dataesr/scientific-paragraphs-categorization huggingface dataset:
The pre-processing, processing and post-processing methods applied to the AM group specimens are detailed in Table  1. The master model and the 3-unit FDPs were scanned using an optical laboratory scanner (Iscan D104i; Imetric 3D SA). An anti-reflective powder coating (Helling 3D Scan Spray; Helling GmbH) was sprayed at a fixed distance of 20 cm on the preparation, intaglio and outer surfaces of the specimens. The accuracy of the scanner was reported as 4 µm by the manufacturer. The scanning was made following a modified triple scan method  21  : the scanning of the preparation (preparation scan); scanning of the specimen, intaglio and outer surface of the FDPs (FDP scan); scanning of the assembly, and the FDP was positioned on the master model (assembly scan) (Fig  1 ). The scan data were exported as STL files to be then imported in a reverse engineering software program (GOM Inspect, V8 Hotfix 5, Rev.
115656, Build 2019-02-15, GOM GmbH, Carl. AG, Brunswick, Germany) for the analysis. Initially, the preparation scan was imported, and the abutment surfaces of the preparation scan were separated applying three surface curves and corresponding sections in the inspection software (GOM Inspect; GOM GmbH) to create 3 areas-marginal, axial and occlusal (Fig  2 ). The marginal area was defined by two curves; the first was positioned at the cavosurface angle and the second at the intersection between the finish line and axial wall of the preparation. A curve separating axial and occlusal areas was positioned where functional and nonfunctional cusp bevels end at the buccal and lingual aspects, and in the approximal areas at the intersection between occlusal and axial preparation walls. Surface patches were created for the three inspection sites (marginal, axial, and occlusal) on the preparation scan.
The internal and marginal adaptation of the FDPs at three defined areas (marginal, axial, and occlusal) for each abutment tooth (premolar and molar) were measured at multiple points throughout the surface using the surface comparison option (GOM Inspect; GOM GmbH) (Fig  2 ). The number of measurement points were 1208 and 1953 at the occlusal area, 1404 and 1913 at the axial area, and 1023 and 1649 at the marginal area on the premolar and molar teeth, respectively (Fig  2 ). The inspection was limited to 500 µm and the exceeding measurements were considered as outliers. The single point measurements were exported to a software program (Microsoft Excel; Microsoft, Redmond, Washington, United States) and were used to calculate the mean space between the marginal, intaglio (axial and occlusal), and total areas of the abutment teeth.
Acknowledgments The authors would like to thank to  Dr. Hyeonjong Lee  ( Yonsei University, Seoul, South Korea ) for his support in developing the modified triple scan protocol, and to  Prof. Dr. Susan Scherrer  ( University of Geneva, Division of Fixed Prosthodontics and Biomaterials ) for her support in SEM analysis and for providing SEM images. Open access funding provided by  Universite de Geneve.
Statistical analysis Statistical differences between IFT experimental groups were assessed using Instat software (GraphPad, California, USA). Parametric data were analyzed using 1-way ANOVA followed by Tukey's multiple comparison test (α=0. 05). For the flexural strength and surface roughness parameter (Sa), a t-test was used. Variations were considered to be statistically significant when the p value was < 0. 05. The normality of the results distribution was assessed with the Kolmogorov-Smirnov test, and the power (1-β) was calculated to be 97. 4%. Weibull distribution analysis was calculated for IFT data using the Weibull statistics option in Excel (Microsoft, USA). For contact angle measurements of the composite cements with zirconia surfaces, 1-and 2-way ANOVA were used followed by Tukey's multiple comparison test (α=0.
Afterward, the suspension was collected at different time intervals  (24, 48 , and 72 h) and incubated on a LB agar medium for 24 h at 37 • C. The number of CFU/mL was determined for each of the incubated samples with the microbial suspensions. The values of the CFU/mL were determined. The experiments were performed three times and the data were presented as mean ± SD. The statistical analysis was performed using the ANOVA single-factor test.
The wealth of data in the National Cancer Database (NCDB) has allowed numerous studies investigating patient, disease, and treatment-related factors in oral cavity squamous cell carcinoma (OCSCC); however, to date, no summation of these studies has been performed. The aim of this study was to provide a concise review of the NCDB studies on OCSCC, with the hopes of providing a framework for future, novel studies aimed at enhancing our understanding of clinical parameters related to OCSCC. Two databases were searched, and 27 studies published between 2002 and 2020 were included. The average sample size was 13,776 patients (range 356-50,896 patients). Four areas of research focus were identified: demographic and socioeconomic status, diagnosis, prognosis, and treatment. This review highlights the impact of age, sex, ethnicity, and socioeconomic status on the prognosis and management of OCSCC, describes the prognostic factors, and details the modalities and indications for neck dissection and adjuvant therapy in OCSCC.
Oral cavity squamous cell carcinoma (OCSCC) is the sixth most common cancer in the world  1. The American Cancer Society estimated that 35,310 individuals would be diagnosed with OCSCC in the United States in 2020 and 7110 would die from this malignancy 2. Today, the reported 5-year survival for OCSCC is around 64%  3  , and there have been no significant improvements in survival over the past few decades  1. Tobacco and alcohol consumption are still the main etiological risk factors for OCSCC  4. Surgical resection remains the optimal first-line treatment for OCSCC, with radiotherapy and chemotherapy serving as adjunctive measures aimed at improving overall survival and loco-regional control in select cases. Today, head and neck cancer specialists have robust scientific data from the National Cancer Database (NCDB), which is a cancer registry organized by the American Cancer Society and the American College of Surgeons that provides hospital-based case data from over 1500 Commission on Cancer-accredited hospitals  5.
NCDB data represent more than 70% of newly diagnosed cancer cases within the United States  5. Large cancer databases such as the NCDB allow investigators the opportunity to examine a myriad of factors related to oncological outcomes in malignancies including OCSCC  6, 7. The wealth of data in the NCDB has allowed numerous studies investigating patient, disease, and treatment-related factors in OCSCC; however, to date, no summation of these studies has been performed. Therefore, the aim of this study was to provide a concise review of the NCDB studies on OCSCC, with the hopes of providing a framework for future, novel studies aimed at enhancing our understanding of clinical parameters related to OCSCC.
Materials and methods A search using the abstract and citation databases PubMed and Scopus was performed to identify NCDB articles on OCSCC. Two combinations of search terms were utilized: ''Oral cancer'' AND ''NCDB''; ''Oral squamous cell carcinoma'' AND ''NCDB''. No time limit or language restriction was applied for inclusion. All NCDB studies for which the principle aim focused on OCSCC were included. Studies dealing with oral cancers other than squamous cell carcinoma (SCC) (e. g. , minor salivary gland malignancies) or head and neck carcinomas located in nonoral cavity anatomical sites were excluded. Three of the review authors separately determined the main bullet point of each included article. They then compared their bullet points, and in the case of a discrepancy, discussions were held until a consensus was reached.
Discussion The NCDB has been used widely to study head and neck cancer including OCSCC, mainly to evaluate commonly utilized therapeutic modalities, determine prognostic predictors, identify demographic and socioeconomic factors, and create machine learning algorithms for predicting occult nodal metastasis. The main advantage of the NCDB is that it collects nationwide data from a large sample of patients, which would be difficult to achieve even in well-organized multicenter studies. However, studies based on the NCDB have inherent limitations associated with the database. Firstly, the data are retrospective and subject to omissions and inaccuracies or miscoding of the medical record  9, 25. The NCDB data are captured from Commission on Cancer-accredited hospitals across the United States  19  , each with systematic differences in data collection and treatment patterns  22  , which ultimately introduces selection bias.
Some relevant data are not included in the NCDB and this may create a confounding bias. For instance, tobacco and alcohol use, as well as other comorbidities and performance status, are not recorded  29. Furthermore, high-risk histological features such as perineural and lymphovascular invasion are not included within the NCDB  17, 25, 31. Tumor biology and genetic markers, which are becoming more widely appreciated prognostic factors, are also not recorded in the database  17, 26, 32. The specific details of different treatment modalities are not available, such as the levels and laterality of neck dissections  25. Additionally, radiotherapy modalities do not include the radiation fields or designation of local versus regional treatment  29. In the same way, the specifics of chemotherapy regimens are not recorded  31, 32.
Diseasespecific survival or patterns of recurrence including local, regional, or distant failures are not included in the NCDB  32, 33. Furthermore, the DOI is frequently omitted  28  and is not distinguished from the tumor thickness, which is not an interchangeable measurement  25. It is important to mention that the data recorded in the NCDB have changed over time, and this may explain the differences in findings between the different articles. For example, 2004 was the first year the NCDB began collecting detailed information on radiation treatment. HPV status was only routinely collected for head and neck cancers starting in 2010  34. However, even after starting to collect this, it is still missing for a lot of patients. Similarly, the Charlson-Deyo comorbidity score was only recorded in the dataset starting in 2003  19  , but is not registered in up to one third of cases  22.
In conclusion, despite its limitations, the NCDB has resulted in a greater understanding of various clinical aspects of OCSCC. This study highlights the major role of surgery and the impact of socioeconomic status on the outcomes of OCSCC. It can be judged that the NCDB is a large and useful database that can aid the clinician in making treatment decisions and evaluating the prognosis. It must be pointed out that the NCDB data give only partial, although very useful, retrospective information regarding demographic, pathological, and treatment details. Therefore, it is important that the results of the various NCDB studies are interpreted critically. Despite these limitations, it is clear that the data can help in clarifying the best practices in the treatment and prognostic evaluation of OCSCC.
The database is especially helpful in generating hypotheses and determining effectiveness of treatment options and surgical approaches when prospective data are not available. Also, database data are important for the evaluation of trends in survival and care for cancer patients. It is clear that definitive evidence on treatment and prognosis must still be derived from well-designed prospective studies and meta-analyses of randomized clinical trials. On the other hand, the NCDB is a very valuable resource for clinicians and researchers involved in the management of OCSCC, offering an incomparable perspective on a very large dataset of patients. Future developments regarding hospital information management, review of data accuracy and completeness, and wider accessibility will help investigators and clinicians to improve the care of patients affected by OCSCC.
Roughness and Wettability The roughness of each surface was measured using a 3D digital profilometer (Keyence, Osaka, Japan) at 2500× magnification. The average roughness (Sa) (n = 5) was calculated using the Keyence 7000 VHX software (KEYENCE, Osaka, Japan)  [24]. Further specimens (n = 3) were kept in dry conditions overnight and then submitted to the evaluation of the sorption time using a 5 µL drop of distilled water into the cement surface through a contact angle device (Biolin Scientific, Espoo, Finland). A horizontal camera was used to record the profile of the water drop and its absorption time, as previously described by Kharouf et al  [25].
Porosity The internal structures of AHP, AHPB, and WRST were inspected in 3D by means of micro-computed X-ray tomography (µCT) (EasyTom 160 from RX Solutions, Chavanod, France). The imaging procedures were executed at a voltage of 45 kV and a current of 160 mA, using a micro-focused tube equipped with a tungsten filament. The source-to-detector distance (SDD) and the source-to-object distance (SOD) were adjusted in such a way to obtain a voxel size of around 2. 3 µm. Volume reconstruction was performed with the software Xact64 (RX Solutions) after applying geometrical corrections and ring artefact attenuation. Such an image process was performed using the Avizo software (ThermoFisher, Waltham, MA, USA) that allowed us to (i) de-noise the images with a median filter; (ii) segmentate the image intensity to reveal the objects of interest (here, the pores); (iii) remove insignificant small objects (below a size of 10 pixels from the segmented 3D data); and (iv) determine the 3D geometrical aspects of the objects of interest (volume and equivalent diameter)  [28].
Statistical Analysis Statistical analysis was performed using the Minitab®21 statical software-(Minitab, LLC, State College, PA, USA). The Shapiro-Wilk test was used to verify the normality of the data in all groups. However, when the normality was not verified as thus, an analysis of the variance on ranks, including a multiple comparison procedure (Tukey test), was used in order to determine whether significant differences existed in the compression modulus and strength values, water sorption tests, roughness measurements, and pH evaluations between the different composites. In all tests, a statistical significance level of α = 0. 05 was adopted.
Samples were positioned respectively at 25 mm (membranes) and 40 mm (scaffolds) from the X-ray target. A distance of 300 mm was used between the source and the detector, with a counting time of 750 ms per picture and an average of five pictures per 0. 25 • step. The Datos X ® software (Version 1. 5, GE Sensing & Inspection Technologies GmbH, Phoenix|X-ray, Wunstorf, Germany) was used to process the data and reconstruct 3D images of the scaffolds. Images were treated using the Vg Studio Max ® software (Version 2. 1 max, Volume Graphics GmbH, Heidelberg, Germany). The maximum voxel size was respectively 6 µm (membranes) and 4. 2 µm (scaffolds).
The media with bacteria and 4 types of apatite specimens were incubated at 37 • C for 24 h. Each sample was tested in quadruplicate (n = 4). The test results were analyzed by measuring radical zones, e. g. , the clear areas formed around the well with a sliding caliper. Data of the bacteria inhibition zone in mm are presented as the mean ± standard deviation (SD). Statistical analysis was conducted with a one-way analysis of variance (ANOVA) continued by Bonferroni post-hoc test. depicted in Figure  1. The media with bacteria and 4 types of apatite specimens were incubated at 37 °C for 24 h. Each sample was tested in quadruplicate (n = 4). The test results were analyzed by measuring radical zones, e. g. , the clear areas formed around the well with a sliding caliper. Data of the bacteria inhibition zone in mm are presented as the mean ± standard deviation (SD).
The cell viability was calculated by the following equation: Cell viability (%) = (Absorbance of the scaffold -Absorbance of medium control) (Absorbance of the control -Absorbance of medium control) × 100  (2)  All tests were conducted at least in triplicate. The mean values of cell viability with the 4 types of apatites were calculated using Microsoft Excel (Version 365, Microsoft, Washington, USA). The IC 50 value was analyzed by linear regression. Data are presented as means ± standard deviation (SD). A one-way analysis of variance (ANOVA) with the GraphPad Prism 7 software (GraphPad Software, Version 9. 3. 1, Graphpad Software Inc. , CA, USA) was used to analyze the results followed by Tukey's test at p-values < 0. 05.
3. 1, Graphpad Software Inc. , CA, USA) was also applied to analyze the results. All tests were conducted at least in triplicate. Data are presented as means ± standard deviation (SD). A one-way analysis of variance (ANOVA) was used to analyze the results followed by Tukey's test at p-values < 0. 05. The spreading of the osteoblast cells on the surface of the apatite materials was visually observed by SEM analysis. To this aim, MC3T3E1 cells were seeded on the doped apatite materials and incubated for 48 h. After 48 h of incubation, the culture was washed with PBS 3 times and fixated with 2. 5% glutaraldehyde. Dehydration series with alcohol were conducted at 50, 70, and 90% concentration before final dehydration with 100% alcohol, 2 times for 30 min each. Specimens were then dried at room temperature, platinum coated, and observed with a JEOL-JSM 6510 microscope (JEOL Ltd.
Post-hoc tests also confirmed that there were significant differences among the samples on the capability of the samples to function as antimicrobial agents. In the present work, the level of protein adsorption reached for each type of apatite samples after contact with Fetal Bovine Serum (FBS) was quantified via a differential approach by UV spectrophotometry (see experimental data for details). Figure  6  shows the results obtained, and the numerical values from the ANOVA analysis are reported in Table  S6. Peroxidated apatite O2-hap showed a similar adsorption level compared to undoped apatite, as no significant difference was found between Ag-hap and hap (p = 0. 084), thus not modifying significantly surface interaction with circulating proteins. Samples involving silver showed however different behaviors.
In the present work, the level of protein adsorption reached for each type of apatite samples after contact with Fetal Bovine Serum (FBS) was quantified via a differential approach by UV spectrophotometry (see experimental data for details). Figure  6  shows the results obtained, and the numerical values from the ANOVA analysis are reported in Table  S6. Peroxidated apatite O 2 -hap showed a similar adsorption level compared to undoped apatite, as no significant difference was found between Ag-hap and hap (p = 0. 084), thus not modifying significantly surface interaction with circulating proteins. Samples involving silver showed however different behaviors. Indeed, there were significant differences on the protein adsorption between Ag-doped with Peroxide-doped (p < 0. 017) and between Ag-doped with Ag-Peroxide-doped (p < 0.
Acknowledgments: We thank  Aurélie Mirland  and  Yannick Thébault  for technical help, respectively, for the drawing of the apatite structure and SEM-EDX acquisitions; and the SynBio3 platform (IBMM, Montpellier) especially  Vincent Darcos  for help in PLGA characteristics refinement. The  French FERMaT Midi-Pyrénées Federation   FR3089  is acknowledged for providing X-ray tomography laboratory facility. The antibacterial test, cell adhesion, and protein adsorption tests were partly supported by the  International Collaborative Research Scheme (KLN)  from the  Ministry of Research, Technology, and Higher Education of the Republic of Indonesia.
Study Design and Subjects This analysis was a part of the randomized controlled trial BBCovid protocol published  (Carrouel et al. , 2020 ) and registered at ClinicalTrials. gov (NCT04352959). One hundred and sixty subjects diagnosed as COVID-19 positive patient were recruited between September and December 2020 in four French hospital centers. The study protocol was reviewed and approved by the National Ethics Committee "Committee for the Protection of Persons South Mediterranean III, " France (2020. 04. 11 sept _20. 04. 06. 46640). Written informed consent was obtained from all enrolled individuals. The study was conducted in accordance with the Declaration of Helsinki and the International Conference on Harmonization-Good Clinical Practice guidelines. The inclusion criteria were: (i) age 18-85 years-old, (ii) RT-PCR positive COVID-19 nasopharyngeal swab, (iii) asymptomatic or mild clinical symptoms for less than 8 days.
Quantification of SARS-CoV-2 Viral Load by Real-Time RT-PCR RNA was extracted from 200 µL of saliva sample using the NucliSens easyMAG instrument (bioMérieux, Marcy-l'Etoile, France), according to the manufacturer's guidelines. The RNA was eluted in 50 µL of water and used as a template for realtime (rt) RT-PCR. Real-time RT-PCR assays were performed with the Invitrogen Superscript TM III Platinum One-Step qRT-PCR system (Invitrogen, Illkirch, France). The mix was composed of 5 µL of extracted RNA, 1 µL of Superscript III RT/Platinum Taq Mix, 12. 5 µL of 2X reaction buffer, 0. 4 µL of a 50 mM magnesium sulfate solution, 1 µL of RdRp-IP2 forward primer (0. 4 µM), 1 µL of RdRp-IP2 reverse primer (0. 4 µM), 1 µL of RdRp-IP4 forward primer (0. 4 µM), 1 µL of RdRp-IP4 reverse primer (0. 4 µM). The primer and probe sequences correspond to the RdRp-IP2 and the RdRp-IP4 assays designed at The Institut Pasteur to target a section of the RdRp gene (nt 12621-12727 and 14010-14116 positions) based on the sequences of SARS-CoV-2 (NC_004718) made available on the Global Initiative on Sharing All Influenza Data data-base on 11 January 2020 (Table  1 ).
Statistical Analysis SPSS Windows 20. 0 (IBM, Chicago, IL, United States) was used for the descriptive statistics median values and interquartile range (IQR) and mean values with SD for the quantitative variables and percentages for categorical variables. One-way ANOVA was used to compare the differences of median between groups in a univariate analysis. Binary logistic regression analysis was used to model the relationship between viral load values as the dependent variable and the other parameters were entered individually as independent variables (adjusted for age and gender). The detailed statistical methods are indicated in the table footnotes. All data were considered statistically significant when p < 0. 05.
ACKNOWLEDGMENTS We thank and acknowledge all the patients and trial team members. More particularly,  Sophie Lengagne ,  Eva Geraud  and  Anthea Loiez  from the  Emile Roux Hospital Center (Le Puyen-Velay, France );  Louis Gauthier  from the  Protestant Infirmary (Lyon, France) ,  Séverine Poupblanc ,  Anne-Hélène Boivin  from the  Intercommunal Hospital Center of "Mont de Marsan et du Pays des Sources" (Mont de Marsan, France) ;  Armand Sophie ,  Caroline Gagneux ,  Adrien Didelot ,  Matthieu Pecquet ,  Marie Paul Perraud Josiane Thimonier  (Cadres des services) from  Saint Joseph Saint Luc Hospital (Lyon, France). We also thank all the technician from the  CNR  for their work. We thank  Stéphane Morisset  independent statistician and special adviser. We also extend our thanks to  Eric Bomel ,  EZUS ,  University Lyon1  who provided central administrative support to the project, and  Eric Gonzalez Garcia , from  Greiner Bio-One GmbH (Kremsmuenster, Austria ) who provided kindly technical support.