dataesr/scientific-paragraphs-categorization huggingface dataset:
Characteristics of parasitological samples We studied retrospectively over the period of January 1, 2011 to December 31, 2016, 15,220 parasitological samples of 9,555 patients from the CHC and CHOG laboratory registries. The majority of them was analysed from the CHAR laboratory data (77. 4%). The increase in the number of samples collected was linear until 2015 and was followed by a slight decrease until 2016. Among these 15,220 samples, 2,919 were positive for 1,521 patients. The average infestation rate was 19. 2% and a decrease was observed between 2011 (26. 4%) and 2016 (12. 8%) (Fig  1A ). The samples were essentially stool samples but 2,075 specimens were digestive fluids collected during an upper endoscopy as duodenal fluid or a colonoscopy. It was positive for 169 patients with the identification of the adult parasite in 41 patients and ova/larvae in 128 patients.
Because of the significant morbidity of these parasitic diseases, our series underlines the need of a proper survey in French Guiana, including clinical data, dynamics of contamination, and the evaluation of the intensity of the infection with the analysis of the eggs per gram of feces, and anaemia level. Indeed, this should better target the preventive measures to be provided such as providing information about the mode of contamination of the parasite, and the proscription of walking barefoot, and could then be implemented as in Guadeloupe and Martinique where the measures implemented allowed a reduction of their prevalence  [10, 11, 24]. However, this study presents some limitations. First, only parasitological data from the CHC and CHOG laboratories were analysed. Yet, these two structures are the reference laboratories for parasitology in French Guiana and receive samples from all over the country as evidenced by the identified residential areas of the patients.
3 mg/kg in 1-hour infusion) combination therapy. AmB-L was then switched to voriconazole (4 mg/kg intravenously twice a day) because of renal toxicity. The clinical course was favorable, with partial recovery of neurological deficits. The French National Reference Center for Invasive Mycoses and Antifungals (NRCMA; Institut Pasteur, Paris) identified R. mackenziei based on morphological features under Biosafety Level 3 (BSL-3) regulations and sequencing of the ITS1-5. 8S-ITS2 region of rDNA (GenBank accession number: MZ128136). DNA extraction method  [11]  and PCR protocol  [12]  have been described elsewhere. MRI reevaluation in August 2014 showed expansion of the lesion and related edema. Posaconazole (2. 7 mg/kg oral suspension 4 times a day) was added to the treatment regimen, and immunosuppression was lowered.
She underwent stereotactic guided biopsy of the lesion. Direct examination showed black fungal hyphae. She was started on cefotaxime, metronidazole, and voriconazole (4 mg/kg intravenously twice daily), and azathioprine was stopped. Seven-day CT reevaluation showed no lesion reduction. AmB-L (5. 7 mg/kg once a day intravenously) and flucytosine (30 mg/kg 4 times a day intravenously) were added to voriconazole. The isolate sent to the NRCMA for identification revealed R. mackenziei after morphological examination under BSL-3 regulations and sequencing of the ITS1-5. 8S-ITS2 region of rDNA (GenBank accession number: MZ128137). Antifungal therapy was switched to posaconazole only (5. 7 mg/kg once a day orally). MRI confirmed the temporoparietal abscess and showed associated lateral sinus venous thrombosis.
S1 Table. Cases reported in Fig 1. To identify cases, we searched in PubMed using the following keywords: "Rhinocladiella mackenzieie," "Ramichloridium obovoideum," "Ramichloridium mackenziei," and "Ramichloridium obovoidea. " We searched from database inception onward without language restrictions. The last search was conducted on May 15, 2020. (DOCX).
Each cup was equipped with an inclinometer (8. IS40. 23321, Kübler, Villingen-Schwenningen, Germany). The distances between the bending point and the proximal and distal articulations of the cups were identical for all specimens and guaranteed consistent lengths of the proximal and distal lever arms with respect to the radiocarpal bone. To reproduce postoperative activity during trotting of a 30 kg dog, the specimens were loaded under axial bending along the machine axis to 300 N compression over 10 cycles at 0. 5 Hz  [22, 23]. Axial displacement and load were recorded from the MTS transducers together with inclinometer and strain gauge output data at 128 Hz. The last cycle of each test was considered for data evaluation. Based on MTS and inclinometer data, construct compliance (CC [ °/N]) and maximum angular deformation (AD [ °]) were computed.
Statistical Analysis. Statistical analysis was performed using SPSS software (version 23, IBM SPSS, Armonk, NY). Mean and standard deviation (SD) were calculated for each parameter of interest. The Shapiro-Wilk test was conducted to ascertain a normal data distribution within all fixation techniques. One-Way Analysis of Variance (ANOVA) with Bonferroni post hoc test was conducted to identify significant differences between OH and RH plates, whereas the differences between OH-P and OH-D were screened with Paired-Sample t-test. A level of significance was set to 0. 05 for all statistical tests.
In 2017 only, the compressed sward height was measured using a rising plate meter (30 × 30 cm, 4. 5 kg/m 2 , Aurea Agrosciences, Blanquefort, France), with 30 measurements made at the start of each observation sequence. The observer always remained quiet and sufficiently close (i. e. within a few meters) to the observed goat to record its activities accurately, and never disturbed natural animal behaviour. For a given observation day (n = 24, Table  1 ), observations were performed in the morning, in the afternoon or both. The validation dataset comprised 187 h of visual observations, which were divided among 69 sequences, 20 goats, 24 observation days (dates) and 12 Lifecorder Plus devices (Table  1 ). Once the recordings were made, the device was removed from the box and connected to a computer to transfer data via a USB cable.
Calculations To compare Lifecorder Plus data (2-min frequency) to visual observation data (1-min frequency) at the same temporal scale, all 2-min observation periods with at least 1 min of "grazing" activity were considered to be "grazing" activity (i. e. grazing was the dominant activity). Observations were performed only at pasture, as no activity could be detected indoors due to a lack of clear and regular head movements, which indicated that the device cannot determine eating time indoors. Analyses of the recorded data clearly showed that the activity level was close to zero when goats were ruminating or engaged in other activities. Grazing activities were thus characterised and defined by an activity level greater than or equal to a given threshold, as defined for dairy cows  (Delagarde and Lamberton, 2015)  and in the preliminary study of dairy goats  (Charpentier and Delagarde, 2018).
Results The duration of validation sequences averaged 162 min (range: 62-242 min) for a total of 69 observation sequences (total of 11,186 min or 5593 2-min periods). Recording time in the morning equalled that in the afternoon. On average, per hour of observation, the goats spent 49 min grazing, 2 min ruminating and 9 min in other activities, which represents 82 %, 3% and 15 % of their time spent grazing, ruminating and in other activities, respectively (Table  2 ). For the entire dataset, the frequency distribution of activity level recorded by the Lifecorder Plus during actual grazing periods differed completely from that observed during actual non-grazing periods (Fig. 2 ). For example, the percentage of activity levels greater than 0. 9, 0. 7, 0. 5, 0. 3 and 0. 1 were 91 %, 95 %, 97 %, 98 % and 100 %, respectively, during actual grazing periods, but only 13 %, 18 %, 23 %, 32 % and 47 %, respectively, during actual non-grazing periods.
Fig. 6. Activity level recorded by the Lifecorder Plus placed on the neck and the fore and hind legs for two additional recording sequences of two goats at pasture (two days independent of the validation dataset). The legs curve is the average between fore and hind legs curves because the signals were similar. For actual activities, only active behaviours (grazing, rumination, and other activities such as walking, running or social interactions) are reported. The "blank" periods are resting time (no activity, no movement). et al. , 2020) and 86 % for the 3D activity sensor  (Nielsen, 2013). The accuracy of the Lifecorder Plus (93 %) can also be considered as high compared to the 90 % accuracy of the RumiWatch device tested on cows  (Steinmetz et al. , 2020). The F1 score of the Lifecorder Plus (96 %) indicates high performance when compared to a 9-axis multi-sensor accelerometer tested on goats  (Sakai et al.
Three animal species from the SWIO region, known to host distinct bacterial lineages/species of Leptospira, were included in the present investigation. Using published molecular and serological data together with original results, we demonstrate that Leptospira serological signatures are not necessarily connected to the Leptospira excreted by animal reservoirs. We demonstrate the shortfalls of only using MAT alone for the identification of Leptospira animal reservoirs and discuss the utility of MAT for clarifying leptospirosis epidemiology.
The present study is a part of a larger research project named RHAPORC ("Relationship between human and animal in pig farming", CASDAR project, funded by the French Ministry of Agriculture) investigating HAR in pig farming and proposing ways to improve it, to enhance welfare for both animals and farmers and, potentially, to improve animal productivity. The present study had two objectives: 1) to investigate HAR in a diversity of pig farming situations and to evaluate the possible correlation between farmers' attitudes, animal behavioral response to humans, husbandry practices, animal health, welfare and productivity and 2) if farmer profiles could be assigned according to their attitudes, to find a way to rapidly associate a farmer with a given profile and better adapt improvement/training programmes.
Data collection To meet our first objective, data were collected in different steps to assess the farmer and pig points of view. The farmer's point of view was assessed through 1) a face-to-face interview which aimed to collect information on the farmer's perception of the pigs and his/her husbandry practices and 2) the observation of the farmer with the sows, to assess his/her practices involving animals. The pig's point of view was evaluated through 1) the reaction of sows when the farmer enters their pen; 2) human approach tests conducted on sows and growers; 3) collection of productivity data for sows and fattening pigs and 4) observation of some health-related parameters for sows. To meet our second objective, the farmer had to fill in a questionnaire composed of closed-ended questions.
, 2009). The investigator carried out this test in three pens, and the farmer carried out the same test in three other pens. The pens were randomly selected among growers weighing around 60 kg. Whereas this survey focused more on reproductive herd, HAR test were also performed on fattening pig to check whether the behavioral answer was the same on the farm for both types of animals. The number of pen was chosen to ensure that the same number of pens can be observed in each farm and that a minimum of repetitions are done. In the fourth part of the survey, the investigators collected technical and economic data on the farm. They recorded, when possible, average farm productivity indicators of the previous year, such as the mean weaning-to-gestation interval, number of piglets born and weaned per litter, pre-weaning mortality and farrowing rate.
For each sow included in the behavioral test, the investigator recorded individual reproduction data for the last litter of the sow, such as total number of piglets, total number of piglets born alive, number of weaned piglets per litter, weaning-to-gestation interval, farrowing interval, parity number and breed. For fattening pigs, the investigator recorded mortality, daily weight gain and time between weaning and slaughter measured during the previous year. At the end of the survey, a multiple-choice questionnaire, in paper format and in several copies, was left at the farm to be filled out by the interviewed farmer and by all other stockpersons of the farm. It was left with a postage-paid envelope to encourage feedback and confidentiality of each respondent. It focused on the same four topics as the interview.
Each variable had from two to six levels, but only a maximum of four levels were kept to ensure 10% of the sample at each level to maintain a consistent and robust number of responses at each level. Variables for which all farmers gave the same answer were not included in the analysis. Technical data provided 11 supplementary quantitative variables, which were categorized. Only variables characterizing the profile at the threshold P < 0. 05 were kept. The number of axes selected from the MCA for the AHC was determined using the Kaiser rule. Data processing and analysis were carried out using R software version 1. 1. 456 and its package FactoMineR version 1. 41  (Le et al. , 2008). A logistic regression model was used to identify explanatory variables of the sow HAR score. The following variables were tested: sow housing (groups with feeding stalls, groups with trough feeding and large groups with electronic feeding stations), floor type (straw bedding and slatted flooring), farmer profile (1, 2 and 3), gilt socialization (yes or no), investigator (A or B), sow parity (1, 2-3, 4-5, 6 and more), gestation stage (early, mid, late), daily physical contact with animals (yes or no), sow group size (<8 sows, from 8 to 20 sows, more than 20 sows), pig breed (five genotypes), on-farm variability in responses (yes or no, see below), farmer gender and age (under 45 years old, from 45 to 54 years old and more than 54 years old) and number of sows on the farm (<200, from 200 to 499 and more than 499).
The relationship between the individual productivity results of sows and the profile of farmer was analyzed using a mixed model, introducing the sow HAR score, sow parity and their interaction as well as sow breed, farmer profile and on-farm variability in responses as fixed effects and farm as random effects. For this analysis, sow HAR scores of 0 to 2 and 3 to 4 of were pooled together; parities 2 and 3, 4 and 5 and 6 and above were also pooled together. Productivity and behavior tests of growers were analyzed using a linear mixed model, introducing farm as a random effect and investigator, investigator clothing and farmer profile as fixed effects. Data processing and analysis were carried out using RStudio for R software version 1. 1. 456 and its package nlme ("non-linear mixed effects") version 3.
1-137. To identify the most relevant questions from the questionnaire designed to discriminate the farmer profiles, three different prospective analyses were done on the data collected from the questionnaires. The first analysis consisted of constructing determination trees using the classification and regression tree (CART) method  (Breiman et al. , 2017)  on the answers obtained from the questionnaire filled out by the interviewed farmers. Classification and regression tree is a statistical approach that can identify the best predictors of a profile among a list of variables, e. g. here, questions. The error rate of the tree was computed using the leave-one-out method. Classification and regression tree modeling was carried out using the statistical programme RStudio for R software and the packages Rpart  (Therneau et al.
Relationship between behavioral tests, farmer profile and technical data A total of 1 724 sows were tested, of which 266 were gilts. The proportions of sows scoring 0, 1, 2, 3 and 4 (fearful to confident sows) were, respectively, 30, 13, 24, 19 and 14%. The mean farm score was 1. 8 ± 1. 4 and ranged from 0. 4 to 3. 2. Logistic regression identified sow housing, floor type, farmer profiles, gilt socialization, investigator and parity as the main explanatory factors of the sow HAR score, with differences between levels (Table  3 ). The sow HAR score was higher (more confident sows) for Profile 3 farmers (central HAR) and in farmers who practise gilt socialization. The scores were also higher for low-parity sows, for sows housed with electronic feeders and for straw-bedded sows. The sow HAR score also showed differences for three other variables.
Maternal behavior assessment following a separation-reunion test After the first suckling, dams and their calves were moved into an individual 15m 2 enclosure. To stimulate behavioral interactions, the calf was separated from the mother for 1 h and placed in an adjacent enclosure (2. 2 ×2. 1 m) allowing visual and auditory communication. Maternal behavior was then videotaped for 30 min using a camcorder (Sony® X60). To assess the change in maternal behavior (i. e. , the number of bleats and sniffing the newborn) the test was repeated at 12 h, 24 h, 48 h, 72 h, and 7d postpartum. Behavioral data were analyzed by one expert person using Boris software 6. 3. 1  (Friard and Gamba, 2016).
All given estimates are presented as ln-transformed least squares means (LSM) ± standard errors (SE), whereas back-transformed LSM values are given in the text and in Table  S1  of the Supplementary Material. Tail raising results are presented as LSM ± SE. P-values are considered significant at <0. 05 and tendencies at <0. 06. Calf behavioral data remained non-normally distributed after transformation (Shapiro-Wilk test); therefore, the effect parity and sex of calf was studied using Mann-Whitney tests. P-values less than 0. 05 were considered as statistically significant and results are presented as medians and lower and upper quartiles (LQ-HQ). Maternal behaviors (total number of bleats, high-pitched bleats, low-pitched bleats, sniffing duration, and sniffing frequency) data were analyzed with PROC GLIMMIX using log link for Poisson data.
Previously, it was accepted that the incidence of human brucellosis correlates with the incidence of brucellosis in livestock  [29, 30]. However, more recent reviews recognize that this may not always be the case and can depend on multiple variables, including proximity to the herd and eating and cultural habits  [22]. Quantitative evidence of human exposure to Brucella spp. linked to seropositive cattle is possible to attain by conducting integrated epidemiological studies on animal and human brucellosis. However, these studies are difficult mainly because zoonotic disease detection in humans and animal hosts are separate and siloed  [31] [32] [33] [34]. As a result, brucellosis data for humans and animals are usually presented separately and not epidemiologically linked by time or location  [35] , or datasets are incomplete because only animal or human data are available  [36] [37] [38].
Recruitment of Human Participants and Categorisation of Brucella Infection Evolution Each herd had a different owner or herd manager, and there was no movement of farm workers between herds included in this study. However, veterinary officials are routinely exposed to more than one herd irrespective of disease status of that herd. All farm workers (n = 150) on case farms (n = 30), a subset of farm workers (n = 53) on control farms (n = 11) and veterinary officials (n = 27) servicing all three state vet areas were sampled for testing. On farms where farm workers were tested, farm managers or owners of herds were administered a structured herd management questionnaire face-toface. The questionnaire collected data on herd management factors, and cattle herd and human symptoms of brucellosis detected as abnormal by the farmer in the year before the last herd test result.
Seropositive reactors on the BrucellaCapt test were allocated to the group defined by the outcomes of the RBT ® , IgM ELISA ® and IgG ELISA ®. Subjects with test results for the IgG ELISA ® that were classed as equivocal (n = 3) were removed from the analysis. Titres were determined using the BrucellaCapt ® test. A titre of greater or equal to 1:320, was considered positive. Questionnaire responses and test results from human participants were captured into an ACCESS 2013 ® (Microsoft suite 2013) relational database, using a unique herd identifier to link test results from farm workers to the herd they were in contact with. The farm managers' questionnaire response shared this unique number.
Acknowledgments: This study would not have been possible without the support and encouragement of the  Gauteng Department of Agriculture and Rural Development. The authors wish to acknowledge the animal health technicians (AHTs), state vets and managers of the department. This study would not have been possible without the following people:  Nolo Moeketsi ,  Gerbrand van der Zel ,  Theo Serebolo ,  Peter Geertsma  and  Johan Walters. We also wish to acknowledge  Anastasia Trataris-Rebisz  for performing the testing of the human samples.
Funding Open Access funding enabled and organized by Projekt DEAL. This publication was supported by the Open Access Publication Fund of the University of Würzburg. The Sharma lab received financial support from the Deutsche Forschungsgemeinschaft (DFG) project Sh580/1-1, the Young Academy program of the Bavarian Academy of Sciences and Humanities (BAdW), and the Bavarian Research Network bayresq. net. The De Reuse's lab was funded by the Agence National de la Recherche [ANR-12-BSV5-0025-Bactox1] and the Pasteur-Weizmann consortium "The roles of noncoding RNAs in regulation of microbial life styles and virulence. ".
Patients Data of antifungal susceptibility testing performed on A. fumigatus clinical isolates as a part of the routine lab procedure between January 2015 and December 2019 were retrospectively collected. A total of 929 A. fumigatus isolates from 426 patients were tested for susceptibility to at least one azole. Among them, 595 isolates were obtained from sputum samples or throat swabs from 123 CF patients included in the cohorts of adult (N = 87) and pediatric (N = 36) "Centres de Ressources et de Competences de la Mucoviscidose" at Rennes University Hospital (France). The remaining strains were isolated from patients hospitalized in ICU (N = 57), Pulmonology (N = 159), Hematology (N = 13) or other clinical wards (N = 105), and used for comparison to isolates from CF patients. performed routinely, the promoter and the whole cyp51A gene were sequenced in both strands from A.
Mycological Examination The PCR mixture contained 5 ml of DNA extract and 20 ml of a mix composed of 0. 625 U of GoTaq ® Hot Start Polymerase (Promega, Charbonnières-les-Bains), 1x Colorless GoTaq ® Flexi Buffer (Promega), 2mM of MgCl2 (Promega), 0. 8mM of dNTP mix (Eurobio, Les Ulis), and 0. 2 mM of each primer. The amplification program consisted of 5 min at 94°C, 30 cycles of 30 s at 94°C, 30 s at 58°C, and 1 min at 72°C, followed by a final step of 10 min at 72°C. Sequences of resistant strains were compared to the wild-type A. fumigatus sequence CM 237 (GenBank accession number AF338659), at http://blast. ncbi. nlm. nih. gov/Blast. cgi.
Ethics and Statistics According to the French Public Health Laws (Code de la SanteṔ ublique, 2017), protocols of this type do not require approval from an ethics committee and are exempt from the requirement of formal informed consent. MIC values were expressed as median and interquartile range. Data analysis was performed using the GraphPad PRISM ® v. 5. 02 software. For comparison of proportion, the Fisher's test was used. A p-value of 0. 05 was considered statistically significant.