dataesr/scientific-paragraphs-categorization huggingface dataset:
Visit 2 At the second visit (T0 + 4 weeks), patients are first asked to complete a self-administered electronic questionnaire about their motivation and behavior in terms of oral health  [46]  that is directly linked to the e-CRF and investigators are blinded to answers. Then, a short (< 5 min) recall about oral hygiene methods is proposed to the patient and conducted by the investigator if needed. A brief clinical examination is conducted, and the outcome examiner then collects the clinical data. Data collection is conducted following the same protocol as for the first visit. Results are delivered to both the investigator and the patient, and are stored in both the e-CRF and the patient's electronic healthcare records. The investigator then conducts full-mouth supragingival and juxta-gingival tooth scaling and polishing (Acteon ultrasonic tip number 1 and Newtron LED handpiece, Satelec Acteon, Merignac, France).
Visit 3 At the third visit (T0 + 8 weeks), patients are first asked to complete the same questionnaire about their motivation for and behaviors in oral health they completed at the second visit. Then, a short (< 5 min) recall about oral hygiene methods is proposed to the patient and conducted by the investigator if needed. A brief clinical examination is conducted, and the outcome examiner then collects the clinical data following the same protocol as for the first visit. Results are delivered to both the investigator and the patient, and are stored in both the e-CRF and the patient's electronic health records. At the end of the appointment, the patient is asked to complete a satisfaction questionnaire specially designed for dental care (Dental Visit Satisfaction Scale  [47] ). Again, data are directly entered by the patient into the e-CRF and investigators are blinded to the answers.
Outcome measures Data collection is performed by three blinded, independent, calibrated outcome examiners at 0, 4, and 8 weeks after patient inclusion. For the primary objective (oral hygiene) and the main secondary objective (gingival inflammation) the outcome will be the value of indices collected during the third visit (8 weeks of follow up). Values range from 0 to 100%. Two additional secondary objectives will be also considered: patient satisfaction after 8 weeks, and patient motivation for change after 4 and 8 weeks in each treatment arm. For the first secondary objective (patient satisfaction after 8 weeks), the Dental Visit Satisfaction Scale questionnaire  [47]  comprises 10 multiple choice questions (MCQ) scored on a 5-point Likert scale, and explores three aspects of patient satisfaction: informationcommunication, understanding-acceptance, and technical competence (Additional file 1).
Data collection methods To promote data quality, investigators and outcome examiners, who will assign scores, are trained in the plaque and gingival inflammation indices by means of group training sessions in real-life patients. To evaluate calibration on the primary outcome (plaque control), investigators and examiners are trained using a large number of pictures of teeth; inter-rater agreement is measured using the Kappa coefficient. Group training sessions and inter-rater agreement assessment are conducted before the beginning of patient inclusion. For the primary and the main secondary outcome measures, data collection forms are generated through a public online platform  [48]. For the patient-reported outcomes (remaining secondary objectives), patients enter their answers to the questionnaires directly on a dedicated and password-protected page of the e-CRF.
Statistical methods The statistical unit for analysis will be the patient. All of the patient's teeth are considered for data collection but unerupted, impacted, or fractured teeth are excluded (site-related exclusion criteria). Six sites per tooth are examined. The demographic and clinical characteristics of patients will be described for both the test and control groups with mean and standard deviation or median interquartile ranges for quantitative variables, and number of subjects and percentages for qualitative variables. The analyses will be performed according to the intention-to-treat principle, modified to include only patients with available outcomes. To respond to the primary objective, the mean plaque score in the test and control groups at 8 weeks will be calculated and compared using Student's t test for unpaired data.
The plaque score at the third visit will be modeled using a hierarchical model accounting for the correlation of the measures per patient and any possible inter-practitioner heterogeneity. The model will be adjusted on randomization stratification factors (center of inclusion, patient gender, and tobacco use) as well as the baseline value collected at the first visit. If necessary, other adjustment factors might also be considered. The main secondary objective (bleeding on probing) will be analyzed using Student's t test (nonparametric test whenever relevant). In cases of patient non-compliance with follow-up visits, sensitivity will be analyzed using the last outcome examiner's assessment (last observation carried forward). Additionally sensitivity will be analyzed considering all missing data as equal to the test or control group's mean values for the given visit.
Data monitoring, harms, and auditing The data will be monitored by an independent clinical research assistant who will compare the data entered in the e-CRF with those in the patient's electronic health records. In the case of disagreement, the patient's physician will be asked to clarify the data. No interim analysis is planned. Concerning harms monitoring, specific adverse event forms can be accessed in the e-CRF. Trial management may be audited by the Agence Nationale pour la Sécurité du Médicament et des Produits de Santé (ANSM, French medicines agency) at any time; the audit would be independent of investigators and the sponsor.
When registering a new patient in the text messages database, several steps are needed, and the process takes 5-10 min. While acceptable in a research environment, these extra steps might affect productivity in a private dental practice. Further integration of such systems into various practice management software could help streamline the process. The legislative and regulatory environment should also be taken into consideration. For the video recording, it might be necessary to seek and record patient consent in some settings, as it would be for photographs. Regarding the cloud platform, the solution proposed by the camera manufacturer fully complies with the new European Union General Data Protection Regulation requirements and relies on a certified cloud provider (Microsoft Azure). Similarly, the telephone network gateway is secured, and all communications are encrypted.
Preparation of specimens Cylindrical specimens (thickness: 2 mm, diameter:10 mm) of each material were designed by a universal CAD software (inLab SW 4. 2. 1; Sirona Dental Systems, NY, USA)  [5, 35]. The designed specimens were milled from selected materials by using the subtractive method (inLab MC X5; Sirona Dental Systems, NY, USA). Before milling process of the materials, the equipment was calibrated to minimize errors. All specimens were finalized with a stepwise polishing with the use of discs of grain sizes 2500 and 4000 grit on a rotary machine under wet conditions (Buehler Metaserv Motopol 12; Buehler, Coventry, Great Britain). Then, the specimens were washed in an ultrasonic bath (ZOKOP 6L; Zokop, Glendale, CA, USA) for 10 min at room temperature and embedded into acrylic molds (Duracryl Self-cure; Erk Dental, İzmir, Turkey).
Surface roughness measurement after polishing After polishing, surface roughness (Ra) of all the specimens was determined by a three-dimensional non-contact profilometer (AEP Nanomap-1000WLI; AEP TECHNOLOGY, Santa Clara, CA, USA) in order to avoid surface damaging. Profiles of 9 mm 2 surface located in the different areas of the specimens were measured with an optical resolution of 550 nm. Average of Ra values were calculated with SPIP software (Image Metrology A/S, Lyngby, Denmark) by using at least three measurement results, according to ISO 4287  [36]. In addition, scanning electron microscope (SEM) (Carl Zeiss EVO LS 10; Carl Zeiss NTS, Germany) (10000x magnification) was used to identify surface alterations and porosities for each material. Samples were coated with Au-Pd prior to analysis in order to prevent charging and at least three images were taken for each sample.
Surface roughness and volume loss measurements after wear testing Three-dimensional surface profile images of all specimens were created, and visual analysis of the images was performed with the Average Ra values were calculated. To measure volume loss after chewing simulation, all images were imported to a reverse engineering software (RapidForm XOR3; GeomagicInc, Cary, NC, USA) which combines images into solid work for measurements. Volume loss estimation for each sample was performed by subtracting the volume of solid meshbox of worn specimen from the total volume.
Statistical analysis For each tested material, a sample size of 12 in each group was estimated with α = 5% and 90% power. Fifteen specimens per group were analyzed considering possible damage or technical problem. Statistical analyses were performed using statistical software (SPSS V23; IBM Corp. Armonk, NY). All data were submitted to Shapiro-Wilk test to test the normality of data, and One-way ANOVA was used to compare normal distribution data between groups. The differences between groups were determined by using a Tamhane's T2 from multiple comparison tests. Paired samples t-test was used to compare the Ra values for each material group separately before and after chewing simulation. The relationship between increase in surface Ra and volume loss were determined by Pearson correlation analysis.
On physical examination, the cat was quite alert and responsive, with a body condition score of 5/9. A left-sided tongue deviation caused by a 2 cm fluctuant, non-painful mass was observed (Figure  1a ). The mucous membrane over the soft palate was eroded by the deviated lateral edge of the tongue (Figure  1b ). The remainder of the clinical examination was unremarkable. A tentative diagnosis of salivary mucocoele, rather than neoplasia, abscess, foreign body or granuloma, was considered reasonable. A minimum laboratory database (microhaematocrit, total proteins, blood urea nitrogen, creatinine) was unremarkable. A CT scan was performed under general anaesthesia in an attempt to determine which glands were affected and possibly to identify an aetiology. A large, welldefined mass with fluid density, with no contrast enhancement after intravenous (IV) injection, was observed within the right mandibular soft tissues.
Homology Modeling of PknB Catalytic Domain and PASTA Domains The catalytic domain of PknB St (residues 3-274) was homology-modeled using the model-building software Modeller (version 9. 18)  (Sali and Blundell, 1993). The crystal structure of the catalytic domain of PknB from M. tuberculosis (PknB Mtb 1O6Y pdb id) in complex with AMP-PCP served as 3D template  (Ortiz-Lombardia et al. , 2003). Hundred models were generated. A final model of PknB St was selected upon the lowest score function values (DOPE score) and best stereochemistry, checked by Molprobity  (Chen et al. , 2010). Subsequently, a molecule of ATP was docked in the binding pocket of this model of PknB St , with Autodock tools, using a grid box, centered on the ATP-binding pocket, and the genetic algorithm of Lamarck  (Morris et al.
, 2009). To validate this procedure, a crystal molecule of AMP-PCP was previously redocked in the ATP-binding pocket of PknB Mtb using similar gridbox and algorithm. Similarly, the three PASTA domains (residues 363-579) of the extracellular domain (ECD) of PknB St were homology modeled using Modeller, from the PASTA-domain crystal templates of PknB Mtb (pdb id 5E12,  Prigozhin et al. , 2016)  and PASTA from Ser/Thr protein kinase (STK1) of Staphylococcus aureus (pdb id 3M9G,  Paracuellos et al. , 2010)  as 3D templates. A final model of PASTA-ECD St was chosen upon lowest score functions and subsequently checked by Molprobity. Using HHpred 2  (Zimmermann et al. , 2018)  the residues 275-362 that correspond to the juxtamembrane and the transmembrane segments, showed no structural homolog so that this portion could not be modeled.
Including regeneration (98% buffer B), one run took 137 min. Ionization (1. 6 kV ionization potential) and capillary transfer (275 • C) were performed with a liquid junction and a capillary probe. Peptide ions were analyzed using Xcalibur 3. 1. 66. 10 with the following machine setup in CID (Collision Induced Dissociation) mode: (1) full MS scan in Orbitrap (scan range [m/z] = 400-1500) and (2) MS/MS using CID (35% collision energy) in Ion Trap (AGC target = 4. 0 × 10 3 , max. injection time = 300 ms, data type = centroid). Analyzed charge states were set to 2-7, the dynamic exclusion to 60 s and the intensity threshold was fixed at 5. 0 × 10 3. The peptide separation for the phosphoproteome analysis was achieved at 300 nl/min with a linear gradient from 0 to 35% buffer B for 48 min and 35-45% for 5 min.
One run took 65 min, including the regeneration step at 98% buffer B. Ionization (1. 6 kV ionization potential) and capillary transfer (275 • C) were performed with a liquid junction and a capillary probe (SilicaTip TM Emitter, 10 µm, New Objective). Peptide ions were analyzed using Xcalibur 3. 1. 66. 10. In HCD (Higher-energy Collisional Dissociation) mode the machine settings were as follows: (1) full MS scan in Orbitrap (scan range [m/z] = 400-1600) and (2) MS/MS using HCD (30% collision energy) in Orbitrap (AGC target = 5. 0 × 10 4 , max. injection time = 55 ms, data type = centroid). Analyzed charge states were set to 2-5, the dynamic exclusion to 40 s and the intensity threshold was fixed at 10 4. The MS proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE  (Vizcaino et al.
Data Analyses The S. thermophilus LMD-9 database (NCBI, version 2010, 1710 entries) was searched by using X!TandemPipeline version 3. 4. 2 (Langella et al. , 2017). In the database used, the proteins where initially annotated using a Blast against the genomes of the strains CNRZ1066 and LMG18311 (which were the two first strains sequenced) with variable e-values which are not always very high and which consequently must be considered carefully. The proteome identification was run with a precursor mass tolerance of 10 ppm and a fragment mass tolerance of 0. 5 Da. Enzymatic cleavage rules were set to trypsin digestion ("after Arg and Lys, unless Pro follows directly after") and no semi-enzymatic cleavage rules were allowed. The fix modification was set to cysteine carbamidomethylation and methionine oxidation was considered as a potential modification.
In a second pass, N-terminal acetylation was added as another potential modification, whereas all other previous settings were retained. The identified proteins were filtered as follows: (1) peptide E-value < 0. 05 with a minimum of 2 peptides per protein and (2) a protein E-value of <10 -4. In routine analyses, protein identification was associated to a function prediction obtained via an elementary Blast toward two S. thermophilus genome sequences (LMG13811 and CNRZ1066). This function prediction need to be carefully considered. A more in-depth Blast was realized against the whole NCBI database for the proteins which were identified as phosphorylated. For the phosphoproteome identification, the precursor mass tolerance was set at 10 ppm, while the fragment mass tolerance was set at 0. 02 Da.
Proteins and phosphoproteins were quantified by the spectral counting (SC) method. MassChroQ "Black Caiman" version 2. 2. 1  (Valot et al. , 2011)  was used for the alignment of retention time. The range for peak detection was set to 10 ppm with a detection threshold ranging from 30,000 to 50,000. MassChroqR (version 0. 3. 7), an R package developed by PAPPSO platform 5  was used to check the quality of data and practice statistical analysis in proteomic. The abundance in number of spectra was modeled using the following generalized mixed model (GLM) with a Poisson distribution as already described  (Millan-Oropeza et al. , 2017). Protein abundance change were detected by analysis of variance (ANOVA) using a Chi-square test. The obtained p-values were adjusted for multiple testing by the Benjamini-Hochberg approach  (Benjamini and Hochberg, 1995).
Adjusted P-values obtained from ANOVA for the proteome was considered significant below a value of 0. 05. For phosphoproteomics, quantification was performed at the peptide level and not at the protein level. In this case, the number of spectra associated to each peptide is generally low (i. e. , comprised between 0 and 2), which prevent proper statistical analysis of spectral counting data. We thus focused on the phosphopeptides showing presence/absence variations between the WT and the Mut strains. To ensure robustness of the results, a peptide was considered as present when detected with at least one spectrum in all the four replicates and absent when not detected in none of the four replicates of a strain. The proteins identified as included in the phosphoproteome have been blasted against the non-redundant NCBI database (update 2018/07/07) for a more specific annotation.
Chaperonin and stress response proteins constituted another important group of phosphorylated proteins. Finally, we identified proteins involved cell wall/membrane/envelope biogenesis, intracellular trafficking and secretion, inorganic ion, lipid and amino acids metabolisms and energy production and conversion. Both the serine/threonine (PknB) and the putative tyrosine kinases contained phosphorylated peptides. Only one PknB amino acid (threonine 291) was found phosphorylated in the four WT replicates. However, because the modeling step identified a TQT motif that needs to be phosphorylated for a fully active kinase in M. tuberculosis and that is conserved in S. thermophilus, we specifically looked at this part of the protein. In our dataset, we identified one peptide including this TQT motif and that was found phosphorylated but only in one replicate and was therefore not retained with our stringent parameters.
We therefore calculated for each strain the percentage of cells that growth on plate after freezing without any additive. Unexpectedly, the mutant exhibited a higher survival rate (73%) than the wild type strain (9%). Longer chains could have a protective effect against a freezing stress. The proteome analysis, realized in one culture condition (exponential phase in rich M17 lac medium) on a total bacterial extract, allowed to identify 891 proteins on the basis of at least two peptides per protein (listed in Supplementary Table  S2 ) representing half of the theoretical proteome. Based on spectral counts, no statistically significant difference in protein abundance was found in our data set except for PknB that was no more detected, as expected, in the mutant. Among the proteins identified, 82% are predicted to be cytoplasmic  (LocateP, Zhou et al.
Methods This study was conducted with patients from the oral mucosal pathologies' consultation of two separate hospital departments (Oral Pathology Department APHP, Henri Mondor Hospital -Créteil, Hôpital Bretonneau-Paris). The cohort of patients is composed of six non-smoking women, aged 4 to 60 years, in good health except for a balanced type 2 diabetic female patient, and a healthy non-smoking male who is Caucasian. The five female patients are Caucasian, the other one is from Iran. This systematic review was elaborated in accordance with the PRISMA guideline  [6]. MEDLINE, Web of Science, Embase and Cochrane Database of Systematic Reviews search was conducted of all relevant literature until March 2019 using Mesh, and the following keywords: Lingual OR Tongue AND papilloma, Lingual OR Tongue AND Squamous papilloma, Lingual OR Tongue AND Horn Lingual OR Tongue AND Cornu.
Exclusion criteria • No precise description of the clinical and or histopathological features. Data were collected independently by two authors (Frederick Gaultier, Sophie-Myriam Dridi) and definitively included by these two authors (Frederick Gaultier, Sophie-Myriam Dridi), and all benchmark ultra, closed system, compliance with manufacturer's standards, kit/ultraview, secondary antibody coupled to HRP multimer, primary antibodies Ki-67 pre-diluted 30-9 Roche (Ki67) and P16 INK4a pre-diluted E6H4 Roche (P16). As only seven patients were treated, no statistical analyses comparing preoperative and postoperative values were conducted. As this is the first study, to our knowledge, to describe a clinical case series, the number of patients included is very small, thus we are not able to establish the prevalence of the lingual horns.
Outcome: first undescribed serial clinical cases with clinical and histopathological characteristics The database search yielded 1585 references, including 954 from PubMed/MEDLINE, 491 from Web of Science, 140 from Embase, and 0 from Cochrane Database of Systematic Reviews. Following the selection of studies according to the inclusion and exclusion criteria and the removal of duplicate articles, full versions of 15 articles were selected for reading (Figure  1 ). After reading, 4 studies [2-5] met the inclusion criteria and were selected for the final analysis. Thus, 10 studies were excluded  [7] [8] [9] [10] [11] [12] [13] [14] [15] ; the reasons for exclusion are specified in Figure  1. The conventional histology was completed by a dual immunhistochemistry staining Ki67 / p16 (Automate ventana The conventional histology (Figures  3A  and 3B ) was completed by a dual immunhistochemistry staining (Ki67 / p16) because of the presence of some koilocyte-like cells within the epithelium (Figure  3C ).
Collection of data Collected data included: baseline patient (clinical and demographic data) and tumor characteristics (pathological and radiological data), chemotherapy regimens, surgical characteristics, outcomes (first date of relapse or progression, date of death or date of last news). Resection margins were considered as clear (R0) or not (microscopically involved (R1) or macroscopically intralesional (R2)). All available radiological exams (CT-scan, Magnetic resonance imaging (MRI)) in each center were independently reviewed by two expert radiologists in order to collect tumor size before and after neo-CT. Radiological responses were assessed according to change in maximal tumor diameter (Recist v1. 1 criterion). Tumor histological response to neo-CT was collected from pathology reports, as Pathologists routinely evaluate it using the Rosen's criteria to assess the percent of necrotic tumor cells in the surgical specimen after neo-CT (good response if > 90% of necrosis on the surgical specimen)  [11, 28]  This study was approved by Institutional review board and done in accordance with the Helsinki declaration.
Statistical analyses The retrospective design of this study and the scarcity of the disease prevented us to calculate a population to confirm statistical hypotheses. Binary data were described by ratios. Quantitative data were described using median and range. Correlations between binary variables were assessed using Fisher exact test. Because of the limited number of patients included, correlations between binary and quantitative variables were assessed using non-parametric Wilcoxon test. Follow-up was estimated using the reverse Kaplan-Meier estimation method (1-KM). Survival curves were performed using the Kaplan-Meier method and analyzed using two-sided log-rank test. Exploratory survival analysis was performed with Cox logistic regression model. Proportional hazards assumption was tested for each analysis.