dataesr/scientific-paragraphs-categorization huggingface dataset:
Presurgical planning and transfer is often a multistep approach, with each step contributing to the resulting discrepancy between the original presurgical planning and the final outcome result following implant placement. When opting for such a procedure, it is necessary to take into consideration the proper time for optimised CBCT image acquisition, diagnostic interpretation, data manipulation, volume segmentation, registration or fusion of distinct 3D datasets, integrated planning and further accurate transfer to enable a predictable outcome, meanwhile avoiding complications. There is an urgent   [8, 17, 19]  Prevention of neurovascular trauma  [8, 17, 19]  Specific challenges for the anterior esthetic zones  [8, 17, 19]  Borderline cases related to inadequate bone morphology, volume and quality  [8, 17, 19]  Augmentation procedures  [8, 17, 19]  Special techniques (grafting, distraction, zygoma implants)  [8, 17, 19, 22]  Suspected trauma history of jaws and teeth  [8, 17, 19]  Doubtful prognosis of neighboring teeth  [5, 8, 17]  Presurgical planning and transfer  [2, 4, 5, 8, 17, 19, 22, 23]  The virtual patient  [23]  Fig.
How to use dental CBCT beyond radiodiagnostics? Apart from its radiodiagnostic potential, dental CBCT may present a further treatment potential, such as the potential for surgical guides and prosthetic rehabilitation via CAD/CAM procedures  [23, [26] [27] [28] [29] [30] [31]. The large variations within CBCT units may lead to variable degrees of linear, diagnostic and 3D model accuracy, which are all needed to refine diagnostic tasks, surgical planning and CAD/CAM transfer. Nowadays, studies are focusing on overcoming technological shortcomings by assessing optimisation of exposure protocols or by registration of CBCT scans with optical datasets to eliminate the drawback of CBCT-derived metal artefacts  [26, 30]. These optical datasets are derived from 3D optical cameras, which may offer the possibility to avoid traditional impression-taking.
This may help to eliminate the necessity of intra-oral impression materials and subsequent fabrication of dental casts, meanwhile reducing time and handling errors inherent to these procedures. The available intraoral 3D scanners may offer excellent accuracy (up to 10 times better than CBCT), while being more comfortable for the patient than conventional impression-taking and far more efficient for the daily workflow  [23, 26, 30]. By image-fusion with basic CBCT data, a digital cast with an accurate surface would thus enable further treatment using integrated 3D dataset for patient-specific CAD/CAM procedures  [23, 30, 31]. This semi-automation may eliminate manual steps and inevitable human errors when producing dental restorations  [32] [33] [34]. Continuous developments may evolve to further simplification and automation, with less chair-side time and fewer recall visits for the patient at an expense of more computer time for the practitioner.
What are the requirements for creating a virtual patient? The aforementioned evolution towards the concept of a virtual patient for dental implant surgery, creates new challenges for appropriate CBCT scanning. The virtual patient is a digital record that is used to plan the ideal implant position with respect to aesthetic, prosthetic and surgical requirements. It integrates information (datasets) obtained from facial scanning technology, digital intra-oral impressions and CBCT imaging in one virtual coordinate system  [23, 28, 31, 32]. The virtual teeth arrangement is planned with regards to aesthetic and prosthetic functional requirements so that the ideal prospective implant position can be identified  [29, 33]. Subsequently, a surgical guide is fabricated for fully guided implant insertion, and the treatment can then proceed with creating the provisional and final prosthesis using the same pre-operatively planned prosthetic setup  [29, 30, 32, 33].
Nevertheless, standards for DICOM compliance for some devices including CBCT and CAD/CAM systems and their interoperability with respect to PACS have not yet been fully established. To facilitate standard communication, accurate image data exchange and 3D data integration into a virtual model, radiographic devices and third-party dental implant software applications should be forced to offer fully compliant DICOM data export  [8, 67]. The huge data volume of CBCT DICOM images requires high storage capacity. To save storage space, DICOM viewers usually compress DICOM imges into smaller files during file export  [68]. This compression is done using specialized algorithms and can be performed using both lossy or lossless methods  [69]. Lossy compression permanently eliminates redundant information, but can result in eccessive image degradation  [68].
In order to avoid loss of information, it is advised to use the original data or data compressed with lossless compression algorithms when transferring information to a thirdpart software. Unfortunately, in literature there is a lack of studies validating the process of image conversion from a proprietary format into DICOM format. Further studies are needed to quantify the amount of information lost during DICOM export, in order to make clinicians aware of this source of error, on top of all other possible sources of inaccuracy during computer aided surgical planning. It is clear that for most CBCT systems there is a diagnostic data loss upon DICOM export and potentially even a further loss when imported into a PACS system or third party software. Indeed, most third party softwares have some additional filtering (e.
g. smoothening) at the import phase, which may result in additional information loss. It is therefore recommended to do presurgical diagnostics in the dedicated CBCT-software of the imaging device, prior to export for presurgical planning purposes. Other challenges in the digital data flow include the fact that there is a growing availability of non-DICOM 3D imaging data formats required to be used for an integrated virtual patient dataset  [23, 28, 38, 39]. Examples include STL and OBJ formats, respectively, used for digital intraoral impressions and printing as well as for facial scanning. Transferring those datasets to PACS systems is actually not possible, as such that the power of the integrated virtual patient information is lost at this level.
Conclusions CBCT imaging is a well-established radiographic modality in treatment planning for dental implants, becoming increasingly popular and globally used in oral health care. This is partially due to new insights into anatomic landmarks, and structures at risk during implant placement such as neurovascular structures. Another reason for the growing use of CBCT scanning is the increasing popularity of computer-guided surgery that relies on digital planning based on high-quality CBCT images  [38] , but may also include the superimposition of intraoral scans and extraoral face scans to create a 3D virtual dental patient  [36, 37]. The virtual patient concept is actually demonstrating again the need for standardisation of image data formats enabling a smooth integration of all available datasets (DICOM, STL, and OBJ files) into a craniofacial virtual reality model.
We presented the items selected in coping concepts in this study. After selecting items in several stages, we drew up the SCOOHP scale with 23 items (15 items for positive coping and 8 items for negative coping). The feasibility study showed good acceptability, good understanding of the items and good consistency reliability (α = 0. 59). Conclusions: This is the first study that has enabled us to draw up a specific tool to assess coping strategies in OHrQOL of PWS. A multicentre study involving a larger sample of PWS is underway in order to perform the psychometric validation of the SCOOHP. Trial registration: Clinical Trials Gov NCT02730832.
Participants PWS and health professionals (HPs) were recruited from the administrative database of the Chartreuse Hospital (Dijon, France) by telephone for outpatients or face-to-face for inpatients. PWS were eligible to participate if they were at least 18 years old, they had a diagnosis of schizophrenia (according to the International Classification of Diseases 10 th Revision: ICD-10)  [29] , they provided informed consent to participate in the study, and French was their native language. The exclusion criteria were a diagnosis other than schizophrenia, individuals who were unstable from a psychiatric perspective, serious physical illness, and intellectual disability. In accordance with the guidelines published by Lancaster et al. , 30 PWS were included in the feasibility study  [30]. The study was registered with www.
Generation of items for coping in oral health Semi-structured interviews with 20 PWS and six health professionals (one dentist, one doctor, one psychiatrist, one psychologist, and two nurses)  [26]  and two FGs  [27]  were conducted with eight different individuals (1 It is not possible for researchers to collect data from everyone in a community. The aim of our study was to include all issues relating to OHrQOL and to obtain a "point of saturation"  [35]  regarding the themes addressed by the PWS and the HP who managed patient care. FG Thirty-four individuals participated in the study. The sample size was sufficient to obtain a "point of saturation" for the data  [35]. Data for the semi-structured interview and the FG were compiled at a site of the Chartreuse Hospital that was conducive to discussion.
Feasibility Study Acceptability questionnaire A feasibility study was conducted with another group of 30 PWS recruited at Chartreuse Hospital. We used the same inclusionexclusion criteria as that used for the SCOOHP. Sociodemographic data were collected, and the purpose of the feasibility study was to determine whether the patients found the SCOOHP questions clearly understandable, awkward, disturbing or surprising. We also sought to establish if certain questions could be added or if certain individuals had problems answering this questionnaire. Acceptability criteria, such as the time taken for completion, the amount of missing data, and the number of patients who did not return or who refused to participate were equally assessed. The SCOOHP was a self-administered questionnaire with five possible answers for each item.
Ethical Aspects This study was carried out in accordance with the recommendations of the ethical review board of the Academic Centre for Dentistry Amsterdam. The protocol was independently reviewed and approved by the Medical Ethics Committee of the Academic Medical Centre Amsterdam under number MEC NL45518. 018. 13 and registered at the Dutch Trial Register (NTR4165). All subjects gave written informed consent in accordance with the Declaration of Helsinki. The clinical study was conducted approximating Good Clinical Practice (GCP) as laid out in the International Conference on Harmonization (ICH). The study was scheduled and executed from September-December 2013 at the Department of Periodontology at the Academic Centre for Dentistry Amsterdam, Netherlands. Participants were recruited from a database that contained individuals from universities in and around Amsterdam who had subscribed as being potentially interested in participating in clinical research.
(2013)  with the exception that 30 cycles were used instead of 35, using F515/R806 primers  (Caporaso et al. , 2011). Primers included the Illumina adapters and a unique 8-nt sample index sequence key  (Kozich et al. , 2013). The amount of DNA per sample was quantified using the dsDNA 910 Reagent Kit on the Fragment Analyzer (Advanced Analytical). The amplicon libraries were pooled in equimolar amounts and purified using the Gel Extraction Kit (Qiagen). The Library was quantified using the Quant-iT TM PicoGreen R dsDNA Assay Kit (Thermo Fisher Scientific). Paired-end sequencing of amplicons was conducted on the Illumina MiSeq platform (Illumina, Eindhoven, Netherlands). The sequence data was processed with mothur v. 1. 31. 2  (Schloss et al. , 2009)  in line with the mothur MiSeq SOP  (Kozich et al.
, 2013). After even sampling at 3,000 sequences, the sequences were grouped in operational taxonomic units by Minimal Entropy Decomposition (MED)  (Eren et al. , 2015)  using a minimum substantive abundance value (-M) of 9. Taxonomy was then assigned by querying the representative sequence of each oligotype against the Human Oral Microbiome Database (HOMD) RefSeq v. 13. 2 2  (Chen et al. , 2010)  using the naïve Bayesian classifier. Sequence data is available through the NCBI sequence read archive (SRA) under accession number SUB3627297.
Statistical Methods Statistical analysis and data visualization was performed in R (R Development Core Team, 2016, version 3. 3. 2) using packages ggplot2 (version 2. 2. 1)  (Wickham, 2009) , vegan (version 2. 4-1)  (Oksanen et al. , 2013) , and glmmADMB (version 0. 8. 3. 3) (Fournier, 2012). Multi-dimensional Scaling (MDS) was performed using parts of the vegan package, while negative binomial regression (nbreg) was performed using the glmmADMB package. MDS were performed using the Bray-Curtis distance measure. When applicable, nbreg was performed with subject as a random factor. For nbreg, the overdispersion parameter α was estimated automatically.
A63987, Beckman Coulter): Libraries were prepared by the TruSeq Stranded mRNA HT library kit (Illumina, RS-122-2103) according to the manufacturer's recommendations. Sequencing was performed in the Illumina NextSeq 500. Clean data were obtained from the raw data by removing the sequences of the adapters and low-quality reads using Btrim64-static  (Kong, 2011). The clean reads were aligned to the A. massiliensis F0489 genome (GenBank accession number: AKFT00000000) using STAR with default parameters, allowing up to one-base mismatches  (Dobin et al. , 2013). Sequence count tables were created with HTSeq  (Anders et al. , 2015). Genes of which expression values were 0 in all samples were removed from the dataset before exploratory analysis. Data were normalized and differentially expressed genes (DEGs) between control and maltitol-treated samples were extracted by using DESeq2  (Love et al.
Significant differences between lower-jaw lingual and upper-jaw buccal plaque at baseline were identified through nbreg analysis of the baseline data with jaw as a fixed factor and subject as random factor. Significant differences were linked to an over-abundance of MED nodes assigned as Streptococcus gordonii, HOT 055, and HOT 056 Granulicatella adiacens (paraadiacens), HOT 534, Gemella morbillorum, HOT 046, residing in the upper buccal supragingival plaque. The lower-lingual plaque was found to be dominated by Fusobacterium nucleatum ss_vincentii, HOT 200, Tannerella sp. , HOT 286, Catonella sp. , HOT 164, Dialister invisus, HOT 118, and a number of Leptotrichia species, including Leptotrichia hongkongensis, HOT 213. The full list of significant taxa is provided in Supplementary Table  S1.
ACKNOWLEDGMENTS We thank  Nienke Hennequin-Hoenderdos  for the preparation of the clinical protocol and  Eveline van der Sluijs  for her help obtaining the IRB approval;  Sam C. Supranoto  and  Danielle Ekkelboom  for screening the participants regarding eligibility and  Esther C. J. Martin  who also collected the plaque samples;  Joyce T. Groenewegen  and  Jasamin E. Choo  for their help during the clinical part of the study. Carolien Bosch-Tijhof , Elly van  Deutekom-Mulder ,  Joyce van der Horst , and  Wendy de Wit  are acknowledged for their help in direct processing of the plaque samples after collection. We also thank  B. W. Brandt  and  E. Zaura  for critically reading the manuscript.
The aim of collecting data to describe populations that suffer inequality in oral health is to develop services that effectively target those in need of additional means. The ICF has previously been used to describe a paediatric population requiring specialist dental care, but has not yet been used in this context with adults. In order to integrate the philosophy of the ICF into the discipline of dentistry, it is necessary to develop an ICF Core Set for Oral Health (a subset of ICF items for use in the specific field of oral health). ICF Core Sets have been produced for a large number of health domains to date and the WHO provides a detailed methodology to guide this process  [5]. Empirical data is required for the development of such an ICF Core Set in Oral Health. This universal tool would clarify issues of functioning and environment with relation to the ability to maintain oral health and access care.
Data collection Data was collected in five specialist dental clinics in France, Argentina, Spain, Ireland, and the UK from May 2015 to July 2016. A convenience sample was constructed by recruiting all patients fulfilling the inclusion criteria consecutively, in order of presentation to the service, on the days when the investigator was present. The ICF Checklist for Oral Health was completed by the investigator based on information in the medical/dental records, direct observation of the patient and from a structured interview with the patient and/or primary carer. Before interviewing the patient and/ or caregiver, the medical and dental files of the patient were studied and all relevant data pre-completed. Patient observation took place during the clinical visit. The interview was then used by the investigating clinician to complete missing data.
The study population The following inclusion criteria applied: i) Patient 16 years of age or above on the day of data collection. iii) Patient with a signed consent form. Informed consent was sought from patients and/or their legal representatives for anonymous data collection and analysis. The study population was not intended to be representative. The study was designed to recruit as heterogeneous a population as possible in order to reflect the wide scope of special care dentistry and the aim of data collection in terms of the ICF was to be as exhaustive as possible. Taking into account previous publications following the ICF Core Set methodology, the aim was to record data for 240 patients.
Data entry and analysis Central, double, data entry was performed using Microsoft Excel 1. Descriptive statistics were used to describe the study population and to examine the frequency of problems recorded by the ICF Checklist for Oral Health. For the ICF components Body Functions, Body Structures and Activities and Participation absolute frequencies and relative frequencies (prevalence) of impairment/limitation in the study population were calculated. For Environmental Factors, absolute frequencies and relative frequencies (prevalence) of items entered as either a barrier or facilitator were reported. Traditionally in dentistry, patients requiring specialist care are divided into those with developmental or intellectual disability, and those with complex medical history. For analysis, the study population was therefore divided into two main groups according to principal medical diagnosis using the ICD-10.
Acknowledgments The authors would like to thank both  Professor Pedro Diz Dios  ( School of Medicine and Dentistry, Santiago de Compostela University, Spain ) for his unfailing support and  Dr Graeme Ting  ( Faculty of Dentistry, University of Otago, Dunedin, New Zealand ) for his help with patient recruitment whilst working at the  Dental Hospital, King's College Hospital NHS Foundation Trust, London, UK.
Ethical approval This study conforms with the Declaration of Helsinki, and was approved by the Norwegian ethical committee (2013/1284/REK Vest, University of Bergen) and by the Norwegian Medicines Agency (13/12062-15; EudraCT 2012-003139-50). The clinical trial followed the European guidelines for advanced therapeutic medicinal products (ClinicalTrials. gov, NCT 02751125; https://clinicaltrials. gov/ct2/show/NCT02751125). Two experienced clinicians informed the patients about the study. After signing the consent form, the patients underwent clinical examination, including clinical photographs and dental impressions, and provided a medical history. If the patient met the inclusion criteria, cone beam computer tomography (CBCT) (Morita 3D Accuitomo F17, Japan) and dental X-ray scans were taken.
Reconstruction of 3-dimensional models The DICOM files of the images were then imported to Mimics program 19. 0 (Materialize NV, Leuven, Belgium). The threshold of each case was selected manually, based on subjective evaluation of the apparent display of the residual jaw bone and the graft, this defined the boundary of the region of interest (ROI) of each case. The mask of the ROI at T0 was achieved and visualized in axial, sagittal, and coronal views. The 2D masks were then transformed into 3D models using the so-called "calculate 3D" function. The volume in cubic millimeters of the graft models was acquired automatically with a display of a color-coded 3D model. The superimposition of the images at T0 and T1 was applied to the Standard Tessellation Language (STL) registration method  [48].
Processing bone biopsies Micro-computed topography analyses The bone biopsy specimens were maintained in 10% buffered formalin. Selected bone biopsies were scanned with the high-resolution μ-CT SkyScan1172® (SkyScan, Kontich, Belgium) with the following technical parameters: 100 mA and 100 kV power intensity, copper-alumina filter and 360 °rotation, and pixel size or resolution for acquisition and image reconstruction of 2. 7 μm. Images from the scanning of biopsies were reconstructed by the software NRecon® (SkyScan) to obtain 2D and 3D images. CTvox (version 3. 2; SkyScan) was employed to create 3D images for the biopsies. The analyzed histomorphometric parameters have been described previously  [49] : bone volume (BV); tissue volume (TV); bone volumetric fraction (BV/TV); trabecular thickness (Tb.
3a, b ). Linear measurements of the width and height were performed from all CBCT scans in iView software (version 2. 2. 0. 3. J; Morita MFG Corporation). Grafted bone could easily be distinguished from residual bone by density and structure on the scans taken immediately after the grafting procedure. As these measurements are known to be operator dependent, the measurements were all done by one specialist in oral radiology (SS)  [50, 51]. All patients had sufficient increase in alveolar width to have dental implants installed (Fig. 4  and Table  3 ). The average volume of bone increased by 887. 23 ± 365. 01 mm 3 (Table  3 ). Both the increase in width of the alveolar ridge and the increase in volume of the alveolar ridge were statistically significant. The mean increase in bone width (n = 14) was 4.
05 mm (95% CI 2. 74, 5. 36; p < 0. 001) and the mean increase in volume (n = 14) was 887. 23 mm 3 (95% CI 676, 1097. 98; p < 0. 001). Formation of mineralized tissues was evaluated by μ-CT and histology from the biopsies taken during implant installation. From the μ-CT scan datasets, 3D models were built for visualization (Fig. 5A ). It was possible to identify  Histological analysis revealed that BCP granules were well integrated with deposition of newly formed bone tissue on the surface of the particles with osteoblast lining cells and subsequent deposition of lamellar bone tissue (Fig. 5B ). The BCP granules demonstrated continuous degradation and dissolution, with the presence of multinucleated cells, probably osteoclasts, as well as macrophage CD68 + cells on the surface of the particles.