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Objectives: Lateral ridge augmentation (LRA) is a surgical technique to gain bone prior to implant placement. Performing cone‐beam computed tomography (CBCT) pre‐ and post‐surgery allows for quantitative comparison of the buccal–lingual width and the vertical height of the edentulous ridges. This study used CBCT images to evaluate the bone regeneration following surgery. Methods: A total of 30 cases from adult patients who underwent LRA and had high‐quality CBCT images taken pre‐ and post‐surgery from the same CBCT scanner were available for the retrospective study. Study data included linear measurements of the bone ridge width and height obtained from the middle of the edentulous ridge and a volumetric measurement of bone growth at the edentulous site observed on the CBCT scan. Results: The reliability of the measurements was excellent as indicated by Intra‐Class Coefficient values of 0.974 or higher. There was a significant mean bone increase from pre‐surgery compared to post‐surgery for both the linear and volumetric measurements. The linear bone gain ranged from 1.5 to 2.5 mm and volumetric gain from 250 to 750 mm3. However, two patients did not gain any bone. Multivariate regression showed the strongest predictors of bone gain post‐surgery were the pre‐surgery bone volume and a surgical site being in the mandible. For maxillary surgical sites, particularly anterior areas, the LRA surgeries were the least successful. Conclusions: LRA before implant placement helped to increase bone for the majority of patients, particularly for surgical sites in the mandible. The quantitative analyses in the CBCT images showed excellent intra‐examiner agreement. [ABSTRACT FROM AUTHOR]

Precision orthodontics entails the use of personalized clinical, biological, social and environmental knowledge of each patient for deep individualized clinical phenotyping and diagnosis combined with the delivery of care using advanced customized devices, technologies and biologics. From its historical origins as a mechanotherapy and materials driven profession, the most recent advances in orthodontics in the past three decades have been propelled by technological innovations including volumetric and surface 3D imaging and printing, advances in software that facilitate the derivation of diagnostic details, enhanced personalization of treatment plans and fabrication of custom appliances. Still, the use of these diagnostic and therapeutic technologies is largely phenotype driven, focusing mainly on facial/skeletal morphology and tooth positions. Future advances in orthodontics will involve comprehensive understanding of an individual's biology through omics, a field of biology that involves large‐scale rapid analyses of DNA, mRNA, proteins and other biological regulators from a cell, tissue or organism. Such understanding will define individual biological attributes that will impact diagnosis, treatment decisions, risk assessment and prognostics of therapy. Equally important are the advances in artificial intelligence (AI) and machine learning, and its applications in orthodontics. AI is already being used to perform validation of approaches for diagnostic purposes such as landmark identification, cephalometric tracings, diagnosis of pathologies and facial phenotyping from radiographs and/or photographs. Other areas for future discoveries and utilization of AI will include clinical decision support, precision orthodontics, payer decisions and risk prediction. The synergies between deep 3D phenotyping and advances in materials, omics and AI will propel the technological and omics era towards achieving the goal of delivering optimized and predictable precision orthodontics. [ABSTRACT FROM AUTHOR]

The structural characterization, efficient recombinant expression and purification of rat lysyl oxidase propeptide region (LOX-PP) is reported. The high isoelectric point and its disordered structure of LOX-PP suggested that LOX-PP could associate with extracellular and intracellular binding partners to influene the its known biological activities as a tumor suppressor and inhibitor of cell proliferation.

Background Upper airway analysis is an often-cited use of CBCT imaging by orthodontists; however, the reliability of airway measurements using this technology is not fully established. Objective To determine the intra-examiner and inter-examiner reliability of the complete process of volumetric and cross-sectional area assessments of the upper airway using CBCT imaging. Materials and Methods Six examiners of varying levels of education and clinical experience performed the steps necessary for airway analysis, including manual orientation, slice and threshold selection and measured nasopharyngeal, oropharyngeal, hypopharyngeal and total upper pharyngeal airway volumes in addition to minimum cross-sectional area on the CBCT images of 10 patients. All measurements were repeated after 4-weeks. Intra- and inter-examiner reliability was calculated using ICC and 95% CI. Results Threshold selection showed poor intra- and poor inter-examiner reliability, whereas minimum cross-sectional area showed moderate intra- and poor inter-examiner reliability. Intra-examiner reliability of volumetric measurements varied based on the region assessed with ICC ranging from 0.747 to 0.976, and was worst for hypopharynx and best for the oropharynx. Inter-examiner reliability of volume measurements was generally lower, with ICC ranging from 0.175 to 0.945, and was worst for nasopharynx and best for the oropharynx. Conclusions This study, for the first time, assessed the reliability of upper airway analysis with CBCT when all steps of image processing and measurement are performed by each examiner. Reliability improved with examiner experience, though was generally low for the hypopharynx and nasopharynx volumes and overall minimal cross-sectional area. The oropharyngeal volume was the only parameter to have excellent intra- and inter-examiner reliability. [ABSTRACT FROM AUTHOR]