Call for algorithmic fairness to mitigate amplification of racial biases in artificial intelligence models used in orthodontics and craniofacial health.

Machine Learning (ML), a subfield of Artificial Intelligence (AI), is being increasingly used in Orthodontics and craniofacial health for predicting clinical outcomes. Current ML/AI models are prone to accentuate racial disparities. The objective of this narrative review is to provide an overview of how AI/ML models perpetuate racial biases and how we can mitigate this situation. A narrative review of articles published in the medical literature on racial biases and the use of AI/ML models was undertaken. Current AI/ML models are built on homogenous clinical datasets that have a gross underrepresentation of historically disadvantages demographic groups, especially the ethno-racial minorities. The consequence of such AI/ML models is that they perform poorly when deployed on ethno-racial minorities thus further amplifying racial biases. Healthcare providers, policymakers, AI developers and all stakeholders should pay close attention to various steps in the pipeline of building AI/ML models and every effort must be made to establish algorithmic fairness to redress inequities.

The use of teleorthodontics during the COVID-19 pandemic and beyond - perspectives of patients and providers.

BACKGROUND: The COVID-19 pandemic significantly impacted dental services, resulting in reduced staff availability, limited appointments, and some dental clinics even being forced to close their doors. Despite these challenges, the need for dental consultants remained present, particularly in emergency situations. One area of orthodontics that had seen a surge in demand during the pandemic is Teleorthodontics. With the help of Teleorthodontics, orthodontic consultations, assessments, and even treatment monitoring could be conducted remotely, making it a safe and convenient option for patients during those challenging times. AIM: This survey aimed to evaluate the acceptance of patients and their orthodontists on the use of different modes of communication through Teleorthodontics during the COVID-19 pandemic and their willingness to continue using this in the future. METHODS: An online survey instrument in Qualtrics was distributed to orthodontic patients at the University of Illinois, Chicago. The survey was available on a rolling basis for up to 6 months. A total number of 364 partients voluntarily participated in the survey. The Faculty and Residents were also asked to participate in a survey through recruitment via their UIC email addresses. RESULTS: According to our survey, both patients and providers showed acceptance of Teleorthodontics and have used it in different forms during orthodontic treatment. The application is easy-to-use, convenient, and not at all time-consuming. Overall satisfaction with using this application was recorded at 92%, with 66% of patients stating that it saved them time by eliminating the need to travel to the orthodontic clinic. 30% of providers found that the interaction with patients using Teleorthodontics was a positive experience and would recommend it in future. CONCLUSION: Teleorthodontics has shown great potential, particularly in follow-up cases, and holds promise as a valuable tool for online remote dental consultations in the future.

Blockchain technology and federated machine learning for collaborative initiatives in orthodontics and craniofacial health.

There is a paucity of largescale collaborative initiatives in orthodontics and craniofacial health. Such nationally representative projects would yield findings that are generalizable. The lack of large-scale collaborative initiatives in the field of orthodontics creates a deficiency in study outcomes that can be applied to the population at large. The objective of this study is to provide a narrative review of potential applications of blockchain technology and federated machine learning to improve collaborative care. We conducted a narrative review of articles published from 2018 to 2023 to provide a high level overview of blockchain technology, federated machine learning, remote monitoring, and genomics and how they can be leveraged together to establish a patient centered model of care. To strengthen the empirical framework for clinical decision making in healthcare, we suggest use of blockchain technology and integrating it with federated machine learning. There are several challenges to adoption of these technologies in the current healthcare ecosystem. Nevertheless, this may be an ideal time to explore how best we can integrate these technologies to deliver high quality personalized care. This article provides an overview of blockchain technology and federated machine learning and how they can be leveraged to initiate collaborative projects that will have the patient at the center of care.

A Novel Vitamin D Receptor Agonist, VS-105, Improves Bone Mineral Density without Affecting Serum Calcium in a Postmenopausal Osteoporosis Rat Model.

BACKGROUND AND OBJECTIVES: VS-105, a novel vitamin D receptor agonist with significantly less hypercalcemic side effects than calcitriol, is a useful tool to investigate whether or not a vitamin D receptor agonist at non-hypercalcemic doses could improve bone mineral density (BMD). METHODS: VS-105 and calcitriol were evaluated in an ovariectomized (OVX) osteoporosis rat model and in calvariae bone organ culture. RESULTS: Treatment of OVX rats by VS-105 (0.1, 0.2 or 0.5 µg/kg, intraperitoneal, 3×/week, for 90 days) significantly improved BMD in the L3 lumbar vertebra in a dose-dependent manner (sham vs. OVX/vehicle: 324 ± 14 vs. 279 ± 10 mg/cm2; VS-105 at 0.1, 0.2 and 0.5 µg/kg: 306 ± 9, 329 ± 12, and 327 ± 10 mg/cm2, respectively) without affecting serum calcium (Ca). Calcitriol at 0.1 µg/kg significantly increased BMD but it also increased serum Ca. VS-105 and calcitriol at the test doses significantly suppressed serum parathyroid hormone and promoted tibia bone growth. With respect to biomarkers of bone remodeling, calcitriol and VS-105 both significantly elevated serum osteocalcin. In the calvariae bone organ culture, net Ca release was significantly less in VS-105-treated groups (vs. calcitriol). CONCLUSIONS: VS-105 is efficacious in improving BMD in a dose range that does not affect serum Ca in OVX rats; the improvement in BMD by VS-105 is attributable to increased osteoblastic activity and reduced osteoclastic bone resorption.

Cyclic stretch and compression forces alter microRNA-29 expression of human periodontal ligament cells.

MicroRNAs (miRs) play an important role in the development and remodeling of tissues through the regulation of large cohorts of extracellular matrix (ECM) genes. The purpose of the present study was to determine the response of miR-29 family expression to loading forces and their effects on ECM gene expression in periodontal ligament cells, the key effector cell population during orthodontic tooth movement. In a comparison between miRs from human periodontal ligament cells (PDLCs) and alveolar bone cells (ABCs) from healthy human subjects, the ABC cohort of miRs was substantially greater than the corresponding PDLC cohort. Cyclic mechanical stretch forces at 12% deformation at 0.1Hz for 24h decreased expression of miR-29 family member miRs about 0.5 fold while 2g/cm(2) compression force for 24h increased miR-29 family member expression in PDLCs 1.8-4 folds. Cyclic stretch up-regulated major ECM genes in PDLCs, such as COL1A1, COL3A1 and COL5A1, while the compression force resulted in a down-regulation of these ECM genes. Direct interactions of miR-29 and Col1a1, Col3a1 and Col5a1 were confirmed using a dual luciferase reporter gene assay. In addition, transient transfection of a miR-29b mimic in mouse PDLCs down-regulated Col1a1, Col3a1 and Col5a1 while the transfection of miR-29b inhibitor up-regulated these genes compared to control transfection indicating that these target ECM genes directly responded to the altered level of miR-29b. These results provided a possible explanation for the effects of the miR-29 family on loaded PDLCS and their roles in extracellular matrix gene expression.