dataesr/scientific-paragraphs-categorization huggingface dataset:
A better growth was observed at 27 °C. The colonies were first blue on the chromogenic medium, and then they produced a yellowbeige pigment, which was also the color observed on the Sabouraud-Chloramphenicol-Agar (Figs. 2  and 3 ). After several days of culture, the colonies looked tan, dry and wrinkled. Microscopic examination of the colonies showed morphological aspects similar to those observed on positive blood cultures. An analysis of the isolate on a Microfilex™ MALDI-TOF mass spectrometer (Bruker, Germany) using the Biotyper Software (Bruker), was performed but was inconclusive as P. aphidis was suggested, but with an insufficient score (between 1. 5 and 1. 6). The APID 32C strip (bioMérieux, France) was also inconclusive. The yeast was urease positive and nitrate positive. Morphological study on Potato-Carrot-Bile medium (Bio-Rad, USA) incubated in a semi anaerobiosis at 27 °C produced more regular elements compatible with the genus Pseudozyma (Fig.
4 ). Final identification was obtained by sequencing (GATC Biotech AG, Germany) of the ITS region followed by GenBank and CBS analysis, giving a 99% and a 99. 7% match to P. aphidis (sequences JQ425372. 1 and DQ778919. 1), respectively. The susceptibility of the isolate was tested by the Etest method (BioMérieux, France) on a RPMI medium, and it showed MIC values of 16 mg/mL for fluconazole, 0. 19 mg/mL for itraconazole, 0. 032 mg/mL for voriconazole, 0. 094 mg/mL for posaconazole, 0. 19 mg/mL for amphotericin B, 432 mg/mL for caspofungin and 432 mg/mL for flucytosine.
Misidentifications as Cryptococcus or Trichosporon species have been described with the VITEK 2 (bioMérieux), The ID32C s (bioMérieux), the RapID Yeast Plus s (Remel) systems  [8, 12]. For our isolate, mass spectrometry analysis suggested P. aphidis but with a low score, which is most likely due to an insufficient number of spectra in the databank, and the API 32C identification algorithm does not include this species in its databank. The risk factors described in all reports of invasive Pseudozyma infection were immunosuppression, neoplastic diseases, impaired mucosal defenses and foreign material, such as a central venous catheter. In our case, the patient had several risk factors: a metastatic adenocarcinoma of the ampulla of Vater, abdominal surgery and a central venous catheter. Her blood count was normal and did not reveal any cytopenia.
All vital parameters remained normal in all horses. None of the horses developed a cough or abnormal mucus secretion. The cytology results of the tracheal washes and bronchoalveolar lavages remained normal in all horses (data not shown). During lower airway endoscopy, we did not observe any local inflammation (reddening, swelling) at the biopsy sites; whereas a fast healing process was detected. On day 8, it was often not possible to identify the biopsy site anymore. Once the EBEC culture conditions had been defined, eight healthy untrained (UT) Standardbred horses (5 mares and 3 geldings, 2. 5 ± 0. 5 years, 450 ± 45 kg) were enrolled for the second part of our study. All horses were determined to be healthy by physical examination, complete blood cell count, serum biochemistry, endoscopic evaluation of the respiratory tract and examination of the tracheal and bronchoalveolar lavage fluid (cytology, bacteriology and virology).
Specificity of PCR was confirmed by melting curve analysis, agarose gel electrophoresis and the absence of signals in RT minus RT reactions. All primers designed for this study were located in single exons except the primer for CXCL8 (2 separate exons). The absence of signals in RT minus RT reactions and the fact that all primers, except for one, were located in single exons confirm the absence of DNA contamination. Real-time quantitative PCR data for TLR1-9, FGF-1, FSP-1, E-cadherin, keratin19, IFN-β, TNF-α, IL-6 and CXCL8 were normalized to the geometric mean of three housekeeping genes (PGK1 (phosphoglycerokinase 1), PPIA (cyclophilin A), RPL0 (ribosomal protein L0)) using qbase + software (Biogazelle, Zwijnaarde, Belgium). Muscle tissue was used as a calibrator for the characterization of TLR mRNA expression in bronchial biopsies and EBEC.
Our data revealed that EBEC are negative for vimentin in comparison with cultures of fibroblasts (Figure  1D ). Fibroblasts strongly expressed mRNA encoding for FGF-1 and FSP-1, whereas these mRNA were expressed about 100-1000 times less in EBEC (Figure  1B ). In contrast, EBEC strongly expressed E-cadherin and keratin19 (Figure  1C ). The EBEC phenotype was further confirmed by TLR mRNA expression, particularly of TLR3 (as discussed in the following paragraph). Figure  2  shows that EBEC have a similar pattern of TLR mRNA expression as the bronchial epithelial biopsy tissue itself. Furthermore, we show that the TLR mRNA expression was neither altered by our culture technique (Figure  2 ) nor by training of the horses (Figure  3B ). Our results indicate that our EBEC cultures had excellent purity, and that their phenotype was maintained during the.
Acknowledgements The authors thank the  University of Liege , the  GIGA , the  Pasteur Institute in Lille , the  ANSES laboratory in Goustranville ,  Raja Fares ,  Ilham Sbai  and  Jean-Clement Bustin  for their support during the study. We also acknowledge  Frederic Farnir  at the  University of Liege  for his help with the statistical analysis.
Literature Search and Paper Filtering Criteria A detailed search of studies from 1970 to 2013 was carried out in the ISI Web of Science and PubMed through key word searches and cited references of other published papers. Keywords and search strings included terms related to robustness (robustness, tolerance, and resistance), heat stress (heat stress, high ambient temperature, high environmental temperature, etc. ), laying hens (laying hen, layer, chicken or poultry), genotype by environment interaction (genotype by environment interaction or genotype-environment interaction), and egg production (egg production, egg quality, laying rate or performance). The numerous papers obtained by this search were then filtered before inclusion in the database. Papers were not eligible for inclusion if: 1) they studied other poultry species like quail or meat-type genotypes such as broiler breeder hens, 2) they were conference proceedings without details on results or on conditions, 3) they were literature reviews with no original data, 4) they did not specify the genotype, the age of the hens, the daily amplitude of temperature variation or the group size, 5) the experiment was performed under one temperature, 6) the experimental temperatures were below 15 • C or above 35 • C, 7) the exposure time was too short to be considered as long-term (less than one week), and 8) the parameters recorded, even if interesting, were too scarce and rarely measured (e.
g. , heat shock proteins). After the filtering step, the final database included data collected from 131 papers with 99 to 1,335 data points per trait (see Appendix). Because the raw data from each study was not available, the final database was made up of the mean values for each trait per heat treatment as summarized in tables and graphs for the retained papers. Similarly, in most cases standard er-rors were not reported for each trait, as such, in order to account for variability in the mean estimates due to differences in sample sizes among studies, we instead estimated the number of independent statistical units (NIS) and included them in the database. For example, in a study presenting the results obtained during 2 weeks of egg collection, with an egg production rate of 50%, and 32 hens in each heat temperature group, reared in cages of 2 hens with a common feeder for 2 cages, we counted 32 independent samples for body weight, 16 for egg production rate and egg mass, 8 for feed intake and feed conversion ratio, and 224 for egg weight (i.
Database Recording Parameters recorded included minimum and maximum daily temperatures, and mean daily temperature (T). We also recorded genotype (GEN) in 3 categories: commercial white birds (CW, 48. 8% of final data), commercial colored birds (CC, 24. 5%), and experimental lines or indigenous flocks (EXP, 26. 7%). To maintain a sufficient number of data per category, it was not possible to define more detailed categories of genotypes. We note that EXP represented a heterogeneous group, as it included both local breeds, generally less productive under standard conditions but well adapted to local conditions, as well as experimental lines selected on a single trait (as opposed to commercial lines selected on wider number of traits) and characterized by a small effective population size. Although more homogeneous, the CC and CW groups exhibited pronounced variability as they included several different commercial lines issued from selection programs over the time span included in the database  (1970 to 2014).
Group size (GS), representing single versus collective rearing (56. 9% and 43. 1% of the cases, respectively) was also included in the database. For all traits recorded between X and Y weeks of age of hens, we attributed a mean age value (A; in weeks) corresponding to the mean of X and Y. The mean hen age in the database was 39. 6 wk, with 25. 8% of data coming from hens younger than 30 wk, 36. 1% from 30 to 40-wk-old hens, 17. 1% from 40 to 50-wk-old hens, 11. 4% from 50 to 60-wk-old hens, and 9. 6% from hens older than 60 wk. Finally, daily amplitude of temperature variation (Δ) was calculated as the difference between maximum and minimum temperatures. In the database, 64% of the data arose from studies with no amplitude of variation or variation less than 3 • C. For the remaining studies, the daily variation of temperature averaged 9.
5 • C. Traits included in the database were hen-day egg production rate per flock (EPR; in %), egg weight (EW; in g), egg mass (EM; in g. d -1 ), daily feed intake (FI; in g. d -1 ), feed conversion ratio (FCR) calcu- lated as the ratio of feed consumption to egg mass (in g. g -1 ), Haugh units (HU), shell thickness (ST; in mm), shell strength (SS; in g), shell proportion (SP; in %), yolk proportion (YP; in %), albumen proportion (AP; in %), body weight (g), and mortality (%). Weekly mortality rate (MORT) was calculated by dividing the total mortality during the experiment by the length of the experiment (in weeks). We calculated a relative weekly body weight change (BW c ) during heat exposure as: BW c = 100 × ⎛ ⎝ 1 - BW 2 BW 1 1 T 2 -T 1 ⎞ ⎠ , where BW 1 and BW 2 were body weight at the beginning and at the end of the heat stress period, respectively, and T 1 and T 2 the hens' ages (in weeks) at the beginning and at the end of the heat stress period, respectively.
Statistical Analysis Egg production rate, mortality, body weight change, and shell proportions were expressed in percentages, which were below 20% or above 80% and were, thus, transformed by arcsine square root, while FCR was log-transformed before analysis. The corresponding abbreviations for transformed traits are, respectively, EPR t , MORT t , BWc t , SP t , and logFCR. The analysis consisted of two steps. In the first step, data were pre-corrected for a random study effect through the MIXED procedure of SAS  (SAS Institute Inc. , 2009). In the second step, we ran the GLMSELECT (SAS Institute Inc. , 2009) procedure on the residuals of the first step to automatically select the best model for each trait. Models were allowed to in-clude the fixed main effects of genotype (GEN), group size (GS) as fixed effects, and covariates for linear effect of temperature (T), nonlinear effects of temperature (T 2 , T 3 ), linear effects of age and amplitude of temperature variation, and all possible two-by-two interactions.
In addition, we introduced observation weights into the model to account for study-specific differences in the variability of data measured on differing numbers of independent samples (NIS), particularly as the NIS varied considerably among the traits and studies considered. For example, mean albumen proportions were calculated on 19 to 2421 NIS depending on the study. However, weighting observations using the raw NIS (which would correspond to giving the latter study in the previous example 127 times more weight than the former) would lead to attributing a disproportionate influence to the few large-scale experiments and largely excluding data from small to medium-sized studies, even though small studies are often more accurate in their monitoring of heat stress than large studies, so that data quality of small-scale studies is quite reliable.
Age or causes of mortality are usu-ally not recorded, and it is difficult to summarize the available data on mortality although it is influenced by chronic heat stress. Similarly, some other effects such as air velocity or humidity could not be included in the models because of the paucity of records, even if they are known to influence the response to heat stress  (Yahav et al. , 2004). This information should be systematically included in a general effort of standardization of data recording in future experiments. Concerning the temperature effect, our study confirmed that large negative effects of heat stress (more than 10% of decrease compared to the optimal value) are observed above 30 • C. However, a real impact of heat stress on some traits was observed below the threshold value of 30 • C.
, 2008). However, sensible heat loss is reduced in brown birds because of heavy feather coverage that limits heat dissipation  (Franco-Jimenez et al. , 2007). Furthermore, brown birds are heavier and, therefore, require more energy for maintenance  (Franco-Jimenez et al. , 2007). This was also the case in our database, where, at onset of lay (before 25 wk), CC were on average 174 g heavier than CW birds. Marsden and Morris (1987)  showed that energy available for production is maximum at 23 • C for brown birds and at 24 • C for white birds. In our analysis birds from experimental lines (EXP) were mostly composed of White Leghorn hens and it is, therefore, not surprising that they showed a similar response to HS as the CW birds. Moreover, the EXP was a heterogeneous group. It was composed on the one hand of experimental lines selected on one unique selection criterion (residual feed intake, clutch length, etc).
Group Size The relationship between group size and ambient temperature has been less studied, as most of the studies on heat-stress effects in laying hens have been performed in single cages. In our database, almost 60% of the studies were done in individual cages, and only two considered both collective and individual rearing. In agreement with our results,  Saki et al. (2012)  showed that group-caged hens have lower egg production, egg weight and egg mass than hens kept in single cages under neutral temperatures of 18 to 22 • C. This could be due, on the one hand, to the lower feed intake of hens reared in group-cages compared to hens kept in single cages (Table  4 ), and, on the other hand, to the higher activity levels in group-caged hens  (Guo et al. , 2012) , both leading to a reduction of energy resources available for production.
ACKNOWLEDGMENTS The authors would like to thank the following institutions for their support and collaboration in this project:  AgroParisTech (Paris, France ),  Wageningen University  (Wageningen, The Netherlands), and  Institut National de la Recherche Agronomique (Nouzilly, France). Utlwanang Moreri  benefited from a joint grant from the  European Commission  and " Institut de Sélection Animale ", the layer breeding division of  Hendrix Genetics  within the framework of the  Erasmus-Mundus joint doctorate "European Graduate School of Animal Breeding and Genetics. "We would also like to thank  Wendy Brand-Williams  and  Andrea Rau  for the English revision of the manuscript ( INRA/AgroParisTech , Jouy-en-Josas, France).
PCR conditions Fresh qPCR mix composition. Oligonucleotide primers and TaqMan probes were selected based on the IS2404 sequence (S1 Table)  [7, 13]. The qPCR mixture contained 0. 3 μM of each primer, 0. 1 μM probe, a glycerol-free Master Mix (SuperHotTaq Master Mix 2X, BIORON) containing 5 mM MgCl 2 and 5 μl of template DNA, in a total volume of 25 μl. Amplification and detection were performed with a thermal cycler (Chromo4, Bio-Rad) using the following program: heating at 95°C for 10 minutes, followed by 40 cycles of 95°C for 15 s and 60°C for 1 minute. The results were analyzed with Opticon Monitor software (Bio-Rad). Dry qPCR mix preparation. Various dry PCR mixtures were prepared and evaluated for efficiency and accuracy. The dry mixes contained 0. 3 μM of each primer, 0. 1 μM probe, and a glycerol-free Master Mix (SuperHotTaq Master Mix 2X, BIORON) containing 5 mM MgCl 2.
Acknowledgments We thank the staff at the  Centre de Dépistage et de Traitement de l'Ulcère de Buruli (CDTUB), Pobè, Bénin ;  Catherine Quinqueneau  and the staff of the  Laboratoire de Bactériologie, CHU, Angers, France ; and the administrative staff of the  Regional Delegation  ( ADR Inserm grand Ouest ) for technical assistance.
The clinical questions were subsequently elaborated according to the Patient-Intervention-Comparison-Outcome-Study (PICOS) method  [18, 30, 31]  that was modified slightly to take into account the aim of screening to lower the burden of the disease in the population. Bibliographic searches for most clinical questions were limited to the time period January 2000 to March 2012 and were performed on Medline, and in many cases also on Embase and the Cochrane Library. Priority was given to recent comprehensive reviews. Additional searches were conducted without date restrictions or starting before 2000 if the authors or editors who were experts in the field knew that there were relevant papers published before 2000. Where no observational data were available, outcomes simulated by mathematical models and expert opinion were accepted as the lowest level of evidence.
Sect. 3. 3   The minimum set of information for monitoring HPV vaccination should include data on vaccine coverage, monitoring of adverse events following immunization and, if possible, a sentinel surveillance of impact on precancerous lesions (VI-A). Sect. 3. 3 3. 4 Standard definitions and parameters for coverage of vaccination should be developed and used in vaccination monitoring (VI-A). Sect. 3. 5   Age at primary vaccination, age at catch-up vaccination, number of doses by single year of age and time between doses, and duration of follow-up since offering primary vaccination should be included in the definitions and performance parameters (VI-A). Sect. 3. 5  Planning, piloting, and modifying HPV vaccination programmes 3. 5 Planning and modification of vaccination programmes and policies should take into account local conditions, including vaccine and vaccination costs and resources required in monitoring, provision of information, and communication.
Acknowledgements Financial support was provided by the  European Union Public Health Programme  (Project no. 2006 322 ,  European Cooperation on Development and Implementation of Cancer Screening and Prevention Guidelines [ECCG]). For the preparation of the present manuscript, MA was supported by the 7th  Framework Programme of DG Research  of the  European Commission  through the  COHEAHR Network  (grant  603019 ). Special thanks are due to the  IARC  staff in the  Quality Assurance, Screening and Communication Groups  who provided technical and editorial assistance.
Flow cytometry and FACS analysis PMN or lymphocyte populations were gated as indicated (S8 Fig) and analyzed for cell death of caspase activation by flow cytometry. FACS analysis was performed using a FACSCanto system (BD Biosciences) or Guava easyCyte (Millipore). FACS data were analyzed using FlowJo software (Tree Star, Inc. ). For each experiment, control samples were included to define the proper gates.
Acknowledgments We thank the research teams of PIET of the  Universidad Nacional (UNA) ,  CIET  of the  Universidad de Costa Rica (UCR)  and  CIML of Marseille-Luminy  for their helpful discussions. Ignacio Moriyón  ( University of Navarra, Pamplona, Spain ) for providing LPS samples,  Laura Monturiol  (Instituto,  Clodomiro Picado ,  UCR, Costa Rica ) for helping with confocal microscope imaging and supplying some inhibitory chemicals,  Arturo Zychlinsky  ( Max Planck Institute for Infection Biology, Berlin, Germany ) for providing several reagents and the helpful discussions and  Reynaldo Pereira  (PIET, UNA) and personnel from  CIEMIC  ( UCR ) for their support and assistance in the electron microscopy techniques.
Statistical analyses First, Kolmogorov-Smirnov tests determined whether residuals were normally distributed. Activity rates data were subjected to arcsine square root transformation and a logarithm transformation was applied to cloacal width, latency to explore the ground, number of fear behaviours and steps per seconds in order to fit a normal distribution. Home cage activities were analysed by week, using two-way on repeated measurements between the 2 weeks (two observation sessions per week) ANOVA (CSP × cage type × week). Fearfulness tests data were analysed by two-way ANOVAs (CSP × cage type) and post hoc LSD Fisher tests, using Statistica software (Statsoft ® ). The level of significance was set at P ⩽ 0. 05. Data are represented as means ± s. e. m.
Therefore, this study aims to  (1)  investigate the suitability of this model to describe the responses of animals to perturbations, and (2) show a concrete example of how this model can be applied in practice in studies investigating the effect of a perturbation on animals. This second point required data on individuals facing an acute perturbation that were monitored before, during and after the perturbation. Data from a published study investigating the effect of a confinement perturbation on fish were used  [8].
To illustrate its genericity, the model was tested on data obtained from a different type of challenge, in a different species; a nutritional challenge in goats  [26]. In this study, 16 lactating goats were followed every day for dry matter intake (DMI) and milk fat content (MFC). Goats initially fed a standard diet were suddenly subjected to a 100% straw diet during 2 days. The measures were recorded before, during and after the nutritional challenge. The present model was fitted to MFC and DMI measures as described in the Materials and Methods. Fig  9  shows that the model was able to correctly fit the responses to the challenge providing values of resistance and recovery for MFC. However, the fitting of the recovery period for DMI was not totally satisfactory since the temporal pattern of DMI seems to display a rebound phenomenon that the model cannot capture in its present form.
Data obtained from laboratory experiments Data obtained from laboratory experiments (i. e. under controlled conditions) can be used to test hypotheses generated from data on interactions in natural systems; they can also be used to tease apart the mechanisms underlying these interactions (e. g. cross-immunity, macrophage production, resistance, tropism), which can be difficult to do in natural systems (e. g. [113, 114] ). Laboratory experiments therefore have an important role to play in studying the effects of multiparasitism and highlighting the synergistic and antagonistic interactions that take place among the diverse parasite groups (e. g. helminths, protozoa, fungi, viruses, acarians) that infect different host taxa, including mammals  [115] [116] [117] , insects  [118, 119] , and plants  [120].