dataesr/scientific-paragraphs-categorization huggingface dataset:
ACKNOWLEDGMENTS We are grateful to  Dr. Geoffrey Onaga  for strain collection in Uganda;  Dr. Bing Yang  for Xol BB 151-3 and BB 156-2 genome sequence; and  Emily Luna  for technical support. We thank  Drs. Mathilde Hutin ,  Céline Pesce ,  Sébastian Cunnac , and  Tuan T. Tran  for seed, constructive discussions, and technical support and  Dr. Young-Ki Jo  for providing Leersia hexandra. This article is based upon work from  COST Action CA16107 EuroXanth , supported by  COST (European Cooperation in Science and Technology).
ACKNOWLEDGMENTS We are very grateful to all the people who were directly involved in the development of this research:  José María Farré ,  José María Hermoso ,  Emilio Guirado ,  David Sarmiento ,  Alejandro Pérez-García ,  Juan C. Codina ,  Eva Arrebola ,  Victor J. Carrión , and  Jesús Murillo. We would like to thank SAT 2803 TROPS and all collaborating farmers. We also extend a special thanks to  Irene Linares  for her collaboration and technical support. This work is especially dedicated to the memory of our colleague  Juan A. Torés Montosa , who sadly passed away in July 2018. He was one of the original researchers responsible for the discovery of BAN disease, and the development of this research line in our laboratory.
FUNDING This research was supported by the  Spanish Plan Nacional I + D + I. Grant  AGL2017-83368-C2-1-R  and partially supported by the  European Union (FEDER). CV and ST were supported by a grant from  FPI ,  Ministerio de Ciencia e Innovación, Spain. FUNDING Capes-MEC  ( Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Ministério da Educação), Brazil , provided financial support for MF. FUNDING This research was supported by a  Marie Curie IOF Fellowship (EU Grant   PIOF-GA-2009-235457  to VV); the  Embassy of France in the United States, Office of Science and Technology -STEM Chateaubriand Fellowship Program  (to JML);  USDA   NIFA Postdoctoral Fellowship Award  No. 2016-04706  (to JJ);  USDA's National Institute of Food and Agriculture , award #  2018-67013-28490  (to JJ, JML, and JEL); and by  IRD JEAI Coana  (to SS and OK).
DATA AVAILABILITY STATEMENT The IX-280 genome assembly has been deposited in GenBank under accessions CP019226 (chromosome) and CP019227 (plasmid pXOO43) and the SK2-3 assembly under accession CP019515. Raw data and associated metadata are available from the Sequence Read Archive (SRA) under accessions SRR5989134 (IX-280) and SRR5990719, SRR5990720, and SRR5990721 (SK2-3).
Statistical Analyses Two statistical software packages, SPSS 20 (for Windows, Inc. , Chicago, IL) and MedCalc (Version 14. 8-©1993-2014 medCalc Software bvba), were used for data analyses. Data are presented as mean and standard deviation (mean ± SD). After normal distribution was examined using the Kolmogorov-Smirnov test, a paired Student t-test was used to compare values between the test and retest. An unpaired Student t-test was used to compare performances of elite and sub-elite subgroups. Relative reliability was assessed using the intraclass correlation coefficient (ICC) between the test and retest. An ICC < 0. 40 was considered low; between 0. 40 and 0. 70 acceptable; between 0. 70 and 0. 90 good and >0. 90 excellent  (Hopkins, 2009). Absolute reliability was analysed by calculating the standard error of measurement (SEM) as follows: SEM = SD × √1 ˗ ICC  (Stratford, 2004).
The usefulness of the test was assessed by calculating the smallest worthwhile change (SWC) as: SWC = 0. 2 multiplied by the between subject's standard deviation  (Hopkins, 2004). The ability of the test to detect small and meaningful performance changes was rated as good if SEM ≤ SWC, satisfactory when SEM = SWC, and marginal in case SEM ≥ SWC  (Liow and Hopkins, 2003). The minimal detectable change (MDC95%) at the 95% confidence interval (CI) of the difference in the score between paired observations was determined as MDC95% = SEM × √2 × 1. 96  (Stratford, 2004). The stability of the reliability determination was quantified using the 95% limits of agreement method of  Bland and Altman (1986). Effect size (dz) was calculated using GPOWER software (Bonn FRG, Bonn University, Department of Psychology)  (Faul and Erdfelder, 2004).
Acknowledgements The authors are grateful to all the participants of the  Tunisian National Taekwondo Team  for their valuable time and contribution. We thank  Mr. Mohamed Ali Rouahi ,  Mr. Seifeddine Trabelsi  and  Mr. Anouar Jlassi  for their help in the experimentation. This study was supported by  The Research Laboratory "Sports Performance Optimization" National Center of Medicine and Science in Sports (CNMSS).
Background: The efficacy of the recombinant, live, attenuated, tetravalent dengue vaccine (CYD-TDV) against virologically-confirmed dengue (VCD) has been documented in a phase 3 trial in Latin America (CYD15, NCT01374516). This is a descriptive secondary analysis of the efficacy and safety of CYD-TDV in participants from Colombia. Methods: Data from 9740 Colombian participants 9-16 years of age who were randomized 2:1 to receive CYD-TDV or placebo were assessed to describe the vaccine efficacy of CYD-TDV against VCD and severe VCD. Estimation was made of the relative risk (RR) for hospitalized VCD cases and severe hospitalized VCD cases after the first dose of CYD-TDV, as well as a description of the incidence of hospitalized dengue from the start of the study and per year of the study until study completion.
Furthermore, World Health Organization (WHO) has considered the availability of the dengue vaccine in its latest recommendations so that it can be taken into consideration at a regional level. 20 ecombinant, live, attenuated, tetravalent dengue vaccine (CYD-TDV) is a recombinant, live, attenuated, tetravalent dengue vaccine administered according to a 3-dose schedule at 6-month intervals (0, 6 and 12 months). Vaccine efficacy (VE) studies have been conducted in several dengue endemic countries, including a phase 3 study, CYD15 (NCT01374516), conducted in 5 Latin American countries (Colombia, Brazil, Mexico, Puerto Rico and Honduras). 21 The study included 3 phases: the active phase, which was an active surveillance of 25 months follow-up that captured all symptomatic dengue cases in the study participants (hospitalized or not); followed by the hospital phase, which was a passive follow-up of the participants to capture those dengue cases that merited hospitalization and a surveillance expansion period from around year 4 to the end of the study, which was reinstated to capture symptomatic dengue cases (hospitalized or not).
The vaccine was administered as per schedule (3 doses at 0, 6 and 12 months), with a follow-up at month 13 including a blood sample. In CYD15, postdose 3 to month 25 VE in the Per-Protocol Analysis Set (primary endpoint) demonstrated a protection of 60. 8% [95% confidence interval (CI): 52. 0-68. 0] against symptomatic virologically-confirmed dengue (VCD); in the intention-to-treat population (participants who had received at least 1 injection), VE was 80. 3% (95% CI: 64. 7-89. 5) against hospitalized VCD and 95. 5% (95% CI: 68. 8-99. 9) against severe VCD after the first injection. 21 In a case-cohort posthoc study of participants of CYD15 who were dengue seropositive at baseline, the VE for symptomatic VCD was 78. 1% (95% CI: 69. 9-84. 1). 22 The objective of the current analysis is to describe the efficacy and safety of CYD-TDV in participants from Colombia, based on the data from CYD15.
Posthoc Case-Cohort Study for Dengue Serostatus at Baseline Data from each efficacy trial were analyzed in a case-cohort study, including a randomly selected subcohort of around 10% of the entire population, as described by Sridhar et al. 22  Baseline dengue serostatus was determined based on measured plaque reduction neutralization test (PRNT 50 ), with a cut off threshold for seropositivity ≥10 or predicted when missing. For participants in the posthoc case-cohort analysis, missing PRNT 50 serostatus at baseline was imputed using month 13 anti-non-structural protein-1 (NS1) titers [cutoff thresholds for positivity of 9 enzyme-linked immunosorbent assay (ELISA) units per milliliter] as a continuous variable and other variables as predictors using multiple imputation (MI) as previously described.
Identification of Cases Active follow-up of the participants occurred from the first injection until month 25; active surveillance of hospitalized and nonhospitalized febrile cases (temperature ≥38°C for ≥2 consecutive days) was conducted. Blood samples were obtained from any participant with an acute febrile illness so as to confirm the presence of dengue. This acute sample was obtained within 5 days after the onset of fever. The reverse transcriptase-polymerase chain reaction was performed to test for VCD, and ELISA for the presence of the dengue NS1 antigen on the acute samples. After this active follow-up stage, a 4-year, long-term safety followup took place with a passive surveillance of hospitalized VCD cases (hospital phase) from years 3-6 of the study; the current subanalysis does not include data from year 6 of the study.
Statistical Analysis According to Serostatus at Baseline 4] [25]  For the MI, the estimate is computed from 10 iterations and combined with the use of Rubin variance rule. The VE (%) and 95% CIs were derived as 1 HR 1 - ( ) × 00. Statistical analyses were performed using SAS version 9. 2 for the original CYD15 analysis and SAS version 9. 4 for NS1 analysis (SAS Institute, Cary, NC). Serious adverse events (SAEs) and deaths were reported in both study groups.
These data validate the WHO recommendations to offer the vaccine where there will be the greatest benefit, that is, populations in areas with high dengue seroprevalence and circulation of the 4 serotypes. Seroprevalence has been reported to be between 79. 5% and 97. 8% in endemic areas of the country but can be lower (50. 8%) as reported by Carabali et al, in Medellin. 16, 17, 28, 29 In our study, serostatus at baseline was measured (PRNT 50 at month 0) or imputed (ELISA NS1 immunoglobulin G at month 13), using tests that are not validated or registered to assess dengue baseline serostatus. Currently, classification of serostatus for implementation of the CYD-TDV vaccine relies on the use of commercially available serologic tests which may perform differently in terms of sensitivity and specificity.
ACKNOWLEDGMENTS Editorial assistance was provided by  Nwoza Eshun , inScience Communications,  Springer Healthcare Ltd ,  United Kingdom. Funding for this assistance was provided by  Sanofi Pasteur. The CYD15 teams in sites in Colombia:  Dr. Victor Sierra , Yopal;  Dr. Edith Rodriguez , Aguazul;  Dr. Hector Velasquez , Acacias;  Dr. Jaime Carrillo , Girardot;  Dr. Victor Osorio ,  La Tebaida ;  Dr. Hector Pachón , Montenegro;  Dr. Reinaldo López , Calarcá;  Dr. Erwin Pardo , Armenia and  Dr. Luis Villar , Bucaramanga.
The study was conducted in three hospitals (Hospital Serdang and Hospital Tengku Ampuan Rahimah (HTAR) in Selangor state and Hospital Teluk Intan in the Perak state) from January 2016 to December 2017. Blood specimens were collected upon admission from all participants using plain tube and EDTA blood tube for serology and PCR tests respectively. Upon availability, blood specimen for serological testing was also collected from the recruited patients on discharge and two weeks after discharge. Blood collected in EDTA tube was stored in -40˚C freezer until DNA extraction. Socio-demography, clinical data and possible risk exposures for all participated patients were recorded using a standardized interviewer-administered questionnaire (S1 File).
0 software (DNASTAR Inc. , Wisconsin, USA) and compared against the GenBank database using BLAST to identify the species  [18]. Multilocus sequence typing (MLST scheme 1) was performed based on the extended, nested MLST targeting seven loci (glmU, pntA, sucA, tpiA, pfkB, mreA, caiB) of seven pathogenic Leptospira species (L. alexanderi, L. borgpetersenii, L. interrogans, L. kirschneri, L. noguchi, L. santarosai, L. weilii)  [19, 20]. For sequence type definition, allelic profiles were analysed through the Leptospira MLST database (http://pubmlst. org/leptospira). All primers used in MLST are listed in Table  1.
Molecular characterization of infecting Leptospira spp. Among the 165 clinically suspected leptospirosis patients, lipL32 was detected in 47 (28. 5%) and rrs gene in 63 (38. 1%) patients. All lipL32-PCR positive samples were positive by the rrs PCR. The blood and serum samples that were positive by lipL32 showed Ct values between 28. 96 and 39. 67. The BLAST analysis of partial 16S rDNA (rrs) gene sequencing revealed two pathogenic Leptospira species with 100% identity, which are L. interrogans (n = 44, 70%) and L. kirschneri (n = 17, 27%), and one intermediate species L. wolffii (n = 2, 3%). The identity of the isolates and the accession numbers of the 16S rDNA for all isolates are listed in Supplementary Table  1  (S2 File). In Selangor hospitals (Hospital Serdang and HTAR), L. kirschneri was found to be more prevalent while L.
interrogans dominated in Hospital Teluk Intan (Perak state), p-value<0. 001 (Table  3 ). MLST was attempted in all PCR positive cases (n = 63). However, only those samples with successful amplification of three or more alleles were included for the analysis. A total of nine blood samples showed amplification for at least three alleles, however only one gave a complete MLST profile. For the sample that showed complete MLST profile, the combination of alleles did not match a known sequence type (ST) in the MLST database for Leptospira species, hence a new ST was created with the help of the MLST curator (www. pubmlst. net) and identified the PLOS NEGLECTED TROPICAL DISEASES isolate as ST 265 Leptospira interrogans. The remaining eight samples amplified at least three loci (Table  4 ). The loci that were most frequently amplified were glmU and pntA (n = 9) followed by mreA (n = 5), sucA (n = 4), pfkB, tpiA and caiB (n = 3).
We tried to arrange the allele pattern for the Leptospira MLST genes detected in human (present study) and rodents from our previous study  [13]. This was done to see whether they share similar alleles in order to determine the epidemiological link as the ST was not available for the human infecting strains to compare with the animal strains. From the MLST dataset (Table  4 ) no link could be established between the human-infecting strains and rats strains (ST 50, ST 238, ST 243 L. interrogans and ST 110 L. kirschneri). None of the seven genes in the human and animal showed similar alleles except for pntA (L. interrogans), sucA (L. interrogans and L. kirschneri), tpiA (L. interrogans), mreA (L. interrogans), however, the allele combinations were different.
Acknowledgments We acknowledge the  Ministry of Health Malaysia  for reviewing and approving all the procedures involved in this study. We thank members of  GLEAN (Global Leptospirosis Environmental Action Network)  and  WHO  Reference Centre, Amsterdam,  The Netherlands  for guidance throughout the project. Special thanks to all doctors, nurses and staff in  Hospital Serdang and Hospital Tengku Ampuan Rahimah in Selangor state and Hospital Teluk Intan  in the Perak state that helped us in recruiting the patients. We also take this opportunity to thank all members of this project, for their commitment and contribution during the performance of this study. The authors thank the Director General of  Health, Malaysia  for his permission to publish this article.
Behavioral battery All the tasks performed by The Jackson Laboratory's Mouse Neurobehavioral Facility (MNBF) were previously validated using control B6 mice. The spontaneous alternation task, a measure of working memory, was conducted as previously described  (Sukoff Rizzo et al. , 2018). Briefly, a clear Plexiglas Y-maze was used under adjusted, ambient lighting (;50 lux). Subject mice were acclimated to the testing room for 1 h before testing. Tested mice were then placed midway of the start arm (A), facing the center of the Y for an 8-min test period, and the sequence of entries into each arm are recorded via a ceiling mounted camera integrated with behavioral tracking software (Noldus Ethovision). The percentage of spontaneous alternation was calculated as the number of triads (entries into each of the three different arms of the maze in a sequence of three without returning to a previously visited arm) relative to the number of alteration opportunities.
Experimental design and statistical analysis For behavioral analyses, groups of 10-12 mice per sex per genotype per diet allowed us to detect effects of. 1. 15 SE at 80% power as shown previously  (Graham et al. , 2019). Changes to vascular structures, white matter and microglia were identified using sample sizes of at least 5. Samples sizes are provided in the figure legends (n, biological replicate and refers to number of mice/samples used in each experiment). Region of interest was standardized for all statistical analyses: hippocampus CA1 (region including stratum radiatum, pyramidal layer and stratum oriens), cortex (region including posterior cortex, layers 4-6), corpus callosum (region between CA1 and posterior parietal cortex). Regions determined based on Allen Brain Atlas. All data were analyzed using GraphPad Prism software.
For comparisons between two groups, significance was calculated using unpaired t tests. For multiple comparisons, significance was calculated using multi-factorial analysis of variance (ANOVA) followed by Tukey's post hoc tests. ANOVA assumes equal variance and this was determined before each test using the Brown-Forsythe test; p values provided are as stated by GraphPad Prism software and significance was determined with p , 0. 05. SEM was used in all graphs.
A, B, WD-fed male mice showed a significant impairment in % correct alternation (A), which was not due to reductions in total activity as measured by total arm entries (B). However, C1qa KO WD-fed male mice showed no significant impairment in % correct alternations when compared with CD-fed male mice. C, D, No differences were observed in % correct alternations between CD-fed and WD-fed female mice. E, G, Activity levels in the open field as measured by cumulative distance traveled revealed no differences between groups in both male and female mice. F, H, Grip strength measurements were not different between groups in both male and female mice. Data are presented as mean 6 SEM, n ! 8, pp , 0. 05 by one-way ANOVA with Tukey's post hoc test. Triglyceride levels were decreased in C1qa KO males and unchanged in females from WT and C1QA-deficient mice (Fig.
3F, H ). The levels of LDL were only increased in males by the WD in both mouse strains (Fig. 3I, K ), while HDL levels were increased in both females and males from WDfed mice (Fig. 3J, L ). Changes in the level of fatty acids were not found in any of the experimental groups (Fig. 3M, N ). Obesity is a high risk for insulin resistance, therefore glucodynamic responses were evaluated in WD-fed and CD-fed WT and C1QA-deficient mice. While no changes in blood glucose levels were found in the basal, non-fasting state (Fig. 4A, C ), only WD-fed WT males presented a moderate impaired glucose tolerance, that was prevented by the deficiency of C1QA in the WD-fed C1qa KO males (Fig. 4B, D ). Finally, no differences in insulin levels were observed (Fig. 4E-H ). Collectively, these data show WD-fed C1qa KO and WT mice were obese but not insulin resistant or diabetic.
Results: We have developed PVAmpliconFinder, a data analysis workflow designed to rapidly identify and classify known and potentially new Papillomaviridae sequences from NGS amplicon sequencing with degenerate PV primers. Here, we describe the features of PVAmpliconFinder and its implementation using biological data obtained from amplicon sequencing of human skin swab specimens and oral rinses from healthy individuals. Conclusions: PVAmpliconFinder identified putative new HPV sequences, including one that was validated by wet-lab experiments. PVAmpliconFinder can be easily modified and applied to other viral families. PVAmpliconFinder addresses a gap by providing a solution for the analysis of NGS amplicon sequencing, increasingly used in clinical research. The PVAmpliconFinder workflow, along with its source code, is freely available on the GitHub platform: https://github.
Methods Details of the workflow can be found in Supplementary Data 2. Briefly, PVAmplicon-Finder takes paired-end FastQ files as input and applies common data preprocessing steps for quality control and filtering (Fig. 1a ). Then, data complexity is reduced before the identification of the PV-related sequences (Fig. 1b ). Groups of sequences are defined based on similarity between identified sequences and available PV sequences in the NCBI database (Fig. 1c ). De novo assembly is then performed to reconstruct the full amplified region covered by several primer systems (Fig. 1d ). Finally, the reconstructed sequences are taxonomically classified based on two independent methodologies, which are alignment-based and homology-based, respectively, before the generation of diverse output reports (Fig.
Identification of PV-related sequences and definition of groups To identify the sequences in an unbiased manner, the sequences were aligned against the complete NCBI "nt" nucleotide sequence database, which includes all sequences from all species (Fig. 1c ). Subsequently, groups of sequences were defined based on two characteristics: the best MegaBlast subject sequence for each query, and the percentage of similarity of each sequence with its corresponding best subject sequence (Fig. 1c ).
Taxonomic classification of PV sequences The taxonomic classification of each PV sequence was then assigned to the extended sequences using two methods, one based on the taxonomic classification of the best subject match (using the e-value computed by BlastN) when aligned against a comprehensive database of PV sequences, and the other based on molecular evolution using the Randomized Axelerated Maximum Likelihood-Evolutionary Placement Algorithm (RaxML-EPA) (Fig. 1e ). For details, see Supplementary Data 2. The results of the classification for DNA sample pool S5 (skin samples pool; CUT primer) are described in Table  2. In this sample pool, 2 putative new PV sequences N sequence showen N = 1 (3 reads) N = 1 (4211 reads) Megablast BlastN RaxML-EPA Megablast BlastN RaxML-EPA Alpha - - - - - - Beta - - - - - - Lambda - - - - - - Tau - - - - - - represented by 5 reads and 39 putative known PV sequences represented by 60,892 reads were identified (Tables  1  and 2 ; Supplementary Tables S5 E and G).
One of the putative new PV sequences in this pool was represented by 3 reads (PV_ 2). The MegaBlast algorithm (using the full "nt" database) aligned it against "Gammapapillomavirus 13 isolate Gamma13_HIVGc158, complete genome" (MF588722. 1) with 81. 25% of identity. Of note, although the Gamma13_HIVGc158 is a complete genome, this sequence is not reported in the Papillomavirus Episteme (PaVE) database. The BlastN algorithm (using the PaVE database) aligned this sequence against HPV-mEV03c45 (MF588721), an unreferenced Gamma PV genome, with 78. 69% of identity. RaxML-EPA found the best position of this putative new sequence in the reference tree close to HPV213 (MF509818), also a potential Gamma PV, but with pending approval of its classification by the International Committee on Taxonomy of Viruses (ICTV) (Tables  2  and 3 ).