dataesr/scientific-paragraphs-categorization huggingface dataset:
One to three reference strains for each species were used to create a database of main spectrum profiles, and the remaining isolates were used as test isolates. A minimum of 10 spectra was used to build the main spectrum profile of each database strain. Interspecies discrimination for all the isolates, including species belonging to the same genus, was possible. Twenty isolates belonging to five species were used to test the database accuracy, and were correctly identified to the species level with a log-score >2. In summary, matrix-assisted laser desorption ionization time-of-flight mass spectrometry is a reliable and rapid method for the identification of most of the human pathogenic Mucorales to the species level.
Each spot was overlaid with 1. 2 µL of alpha-cyano-hydroxycinnamic acid in 2. 5% of trifluoroacetic acid and 50% of acetonitrile in water (Bruker Daltonik), and air dried at room temperature. Spectra were acquired using a Microflex LT mass spectrometer (Bruker Daltonik). Spectra were recorded in positive linear mode within a mass range from 2. 000 to 20. 000 Da and were analyzed using the software Flex Analysis (Bruker Daltonik).
Construction of the Database The database was constructed by generating main spectrum profiles. For each species, one or two isolates (or three isolates for L. ramosa) were used to generate the main spectrum profiles. Strains were cultured on malt extract agar for 7 days at 35 • C (except for Mucor species that were cultured at 30 • C). For each strain, five independent cultures were performed, and from each culture, two fungal suspensions were prepared. Extractions were performed as described above, and each sample was spotted in duplicate. Then, 20 independent spectra were generated per strain. After processing and the visual inspection of each spectrum in the software FlexAnalysis, at least 10 spectra were retained to generate the main spectrum profiles by using the software Biotyper 2.
Accuracy Test of the Database For the accuracy test of the database, MALDI-TOF mass spectrometry analysis was performed for a set of isolates (n = 20, Table  2 ), as described above. Each isolate was tested in quadruplicate. Each spectrum was compared to the newly generated database by the MALDI Biotyper software with default parameters. The algorithm generated a log score value ranging from 0 to 3, by comparing peak intensities, positions, and frequencies. Levels of identification were calculated and interpreted according to the manufacturer: a log score value of >2 indicated species identification, a log score value between 1. 7-2 indicated genus identification, and a log score value <1. 7 indicated a non-reliable identification.
Evaluation of Parameters (Medium, Incubation Time) 3. 1. 1. Medium Spectra were evaluated for three Mucorales species grown on three different culture media after two different incubation times. After both time points, the spectra were similar, but the intensity of the peaks was different on the three media. For both incubation times, higher intensities of peaks were obtained on malt extract agar compared to RPMI 1640 agar and Sabouraud agar (data not shown). After 2 days of incubation, more peaks were obtained on RPMI 1640 agar, whereas at day 7, more peaks were obtained on Sabouraud agar. Nevertheless, the spectra remained similar on the three media, and differences were species-dependent (data not shown). Globally, malt extract agar seemed to be the most reliable medium, and was chosen for the subsequent experiments.
Construction of the Database After these preliminary experiments that allowed the determination of the medium and incubation time, the database was set up. For assessing the intergenera, interspecies, and intraspecies variability, all the main spectrum profiles from the database were identified against the database itself. The results of the log-score values are presented in Table  3. A log-score of 3 indicated a perfect match (i. e. , when a database strain was compared to itself). A high intergenera variability was observed with a log-score <1. 1 for all the strains. The highest similarity between two isolates belonging to different genera was obtained between M. indicus and R. pusillus (log-score value of 1. 01). Similarly, high interspecies variabilities were found for all the species belonging to the Lichtheimia (highest log-score of 1.
Construction of the Database After these preliminary experiments that allowed the determination of the medium and incubation time, the database was set up. For assessing the intergenera, interspecies, and intraspecies variability, all the main spectrum profiles from the database were identified against the database itself. The results of the log-score values are presented in Table  3. A log-score of 3 indicated a perfect match (i. e. when a database strain was compared to itself). A high intergenera variability was observed with a log-score <1. 1 for all the strains. The highest similarity between two isolates belonging to different genera was obtained between M. indicus and R. pusillus (log-score value of 1. 01). Similarly, high interspecies variabilities were found for all the species belonging to the Lichtheimia (highest log-score of 1.
Accuracy Test of the Database Twenty different isolates belonging to the major species (and not used for the construction of the database) were spotted in quadruplicate, and identification was performed using the newly generated database by calculation of the log-score values. Isolates belonged to the most common pathogenic species, namely R. arrhizus, L. corymbifera, L. ramosa, Mucor indicus, and R. pusillus. The log-score values obtained for all the isolates are shown in Table  2. For all the tested isolates, high log-score values of >2 were obtained. For each of the strains, a more detailed analysis was also performed. The 10 best matches were recorded, and log-score values obtained for strains belonging to the same species (measuring the intraspecies variability) and different species (measuring the interspecies variability) were analyzed (Figure  2 ).
Accuracy Test of the Database Twenty different isolates belonging to the major species (and not used for the construction of the database) were spotted in quadruplicate, and identification was performed using the newly generated database by calculation of the log-score values. Isolates belonged to the most common pathogenic species, namely R. arrhizus, L. corymbifera, L. ramosa, Mucor indicus, and R. pusillus. The log-score values obtained for all the isolates tested are shown in Table  2. For all the tested isolates, high log-score values of >2 were obtained. For each of the strains, a more detailed analysis was also performed. The 10 best matches were recorded, and log-score values obtained for strains belonging to the same species (measuring the intraspecies variability) and different species (measuring the interspecies variability) were analyzed (Figure  2 ).
For L. corymbifera and R. pusillus, no overlap of logscore values was seen, indicating that all the tested isolates of these species exhibit a high similarity. In contrast, for L. ramosa and R. arrhizus, log-score values of <2 were obtained. This indicates that the isolates of these species show a certain degree of interspecies variability. Nevertheless, this did not preclude the correct identification to the species level (Table  2 ). Plot of log-score values obtained for the isolates, belonging to four species, were used for the accuracy test of the database. On each graph, the left panel plots the log-scores values obtained for isolates belonging to the same species (as a marker of intraspecies variability), and the right panel plots the log-scores values obtained for isolates belonging to different species (as a marker of interspecies variability).
Discussion MALDI-TOF mass spectrometry is widely used for the identification of bacteria  [28]  and yeasts  [16]  to the species level. Major advantages of this identification technique compared to molecularbased identification are its accuracy combined with simplicity, cost effectiveness, and the possibility Plot of log-score values obtained for the isolates, belonging to four species, were used for the accuracy test of the database. On each graph, the left panel plots the log-scores values obtained for isolates belonging to the same species (as a marker of intraspecies variability), and the right panel plots the log-scores values obtained for isolates belonging to different species (as a marker of interspecies variability).
Therefore, we set up a standardized technique for the sample preparation, and built our own database for the identification of Mucorales to the species level, including reference strains for the most common species responsible for human disease. Our results demonstrate that a precise discrimination of Mucorales species with a high variability between genera, and also between species, is possible. Intraspecies variability was species-dependent: for some species, a low variability was seen, while for R. arrhizus and L. ramosa, a certain degree of intraspecies variability was obtained. One of this study is that for some species, only a relatively low number of isolates was included. That might be the reason why for those species, no intraspecies variability was observed. The intraspecies variability of R.
arrhizus  [18, 21, 22, 24, 26, 27]  and L. ramosa  [25, 27]  was already reported by others. Our results are in accordance with these findings. Taking these findings into account, it is of major importance to include several isolates of each species into the database to maximize the possibility of reliable identification. The accuracy of identification of Mucorales to the species level by MALDI-TOF mass spectrometry has already been evaluated by other studies. In one study, a database was set up, including a total of 19 isolates belonging to Mucor, Lichtheimia, Rhizopus spp. , and R. pusillus. The database was further tested for accuracy with eight Mucorales isolates, including one R. arrhizus and four L. ramosa strains. No problems in identification were reported; all the log score values were >2  [23].
Another study analyzed the identification of pathogenic Lichtheimia species  [25]. The database comprised 12 Lichtheimia strains belonging to five different species, and seven strains belonging to seven different Mucorales species were also added. The database was tested with 34 additional Lichtheimia isolates. All the isolates of L. corymbifera, L. ornata, Lichtheimia hyalospora, and Lichtheimia sphaerocystis were correctly identified when taking the highest obtained log-score value into account. When compared to other species, log-score values >2 were obtained, indicating a false identification. The identification of L. ramosa strains was even more difficult; log-score values of <1. 9 were obtained for two of the 17 tested isolates. Aggravatingly, some isolates exhibited the highest obtained log-score values for a different species, indicating a false identification  [25].
Despite the intraspecies variability of L. ramosa, in our database, no false identifications were seen for the Lichtheimia species. Problems in the identification of L. ramosa isolates were also seen in another study evaluating the commercialized Bruker library alone or in combination with an in-house library  [27]. The databases were tested with 111 isolates. Despite a significant increase from 49. 5% to 81. 1% of isolates identified correctly to the species level, when using both libraries compared to the Bruker library alone, seven isolates, including one L. ornata and three L. ramosa isolates were misidentified. For the other three tested isolates of L. ramosa, only an identification to the genus level was possible (log-score value ≥1. 7). The intraspecies variability of L. ramosa may be related to the existence of at least two different clades within this species, as described previously  [31].
arrhizus isolates. Identification was only possible to the genus level (log-score values >1. 7 and <2)  [21]. The National Institutes of Health also designed an in-house library containing 152 different mold species, including 27 Mucorales isolates. While no problems were reported when challenged by three R. arrhizus isolates, the identification of the same isolates by the Burker database was impossible. Identification of all the other tested Mucorales isolates (n = 9) by the National Institutes of Health database was successful  [18]. Problems in the identification of Mucorales to the species level using the Burker database were also reported by others  [26]. Globally, different results for the identification of Mucorales to the species level by MALDI-TOF mass spectrometry were obtained, especially for species showing intraspecies variability.
) were used for the construction of the database: L. corymbifera CBS 429. 75, L. corymbifera CBS 100. 31, L. ramosa CBS 270. 65, L. ramosa CBS 269. 65, L. ramosa CBS 582. 65, L. ornata CBS 291. 66, Mucor circinelloides f. circinelloides CBS 195. 68, M. circinelloides CBS 384. 95, Mucor indicus CBS 226. 29, Rhizomucor miehei CBS 182. 67, Rhizomucur pusillus CBS 354. 68, R. pusillus IP 3. 77, Rhizopus microsporus var. chinensis CBS 631. 82, Rhizopus microsporus var. oligosporus CBS 112589, R. arrhizus CBS 112. 07, R. oryzae IP 4. 77, Syncephalastrum racemosum CBS 441. 59, and Cunninghamella bertholletiae CBS 190. 84. List of isolates used for the construction of the database.
Funding: This research was funded by an educational grant from  Gilead Sciences , grant number  IX-FR-131-0288. Conflicts of Interest: P. S. has received research grants from  Basilea Pharmaceutica ,  Gilead  and  Pfizer , and has received travel grants from  Gilead  and  Pfizer. During the past 5years, E. D. has received: research grants from  MSD  and  Gilead ; travel grants from  Gilead ,  MSD ,  Pfizer  and Astellas; and speaker's fees from  Gilead ,  MSD  and  Astellas. H. G. , F. L. and F. G. : none to declare.
016% w/w gel. Patients (18 years) with IA-IB biopsy-confirmed MF-CTCL with no known hypersensitivity to the study drug were enrolled in this "split-face," 2-arm open-label study (NCT03380026). Chlormethine 0. 016% w/w gel was applied once-nightly, over 8 cm 2 of designated area, during a 4-month period to all lesions studied, while half of the lesions also received Triamcinolone. The secondary endpoint of the study, which was to assess patients who had moderate to severe reactions to chlormethine 0. 016% w/w gel leading to treatment hiatus or discontinuation, through patch testing, skin biopsies, and T cell receptor immunosequencing are reported. As of May 2019, 25 patients were enrolled. The incidence of moderate to severe contact dermatitis was 24% for lesions treated with chlormethine 0.
IntroductIon EMONO is an equimolar mixture of oxygen and nitrous oxide which has an analgesic effect with a reduction of the perception threshold of different painful stimuli. This is the only way that nitrous oxide is available in France for dental care. At this concentration, nitrous oxide should not cause deep sedation. It causes modifications in consciousness: patients are relaxed, sedated, and less aware of their surroundings. Pulmonary absorption and elimination of nitrous oxide is very quick because of its low solubility in the blood and tissues, which explains the rapidity of the analgesic effect and the quick return to the initial status after discontinuation of inhalation. 1 -5  According to the characteristics summary of the product available on the French government's public drug database, EMONO indications in dentistry are dental care in infants, children, and adolescents, as well as anxious or patients with disabilities.
Participants This single-center, prospective epidemiological study was conducted at the Dental Service of Nantes Hospital from November 2014 to May 2015. All patients aged 3-15 with a need of dental care under EMONO at the Dental Service of Nantes Hospital could be included. EMONO is applied with a naso-oral mask during the entire treatment session. During care, the mask is repositioned on the nose so that the practitioner can access oral cavity. Exclusion criteria were: (i) not being able to provide an answer for the evaluation, (ii) dental treatment possible without the use of EMONO, (iii) or important treatment justifying the use of general anesthetic. Depending on the severity of the cases, children could be treated during only one session or over several sessions. For children with several sessions, data were collected during the first and final session.
Assessment The data collected included the medical history of the child, family situation (separated parents or not), parents' anxiety for the dental care of their children or not, and information about the session of dental care with the use of EMONO. This latter part of the assessment was assessed by the practitioner, taking into accounts his/her comments and the answers to questions asked to the child. Regarding the effects felt by the child, if he/she could not verbalize his/her perception, the data could not be collected. They were then rated non-collectable.
The corresponding odds ratio and associated confidence interval were estimated. Discrimination of the final logistic model, which describes its ability to discriminate between the presence and absence of a contact prolongation attempt, was assessed using the area under the receiver operating characteristic (ROC) curve and the goodness-of-fit of the model was assessed using the Hosmer-Lemeshow test. The conditions for validity were verified for all of the tests and the model. The data were computed using the Epidata® software and all analyzes were performed using SAS software 9. 3®.
The published data also point in this direction since many cases of abuse of pure nitrous oxide have been recognized in recent years. 8 The fact that EMONO is appreciated by patients is particularly interesting in the context of dental care because its use is totally framed. Of the 76 patients included in this study it is important to note that over half of them (53%) had never inhaled nitrous oxide before inclusion. The study population is made up of more than half by naive consumers, for whom the first session of care was a discovery of the product and its effects. It is interesting that among the 12 patients who attempted or showed a willingness to extend the contact with the gas, 5 consumers were "naive" and 7 had already used EMONO. An estimated 55% of patients had already experienced EMONO in those who did not attempt or show a willingness to extend the contact with the gas.
Survey methodology In this review, we discussed the current literature related to serpins and their functions in health and disease, with a focus on the human gut microbiota. References mentioned in this review were retrieved from PubMed up to 2019. We used the research terms such as serpin, microbiota, health and diseases. Considered references will provide more information about serpins and their impact on the human health. We excluded the studies related to the serpin engineering and the improvement of their biochemical behaviors. Protein sequences encoding for serpins were isolated from the NCBI public database using the key word ''serpin''. Phylogenetic tree was built with PhyloT (https://phylot. biobyte. de/) and ITOL.
Serpins structure Many structural and biochemical analysis provided a major knowledge progress on serpin family. Serpins display a single domain of 40-60 kDa (PFAM ID PF00079) with an average size of 350-400 amino acids  (Stein & Carrell, 1995; Irving et al. , 2000; Gettins, 2002). Currently, around 200 three-dimensional structures of serpin and serpin-protease complexes are available in PDB database deriving from both eukaryotes and prokaryotes Eriksson,  Carlson & Velez (1986) ,  Lomas et al. (1992 ), Yang et al. (2000) ,  Saunders et al. (2012)  and Heit et al. (  2013 ) Antichymotrypsin (SERPINA3) Complement activation, apoptosis, prohormone conversion Emphysema, Alzheimer's disease  Law et al. (2006) ,  Kamboh et al. (2006)   that display significant structural similarities. Most of these structures (∼90%) belong to eukaryotic species, while only three serpins structure from thermophilic and pathogenic bacteria are solved  (Irving et al.
Phylogenetic study Analysis of serpins available in the public databases (NCBI) demonstrated that these bacterial antiproteases are distributed in different phyla, mainly Actinobacteria, Firmicutes, Bacteroidetes, Cyanobacteria and Proteobacteria (Fig. 2 ). In order to explore the distribution of these serpins within each phylum, we carried out a phylogenetic study at the family level (Fig. 2 ). We noted a significant proportion of serpins that were only represented in a small number of species (<50 species) of a given family which we classified as rare. In addition to rare families, we found that serpins from the Actinobacteria phylum were mainly distributed in three families: Streptomycetaceae, Bifidobacteriaceae and Pseudonocardiaceae. In the Bacteroidetes phylum beside rare families, serpins belong to the Prevotellaceae, Bacteroidaceae and Porphyromonadaceae families.
Funding This work received funding from the  Microbiology  and the  Food Chain division (MICA)  of the  INRA institute through the metaprogramme MEM -Meta-omics and microbial ecosystems , two  ANR projects SerpinGuTarget and Titan  and the  CMCU-PHC Utique  (n • 19G0819) - Campus France  ( 41786NC ). This work was supported by the SerpinGuTarget (Contract number  ANR-14-CE16-0018 ) and Titan (Contract number  ANR-18-CE18-0019-03 ). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Acknowledgements The authors wish to thank the students who worked on this study, and more specifically  Romain Elias ,  Stanislas Charton  and  Clément Roy. We would like to express gratitude to  Mr. Stephane Grolleau  for his technical assistance during DSC experiments at IMN (The  Institute of Materials of Nantes ). This research was financially supported by the DRAC (regional management of cultural affairs) of the Loire Region.
Funding This work benefited from the financial support of the  LabeX LaSIPS  ( ANR-10-LABX-0040-LaSIPS ) managed by the  French National Research Agency  under the '' Investissements d'avenir" program  ( ANR-11-IDEX-0003-02 ). This work was carried out within the MATMECA consortium and supported by the  ANR  under contract number  ANR-10-EQPX-37.
Several simple techniques have been used to reduce metallic artifacts, such as increasing kV or mAs, using softer reconstruction kernel, using iterative reconstructions (IR), using thinner slices, and adapting windowing  [1, 5, 6]. However, these techniques have a limited impact on artifact reduction and may require an increased delivered dose or a reduction of spatial resolution. Another strategy to reduce metallic artifact consists of using extrapolated mono-energetic images obtained with dual-energy CT  [2, [7] [8] [9]. However, dual energy CT-scanners are not widespread, datasets are usually acquired prospectively, and postprocessing is time-consuming. Recently, metal artifact reduction (MAR) algorithms have been proposed  [2] [3] [4] [10] [11] [12] [13] [14]. MAR aims to reduce artifacts caused by beam hardening and photon starvation.
CT examinations Datasets were acquired using four distinct CT systems including Revolution GSI ® (GE Healthcare), Ingenuity Elite ® (Philips Medical Systems), Somatom EDGE ® (Siemens Healthineers) and Aquilion Prime ® (Canon Medical Systems). The CT units were equipped with the following MAR algorithms: Smart-MAR ® (GE Healthcare), SEMAR ® (Canon Medical Systems), iMAR ® (Siemens Healthineers) and O-MAR ® (Philips Medical Systems). The basic principle of the first two MAR algorithms relies on projection-based MAR whereas the last two rely on model-based iterative algorithms.