dataesr/scientific-paragraphs-categorization huggingface dataset:
Variables The e-CRF registered 290 variables including demographics, comorbidity, data on infection and diagnosis, previous eradication attempts, current treatment, compliance, AE and effectiveness  [36]. The variable treatment length was assessed using three categories for first-line therapies, corresponding with the most frequent treatment durations: 7, 10 and 14 days; and two categories for second-line attempts: 10 and 14 days. The variable dose of the proton pump inhibitor (PPI) was grouped in three categories (low, standard and high doses) according to reports by Graham and Kirchheiner  [25, 39]  (See File S2).
Institutional Review Board Statement: The Hp-EuReg protocol was and approved by the Ethics Committee of La Princesa University Hospital (Madrid, Spain) that acted as reference Institutional Review Board  (20-Dec-2012)  and was conducted according to the guidelines of the Declaration of Helsinki, was classified by the Spanish Drug and Health Product Agency, and was prospectively registered at Clinical Trials. gov under the code NCT02328131. An addendum for a ten-year extension of the project was also approved  (15-Jan-2015). Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.
Acknowledgements The project received funding from  ANR  ( ANR-10-GENOM_BTV-015  UtOpIGe),  Alliance R&D, FranceAgrimer ,  InaPorc , and  INRA GISA metaprogramme (HealthyGrowth). The authors are extremely grateful to the personnel of Le Rheu test experimental station for measurement and sampling performed on live pigs and carcasses; to the  INRA PEGASE  staff for laboratory analyses; and the  French breeding companies (Axiom, Choice Genetics France, Nucléus ), members of Alliance R&D who produced the animals and provided pedigree data. The authors are indebted to  A. Davenel  for performing the MRI analyses. C. Dugué   0000-0002-6781-344X.
However, in data registered during horse competitions, the inclusion of several additional random effects in the model in addition to the genetic effect has been studied, but the optimal set of effects to be included remains unclear  [8, 25]. The objective of this study was to estimate the genetic parameters that are relevant to the variability of the position of horses in endurance races, including the genetic correlation between the variability of position and the position by defining an appropriate transformation of the trait. The effects of including the rider, the rider-horse interaction, or permanent environmental effects as additional random effects in the model were also evaluated.
Methods The total dataset consisted of 2863 ranking records from 621 horses (238 males, 253 females and 130 geldings) aged between 5 and 24 years, with at least two records per horse. Most of the horses were Arabian horses (69. 6%), and the remaining were Anglo-Arabian horses (20. 5%), Spanish sport horses (5. 5%), and horses of other breeds (4. 4%). The records were collected during 581 endurance races held in Spain (92% of records), in France (6%), and in other countries (2%), between 2000 and 2016. Records on non-placed animals were removed from the dataset. The number of records per horse ranged from 2 to 22, with an average of 4. 6 records per horse. The number of different riders in the dataset was 612. The average number of riders who rode a particular horse was 1. 9; 56. 8% of horses were ridden by different riders.
y i = x i b + z i u + w i r + e 1 2 (xib * +z i u * +w i r * ) ε i. u u * ∼ N 0 0 , σ 2 u ρσ u σ u * ρσ u σ u * σ 2 u * ⊗ A , Model R: Rider effect with 612 levels. Model RH: Rider-horse match effect with 1196 levels. Model P: Permanent environmental effect, a second horse effect different from the genetic effect, with 621 levels. Variance components were estimated using the Bayesian procedure of the GSEVM software  [28]. For comparative purposes, since residual variance is not unique in the HE models, a residual variance can also be estimated for a particular level of systematic effects. A global residual variance was estimated in the HE models by adding the averages of the estimates of all the levels within systematic effects. To maintain estimability of the corresponding linear combination, solutions for all levels of each of the other systematic effects were averaged within all the remaining systematic effects and added to the solution for that particular desired level of the systematic effect.
Results Table  1  shows the estimates of variance components and genetic parameters obtained from the six models, as well as the DIC value for each model as a comparative measure of fitness. Based on the DIC criterion, any HE model was preferable to any HO model. For both the HO and HE models, inclusion of rider as an additional random effect produced the best fit, while inclusion of a permanent random effect resulted in the worst fit. Heritability of rank ranged from 0. 12 (HE-P) to 0. 15 (HO-RH), and given their standard deviation, we considered that there was no difference between these values. HE models tended to give slightly higher estimates of the global residual variance because they express the variance in an intermediate scenario within all systematic effects. The HE models assume that records are balanced across the dataset, whereas in the real dataset they are unbalanced.
526 patients inclus, dont 260 (49,4 %) randomisés dans le groupe de traitement empirique et 266 (50,6 %) dans le groupe expérimental. Le taux de résistance à la clarythromycine et à la lévofloxacine était respectivement de 23,3 % et 12,8 %. Le test respiratoire était disponible pour 415 (78,9 %) patients. Le traitement guidé par la sensibilité aux antibiotiques était supérieur au traitement empirique en termes d'éradication d'Helicobacter pylori (85,5 % vs 73,1 %, RR=1,85, IC95 % [1,25-2,78], p=0,003). Ces résultats étaient similaires après imputation multiple des données manquantes (RR=1,61, IC95 % [1,14-2,27], p=0,003) et en analyse per-protocole (RR=1,89, IC95 % [0,25-2,78], p=0,003). Conclusion. Dans un pays présentant un taux élevé de résistance à la clarythromycine, un traitement guidé par la sensibilité aux antibiotiques permet d'obtenir un taux d'éradication d'Helicobacter pylori supérieur à un traitement empirique (ClinicalTrials.
Randomization and blinding Eligible patients with H. pylori infection were randomly assigned, on a 1:1 ratio, to receive either a tailored triple therapy guided by the results of the PCR test detecting resistance to clarithromycin and levofloxacin (HelicoDR ® ) or an empirical triple therapy (PPI-amoxicillin-clarithromycin). Centralized randomization was performed using a computer-based randomization list generated by the study statistician at the data center. Randomization, which was performed using CleanWEB © (Telemedicine Technologies S. A. -2007), was balanced in blocks of various sizes, with stratification according to the center and previous eradication treatment (yes/no). Patients and investigators were not blinded to treatment assignment. Primary endpoint (urea breath test result) was assessed by physicians who were blinded to the treatment groups.
Statistical analysis The sample size calculation was based on the following assumptions: an eradication rate of 70%, a 20% increase in eradication rate in the PCR-guided group, a two-sided α of 0. 05, and a power of 95%. Accordingly, 200 patients with a urea breath test follow-up were necessary in each group. Therefore, we planned to recruit 500 patients with bacteriologically documented H. pylori infection. Continuous data is presented as a mean (SD) or median (interquartile range) as appropriate. Categorical data is presented as counts and proportions. The statistical analysis followed the intention-to-treat principle, i. e. all patients were analyzed in the group to which they were randomly assigned, for the efficacy endpoint and on the treatment principle for the safety endpoints. We first used a multilevel model, a randomcenter effect logistic regression, to account for potential clustering  [22].
Crude and multivariate odds ratios (ORs) were estimated with their 95% CI. All analyses were performed with the use of R version 2. 10. 11 (The R Foundation for Statistical Computing; http://www. R-project. org) and Stata version 12. 1 (StataCorp, College Station, TXT, USA). A two-sided p value ≤0. 05 was considered to indicate statistical significance. No interim analysis was performed. Reporting of the present study was done according to the CONSORT 2010 Statement [23]. This trial is registered with ClinicalTrials. gov, number NCT01168063.
211 Da elemental composition: C22H36O15N2 and Glycan 2; 668. 227 Da elemental composition C26H40O18N2) and acetylation of protein N-termini. The precursor mass tolerance was set to 20 parts-per-million (ppm) for the first search and 10 ppm for main search, with a maximum false discovery rate of 1. 0% set for protein and peptide identifications. The resulting outputs were processed within the Perseus (v1. 4. 0. 6) (28) analysis environment to remove reverse matches and common proteins contaminates prior to further analysis. Glycopeptide identified were manually assessed according to the guidelines of Chen et al. (29) , annotated manually with the aid of Protein Prospector tool MS-Product (http://prospector. ucsf. edu/prospector/cgibin/msform. cgi?form=msproduct). The MS proteomics data were deposited in the ProteomeXchange Consortium via the PRIDE partner repository  (30, 31)  with the dataset identifier PXD018788.
Data can be accessed under username: reviewer60750@ebi. ac. uk, password: C7kqIWps. Analysis of BCAL2737a degradation in Burkholderia strains. As BCAL2737a was not annotated in the reference B. cenocepacia strain J2315 (see Results), we re-analyzed the previously published B. cenocepacia K56-2 peptidome datasets (Pride accession: PXD014614) (32) including BCAL2737a. Searches were performed against the predicted amino acid sequence of BCAL2737a and the K56-2Valvano proteome (NCBI: Taxonomy ID: 985076) with identical setting as above. The resulting outputs were processed in the Perseus (v1. 5. 0. 9) analysis environment to remove reverse matches and common protein contaminates prior to further analysis. Peptides identified across samples were visualized in heat maps using R (https://www. r-project.
Statistical analysis. Means and standard deviations were calculated using GraphPad Prism 8 software (GraphPad Prism 8; GraphPad Software, USA). Three independent repeats were tested for every sample in ELISA. The cutoff value is calculated based on OD450 nm value of samples tested negative in CFT (excluding inconclusive results). Samples were considered positive when the absorbance reading exceeds the cutoff value computed by two standard deviations above the mean of the negative control. The specificity and sensitivity of the ELISA and western blot tests were determined using the CFT as a standard according to the following formulas: Sensitivity (%) = !"#"$"%&" ()*+,+-" !"#"$"%&" ()*+,+-". /"*, %"01,+-" ×100% Specificity (%) =.
RESULTS Identification of a protein-glycan glycoconjugate antigen for antibody detection. In a previous study characterizing the general protein glycosylation system in B. cenocepacia, one of the most abundant and highly glycosylated glycopeptides found, designated A0K9U9, could not be ascribed to any annotated protein in the database of the type strain J2315  (21). To localize the gene encoding this peptide, its 71 amino acid sequence was used as query in Artemis (33) to search the translations in all frames for B. cenocepacia type strain J2315. This resulted in the identification of a short open reading frame in chromosome 1 (at base pairs 3008284-3008496) located in the intergenic region between BCAL2737 (encoding a putative pseudouridine synthase) and BCAL2738 (encoding a putative exported protein), which was preceded by a ribosomal binding site sequence (Fig.
1 ); we designated this open reading frame BCAL2737a. The predicted BCAL2737a gene encoded a 71-amino acid polypeptide; it also contained a 21amino acid signal peptide, predicted by SignalP v. 5. 0  (34) , as expected for a glycosylated protein since glycosylation takes place in the periplasm. The BCAL2737a protein did not show any homology with known proteins in the database. The mature polypeptide contained 3 serine residues (Fig. 1 ) that become O-glycosylated based on experimental evidence by mass spectrometry  (21). Therefore, the BCAL2737a polypeptide was selected for further analysis since because of its small mass, combined with 3 glycosylation sites, it could be an appropriate antigen to detect antibodies against Burkholderia O-glycans.
Western blot analysis revealed that purified CtxB-BCAL2737a expressed in ΔpglL exhibited decreased electrophoretic mobility, suggesting it corresponded to an unglycosylated form (Fig. 3A ), in agreement with the results found with crude lysates (Fig. 2B  and D ). Similarly, only the protein expressed in K56-2 was detected with PNA, indicating the correct trisaccharide glycan residues were present. Glycosylation was also verified by mass spectrometry confirming at least three serine residues within BCAL2737a are glycosylated (Fig. 3B , Supplementary Dataset). To further support the degradation of unglycosylated BCAL2737a peptidome datasets from Oppy et al. (32)  were reanalyzed against a K56-2 proteome containing the BCAL2737a protein sequence. The new analysis identified multiple peptide breakdown products previously not assigned to known proteins, which were more abundant and intense in the glycosylation null strain ΔpglL compared to K56-2 and the pglL complemented strain (Fig.
Acknowledgements (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. We thank  Dr. Nora Madani  for suppling equine sera from the experimental trial with B. mallei and  Dr. Keren Turton  for a critical review of the manuscript. We also than  Dr. Pat Lenihan  (Ireland),  Dr. Vania Lucia Santana  (Brazil), and  Prof. Mohammed Sami   A (Kuwait)  for providing field negative and positive horse sera. This research was supported by a  Medical Research Council   Confidence in Concept grant  ( CD1617-CIC04 ) to M. A. V. and R. J. I. This work was supported by  National Health and Medical Research Council of Australia (NHMRC)  project grants awarded to NES ( APP1100164 ). We thank the  Melbourne Mass Spectrometry and Proteomics Facility of The Bio21 Molecular Science and Biotechnology Institute at The University of Melbourne  for access to mass spectrometry infrastructure.
In investigating outbreaks, genome sequencing of isolates from patient clusters has provided evidence for the close genetic relationship of epidemiologically linked However, genetic diversity both within a patient and across the isolates within an outbreak has also been observed, suggesting a simmering threat of infections. The large number of sequenced isolates from around the world has also provided evidence of infections acquired during travel, often associated with hospital stays in other countries. With genomes of over 700 isolates publicly available in GenBank, a deep resource of data is available for genomic comparisons. These genomes have been further mined by correlating genomic changes in known mutation hot spots, including drug target loci, with resistance data to identify resistance mechanisms.
As the clinical population structure of C. auris is quite different from that of other pathogens where STR typing is applied, adding markers to more finely resolve relationships within a clade and resolve discrepancies with genome data would be needed. Additional development may also prioritize clade discriminatory markers; several markers in the current panel have the same allele in clade I and III isolates, and none appear to be conserved in and unique to all isolates from a clade. Additional development might also examine STR variability across a more genetically diverse set of isolates, such as by screening the over 700 genomes in the NCBI database, selecting those that are not part of clonal clusters. This would provide needed information about the mutation rates of different STR markers, which might help guide their selection.
The use of a set of reference isolates that is easily available to researchers around the world is also critical to include for standardizing STR clade assignments by different groups. Comparison across studies will require development of a centralized database that includes quality standards. In addition to genotypes being shared, the raw data of the capillary electrophoresis could be curated, as is done for various MLST databases. Recommended best practices will also help yield more comparable studies. These should include standardization of DNA input requirements and inclusion of an allelic ladder, which have been shown to impact typing results  (12). Simplifying analysis procedures is also needed; currently, expertise and specialized software are required to generate genotypes. The use of different software to construct minimum spanning trees may affect results and therefore the relationships between genotypes or isolates.
| Glomerular filtration rate Glomerular filtration rate (GFR) had been measured using a combined plasma exogenous creatinine Iohexol clearance test (PEC-ICT). 21, 22, 25 iefly, 64. 7 mg/kg exo-iohexol and 40 mg/kg creatinine had been injected intravenously. Ethylenediaminetetraacetic acid (EDTA) plasma samples had been collected before and 5, 15, 30, 60, 90, 120, 180, 360, and 600 minutes after injection. For our study, only values of the exoiohexol clearance were used. The plasma levels of exo-iohexol had been analyzed using high-performance liquid chromatography with ultraviolet detection. 23 Pharmacokinetic analyses had been performed using WinNonlin (WinNonlin Version 4. 0. 1, Scientific Consulting Inc, Apex, NC). The plasma data had been subjected to noncompartmental analysis using a statistical moment approach.
| Statistical analysis SAS (Statistical Analysis Software Version 9. 4, SAS Institute Inc, Cary, North Carolina) was used for all statistical analyses using a global significance level of 5%. An ANOVA F-test was used to check for the presence of a group effect on each variable (SDMA plasma , GFR, and sCr) and was followed by Dunnett's multiple comparisons where diseased animals (DM/CKD) were compared pairwise with healthy controls. P values were adjusted for multiple comparisons. Kendall's Tau correlation coefficients (τ B ) were calculated to investigate the relationship between GFR and , SDMA plasma , and sCr. Subsequently, we calculated the specificities and sensitivities (and 95% confidence interval) for SDMA plasma and sCr at their predefined cutoff values and at 2 different levels of GFR impairment since the renal clearance is the gold standard for CKD diagnosis.
33 Five cats out of all achieved a renal clearance between 1. 2 and 1. 7 mL/(min kg), indicating the presence of mild renal impairment. Furthermore, the small number of cats with early CKD could explain the reason for no added diagnostic value of SDMA that could be established in our data set and further studies are needed. The allocation of the cats to the different subgroups was based on physical examination and routine laboratory analysis. But when the GFR result was taken into account, 3 cats initially considered as healthy and 2 cats with DM were found to have mildly impaired renal function. On the other hand, 1 cat of the CKD group had a GFR value >1. 7 mL/(min kg). Residual frozen blood samples stored for maximum 8 years were used for SDMA analysis. Short-term stability of the molecule in blood has already been reported.
Dissection and parasite identification After behavioural observations, gammarids were individually stored in ethanol (96%) before dissection and parasite identification. Individuals were measured (length of the fourth coxal plate,  Bollache & Cézilly, 2000)  and sexed (morphology of the second pair of gnathopods,  Hume et al. , 2005)  with a SMZ1500 Nikon stereomicroscope (Mitsubishi, Tokyo, Japan) coupled with an R1 Nikon camera (Mitsubishi, Tokyo, Japan) connected to a computer with NIS-Br software. Gammarus pulex individuals were dissected to attest acanthocephalan infection, identify parasite species, and count the number of parasites. Phenotypic alteration induced by acanthocephalans on their intermediate hosts depends on both species and developmental stage of the parasite. Therefore, a posteriori exclusion-inclusion of gammarids was applied after dissection, and only cystacanth stages (i.
laevisinfection. Statistical analyses were conducted using R 3. 5. 0 software (A Language and Environment for Statistical Computing), and the additional libraries "nlme"  (Pinheiro, Bates, Debroy, & Sarkar, 2019) , "AICmodavg"  (Mazerolle, 2019) , "ggplot2"  (Wickham, 2016)  and "car"  (Fox & Weisberg, 2018).
Acknowledgements We are grateful to  Coralie Jacquemin ,  Eric Meineri  and  Maxine Thorel  for their comments and suggestions that helped improve an earlier version of the manuscript. We thank  Mathilde Gaston  for her excellent work and help with behavioural observations. Finally, we thank  Marjorie Sweetko  for improving the English of this manuscript. This work was funded by the  Labex DRIIHM ,  French programme "Investissements d'Avenir"  ( ANR-11-LABX-0010 ) managed by the  ANR within the Observatoire Hommes-Milieux Bassin Minier de Provence (OHM BMP ) and the  ECCOREV Research Federation  ( FR 3098 ). Hadrien Fanton  received a PhD fellowship from the  Ministère de la Recherche et de l'Enseignement Supérieur  and this paper is part of his Ph. D. thesis.
RumiWatch accuracy for lying, standing, and walking activity has been reported as sufficient for research purposes  [27, 28] , and the RumiWatch has previously been used successfully in one study to detect lameness in zero-grazing cows  [16]. A pedometer was attached to a rear leg at the metatarsus position for each observed cow. Daily summaries of 14 behaviors (Table  2 ) were generated using the RumiWatch Converter 7. 3. 36, algorithm V00_56  [29]. The mean and standard deviation of the 24-hour summaries for each of the 14 measures for each of the seven scoring events is presented (Table  3 ). Operator errors and technical faults resulted in smaller than expected sample sizes. Some pedometers failed to operate at all. One appeared to operate but failed to record data. Three recorded erroneous data with no or unfeasibly low walking time and these were excluded from the analysis.
The first three trials had 16 and the final trial had 15 useable data sets (Table  1 ). Samples were of mixed parity. In trial 1, five cows were first lactation and 11 were multiparous. In trial 2, there was one cow with a parity of 1 and 15 cows were multiparous. In trial 3, all the cows were multiparous. In trial 4, three cows had a parity of 1 and 12 cows were multiparous. Power analysis was performed to inform the interpretation of the findings using the R package pwr  [30]. Spearman's Rho correlation was calculated for behaviors and mobility score in individual trials. Generalized linear models were used to assess associations in aggregated data. Mobility score was the dependent variable while the "behavior" (e. g. , lying bouts) and trial were the fixed effects. The data and the r code used in this study are available online via github  [31].
† p < 0. 10, *p < 0. 05, ** p < 0. 01. In addition to analyzing individual trial data, the individual trial data was also aggregated/pooled as follows. Trials 1A, 2, 3A, and 4a were combined into one dataset, henceforth known as aggregated dataset A. Trials 1B, 2, 3B, and 4B were combined into another dataset labeled as aggregated dataset B. With 62/63 observations, these datasets were sufficiently powered (f2 = 0. 16) to detect what Ford  [33]  described as 'medium' effect sizes with an alpha of 0. 1 in a general linear model with two independent variables. This would be a comparable effect size to a Pearson's correlation of ~0. 31  [33]. For aggregated dataset A only, Laying Counter and Stand Up were significantly associated with mobility. Laying counter and Stand Up counter are almost identical measures with a Pearson's correlation of 0.