dataesr/scientific-paragraphs-categorization huggingface dataset:
The investigators' awareness of new research published after the cut-off date for inclusion is not a valid reason for conducting a new search. Finally, after identifying the studies to be included, the studies' citations should be evaluated to ascertain if there are any additional relevant records or sources of data that should be included as evidence. Any additional identified studies are then evaluated as below using the same inclusion and exclusion criteria. Step 3B: The screening process To determine their relevance and eligibility for inclusion or exclusion, articles are independently screened, typically by at least two investigators. There are multiple software platforms that facilitate a more uniform approach to the screening process including DistillerSR®, Rayyan, or Health Assessment Workspace Collaborative (HAWC).
Step 6B: Integration of evidence: endocrine disrupting activity The main aim of integration at this stage is to qualitatively assess evidence of endocrine disrupting activity. In Step 5, individual streams of evidence were evaluated and assessed with respect to this feature. Again, the overall strength of the evidence achieved from integrating multiple streams of evidence will be at least as high as the highest strength of evidence obtained for any single stream (Fig. 4 ). The same classifiers are used to describe the strength of data in this step as in Step 6A (Table  5 ). Step 7: Conclusions, recommendations, uncertainties and consequences Drawing conclusions: the IPCS/WHO definition of an EDC The IPCS/WHO definition of an EDC requires an integration of: 1) the health outcome; 2) the endocrine activity; and 3) the plausibility of the link between the outcome and endocrine activity.
We anticipate that the completion of Steps 1-6 could take more than a year to conduct if a relatively large dataset is identified; importantly, this could lead to further delays in the already lengthy processes for regulatory decision-making and other public health oriented actions. We also note that some risk assessment groups will need to make concrete decisions about how PECO statements are written and which risk of bias tools are used in evaluation of studies within evidence streams, as this level of consistency is needed to produce harmonized evaluations. In fall 2015, the US National Academy of Sciences convened a panel specifically to evaluate the data in support of "low dose effects" for environmental chemicals including EDCs. (For narrative reviews of the 'low dose' literature, see  [96, 97].
Evaluation methods for in silico models Standardization and curation of the investigated dataset to ensure consistency. This should include a clearly-stated method (including inclusion and exclusion criteria) for curation of the data and a review of the rules applied to chemical structures in order to ensure standardization QSAR models: ▪ Use of sufficiently diverse training set covering the EDC compound domain of interest ▪ Use of sufficiently diverse external test set covering the EDC compound domain of interest should be used ▪ Assembly of internal and external validation, i. e. several internal and external validation sets, and models created in a double loop fashion, followed by consensus predictions Use of sufficiently diverse training set covering the EDC compound mechanism/domain of interest ▪ All training set compounds should, approximately, fit the derived model equally well unless there are demonstrable differences in the binding affinity ▪ Use of sufficiently diverse external test set that covers the EDC compound domain of interest to demonstrate generalizability Protein structure based models: ▪ Several protein structures should be used to account for flexibility of the protein covering relevant conformations ▪ Use of sufficiently diverse training set covering the EDC compound domain of interest ▪ Consensus docking and scoring to ensure robustness and stability of results ▪ Use of sufficiently diverse external test set covering the EDC compound domain of interest.
24-h uric acid excretions Because owners were reluctant to have their dogs catheterized and hospitalized for a 24-h period and some dogs would not eat well in hospital, a modified urine collection procedure was implemented. Owners presented their dog to the veterinarian 24 h prior to their scheduled data collection visit. At that time, the bladder was catheterized using aseptic technique and all urine was removed and discarded. The owners were required to collect all urine the dog voided in a clean container over the next 24 h and immediately add the sample to the refrigerated pooled urine. At 24 (+/-2) hours, the bladder was catheterized and emptied at the VMTH after imaging studies were performed; this urine was added to the pooled samples and the total amount recorded. An aliquot was submitted to the VMTH Clinical Diagnostic Laboratory for uric acid analysis using a colourimetric assay as previously described  [9].
Statistical analyses A linear mixed model (mixed procedure of SAS) was used to assess the influence of visit number (fixed effect in 2, 3, or 4 levels) on the following parameters: appetite, activity, coat scores, body weight, BCS, % lean body mass, % fat mass, plasma amino acid concentration, urine pH, volume, USG, and urinary concentration and urinary excretion of individual purine metabolites. The dog was included as a random term, as each dog was its own control. According to the residual distribution of each model, data were ranked or not. Data that were ranked (rank procedure of SAS) for non-normal distribution included appetite, activity, and coat quality scores, and for these, as well as BCS, medians are reported. Normally distributed data are reported as least square means ± standard errors.
Compliance One owner fed excessive treats (22-25% of energy provided as treats) and used treats not on the recommended list provided. Another owner allowed her dog to consume various other foods including an unknown portion of deer carcass primarily between the 6 and 12 month visits. Data from both of these dogs are included in the analyses. The two dogs that were lost to follow up after the 2 and 6 -month visits, respectively were removed from the study because the primary investigators were unable to contact them despite repeated efforts via phone and email.
Although the rel- evance of the crossbred model has been shown  [4, 5] , its use in applied breeding programs is limited, because pedigree relationships between purebred and crossbred individuals are often not known, and large datasets on crosses are needed  [6]. Genomic approaches offer tools that allow to perform much deeper analyses, and thus, to understand the effects and the mechanisms of the genes and their interactions that underlie complex traits and to explore new directions for their improvement  [7]. In addition, genomic evaluation renews the interest in crossbred individuals because they can be used as training animals  [8]. In the case of additive inheritance, a joint genomic evaluation of purebred and crossbred individuals was proposed  [9]. Toosi et al. [10]  and Zeng et al.
Methods In this section, we illustrate the partition of variance components (additive and dominant) across two pig lines 1 and 2 and the crossbred population. Data for this study were provided by Genus plc (Hendersonville, TN, USA). Animal Care and Use Committee approval was not obtained for this study because the data were obtained from an existing database. Lines 1 and 2 were two unrelated lines, and population 12 consisted of both reciprocal crosses of animals from lines 1 and 2. Data on litter size (total number of piglets born per litter) were analyzed. The average litter size was equal to 12. 68 ± 3. 07, 13. 15 ± 3. 20 and 13. 64 ± 3. 16 for lines 1 and 2 and population 12, respectively. A total of 34,753 records were available for 8265 sows. Genotypes for all sows were generated using the Illumina PorcineSNP60 BeadChip (Illumina, San Diego, CA).
Acknowledgements We are grateful to members of X-GEN, SelDir projects, and  Miguel Toro  for their helpful and constructive comments. This work was financed by the  INRA  SELGEN metaprogram -project  X-GEN and EpiSel  (ZV, AL), as well as  AGL2010-15903  (LV). The project was partly supported by the  Toulouse Midi-Pyrénées Bioinformatics platform.
Model structure The previously published decision model (UK perspective) that we adapted was designed as a simple decision tree over a time horizon of 5 months. 8 In this adapted model, a hypothetical cohort of 1,000 neutropenic patients at risk of IFIs entered the decision tree and were treated using either a DD or an empiric approach (Figure  1 ). Patients treated using a DD approach received antifungal therapy following both clinical suspicion and a positive diagnostic test result suggestive of an IFI. Patients treated using an empiric approach received antifungal therapy following clinical suspicion of an IFI alone. Patients treated using an empiric approach could ultimately have a proven, probable, or no fungal infection. Following initiation of antifungal therapy regardless of approach, patients survived or died based on epidemiological and clinical data obtained from published literature.
Predicted survival following a DD or an empiric approach was the primary clinical outcome of interest. Mortality inputs were obtained from epidemiological and clinical studies due to a lack of data from head-to-head comparative antifungal treatment studies. 9,10 Specifically, overall mortality during the years 2002-2006 was reported as 10. 7% (95% CI: 9%-13%) and IFI-related mortality as 28. 6% (95% CI: 19%-39%) in a population of patients treated with myelosuppressive chemotherapy for hematological malignancies or following autologous stem cell transplantation. 9 A 28. 6% increase in mortality was assumed for patients with IFIs since IFI deaths would only occur in patients with IFIs. Given this assumption, the overall mortality was adjusted to be specific to patients with and without IFIs (Table  1 ).
As we observed, there was considerable heterogeneity in physicians' treatment habits and considerable variability in resource utilization was noted for the four cities evaluated. Second, the clinical data used in the model were obtained from the published literature and supplemented with resource use and cost data obtained from top clinicians located at tier-3A hospitals in the People's Republic of China. These results may not be generalizable to a broader population. However, results from our analysis were consistent with published clinical studies, suggesting that a DD compared to an empiric treatment approach is cost saving for neutropenic fever in the People's Republic of China. Third, the incidence data incorporated into the model were for IFIs, not specifically invasive aspergillosis.
Acknowledgments Interim findings for the Shanghai analyses were presented at the ISPOR 17th Annual European Congress, November 8-12, 2014, in Amsterdam, the  Netherlands , as a poster presentation. The abstract for this presentation is available on http://www. valueinhealthjournal. com/article/S1098-3015(14)04409-X/pdf. Interim findings for the Beijing, Chengdu, and Guangzhou analyses were presented at the 2015 ISPOR Annual International Meeting, May  16-20 , 2015, in Philadelphia, PA, USA, as a poster presentation. The abstract of this poster is available on https://www. rti. org/publications/abstract. cfm?pubid=24212.
On farm data collection In France, a participative study generated detailed on farm knowledge from 'real farm' situations and disseminated best practice. Data were collected on farms using one of three different farming systems: one lambing period per year, pastoral system and accelerated system (three lambing in 2 years) to understand factors associated with lamb mortality (for details see Supplementary Material). Overall mortality was 13. 4%, but varied across farms from 3. 6% to 31. 2%. Lamb mortality followed a similar pattern to experimental studies, with 54% of mortality occurring within the first 2 days of life. However, the farmers in the study felt that they had little or no ability to influence lamb mortality during this period, and had more control over mortality occurring after the first 2 days.
, 2016). Briefly, DNA was removed with TURBO DNA-free (Ambion, Inc. ) and the quality of RNA was assessed using a NanoDrop (ND-1000; Thermo Scientific) and a bleach agarose gel 2% as previously described  (Aranda et al. , 2012). cDNA was prepared using 1 µg of RNA, random hexamer primers (0. 2 µg/µl), and M-MulV-RT (20 U/µl, reverse transcriptase of Moloney Murine leukemia Virus; Thermo Scientific). Specific primers were designed with the Primer3Plus software 1 and are listed in Table  1. The absence of contaminating DNA was controlled by lack of amplification products after 35 qPCR cycles. Control reactions with no template (water) and minus-Reverse Transcriptase were run with all reactions. 16S rRNA (HPrrnA16S) was used as a reference gene for normalization and the relative gene expression was calculated using the 2 -Ct method  (Livak and Schmittgen, 2001).
In silico Identification of TA Modules Analyzed sequence data and loci annotations of 260 H. pylori genomes were retrieved from the NCBI database 2  by a series of custom Perl scripts. In addition, the genomes of 57 Helicobacter non-pylori strains were included in the comparative analysis. We also selected the sequences from known toxin and antitoxin modules that were classified into super-families as stated previously  (Leplae et al. , 2011)  and compared their homology with previously referred Helicobacter genomes. Briefly, each TA protein pair was queried using PSI-BLAST  (Altschul et al. , 1997)  under the following parameters: matrix = BLOSUM62, word size = 3, PSI-BLAST threshold = 0. 005, expect threshold = 10, and without filtering low complexity regions. Hits were carefully examined and selected according to their functional annotation.
However, by comparing the nucleotidic sequences of all H. pylori strains deposited in the GenBank, no stop codon was found in this gene, suggesting a problem of annotation in the strain 26695. To demonstrate that hp0968 antitoxin gene is present and transcribed in 26695 strain, we performed RT-PCR experiments using primers that hybridize with TA genes as shown in Figure  1A. We found that both hp0968 and hp0967 genes were transcriptionally expressed and as expected, they presented a single mRNA similar to other type II TA systems (Figure  1B ). The analyses of the internal controls for hp0316-hp0315, hp0893-hp0892, and hp0895-hp0894 TA genes also showed that they are genetically organized as bicistronic operons (Figure  1B ). We also amplified the coding region of both hp0967 and hp0968 genes of H.
Environmental Cues Differentially Regulate Expression of H. pylori Type II TA Systems In order to elucidate the environmental cues that may affect expression of type II TA systems we performed qRT-PCR experiments. Relative expression was determined during both exponential (24 h) and stationary phase (48 h). Interestingly, expression of all the type II TA genes was higher during stationary phase than in exponential phase (Figure  2A ); although hp0316-hp0315 and hp0968-hp0967 showed the highest transcriptional levels (Figure  2A ), and hp0893-hp0892 and hp0895-hp0894 were poorly expressed in this growth condition. Similarly, expression of cagA and vacA was found increased during stationary growth phase (Figure  2B ), in agreement to previously reported data  (Thompson et al. , 2003; Boonjakuakul et al.
The hp0968-hp0967 Genes Are Highly Prevalent among Helicobacter Strains We performed PCR experiments to identify type II TA genes in a collection of 114 clinical H. pylori isolates. These bacteria were isolated from patients with diverse pathologies, such as non-atrophic gastritis, premalignant lesions, gastric ulcer, and gastric cancer. Whereas hp0968-hp0967 was the most prevalent type II TA system in these isolates (in over 70% of all isolates), hp0895-hp0894 genes were the least prevalent (in less than 50%) (Figure  5A ). In addition, a Blast search in sequences deposited in GenBank 5 using sequences of different TA families (included Vap), revealed the presence of type II TA genes in other H. pylori strains. TA genes of the Vap family were highly prevalent, presenting high identity and constituting a genetic signature inside H.
pylori species (Figure  5B ). In agreement with our findings in the clinical isolates, the hp0968-hp0967 genes presented the highest prevalence as compared to the other type II TA genes (Figures  5A-C ). Interestingly, in both groups of H. pylori clinical and sequenced strains, the hp0968 antitoxin gene was more conserved than hp0967 toxin gene (Figures  5A-C ). Since the number of type II TA systems has been associated to bacterial pathogenicity  (Georgiades and Raoult, 2011; De la Cruz et al. , 2013) , we studied the presence of the type II TA systems 5 http://www. ncbi. nlm. nih. gov/genbank/ of different families in other Helicobacter species, and found that the presence of type II TA genes varied from one species to another. Species phylogenetically related to H. pylori such as H. acinonychis (big cats) and H.
, 2004). Based on the above notions, we suggest that VacA may have a role in bacterium-bacterium interactions, as it occurs during biofilm formation. In terms of prevalence, hp0968-hp0967 system was the most prevalent in both clinical and sequenced H. pylori strains. Moreover, the hp0968-hp0967 system was also widely distributed in all Helicobacter species. It was recently reported the retention of the antitoxin gene but not the toxin gene in TA modules of Xanthomonas genomes  (Martins et al. , 2016). Both clinical and sequenced H. pylori strains revealed the same profile, loss of toxin and retention of antitoxin genes. In H. pylori and non-pylori genomes deposited in GenBank, hp0968 antitoxin gene was much more prevalent than hp0967 toxin. The retention of antitoxin genes in bacterial genomes has been postulated due to the toxinindependent functions of type II antitoxins such as MqsA and DinJ  (Wang and Wood, 2011; Hu et al.
, 2012). The presence and homology of type II TA genes in Helicobacter strains generated two main clusters: H. pylori and other Helicobacter species, showing that these TA systems represent a DNA signature for H. pylori. Moreover, species phylogenetically related to H. pylori such as H. acinonychis and H. cetorum were separated from the rest of Helicobacter species and grouped with H. pylori strains, supporting the concept that TA genes are part of the prokaryotic mobilome and that they are involved in the bacterial evolution  (Koonin and Wolf, 2008). Searching type II TA genes by using Toxin-Antitoxin Data Base (TADB 3 ) we found two TA systems for the H. pylori strains 26695 and J99 (HP0892-HP0893 and HP0894-HP0895). In the case of other Helicobacter species, H. hepaticus was the only species showing one TA system (HH0272-HH0273), which clearly indicates the need for an update and construction of a new database that integrates more bacterial genomes.
ACKNOWLEDGMENTS This study was supported by grant  FIS/IMSS/PROT/G14/1329  (to MC-M) from the  Fondo de Investigación en Salud (FIS)-IMSS , México. We thank  Areli Altamira-Velasco ,  Mariana Chávez-Montaño ,  Diana Márquez-Delfín , and  Mariana Ramírez-Etienne  for technical assistance.
Genome Analysis Whole genome sequencing (WGS) was performed as described recently  (Quance et al. , 2016). Phylogenetic placement was performed using kSNP, a program that can analyze raw, unassembled reads  (Gardner and Hall, 2013)  using the genomes listed in Table  S1. Genome assembly and automatic annotation was performed using the PATRIC resource 1   (Wattam et al. , 2014a). Confirmation of the presence of predicted protein encoding genes in other genomes was performed using BLASTP 2  within the Brucella genus (Taxonomic ID 234) or Brucellaceae.
Flow Cytometry Analysis Cells were infected as above with the exception that mCherryexpressing bacteria were used. At 24 hpi cells were detached with trypsin, fixed, and analyzed by flow cytometry (MACSQuant VYB, Miltenyi). Data were analyzed using the MACSQuantify software. This gave % of infected cells (i. e. , % of mCherry positive cells) as well as the MFI (median fluorescence intensity) of infected cells, which is indicative of the number of bacteria inside cells.
When compared with the API online database (https://apiweb. biomerieux. com), this isolate was identified as O. anthropi with a probability of 99. 9%. However, some results were not consistent with this identification such as the positive adipic acid assimilation, the negative malate assimilation and the absence of nitrate reduction at 48 h. Literature searches were performed at PubMed using various combinations of the search terms of "Ochrobactrum," "Brucella," "frog, " and "amphibian. " No case reports indicating prior isolation of Brucella species from frogs were found so no further efforts to identify the organism were made. Because of the unusual nature of the case, the isolates were stored in 10% glycerol at -80 • C. Several years after the original isolation of the organism, the literature search was repeated and yielded a report of isolation of a potentially novel Brucella species from frogs  (Eisenberg et al.
, 2012)  along with a case report documenting abscesses associated with a B. inopinata-like bacterium in a big-eyed tree frog purchased from a pet store  (Fischer et al. , 2012). The two isolates were thus revived and a recA gene-based multi-primer PCR was performed. Both yielded a 167 bp product, specific to the Brucella genus (data not shown). An attempt was made to characterize the liver isolate (thereafter referred as B13-0095) using traditional Brucella biochemical analysis  (Alton et al. , 1988)  at the National Veterinary Services Laboratories (NVSL, Ames, IA, USA). The isolate did not conform to the characteristics of any recognized Brucella species. The unusual profile included strong urease activity, no requirement for carbon dioxide, no production of hydrogen sulfide, no sensitivity to the dyes thionin or basic fuchsin at 1:25,000, no agglutination with monospecific anti-A and M serum, and no lysis by Tbilisi phage at RTD or RTD × 10 4.
B13-0095 was later analyzed by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry, using a Vitek MS and a database able to identify Brucella isolates at the species level (J. Mesureur and A. Keriel, unpublished data). B13-0095 was clearly discriminated from O. anthropi and was identified as B. inopinata with an identification score ≥99. 99%. B13-0095 has an atypical growth rate for Brucella, as it gives 2-3 mm large colonies within 48 h at 37 • C on blood-agar plates. We quantified its growth rate in liquid broth, compared to B. suis 1330 as a representative of classical Brucella species. B13-0095 reached stationary phase within 5 h of culture, whereas B. suis required at least 24 h to do so (data not shown), confirming that B13-0095 has a very rapid growth in vitro.
Full sequence alignment of the 16S rRNA gene of B13-0095 with sequences of BO1, BO2, the Brucella spp. consensus sequence and O. anthropi showed that B13-0095 shares 100% sequence identity to those of BO1 and BO2, 99. 6% The genes highlighted in gray belong to the ectoine utilization cluster described in Figure  2A. identity with other Brucella spp. and 97. 7% with O. anthropi ATCC 49188. The draft sequence was deposited in NCBI under the accession number SAMN05277611. The FASTQ files were deposited in NCBI Short Read Archive under the bioproject number PRJNA326393. B13-0095 genome was then assembled, resulting in 38 contigs (338 bp to 767 kbp). Automatic annotation using RAST predicted 3326 protein encoding genes (peg), and PATRIC FigFam search identified 20 that seem unique to B13-0095 among the Brucella genus (Table  3 ) and 26 that are conserved within the BO clade, among which 10 are also present in O.