dataesr/scientific-paragraphs-categorization huggingface dataset:
METHODS An electronic search in the PubMed and Scopus databases was conducted with the following keywords: ("photobiomodulation" OR "PBM" OR "laser therapy" OR "LLLT" OR "laser") AND ("head and neck cancer" OR "oral cancer") AND ("mucositis" OR "oral mucositis" OR "dysgeusia" OR "oedema" OR "xerostomia" OR "dermatitis" OR trismus) until October 2021. Papers in languages different from English, Italian, Spanish, Portuguese, and French were excluded. Only original articles and reviews were initially included, excluding short reports and case reports. Further, articles not specifying laser protocol were also excluded. A global group of experts in oral medicine, oncology, radiation biology, and PBM examined and discussed this literature to further develop consensus.
| DISCUSSION Data from the American Joint Replacement Registry showed that infection is the number one cause of early and late failure for both hip and knee replacement. 20 Despite best efforts of prevention, the number of primary hip and knee replacement leading to infection is still on the rise and affects patient quality of life, risk of infection recurrence, amputation, and death. In this in vivo study, we demonstrated that a novel covalently grafted antimicrobial compound significantly decreased MRSA growth both on a titanium disc and in the surrounding soft tissues. Moreover, our finding also indicates the absence of local and systemic toxicity. High bacterial median log 10 reductions on implants were achieved at both 7 and 14 days postoperatively despite the use of a high inoculum, the absence of antibiotics, and the use of a virulent strain with known capability to adhere to biomaterials (MRSA).
In principle, DEXA and SDEXA could use almost the same processing. DEXA needs spectral information, which is generated by filtration, while scout scans from a dual-energy CT system can use a spectral detector fulfilling this task. Both methods then need the calculation of the aBMD and segmentation. First, we show how to calculate aBMD data and present a denoising algorithm improving the SNR of aBMD results. Denoising is applied, as scout acquisitions are conducted with a very low dose and additionally material decomposition introduces anti-correlated noise onto the aBMD material maps. As a standard of reference, spectrally determined vBMD values from the subsequent CT measurement are used, allowing the generation of projected aBMD masks from CT data to obtain a matched comparison between vBMD and aBMD.
With our approach using the same CT system, where we compare SDEXA with vBMD, we know the beam geometry and position. This allowed us to match vBMD with SDEXA in a more precise way. In comparison to Laugerette et al. [11, 12] , where phantom measurements and fracture differentiation on scout measurements were analyzed, we investigated the correlation between measured aBMD and vBMD. Furthermore, we generated projected aBMD images in anterior-posterior (AP) and lateral views from the spectral CT data and compared the osteoporosis classification accuracy for both views. The aim of this study was to assess the clinical performance of SDEXA measurements using volumetric BMD as a ground truth.
Protocol settings A standard CT abdomen protocol with a fixed tube voltage of 120 kVp and an exposure of from 20 to 122 mAs per rotation (1. 80 to 10. 5 mGy CT dose index volume) was used on a 64-slice single source dual-layer CT scanner with a detector coverage of 4 cm and a rotation time of 0. 33 s (IQon, Philips Healthcare, Best, The Netherlands). Scout scans were acquired with a peak tube voltage of 120 kVp and a tube current of 30 mA. The CT dose index volume and dose length product, estimated dose converted from two-dimensional (2D) to 3D were approximately 0. 06 mGy and 3. 5 mGy*cm (< 0. 06 mSv, k = 0. 015 for abdomen and pelvis) in scout measurements and on average 7. 2 mGy and 400 mGy*cm (≈ 6. 0 mSv, k = 0. 015 for abdomen and pelvis) in abdomen CT protocols. Spectral raw data were reconstructed using a standard soft tissue filter kernel (type B) with an axial slice thickness of 0.
By adjusting the projection angle to 0 or 90°, AP and lateral scout images could be projected. Volumetric BMD images (Fig. 1c ), as well as 3D spine masks (Fig. 1c , yellow mask), served as input for the projection algorithm. By projecting the vBMD maps, artificially generated aBMD maps in lateral and AP view were generated for every patient. Correlation and classification analysis was performed on those projected aBMD maps, as well as measured aBMD maps from spectral scout images. To obtain a trabecular-based 2D mask for aBMD quantification on scout measurements (Fig. 1f , yellow mask), projected aBMD maps (Fig. 1e ) together with an image registration step were used. The open-source software SimpleITK  [23, 24]  served as an affine and translatory registration library. An aBMD value for L1 to L4 was obtained in all patients.
Statistical analysis The open-source scientific computing library for Python SciPy  [25]  was used to calculate a linear least-squares regression to correlate the 3D with 2D BMD measurements. The slope, intercept, Pearson correlation coefficient, and p-value for a hypothesis test whose null hypothesis is that the slope is zero were obtained. Furthermore, the standard error of the estimated slope was assessed, and a 95% confidence interval on slope and intercept was calculated by using a two-sided inverse Student t-distribution. In addition, a two-sided t-test for the null hypothesis that two independent samples have identical mean values was used. To compare the classification accuracy of aBMD measurements, a receiver operating characteristic (ROC) for a binary classification task was consulted  [26].
Study Measures and Data Collection Children were examined for three variables: DMFT index, BMI, and Vitamin D serum levels. The DMFT index is a measurement for dental caries ranging from 0-28 for permanent dentition and 0-20 for primary dentition, in which 0 means no caries, and the higher the number, the higher the number of dental caries. DMFT and dmft are used to assess the permanent and primary dentitions respectively and their average is calculated for mixed dentitions. However, for easier presentation and understanding, only the notation of DMFT is used in the tables and in the text. Each tooth is given a single score. A healthy, non-carious, not filled, and not missing due to caries tooth is given a score of 0. In contrast, a carious tooth, filled with restoration or missing due to caries, is given a score of 1.
Data Analysis Multivariate regression analysis is performed to investigate the effects of Vitamin D level, BMI, and other possible confounders on DMFT. Furthermore, DMFT, Vitamin D, and BMI variables were categorized to assess odds ratios between the categories. Categorical analysis is common in the literature to study these associations  [49] [50] [51]. This is probably due to the high number of known and unknown covariates affecting the correlation. Statistical analysis was performed via the Statistical Package for the Social Sciences (SPSS) (SPSS for Windows, Version 25. 0, Chicago, IL, USA) program. Numerical variables were presented as the median and interquartile range (IQR), while categorical variables were presented as the frequency and percentage. Normal distribution was evaluated by the Kolmogorov-Smirnov test.
The comparison between the sexes revealed higher levels of Vitamin D concentration and dental caries in boys (Table  2 ). In contrast, age and BMI were not significantly different among the two groups. A comparison of the three main variables according to the season in which the data were collected revealed that Vitamin D levels were significantly higher in summer in contrast to winter. On the other hand, the BMI was higher in winter than in summer (Table  3 ). Taking DMFT as the dependent variable, multivariate regression analysis was done to check the effects of age, sex, seasons, BMI, and vitamin D on DMFT. Age was the only significant variable after adjustment (Table  4 ). Age and BMI negatively affected DMFT, while vitamin D levels were positively associated with the DMFT index. Next, the data are categorized to examine the crude ORs.
Background: Three-dimensional (3D) printing is now a widely recognized surgical tool in oral and maxillofacial surgery. However, little is known about its benefits for the surgical management of benign maxillary and mandibular tumors and cysts. Purpose: The objective of this systematic review was to assess the contribution of 3D printing in the management of benign jaw lesions. Methods: A systematic review, registered in PROSPERO, was conducted using PubMed and Scopus databases, up to December 2022, by following PRISMA guidelines. Studies reporting 3D printing applications for the surgical management of benign jaw lesions were considered. Results: This review included thirteen studies involving 74 patients. The principal use of 3D printing was to produce anatomical models, intraoperative surgical guides, or both, allowing for the successful removal of maxillary and mandibular lesions.
Search strategy An electronic search of the literature was conducted using the PubMed and Scopus databases. The investigators searched the databases until December 27, 2022, using the following equation: (("guided surgery") OR ("digital design") OR ("virtual surgical planning") OR ("computer-assisted planning") OR (CAD/CAM) OR ("3D printed model") OR ("three-dimensional printing") OR ("Additive manufacturing") OR ("rapid prototyping")) AND (("jaw cyst") OR ("odontogenic tumor") OR ("benign jaw tumor") OR ("mandibular cyst") OR ("mandibular tumor")) NOT ((scapular) OR (fibula) OR (malignant)) Additional relevant research articles were added after conducting a manual search.
Screening of studies and data collection The selection of articles, according to the inclusion and exclusion criteria defined above, was carried out independently by the three reviewers (MF, OT, and SG) for the title, abstract, and full-text screening stages. The initial search yielded a first list (list 0). A second list was obtained by selection based on titles and their abstracts (list 1). A third list was yielded after reading the full-text articles (list 2). In addition, the electronic search was complemented by a manual search (list 3). For eligible articles, the following data were recorded: the publication date, author's nationality, study design and number of patients, the type of lesions and their localization, application of 3D printing, the clinical criteria that had been evaluated, and the obtained outcomes.
General information about the included studies All articles were published between January 2017 and December 2022. Among the 13 selected articles: one study was a randomized clinical trial  [11] , one was a comparative retrospective study  [12] , one was a prospective clinical trial (Clinical trial registration number: NCT05253261)  [13] , two were case-series  [14, 15] , six studies were case reports  [16] [17] [18] [19] [20] [21] , and there were two technical notes  [22, 23]  (Table  1 ). The risk of bias in the included studies ranged from "low" to "some concerns". A summary of the risk of bias is provided in Fig. 2. The follow-up time of the studies ranged from 3 weeks to 4 years. The age of the patients ranged from 5 to 35 years.
Acknowledgments: The team thanks the  Conseil Régional du Nord-Pas de Calais  and the  European Regional Development Fund (ERDF)  for the support of the  SEM facility in Lille (France)  and the  University of Lille ,  CNRS ,  INRAE ,  Centrale Lille ,  UMR 8207-UMET-Unité Matériaux et Transformations  for the financial support.
Study design and participants REGOBONE, an investigator-initiated signal-seeking trial, is a basket study of five parallel independent cohorts of different metastatic bone sarcoma histopathological subtypes. Parallel cohorts assessed the activity and safety of regorafenib or placebo, using a randomised, non-comparative, double-blind, placebo-controlled phase II trial design. We present here the results of the chordoma cohort. The study was approved by an ethical and regulatory committee (French Ethical Committee, Comité de Protection des Personnes Sud Méditerrannée 1, approved on 26 March 2014). All patients provided written informed consent before enrolment. The trial is registered in the European Clinical Trials Register database (EudraCT N : 2013-003910-42) and at ClinicalTrials. gov (NCT02389244).
Statistical analysis When the REGOBONE study was designed there was a paucity of published data regarding PFS of patients with metastatic/recurrent chordoma following failure of prior targeted therapy or chemotherapy for progressing relapsed disease. Therefore, we chose PFR-6 as the primary endpoint. Using a similar design as for the other REGOBONE cohorts, we calculated the sample size by A'Hern single stage design for phase II trials similar to a Fleming phase II design but assuming an exact binomial distribution. 12 The sample size for chordomas cohort was calculated as follows: a lower limit of 40% progression-free patients or less would mean that the regorafenib did not warrant further investigation in this setting. A sample size of 23 patients provided 80% power to reject the null hypothesis with a one-sided, type 1 error of 5%, with 10 successful patients being the lower cutoff.
ACKNOWLEDGEMENTS We thank the patients and their family for their participation in the study. We thank all the UNICANCER sarcoma staff members involved in the trial management. The data management was conducted by  UNICANCER , the analysis was done by  Centre Léon Bérard. We thank the patient advocacy group InfoSarcomes. We thank the  French National Cancer Institute  for funding the labelled networks for management of sarcoma (e. g. NetSarc, RRePS, RESOS, and InterSarc).
Sample harvesting and preparation In each patient, two bone samples were harvested (one AB and one FB sample). All samples were retrieved using an oscillating saw. The AB samples were taken from the vicinity of the connecting area of the original bone to FFF during bone contouring. Since all FFF's were CAD/CAM-planned and raised using CAD/CAM templates, the slice of bone between two segments (which was not further used) was taken as the FB sample. Patient data are listed in Table  1. After harvesting, the bone samples were fixed in 4% neutral buffered formalin. Subsequently, dehydration in ascending alcohol series (water, 70%/80%/96%/100% ethanol) for three days each followed. The samples were defatted in xylene and infiltrated, embedded, and polymerized in Technovit ® 9100 New (Heraues Kulzer, Wehrheim, Germany).
Synchrotron computed tomography imaging Samples of four patients were SR μ-CT scanned at a voxel size of 2. 27 μm, and samples from seven patients (including 3 that were analyzed at the 2. 27 voxel-size setup) were scanned at 640 nm voxel size to address the difference in bone morphology at two different voxel-sizes [Figures for all samples are listed in Supplementary Figure  S1  (2. 27 μm), respectively Supplementary Figure  S2  (640 nm)]. The imaging of the 640 nm data was performed at Synchrotron Soleil, France. A SR μ-CT setup of the Psiché (PSICHÉ) beamline was used with a beam energy of 45 keV and a sample to detector distance of 45 mm. For each sample, a total of 5600 projections were exposed for 40 ms each and were recorded over an angle of 360 °using a Hamamatsu ORCA Flash sCMOS camera.
Phase retrieval and image reconstruction was performed using Paganin's method  (Paganin et al. , 2002)  and a filtered back projection algorithm, respectively with a delta/beta ratio of approximately 65. Data of 2. 27 μm voxel-size were acquired at the beamline ID 19 of the European Synchrotron Radiation Facility (ESRF) in Grenoble, France using 46. 9 keV beam energy and a sample detector distance of 460 mm. For each sample, 4000 radiographs over an angle of 360 °were recorded at an acquisition time per frame of 20 ms. A pco. edge 5. 5 camera (PCO AG, Kelheim, Germany) was used. As with the 640 nm data, reconstruction was carried out using Paganin's method in combination with the conventional filtered back projection algorithm employing a delta/beta ratio of 350  (Paganin et al. , 2002).
Segmentation of samples For all samples, representative volumes of interest (VOIs) were selected with a particular emphasis on artifact-free and physiological bone anatomy. In FB, cortical regions were chosen; and AB was mostly assigned to the cortical bone. The VOI of the 640 nm scan was set within the VOI scanned at 2. 27 μm. Within each VOI, different tissue regions were segmented into mineralized tissue, vessel pores, and osteocyte lacunae. For both voxel-sizes (2. 27 and 640 nm), inhouse-developed MATLAB (R2018b, The MathWorks Inc. , Natick, MA, United States) scripts combining several different morphological operations were used. To obtain the mineral mask on the binarized data, a closing of all pores (vessel pores and osteocyte lacunae) within the mineralized region was achieved by a Euclidian distance map coupled to a thresholding step.
Combining the mineral mask and the inverse of the binarized data resulted in a mask containing vessel pores. Osteocyte lacunae were extracted from the gray value data with a bottom-hat transformation and a following thresholding step. A connected component analysis was used to size and filter osteocyte lacunae between 30 and 8,000 μm 3 and with length and width below 130 and 30 μm.
Absolute permeability and tensor of absolute permeability Fluid simulation was performed for all 2. 27 μm scans. The tensor of permeability was calculated through the Absolute Permeability Tensor Calculation module (Thermo Scientific Avizo Software, XLab Module, Version 2020. 2). This tensor enables the computation of permeability in all three spatial directions as well as the computation of eigenvectors and their associated eigenvalues. The ratios of three eigenvalues (E1, E2 and E3) to each other were determined to quantify the anisotropic behavior of absolute permeability (with E1>E2>E3). The termination conditions for the simulations were that either the convergence criterion was smaller than 10 -5 or the number of iterations reached 10 6. Tensor calculation is based on a mathematical approach which considers the sample to be representative of an infinite or macroscopic material.
In only one sample does the 640 nm voxel-size data reveal a lower lacunar density, which might have originated from the heterogeneity within the individual sample. It must be noted that the analysed VOI of this particular sample was much smaller than that of the other samples. This implies that at 2. 27 μm voxel-size of the used imaging setup and analysis, potentially undersegments about 5%-15% of the lacunae. Additionally, the shape of each lacuna was examined: the ratios of the lacunae principal axes lengths indicate a similar shape in the lacunae of AB and FB. The shape of the osteocyte lacunae and the potential influence on the function of osteocytes as a "mechanosensor" of the bone are assumed to be affected by mechanical loading of the bone  (van Oers et al. , 2015). Round osteocytes are considered to be more mechanosensitive compared to elongated osteocytes in long bones that are accustomed to high mechanical loadings  (Bacabac et al.
Acquisition and reconstruction parameters Three acquisitions were performed at 120 kVp and 255 mAs using a retrospective ECG-gated helical acquisition at a chosen heart rate (60 bpm) on each CT system. Tube current modulation was disabled. Beam collimation, rotation time, and pitch factor for the EID-DECT scanner were chosen to imitate clinical practice (Table  1 ). Data were reconstructed during the mid-diastolic phase (78% of the R-R interval) of the cardiac cycle. For EID-DECT, raw data were reconstructed according to clinical practice using high-resolution (HR) parameters, with level 1 of the 7 available levels in the spectral reconstruction algorithm, the highest-frequency kernel available CB (Cardiac Standard) and the minimal slice thickness achievable (0. 67 mm), corresponding to HR-EID-DECT images.
Task-based image quality assessment A task-based image quality assessment was performed using iQMetrix-CT software developed by a working group from the French Society of Medical Physicists (SFPM)  [39]. For all CT systems, the NPS was computed on the same volume in the z-axis (close to 5. 5 mm) using four square regions of interest (ROIs) of 64 × 64 pixels (Supplemental Fig. 1. A). Table  1  Acquisition and reconstruction parameters used on the dual-layer energyintegrating detector dual-energy CT systems (EID-DECT) (IQon CT, CT7500) and spectral photon-counting CT (SPCCT) systems HRB (high-resolution standard filter) and CB (cardiac standard filter) were used for high-resolution (HR) imaging in combination with 0. 67 mm slice thickness. Detailed 2 was used for ultra-high-resolution (UHR) imaging in combination with 0.
For SPCCT, raw data were reconstructed using high-resolution parameters with HRB kernel and 0. 67-mm slice thickness, and ultra-highresolution parameters with Detailed-2 kernel and 0. 43 mm slice thickness Fig. 2  Task-based transfer function curves according to the energy levels obtained for dual-energy CT images from two dual-layer CT scanners with energy-integrating detectors (IQon CT, CT7500) and a spectral photon-counting CT (SPCCT). For SPCCT, raw data were reconstructed using high-resolution parameters with HRB kernel and 0. 67-mm slice thickness, and ultra-highresolution parameters with Detailed 2 kernel and 0. 43 mm slice thickness Fig. 3  A Contrast between the phantom background material and the iodine insert according to the energy levels obtained for two duallayer energy-integrating detectors dual-energy CT images (IQon CT, CT7500) and a spectral photon-counting CT (SPCCT).
Acknowledgements We acknowledge  Angele Houmeau ,  Bernard Martin ,  Pierre Lin-Wee-Kuan ,  Cyril Prieur ,  Adeline Mansuy ,  Morgane Bouin ,  Apolline Barbe ,  Jean-Baptiste Langlois ,  Franck Lavenne ,  CERMEP Facility  and their employee for their help in conducting this clinical research experience. We thank  Teresa Sawyers Teresa Sawyers , medical writer at the  BESPIM, Nîmes University Hospital  for her help in editing the manuscript.
Porosity After the storage in distilled water for 24 h at 37 • C, the interior texture of BD, BR, and WR were investigated in 3D by using micro-computed X-ray tomography (µCT) (EasyTom 160 from RX Solutions, Chavanod, France). A current of 125 µ and a voltage of 45 kV were used in the execution of imaging procedures using a micro-focused tube supplied with a lanthanum hexaboride (LaB 6 ) filament. The source-to-object distance (SOD) and the source-to-detector distance (SDD) were regulated to have a voxel size of around 2. 3 µm. The software Xact64 (Version: 22. 01. 1 2022-03-14, RX Solutions, Chavanod, France) was used to perform the volume reconstruction after the application of ring artifact attenuation and the geometrical corrections. The Avizo software (Version: 3D 2022-2) was used in the image process to remove insignificant small objects, de-noise the images with a median filter, determine the 3D geometrical aspects of the objects of interest, and segment the image intensity in order to reveal the objects of interest  [19].
The compression strength was calculated in megapascals (MPa) according to the following formula: σc = 4P/πD 2   where P is the maximum recorded force during the test and D is the initial sample diameter. The results of mechanical tests were statistically analyzed using the Kruskal-Wallis test associated with the Tukey test. SigmaPlot release 11. 2 (Systat Software, Inc. , San Jose, CA, USA) was performed with a statistical significance set at α = 0. 05.