dataesr/scientific-paragraphs-categorization huggingface dataset:
Cardiac conduction abnormalities are commonly found in HOS. They are more likely to occur in those with a structural heart defect, but it is reported that about 40% of cases have conduction abnormalities alone  [16]. We were not able to study this manifestation of HOS, as recording of functional abnormalities is optional and reported data are not complete. It is therefore possible that some patients with upper limb anomalies and only conduction heart defects will be diagnosed later in adolescence or adulthood when the symptoms of heart disease develop. Other associated anomalies have also been described in HOS patients and may include craniofacial, tracheal, pulmonary, vertebral, renal and lower limb anomalies  [5, [32] [33] [34] [35] [36]. These can be incidental findings or may be atypical cases of HOS due to specific sequence variants of the TBX5 gene  [11, 36, 37].
We observed single cases with cleft uvula, brain cyst, spleen anomaly, pyelon duplex, ectopic kidney and hemivertrebra. Lower limb anomalies were found in 3 patients. The types of anomalies (one bilateral hip dislocation, one lower limb shortening, one club foot) would suggest random association rather than the clinical spectrum of HOS. Two cases with renal anomalies and a case with hemivertebra were evaluated for the possible diagnosis of VATER, but this was not conclusive. The patient with hemivertebra had ASD type secundum, radial and thumb aplasia on the right hand and phocomelia on the left side, which is more indicative of HOS. Data on molecular tests for cases with associated anomalies were not available. The proportion of familial cases was 15. 1%, which is consistent with the results of the only population study on HOS  [20]  and contrasts with clinical reports citing that up to 85% of cases are familial due to the ascertainment bias  [16, 20, 23].
Prevalence The results of this European study show that HOS is a very rare condition with an average prevalence of 0. 7 per 100,000 births and a high regional variation [range 0. 3 (N W Thames)-2. 4 (Vaud) or 1: 330,763 to 1: 41,737]. The prevalence is higher in registries were familial cases are recorded. The mean prevalence of 1: 135,615 births represents a minimum figure and refers to a group of patients with obvious clinical presentation. The only population-based study on HOS was conducted in Hungary covering the 1975-1988 period  [20]. The established prevalence of 0. 95 per 100,000 births is in agreement with the prevalence of 1. 0 per 100,000 births recorded in our dataset for 1990-2000. Interestingly, there is a significant decrease in the prevalence rate for 2001-2011 period, for which there is no obvious explanation and requires further monitoring.
Conclusions HOS is a rare genetic condition with regional variability. It is often missed prenatally in spite of the presence of major anomalies. When discovered, half of the parents will opt to continue the pregnancy even in the presence of severe limb defects and CHD. Our data indicate that the number of severe CHD in HOS is underestimated since they are present in one quarter of HOS patients. In spite of this, the overall first week survival is good, which is important information for genetic counselling of affected families.
Acknowledgements This study is part of the  EUROCAT Joint Action  funded by the  EC , under the framework of  EU   Health Programme 2008-2013 , Grant Agreement 20102204 (Executive Agency for Health & Consumers). All registers in England are funded by  Public Health England. We thank doctors  Sebastiano Bianca ,  Jean Chapple ,  Berenice Doray ,  Christine Francannet ,  Anna Latos-Bielenska ,  Carmen Mosquera-Tenreiro ,  Mary O'Mahony ,  Joaqin Salvador ,  Gioacchino Scarano ,  David Stone ,  Romano Tenconi  for providing data for the present study. We also thank the many people throughout Europe involved in providing and processing information, including affected families, clinicians, health professionals, medical record clerks and registry staff.
Using this approach, we have obtained a 100% response rate. Two patients who relapsed during follow-up were retreated using the same approach and achieved a second complete response. As DIS and rituximab can impact organ engraftment, we assessed the potential risk of graft rejection. For this purpose, we systematically took serial myocardial biopsies, the gold standard for diagnosis of graft rejection. Using this rigorous protocol, we did not detect any increase in rate of graft rejection in patients treated with either DIS or rituximab (Table  3 ). No treatment-related neutropenia or infections were detected in patients treated with rituximab. The primary goal of our study was prevention of PTLD. Since the incidence of PTLD is very low, prospective randomized studies are very difficult to design and recruit for; therefore, comparisons with historical data are appropriate to address this question.
The number of chemotherapy cycles depended on the prognostic subgroup: favorable or unfavorable (Fig  1 ). 18, 19 he study was approved by the respective scientific boards and national ethics committees and was registered in ClinicalTrials. gov. 20 Patients were centrally randomly assigned to receive either standard or investigational treatment. A minimization technique was used for treatment allocation in each prognostic subgroup (favorable v unfavorable), stratifying by institution, Ann Arbor stage (I v II), and availability of baseline PET.
Early PET Scan A prospective central reading of the early PET scan was planned in the protocol. 21 For technical reasons, centralized review for the LYSA group started from the initiation of the trial, and for EORTC/FIL groups, it occurred from 2008 onward. In case of absence of a timely (Ͻ 72 hours) centralized reading, the local result of the early PET scan was decisional for further treatment in the experimental arm (first PET interpretation). A blinded second central PET review (second central review) was performed retrospectively after the recommendations of the independent data monitoring committee (IDMC) by four experts on the scans of 52 patients with events (including patients with early PET-negative and early PET-positive scans) and 52 randomly selected patients without events using a dedicated workstation (POSITOSCOPE; Keosys, Saint-Herblain, France).
RESULTS The database was locked for the interim analysis at April 19, 2010. The analysis was based on patients randomly assigned on or before August 31, 2009, at which time a total of 1,137 patients had been randomly assigned, with 61%, 25%, and 14% recruited by LYSA, EORTC, and FIL respectively. Median follow-up at the clinical cutoff date (October 31, 2009) was 1. 1 years. A baseline PET scan was performed in 93. 2% of patients. Figure  2  shows the flowchart for patients enrolled in the interim analysis (favorable subgroup, n ϭ 444; unfavorable subgroup, n ϭ 693). In the favorable subgroup, 85. 8% (381 of 444) had a negative early PET scan, and in the unfavorable subgroup, 74. 8% (519 of 693) had one. The frequency of early PET-negative scans was somewhat higher in the experimental arm (81.
Time-of-flight information and delay line signals are read by a time-to-digital converter (LeCroy 3377 TDC) operated in common stop mode and gated to accept only events in the expected time-of-flight range from 55 μs to 87 μs. Data from the TDC and ADC are read into a personal computer by a CAMAC system and are analyzed in offline mode. To correct for varying detection efficiency at http://www. epjtechniquesandinstrumentation. com/content/1/1/6 different positions of the delay line anodes, the detector was homogeneously illuminated using an 241 Am α-source. The efficiency map obtained this way was used to weigh counts in the electron-scattering measurements.
Energy scans are used to measure the electronimpact-energy dependence of the total cross section for metastable state excitation that is used to calibrate the impact energy scale based on RMPS calculations. From the measured energy dependence of the cross section the width of the electron energy distribution is Figure Velocity distribution in the target jet. The velocity distribution is determined from the time-of-flight distribution of helium excited by electrons with threshold energy, and the logistic fit to the experimental data is used in simulations of the experiment. The mean velocity is 1624 ms -1 and the full width at half maximum (FWHM) of the distribution is 220 ms -1. http://www. epjtechniquesandinstrumentation. com/content/1/1/6 determined by comparison with theoretical cross-sectional data  [12]  that are convoluted with Gaussian distributions of different standard deviation.
Data analysis In the experiment, the momentum transfer in the detector plane is measured very accurately. Error propagation analysis for Eq. (  6 ) with typical values results in an uncertainty of q x,y = 0. 068 a. u. that originates mainly from the transversal size of the gas jet. Analogously, the uncertainty of the momentum in the jet direction given by Eq. (  7 ) is an order of magnitude higher: q z = 0. 8 a. u. , which is almost exclusively due to the initial velocity distribution in the gas jet. Because the highest transferred momentum is 0. 4 a. u. at 2. 2 eV excess energy, no useful information about the momentum transfer in z-direction is available. Therefore, in the analysis, projections of the momenta on the x-y plane are used. Two methods of data analysis are applied. First, restricting analysis to events near the peak of the time-of-flight distribution is used to suppress large q z -values.
Acknowledgements This work was supported, in part, by the  United States National Science Foundation  under grants No. PHY-1068140 ,  PHY-1212450 , and  PHY-14230245 , as well as the XSEDE allocation PHY-090031 (KB and OZ). Support of the  Australian Research Council  and iVEC via the  The Pawsey Centre 's advanced computing resources is gratefully acknowledged as well (DVF and IB).
Heterologous antigen expression did not modify yeast RNA and TSP patterns as compared to wild type yeasts (Figure  S2 ). Theses profiles were maintained independently of yeast amounts loaded on sucrose (data not shown). To look for the structure of RNPs, yeast lysates were observed by electron microscopy (EM). In the N recombinant SMD1168 yeast, we found numerous RNPs with herringbone shape of 20-22 nm diameter and variable rod length of 30 to 200 nm (Figure  4A ). This finding was similar to that previously described in recombinant P. pastoris GS115 strain  [32]  and in mammalian cells infected by MV  [29]. In the N-PbCS sample, RNPs appeared less rigid than N-only RNPs with length spanning from 30 to 70 nm. Most N-PbCS RNPs were detected in microenvironments where discrete rings were visible next to rod-like structures (Figure  4B ).
Electron Microscopy SMD1168 yeasts expressing N or N-PbCS were lysed and clarified as described above. EM was directly performed on N clarified lysate, while the N-PbCS clarified lysate was concentrated by ultracentrifugation on 20-60% sucrose gradient for 1 h30 at 32,000 rpm (SW32 Ti). The fractions at the interphase were collected, and further ultracentrifuged on 30% sucrose cushion for 4 h at 32,000 rpm (SW32 Ti) to collect the pellet. Samples were spotted on glow discharged carbon coated grids (EMS, USA) and negatively stained with NanoW (Nanoprobes, USA)  [65]. Samples were then observed at 120 kV with a Philips/FEI CM 12 transmission electron microscope. Images were recorded using a KeenView camera (OSIS, Germany) and ITEM software (OSIS, Germany). RNP length and diameter were estimated as the average measures of 50 particles counted manually.
8. 2. 0, Zeiss) and was composed of a motorized inverted microscope (AxioObserver Z. 1, Zeiss) equipped with a halogen illuminator (HAL100, Zeiss), a metal halide illuminator (HXP120, Zeiss) and a CCD camera (AxioCam MR, Zeiss). DAPI, Alexa Fluor and Cy3 were detected with specific filter sets. Stacks of 6 focal planes spaced 0. 5 mm apart were acquired with a 100x oil objective (EC Plan-Neofluar 100x/1,30 Oil Iris, Zeiss). Images were then processed with the ImageJ software  [67].
If mice showing these signs had been euthanized before day 15, or had received any treatment, the outcome of the experiment (possibility to recover from cerebral malaria) would have been arbitrarily changed. No significant weight change was observed. Parasitemia level was not correlated to the day of death. Identified moribund mice were euthanized by C0 2 treatment in an appropriate chamber. Blood samples (2 ml) were collected from day 3 to 7, diluted in 600 ml 1xPBS and analyzed in plates by Fluorescence Activated Cell Sorting (FACS; MacsQuant, Miltenyi Biotec). Doublets and clusters of red blood cells (RBCs) were excluded from counts. Single GFP + RBCs (infected RBC, iRBCs) among total RBCs were estimated and data analyzed by the MACSQuantify TM Software. For IgG quantification in blood, sera from bleedings were separated from blood samples by Capiject T-MG Capillary Blood collection System (Terumo Medical Corporation) and stored at 220uC untill ELISA tests.
Acknowledgments The authors are grateful to the  Transversal Research Project  staff from the  Institut Pasteur. The authors thank  Dr Bertrand Raynal  ( Macromolecule Biophysics  and  Interactions Core Facility, Institut Pasteur)  for providing the sedimentation calculation routine. We are grateful to  Salah Mecheri (Host-Parasite Interaction Biology Unit of the Institut Pasteur)  for providing his expertise on cerebral malaria in the mouse model. We thank  Jean-Michel Betton  ( Structural Microbiology Unit of the Institut Pasteur ) for helpful discussions on fusion protein design. We are grateful to  CEPIA (Institut Pasteur)  for technical support in mosquito housing. Daria Jacob  was supported by  DIM Malinf  and the  Ile-de-France Regional Council  (http://www. dim-malinf. org/),and  Pauline Formaglio  by the  DGA  ( Directorate General of Armament ) and the  FRM (Foundation for Medical Research ).
Low impedance (<5 kΩ) between electrodes was obtained by shaving, gently abrading the skin with sandpaper and then cleaning it with isopropyl alcohol. Signals were analogue-to-digitally converted at a sampling rate of 2000 Hz by PowerLab system (16/30-ML880/P, ADInstruments, Bella Vista, Australia) and octal bio-amplifier (ML138, ADInstruments) with bandpass filter (5-500 Hz) and analyzed offline using Labchart 7 software (ADInstruments).
Data analysis Peak-to-peak MEP and Mmax amplitudes were measured offline for each individual response. Individual MEP and Mmax amplitudes were then averaged and MEP amplitudes were normalized to Mmax amplitudes evoked in relaxed muscle. Data collected from a similar group of subjects in our laboratory indicated Mmax amplitudes were similar at rest and at the contraction intensities employed in this study (i. e. up to 50% MVC, unpublished observations, 2012). RMT was determined as the lowest stimulus intensity producing at least 5 MEPs of at least 0. 05 mV from 10 stimuli. RMT was also determined from 6 and 8 stimuli (minimum of 3 and 4 MEPs, respectively). Stimulus intensities of 120 and 130% RMT were determined for comparison with methods used in other lower-limb studies  [9, 11, 13, 14, 27, 30, 33].
Acknowledgements We sincerely acknowledge the assistance of  Dr Léonard Féasson  and  Dr Pascal Edouard  for conducting the medical inclusions and  Régis Bonnefoy  for his technical expertise. John Temesi  was supported by a doctoral research grant from the  Rhône-Alpes Region. Mathieu Gruet  was supported by a grant from the  Fonds de Dotation Recherche en Santé Respiratoire , appel d'offres 2011 for research on the brain during exercise.
Acknowledgements TZ thanks the  Alexander von Humboldt Foundation  for a  Humboldt Award  and the  French-German L. E. A. "Sono" as well as ERC "Ree -cycle". Supercomputing access was granted by the  LRZ Munich  ( HLRB  Project  pr63ca ). This work was supported by the CheMISyst excellence project ( 2012-2019 ).
GLT1 Underlies Higher Aspartic and Glutamic Acid Consumption in the SA Strain In order to identify causative loci for traits of interest, we further studied in detail QTL2 and QTL5 underlying aspartic and glutamic acid consumption differences, because these two amino acids were highly preferred by both strains. For this, we examined polymorphisms' data from the SGRP and YRC databases, gene function descriptions from SGD and performed a GO term search over a set list of nitrogen related genes. Initially, we filtered genes based on the presence of single nucleotide polymorphism within the ORF or regulatory regions between both strains and selected several genes adjacent to the QTLs. Next, we looked at those genes with function descriptions which could be most likely related to nitrogen metabolism.
Polymorphisms in the Validated Genes GLT1, AGP1 and ASI1 To identify the polymorphisms that could underlie the allelic effects observed in the reciprocal hemizygotes strains, we further analysed the changes within the regulatory and coding regions of GLT1, AGP1 and ASI1 by examining the SGRP database  [38]  and SIFT analysis results  [38]. A SIFT analysis allows to predict if an amino acid substitution could significantly affect a protein domain based on sequence homology analysis and the physical properties of the amino acid changes. Sequence comparison analysis on the GLT1 sequence revealed four non-synonymous polymorphisms in the WE background (G65E, D321N, K679R and G1988D) affecting several domains of the protein. A SIFT analysis identified that G1988D could be deleterious, affecting the FAD/NAD(P)-binding domain.
Another possible explanation for the observed pleiotropy is that most amino acid permeases can transport more than one type of amino acid. For example, Bap2p and Bap3p permeases mainly transport branched amino acids, Agp1p branched polar, branched non-polar amino acids and even some aromatic amino acids  [17, 49]. To identify the allelic variants underlying nitrogen assimilation differences between SA and WE strains, we looked for candidate loci within QTLs. To this end, we tried to narrow down the number of genes by utilising a filtering strategy combining the SGD gene description and polymorphisms data from SGRP and YRC databases  [2, 38, 51]. Using this approach, we identified candidate genes, AGP1 for QTL1, GDH2 and GLT1 for QTL2, AGP3 for QTL3 and ASI1 and GAT2 for QTL9. Subsequently, we performed reciprocal hemizygosity analysis and validated an effect for GLT1, AGP1 and ASI1.
Reciprocal Hemyzigosity Assay The genomic intervals of each QTL were examined in the Saccharomyces genome database (SGD), the Gene Ontology (GO) term database  [62] , the SGRP database  [38]  and the YRC database  [51]. The sequence of the candidates genes were downloaded from the SGRP BLAST server of the University of Toronto (http://www. moseslab. csb. utoronto. ca/sgrp/). To validate the presence of a QTL, we performed a reciprocal hemizygosity assay  [63]. The gene URA3 (essential for pyrimidine biosynthesis) previously deleted in the parental strains  [55]  was used as a selectable marker with some modifications. Briefly, we used haploid versions of the parental strains (WE MAT a, ho::HygMX, ura3::KanMX and SA MAT alpha, ho::NatMX,ura3::-KanMX) to delete each target gene and construct all possible combinations of single deletions.
Next, mutated parental strains were crossed to generate the reciprocal hemizygote strains and selected in double drugs plates (50 mg/mL Hygrormycin B and 100 mg/mL Nourseothricin). The diploid hybrid strains were confirmed by MAT locus PCR  [64]  and the deletions of the target genes were confirmed by PCR using the primers pairs A1/S8 o A4/S5  [26]. Primers are listed in Table  S5. Complete alignment was performed using ClustalX2 (Complete alignment option) and the phylogenetic tree was built using the maximum likelihood algorithm and Tamura-Nei model to estimate genetic distance in PhyML 3. 0 software  [65].
This work was funded by grants from  ATIP-Avenir ,  ARC  ( SFI20111203947 ) to GL and  FONDECYT 1100509  to CM. FAC is supported by  Conicyt  (Apoyo al retorno de investigadores desde el extranjero grant number  82130010 ). VG is supported by  FONDECYT Post-Doctoral 3120107. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
The Kimura distance we observed in Uganda was indeed <2. 5% for the F gene between 2001 and 2011. Until recently most of the classification of these viruses was based on the F-protein cleavage site partial sequences and their restriction analysis  [3]  but this method harbored inconsistencies for example in the evolutionary distances between genotypes and subgenotypes  [20]. In the present study we used the new classification system proposed by Diel et al. [7]  for nomenclature and classification of the class II ND viruses to classify our viruses and compare them with other East Africa strains with full F gene sequence available in GenBank. Our study confirmed the benefit of using this new classification system for NDV strains but at the same time highlighted some differences in the different genotyping criteria; specifically the distance estimates percentages and tree topology.
In our current analysis, while most of the East African NDV strains have a sufficient distance estimate from the other genotype V strains to form a new genotype, the tree topology analysis does not differentiate them into a different genotype but rather groups them among genotype V viruses (Figure  2 ). This highlights the importance of both distance estimates and tree topology for NDV genotyping and suggests that criteria used for genotyping may need to be updated in the future. The Ugandan viruses from our study clustered in genotype V with most other NDV sequences from Kenya and Tanzania that were available in GenBank for analysis. Interestingly, there was very limited diversity among our isolates, all of them clustering in genotype V. Our strains also differed from the genotype Ia strains identified in Tanzania (previously classified as lineage 1a)  [20] , genotype II strains identified in Tanzania and Ethiopia (previously classified as lineage 2)  [20, 22] , genotype IV strain identified in Sudan (previously classified as lineage 3b)  [23] , genotype XIII isolates from Burundi and Tanzania (previously classified as genotype VIIb or lineage 5b)  [16, 20] , genotype VIf strains from Tanzania (See figure on previous page.
) Figure  2  Phylogenetic trees (ML trees) of the fusion (F) gene of Ugandan Newcastle disease virus (NDV) isolates at the nucleotide level. Partial F gene sequences are indicated with a "*" symbol after the strain name. A single representative virus was selected for strains with identical nucleotide sequences: NDV/chicken/Uganda/MU001/2011 was identical to NDV/chicken/Uganda/MU004/2011 and NDV/chicken/ Uganda/MU005/2011; NDV/chicken/Uganda/MU026/2011 to NDV/chicken/Uganda/MU028/2011; and NDV/duck/Uganda/MU062/2011 to NDV/ chicken/Uganda/MU063/2011. The F sequences of our Ugandan NDV isolates were compared with A) all full F gene sequences available in GenBank database: 1209 sequences, and B) the reference vaccine strain Lasota, a representative strain for each of the genotype V subgenotypes, and all the East African NDV strains available in the database (indicated with an open circle).