dataesr/scientific-paragraphs-categorization huggingface dataset:
LINE-MYC primers (obtained from  [Rebbeck, 2007] ) Standard curves were constructed for each primer set using CTVT tumour 29T1 as reference. Relative DNA input was calculated using standard curves as follows: (Ct = m(log10(iA)) + b), with each of the parameters defined as follows: Ct = threshold cycle, m = slope of the standard curve, iA = input amount, b = y-intercept of the standard curve. Relative DNA input for LINE-MYC was then normalised to ACTB. LINE-MYC and ACTB are present in three and two copies respectively in 24T and 79T CTVT tumours  (Murchison et al. , 2014) ; however, it is possible that copy number at these loci differs between tumours in the current dataset. Forward.
NuMTs in CanFam3. 1 We first assessed the potential contribution of NuMTs present within the CanFam3. 1 assembly to our variant calling. We used wgsim (https://github. com/lh3/wgsim) to simulate sequence reads from CanFam3. 1 (excluding the MT chromosome) to a coverage of 0. 3X (i. e. the average nuclear genome coverage sequenced as part of this study). We then used BWA  (Li and Durbin, 2009)  to align the reads to the CanFam3. 1 MT reference and used Samtools depth  (Li et al. , 2009; Li, 2011)  to assess the MT genome coverage. Any MT genome coverage detected from this analysis would be expected to arise from NuMTs. The average MT genome coverage from this analysis was 0 (Figure 1-figure supplement 5), indicating that the NuMTs known to be present within CanFam3. 1 are at insufficient copy number and/or are too divergent to map to the MT reference genome using the alignment parameters used in this study.
Substitution calling Extraction and filtering Substitutions were called using CaVEMan (Cancer Variants through Expectation Maximisation), an inhouse variant calling algorithm, as previously described (Nik-Zainal et al. , 2012) (http://cancerit. github. io/CaVEMan/). As CaVEMan is designed for matched tumour-normal data, and CTVT tumours and normals are unmatched (i. e. they are different individuals), we used simulated reads derived from the reference genome as the 'normal', and called all substitution variants relative to this. A variant allele fraction (VAF value, i. e. number of reads supporting the substitution variant as a fraction of the total number of reads covering the substitution variant position) was reported for each substitution detected. The following list of in-built post-processing filters was used to improve the specificity and sensitivity of substitution calls:.
Extracting substitution variants from publicly available dog sequences In order to enrich our panel of germline substitutions created from 338 CTVT hosts, we included an additional set of 252 publicly available complete dog mtDNA genomes (see Supplementary file 8). To extract substitution variants from available fasta files, sequences were aligned with the CanFam3. 1 dog mitochondrial reference genome using Clustal Omega  (Sievers et al. , 2011). Alignment errors in the multiple sequence alignment, usually due to miscalls caused by closely mapped indels, were inspected manually and corrected to minimise gaps. Substitutions were extracted using snp-sites (https://github. com/sanger-pathogens/snp_sites). For those samples missing data in regions MT: 15510-15532 and MT: 16040-16550 we substituted the most likely substitution at polymorphic sites based on phylogenetic position.
Indel calling Extraction and filtering Small insertions and deletions (indels) were extracted from the sequencing data using cgpPindel (https://github. com/cancerit/cgpPindel). The following list of in-built filters was used to improve the specificity and sensitivity of indel calls:. Indels were required to have 3 supporting reads on either the forward or reverse strands or 2 supporting reads on both the forward and reverse strands. Indel calls with at least 4 supporting pindel-mapped reads were required to have at least 1 supporting BWA-mapped read or, failing that, if REP= 0 (see 'Substitution calling-Extraction and filtering'), then at least one supporting pindel-mapped read on both strands. Indels called within the simple repeat region MT:16129-16430 inclusive were excluded. Samples with very high coverage of the mitochondrial genome (24T-Dog, 24H-Dog, 1T-Dog, 2T-Dog, 3T-Dog, 4T-Dog, 4H-Dog, 498H-Dog, 432T-Dog, 455T1-Dog, 231T-Dog, 79H-Dog, 79T-Dog), see Supplementary file 2A, were excluded from this analysis due to frequent false positives, together with samples 1380T-Dog and 1381T-Dog.
Variant Allele Fraction calculation for indels Although primary indel calling was carried out using cgpPindel, indel allele fraction for wild type and mutant indels was calculated using vcfCommons (unpublished in-house software developed at the Wellcome Trust Sanger Institute; for additional information please contact cgp@sanger. ac. uk). The algorithm takes all mapped and unmapped reads in the region of an indel and performs an alignment of the reference and the predicted mutated path using Exonerate  (Slater and Birney, 2005). The predicted mutated path is the reference with the change predicted by cgpPindel applied to it. Based on this alignment, reads are classified into 3 categories: 1. aligns to reference path 2. aligns to mutated path 3. ambiguous; a read sequence aligns to the reference and mutated path with identical scores which makes it impossible to determine the true path Indel VAF values were normalised to take account of host contamination in Figure  2B.
Phylogenetic analyses Phylogenetic trees Phylogenetic trees were constructed using a maximum likelihood (ML) method implemented in PhyML 3. 0  (Guindon et al. , 2010)  using the General Time Reversible (GTR) + G + I nucleotide substitution model with transition/transversion (ts/tv) ratio, gamma distribution shape parameter and proportion of invariant sites estimated in PhyML for each dataset. Phylogenetic trees constructed using RAxML 8. 2. 6 with a rapid climbing algorithm and identical model specification were consistent with the phylogenetic trees obtained using PhyML. Prior to tree construction jModelTest2  (Darriba et al. , 2012)  (https://code. google. com/p/jmodeltest2) was used to determine the best fitting substitution model for the alignment, inferred using the Akaike Information Criteria (AIC).
The tree topology was estimated using a combination of Nearest Neighbor Interchange (NNI) and Subtree Pruning and Regrafting (SPR)  (Hordijk and Gascuel, 2005)  algorithms. Trees were visualised using Dendrocope  (Huson and Scornavacca, 2012). Bootstrap support values were obtained from 100 bootstrap replicates. Nodes with 60% support are labelled in Figure  1 -source data 2 and Figure  3 -source data 1. The long branch-lengths in CTVT clade 4 were further investigated by visually validating sequence alignments involving these samples.
Automated recombination analysis The RDP4 package  (Martin et al. , 2015)  was used to detect recombination events within the complete sample set (i. e. 449 CTVT tumours, 338 CTVT hosts and 252 additional dogs) using a Bonferroni corrected p-value cutoff of 0. 05. Default parameters were used for the following programs implemented within the RDP package: RDP  (Martin and Rybicki, 2000) , MaxChi  (Smith, 1992) , Chimaera  (Posada and Crandall, 2001) , 3Seq  (Boni et al. , 2007)  and SiScan  (Gibbs et al. , 2000).
Long read sequencing A genomic library was created directly using 5mg of genomic DNA from sample 559T, not utilizing shearing or amplification techniques, as previously described  (Coupland et al. , 2012). The library was sequenced using two PacBio SMRT cells using the Pacific Biosciences RS sequencer (Pacific Biosciences, Menlo Park, CA). Each SMRT cell yielded ~1Gb of sequence data with mean read length 11,421bp and N50 read length 19,382bp. Average sequence coverage across the mitochondrial genome was 111. 3X.
Acknowledgements We thank  Simon Frost ,  Young Seok Ju  and  Ludmil Alexandrov  for helpful discussions and advice. This work was supported by grants from the  Wellcome Trust  ( 102942/Z/13/A ) and the  Royal Society  ( RG130615 ), and a  Philip Leverhulme Prize  from the  Leverhulme Trust. We are grateful to  Michael Stratton  for his support. We would like to acknowledge the  Core Sequencing Facility , IT groups and members of the  Cancer Genome Group of the Wellcome Trust Sanger Institute. We are very grateful to  Cathy King  and all  World Vets  staff and volunteers who contributed to sample collection. We would like to thank the following individuals for useful information and for their help with obtaining samples for this project:  Adrian Baez-Ortega ,  Ekaterina Batrakova ,  Rafaela Bortolotti Viera ,  Matthew Breen ,  Austin Burt ,  Fernando Constantino Casas ,  John Cooper ,  Amici Cannis Cotacachi ,  Lytvynenko Dmytro ,  Ariberto Fassati ,  Ricardo Gaitan ,  David Hanzlı  ´c ˇek,  Mike Hobart ,  Rafael Ricardo Huppes ,  Matilde Jimenez-Coello ,  Debra Kamstock ,  Patrick Kelly ,  Tatiana Korytina ,  Ada Krupa , Anna.
5% for clarithromycin, 14. 1% for levofloxacin, and 34. 9% for metronidazole  [7]. Routine surveillance of antibiotic resistance in H. pylori could inform treatment recommendations and assess the efficacy of public health strategies aiming to control antibiotic resistance. This audit aimed to assess microbiology laboratory compliance with NICE guidance for the noninvasive diagnosis of H. pylori and to determine the number of laboratories undertaking culture and antibiotic susceptibility testing (AST). This data will be used to inform the need for enhanced implementation of the NICE guidance and decisions on how any future national H. pylori antibiotic resistance surveillance systems could be set up across England.
pylori in England are not known, and we do not know whether the threshold of resistance (20%) for changing the combination has been reached. Although it is not current practice, we recommend that patient demographic data, including indication for the test, should be routinely collected. As most laboratories perform stool antigen tests, this demographic and clinical data could be used to monitor H. pylori prevalence rates in different sectors of the population. Furthermore, commercial assays for detection of AMR in H. pylori in the stool specimens are available and could prove to be a useful tool for rapid detection of resistance to first-line agents like macrolides and quinolones  [23] [24] [25]. The use of multiple antibiotics for a prolonged period of time for the treatment of recurrent H.
Search strategy We searched Embase, OVID and the Cochrane Library to identify English-language abstracts published up to December 2015. Search terms and strategy were determined by the investigators with advice from a librarian. We applied the following search terms in various combinations which was adapted for each database: Search terms: antidepressants, selective serotonin reuptake inhibitors, SSRIs, pregnancy, autistic spectrum disorder, developmental delay, autism, ADHD, birth defects. We also hand-searched reference lists of included and excluded articles for articles of potential relevance.
Data management Abstracts were retrieved and screened and articles determined to be of potential relevance were retained. These articles were screened in detail and articles meeting inclusion criteria were included. Each abstract screened and each potentially relevant article retrieved was reviewed independently by two authors (JLN and DM). Discordances were resolved by discussion among the three authors. Review articles were excluded, though references were hand searched for other relevant original data-containing studies. Abstracts were included for analysis (human) if they satisfied the following inclusion criteria: • Provided exposure data on gestational SSRI use • Provided quantitative measures of cognitive behavioral or developmental function in the children exposed in utero • Controlled for exposure to other potentially teratogenic medications Abstract were included for analysis (animal) if they.
• Provided data on gestational antidepressant use • Provided quantitative measures relevant to cognitive behavioral or developmental outcomes We did not restrict by study design but quantitative results had to be available. We excluded articles where we could not obtain an English translation, review articles, and studies where we had abstracts. Data from included articles were extracted using a standardized form describing the following study characteristics: year, target population, location, sample size, study design, outcome measure, knowledge gaps, key conclusions and study setting. We assessed for duplicate citations and tools. Where the data on outcomes was available within the published study, we abstracted it from each of these studies. Where the data was not available, we wrote to the authors to request it.
Results The flow chart (Fig. 1 ) shows the study search results. Our search retrieved 112 citations of which 67 were potentially relevant abstracts. Of these 67 abstracts screened, 38 articles fit the inclusion criteria. Of these 27 were human studies and 11 were animal studies. Suitable data was available for abstraction in the papers from 21 studies and included in the human dataset. We did not receive responses for requests for data from the three Motherisk studies  [64] [65] [66]  and Suri et al. [67]. Casper et al. [68]  and Galbally et al. [69]  indicated an inability to access the data at the time it was requested. Eleven animal studies were identified with adequate data for abstraction from the published papers. Human study participant size ranged from 36 to 654,000. 16 of the 21 studies included in the analysis used a cohort design and 5 were case controlled.
Both charging and discharging cycles signals are generated by a PC using the LabVIEW software (National Instrument, Austin, TX, USA) and sent to power components via digital interfaces (GPIB and RS232). All the battery terminal voltage and current measurements from the different sensors were centralized, treated and stored in the supervising PC. In order to verify the validity of the proposed model and to evaluate its performance, experiments are conducted with a hybrid pulse test and a dynamic stress test (DST)  [29]. As shown in Figure  4 , the hybrid pulse test is a sequence of pulse cycles including standard Hybrid Pulse Power  In order to verify the validity of the proposed model and to evaluate its performance, experiments are conducted with a hybrid pulse test and a dynamic stress test (DST)  [29].
As shown in Figure  4 , the hybrid pulse test is a sequence of pulse cycles including standard Hybrid Pulse Power Characterization (HPPC) profile and a custom-defined discharging/charging pulse profile  [29]. The purpose of hybrid pulse test is to provide battery dynamic datasets for all SOC range for parameters identification. On the other hand, DST simulates the driving cycle-based conditions, and aims to evaluate the proposed model performance as shown in Figure  5. Characterization (HPPC) profile and a custom-defined discharging/charging pulse profile  [29]. The purpose of hybrid pulse test is to provide battery dynamic datasets for all SOC range for parameters identification. On the other hand, DST simulates the driving cycle-based conditions, and aims to evaluate the proposed model performance as shown in Figure  5.
Identification Results The parameters estimation process (Figure  2 ) have been performed with the recorded datasets of the hybrid pulse test (Figure  4 ). A number of generations 200 is selected to achieve the optimal solution for objective function ̂. The pre-computed coefficients , , , are used in Equation (  4 ) based on a previous work presented in  [14, 15]. The identified model parameters are given in Table  2. In order to validate the identification results with the proposed model, the measured voltages of hybrid pulse test on two type batteries are compared with the fractional-order model output voltages in Figure  6.
Identification Results The parameters estimation process (Figure  2 ) have been performed with the recorded datasets of the hybrid pulse test (Figure  4 ). A number of generations g " 200 is selected to achieve the optimal solution for objective function f ´χ g i ¯. The pre-computed coefficients K 0 , K 1 , K 2 , M are used in Equation (  4 ) based on a previous work presented in  [14, 15]. The identified model parameters are given in Table  2. In order to validate the identification results with the proposed model, the measured voltages of hybrid pulse test on two type batteries are compared with the fractional-order model output voltages in Figure  6.
Identification Results The parameters estimation process (Figure  2 ) have been performed with the recorded datasets of the hybrid pulse test (Figure  4 ). A number of generations 200 is selected to achieve the optimal solution for objective function ̂. The pre-computed coefficients , , , are used in Equation (  4 ) based on a previous work presented in  [14, 15]. The identified model parameters are given in Table  2. In order to validate the identification results with the proposed model, the measured voltages of hybrid pulse test on two type batteries are compared with the fractional-order model output voltages in Figure  6. From Figure  6 , it can be seen that the model prediction is very close to the experimental measurement over the entire SOC range.
Microscopy The development of colonies on the surface of filter papers was observed using a Zeiss confocal micro-scope (LSM 700 with 4 laser lines) with an inverted stage. A 10X lens and the "tile stacking" function were used to observe the development of the colonies. A laser excitation wavelength of 555 nm was used to observe C. vulgaris cells and micro-colonies. Image analysis was performed using the ImageJ software (http://rsb. info. nih. gov/ij/). The area of the colonies was measured by classical image processing operations:  conversion to binary using the threshold value obtained by the moments method  hole filling  pixel size calibration  particle analysis.
Acknowledgements This work has benefited from the financial support of the  LabeX LaSIPS  ( ANR-10-LABX-0040-LaSIPS ) managed by the  French National Research Agency  under the " Investissements d'avenir" program  ( n°ANR-11-IDEX-0003-02 ). The Chair of  Biotechnology of CentraleSupélec , in turn funded by  Reims Métropole ,  Conseil Général de la Marne  and the  Région Champagne-Ardenne  are also acknowledged for their financial support of this project. Laser Zentrum Hannover  acknowledges financial support from  Deutsche Forschungsgemeinschaft (DFG) , the  Cluster of Excellence REBIRTH , and  Lower Saxony  project  Biofabrication for NIFE.
This effect can be obtained by increasing the size and decreasing the number of the apertures in the last grids (AG2, AG3 and GG). If the gas density decreases inside the accelerator, also the amount of negative ions that are neutralized by stripping reactions decreases, hence the efficiency of the accelerator is increased. An estimate of the efficiency improvement compared to the MITICA case is planned in the next future using the AVOCADO code  [25].
First analyses on the DEMO NBI extraction/acceleration system To optimize the design of DEMO NBI extraction/acceleration system, a self-consistent model of the DEMO NBI grids has been developed in the COMSOL environment, able to investigate the magnetic, the electrostatic and the particle tracking aspects at the same time. In this model, each beamlet is composed by 1000 macroparticles, starting from a meniscus pre-calculated with the SLACCAD code [26], analogously to the SPIDER  [14]  and MITICA  [15]  cases. The particles are deflected by the magnetic and electric fields at the same time, being the electric field calculated summing the field generated by the grids plus the contribution due the negative space charge of the particles. The model, shown in figure  5 , includes all the grids, with circular apertures in the first three grids, slotted apertures in the AG2 and frame-like apertures in the AG3 and GG.
However, the eff ect should be minimal because HBsAg screening was only started at blood banks in 2011 and frequent shortages of testing kits have occurred. In a subset of participants with available information about previous blood donation, HBsAg prevalence was similar between fi rst-time and repeat donors. Finally, we assessed treatment eligibility at a single timepoint, but the longitudinal follow-up of our cohort is likely to identify additional eligible patients. We will address this question in the future. In high-income countries, community-based screening for viral hepatitis has rarely been done without assessment of the proportion of infected individuals in need of treatment. 33, 34 Consequently, our study provides original and important data about need for treatment, particularly in the general population, which will be useful for clinicians as well as policy makers.
Acknowledgments We thank the  European Commission  for funding the programme,  Gilead Sciences (USA)  for providing tenofovir treatment for the patients, the  MRC laboratories The Gambia unit, the local Ministry of Health and Social Welfare , and the  National Public Health Laboratories  for supporting the project. We thank all study participants and the PROLIFICA team, in particular  Ignatius Baldeh ,  Famara Bojang ,  Amie Ceesay ,  Mavis Foster-Nyarko ,  Debbo Jallow ,  Sheriff Kolley ,  Yamundow Jallow Samba ,  Alagie Sanneh ,  Bakary Sanneh ,  Demba Sonko ,  Lamin Bojang , and  Mamina Bojang. We thank  Mariama Jammeh , the coordinator of the national blood bank programme,  Debbie Garside , the project manager of  PROLIFICA ,  Christian Bottomley  for statistical.
Study protocol The trial was conducted in the neonatal intensive care unit of Robert DebreUniversity Hospital, Paris, France. Study was approved by the Ethics Committee (Comitede Protection des Personnes), Hopital Saint Louis, Paris, France (n˚: 06-12-07, January 15 th 2007) and was registered in the EUDRACT database (n˚: 2006-005335-16). All neonates were included after parental signed consent. 1. Inclusion criteria included postmenstrual age ! 35 weeks with a pathologic 24-hour intraesophageal pH monitoring. The latter was defined by a reflux index (RI, percentage of the entire record with intra-esophageal pH is <4) superior or equal to 5%. In our unit, 24h-pH monitoring is performed only in neonates with a postmenstrual age ! 35 weeks because of tube feeding and it is either prescribed systematically or following medical decision in the presence of clinical symptoms of GERD (vomiting oxygen, desaturation and bradycardia.
,). 2. Exclusion criteria included treatment with a PPI within a week of inclusion, acute gastrointestinal disease, metabolic and biological disorders and co-administration of atazanavir or ritonavir. 3. For pH monitoring, a single-use pediatric pH catheter with a pH-sensitive antimony electrode (VersaFlex 1 , Sierra Scientific Instruments) was placed in the lower esophagus through nasal insertion after a 3-hour fasting period. Positioning of the catheter was calculated using a body height formula (Strobel formula) or checked by chest X-ray. Recordings were performed with an external device (Ambulatory pH recorder, Orion II, Medical Measurement Systems) and pH curves were analyzed using appropriate software (GastroTrac 1 , Alpine Biomed Corp. and Medical Measurement Systems). In addition, oro-pharyngeal pH monitoring was performed using litmus paper (VWR International, France) 4.