dataesr/scientific-paragraphs-categorization huggingface dataset:
For remaining results, courses 1 and 4 data were collected at the end of UPA treatment; courses 2 and 3 data were collected after the first menstrual bleed after UPA treatment and subsequent NETA/placebo treatment. b The same three fibroids identified at screening were followed throughout the study. c Scores on VAS range from 0 to 100, with higher scores indicating more severe pain. d On the UFS-QoL questionnaire, scores for symptom severity range from 0 to 100, with higher scores indicating increased severity. Total scores for health-related QoL range from 0 to 100, with higher scores indicating a better QoL. e n ¼ 131. f n ¼ 108. g Scores on VAS range from 0 to 100, with higher scores indicating a better health state. Donnez. Long-term treatment of uterine fibroids. Fertil Steril 2014. discomfort or pain and/or anxiety and depression at baseline, but few women reported these conditions at the end of each UPA treatment course and at 3-month follow-up (Tables  1  and 2 ).
DISCUSSION In these sequential studies of women with fibroids and excessive menstrual bleeding, we administered intermittent courses of UPA. Women had the option of surgery after one course, but for many women the goal is to avoid surgery and most decided to enroll into the extension study where they could receive up to three additional courses even if surgery was planned at baseline. Intermittent UPA (administered over an 18-month period) induced high rates of amenorrhea (nearly 90% during repeat treatment courses), confirming its ability to control for the long term the most troublesome symptom FIGURE  1  (A) Time to no bleeding (persistent amenorrhea; PEARL III extension full analysis set). Time to amenorrhea was defined as the first day for which there was subsequently no bleeding for longer than 35 days to the end of UPA treatment within each treatment course, assessed using the patient diary data from the date of the first dose of UPA (day 0, which was to be within the first 4 days of the start of menstruation for treatment courses 1 and 2 and on the first day of menstruation for treatment courses 3 and 4).
One day of spotting in any 35-day interval was accepted. Circles denote censored observation (i. e. , a participant had a subsequent interval of 35 days or less up to the end of UPA treatment for which no more than 1 day of spotting was observed). (B) Percent change from baseline in total volume of the three largest fibroids (PEARL III extension full analysis set). N ¼ number of women with nonmissing observations. The same three fibroids identified at screening were followed throughout the study. Box extends to 25th and 75th percentiles (IQR) and shows median value. Mean values are also plotted. Whiskers extend to 10th and 90th percentiles. Courses 1 and 4 data were collected at the end of UPA treatment; courses 2 and 3 data were collected after the first menstrual bleed after UPA treatment and subsequent NETA/placebo treatment.
SUPPLEMENTAL FIGURE 5 Time to spotting/no bleeding (PEARL III extension full analysis set). Time to spotting/no bleeding was defined as the first day for which there was subsequently only spotting or no bleeding for longer than 35 days to the end of UPA treatment within each treatment course, assessed using the patient diary data from the date of the first dose of UPA (day 0, which was to be within the first 4 days of the start of menstruation for treatment courses 1 and 2 and on the first day of menstruation for treatment courses 3 and 4). Circles denote censored observation (i. e. , a woman had a subsequent interval of 35 days or less up to the end of UPA treatment for which only spotting or no bleeding was observed). b The same three fibroids identified at screening were followed throughout the study.
SUPPLEMENTAL TABLE 2 b Amenorrhea (and spotting or no bleeding) assessed while under UPA treatment. For remaining results, data were collected at the end of UPA treatment. c The same three fibroids identified at screening were followed throughout the study. d Scores on VAS range from 0 to 100, with higher scores indicating more severe pain. e On the UFS-QoL questionnaire, scores for symptom severity range from 0 to 100, with higher scores indicating increased severity. Total scores for health-related QoL range from 0 to 100, with higher scores indicating a better QoL. a All adverse events that occurred during UPA treatment in at least 3% of women overall and all SAEs are included. b One woman had two off-treatment SAEs. c A 46-year-old woman was diagnosed with a lobular breast cancer 2 months after the end of treatment (T1, grade II).
Acknowledgments: The authors thank  Paul Terrill  of  MDSL International  for statistical consultancy during the PEARL III and PEARL III extension studies and the preparation of tables and figures of this manuscript. The authors also thank  Oliver Pohl  (freelance medical writer, formerly PregLem S. A. ) for coordinating the manuscript writing and editorial assistance (funded by  PregLem S. A. )  with the support of  Sarah Brittain  of  MDSL International  and  Florence S. Jean  and  Annie Dacquin  of PregLem S. A.
Hyper-IgM (HIGM) syndrome is a heterogeneous group of disorders characterized by normal or elevated serum IgM levels associated with absent or decreased IgG, IgA and IgE. Here we summarize data from the HIGM syndrome Registry of the Latin American Society for Immunodeficiencies (LASID). Of the 58 patients from 51 families reported to the registry with the clinical phenotype of HIGM syndrome, molecular defects were identified in 37.
Patient Demographic and Baseline Characteristics The six participating countries reported a total of 58 patients from 51 families with clinical features of HIGM syndrome. The gender ratio was 48 male/10 female. The distribution of patients by countries is shown in Fig. 1. Of these 58 patients, genetic defects were identified in 37. The detailed clinical and laboratory data for these 37 patients were analyzed for this paper. In this group of molecularly-defined patients, 35 from 25 non-related families were CD40L-deficient and 2 unrelated (1 male and 1 female) patients were AID-deficient. Seventeen patients (all males with CD40L-deficiency) are from families with a positive history of infections affecting other male members. Patient P36, with AID deficiency is from a consanguineous family. The patients' baseline characteristics including the mean age at the first clinical manifestation, age at diagnosis, serum immunologlobulin levels, etc.
Acknowledgments The authors thank the patients and their families for their participation in this study,  Baxter Biosciences  for supporting the  Latin American Advisory Board  on Primary Immunodeficiencies initiative,  Fundação de Amparo a Pesquisa do Estado de São Paulo  ( FAPESP  grants:  2012/50515-4  to OCM, and  2006/57643-7 , and  2012/51745-3  to ACN) and the  Jeffrey Modell Foundation  for financial support. Furthermore, we acknowledge  Dr Eunice Duarte  from the  Lab Alfa LTDA  and  Lusinete Tavares  from the  Federal University of São Paulo  for blood sample collection of Brazilian patients;  Dr. Silvia Danielian  from  Garrahan Hospital  ( Buenos Aires, Argentina ) and laboratory members for molecular genetic analysis of Argentinean patients, and the mycologist  Andrés S. M. Burkett  from  Unidad de Micología, Hospital de niños   Ricardo Gutiérrez  ( Buenos Aires, Argentina ), for providing the pictures of Aspergillus niger cultures.
Chemical Library Selection and Preparation The compounds used in the experimental screening were selected from the Enamine HTS collection (September 2009) and processed with the program Pipeline Pilot™ version 7. 5 (Accelrys, San Diego, USA). The selection was based on a hierarchical procedure combining the compliance with physicochemical thresholds (molecular weight, logP, etc. ) and the absence of chemical moieties commonly associated with toxicity and an increase in false-positive rates. The physicochemical thresholds used for the compound selection were the following: number of hydrogen bond acceptors < 13; number of hydrogen bond donors < 8; 150 < molecular weight < 700; logP < 6; topological polar surface area (TPSA) < 160; and number of rotatable bonds < 13. Later in the process, a fingerprint-based criterion [using a similarity threshold of 0.
8 for the Tanimoto index (Tn) and a Ward classification] was applied to ensure the chemical diversity of the resulting collection, followed by a random selection, to end up with 25,000 compounds for purchasing. The chemical library was formatted in barcoded racks of 96 tubes and stored at room temperature or -20 °C for dried or 10 mM DMSO-dissolved copies, respectively. The workstation to dilute and aliquot the library was a CyBI-Well® (CyBio, Savigny Le Temple, France) liquid handler. The sample management system avoids repeated freeze-thaw cycles and ensures the longest possible lifetime for all of the samples. Structures, compound ID, and library manipulations were recorded in MDL ISIS and Microsoft Access databases.
Cell Death Assay Cells were treated with molecules for 24 h. Cell death was evaluated by propidium iodide and Annexin V double staining (BD Pharmingen, Le Pont de Claix, France), and analyzed by flow cytometry with FlowJo software (TreeStar, Ashland, OR, United States). Viable cells are gated as propidium iodide and Annexin V double-negative cells. Drug combination effects with ABT-737 were measured using the Chou-Talalay method. 20 The resulting combination index (CI) calculated with the CompuSyn software (Paramus, USA) indicates an additive effect (CI = 1), synergism (CI < 1), or antagonism (CI > 1). The 50% cytotoxic concentrations (CC 50 ) were determined from the dose-response curves (DRCs) and the tumor-specificity (TS) index calculated with eq 4: TS CC PBMC CC BP CC IM = ( )× ( )+ ( ) 50 50 50 2 3 9 (3) (4).
Docking Experiments The two enantioners of BDM_53787 were docked into the binding pocket of Bfl-1 using the programs MOE-DOCK 2012. 10 (Chemical Computing Group Inc. , Montreal, Canada) and Autodock 4. 2. 21 The structure of Bfl-1 (pdb code 2VM6) was prepared using MOE 2012. 12 and the structure preparation protocol with default settings. MGL-Tools 1. 5. 6 was also used to prepare the protein structure prior to its use with Autodock 4. 2. Figures were generated with MOE 2012. 10. The selected complex proposed by Autodock was also investigated within MOE 2012. 10, and a full minimization of the complex was carried out. Then, the molecular surface of the protein in the vicinity of the binding site and the electrostatic map were calculated to picture the pocket of Bfl-1 and the polarity of the favored interacting regions with BDM_53787.
15 These cell lines also express other anti-apoptotic Bcl-2 protein family members (Bcl-xL and Mcl-1 for BP3, and Bcl-2 and Bcl-xL for IM9). 15 As shown in Figure  1D , BDM_ 49234 and BDM_ 53787 (structures shown in Fig. 1E ) demonstrated strong activity against BP3 and IM9 cell lines because less than 30% of BP3 and 10% of IM9 cells were still viable following 24 h treatment with 12. 5 µM of the compounds. Screening to identify molecules targeting Bfl-1 and displaying cytotoxic properties. Twenty-five thousand compounds were screened at 30 µM to find inhibitors of Bfl-1 (30 nM) binding to Bim BH3 (15 nM). (A) Data plot of screening results. Negative and positive controls were prepared by incubating Bim BH3 with Bfl-1 or its vehicle, respectively. For each incubate, polarization data were expressed as fluorescence measured in the well.
Docking of BDM_53787 Compound into the Bfl-1 Binding Pocket For the docking procedure, we decided to only dock compound BDM_53787. The main reason is that because of its putative transient link to the Cys55 of Bfl-1, only the reaction product of BDM_49234 binds to Bfl-1, but not the parent compound. Although some docking programs, including Autodock 4. 2, now allow docking of covalently bound ligands, we cannot rule out that the reactivity of this compound might involve another residue than Cys55. As such, it would be very speculative to propose a binding mode for this molecule bound to Cys55. On the contrary, the two enantiomers of BDM_53787 were docked into the binding pocket of Bfl-1 using two different programs (MOE-DOCK and Autodock 4. 2). 21 In addition, to assist the selection of the binding pose of BDM_53787, the crystal structure of Bfl-1 in complex with the interacting α-helix Bim (pdb code 2VM6) was used to predict the hotspot residues of Bim interacting with the binding pocket of Bfl-1 using the virtual alanine scanning DrugscorePPI server.
Funding The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by institutional grants from  INSERM, University of Lyon  (to NB),  University Paris Diderot  (to BV), University of Lille 2 (to BD), and  Institut Pasteur de Lille  (to BD), and by a specific grant from the  Association pour la Recherche sur le Cancer (ARC)  (to NB, BV, and BD). The purchase of the 25,000-compound Enamine library was made possible thanks to funding from the  French National Research Agency (ANR) Piribio Program PPIFocusDb  ( ANR-09-PIRI-0017 )  Edition 2009 du Programme Physique et Chimie du Vivant.
Positive PCR products were purified using the Exonuclease I/Shrimp Alkaline Phosphatase (GE Healthcare) and sequenced using BigDye Terminator version 3. 1 kits and an ABI PRISM 3130 DNA automated sequencer (Applied Biosystems, Foster City, CA, USA). Nucleotide sequences were analyzed using SeqScape®v2. 5 software (Applied Biosystems, Foster City, CA, USA). Using a Chi-square test, Departures from Hardy-Weinberg equilibrium were determined in all groups for each SNP genotype distribution. Mann-Whitney test was conducted to compare medians. The significance of associations between genotype/alleles variants and susceptibility to HCC were assessed using Chi-square and Fisher's tests with an estimation of the risk by computing ORs and their 95% CIs. A p-value <0. 05 was considered statistically significant.
discussion We report here the first prospective hospital-based series of HF patients in Uganda and show that RHD, a preventable disease, remains the major cause of HF in a young population. However, CHD was the leading cause among children, especially those under 10 years. Other causes were also identified as hypertensive cardiomyopathy, endomyocardial fibrosis and presumed ischaemic heart disease. A small fraction of young surgical candidates had access to treatment through the efforts of NGOs. We believe our study will add to the knowledge of cardiovascular   disease in sub-Saharan Africa, as robust echo-based data are limited, 5,15-17 and surgical outcomes seldom depicted. Regarding the aetiology of HF, our findings are consistent with those of other sub-Saharan countries, as illustrated in Table  3.
Introduction Current knowledge on microbiology is evolving rapidly as metagenomics, single-cell genomics, and culturomics advance  (Edwards and Rohwer 2005; Lagier et al. 2012; Rinke et al. 2013). Nonetheless, these technologies leave unclassified a dark matter that comprises as much as 70% of sequences obtained by metagenomics and at least 16% of microbes observed by electron microscopy in the gut  (Edwards and Rohwer 2005; Suttle 2005; Lagier et al. 2012; Hugon et al. 2013). Culture and single-genome sequencing allow for the recovery of the genomes of unidentified microbes, then reannotating metagenomic databases  (Lagier et al. 2012; Rinke et al. 2013). However, in most metagenomic studies, identifications of microbes have been based on 16S ribosomal DNA (rDNA) similarity  (Eckburg et al.
RNAP2 phylogeny reconstructions clearly delineated four branches (fig. 1  and supplementary fig. S1 , Supplementary Material online). Interestingly, we detected that a sequence recovered from the draft genome of Hydra magnipapillata, a multicellular freshwater predatory cnidarian, was clustered with RNAP2 from amoeba-associated mimiviruses. The H. magnipapillata draft genome (&1. 0 gigabase pair large) had been obtained by a whole-genome shotgun procedure then 454 sequencing from laboratory strain 105 that was recloned from a single polyp and was described in 2010 in Nature  (Chapman et al. 2010). Further analyses of the scaffold harboring the RNAP2encoding sequence (scaffold 39305 [GenBank accession no. GL020074. 1]) found that 21 of the 186 predicted genes had a mimivirus gene as best match, including one encoding a major capsid protein (fig.
2a ; supplementary fig. S2  and table  S1 , Supplementary Material online), suggesting that a hidden Mimivirus relative was sequenced concurrently with the Hydra genome and unrecognized. This serendipitous finding indicated that RNAP2 is a promising tool to detect hidden giant viruses and prompted us to search for other similar misidentifications in the National Center for Biotechnology Information (NCBI) GenBank protein sequence database. BLASTp analysis using RNAP2 from Megavirales allowed us to recover two additional RNAP2 that were clustered with giant viruses despite being not annotated as viral. The first sequence was from a marine group II Euryarcheota (strain SCGC AB-629-J06; accession no. NZ_AQVM00000000) and was among whole-genome shotgun sequences obtained from Lake Washington (WA, unpublished).
The Euryarcheota is a phylum of mainly marine archaea, which are among the most abundant archaea in the oceans  (Massana et al. 2000). BLASTp analysis for the 368 predicted proteins available in GenBank for this organism identified 92 genes having as best hit a mimivirus, mostly members of a distant group within the family Mimiviridae that encompasses Phaeocystis globosa virus and organic lake phycodnaviruses  (Yutin et al. 2013 ) (fig. 2b ; supplementary fig. S3  and table  S2 , Supplementary Material online). In contrast, no 16S rDNA sequence (nor capsid-encoding sequence) was found. The second sequence was from an eukaryotic plant pathogen, Phytophthora parasitica. Further analyses showed that a contig (accession no. KI669605; unpublished) from Phy. parasitica strain INRA-310 harbored both genes encoding RNAP subunits 1 and 2, and that 17 of its 120 predicted genes matched with a Megavirales member, as best match in 12 cases (fig.
2c  and supplementary table  S3 , Supplementary Material online). Seven sequences were most related to African swine fever virus, including one homologous to its capsid gene. In the RNAP2 phylogenetic reconstruction, the marine group II euryarchaeote was clustered with P. globosa virus, whereas Phy. parasitica was clustered with African swine fever virus as a new distant member of the family Asfarviridae. Overall, the detection of these three overlooked giant viruses is a proof of concept that we can detect unknown viruses through comparative analyses of RNAP2 including in the genome of eukaryotes where they were not previously identified. Following our hypothesis of a fourth domain of life  (Boyer et al. 2010) ,  Wu et al. (2011)  used RNAP sequences to "fish" into environmental sequence databases, mostly that from the Sorcerer II Global Ocean Sampling expedition, aiming to recover unknown organisms and identify new clades.
These authors identified environmental sequences that were among the deepest branches within a domain of life or even between the branches encompassing Bacteria, Archaea, and Eukarya members and large viruses (only poxviruses being analyzed), and they assumed that these sequences could come from unknown viruses. We speculated here that obtaining reconstructed putative ancestral sequences of RNAP2 will increase the sensitivity to detect similarities to distant and unknown viruses. Thus, the distance may be theoretically greater between two distant members from a single phylum than between these sequences and the ancestor of this phylum. Therefore, we used MEGA5 software  (Tamura et al. 2011)  to construct the putative ancestral sequences (we named "mamas") of the RNAP2 from all members of the  Megavirales, Archaea, Bacteria, and Eukarya, and then LUCAR2, the putative ancestral sequence of these four reconstructed sequences.
S5 , Supplementary Material online). Therefore, using RNAP2 mamas allows us to decrease the distance to the bottom level from each branch. Our next step was to use LUCAR2 as fishhook to recover distant homologs in the NCBI environmental database (env_nr) through BLASTp searches. This approach was fruitful for finding metagenome sequences composing new clades in the viral branch (fig. 4 ). Most of these metagenomic sequences were clustered within the Mimiviridae in the RNAP2 tree. Nodes within phylogeny were well supported with high confidence values. The novelty of these sequences was confirmed by phylogenetic analyses with other eukaryotic RNAP2 sequences and the best 100 BLAST hits, in addition to the same data sets. Indeed, these analyses showed that these metagenomic sequences were still clustered with viruses (supplementary fig.
Materials and Methods Collection of RNAP2 Homologous Sequences from the Three Cellular Branches of Life and from Members of the Proposed Order Megavirales BLASTp searches for DNA-dependent RNAP2 homologous sequences from cellular organisms were performed using Acanthamoeba polyphaga mimivirus RNAP2 (gi: 311977620) as query sequence against the NCBI GenBank nonredundant protein sequence database (nr) with a number of target sequences limited to 20,000. Orthologous gene sequences to RNAP2 were obtained by Orthomcl  (Li FIG. 4. -Phylogeny reconstruction using the maximum likelihood method for DNA-dependent RNAP2 from members of the Megavirales and metagenomic sequences fished by the reconstructed putative ancestral RNAP2 sequence. Members of Megavirales are indicated in red, whereas metagenomic sequences are indicated in pink and sequences related to giant viruses and previously misclassified are indicated in black.
Scale bar represents the number of estimated changes per position. et al. 2003) using complete protein sets from the seven families of the proposed order Megavirales (Asfarviridae, Ascoviridae, Iridoviridae, Phycodnaviridae, Poxviridae, Marseilleviridae, and Mimiviridae) directly downloaded from the NCBI website (ftp://ftp. ncbi. nih. gov/genomes/Viruses/); RNAP2 from pandoraviruses, P. globosa viruses, and organic lake phycodnaviruses were collected from the NCBI GenBank nonredundant protein sequence database using BLASTp searches. Criteria for Selection of Sequences of RNAP 2 from Cellular Organisms RNAP2 is highly conserved and may possess bulk of homologs in protein sequence databases. We aimed at obtaining an informative tree based on RNAP2 sequences from megaviruses and a comprehensive, representative, and unbiased set of species from Bacteria, Archaea, and Eukarya.
Therefore, we selected RNAP2 sequences from members of Bacteria, Archaea, and Eukarya by using TimeTree, which is a professional resource where divergence time between species is reported on the molecular clocks based on studies published in peer-reviewed journals  (Hedges et al. 2006). Precisely, species that were selected for this study were those that diverged around 500 Ma, a time point that allowed obtaining a reasonably comprehensive and representative set of members from Bacteria, Archaea, and Eukarya. The genomes of the majority of the organisms considered here are available and have been annotated. Taxon filter is a Java-based program that we used to filter out taxons and gi identifications from the BLAST results in XML format. Then, protein sequences from the selected species were downloaded directly from the NCBI GenBank nr database using the gi identifications.