dataesr/scientific-paragraphs-categorization huggingface dataset:
28 However, few robust analyses of the impact of journal initiatives on published research quality exist. The NPQIP (Nature Publication Quality Improvement Project) Collaborative group examined the potential impact of Nature journals' checklist on the reporting quality of in vivo research in 448 articles using primarily a controlled before-after study design. 21 Our analysis of Nature journals' publications differs by focusing on Nature Medicine (considered to be focused on translational research) and by evaluating a larger sample size (n=949) over a longer period to increase our confidence that changes observed were due to the publishing group's intervention rather than secular trends in editorial practices or culture. Nevertheless, our data support their conclusions and expand on them by demonstrating improvements in study quality after instituting reporting and methodological standards at other journals.
Non-compartmental analysis Non-compartmental analysis describes the evolution of CLD concentrations without any assumptions. This analysis is mainly used to obtain basic TK parameters. The noncompartmental analysis was performed using the PKanalix software (Lixoft, version 2019R1). To compare TK parameters between different species, a non-compartmental analysis was performed on CLD kinetic data in pigs and with data previously obtained on goats and ewes  (Fournier et al. , 2017; Saint-Hilaire et al. , 2019). Non-lactating and non-pregnant adult ewes (n=5) and goats (n=4) of 65. 8 ± 2. 2 and 33. 0 ± 3. 5 kg (mean ± standard error (SE)) BW respectively were used in these studies. For each species, four TK parameters were calculated with the non-compartmental analysis: total body clearance (CL), steady-state distribution volume (Vss), mean residence time (MRT) and area under the serum curve (AUC).
Moreover, age differential between the two breeds may have amplified growth performance differences and fatness of carcass  (Renaudeau et al. , 2006). CLD has a different behavior from other POPs such as PCB because CLD is known to be more concentrated in liver and muscle than in fat tissues  (Lastel et al. , 2016; Lastel et al. , 2018). High concentrations of CLD in liver and muscles may be explained by its affinity for plasmatic proteins  (Soine et al. , 1982). CLD linked to plasma proteins would arrive faster and in greater quantities in organs and tissues heavily irrigated (liver and muscles) than in those weakly perfused (fat tissues). Slaughtering data were analyzed to characterize molecule distribution in the three matrices analyzed (liver, muscle and fat) and to highlight possible differences in CLD distribution between the two breeds.
Conclusion This study permitted to establish for the first time a NLME model of CLD in growing pigs. Major TK parameters like body clearance (76. 7 mL kg -1 d -1 ) and distribution volume (6 L kg -1 ) were determined. ADG is an important covariate explaining inter-individual TK parameters variability. This study provided relevant and original data to describe distribution and elimination of CLD in pigs. In the near future, these results may be used by the risk manager to assess adequate rearing management practices in CLD contaminated areas. Moreover, since the pig is a valuable model for humans, these results may also be used to build a TK model of CLD in humans. Koh, W. X. , Hornbuckle, K. C. , Thorne, P. S. , 2015. Human serum from urban and rural adolescents and their mothers shows exposure to polychlorinated biphenyls not found in commercial mixtures.
Acknowledgements The experiment was funded by  ANR  through research program  INSSICCA  ( ANR-16-CE21-0008-01 ). The authors thank  Harry Archimède  (URZ),  David Beramice ,  Bruno Bocage ,  Katia Benony ,  Laurent Dantec ,  Mario Giorgi ,  Felix Silou  (PTEA),  Valeriuse Calif ,  Yoann Félicité ,  Dalila Feuillet ,  Lucien Philibert  (URZ) and  Pamela Hartmeyer  ( URAFPA ) for their technical support. They are grateful to  Alain Chauvin  and  Francis Le Gouevec  ( UEPR, Rennes ) for surgeries. They warmely thank  Catherine Adam  ( LEAE-CART ) for analysis and  Pierre-Loic Saaidi  ( Génomique Métabolique ,  CEA ,  CNRS ,  Univ Evry, Université Paris-Saclay, Evry, France)  for the 10-monohydrochlordecone synthesis. They thank  Jean-Pierre Thomé  ( LEAE-CART ) for his advices.
MSU-induced peritonitis model One milligram of preformed MSU crystals was injected intraperitoneally at h0 and a peritoneal lavage was conducted 6h later, under anesthesia, with cold PBS. Peritoneal fluid was subsequently analyzed by flow cytometry and ELISA. Briefly, the liquid was filtered through a 40µm porosity strainer, centrifuged at 300g 5min at 4°C and cells were stained with anti-Gr1-FITC, anti-CD11b-APC and anti-CD14-PE antibodies to count the neutrophil and monocyte populations. Absolute numbers were also determined in peritoneal collections by multiplying the percentages of neutrophils/monocytes to the absolute numbers of cells in the lavage. Flow cytometry acquisitions were realized with the BD Accuri C6 cytometer (BD), data were analyzed with the BD Accuri Software.
Magnetic resonance imagery (MRI) To detect and localize inflammation in paws, anatomical MRI was acquired in eight ex vivo mice. The day before MRI exam, 3mg of MSU and PBS were injected subcutaneously in the left and right paws respectively. ALDARA cream was applied on paws in four mice; control cream was applied on the other four. Mice were sacrificed under isoflurane anesthesia just before the MRI. MRI was performed on 7/30 Biospec system (Bruker Biospin, Ettlingen, Germany). Transmission was achieved with a quadrature volume resonator (inner diameter of 86 mm), and a surface coil (~ 10 mm), installed on paw, was used for signal reception (Bruker BioSpin, Ettlingen, Germany). MRI experiments were realized with ParaVision 6. 0. 1 software. T2WI anatomical dataset was acquired using RARE-3D sequence using following parameters: FOV: 15 x 15 x 8 mm3, matrix 150 x 150 x 80, TE eff = 26.
MRI Data analysis and 3D reconstruction The signal bias of T2WI induced by the surface coil used was corrected with N4 bias correction (Advanced Normalization Tools, ANTs). Paws were automatically co-registered based on the bones to one of the control mouse using FLIRT (FMRIB Software Library, Oxford, UK). The inflammatory areas were automatically segmented using FAST (FMRIB Software Library, Oxford, UK). Volumetric images were obtained with the help of the 3D viewer module of Image J, 3D reconstruction was made using the 3D Slicer software.
Analysis of RNA-seq data The transcriptome data set, composed of sequencing reads, was generated by an Illumina NextSeq instrument. The objective was to identify genes that are differentially expressed between two experimental conditions, namely treatment and control. For every sample, quality control was carried out and assessed with the NGS Core Tools FastQC (http://www. bioinformatics. babraham. ac. uk/project s/fastqc/). Sequence reads are mapped using STAR  [14]  and unmapped reads are remapped with Bowtie2  [15]  using with the very sensitive local option. The total reads mapped were finally available in BAM (Binary Alignment Map) format for raw read counts extraction. Read counts were found by the htseq-count tool of the Python package HTSeq  [16]  with default parameters to generate an abundant matrix.
At last, differential analyses were performed by the DESEQ2  [17]  package of the Bioconductor framework. Up-regulated and down-regulated genes were selected based on the adjusted p-value and the fold-change information. Gene expression was analyzed using dedicated R scripts to build volcano plots and graphs of Gene Ontology (GO) terms enrichment. Heatmaps were built using the online application heatmapper (http://www. heatmapper. ca/). IPA (Ingenuity pathway analysis, Qiagen) was used for pathway analysis. Predictions of immune cell population from RNAseq data were made with the ImmQuant deconvolution software  [18].
Real-time quantitative PCR (RT-qPCR) Total RNA was reverse transcribed using the cDNA synthesis kit (iScript ready-to-use cDNA supermix, Biorad). Real-time quantitative RT-qPCR was performed in a total volume of 20µL using the Sso-advanced universal SYBR-Green supermix (Biorad) and gene-specific primers (sequence available upon request). After a denaturing step at 95°C for 30 seconds, 40 cycles were performed (95°C for 5s and 60°C for 20s) using a Rotor-Gene 6000 real-time PCR machine (Corbett Life Science). Results were obtained using the SDS Software (Perkin Elmer) and evaluated using Excel (Microsoft). Melting-curve analysis was performed to assess the specificity of PCR products. Relative expression was calculated using the comparative threshold cycle (Ct) method, normalized on a control group.
Statistics Following normality tests (Kolmogorov-Smirnov and Shapiro-Wilk), data were analyzed with a Mann-Whitney test (two-tailed unpaired) to compare two independent groups using GraphPad 5. 01 software. A probability (p) value of < 0. 05 was considered significant. *p < 0. 05, **p < 0. 01, ***p < 0. 001.
S8B ). Of note, these genes are connected in a network (predicted by IPA) in which SYK/AKT fill a central position (Supplementary Fig. S14 ). Although IL-1β repression by type I IFN has been previously described  [30]  and attributed to signaling through the IL-10 / STAT3 pathway  [31] , our dataset does not clearly point to such connection. Rather, reduced Tlr6 expression and downstream NF-κB signaling is supported by the genes network built by IPA to account for diminished Il-1b expression. Altogether, our data suggest that the therapeutic properties of imiquimod in our experimental setting are mediated by the ability of this compound to impair two major hallmarks of inflammation: neutrophil recruitment and/or activation and IL-1β production. Because our data point to a possible involvement or TLR-dependent signaling (possibly TLR1, 2 and 6) in our model of experimental acute gout, we tested the impact of MSU injection in MyD88-and Il-1R1-deficient animals.
Signaling pathways supporting anti-inflammatory effects of type I IFNs The anti-inflammatory effects of type I interferons are a matter of controversy, but can be supported by at least two lines of evidence: (i) sustained type I IFN production in chronic viral infections induces immunosuppression  [41] , as demonstrated in the LCMV model  [42, 43]. (ii) IFNβ is an effective treatment against inflammation of the central nervous system in multiple sclerosis  [44]. However, precise mechanisms underlying these immunomodulatory effects are still poorly understood. Using an alum-induced peritonitis model, the induction of the IL-10/STAT3 axis in response to type I IFN and LPS signaling was proposed as a predominant event to explain subsequent immunosuppression  [31]. In our dataset of imiquimod-modulated genes, several STAT3 targets (e.
Their activation by MSU crystals binding to the plasma membrane  [46]  thus appears as an important contributor to neutrophil recruitment and activation, which could be impaired by already existing inhibitors developed for other pathologies, such as leukemia. Furthermore, RNAseq analysis using the ImmQuant software predicts that skin dendritic cells might be important mediators of the imiquimod-dependent anti-inflammatory response. The functional connection linking these cells and reduced neutrophil infiltrate will be a major research focus of ours. In conclusion, our in vivo model in mice uncovers an unsuspected complexity of the pathogenesis of gout triggered by urate crystals, as illustrated by its independence from the NLRP3 inflammasome. In addition, novel insights emerge from RNAseq analyses, such as the possible role of TLR1, 2 and/or 6 as sensors priming the NK-κB pathway.
Acknowledgements Work in our laboratory is supported by grants from the  Agence Nationale de la Recherche (ANR)  ( ANR-11-LABX-0070_TRANSPLANTEX ), the  INSERM  ( UMR_S 1109 ), the  Institut Universitaire de France (IUF) , the  University of Strasbourg (IDEX UNISTRA) , the  European regional development fund (European Union )  INTERREG V program  (project n°3. 2 TRIDIAG) and  MSD-Avenir  grant AUTOGEN. The input and advices from  Roméo Ricci  and  Zhirong Zhang  ( IGBMC, Illkirch, France ) at the initial step of this work is greatly acknowledged. PG thanks  Dr. Stephan Blüml  ( Vienna Medical University, Austria ) for helpful discussions and  Dr. Philippe Bouillet  ( WEHI, Melbourne, Australia ) for critical reading of the manuscript.
Genetic effects on brucellosis infection. Out of the 237 ibex from the Bargy massif that were first tested, 89 were found seropositive to brucellosis (37%). The probability to be seropositive was lower in males than in females and reached a maximum in the core area of the massif (SSU3, SSU4) (see Tables  S4, S5 , Figs. 1, 2 ). We observed a slight temporal decrease of the seroprevalence over the monitoring period (only significant for the dataset covering the whole 2012-2017 study period). Brucellosis seropositivity also tended to increase with age but 95% confidence intervals of the effect size did not exclude zero (Average Effect Size = 0. 41 [95% CI: -0. 13,0. 95]) (Fig. 1 , Table  S4 ). We did not find any significant effect of the multi-locus heterozygosity (MLH) on the individual serological status (general effect) (Fig.
Polymorphism in microsatellites of the 3′ UTR of the gene were associated with resistance to Brucella infection in water buffalo Bubalus bubalis  36  and in the domestic goat  31  , a species closely related to the Alpine ibex. In particular, some SLC11A1 genotypes have a higher ability of controlling the intracellular replication of Brucella in vitro  60. We also genotyped Mhc-Drb and Tlr genes for a subset of the individuals (N = 146) sampled between 2012 and 2014. The second exon of the Mhc-Drb class II gene encoding the ligand-binding domain of the protein was amplified and sequenced using Illumina MiSeq system following the procedure detailed in Quéméré et al. 17. Haplotypes and individual genotypes were identified using the SESAME barcode software  72. Tlr genes (Tlr1, Tlr2 and Tlr4) were genotyped using the two-step procedure described in Quéméré et al.
17. A pilot study on 30 individuals was first performed to identify polymorphic sites (SNPs). We screened almost the entire coding region of the three Tlr genes (92% in average) including the leucine-rich extracellular region of receptors involved in antigen-binding. Details on primer sequences and accession numbers are provided in Table  S2. SNPs were then genotyped for 146 individuals using the KASPar allele-specific genotyping system provided by KBiosciences (Hoddesdon, UK). Details on SNP position and codon change can be found in Table  S3. Haplotypes were then reconstructed from the phased SNPs using the procedure implemented in DNASP v5  73.
Genetic diversity. The genetic diversity of both microsatellites and immunity-related genes was evaluated by calculating the expected heterozygosity (H E ) and the number of alleles/haplotypes (N A ) as implemented in GENETIX software v4. 05. 2  74. For each locus, a test for Hardy-Weinberg proportions was performed based on 1000 permutations. To allow comparison with other ibex populations  42  and between the two monitoring periods (before and after culling operations), we used FSTAT version 2. 9. 3  75  to calculate the allelic richness (sNA), a standardized measure of number of alleles corrected for differences in samples size. Lastly, standardized multi-locus heterozygosity at neutral microsatellites (MLH) was calculated for each individual as the ratio of its heterozygosity to the mean heterozygosity of the population  76.
The most complete models used in the inference included the effects of genetic effects hypotheses, age sex, year and location. We compared the maximal model with all its sub-models (See Tables S6 and S7 for the full lists of model tested). The effect of Slc11A1 and Tlr genes were evaluated in separate analyses because of different samples sizes (262 and 146 individuals respectively). We conducted an initial exploration of our data to ascertain their distribution and spread, to identify outliers and examine relationships between variables  81. We used variance inflation factors (VIF) to assess which explanatory variables were collinear, and should be retained in the analyses (i. e. VIF values <3)  81. To minimize multicollinearity, the effects of the most frequent haplotype of a gene and its heterozygosity status were evaluated in separate models.
Model averaged parameter estimates are provided with their unconditional standard errors (SE) and 95% confidence intervals, after averaging model with ΔAIC < 7 (relative to the best model) as recommended by Burnham et al. 79  and using the "zero method" (i. e. a zero is substituted into models where the parameter is absent). Analyses were performed using the package lme4 82 , MUMIN v1. 7. 7  83  and AICcmodavg v1. 25  84  in R version 3. 3. 3 (R Development Core Team, 2017).
Acknowledgements The authors would like to thank  Carole Toïgo , the field technicians and researchers from the  French Hunting and Wildlife Agency  ( Office National de la Chasse et de la Faune Sauvage, now Office Français de la Biodiversité ) who performed ibex captures, monitoring and sampling. We also thank the local veterinary services, the local veterinarians and the  Préfecture of Haute Savoie  who supported the field work and the departmental laboratory staff that performed blood DNA extractions. Data used in this work were partly produced through the genotyping and sequencing facilities of  ISEM (Institut des Sciences de l'Evolution-Montpellier ) and  LabEx Centre Méditerranéen Environnement et Biodiversité. Thanks also go to  Lukas Keller  and  Alice Brambilla  for helpful suggestions and comments.
PATIENTS AND METHODS This retrospective study was conducted from January 2011 to December 2017 in a tertiary care institution (Henri Mondor University Hospital, Créteil, France). Patients were enrolled if they matched two databases, both extracted from the logs of the microbiology laboratory. The first database included patients who had at least one respiratory sample [sputum, tracheal aspirate, protected sample brush, bronchoalveolar lavage (BAL)] yielding positive Aspergillus spp. culture during the study period. The second included patients with Mycobacterium spp. detected in at least one respiratory sample. Patients who had Aspergillusand Mycobacterium-positive cultures separated by more than a 3-month period were excluded to strictly focus on co-isolation cases. When non-tuberculous mycobacterium (NTM) was isolated, cases were classified as colonization or infection according to American Thoracic Society (ATS)/ Infectious Diseases Society of America (IDSA) criteria  (Griffith et al.
Positive serology comprises an ELISA titer >10 IU/mL and a precipitin test with ≥2 precipitin lines according to the manufacturer instructions. Standard bacterial cultures from respiratory specimens were also collected in the same 3-month period. Clinical and microbiological characteristics of the population were reported in percentage, mean and standard deviation (SD) as appropriate. Clinical and microbiological characteristics of patients with and without concomitant Aspergillus spp. /Mycobacterium spp. colonization were compared using Pearson chi-square or Fisher test for qualitative variables and Student's t-test or Wilcoxon-Mann-Whitney for quantitative variables as appropriate. The data were analyzed using Prism 6. 0 software. The authors testify that all procedures contributing to this work are in compliance with the ethical standards of the Helsinki Declaration of 1975, as revised in 2008.
Results The dataset was composed of the last three trials of the conditioning and contained five phases: before the stimulus was broadcasted (initial phase -1 of trials 10 to 12: 10 to 30 s), while the stimulus was broadcasted (anticipation phase 0 of trials 10 to 12: 20 s), after the signal had stopped and when the entrance of the partner was delayed, for testing the discrepancies from expectations (delayed phases 1, 2, 3 of 12th and last trial: 30 s each). Behavioural and acoustic parameters were used to build scores using multivariate analyses carried out in two steps. A linear discriminant analysis was first computed on a subset of data containing the first two phases of trials (i. e. , before phase -1 and during phase 0 the stimulus). The remaining data set (containing the last three phases of the 12th trial: after the stimulus, when the partner was delayed) was compared using two behavioural scores (LD1bev.
The delay of 90 s was long enough to make the arrival unpredictable and mimic a long absence of the expected reward, considering the duration of a normal trial. If piglets learned the two-way associative paradigm, this last test would lead to a discrepancy from their expectation and allow us to track changes in emotional states  26. In order to study each phase using a similar timing and to study the changes in activity, we divided the delayed period into three 30 s phases (named phases 1, 2 and 3). We choose 30 s as it was the maximum duration of the randomly set initial phase (Phase -1). Behavioural measures. Behaviours were monitored using a camera (Bosh, Box 960H-CDD) and annotated using The Observer XT 14. 0 (Noldus, The Netherlands) software. The square room was split into 16 equallydimensioned zones to assess the mobility and exploratory behaviour of the piglet.
Acoustic measures of grunts. A spectro-temporal analysis was performed with custom-written codes using the Seewave R package  30  implemented in R  31. We first studied the spectral properties of the remaining background noise of the experimental room (electric noises and remaining low frequency noises from the rest of the building), using 20 examples of 0. 5 s fragments. Since the first quartile (Q25) of the normalized spectrum of the A speaker was located in the centre of the room 1 m above the ground and broadcast a 2 s audio stimulus associated with the upcoming partner. Blue or white light around the partner's door were used as visual stimulus and announced the entrance of the partner. When the human entered the room, they would place a bucket on the floor and sit on it for two minutes, giving additional care to the tested piglet.
Statistical analyses. Behavioural and acoustic scores. To assess changes in global behavioural and acoustic responses during the anticipation phase, parameters were used to build scores using multivariate analyses carried out in two steps. First, a linear discriminant analysis was computed on a subset of data containing the first two phases of the test, maximizing differences between groups of an ad hoc factor 'phase*treatment*partner'. Two behavioural scores (LD1bev. and LD2bev. ) and one spectral acoustic score (LD1ac. ) were built. On the remaining dataset (trial 12: phases 1, 2, 3 for which the entrance of the partner was delayed), a projection was computed using LDs scores, allowing analysis of the differences in behavioral/acoustic space(s). Statistical tests and validation. We tested for differences in LDs scores since the purpose of using a delayed entrance of the partner was to know whether the piglets would keep the same state that they had during anticipation, return to the state they had in the initial phase or exhibit an intermediate response.
The following two-way interactions were tested: 'partner' and 'treatment' , 'replicate' and 'partner' , 'replicate' and 'treatment'. To test for biases in the piglet's location in the room prior to the playback of any stimulus (phase -1), the time spent near to the upcoming partner's door (parameter loading the most on the LDs), was used as response variable and trials were grouped in a three-level factor: 'beginning: trials 2-4' , 'middle: trials 6-8' and 'end: trials 10-12'. The model tested the three-way interaction between 'trial' , 'partner' and 'treatment' and two-way interactions between 'replicate' and 'partner' or 'treatment'. All linear models were validated by visual inspection of the symmetrical and normal distribution of the residuals ('plotresid' in 'RVAideMemoire' R package  32  ).