 94 μM, respectively) seems to indicate that a part of the resveratrol reacted with other compounds.