dataesr/scientific-paragraphs-categorization huggingface dataset:
5 mandibular bone adjacent to the first molar was obtained from Smoc2 -/-mutants and their respective wildtype (WT) controls. Following RNA extraction with the RNeasy Micro-kit, mRNA-seq library preparation was achieved according to Illumina protocols. Sequencing for each group was performed in triplicate. Sequence mapping relative to the mm10/NCBI37 mouse reference genome were performed using Tophat. Only when unique aligned sequence reads were obtained was gene expression quantification performed using HTSeq-0. 6. 1 (described at https ://www-huber. embl. de/users /ander s/HTSeq /doc/overv iew. html). For each transcript, reads per exon kilobase of model per million sequence reads (RPKM) were then converted to raw read counts, then added for each gene locus. Data normalization was performed as described  53  and resolved with the DESeq Bioconductor package.
as part of a French Ministry of Health National Program for Clinical Research, PHRC 2008 HUS (Strasbourg University Hospital) No. 4266 and in the INTERREG IV Offensive Sciences A27 "Orodental manifestation of rare diseases" EU funded (ERDF) project. The two cousins and their family members gave informed written consent and documents for the D[4]/phenodent registry, a Diagnosing Dental Defects Database [see www. pheno dent. org, to access assessment form], which is approved by CNIL (French National commission for informatics and liberty, number 908416). The clinical study is registered at https ://clini caltr ials. gov: NCT01746121 and NCT02397824, and with the MESR (French Ministry of Higher Education and Research) Bioethics Commission as a biological collection "Orodental Manifestations of Rare Diseases" DC-2012-1677 within DC-2012-1002 and was acknowledged by the CPP (person protection committee) Est IV December 11th 2012.
Acknowledgements This work was supported by the  EU-funded projects (ERDF)   A27  " Oro-dental manifestations of rare diseases " in the framework of the  RMT-TMO Offensive Sciences initiative INTERREG IV and INTERREG V Nr. 1. 7RARENET , the  Institut d'Etudes Avancées (Institute of Advanced Studies) de l'Université de Strasbourg  (USIAS Fellows 2015), and the grant  ANR-10-LABX-0030-INRT  managed by the  Agence Nationale de la Recherche  under the  frame program Investissements d' Avenir   ANR-10-IDEX-0002-02. Sequencing was performed by the GenomEast/IGBMC high-throughput sequencing platform, supported by the  France Genomics National Infrastructure , funded as part of the  Investissements d' Avenir program  ( ANR-10-INBS-0009 ). SM was a recipient of a  Junior Research Fellowship  ( Embassy of France in Thailand, Service de Cooperations and Cultural Actions, 2018 ), a  Franco-Thai fellowship  in collaboration with  Khon Kaen University  from 2014-2017 during his Master's and Ph.
Analysis plan Ultimate stress at fracture and Young's modulus (E) were evaluated using formulae of linear elasticity: r u ¼ F u S (1) r ¼ Ee (2) where r represent the stress (Pa), F the load in (N), S the section area (m 2 ), E is the Young's Modulus (Pa), and e the strain (no unit). Subscript u stand for ultimate at fracture. Section area and displacement of some landmarks were assessed using 3D micro-CT images at each step by using ImageJ # software.
Quantification of Alveolar Bone Resorption To quantify the extent of alveolar bone loss, the maxillae were scanned using a micro-computed tomography (mCT) equipment (SkyScan 1272; Bruker, Belgium), as previously described  (18, 32). 3D-digitized images were generated using a modified conebeam algorithm in a reconstruction software (Nrecon software, Bruker, Belgium). Alveolar bone loss was quantified using two methods: (a) by measuring the linear distance from the cementenamel junction (CEJ) to the alveolar bone crest (ABC) and (b) by quantifying the percentage of remnant alveolar bone, by considering the average of untreated mice bone levels as 100%, as previously described  (33, 34). In turn, the CEJ-ABC linear distance was quantified in (a) the interdental area comprised between the first and second molar and (b) the distal surface of the distal root of the first molar.
Flow Cytometric Data Analysis by tSNE T-distributed stochastic neighbor embedding (tSNE) analysis of 11-parameter flow cytometry data obtained from untreated mice was performed using the FlowJo software (BD Biosciences, USA). Samples were randomly downsampled to 10,000 events per sample, and analysis was run on equivalent numbers of events per sample. Following downsampling, 11-parameter samples were concatenated and visualized with tSNE (Barnes-Hut implementation) in FlowJo. The following parameters were tuned in preliminary experiments and then used as default values: iterations, 550; perplexity, 40; eta, 200; theta, 0. 5. All parameters, except for lineage marker CD45 and DAPI live/dead marker, were included in the analysis.
Flow Cytometry of Stimulated Splenocytes In order to analyze the surface expression of co-stimulatory molecules CD40 and CD80 in B lymphocytes, dendritic cells, and macrophages obtained from total splenocytes, the following antibodies were used: CD19 (6D5), MHC-II (M5/114. 15. 1), CD11c (N418), CD11b (M1/70), Ly6C (HK1. 4), CD80 (16-10A1), and CD40 (HM40-3) (eBioscience, Thermo Fisher Scientific, USA; Biolegend, USA; and Abcam, England). Live/ Dead Fixable viability dyes (eBioscience, USA) were used to exclude dead cells. All the experiments were acquired using a FACS LSR Fortessa X20 flow cytometer (BD Biosciences, USA) and analyzed with FlowJo software (BD Biosciences, USA).
Statistical Analysis Statistical analysis was performed using the GraphPad Prism v. 4. 01 software (GraphPad Software, Inc. , USA). Heatmaps from qRT-PCR fold-change data were done in Excel v. 16. 39 software (Microsoft, USA). The normality of data distribution was established using the Kolmogorov-Smirnov test. When a parametric analysis was carried out, the statistical differences were determined using the ANOVA and the Tukey or Holm-Sidak post-hoc tests. When a nonparametric analysis was carried out, the statistical differences were determined using the Kruskal-Wallis and Dunn tests. A difference was considered significant when p < 0. 05.
ACKNOWLEDGMENTS We thank  Dr. Keith Mintz  and  Dr. Daniel Danforth  (Microbiology and  Molecular Genetics ,  University of Vermont ) for providing us with the bacteria wild-type and mutant strains. We are also grateful to  Ms. Darna Venegas  and  Daniela Salinas  ( Microbiology Laboratory, Faculty of Dentistry, Universidad de Chile ) and  Dr. Jonatan Rodriguez  ( Department of Microbiology, Tumor and Cell Biology, Karolinska Institute ) for sharing their expertise on microbiology work. We thank the  Plataforma Experimental Bio-CT  from  Universidad de Chile  ( FONDEQUIP EQM150010 ) for their support with the mCT analysis.
Analysis After the survey closure, the Excel sheets were downloaded, cleaned, and imported to SPSS version 23. 0 for analysis (IBM Corp. , Armonk, N. Y. , USA). Frequencies, percentages, means, and standard deviations were calculated for descriptive statistics. Prior to PCA, the suitability of data for this analysis was assessed. The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy was 0. 91 which is above the recommended value of 0. 6. The P-value of Bartlett's test of Sphericity  [32]  was statistically significant (P< 0. 0001), supporting the use of PCA. Major attitude components were, therefore, extracted from the 16 items in section 2 of the survey. Extraction was based on eigenvalues >1. Varimax rotation with Kaiser normalization was used and loading coefficients < 0. 4 were suppressed to facilitate interpretation of factor loading.
Regression coefficients of the factors extracted from the PCA were saved to the dataset and used as explanatory variables for further analysis. Two types of outcomes were assessed. The first was the stress levels based on the categories of IES. These were included in a multilevel ordinal logistic regression where the explanatory variables were the major worries/ attitudes derived from the PCA, the ratio between the number of COVID-19 deaths to cases per million at country level (fatality rate)  [33]  and whether the participant received training to manage public health emergencies. The model controlled for confounders (personal and professional background factors) which were introduced as fixed effects and country was included in the model as a random effect factor. The second set of outcomes was the scores indicating change in behaviors due to the COVID-19 pandemic (frequent handwashing and avoiding crowded places).
Also, the study used validated tools with high internal consistency and/ or factor loadings. In addition, the study captured the psychological impact of the pandemic at its early stages thus providing important and valuable information that can be used in designing support systems for dental academics. The study, however, had some limitations. First, data were collected at different stages of the pandemic in various countries and this may have confounded the assessment of the level of stress. In addition, the study was cross-sectional and thus, cannot prove causality. Also, the response rate was low similar to previous research  [35]  and this may be attributed to the psychological impact of the pandemic with resulting possible underestimation of the level of stress reported in the study since those with higher levels of stress may be more likely to ignore the survey.
Data Data were retrospectively collected in medical observations with a hospital full-text research software dedicated to medical observation search from patients who were treated from January 2007 to January 2018 with microvascular free fibula flap (MFFF) and dental implants. Key words used for collecting data were: dental implants, free fibula flap, mandibular reconstruction. Inclusion criteria were: reconstructed mandible with MFFF, placement of dental implants on the flap. Exclusion criteria were: lack of saved data, patients who were lost to follow-up and patients who did not meet inclusion criteria. Collection of data was standardized thanks to a form, which was completed by 2 independent reviewers. Data recorded were: gender, age, reason for mandibulectomy and bone reconstruction, previous radiotherapy on the MFFFF, number of implants on the reconstruction, length and number of segments of the reconstruction, height of resorption, type of prosthetic rehabilitation (fixed or removable and implant connexion), quality of soft tissues, and follow up.
Bone resorption measurements Peri implant bone resorption was defined as the distance between the implant collar and the crestal level of the bone. The criteria "no resorption" was proposed when bone appeared at the implant collar (Fig. 1 ). Measurements were taken on panoramic radiograph, on the postoperative orthopantolomography and on a later control radiograph. Peri-implant bone resorption was considered from any visible crater-like shape. Measures were taken on the mesial and distal aspects of the implants with, as much as possible, an orthogonal incidence of the X-rays. They were performed by 2 different operators with the Image J ® software. The software allows precise measurements on a 1/1 scale. Resorption was classified as light (<0. 8 mm) to moderate (0. 8-1. 5 mm) or severe (>1.
Results 85 clinical reports were reviewed for 39 retained; the reasons for exclusion were missing data (panoramic radiograph or missing clinical reports). 21 patients presented with PIBR, and 18 without. Patients 13 women and 26 men were included, aged from 26 to 77 (mean: 55. 97). Ninety-eight implants were placed on the fibula flaps, ranging from 1 to 5 (mean: 2. 51). Reasons for mandibular reconstruction were malignant tumor, i. e. epidermoid carcinoma or sarcoma for 21 patients (53. 8%), benign tumor i. e. ameloblastoma, fibroma or chronic osteitis for 7 patients (17. 9%), osteoradionecrosis for 7 patients (17. 9%), trauma for 4 patients (10. 3%).
Implants One of the limitations of the study was that measurements were performed on panoramic radiographs, and thus could not be precise for the reconstruction length, especially when the anterior arch of the mandible was included. Furthermore, this type of radiograph may not report a buccal or lingual bone resorption aligned with an implant. However, this type of radiograph remains valuable for evaluating PIBR  [8]  and to assess the point of bone attachment to implants  [9] , especially in case of very atrophic mandibles with unfavorable imaging conditions  [10]. Using ImageJ® software also allows a better measurement precision.
Other bias As several data lacked, chronological evaluation could not be performed for each patient. The type of dental rehabilitation was not recorded either in this retrospective study. The prothesis defines the different forces applied on implants which contribute to determine their durability. Furthermore, short follow up does not allow significant conclusions. Patients treated with MFFF followed by dental implants only represent a small sample of the population, which explains the small number of clinical reports included, and the difficulty to establish relevant statistics.
Economic background French oral health spending in 2017 amounted to approximately  D 11. 3  Billion. The National Health Insurance (NHI) and other government funds covered 37 % (D 4. 2 Billion), the Complementary Health Insurers (CHIs) 41 % (D 4. 6 Billion), and the remaining 22 % were out-of-pocket (OOP) payments from patients were D 2. 5 Billion (Fig. 1  and ANNEX A ). According to the National Medical Health Data system (SNIIRAM Database, 2018 extraction), the costs of dental prostheses which were, for the majority of patients, partially reimbursed but with no price ceilings, varied quite drastically from region to region and amongst General Dentists. For example, the price of a ceramic 'white' dental crown could vary from under D 500 to over D 1000 depending on the dentist. Higher costs in areas with a higher concentration of dentists have been attributed to lower ratios of patients with needs, higher overheads and supplierinduced demand  [23, 24].
Aim: This systematic review aimed to evaluate the use of three-dimensional (3D) printed bone models for training, simulating and/or planning interventions in oral and cranio-maxillofacial surgery. Materials and methods: A systematic search was conducted using PubMed® and SCOPUS® databases, up to March 10, 2019, by following the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) protocol. Study selection, quality assessment (modified Critical Appraisal Skills Program tool) and data extraction were performed by two independent reviewers. All original full papers written in English/French/Italian and dealing with the fabrication of 3D printed models of head bone structures, designed from 3D radiological data were included. Multiple parameters and data were investigated, such as author's purpose, data acquisition systems, printing technologies and materials, accuracy, haptic feedback, variations in treatment time, differences in clinical outcomes, costs, production time and cost-effectiveness.
Search strategy Medline (PubMed) database and Scopus database were searched up to  March 10, 2019   This process only selected articles that had search terms in the title or in the abstract without any restriction on language. The search was also launched with the following MeSH (PubMed) terms: ("Surgical Procedures, Operative" OR "Teaching") AND "Printing, Three-Dimensional" AND "Models, Anatomic" AND "Head". Other interesting original research articles were added through manual search.
Science mapping A science mapping analysis of subject domains was performed by using keyword co-occurrence networking on VOSviewer (free software, version 1. 6. 15, Centre for Science and Technology Studies, Leiden University, The Netherlands, 2017). A network analysis of the Pubmed MeSH keywords was generated from the matrix of retrieved papers (threshold value at 90). The MeSH termsdocument matrix allowed to measure document similarities between clusters of topics.
Study analysis All the retrieved references, after launching the search algorithm, were managed using Endnote® Abstracts of studies retrieved using the search strategy and those from additional sources were screened independently by three authors (M. M, A. N. and S. C) to identify studies that potentially met the inclusion criteria. Papers fulfilling the inclusion criteria, and those presenting insufficient data in the title and the abstract to make a decision, were selected for full analysis. After reading the full texts, the proper articles were included in an evidence table. Any disagreement over the eligibility of studies was resolved through discussion and consensus among the authors.
Search general results After database screening and removal of duplicates using Endnote®  [21] , 1157 articles were identified. After abstract screening, 119 studies were selected. After full text reading, 64 articles were selected, plus 5 other articles found among the related ones found by additional manual search (Fig. 3 ). The main reason for excluding articles was a content not addressing AM models issues. Many excluded articles dealt with analogic models, virtual models or perfusion-based models, or related to the orthopedic and veterinary fields. Six articles were not written in English/French/Italian. Eight articles were excluded after reviewers' discussion: three authors involved commercial models  [22] [23] [24] , one article dealt with papercraft models  [25] , one article dealt with a silicon model molded on a 3D printed mold  [26]  and 3 articles dealt with other surgical fields (orthopedics  [27, 28]  and veterinary sciences  [29] ).
Image acquisition and processing Image acquisition and processing are the first steps to create a 3DP model (Table  3 ). The most frequently used radiological exam was the CT, followed by cone beam computed tomography (CBCT) and MRI. Software was used to process the radiological data. The most frequently used were Mimics® (Materialise, Leuven, Belgium), followed by OsiriX® (Pixmeo, Geneva, Switzerland) and 3D Slicer® (Surgical Planning Laboratory, Isomics Incorporated, Cambridge, USA). Most of the authors did not specify entirely their digital work-flow to create the STL printable file, making it difficult to reproduce the procedure properly.
Cost Cost remains an important parameter that cannot be ignored. There are multiple additional costs in terms of software, printers, printing materials, operators and training hours to produce an in-house 3DP model. In order to print a model, the first step is to process the DICOM file into an STL file. Among all the commercial software available, the commercial software package Mimics®, was the most widely used software, despite a relatively high cost when compared to others. Many free or open source software are available, like ITK-Snap®, Slicer® or InVesalius®  [31, 35, 39, 40, 60, 79]. OsiriX® possesses a free version (demo) that allows to export STL renderings  [12, 46, 47, 52, 63]. ME printers were the cheapest printers, with reported prices ranging between 2500$ and 3000$  [47, 82].
However, as previously mentioned, these showed limitations in terms of accuracy. PLA and ABS were the cheapest reported materials  [32, 37, 39, 47, 52, 82]. PC cost was reported to range from 105$ to 155$ for the production of a mandible  [43, 57]. The cost for a temporal bone model using BJ was around 400$  [67]. MJ models costs ranged from 270$ to 1000$. One team affirmed that these models were too  To generate a rapid-prototyped temporal bone model from computed tomography (CT) data with a specific focus on internal anatomic fidelity. Three point bending tests, using a Texture Analyzer® were performed to determine the elastic modulus and yield point. Thanks to a 3-axis accelerometer the drill vibration during the drilling was evaluated on different materials. The printed bone models were highly realistic.
Design of the study This was a prospective cross-sectional paired diagnostic study. All patients were observed twice, in a random order for each subject, by two independent operators blinded to each other. Conventional oral examination was first carried out under IL. This was followed by AF examination using the VELscope system®. The two operators examining each patient had a different experience. The junior was the less experienced and the senior was the more experienced. Five operators participated to the study. The study was approved by institutional Research and Ethics Committees of University Hospital of Bordeaux, France (2010-A00262-37) and it was registered on ClinicalTrials. gov (NCT01167790).
Acknowledgements. The authors acknowledge  D Maldonado  for data management,  H Savel  for participation to the study design,  M Meddeb  as clinical research assistant,The " Direction de Recherche Clinique du CHU de Bordeaux " for technical assistance and the  French National Cancer Institute (InCa)  for funding of the study (Convention de recherche n°2009-348-Projet FLUO-K).
Bonding of resin composite fillings, for example following root-canal treatment, is a challenge because remaining gaps grow and lead to failure. Here, phasecontrast-enhanced micro-computed tomography (PCE-CT) is used to explore methods of non-destructive quantification of the problem, so that countermeasures can be devised. Five human central incisors with damaged crowns were root-filled followed by restoration with a dental post. Thereafter, the crowns were rebuilt with a resin composite that was bonded conventionally to the tooth with a dental adhesive system (Futurabond U). Each sample was imaged by PCE-CT in a synchrotron facility (ID19, European Synchrotron Radiation Facility) with a pixel size of 650 nm. The reconstructed datasets from each sample were segmented and analysed in a semi-automated manner using ImageJ.
Image analysis The high-resolution reconstructed datasets characteristically contained about 2100 slices orthogonal to the long axis of the tooth. Each dataset occupies 80 Gigabytes or more of disk space. Data were visualized using ImageJ and Amira. To isolate debonding and interfacial gaps, the datasets were processed using the free extension package MorpholibJ for ImageJ  (Legland et al. , 2016). As a first step, a threshold was defined using the grey value range corresponding to gaps in the restoration [Fig. 4(a) ]. The resulting binary images had their different sets of connected pixels and voxels individually numbered and labelled using the 'Connected components Labelling' algorithm. The different components localized to the adhesive layer were then visually selected, discarding the irrelevant (outside of the interface) labels by using the 'Select Labels' function of MorpholibJ.
Results Laboratory mCT scans generated datasets that reproduced the approximate geometry and the main components of the tooth restoration within the root and the reconstructed crown. In such data, however, there was no difference in contrast between the resin composites used for crown reconstruction and the resin cement (Fig. 5 ), nor was it possible to distinguish the adhesive polymer layer or any gaps therein. Furthermore, the interfaces between restorative materials and tooth substrate were blurred, making it impossible to evaluate the extent of bonding between the tooth tissues and the dental materials. PCE-CT at sub-micrometre resolution provided 3D datasets with an impressive contrast and a remarkable amount of detail (Figs. 5 6 7 ). The micromorphology of the tooth and restoration were fully visible, revealing micrometre-diameter dentin tubules, highlighting the presence of fillers in the different resin composites and well reproducing the layout of single fibres within the fibreglass post.