Journal of dental research最新文献

Mesenchymal stem cells (MSCs), characterized by their undifferentiated and multipotent nature, can be derived from various sources, including bone marrow, adipose, and dental tissues. Among these, dental MSCs (DSCs) exhibit universal MSC characteristics and are attracting considerable attention for regenerating oral and craniofacial tissues. This review provides a contemporary overview of recently published clinical studies using DSCs for various orodental and maxillofacial regenerative applications, including bone, periodontal, and endodontic regeneration. It also explores the utilization of DSCs in treating systemic conditions, exemplified by their application in managing conditions such as COVID-19 and osteoarthritis. The available evidence underscores the potential of DSCs and their secretome as efficacious tools in regenerative medicine for both dental and nondental clinical applications, supporting the continued promise of stem cell-based therapies. It is nevertheless evident that there are a number of important challenges that restrict the widespread utilization of DSCs, namely, difficulty in standardizing autologous preparations, insufficient cell surface marker characterization, high production costs, and regulatory compliance requirements. Further, the unique requirements of dental applications, especially complex structures such as the periodontium, where temporospatial control over the healing process is required, necessitate the combination of stem cells with appropriate scaffolds according to the principles of tissue engineering. There is currently insufficient evidence to support the clinical translation of DSCs into clinical practice, and phase 3 clinical trials with standardized protocols for cell sourcing, propagation, dosing, and delivery are required to move the field forward. In summary, this review provides a contemporary overview of the evolving landscape of stem cell therapy, offering insights into the latest developments and trends as well as the challenges that need to be addressed for the widespread application of DSC-based cell therapies.

Current interventions for oral/dental diseases heavily rely on operative/surgical procedures, while the discovery of novel drug targets may enable access to noninvasive pharmacotherapy. Therefore, this study aims to leverage large-scale data and Mendelian randomization (MR) techniques, utilizing genetic variants as instruments, to identify potential therapeutic targets for oral and dental diseases supported by genetic evidence. By intersecting 4,302 druggable genes with expression quantitative trait loci from 31,684 blood samples, we identified 2,580 druggable targets as exposures. Single nucleotide polymorphisms associated with dental disease/symptom traits were collected from FinnGen R9, the Gene-Lifestyle Interactions in Dental Endpoints consortium, and the UK Biobank to serve as outcomes for both discovery and replication purposes. Through MR analysis, we identified 43 druggable targets for various dental disease/symptom traits. To evaluate the viability of these targets, we replicated the analysis using circulating protein quantitative trait loci as exposures. Additionally, we conducted sensitivity, colocalization, Gene Ontology/Kyoto Encyclopedia of Genes and Genomes annotation, protein-protein interaction analyses, and validated dental trait-associated druggable gene expression in animal models. Among these targets, IL12RB1 (odds ratio [OR], 1.01; 95% confidence interval [CI], 1.01-1.01) and TNF (OR, 0.98; 95% CI, 0.97-0.99) exhibited therapeutic promise for oral ulcers, whereas CXCL10 (OR, 0.84; 95% CI, 0.76-0.91) was for periodontitis. Through a rigorous quality control and validation pipeline, our study yields compelling evidence for these druggable targets, which may enhance the clinical prognosis by developing novel drugs or repurposing existing ones.

Oral leukoplakia (OL) has an inherent disposition to develop oral cancer. OL with epithelial dysplasia (OED) is significantly likely to undergo malignant transformation; however, routine OED assessment is invasive and challenging. This study investigated whether a deep learning (DL) model can predict dysplasia probability among patients with leukoplakia using oral photographs. In addition, we assessed the performance of the DL model in comparison with clinicians' ratings and in providing decision support on dysplasia assessment. Retrospective images of leukoplakia taken before biopsy/histopathology were obtained to construct the DL model (n = 2,073). OED status following histopathology was used as the gold standard for all images. We first developed, fine-tuned, and internally validated a DL architecture with an EfficientNet-B2 backbone that outputs the predicted probability of OED, OED status, and regions-of-interest heat maps. Then, we tested the performance of the DL model on a temporal cohort before geographical validation. We also assessed the model's performance at external validation with opinions provided by human raters on OED status. Performance evaluation included discrimination, calibration, and potential net benefit. The DL model achieved good Brier scores, areas under the curve, and balanced accuracies of 0.124 (0.079-0.169), 0.882 (0.838-0.926), and 81.8% (76.5-87.1) at testing and 0.146 (0.112-0.18), 0.828 (0.792-0.864), and 76.4% (72.3-80.5) at external validation, respectively. In addition, the model had a higher potential net benefit in selecting patients with OL for biopsy/histopathology during OED assessment than when biopsies were performed for all patients. External validation also showed that the DL model had better accuracy than 92.3% (24/26) of human raters in classifying the OED status of leukoplakia from oral images (balanced accuracy: 54.8%-79.7%). Overall, the photograph-based intelligent model can predict OED probability and status in leukoplakia with good calibration and discrimination, which shows potential for decision support to select patients for biopsy/histopathology, obviate unnecessary biopsy, and assist in patient self-monitoring.

The status of oral health research in the World Health Organization (WHO) African region is unclear, yet the need for such information is central to moving an oral health agenda forward. Such an agenda is essential for effectively translating research into actionable practices and supporting regional strategies. The aim of this scoping review was to provide data on the scope and output of oral health research in the WHO African region to be used as a starting point for establishing a research agenda that can affect oral health in the region. We conducted a systematic search in PubMed; EMBASE; Epistemonikos; Scopus; the International Association for Dental, Oral, and Craniofacial Research General and Regional Sessions; ProQUEST; PROSPERO; and African regional databases such as Regional African Index Medicus and the African Journal Online. We included primary and secondary studies published in English, French, or Portuguese between January 1, 2011, and December 31, 2022, addressing oral health-related research having individuals, groups, or populations as units of analysis. These reports either addressed a topic relevant to the WHO African region assessed using the title and study objective or were conducted in a country in the region. We excluded in vitro and in vivo studies focusing on cells, biomarkers, or animals. We assessed 24,014 records, and 1,379 proved eligible. Our findings indicate a preference for particular research designs less suitable for evidence-informed practice guidelines and oral policies, a limited scope of oral health research topics, and important regional differences in research capacity. Furthermore, publications by researchers in the WHO African region tend to be published in journals with a limited readership. A discussion of our findings among oral health researchers at academic institutions in the WHO African region on how to create within- and across-country collaborations could potentially improve both health and oral health in the region.

Advances in imaging technologies combined with artificial intelligence (AI) are transforming dental, oral, and craniofacial research. This editorial highlights breakthroughs ranging from gene expression mapping to visualizing the availability of global AI data, providing new insights into biological complexity and clinical applications.

Spatial transcriptomics (ST) is a cutting-edge methodology that enables the simultaneous profiling of global gene expression and spatial information within histological tissue sections. Traditional transcriptomic methods lack the spatial resolution required to sufficiently examine the complex interrelationships between cellular regions in diseased and healthy tissue states. We review the general workflows for ST, from specimen processing to ST data analysis and interpretations of the ST dataset using visualizations and cell deconvolution approaches. We show how recent studies used ST to explore the development or pathogenesis of specific craniofacial regions, including the cranium, palate, salivary glands, tongue, floor of mouth, oropharynx, and periodontium. Analyses of cranial suture patency and palatal fusion during development using ST identified spatial patterns of bone morphogenetic protein in sutures and osteogenic differentiation pathways in the palate, in addition to the discovery of several genes expressed at critical locations during craniofacial development. ST of salivary glands from patients with Sjögren's disease revealed co-localization of autoimmune antigens with ductal cells and a subpopulation of acinar cells that was specifically depleted by the dysregulated autoimmune response. ST of head and neck lesions, such as premalignant leukoplakia progressing to established oral squamous cell carcinomas, oral cancers with perineural invasions, and oropharyngeal lesions associated with HPV infection spatially profiled the complex tumor microenvironment, showing functionally important gene signatures of tumor cell differentiation, invasion, and nontumor cell dysregulation within patient biopsies. ST also enabled the localization of periodontal disease-associated gene expression signatures within gingival tissues, including genes involved in inflammation, and the discovery of a fibroblast subtype mediating the transition between innate and adaptive immune responses in periodontitis. The increased use of ST, especially in conjunction with single-cell analyses, promises to improve our understandings of craniofacial development and pathogenesis at unprecedented tissue-level resolution in both space and time.

Intraoral scanners (IOSs) have emerged as a cornerstone technology in digital dentistry. This article examines the recent advancements and multifaceted applications of IOSs, highlighting their benefits in patient care and addressing their current limitations. The IOS market has seen a competitive surge. Modern IOSs, featuring continuous image capture and advanced software for seamless image stitching, have made the scanning process more efficient. Patient comfort with IOS procedures is favorable, mitigating the discomfort associated with conventional impression taking. There has been a shift toward open data interfaces, notably enhancing interoperability. However, the integration of IOSs into large dental institutions is slow, facing challenges such as compatibility with existing health record systems and extensive data storage management. IOSs now extend beyond their use in computer-aided design and manufacturing, with software solutions transforming them into platforms for diagnostics, patient communication, and treatment planning. Several IOSs are equipped with tools for caries detection, employing fluorescence technologies or near-infrared imaging to identify carious lesions. IOSs facilitate quantitative monitoring of tooth wear and soft-tissue dimensions. For precise tooth segmentation in intraoral scans, essential for orthodontic applications, developers are leveraging innovative deep neural network-based approaches. The clinical performance of restorations fabricated based on intraoral scans has proven to be comparable to those obtained using conventional impressions, substantiating the reliability of IOSs in restorative dentistry. In oral and maxillofacial surgery, IOSs enhance airway safety during impression taking and aid in treating conditions such as cleft lip and palate, among other congenital craniofacial disorders, across diverse age groups. While IOSs have improved various aspects of dental care, ongoing enhancements in usability, diagnostic accuracy, and image segmentation are crucial to exploit the potential of this technology in optimizing patient care.

Human adipose-derived stem cells (hASCs) are commonly used in bone tissue regeneration. The N6-methyladenosine (m⁶A) modification has emerged as a novel regulatory mechanism for gene expression, playing a critical role in osteogenic differentiation of stem cells. However, the precise role and mechanism of alkylation repair homolog 5 (ALKBH5) in hASC osteogenesis remain incompletely elucidated and warrant further investigation. Herein, we employed methylated RNA immunoprecipitation sequencing, RNA sequencing, and weighted gene coexpression network analysis to identify a key long noncoding RNA (lncRNA) in hASCs: lncRNA AK311120. Functional experiments demonstrated that lnc-AK311120 promoted the osteogenic differentiation of hASCs, while a mutation at the m⁶A central site A of lnc-AK311120 was found to decrease the level of m⁶A modification. The osteogenic effect of ALKBH5 was confirmed both in vitro and in vivo using a mandibular defect model in nude mice. Subsequent investigations revealed that knockdown of ALKBH5 resulted in a significant increase in the m⁶A modification level of lnc-AK311120, accompanied by a downregulation in the expression level of lnc-AK311120. Additional rescue experiments demonstrated that overexpression of lnc-AK311120 could restore the phenotype after ALKBH5 knockdown. We observed that AK311120 interacted with the RNA-binding proteins DExH-Box helicase 9 (DHX9) and YTH domain containing 2 (YTHDC2) to form a ternary complex, while mitogen-activated protein kinase kinase 7 (MAP2K7) served as the shared downstream target gene of DHX9 and YTHDC2. Knockdown of AK311120 led to a reduction in the binding affinity between DHX9/YTHDC2 and the target gene MAP2K7. Furthermore, ALKBH5 facilitated the translation of MAP2K7 and activated the downstream JNK signaling pathway through the AK311120-DHX9-YTHDC2 complex, without affecting its messenger RNA level. Collectively, we have investigated the regulatory effect and mechanism of ALKBH5-mediated demethylation of lncRNA in hASC osteogenesis for the first time, offering a promising approach for bone tissue engineering.

Adequate and transparent reporting is necessary for critically appraising published research. Yet, ample evidence suggests that the design, conduct, analysis, interpretation, and reporting of oral health research could be greatly improved. Accordingly, the Task Force on Design and Analysis in Oral Health Research-statisticians and trialists from academia and industry-identified the minimum information needed to report and evaluate observational studies and clinical trials in oral health: the OHStat Guidelines. Drafts were circulated to the editors of 85 oral health journals and to Task Force members and sponsors and discussed at a December 2020 workshop attended by 49 researchers. The guidelines were subsequently revised by the Task Force's writing group. The guidelines draw heavily from the Consolidated Standards for Reporting Trials (CONSORT), Strengthening the Reporting of Observational Studies in Epidemiology (STROBE), and CONSORT harms guidelines and incorporate the SAMPL guidelines for reporting statistics, the CLIP principles for documenting images, and the GRADE indicating the quality of evidence. The guidelines also recommend reporting estimates in clinically meaningful units using confidence intervals, rather than relying on P values. In addition, OHStat introduces 7 new guidelines that concern the text itself, such as checking the congruence between abstract and text, structuring the discussion, and listing conclusions to make them more specific. OHStat does not replace other reporting guidelines; it incorporates those most relevant to dental research into a single document. Manuscripts using the OHStat guidelines will provide more information specific to oral health research.