dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgements We thank  Stephan Handschuh  and  Brian Metscher  for performing the μ CT-scans. Research was funded by a grant from the  University of Antwerp  ( BOF/KP 24346 ) and the  Agence National de la Recherche  ( ANR-16-ACHN-0006-01 ) to S. V. W. , and by a grant from the  Austrian Science Fund  ( FWF J3186-B17 ) to E. H.
Statistical Analysis Statistical analysis was performed using SPSS version 19. 0. Continuous data were compared using the t-test and presented as mean and standard deviation. Categorical data were analyzed using the chi square or the Fischer exact test. Results were considered statistically significant for a p value less than 0. 05. We also used repeated measure analysis with binary outcome to test the effect of average PI on bleeding events adjusting for months since implant, age and gender. Using a binary outcome analysis, we model the odds of a "success" (bleeding event), p(x)/(1-p(x)). The slope=b means that the odds increase multiplicatively by exp(b) for every one-unit increase in the predictor, PI.
We examined the association of bleeding with PI. It has been hypothesized that decreased PI may lead to arteriovenous malformations and thus an increased risk of bleeding through a similar mechanism to the Heyde syndrome in aortic stenosis. 27 Wever-Pinzon et al  37  reported low PI to be associated with increased risk of non-surgical bleeding during the first 3 months after implantation of HMII. We, however, did not find any association between bleeding events and PI. Recent data suggests that the bleeding risk of continuous flow MCS support may be offset by minimizing the use of anti-coagulation. 38 However, pump thrombus and embolic cerebrovascular accidents remain a concern. In our study, the level of INR was not statistically different in patients with and without thromboembolic events.
The IRC cDNA, after dilution by a factor of 20, underwent the same quantitative RT-PCR protocol as the unknown samples. PCR efficiency for each quantified target and reference was calculated with known serial dilutions of each specific cDNA. LIGHT-CYCLER â 480 Software release 1. 5. 0 was used to analyze data, and each specific target transcription level was normalized to the geometric mean of the transcription level of the reference gene, with the MatriceLab Innove (MLI) designed the study, performed the endometrial immune profile (with its molecular analyses and CD56 + cell count), suggested personalized care, and remained in contact with physicians to follow-up each IVF/ICSI attempt. Physicians recruited patients, performed the endometrial biopsies, and provided the personalized care before and after performing the IVF/ICSI.
Statistical Analysis Statistical analyses were performed with MEDCALC Statistical Software version 12. 7. 2 (MedCalc Software, Ostend, Belgium; http://www. medcalc. org; 2013). Comparisons between groups (the control group and the different subgroups of women with RIF) used the ANOVA test. The effect of treatment on immune biomarkers was analyzed with the nonparametric paired Wilcoxon test. A P-value <0. 05 was considered statistically significant.
Acknowledgments We first thank the patients who agreed to the retrospective collection of their pregnancy outcomes. We also want to thank the physicians who agreed to participate in this procedure: Alexandre F,  Alvarez S ,  Aubriot FX ,  Ayel JP ,  Bailly M, Benifla JL ,  Bidet M, Bstandig B, Bouret D, Bulwa S, Cedrin I, Cornelie C, Chelly C, Chevalier N, Cornet D, Creux H, Delvigne A, Delaroche L, Descat E, Douard S, Elbaze R, Farges F, Fari M, Godefroy A, Grossetti A, Gout C, Frydman R, Herve F, Jacquesson L, Kerbrat G, Larue L, Lechat X, Lenoble C, Levy G, Massari A,Mathieu-D'Argent E, Nathan C, Neuraz A, Oger P, Olivennes F, Parneix I, Patillot A, Schumacker A, Roubach AC, Rodrigue M, Teboul J, Divry V, Zitoun P. We particularly thank physicians of the reproductive unit of the hospital  Les Bluets (Paris)  for their enthusiasm and support.
Mfd promotes bacterial survival in vivo in the context of NO stress Wild type and iNOS-KO mice were inoculated intranasally with wild type and Δmfd mutant bacteria. After 3 days post infection, the mortality of wild type mice infected with Bc 407 reached 70% (7/10). By contrast, mortality of wild type mice infected with the Δmfd mutant only reached 44% (4/9). In iNOS-KO mice, mortality was of 71% (5/7) for mice infected with Bc 407 and 75% (6/8) for iNOS-KO mice infected with the Δmfd strain. No additional death occurred after 3 days post infection. These data demonstrate the strong implication of Mfd in the resistance to the host NO response in vivo. To complete these data, wild type and Δmfd mutant strains were recovered from various organs following infection. The lungs and brain of the mice were collected and crushed after animal death or at day 7 were the surviving mice were euthanized.
NO inducer in vitro Bacteria were exposed directly to chemically generated NO+ in a cell-free system as described by Miyagi et al. [58]  with modifications. Briefly, bacteria were grown in LB medium until mid exponential growth phase at 37°C with shaking. Cultures were then diluted to 10 4 cfu/ml in RPMI-1640 medium (Invitrogen) in the presence of 0 to 10 mM sodium nitrite (Walco Pure Chemical Industries Ltd); NO+ is generated from the sodium nitrite by a chemical reaction  [58]. The bacteria were then cultured at 37°C for 0 to 4 h, harvested and plated on agar plates to evaluate bacterial survival. Using this cell free assay, the NO concentration required to decrease by 50% the survival rate of each strain (IC 50 ) was calculated using the GraphPad PRISM software (version 6. 0, GraphPad Software, San Diego, CA) with non-linear regression.
Acknowledgments We are indebted to the  Unité d'Infectiologie Experimentale des Rongeurs et Poissons (IERP) ,  INRA ,  Jouy en Josas, France , for performing the experiments mice and to  J. C. Jeanny Institut des Cordeliers, Paris  for generously providing the iNOS-KO mice. We warmly thank  Kahina and Jean Claude Diné  for their help to isolate bone marrow macrophages from mice. We thank  B. Michel  for very helpful discussions. We thank  Oriana Rossi  for her help in the design of the model figure. We thank  Mylene Sperry  for excellent technical assistance.
ads. uga. edu/wiki/doku. php?id = application_programs), which solves mixed model equations using the PCG algorithm  (Tsuruta et al. , 2001). The program stopped when the convergence criterion (the squared ratio of the norm of residual and right-hand-side vectors;  Tsuruta et al. , 2001)  was less than 10 -15. The program was compiled with the Intel Fortran Compiler 14. 0 (Intel Corporation, Santa Clara, CA). We used multi-threaded version of BLAS and LAPACK in the Intel Math Kernel Library 11. 0 (Intel Corporation). All the analyses were performed on a computer running Linux (x86_64) with Intel Xeon E7-8857 CPU (3. 0 GHz) processors with 24 computing cores.
Data Phenotypic data for final score and pedigree information were provided by Holstein Association USA Inc. (Brattleboro, VT). The phenotypic data included 11,626,576 records from 7,093,380 cows classified up to March 2014, and pedigree data included 10,710,380 animals. Genotypes for 60,671 SNP markers were available for 569,404 animals. We will refer to these data as the full data set. A truncated data set used for validation contained only 10,671,898 phenotypes from cows classified in 2009 or earlier.
Validation We defined the predicted bulls as young genotyped bulls that had no daughters classified in the truncated data (i. e. , by the end of 2009) but had at least 30 daughters classified by March 2014 (n = 2,948). Daughter deviations  (VanRaden and Wiggans, 1991)  for the predicted bulls (DD2014) were calculated from the full data set without genomic information. Genomic predictions for the predicted bulls (GEBV2009) were calculated using the truncated data set with different definitions of the core animals for G APY -1. The following definitions were considered: genotyped bulls with at least 1 classified daughter up to 2009 (Core09K; n = 9,406), the bulls included in Core09K and their dams genotyped and classified up to 1971 2009 (Core10K; n = 10,458), the animals included in Core10K and genotyped and classified cows born up to 2009 (Core17K; n = 16,828), and randomly sampled 5,000 (Rand05K), 10,000 (Rand10K), 15,000 (Rand15K), 20,000 (Rand20K), and 30,000 (Rand30K) animals from the 77,066 genotyped animals born in 2009 or earlier.
The random sampling was replicated 3 times. Parent averages (PA2009) for the predicted bulls were also calculated with the truncated data set using a traditional animal model. A linear regression analysis was conducted for each combination of DD2014 with genomic predictions (or parent averages) for predicted bulls. The coefficient of determination (R 2 ) and regression coefficient (b 1 ) of DD2014 on GEBV2009 (or PA2009) were calculated as a validation reliability and a bias indicator, respectively.
, 2014). When the full data were used, we needed fewer rounds to reach the same convergence criterion (Table  2 ). Table  3  shows R 2 and b 1 (squared accuracy and bias) of DD2014 on PA2009 and GEBV2009 from various G APY -1. Genomic predictions always had greater accuracy and less bias than PA2009. The R 2 and b 1 were very similar across different sets of core animals. For ran- domly sampled core animals, R 2 and b 1 were almost consistent over replicates. The greatest R 2 was achieved with 10,000 or more core animals. Lourenco et al. (2015)  reported that GEBV from G APY -1 with 8,000 core animals accounted for 97% of prediction accuracy from GEBV with G -1 for birth weight in the US Angus population. Figure  1  shows the correlations of GEBV2009 from Rand30K with GEBV from the other definitions of core animals.
couchianus annotated transcripts with an N50 of 3,609 bp, an average length of 2,575 bp, and a total size of 51 Mb (Table  2 ). The resulting inferred transcriptome of X. couchianus covers 99 % of the gene number and 97 % of the nucleotides of the X. maculatus transcriptome. Using the same method we produced 20,325 X. hellerii transcripts with a final N50 of 3,635 bp, average length of 2,581 bp, and a total size of 52 Mb (Table  2 ). The inferred X. hellerii transcriptome also covers 99 % of gene number and 99 % of nucleotides of the reference X. maculatus transcriptome. There are several reasons why the RATT tool fails to transfer some gene models to new genomes. For example, there are 174 genes annotated in the X. maculatus genome that were not transferred to X. hellerii. Attempts to manually align these gene models failed for 15 of them, three of these gene models are located in contig breakpoints, 13 of them mapped to multiple locations and the remainder can be aligned but failed one of the quality control steps during RATT transfer.
0  [24] , with the parameters of minimum cluster match length of 400 bp and max gap size of 500 bp. After Nucmer alignment, de novo assembled scaffolds of X. couchianus and X. hellerii were placed using a custom Perl script based on nucleotide alignment position of X. couchianus and X. hellerii scaffolds relative to the X. maculatus chromosomes. Scaffolds or contigs that could not be placed onto chromosomes were collected into a file called "unplaced".
Genome annotation Using RATT  [14]  synteny between the reference and the query, InDels were established and identified between species to avoid frame shifts between two species. Gene models from X. maculatus were then transferred and corrected onto X. couchianus and X. hellerii genomes by RATT. The total of 20,482 gene models annotated in X. maculatus, resulted in transfer of 20,300 and 20,325 gene models over to X. couchianus and X. hellerii, respectively. Custom Perl scripts were used to make RATT executable on multiple threads and convert the RATT output to the latest EMBL format implementation.
Pathway enrichment analyses Genes with high impact variants identified among three Xiphophorus species were further tested for significant association with known canonical pathways. We define variants that change coding sequences among species as critical variants. HGNC gene symbols annotated from Ensembl or top BLAST hit (NBCI non-redundant protein database, e-value cutoff E-10) for genes that were not annotated in Ensembl were used for functional analyses. The WEB-based GEne SeT AnaLysis Toolkit (WebGestalt) database was used for functional characterization and classification of gene symbols harboring high impact variants  [29]. Enriched functional groups and pathways were identified by the Benjamini & Hochberg method for Multiple Test Adjustment  [30].
Acknowledgements We thank the  Xiphophorus Genetic Stock Center ,  Texas State University , for maintaining the pedigreed fish lines, helping with dissections, and caring for the animals used in this study. This work was supported by the  National Institutes of Health, Division of Comparative Medicine ,  R24 OD-011120  and  R24 OD-011198 ,  R24 OD-011199 ,  R24 OD-018555  and  Natural Science Foundation of Fujian Province of China  (No. 2015J05074 ).
2012). A related effect, that can influence the results, is mixing. As the mixing is likely macroscopic, and not microscopic  (Fryxell et al. 1991a ), it cannot be easily treated in 1-D calculations. Given the huge computational costs associated with full 3-D non-LTE time-dependent calculations, and our still limited understanding of SN ejecta, 1-D calculations are an essential analysis tool. We compute the observer's spectrum in two ways. First, we compute the spectrum with the CMFGEN calculation. To do this we perform a Lorentz transformation of the outer boundary comovingframe intensities, and then integrate them in the usual way to obtain the observed flux. In the second method we use a separate code, CMF FLUX  (Busche & Hillier 2005). In this code we first solve for the radiation field, similar to the CMFGEN calculation.
ACKNOWLEDGMENTS LD acknowledges financial support from the  European Community  through an  International Re-integration Grant , under grant number  PIRG04-GA-2008-239184 , and from  "Agence Nationale de la Recherche " grant  ANR-2011-Blanc-SIMI-5-6-007-01. DJH acknowledges support from  STScI  theory grant  HST-AR-12640. 01 ,and  NASA  theory grant  NNX14AB41G. SW was supported by  NASA  ( NNX14AH34G ) and the  DOE High Energy Physics Program  ( DE-SC-00010676 ). SCY was supported by the  Basic Science Research  ( 2013R1A1A2061842 ) program through the  National Research Foundation of Korea (NRF). This work was granted access to the HPC resources of CINES under the allocations c2013046608 and c2014046608 made by  GENCI  ( Grand Equipement National de Calcul Intensif ). This work also utilised computing resources of the Mésocentre SIGAMM, hosted by the  Observatoire de la Côte d'Azur, Nice, France.
Various small mammal surveys performed through 1983-2009 show that coastal Guinea is outside the geographic range of M. natalensis  23, 24. The human and murine data have been compiled and mapped in Supplementary Figure  3. This discrepancy between high human seroprevalence and the possible absence of the reservoir invited us to verify on the field this unusual epidemiological scenario. In May 2014 we captured sixteen M. erythroleucus in Madina Oula, while not a single M. natalensis was caught. Six animals were LASV PCR-positive (prevalence 37. 5%), and phylogenetic analysis of the nucleotide sequences from complete GP, NP, polymerase and Z segments of these BSL-4-isolated strains show that they belong to lineage IV (Fig. 1 ). In all trees, the Madina Oula sequences clustered to those from Sierra Leone (Josiah, NL and LM395) and forest Guinea (Z148 and Z158) rather than to those from Upper Guinea (Bantou).
Acknowledgements This research was funded in Nigeria by the  European Foundation Initiative for African Research into Neglected Tropical Diseases (EFINTD)  via a  postdoctoral fellowship grant  to  A. Olayemi  under the project ' Ecology of transmission of the deadly Lassa virus from rodents to humans across various flashpoints within Nigeria ' (Grant No. 1/85/022 ). The  German Research Foundation  also supported our work by grants awarded in Nigeria and  Guinea (DFG ,  FI 1781/1-1  and  GU 883/3-1 ). We would like to thank  Akinola Awoyelu in Kako  and  Gideon Igbana in Onmba Abena  for their immense help during the fieldwork in Nigeria. Our gratitude also goes to  Moussa Fofana , our driver in Guinea.
Ultrawide band detection is required to resolve the slow varying and fast varying spatial contributions, resulting in a resolution and overall image quality that is not possible using narrower bands. Combined with a complete 360°angular coverage, MORSOM yielded highfidelity images of opaque biological tissues that were not accessible by optical and optoacoustic microscopy methods. We chose single-element detectors because detector arrays might only achieve up to 35-MHz bandwidths and have less preferential focusing characteristics. Therefore, MORSOM capitalizes on the collection of a uniquely rich and spatially precise data set, which we combined with a novel image reconstruction implementation to produce a higher SNR and higher and more isotropic in-plane resolution compared with RSOM. The MORSOM-50 Zebrafish images exhibited higher contrast, richer anatomical detail and an improved SNR of ~15 dB over RSOM, as shown in Figure  3e  and 3f,.
5j ), as well as in the aforementioned Marseille data set (Fig. 5k ). We next ascertained the molecular cues regulating SOX9 expression downstream PML. Since the regulation was observed at the mRNA level, we interrogated SOX9 promoter in silico and in public datasets. The ENCODE project has provided a vast amount of information about regulators and binding sites  43. SOX9 promoter exhibited a 2 kb region of acetylated H3K27 (H3K27Ac), which would indicate the proximal regulatory region. To our surprise, we found PML among the 10 proteins with highest confidence DNA-binding score in SOX9 promoter region (Fig. 5l ; cluster score ¼ 527 (refs 44-46)). There is limited evidence of the capacity of PML to regulate gene expression in concordance with transcription factors through association with DNA  [47] [48] [49].
Methods Cell culture. MDA-MB-231, BT594, HBL100, MCF7 and T47D cell lines were obtained from the American Type Culture Collection (Manassas, VA, USA) or from Leibniz-Institut-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH (DMSZ, Germany), who provided an authentication certificate. None of the cell lines used in this study was found in the database of commonly misidentified cell lines maintained by ICLAC and NCBI biosample. PDX44-derived cell line was generated by Dr Ibrahim and Dr Serra starting from xenograft tumours. Cell lines were routinely monitored for mycoplasma contamination and quarantined, while treated if positive. All cell lines were maintained in DMEM media supplemented with 10% (v/v) foetal bovine serum and 1% (v/v) penicillin-streptomycin. OS formation assays were carried out as previously described  64.
sh41STAT3 (TRCN0000020841): CCGGGCTGAAATCATCATGGGCTATCTCGAGATAGC CCATGATGATTTCAGCTTTTT; sh43STAT3 (TRCN0000020843): CCGGGCAA AGAATCACATGCCACTTCTCGAGAAGTGGCATGTGATTCTTTGCTTTTT. sh1SOX9 (Addgene, GenBank ID: RHS3979-9587792; GCATCCTTCAATTTCTG TATA); sh2SOX9 (TRCN0000342824): CCGGCTCCACCTTCACCTACATGAAC TCGAGTTCATGTAGGTGAAGGTGGAGTTTTTG. Sub-cloning of shC and sh4PML into pLKO-Tet-On vector was done introducing AgeI and EcoRI in the 5 0 -end of top and bottom shRNA oligos, respectively (following the strategy provided by Dr Dmitri Wiederschain  65  , Addgene plasmid: 21915). HA-PMLIV was sub-cloned into a TRIPZ vector using Age1-Mlu1 sites. Immunoassays. Western blot analysis was carried out as previously described  20. Uncropped scans are provided as part of the Supplementary Information (Supplementary Fig.
Immunofluorescence images were obtained with an AxioImager D1 microscope. For immunohistochemistry, tissues were fixed in 10% neutral-buffered formalin and embedded in paraffin according to standard procedures. Three to four mm-thick sections were stained for PML (clone PG-M3 Santa Cruz Biotechnology Inc, sc-966, 1:200 dilution), and vimentin (1:1,000, NCL-L-VIM-V9, Novocastra). Antigen retrieval was performed with citrate buffer (pH 6). Detection was performed with the ABC Kit from Vector Laboratories and 3,3 0 -diaminobenzidine (DAB)-based development. Sections were counterstained with haematoxylin. The PML general immunoreactivity scoring system (used in Fig. 1h ) is described in ref. 20. For the Marseille data set, PML (1:200), SOX9 (1:400, Millipore) and phospho-STAT3 (Tyr705) (1:100, Cell Signalling: M9C6) immunostaining was performed as reported  11, 20.
The percentage of PML-high (Ph) and -low (Pl) immunoreactive tumour cells in the Marseille data set was quantified separately and the h-score was calculated, attributing a relative value of 1 Â to Pl and 2 Â to Ph intensity nuclear signal (h ¼ (1 Â Pl) þ (2 Â Ph)). For SOX9 automated quantification and construction of tissue microarrays (TMAs) in the Marseille data set was carried out as reported  23. In brief, cores were punched from the selected paraffin blocks, and distributed in new blocks including two cores of 0. 6 mm diameter for each tumour. All the TMA blocks were stored at 4 °C. TMA serial tissue sections were prepared 24 h before immunohistochemistry processing and stored at 4 °C. The immunoperoxidase procedures were performed using an automated Ventana Benchmark XT auto-stainer.
b-actin (Hs99999903_m1, cat: 4331182) and GAPDH (Hs02758991_g1, cat: 4331182) housekeeping assays from Applied Biosystems showed similar results (all quantitative PCR with reverse transcription data presented were normalized using GAPDH). ALDH1 activity by FACS. To measure the ALDH1 activity present in the cells, the ALDEFLUOR assay was carried out according to manufacturer's (Stemcell Technologies) guidelines. In brief, dissociated MDA-MB-231 cells were resuspended in ALDEFLUOR assay buffer at a final concentration of 1. 10 6 ml À 1. ALDH substrate, bodipyaminoacetaldehyde was added to the cells at a final concentration of 1. 5 mM. Immediately, half of the cells were transferred to an Eppendorf tube containing a two fold molar excess of the ALDH inhibitor, diethylaminobenzaldehyde. Both tubes were incubated for 45 min at 37 °C, and after this incubation cells were centrifuged at 250g for 5 min at 4 °C and resuspended in ice-cold ALDEFLUOR assay buffer.
Cells were analysed using a FACSAria1 (Becton Dickinson) flow cytometer. DRAQ7 (BiostatuS) was added prior analysis to each tube for dead cell exclusion. FACSAria1 was also used for sorting cells. Data were analysed using the FACSDiva software. Reagents. For in vitro experiments, SI3-201 (Sigma-Aldrich, SML0330) was prepared at 10 mg ml À 1 in dimethylsulfoxide and used at the indicated concentrations. TG101348 (Santa Cruz, sc-364740) was prepared 100 mg ml À 1 in dimethylsulfoxide and used at the indicated concentrations. ATO (Sigma-Aldrich) was prepared at a concentration of 100 mM in NaOH 1 N and subsequently diluted to 0. 1 mM in PBS for a 1,000 Â working solution. ATO was used at 150 nM either 3 or 6 days as indicated in figure legends. For in vivo experiments a dose of 5 mg kg À 1 per day was intraperitoneally administered.
Patient data sets, bioinformatics and statistical analysis. All studies involving human subjects were approved by the corresponding committees with informed consent as stated in the original publications  3, 23, 25. The use of MSK/EMC and Marseille cohorts were previously described  23, 25. For MSK/EMC, MFS curves were plotted using Kaplan-Meier estimates and compared using the Gehan-Breslow-Wilcoxon test. Two groups were compared using mean PML expression values as the cutoff between PML high and low. Kaplan-Meier survival and correlation analysis in patient samples: publicly available and clinically annotated BCa cohorts with gene expression profiles (GSE2603, GSE2034, GSE5327 and GSE12276) were pooled as described above. To remove systematic biases, before merging the expression measurements were converted to z scores for all genes.