dataesr/scientific-paragraphs-categorization huggingface dataset:
As a result, major concerns remain about the robustness and generalizability of DL methods for 3D cephalometric landmarking,. highlighting the need for additional evaluation studies with clinically-relevant datasets, clear reference data and broader outcome metrics  (Dot et al. 2020; Schwendicke, Chaurasia, et al. 2021). Recently, the fully convolutional neural network (CNN) SpatialConfiguration-Net (SCN) was proposed as a heatmap regression method integrating a spatial configuration module for landmark localization  (Payer et al. 2019). SCN has shown impressive results for the localization of anatomic landmarks on datasets of hand radiographs, lateral cephalograms and spine CT scans, but has yet to be evaluated on craniomaxillofacial CT scans  (Payer et al. 2019; Sekuboyina et al. 2021). One difficulty to overcome is data size, as high resolution Head CT scans exceed the memory capacity of a typical graphical processing unit (GPU).
There are two solutions to overcome this obstacle: 1) downsampling the scans by decreasing their resolution; 2) implementing the CNNs on small 3D image patches. However, downsampled data necessarily result in less accurate landmark localization, while image patches oftentimes lack volumetric context. But a 2-step, coarse-to-fine approach combining both methods could overcome these limitations  (Chen et al. 2021; Sekuboyina et al. 2021). The main goal of this study was to design and implement a coarse-to-fine DL method based on SCN for automatic landmark localization, before thoroughly evaluating its performance with a set of 33 landmarks on a hold-out test dataset of craniomaxillofacial CT scans from clinical practice.
Materials and Methods A DL pipeline was followed to localize cephalometric landmarks automatically on randomly selected craniomaxillofacial CT scans. We compared the results of our DL-based method on a hold-out test dataset (the index test) with those obtained by manual landmarking (the reference test). Our outcome set included localization accuracy, cephalometric measurements and comparison to manual landmarking reproducibility. This study was approved by an appropriate Institutional Review Board (IRB No. CRM-2001-051) and its reporting followed recently published recommendations on artificial intelligence in dental research  (Schwendicke, Singh, et al. 2021).
Dataset Two hundred randomly-selected presurgical CT scans were obtained from a retrospective sample of consecutive patients having undergone orthognathic surgery in a single maxillofacial surgery department described in a previous study  (Dot et al. 2022 Jan 17). Two subjects refused to participate; their data was excluded from the dataset. 198 subjects (198 anonymized presurgical CT scans) were eventually included in our dataset and randomly distributed among a training set (n = 128), a validation set (n = 32) and a test set (n = 38) (Appendix Figure  1 ). CT scans and patient characteristics are detailed in Appendix Table  1.
Manual Landmarking (Reference Test) Thirty-three landmarks, divided into skeletal (n = 21) and dental (n = 12) landmarks (Fig. 1A ), were manually annotated on each CT scan, either once (n = 178) by operator #1 (a trained orthodontist with 5 years of clinical experience), or twice (n = 20) by operators #1, #2 (a trained orthodontist with 5 years of clinical experience) and #3 (a final year postgraduate maxillofacial surgeon). The reference data used to train and test our DL model were either the single annotations (n = 178) or the means of the 6 annotations (n = 20, test set only). The scans annotated six times were part of a previous repeatability and reproducibility (R&R) study  (Dot et al. 2021). Landmark definitions and landmarking procedure are detailed in the appendix.
Heterogeneity in the methods and datasets make studies reporting DL results notoriously difficult to evaluate and compare  (Schwendicke, Singh, et al. 2021). The main strength of our study is that it provides a validation of our method based on a clinically-relevant test dataset, randomly selected from a clinical sample of presurgical CT scans. Moreover, we carefully constructed our reference test (manual landmarking) using the means of the six repetitions from a previously published R&R study for twenty of the test scans and asking one of this R&R study's operators to label the 178 remaining scans. Overall, our results are comparable to current state-of-the art studies localizing landmarks on CBCT scans, some landmarks showing slightly better and other slightly worse localization results  (Torosdagli et al.
2019; Zhang et al. 2020; Chen et al. 2021). However, previous studies lacked a clear definition of their dataset, localized fewer landmarks and evaluated their results following a cross-validation approach with no hold-out test dataset, which might question the generalizability of the results. It must be noted that our study focused on CT scans because it is the only imaging modality used for computer-assisted planning and personalized implant manufacturing for orthognathic surgery in our maxillofacial surgery department at this time. In future works we plan to use CBCT data in order to fine-tune our model and evaluate its accuracy on this other widespread imaging modality. Currently, our method does not perform automatic detection of the presence or absence of the landmarks; in the case of missing landmarks, those were deleted manually.
3 )  (Wang et al. 2021; Dot et al. 2022 Jan 17). To conclude, the proposed method achieved high accuracy on a test set of presurgical CT scans, providing results on par with those of clinicians for skeletal landmark localization and subsequent cephalometric measurements. The localization of dental landmarks still requires. improvement to provide more reliable cephalometric measurements. Despite these promising results, our model requires additional testing in order to further evaluate its generalizability, reproducibility and robustness. The model is yet to be evaluated on an external test dataset including data from other clinical centers and CT machines. Afterwards, a prospective diagnostic efficacy study should evaluate the impact of using such an automated tool in routine clinical practice.
Statistical Analysis The statistical analyses were performed using the IBM SPSS Statistics (version 26. 0, Chicago, IL, USA). The level of significance was set at p ≤ 0. 05. The primary outcome of the study was the µTBS calculated in MPa. The normality distribution of the continuous variable was assessed using Kolmogorov-Smirnov tests. Two-way ANOVA with two between-subject factors (the first factor-bonding materials: PBU/SBU adhesives; the second factor-the condition of humidity: RH:50%/RH:90%) were used to compare the µTBS among groups. This was followed by univariate analyses due to statistical interaction.
One image was taken for each specimen using a 100× magnification. The micrographs at 100× magnification, showing the canal wall surface of both groups at the coronal, middle, and apical thirds, were coded for blinded analysis by an experienced examiner independent of the experiment, using the VHX-5000 communication software (KEYENCE, Osaka, Japan) to measure the total area of the residual obturation materials (gutta-percha and sealer) (Figure  2 ). The residual filling material percentages after retreatment were calculated by dividing the area of the residual materials measured during the analysis by the total area of the root canal of each specimen.
One image was taken for each specimen using a 100× magnification. The micrographs at 100× magnification, showing the canal wall surface of both groups at the coronal, middle, and apical thirds, were coded for blinded analysis by an experienced examiner independent of the experiment, using the VHX-5000 communication software (KEYENCE, Osaka, Japan) to measure the total area of the residual obturation materials (gutta-percha and sealer) (Figure  2 ). The residual filling material percentages after retreatment were calculated by dividing the area of the residual materials measured during the analysis by the total area of the root canal of each specimen. Sirona) were used to dry the canals, and then 3 mL of 17% EDTA was applied, followed by 1 min of activation, and a final rinse with 3 mL of 6% NaOCl.
Statistical Analysis Sigma Plot software (11. 2, Systat Software, Inc. , San Jose, CA, USA) was used for data analysis, with a significance level of α = 0. 05. The normality of data distribution within both groups was tested using the Shapiro-Wilk test. The normality was not verified, thus, Kruskal-Wallis one-way Analysis of Variance on ranks including multiple comparison procedures (Tukey Test) was applied to determine whether significant differences existed between the different retreatment techniques for the removal of filling materials at apical, middle, and coronal thirds.
Characterization Methods The crystalline structure of the AgHAp thin films was examined by X-ray diffraction (XRD). The AgHAp thin film was measured in grazing incidence (GIXRD) geometry, with a Rigaku SmartLab 3 kW equipment (Rigaku, Tokyo, Japan), using CuK α radiation (λ = 1. 5418 Å) and an incidence angle of 0. 5 •  [30]. The patterns were acquired in the 2θ range 15-70 • , with a step size of 0. 02 • , and a dwell time of 8. 5 s. SCIENCE SES 2002 system and a monochromatic source of the X-ray radiation Al K α (hν = 1486. 6 eV) were used to collect X-ray photoelectron spectroscopy (XPS, Scienta Omicron, Taunusstein, Germany) data. All samples were recorded to have the carbon (C 1 s) peak for sp2 carbon at a binding energy of 284. 8 eV. All XPS data were processed using the Casa XPS 2. 3.
14 software (version: 2. 3. 14) [31]. The surface morphology of the obtained coatings was analyzed by scanning electron microscopy with the aid of a Hitachi S4500 equipment (Hitachi, Tokyo, Japan). The 3D reconstruction of the 2D SEM micrographs was carried out with Image J software (ImageJ 1. 51j8, National Institutes of Health, Bethesda, MD, USA)  [32]. Additional data regarding the morphology of the coatings was obtained using an inversed trinocular metallographic microscope OX. 2153-PLM (Euromex, Arnhem, The Netherlands). The images were recorded using the 10X magnification and the 2D metallographic images obtained were represented in 3D with the aid of Image J software (ImageJ 1. 51j8, National Institutes of Health, Bethesda, MD, USA)  [32]. Information about the surface topography of the coatings was also obtained using atomic force microscopy (AFM, NT-MDT, Moscow, Russia) technique.
For this purpose, a NT-MDT NTEGRA Probe Nano Laboratory instrument (NT-MDT, Moscow, Russia) was used. The instrument was operated in non-contact mode using a silicon NT-MDT NSG01 cantilever (NT-MDT, Moscow, Russia) coated with a 35 nm gold layer. The data was recorded at room temperature. The AFM topography was acquired on a surface area of 3 µm × 3 µm. The AFM recorded data was processed with the aid of Gwyddion 2. 59 software (Department of Nanometrology, Czech Metrology Institute, Brno, Czech Republic)  [33]. Fourier-transform infrared spectroscopy (FTIR) measurements were achieved using a SP 100 Perkin Elmer spectrophotometer (PerkinElmer, Waltham, MS, USA) operated in Attenuated total reflectance mode (ATR-FTIR, PerkinElmer, Waltham, MS, USA). The spectra were acquired in the 4000-400 cm -1 spectral range with a resolution of 4 cm -1.
For cell cycle analysis, the cells were detached with trypsin, washed in PBS, fixed in 70% cold ethanol, and then kept overnight to -20 • C. The cells were rehydrated with PBS, treated with RNase A (1 mg/mL) and stained with propidium iodide (100 mg/mL) at 37 • C for 1 h. The changes in cellular DNA content were measured using EPICS XL flow cytometer (Beckman Coulter, Brea, CA, USA) and analyzed with FlowJo 8. 8. 6 software program (Ashland, OR, USA). In vitro antifungal activity of the thin films was also evaluated using Candida albicans ATCC 10231 fungal strain. The in vitro antifungal assays were performed as previously described in  [34]  and the antifungal activity of the thin films was assessed after 48 h of incubation with the fungal suspensions. The qualitative antifungal evaluation was carried out with the aid of scanning electron microscopy (SEM) and confocal laser scanning microscopy (CLSM, Leica, Wetzlar, Germany).
09 eV) were observed. The peak of Ag (Ag(3d 3/2 ) was identified at BE of 368. 4 eV and peak of Ag(3d 5/2 ) was observed at BE of 374. 3 eV in good agreement with previous studies  [39, 40]. The high resolution XPS spectra of Ag element was presented in Figure  2B. The surface morphology of HAp, 0. 05 AgHAp and 0. 1 AgHAp coatings was investigated using three different techniques scanning electron microscopy, metallographic microscopy, and atomic force microscopy. The images obtained by SEM studies are depicted in Figure  3a-f. The results obtained by SEM revealed that all of the investigated coatings presented a homogenous and uniform surface without any noticeable cracks or unevenness. Moreover, the SEM data also highlighted that the particles have nanometric dimensions and an ellipsoidal shape.
Additional information about the biocompatibility of the thin films was gathered by AFM studies. For this purpose, the AFM topographies of the thin films' surfaces were acquired at room temperature in normal atmospheric conditions on a surface of 40 µm × 40 µm. The results of the AFM studies are depicted in Figure  12a-f. The 2D AFM images highlighted that on the surface of the investigated thin films, typical patterns of cellular morphology of MG63 (ATCC CRL1427) cells having typical spindle-like shapes were found  [49, 50]. More than that, the data also suggested that the MG63 (ATCC CRL1427) cells had a good adherence to the samples and proliferated on the surfaces of the HAp, 0. 05 AgHAp and 0. 1 AgHAp thin films. Furthermore, both the 2D AFM topographies as well as their 3D representations emphasized that the MG63 (ATCC CRL1427) cells were very well spread out and that they formed a monolayer that completely covered the HAp and AgHAp coatings.
albicans cells development was strongly inhibited by the presence of both AgHAp thin films and that the 0. 05 AgHAp and 0. 1 AgHAp thin films did not allow fungal biofilm formation on their surface. The results of the CLSM observation are presented in Figure  14a-f. On the other hand, CLSM images determined that the HAp thin films promoted and positively influenced the adherence and proliferation on their surface and also that allowed the fungal cells to form biofilm on their surface. These results are in good agreement with the ones obtained by SEM investigation and with our previously reported data  [55] [56] [57]. Additional information about the antifungal activity of the HAp, 0. 05 AgHAp, and 0. 1 AgHAp thin films were obtained by performing in vitro quantitative antifungal assays. For this purpose, the thin films were incubated with fungal suspensions and their antifungal properties were assessed by determining the colony forming units (CFU) after 48 h of incubation.
Similar results have been achieved by the simultaneous inhibition of BRAF and MEK signaling combining dabrafenib and trametinib, showing a benefit in 20 out of 43 BRAF V600E mutated CCA patients  [108]. Also, an antagonist against CXCR4 (AMD3100) approved by the FDA had minor effects on solid tumors and showed significant adverse side effects  [109]. Although, AMD3100 has been developed into the structurally similar compound (BPRCX807), which in the preclinical setting prevents tumor growth, cell migration, and metastasis in HCC  [110]. Finally, the benefits of the mTOR inhibitor (everolimus) is currently investigated in phase IV in liver transplants and liver tumor recurrence (NCT02081755), but results from this trial is awaited. In contrast to inhibition of RTKs, the restoration of silenced proteins like ARID1A and PBRM1, which are often mutated in CCA, is a more challenging approach and require continued investigation  [111].
Randomization Patients will be randomly assigned to one of the two arms: "ICA" and "IANB" at a ratio of 1:1. The randomization list will be computer-generated by the study statistician and the randomization process will be centralized through a secured clinical data processing website managed by Ennov© Clinical system software (Ennov, Paris, France). The investigators will enter the patient's information (initials, age, and date of birth mentioning the month and year only) and the software will provide the patient's unique allocation number and randomization group. As it's a randomized controlled study, the patients are blinded. The unblinding occurs if a patient decides to leave the protocol prematurely. The best care will be provided by the investigator and the pulpotomy will be performed under the best conditions to relieve the patient's pain.
Statistical analysis The analysis will be based on intention-to-treat (ITT) using the "missing = failure" strategy. A robustness analysis, supported by the per-protocol approach, will be carried out if the patients present with protocol deviations (error of randomization). Qualitative variables will be described by the percentages and numbers of each modality. Quantitative variables will be described by means and standard deviations. Con dence intervals at 95% will be presented. A paper case report form (CRF) will be created for each patient inclusion for data collection and will be based on the establishment of a clinical database. All information required by the protocol must be provided in the CRF, necessary for statistical analyses. To assess the primary endpoint (time to return to baseline heart rate and blood pressure), the mean values will be estimated by the Kaplan-Meier method (survival curves) and compared using Log-Rank tests.
To assess the secondary endpoint (time to baseline O2 and change in measurements over time), the 2 arms will be compared in the same way as the heart rate and blood pressure parameters. Univariate and multivariate Cox models will be used to investigate the factors associated with the time to the baseline of cardiopulmonary constants. The difference in pain between D0 and D + 3 will be compared between the 2 groups with a Student's t-test or a Wilcoxon test. Data for the analysis are collected from the rst questionnaire (French version of the Corah's dental anxiety scale), the three phases of cardiopulmonary monitoring, the VAS assessment, and the postoperative questionnaire given to the patient at the end of the procedure. The information recorded on the postoperative questionnaire will be collected by a telephone call 3 days after the procedure.
This trial was registed at ClinicalTrials. gov and this article is based on the 2nd version of the protocol published in December 2019. It was not submitted earlier to be published due to changes in the study status. The recruitments have begun beginning of March 2019 and due to the COVID-19 pandemic, the patient inclusions were delayed to resume by May 2020. The nal inclusion will be terminated 1st of July 2022. ID: intra-diploid; IS: intra-septal; IO: intraosseous; ICA: intraosseous computerised anaesthesia; IANB: inferior alveolar nerve block; BPM: beats per minute; CPP: Comité de Protection des Personnes; VAS:.
This trial was registed at ClinicalTrials. gov and this article is based on the 2nd version of the protocol published in December 2019. It was not submitted earlier to be published due to changes in the study status. The recruitments have begun beginning of March 2019 and due to the COVID-19 pandemic, the patient inclusions were delayed to resume by May 2020. The nal inclusion will be terminated 1st of July 2022. ID: intra-diploid; IS: intra-septal; IO: intraosseous; ICA: intraosseous computerised anaesthesia; IANB: inferior alveolar nerve block; BPM: beats per minute; CPP: Comité de Protection des Personnes; VAS: Visual Analogue Scale Declarations Figures.
Current population CBCT examinations performed in the Odontology Department of Toulouse University Hospital were used to establish the contemporary sample. The city of Toulouse is the fourth most populated city in France, and the hospital received patients from all over the Occitanie region. The database was spread between January 2019 and July 2021, and the population is composed of patients requiring 3D radiography for endodontic, implant, surgery, or orthodontic treatment. The selection criteria were mature roots, non-carious, no fracture, no root resorption and no root canal filling. The criteria for exclusion were unclear or distorted CBCT images, previously endodontically initiated or treated teeth and teeth with posts or crowns. Any physiological or pathological process such as an immature apex was also excluded.
The scanning device used was a Carestream Dental CS9600. Only the voxel size of 0. 075 mm or 0. 150 mm and small (60 × 60 mm) or medium (120 × 100 mm) field of view were used. The following parameters were used in the small field of view for an adult of average weight: 120 kV, 3. 2 mA, voxel size 0. 075 mm and dose area product 454 mGy/ cm 2. For the medium field of view, the following parameters were used: 120 kV, 3. 2 mA, voxel size 0. 150 mm and dose area product 1089 mGy/ cm 2. Images were exported in DICOM format. All reviews were anonymized using DicomCleaner® software (version 10. 2, www. dclunie. com), however, the date of birth, sex of the individual and acquisition parameters were kept. Finally, 329 individuals were selected (143 men and 186 women), aged between 10 and 81 (average age 40.
CBCT image analysis Images were examined using the CS Dental Imaging® software 3D Module version 3. 10. 4. All samples (ancient and current populations) were observed in three planes: coronal, sagittal and axial (Fig. 3 ). The following features were analyzed: type and number of tooth, number of roots, number of root canals and canal configuration. We assume a separate root has one-quarter to one-third of the total root length, independent of the others  (Turner et al. , 1991). An individual root canal was defined as a separate orifice found from the floor of the pulp chamber to apex  (Nosrat et al. , 2015). The Vertucci classification was chosen in order to record the root canal configuration (Table  3 )  (Vertucci, 1984).
CBCT was used in the present study because it permitted complete crania and mandibles to be analyzed. Archeological samples receive a lower radiation than in a conventional scanner, and the CBCT does not damage historical material. A database of patients was available from the same device that enabled the ancient population acquisitions. Some limitations to this study should be noted. The choice of two voxel sizes (0. 075 and 0. 15 mm) for the current population might be questioned, but no significant difference was found for the root canal configurations between these two resolutions. In other words, the 0. 075 mm voxel size did not reveal a more accurate configuration than the 0. 15 mm resolution in our study. A systematic review of the literature was conducted in 2020 with the objective of evaluating the relationship between voxel size and prevalence of the second mesio-buccal canal in maxillary molars.
19 Circumferential 1mm chamfer finish line design, 1. 5 mm occlusal and 1mm axial reductions were employed for both premolar and molar teeth. A digital impression was obtained from the typodont model by using an optical laboratory scanner (Iscan D104i; Imetric 3D SA, Courgenay, Switzerland). The digital files were exported in standard tessellation language (STL) format and were then processed in a model processing software program (Dental System, Model Builder; 3 Shape, Copenhagen, Denmark). Later the model was 3D printed (P30; Rapidshape, Straumann, and SheraPrint Model Plus Sand; SHERA Werkstoff-Technologie GmbH & Co) to be used as the master model. The rationale behind obtaining the master model from a 3D printed material was to ensure the similar surface characteristics and light reflection properties between the specimens and the master model.