dataesr/scientific-paragraphs-categorization huggingface dataset:
Discussion 7] [18]  Our findings demonstrate that these cancers also have high and heterogeneous incidence and mortality rates in South American countries; however, because of the low number of population-based cancer registries that are continuously updated in this region, it is expected that the official incidence numbers may be underestimated in this large geographic area. Data retrieved from the Brazilian National Institute of Cancer revealed that oral cavity cancer accounted for 61%      (31,583) of the cases analysed, whereas 39% (20,222) affected the oropharynx in the period 2000-2010. Moreover, using data from the HCR databases available in the files of the Sa ˜o Paulo Cancer Registry (FOSP/Brazil), a slight increase in the number of oral cavity and oropharynx cancers was observed.
6, 25 In this study, we found that mortality trends are decreasing by about 2. 5% in South America, although in some regions like in Brazil and Peru there still is an increase among females. An important issue regarding mortality trends in South American public databases is the impossibility of distinguishing data between the oral cavity and oropharynx, because both sites are aggregated as one unique topography (e. g. lip, oral cavity and pharynx) (IARC, 2015). Therefore, it is difficult to verify the real mortality trends regarding oral cavity and oropharynx cancers in this population. Although oral cavity and oropharynx cancers are wellknown diseases, access to large and representative public databases to appropriately understand their incidence, distribution, and clinicopathological characteristics in South American countries is still insufficient or completely absent in some regions.
In Brazil, for example, the INCA gets cancer data from the population-based cancer registries and HCRs (INCA, 2013) with the objective of gathering all available data and creates a reliable database. However, not all data are regularly updated, and not all hospitals and states send data to this centre, making the results incomplete. As a consequence, official data on oral and oropharynx cancers incidence in Brazil are very likely to be underestimated. Another Brazilian public database, the FOSP collects data from all cancer centres of Sa ˜o Paulo state, the most populated and economically developed in Brazil. This database seems to be more reliable, because it is constantly updated and has a unified system to collect data; however, it represents only one state of the whole national territory, and it is formed by data from patients from Sao Paulo and also from different parts of Brazil to receive treatment in Sa ˜o Paulo.
Translational Value In conclusion, the incidence of oral and oropharynx cancers is very heterogeneous among South American countries, whereas mortality rates are decreasing in most of them. However, this study showed that the development and improvement of national cancer databases are highly desirable and necessary to better understand the characteristics and distribution of these lesions in South America, because current databases do not seem to provide reliable data. These improvements could posteriorly allow the development of more effective public strategies to deal with oral cavity and oropharynx cancers.
cancers for South America were obtained from the public databases of the Cancer Incidence in Five Continents (CI5) publication of the International Agency for Research on Cancer (IARC) volume IX (period 1998-2002) for population-based cancer registries of Bahia Blanca (Argen- tina); Brası ´lia, Cuiaba, Goiania, Sa ˜o Paulo (Brazil); Chile; Colombia; Costa Rica; Ecuador 14 and volume X (period 2003-2007) for the population-based cancer registries of Bahia Blanca, Cordoba, Mendoza, Tierra del Fuego (Argentina); Ara- caju, Belo Horizonte, Cuiaba, Fortaleza, Goiania, Sa ˜o Paulo (Brazil); Valdivia, Provincia Bio Bio, Antofagasta (Chile); Cali, Bucaramanga, Manizales, Pasto (Colombia); Costa Rica; Villa Clara (Cuba); Quito and Cuenca (Ecuador) (available at: http://ci5. iarc. fr/CI5I-X/Pages/download.
However, the mere communication of esthetic information is often insufficient. These data can be supplemented and transmitted to the laboratory with the aid of the Ditramax ® system (Figures  2a, b, c ). This system allows esthetic reference lines of the face to be recorded and transferred onto the plaster model, thereby facilitating the creation of prostheses. This tool can also be used throughout the diagnostic phase when developing the prosthetic project, when creating temporary teeth, or even in the final phase of development of custom prostheses. Ditramax simplifies the job of the prosthetist by using photographic data (age, sex, facial type) and occlusal data of the patient, and allows the number of trial sessions necessary to correct the shapes and axes of the prosthetic teeth to be decreased.
3D simulation 20 Planning software has been developed for each discipline; however, we will be focusing on multidisciplinary software programs (Invivo 5 ® by Anatomage Dental, SimPlant OMS ® by Materialise Dental, Maxilim® by Medicin, and Dolphin 3D ® from Dolphin Imaging). These software programs are capable of (Figures  4, 5 ): -Cephalometric analysis in 2D and 3D with integration of telera-diographs of the face and profile (Figure  6 ); -Calculation of angles, lengths, and bone densities in Hounsfield units; -3D analysis of airways before and after simulations; -Highlighting and marking of anatomical elements such as the mandibular nerve, protrusion of the mental foramen, descending palatal artery, sinus, etc. ; -Segmentation of different parts (sinus, maxillary airways, mandible, virtual extractions); -Simulation of tooth displacement (integration of the orthodontic setup);.
Digital workflow is applied at every stage of our plan, including the diagnostic imaging, intraoperative, and prosthetic restoration phases. The consolidation of digital datasets in implantology has allowed for massive progress in the diagnosis and treat-CONCLUSIONS ed in cases of inflammation with low pressure (<20 mg). Over the course of the second year, the frequency of maintenance visits must be determined based on the presence of risk factors with a special program tailored to the patient's profile (such as general health, smoking habit), the type and extent of the edentulism treated, the presence of parafunction or dysfunction, and the state of the remaining teeth. In patients with a history of periodontitis or peri-implantitis, quarterly visits should be scheduled. Biannual visits over 2 years will be sufficient for patients without any medical history and will become annual after the first 2 years.
A metrological protocol is needed to perform the fit adaptation measurement. The objective is to evaluate the gap between the prepared tooth coping and the prosthesis coping on the basis of dimensional criteria described in Section 3. 2. As the best fit adaptation measurement is evaluated through the dimensions of the gap between the tooth preparation coping and the prosthesis coping, it is necessary to access the gap volume. As the prosthesis shape covers this volume, micro-CT imaging seems to be a relevant data acquisition technique to access the gap dimensions  [22].
The Issue of Matching and Identifying Acquisition and Prosthesis Axis. The principle of micro-CT tomography consists in the mathematical reconstruction of a complete volume from a series of several hundred of projection images (radiograph or radiograms) obtained by illuminating with an X-ray source an object from different directions and collecting the transmitted data thanks to a detector  [25]. Either the X-ray source or the detector (linear or array detector) is moving during the exposure around the stationary object (rotation around an axis) or they are stationary and the object is rotating around the axis. In some case an additional sliding movement is added to the rotation movement. The reconstructed images are obtained from the scan data by mathematical processing (solving the inverse Radon transformation using filtered back projection or linear algebra or iterative physical model-based maximum likelihood expectation maximization).
X-Ray Micro-CT Acquisition. The CT images of the two types of assembly have been created with an X-ray microtomograph (X-View X50-CT, North Star Imaging) equipped with a cooled open microfocus a Dual Head XWT240-XC190 tubes used in mode reflection less than from and a flat panel detector NSI Dexala 752 (9. 9  × 11. 4  , 75 mm pixel pitch, 3073 × 3888 pixel matrix, dynamic range 14 bit). For the acquisition, reflection mode configuration of the X-ray source was used (detail detectability less than 1 m) with an accelerating voltage of 130 KV, a current of 50 A. The detector was used in 2 × 2 binning mode and the exposure time was 200 ms per frame. A stack of roughly 1300 grayscale images was obtained from 1200 projections using a standard filtered back-projection reconstruction algorithm. The reconstruction of the CT image using a standard filtered back-projection reconstruction algorithm was performed with the NSI in-house software efX-CT.
The magnification adopted allowed us to create CT image with a voxel size of approximately 8 × 8 × 8 m 3 which is consistent for measuring a gap of 100 m. The image stack acquired was also processed using Avizo the 3D analysis software commercialized by FEI (Visualization Sciences Group) to visualize the assembly and the open source image-processing software ImageJ  [37]  to measure the Advances in Materials Science and Engineering gap in 3D. A maximal covering sphere (MSC) algorithm was used  [38, 39]  to perform the 3D gap measurement.
Acknowledgments 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  (no. ANR-11-IDEX-0003-02 ). This work also received financial support from the  French "Agence Nationale de la Recherche ," through the  "Investissements d' Avenir" program  ( ANR-10-EQPX-37 MATMECA Grant ). The authors would like to thank  Mr. N. Lenoir  ( Laboratoire Navier ,  UMR 8205 ) and  Mr. B. Smaniotto  ( LMT Cachan, UMR8535 ) for their technical assistance in performing the micro-CT acquisitions.
ACKNOWLEDGEMENTS This study was supported by the  Research National Agency  through the  DHP  project (dir:  S. Rottier ;  2012-14 ;  Université Bordeaux 1/LaScArBx ; Grant number:  ANR-10-LABX-52 ) and the PEPS 3Dent'in (dir:  P. Bayle ;  2013-14 ;  PEPS IdEx Bordeaux/CNRS ; Grant number:  ANR-10-IDEX-03-02 ). M. Le Luyer  benefited from a doctoral grant of the  Ministère de l'Enseignement Supérieur et de la Recherche. MicroCT data presented in this work were produced through the technical facilities of the  MRI platform and of the labEx CeMEB. We are grateful to  Renaud Lebrun.
The TEARS trial was approved by the appropriate ethics committee [Comité de Protection des Personnes (CPP) Ouest VI, #2007/493] in 2007, prior to first patient recruitment. All patients gave their signed written informed consent to participate in the TEARS study, as approved by the ethics committee. The TEARS study was registered on ClinicalTrials (ClinicalTrials. gov: NCT00740948) in August 2008 soon after the enrolment of the first patients, since this registration as not required by French authorities before the beginning of a trial at this time. The authors confirm that all ongoing and related trials for this intervention are registered. The present study is an ancillary analysis of the TEARS study, focusing on patients who underwent in-depth salivary-gland evaluation (by histology and/or ultrasonography) at baseline (dataset available online as S1 Dataset file).
Statistical analysis Data were described as median [interquartile range] for continuous variables and number [percentage] for categorical variables. We computed Spearman's coefficients to assess potential correlations linking the three methods used to assess the baseline severity of salivary-gland involvement [SGUS, focus score, and UWSF]. We then evaluated whether baseline severity of salivary-gland involvement predicted the response to rituximab after 6 months. We compared patient groups using the Mann-Whitney, chi-square, or Fisher's test, as appropriate. All analyses were performed using GraphPad Prism software or SPSS v20. Values of p<0. 05 were considered significant. In the rituximab group, we observed a trend towards a lower baseline UWSF in nonresponders compared to responders [p = NS, Table  1 ].
Item generation Extensive statistical analyses were performed within the SICCA dataset with input from the working group to better understand the similarities and differences between the AECG and ACR criteria sets. Concomitantly, statistical analyses were performed within the OMRF cohort comparing the ACR and the AECG criteria, and a high level of concordance was identified (91% concordance among 646 OMRF participants, including 244 who met both sets of criteria and 343 who did not meet either). ( 13 ) Considering the high level of concordance observed between the AECG and ACR criteria, and the fact that the components in both criteria sets overlap to some degree, there was general agreement on many of the key items for inclusion. However, some tests were included in the AECG but not in the ACR criteria (the Schirmer test, unstimulated whole saliva (UWS) flow rate, sialography, salivary scintigraphy), and others were included in the ACR but not in the AECG criteria (the antinuclear/ANA antibody titer and rheumatoid factor/RF).
• Oral tests: labial salivary gland (LSG) biopsy to identify focal lymphocytic sialadenitis (FLS) and focus score (FS)(  26 ); UWS flow rates. (27, 28)  • Ocular tests: OSS using lissamine green and fluorescein, and other ocular tests such as Schirmer test and tear break-up time. For the ocular staining test, the Paris-Sud cohort used the VBS,(29) while SICCA used the OSS,  (30)  and OMRF used both. The Paris-Sud cohort also used fluorescein and collected data on the individual OSS components, so it could be computed subsequently. Thus data from the Paris-Sud and OMRF cohorts could be analyzed to establish a conversion algorithm between both scores as follows: for lower scores, 1-3, the VBS was equal to the OSS, but VBS of 4, 5, or 6 were equivalent to OSS scores of 5, 6, or 7, respectively.
For the clinical vignettes, the ocular staining test was expressed as the OSS ranging from 0 to 7 and above. A group of four ophthalmologists from France, the US, and the UK formed an ad-hoc working group that interpreted the analyses performed on the Paris-Sud data (ML and TML) and on the OMRF data (AR). Together, they derived the conversion algorithm between the OSS and the VBS described above. In addition, since the VBS of 4 (previously used in the AECG criteria) was equivalent to an OSS of 5, the group agreed to modify the OSS threshold to 5 in the new criteria set. This threshold has also been shown, as part of subsequent analyses of the SICCA data, to be more specific for diagnostic purposes than the previous score of 3 (data not shown).
• Serological assays: including anti-SSA/B(Ro/La), ANA titers, RF, IgG, presence of complement C3 and C4. Cohort PIs were each asked to provide a dataset that consisted of a random sample of 400 individuals with equal numbers of pSS cases and non-cases (using their own diagnostic definition), and without revealing case status in the dataset. The combined datasets thus comprised 1200 individuals with well-characterized data on the phenotypic features of SS. Clinical vignettes describing each individual's relevant features in text form were computergenerated using a program written in R version 3. 2. (31) Vignettes described each individual with respect to age, gender, reported symptoms, clinical signs, and provided test results including ANA titers, RF, IgG, C3, C4, anti-SSA(Ro), anti-SSB(La), OSS for each eye, Schirmer for each eye, whether or not the LSG biopsy revealed FLS, and a FS (supplemental Figure  1 ).
Assessment of SS case/control status We excluded 4 vignettes selected randomly from the study population to obtain 1196 vignettes that were randomly distributed into 26 surveys, each containing 46 individual vignettes. Research Electonic Data Capture (REDCap),  (32)  was used to administer each survey blindly to two clinician-experts. Twenty six pairs of clinician-experts participated in the first survey exercise, and each pair completed one survey. They were instructed to review each vignette, and asked if they thought the patient described had pSS. Responses included: "yes", "no", and "not sure". Concordant yes/no responses were used to assign case/non-case status; concordant "not sure" responses were interpreted as non-gradable vignettes. All vignettes with discordant answers (yes/no; yes/not sure; or no/not sure) were included in a second round of surveys that were each sent to a third clinician-expert (a total of nine clinician-experts contributed to the second round of surveys).
Criteria were defined based on scores computed as weighted sums of binary indicators of presence/ absence of items, with weights reflecting relative importance. In addition to the MCDAderived weights, we used logistic regression models fitted to the development sample to derive alternate weights from item-specific coefficients. Cut-off values for case designation for candidate criteria were computed using receiver operating characteristic (ROC) methods applied to clinician-expert-defined outcomes in the development dataset. For each candidate, two cut-off values were identified using a generalized Youden index. (34)  The first weighted sensitivity and specificity as equally important, and the second weighted specificity as twice as important as sensitivity. We held a final meeting of the SS Working Group to present and discuss testing and adaptation of the draft criteria results.
Criteria development Random forest variable importance rankings based on the clinician-expert classifications of the development dataset vignettes are shown in Figure  3. Results based on all vignette variables, as well as the binary indicators consistent with items included in the MCDA survey are shown. Rankings agree well with results from the MCDA survey, and clearly indicate the relatively greater importance of objective measures such as the LSG FS and antibody results in expert classification decisions. Oral and ocular symptoms did not affect classification performance, reflecting the observation that over 94% of individuals had at least one symptom. An initial criteria score was developed as a weighted sum of the 7 items in the MCDA survey, based on the average weights reported in Table  1.
We used logistic regression models to develop an alternate empirical criteria score for the development data, focusing on the items used in the MCDA survey, but including indicators for anti-SSA(Ro) and anti-SSB(La) positivity as separate variables. Scores were computed using weights based on rescaled regression coefficients from a model retaining items representing significant predictors of case status. (35)  Oral and ocular symptoms, and anti-SSB(La) positivity were excluded because they did not affect classification performance based on the random forest variable importance rankings from the clinician-expert classifications of the development dataset vignettes (Figure  3B ). Furthermore, oral and/or ocular symptoms had been used among inclusion criteria for participation in the three patient cohorts, and therefore a group decision was made that oral and/or ocular symptoms or suspicion of SS based on one of the domains of ESSDAI would be preliminary requirements for applying the new SS classification criteria.
Criteria validation We compared the validation and development data with respect to key variables, including their associations with outcome classification. Overall agreement was quite high, indicating no major differences apparent in the two datasets (supplemental table). Initial validation of the selected criteria was based on estimated sensitivity and specificity using the clinician-expert responses in the full validation dataset. Sensitivity was 96% (95% CI: 92%, 98%), and specificity was 95% (95% CI: 92%, 97%). Validation was also performed in the subset of 49 difficult cases and non-cases, for which sensitivity was 83% (95% CI: 66%, 93%), and specificity was 100% (95% CI: 77%, 100%).
Acknowledgments We would like to express our appreciation to  Steve Taylor  and  Kathy Hammitt  from the  Sjögren's Syndrome Foundation  for hosting three of the meetings of the  International SS Criteria Working Group ,  Dr Frédéric Desmoulins  for his important work in preparation of the Paris-Sud cohort dataset, and  Mi Lam  for her contribution in preparation of the SICCA dataset. We are very grateful to  Paul Hansen  and  Franz Ombler , the developers and owners of the 1000Minds software (https://www. 1000minds. com),who granted us an  Academic Award , providing both access and technical support to their software. We also express our greatest appreciation to all participants who enrolled in the three patient cohorts used for development and validation of the criteria, and to the clinician-experts members of the international working group for attending meetings, providing valuable input as part of these meetings, and responding to several rounds of surveys, including grading multiple vignettes.
Analysis of mRNA expression by RT-qPCR After 7 days of culture with biomaterials, total RNA was extracted. RNA concentration and purity were evaluated by spectrophotometry (Nanodrop, Thermo Scientific, Wilmington, MA, USA). Total RNA concentration and purity was measured and samples with OD260/280 ratio above 1. 8 were used for the study. cDNA was synthesized using the Superscript II kit (Invitrogen) according to the manufacturer's instructions. For the qRT-PCR reactions, succinate dehydrogenase complex subunit A flavoprotein (SDHA), ubiquitin C (UBC) were used as reference genes on the Bio-Rad CFX manager software. Non-transcribed RNA samples and a water control were used as negative controls. The datas were analyzed based on the comparative 2ΔΔCt method (CFX Manager Software Version 2. 1, Bio-Rad Laboratories).
Statistical analysis Two primary cell lines of DPSC and of GSC were used in this study. All culture experiments were at least reproduced twice in triplicate. Statistical analysis was performed using one-way ANOVA (Kruskal Wallis modified Dunns test) and was carried out using Prism GraphPad 5 software (GraphPad Software Inc, La Jolla, CA, USA). Results are presented as mean ± standard deviation (SD). Results were considered significant with a p value <0. 05. (on graphs Ã : p<0. 05; ÃÃ : p<0. 01; ÃÃÃ : p<0. 001; ÃÃÃÃ : p< 0. 0001).
Knowledge of vertebra location, shape, and orientation is crucial in many medical applications such as orthopedics or interventional procedures. Computed tomography (CT) offers a high contrast between bone and soft tissues, but automatic vertebra segmentation remains difficult. Hence, the wide range of shapes, aging, and degenerative joint disease alterations as well as the variety of pathological cases encountered in an aging population make automatic segmentation sometimes challenging. Besides, daily practice implies a need for affordable computation time. This paper aims to present a new automated vertebra segmentation method (using a first bounding box for initialization) for CT 3D data which tackles these problems. This method is based on two consecutive steps. The first one is a new coarse-to-fine method efficiently reducing the data amount to obtain a coarse shape of the vertebra.