dataesr/scientific-paragraphs-categorization huggingface dataset:
All the genes involved in lipid A biosynthesis are also present in B13-0095 genome, however region 2 contains an additional fragment of 6. 5 kb encoding hypothetical or phage proteins. Finally, PATRIC identified several other genes putatively related to LPS in B13-0095 genome, all of them being present in all the Brucella analyzed in this study. Among them, lptA, lptB, and lptC are predicted to encode proteins involved in LPS export to the outer membrane. The Lpt system is encoded by 7 genes in E. coli  (Sperandeo et al. , 2009) ; search for orthologs identified the genes encoding the 4 remaining proteins, which are conserved across Brucella.
, 2014). The B. suis ∆virB8 mutant provides a control showing that both cell lines are able to control infection by attenuated strains. Thus, the elevated rate of replication of the frog isolate cannot be attributed to a reduced fitness of these cells. Low magnification observation of cells infected with fluorescent bacteria at 24 hpi suggested that, with B13-0095, there were more cells infected and that infected cells contained more bacteria (data not shown). This was confirmed using a flow cytometry analysis in which the level of infection is given by the % of fluorescent cells and the rate of intracellular replication is given by the median fluorescence intensity (MFI) of infected cells. We observed that B13-0095 infects more HeLa cells than B. suis and replicates much faster within infected cells (Figure  7 ).
cannot be excluded. Matrix assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometry (MS) is rapidly becoming the method of choice for bacterial identification in clinical laboratories. It allows a fast identification of bacteria and yeast, but its accuracy largely depends on the coverage of the database. With regard to Brucella, accurate identification by MALDI-TOF MS is currently limited because this genus is either not represented in the databases of the two main manufacturers, or only in a bioterrorism database with restricted availability  (Cunningham and Patela, 2013). Using a safe inactivation protocol developed recently  (Mesureur et al. , 2016) , we constructed an exhaustive MALDI-TOF MS Brucella database that can identify all Brucella spp. , in most cases at the species level (J.
Mesureur and A. Keriel, unpublished data). This database allowed us to clearly discriminate the frog isolates B13-0095 from O. anthropi and identified it as B. inopinata (this data will be presented in a separate publication). Another possibility would be to exploit the absence of some genes (shown in red in Figure  2  and Table  S3 ) from Ochrobactrum spp. genomes to discriminate between atypical Brucella and O. anthropi using PCR. Isolation of Brucella spp. from frogs from Africa, Australia and America suggests that they may be widespread and highlight a need for a broader assessment of the presence of Brucella in amphibians worldwide. Thus, not only better identification tools are required, but prevention measures should also be taken. Whilst the zoonotic potential of this group is not known yet, their close proximity with strains associated with human disease suggests that they might present a risk to the animals' keepers and thus, unnecessary contact with potentially infected amphibians should be avoided.
Assigned methods and procedures Viral infection Mice will be identified by ear punch or tail tatoo/marking. For infection, the mouse will first be lightly anesthetized in an isoflurane chamber with 1 L O 2 : 3% isoflurane. A drop of the specified volume (50-100 uL) of IFV (10-2 Â 10 6 TCID 50 ) will be pipetted into the animal's nostril, allowing the drop to be inhaled. The process may be repeated using the other nostril (usually six drops: three per nostril ¼ one dose). Bio Medic Data Systems (BMDS) IPTT300 microchips will be implanted by subcutaneous (SQ) injection to aid in identification and body temperature monitoring, and a drop of tissue adhesive at the trochar injection site will be applied.
Animals Adult CKD and healthy cats were included, regardless of breed and sex. In all cats, physical examination, complete blood count (CBC), serum biochemistry (BC), including total thyroxine (TT4) measurement in cats older than 6 years, and urinalysis were performed to assess the general health status. Diagnosis of CKD was made prior to inclusion. Cats were diagnosed with CKD based on the presence of compatible clinical and laboratory findings (i. e. renal azotemia (sCr and urea exceeding the RI we established in a previous study  7  i. e. (0. 73-1. 83 mg/dL; 64. 5-161. 8 lmol/L) for sCr and (17. 4-35. 6 mg/dL; 6. 2-12. 7 mmol/L) for serum urea) and urine specific gravity (USG) <1. 035). Cats with CKD were classified into four stages according to the IRIS guidelines. 27 Cats with borderline sCr, but abnormal renal ultrasonographic findings at time of inclusion, with available follow-up data confirming CKD, were also included.
Assays Serum CysC and uCysC were analyzed with PENIA j using the nephelometer, k previously validated for cats,  22  and with PETIAl l using the Cobas auto-analyzer. m The validation report of the PETIA for CysC measurement in cats has been added as Data S1. Urinary CysC was expressed as a ratio to the urinary Cr (uCr) concentration, to compensate for differences in urine flow rates. 33 lasma Cr was analyzed with an enzymatic assay n and plasma concentrations of the stereo-isomers endo-and exo-iohexol were determined by high performance liquid chromatography with ultraviolet UV detection, both validated by van Hoek et al. 32  Serum Cr measured in BC b was analyzed with a modified Jaff e assay, validated at a veterinary commercial laboratory. o.
Pharmacokinetics for GFR determination All analyses were performed using WinNonlin. p The data were subjected to noncompartmental analysis, as described by Watson et al. 34  The area under the plasma concentration versus time curve (AUC) was calculated using the trapezoidal rule with extrapolation to infinity. The ratio of endo-and exo-iohexol was determined per batch of iohexol and the administered dose of each stereoisomer was calculated. The plasma clearance of Cr, endo-and exo-iohexol was determined by dividing the dose administered by AUC and indexed to bodyweight (mL/min/kg).
In contrast, a higher specificity was present, which means that if sCysC is increased in cats, CKD is definitely present. The findings of the present study do not encourage the clinical use of CysC measurement in cats. However, suboptimal CysC determination in cats cannot be completely ruled out. We obtained a signal with the PETIA and PENIA, but we cannot exclude that measurement of CysC in cats by human assays is suboptimal. Western blot analysis with antibodies from the  PENIA  22  could not demonstrate good cross-reactivity at 13 kDa, in contrast with the antibodies from the PETIA (Data S1). For both assays, bands at 26 and 52 kDa were visible. In humans, it has been shown that denaturing agents or high temperature can cause di-and polymerization of CysC. 48 It is unknown whether this occurs in dogs and cats.
Acknowledgments For this work support was received from the institute for the promotion of innovation by science and technology in Flanders (IWT) through a bursary to L. F. E. Ghys. The authors thank MedVet,  AML Veterinary Medicine , for the analyses of the samples. The authors also thank  Ms. Bieke Weyn ,  Mrs. Saar Muylaert ,  Mrs. Elke Lecocq ,  Mrs. Kristel Demeyere ,  Mrs. Siegrid De Baere , and  Ms. Jelle Lambrecht  for their technical assistance. This article received support from the  Institute for the Promotion of Innovation by Science and Technology in Flanders (IWT)  (grant number:  11070 ).
Construction and purification of HpMutS2 and variants The cloning of the wild-type hpmutS2, hpmutS2ΔSmr, and HpSmr from H. pylori strain 26695 was performed as described in  [7]. Briefly the wild-type HpMutS2 was cloned in pET28b expression vector under control of IPTG inducible promoter with C-terminal His 6 tag. Nucleotide binding Walker-A and hydrolysis Walker-B motifs were identified by multiple sequence alignment using Clustal Omega (http://www. ebi. ac. uk/Tools/msa/ clustalo/). The MutS2 sequences from different bacteria were obtained from the NCBI protein database. To generate point mutations in these motifs, QuikChange II Site directed mutagenesis kit (Agilent technologies) was used. Primers and PCR reaction were designed according to the manufacturer's recommendation. Fallowing pairs of primer were used for mutagenesis (5′-3′): HpMutS2-G338R, Forward: GGCGTGAATGCGGGCC GTAAAACCATGCTC, Reverse: GAGCATGGTTTTACGGCCCGCATTCACG CC HpMutS2-E413A, Forward: CTTTTAGGCGTTGATG CGATCGAGCTAGGGACTGACGC Reverse: GCGTCAGTCCCTAGCTCGATCGCATCAA CGCCTAAAAGC A slightly modified version of purification protocol described previously  [7]  was used to optimize the yield and stability of proteins.
Electrophoretic mobility shift assay (EMSA) Radiolabeled DNA substrates (0. 16 nM) were incubated with increasing concentrations of HpMutS2 and mutants in buffer A with 1X BSA (0. 1 μg/μl). ATP, ADP, and ATPγS (1 mM each) were added separately to the reaction mixture. The NaCl concentration was maintained to 110 mM by adding storage buffer C to the reaction mixture. After incubation of 30 min on ice, the reaction mixtures were electrophoresed on native PAGE (8 %) at 4 °C. The gels were transferred on to Whatman 3 mm paper and dried under vacuum at 80 °C for 45 min. The gels were visualized by phosphorimaging and quantified using Image Gauge (Version 3. 0). The dissociation constants were determined by non-linear regression analysis and calculated by plotting the percentage of bound DNA versus concentration of protein using "One site -Specific binding with Hill slope" equation of the Graph-Pad Prism 5 software.
Funding This work was supported by  Council of Scientific and Industrial Research (CSIR), India  (grant number  37 (1502)/11/EMR-II ), the  Agence Nationale pour la Recherche  (grant number  ANR-09-BLAN-0271-01 ), the  INSERM  and the  Indo-French Centre for Promotion of Advanced Research (CEFIPRA)  (grant number  5203-5 ). DNR acknowledges DST for J. C. Bose Fellowship. Prashant P. Damke is supported by  IISc  fellowship. Research stay of Prashant P. Damke at  CEA, Institute of Cellular  and  Molecular Radiobiology ,  Fontenay aux Roses , France was jointly supported by  CEA  and  IISc. Rajkumar Dhanaraju  was supported by a  Senior Research Fellowship in the CSIR research grant.
The control values of the Abnova EIAs were within the reported range. Intra-assay and inter-assay coefficients of variation for epinephrine were 5. 18% and 4. 79% and for norepinephrine were 4. 80% and 2. 37% respectively. Serum cortisol, epinephrine and norepinephrine values are expressed as ng/mL. The absorbance values of all enzyme-immunoassays were determined using an Epoch microplate reader and Gen5 software (Biotek) (BioTek, Winooski, VT, USA). A test and reference filter of 405 and 540 was used for the cortisol EIA and 450 and 630 for the epinephrine and norepinephrine EIAs.
Behavioral Analysis Calf behavior was recorded continuously in real time by video camera (Kobi CCD Video Camera, Model K-32HCVF, Ashmore, Queensland, Australia) during exposure to each activity. A digital video recorder (Kobi H. 266, Model XQ-L 900H, Ashmore, Queensland, Australia) was used to record the images, and the video data were then analysed using a continuous recording of each animal and Cowlog 2. 0 behavior software (Research Centre for Animal Welfare, University of Helsinki, Helsinki, Finland) for coding of behaviors  [34]. Exit times from the chute were recorded for calves in each group. The duration of time spent by NM calves in the following mutually exclusive states was continuously recorded: running, trotting and walking, together with distance travelled. Similarly, the duration of time spent by ER calves was continuously recorded for behaviors in the ethogram developed for this activity, except that eye roll and vocalizations were noted as one:zero occurrences on the day (Table  1 ).
Statistical Analysis Behavior and endocrinological parameters were analysed using a general linear model with the following factors: treatment group, calf, replicate and before/after treatment, together with the respective two-way interactions between these factors, using the statistical package Minitab 16 (Minitab Inc. , State College, PA, USA). During analyses, all data were checked for normal distribution of residuals using the Anderson-Darling test. For data not satisfying the Anderson-Darling test, log 10 transformations were made and back-transformed means are reported in addition to transformed data. The log 10 parameters produced a normal distribution of residuals.
Acknowledgments: The authors thank  Mandy Paterson  for initiation of the research,  Glen Mansfield  (former Australian Professional Rodeo Association Executive Director and Chairman of the  Board ) for support of the project and  Australian Champion Rodeo Cowboys ,  Shane Iker  and  Shane Kenny , for undertaking the roping, and the latter also for use of the farm and engagement of suitable animals. Thanks also to  Jo Smith  for veterinary assistance in sampling, and to  Sarah Zito  for editing assistance. This research was funded by the  Australian Professional Rodeo Association (APRA).
Results Three hundred and forty horses were included in the study. The demographic characteristics of the study population are summarised in Table  1. Given that the field conditions limited the available time per horse, the number of missing data varied from one measurement to another. The numbers of available data per measurement are given in Additional files 1, 2, 3 and 4. Most horses were females or geldings, and intact males were significantly underrepresented (Chi 2 p < 0. 01). Furthermore, most of the horses were purebred or part-bred Arabians, whereas Anglo-Arabians and Others were significantly underrepresented (Chi 2 p = 0. 03). There were slightly more horses in Group 6y than in the two other groups. The measured HR was slightly higher than the usual resting HR for horses, and no arrhythmias were observed on the reviewed cine-loops.
Discussion The present study reports changes in echocardiographic dimensions of the heart in young Arabian type horses at the end of their growth period and at the beginning of their endurance training for competitions. All external variables included in the analyses influenced to some extent several of the measured dimensions. Morphometric dimensions, age and breed showed most consistently an influence on LA measurements, whereas BWT, breed and Km-career had most consistently an influence on LV measurements. All the horses in the study population had at least one purebred Arabian parent. Our study population was chosen to be representative of the horses participating in endurance competitions. This choice was in accordance with literature data indicating that purebred or mixedbreed Arabians are largely overrepresented in endurance competitions, although some other breeds do participate  [29, 30].
Furthermore, some horses were bred during this period, which decreased the training period. Therefore, it was not possible to analyse objective parameters, such as gains, speed at kilometre, or numbers of start  [4, 5, 13, 14]. The most accessible parameters were Km-career and d-career, since this information was freely available in the FEE database. We hypothesised that a horse having participated in a greater number of competitions or longer competitions would have been trained harder. Even though we observed a weak relationship between Km-career and some LV measurements, better performance indicators are clearly needed. Long-term information on the endurance horses' competitive performance was not yet available at the time of the present study and will be addressed in the future. Lastly, we had no possibility to record and therefore to compare echocardiographic measurements taken before and after exercise.
, 2013 Judson et al. , 2014 Judson et al. , 2015)). The National Library of Medicine databases, Tox21 (Toxicity Testing in the 21st Century), and ToxCast™ (Toxicity ForeCaster) are among the efforts to compile, organize, manage, and store these data to better understand determinants of population health (U. S. EPA 2016;  Krewski et al. 2014; NRC 2009)  and to help answer such questions as: Which chemicals are environmentally better choices in commerce? Why do individuals and specific subpopulations respond differently to chemical exposures? What happens when people are exposed to low levels of multiple chemicals? How do factors like socioeconomic volume 124 | number 11 | November 2016 • Environmental Health Perspectives status and pre-existing illness influence public health risk? How might evaluating and applying these data, methods, and models support environmental health decisions? A revolution in molecular, computational, and systems biology has occurred over the past 25 years, providing dramatic insights into the causation of disease.
We evaluated transcriptomic and epigenomic data (epidemiological and clinical) in the range of environmental exposures for three chemicals: a) benzene and other leukemogens  (McHale et al. 2011 (McHale et al. , 2012;; Smith et al. 2011; Thomas R et al. 2012 Thomas R et al. , 2013 Thomas R et al. , 2014)) ; b) ozone  (Duncan et al. 2012; U. S. EPA 2013a; Hatch et al. 2014; McCullough et al. 2014 McCullough et al. , 2016)) ; and c) polycyclic aromatic hydrocarbons (PAHs), including tobacco smoke and benzo  [a]  proteomic, and epigenomic data as available, and molecular animal and in vitro data for benzene and B[a]P (U. S. EPA 2013b;  French et al. 2015). We evaluated exposures for benzene of < 0. 1 to 10 parts per million (ppm) and ozone of 0. 5 ppm for 2 hr. We used individual measures of the exposure-dose relationship for benzene and ozone (benzene urinary metabolites  (Vermeulen et al.
2004 ) and heavy oxygen-labeled ozone ( 18 O 3 )  (Hatch et al. 2014). For PAH exposures, we used self-reported smoking. The PAH-tobacco smoke prototype focused on pathway mining of existing human microarray data from the ArrayExpress (http://www. ebi. ac. uk/) and Gene Expression Omnibus (http://www. ncbi. nlm. nih. gov/geo/). The toxicogenomics data were compared qualitatively and quantitatively to known health outcomes associated with these chemicals, specifically hematotoxicity and leukemia (benzene and other known leukemogens), lung inflammation and injury (ozone), and lung cancer (PAHs). The results of these data-rich comparisons therefore enabled us to draw on a wealth of chemical-and disease-specific data to help characterize associations among upstream molecular changes, downstream cellular events, and public health outcomes.
g. , NIH NCBI PubChem, BioSystems; Biotechnology Information (NCBI) NHANES; European ArrayExpress databases, such as BioSystems, (http://www. ebi. ac. uk/)] Gene Expression Omnibus, Pubchem (http://www. ncbi. nlm. nih. gov/ gquery/?term=NCBI) New data types QSAR, HT in vitro screening assays, read- High-content assays, medium-throughput Molecular epidemiology, clinical (Also uses the data from column to left) across, AOP development assays, knowledge-mined large data sets, and animal studies, AOP network AOP development development Exposure paradigms of studies In vitro, in silico All relevant All relevant considered Metabolism in test systems Some to none Partial to intact Intact Incorporation of toxicokinetics Reverse toxicokinetic models Reverse toxicokinetics models, biomonitoring Dosimetry and PK modeling, biomonitoring Consideration of human variability and In vitro methods available In vitro and in vivo methods available In vivo methods available susceptibility Use of traditional in vivo data In vitro assays anchored to pesticide None to limited; especially can be used in New data types augment traditional; registration and pharmaceutical data AOP development traditional data currently remain basis for assessment Hazards Nonspecific Nonspecific to identified Identified Potency metrics Relative rankings based on QSAR or HT Relative rankings and toxicity values Risk distributions, cumulative & toxicity values community risks Likely strength of evidence linking Suggestive to likely Suggestive to likely Suggestive to known exposure to effect Numbers of chemicals that can be 10,000s 100s-1,000s 100s assessed Time to conduct assessment Hours-days Hours-weeks Days-years Note: ACToR, Aggregated Computational Toxicology Resource (U.
Herd selection This study was performed in four EU countries with a medium to highly intensive pig production  [21] ; Belgium, France, Germany and Sweden. Per country the aim was to include 60 farrow-to-finish herds with ≥ 100 sows and ≥ 500 finishers. For Belgium an email list of pig farmers who subscribed to a newsletter issued by the faculty of veterinary medicine of Ghent University was used to select the herds based on willingness to participate. Only the Dutch speaking part of Belgium, Flanders, which represents 90 % of pig production in Belgium  [22] , was included in the study due to logistic reasons. Herds in the north-western part of France, representing 75 % of the country's pig production, were randomly selected from a database of the Institute for pig and pork industry. In Germany the herds were selected from consultancy circles and with veterinarians' input in the three regions with the largest pig production, Niedersachsen, Nordrhein-Westfalen and Mecklenburg-Vorpommern (64 % of total German production)  [23].
Data collection Technical parameters (e. g. number of weaned piglets per sow per year (WSY)) and herd management characteristics (e. g. farrowing rhythm) were collected, together with information on the biosecurity status of the herd using the risk-based scoring system Biocheck. UGent™ (www. Biocheck. UGent. be). The technical parameters were collected from the herd management system if available or by interviewing the farmer. The farrowing rhythm refers to the interval, expressed in weeks, between the birth of two batches of piglets. In this study this ranged between a 1-week system and a 5-week system for Belgium, France and Germany, while in Sweden systems with a farrowing rhythm of over 5-weeks were also used. The latter were coded for analysis as >5-week systems. The number of weaned piglets per sow per year was calculated as the number of litters per year times the number of liveborn piglets per sow minus the mortality until weaning.
If the animal category in which the product was used was not explicitly mentioned on the invoice, the farmer was asked to provide more information. Herd level antimicrobial usage data were used to calculate the "treatment incidence" (TI) per herd and age category by the formula described below and as described and used before in several publications  [1, 20, 27, 28]. The TI is a technical unit of measurement that quantifies how many animals out of a theoretical group of 1000 animals received daily an AM treatment. Or, if one animal would live for a theoretical period of 1000 days, how many of these days it would have been treated with an antimicrobial. Divided by 10 this gives the percentage of the lifespan an average animal on this herd was treated with a daily dose of antimicrobials. Combined TI's were calculated for sows, gilts and boars (TI Breeding) and over a standardized period at risk of 200 days for the lifespan of a pig from birth until slaughter (TI 200).
Data processing A LOG transformation of the data for the number of sows as an outcome variable (data not shown) in the regression models was needed to correct for the right skewedness of this variable. Outcomes for TI 200 and TI breeding were also LOG transformed using SPSS statistics 22 (IBM), after adding one to the original outcome to adjust for zero values in the data. Biocheck. UGent™ is a webbased scoring system using Limesurvey.