Shared genetic risk between major orofacial cleft phenotypes in an African population.

Nonsyndromic orofacial clefts (NSOFCs) represent a large proportion (70%-80%) of all OFCs. They can be broadly categorized into nonsyndromic cleft lip with or without cleft palate (NSCL/P) and nonsyndromic cleft palate only (NSCPO). Although NSCL/P and NSCPO are considered etiologically distinct, recent evidence suggests the presence of shared genetic risks. Thus, we investigated the genetic overlap between NSCL/P and NSCPO using African genome-wide association study (GWAS) data on NSOFCs. These data consist of 814 NSCL/P, 205 NSCPO cases, and 2159 unrelated controls. We generated common single-nucleotide variants (SNVs) association summary statistics separately for each phenotype (NSCL/P and NSCPO) under an additive genetic model. Subsequently, we employed the pleiotropic analysis under the composite null (PLACO) method to test for genetic overlap. Our analysis identified two loci with genome-wide significance (rs181737795 [p = 2.58E-08] and rs2221169 [p = 4.5E-08]) and one locus with marginal significance (rs187523265 [p = 5.22E-08]). Using mouse transcriptomics data and information from genetic phenotype databases, we identified MDN1, MAP3k7, KMT2A, ARCN1, and VADC2 as top candidate genes for the associated SNVs. These findings enhance our understanding of genetic variants associated with NSOFCs and identify potential candidate genes for further exploration.

Rare Variants Analyses Suggest Novel Cleft Genes in the African Population.

Non-syndromic orofacial clefts (NSOFCs) are common birth defects with a complex etiology. While over 60 common risk loci have been identified, they explain only a small proportion of the heritability for NSOFC. Rare variants have been implicated in the missing heritability. Thus, our study aimed to identify genes enriched with nonsynonymous rare coding variants associated with NSOFCs. Our sample included 814 non-syndromic cleft lip with or without palate (NSCL/P), 205 non-syndromic cleft palate only (NSCPO), and 2150 unrelated control children from Nigeria, Ghana, and Ethiopia. We conducted a gene-based analysis separately for each phenotype using three rare-variants collapsing models: (1) protein-altering (PA), (2) missense variants only (MO); and (3) loss of function variants only (LOFO). Subsequently, we utilized relevant transcriptomics data to evaluate associated gene expression and examined their mutation constraint using the gnomeAD database. In total, 13 genes showed suggestive associations (p = E-04). Among them, eight genes (ABCB1, ALKBH8, CENPF, CSAD, EXPH5, PDZD8, SLC16A9, and TTC28) were consistently expressed in relevant mouse and human craniofacial tissues during the formation of the face, and three genes (ABCB1, TTC28, and PDZD8) showed statistically significant mutation constraint. These findings underscore the role of rare variants in identifying candidate genes for NSOFCs.

Using machine learning algorithms to investigate factors associated with complete edentulism among older adults in the United States.

AIMS: Edentulism is an incapacitating condition, and its prevalence is unequal among different population groups in the United States (US) despite its declining prevalence. This study aimed to investigate the current prevalence, apply Machine Learning (ML) Algorithms to investigate factors associated with complete tooth loss among older US adults, and compare the performance of the models. METHODS: The cross-sectional 2020 Behavioral Risk Factor Surveillance System (BRFSS) data was used to evaluate the prevalence and factors associated with edentulism. ML models were developed to identify factors associated with edentulism utilizing seven ML algorithms. The performance of these models was compared using the area under the receiver operating characteristic curve (AUC). RESULTS: An overall prevalence of 11.9% was reported. The AdaBoost algorithm (AUC = 84.9%) showed the best performance. Analysis showed that the last dental visit, educational attainment, smoking, difficulty walking, and general health status were among the top factors associated with complete edentulism. CONCLUSION: Findings from our study support the declining prevalence of complete edentulism in older adults in the US and show that it is possible to develop a high-performing ML model to investigate the most important factors associated with edentulism using nationally representative data.

The Iowa Health Data Resource (IHDR): an innovative framework for transforming the clinical health data ecosystem.

IMPORTANCE: This manuscript will be of interest to most Clinical and Translational Science Awards (CTSA) as they retool for the increasing emphasis on translational science from translational research. This effort is an extension of the EDW4R work that most CTSAs have done to deploy infrastructure and tools for researchers to access clinical data. OBJECTIVES: The Iowa Health Data Resource (IHDR) is a strategic investment made by the University of Iowa to improve access to real-world health data. The goals of IHDR are to improve the speed of translational health research, to boost interdisciplinary collaboration, and to improve literacy about health data. The first objective toward this larger goal was to address gaps in data access, data literacy, lack of computational environments for processing Personal Health Information (PHI) and the lack of processes and expertise for creating transformative datasets. METHODS: A three-pronged approach was taken to address the objective. The approach involves integration of an intercollegiate team of non-informatics faculty and staff, a data enclave for secure patient data analyses, and novel comprehensive datasets. RESULTS: To date, all five of the health science colleges (dentistry, medicine, nursing, pharmacy, and public health) have had at least one staff and one faculty member complete the two-month experiential learning curriculum. Over the first two years of this project, nine cohorts totaling 36 data liaisons have been trained, including 18 faculty and 18 staff. IHDR data enclave eliminated the need to duplicate computational infrastructure inside the hospital firewall which reduced infrastructure, hardware and human resource costs while leveraging the existing expertise embedded in the university research computing team. The creation of a process to develop and implement transformative datasets has resulted in the creation of seven domain specific datasets to date. CONCLUSION: The combination of people, process, and technology facilitates collaboration and interdisciplinary research in a secure environment using curated data sets. While other organizations have implemented individual components to address EDW4R operational demands, the IHDR combines multiple resources into a novel, comprehensive ecosystem IHDR enables scientists to use analysis tools with electronic patient data to accelerate time to science.

Protein-protein interaction network module changes associated with the vertebrate fin-to-limb transition.

Evolutionary phenotypic transitions, such as the fin-to-limb transition in vertebrates, result from modifications in related proteins and their interactions, often in response to changing environment. Identifying these alterations in protein networks is crucial for a more comprehensive understanding of these transitions. However, previous research has not attempted to compare protein-protein interaction (PPI) networks associated with evolutionary transitions, and most experimental studies concentrate on a limited set of proteins. Therefore, the goal of this work was to develop a network-based platform for investigating the fin-to-limb transition using PPI networks. Quality-enhanced protein networks, constructed by integrating PPI networks with anatomy ontology data, were leveraged to compare protein modules for paired fins (pectoral fin and pelvic fin) of fishes (zebrafish) to those of the paired limbs (forelimb and hindlimb) of mammals (mouse). This also included prediction of novel protein candidates and their validation by enrichment and homology analyses. Hub proteins such as shh and bmp4, which are crucial for module stability, were identified, and their changing roles throughout the transition were examined. Proteins with preserved roles during the fin-to-limb transition were more likely to be hub proteins. This study also addressed hypotheses regarding the role of non-preserved proteins associated with the transition.

Clinically actionable secondary findings in 130 triads from sub-Saharan African families with non-syndromic orofacial clefts.

INTRODUCTION: The frequency and implications of secondary findings (SFs) from genomic testing data have been extensively researched. However, little is known about the frequency or reporting of SFs in Africans, who are underrepresented in large-scale population genomic studies. The availability of data from the first whole-genome sequencing for orofacial clefts in an African population motivated this investigation. METHODS: In total, 130 case-parent trios were analyzed for SFs within the ACMG SFv.3.0 list genes. Additionally, we filtered for four more genes (HBB, HSD32B, G6PD and ACADM). RESULTS: We identified 246 unique variants in 55 genes; five variants in four genes were classified as pathogenic or likely pathogenic (P/LP). The P/LP variants were seen in 2.3% (9/390) of the subjects, a frequency higher than ~1% reported for diverse ethnicities. On the ACMG list, pathogenic variants were observed in PRKAG (p. Glu183Lys). Variants in the PALB2 (p. Glu159Ter), RYR1 (p. Arg2163Leu) and LDLR (p. Asn564Ser) genes were predicted to be LP. CONCLUSION: This study provides information on the frequency and pathogenicity of SFs in an African cohort. Early risk detection will help reduce disease burden and contribute to efforts to increase knowledge of the distribution and impact of actionable genomic variants in diverse populations.

COVID-19 associated oral and oropharyngeal microbiome: Systematic review and meta-analysis.

Three years into the coronavirus disease 2019 (COVID-19) pandemic, there are still growing concerns with the emergence of different variants, unknown long- and short-term effects of the virus, and potential biological mechanisms underlying etiopathogenesis and increased risk for morbidity and mortality. The role of the microbiome in human physiology and the initiation and progression of several oral and systemic diseases have been actively studied in the past decade. With the proof of viral transmission, carriage, and a potential role in etiopathogenesis, saliva and the oral environment have been a focus of COVID-19 research beyond diagnostic purposes. The oral environment hosts diverse microbial communities and contributes to human oral and systemic health. Several investigations have identified disruptions in the oral microbiome in COVID-19 patients. However, all these studies are cross-sectional in nature and present heterogeneity in study design, techniques, and analysis. Therefore, in this undertaking, we (a) systematically reviewed the current literature associating COVID-19 with changes in the microbiome; (b) performed a re-analysis of publicly available data as a means to standardize the analysis, and (c) reported alterations in the microbial characteristics in COVID-19 patients compared to negative controls. Overall, we identified that COVID-19 is associated with oral microbial dysbiosis with significant reduction in diversity. However, alterations in specific bacterial members differed across the study. Re-analysis from our pipeline shed light on Neisseria as the potential key microbial member associated with COVID-19.

An Overview of Time-to-Event Analysis in Dental Research.

Time-to-event (survival) analysis is an integral tool in the wheelhouse of the dental researcher. While there are many references available for the study of time-to-event analysis, they tend to be written for audiences trained in statistical methodology. Moreover, the canonical examples offered by most time-to-event analysis references are focused on outcomes that do not translate directly to dentistry. This article provides a tutorial of time-to-event analysis for the specific context of dental research. Our tutorial assumes no statistical training or computing experience. Using real data from a dental study as our extended example, we explain foundational concepts, including median survival, Nth-year survival, the log-rank test, and the Cox model.

Spent culture supernatant of Streptococcus gordonii mitigates inflammation of human periodontal cells and inhibits proliferation of pathogenic oral microbes.

BACKGROUND: The oral commensal bacterial species Streptococcus gordonii has been reported to regulate the inflammation of oral epithelial cells stimulated by the periodontal pathogen Porphyromonas gingivalis. This study investigated the activities of S. gordonii metabolites in S. gordonii spent culture supernatants (Sg-SCS) on periodontal-related bacterial growth and periodontitis-associated inflammatory cytokines. METHODS: Sg-SCS was collected from S. gordonii cultures grown in Dulbecco Modified Eagle Medium and added to the growth media of representative health- and disease-related oral species: S. gordonii, Streptococcus sanguinis, Streptococcus mitis, Streptococcus oralis, P. gingivalis, Tannerella forsythia, and Treponema denticola. The Sg-SCS was also tested for its ability to regulate the expression of proinflammatory cytokines by human macrophages, epithelial cells, and gingival fibroblasts upon stimulation with P. gingivalis-derived lipopolysaccharide (Pg-LPS). RESULTS: Sg-SCS significantly reduced transcript and protein levels of interleukin (IL)-1ß, 6, and 8 induced by Pg-LPS stimulation in multiple types of periodontal cells. mRNA sequencing and bioinformatics analyses indicated that Sg-SCS significantly affects 10 inflammatory pathways. Additionally, Sg-SCS exhibited suppression of the growth of periodontal disease-related bacteria, including T. denticola and P. gingivalis, along with the primary plaque-colonizing species S. oralis. At a low concentration, Sg-SCS also inhibits P. gingivalis adhesion. CONCLUSIONS: These results strongly suggest that S. gordonii-derived SCS contains metabolites that have anti-inflammatory properties and an ability to inhibit periodontitis-associated pathogenic bacteria. Further investigation will be needed to identify the individual metabolites within the Sg-SCS to develop a novel metabolite-based approach to treating and preventing periodontitis.

Damaging Mutations in AFDN Contribute to Risk of Nonsyndromic Cleft Lip With or Without Cleft Palate.

Novel or rare damaging mutations have been implicated in the developmental pathogenesis of nonsyndromic cleft lip with or without cleft palate (nsCL ± P). Thus, we investigated the human genome for high-impact mutations that could explain the risk of nsCL ± P in our cohorts.We conducted next-generation sequencing (NGS) analysis of 130 nsCL ± P case-parent African trios to identify pathogenic variants that contribute to the risk of clefting. We replicated this analysis using whole-exome sequence data from a Brazilian nsCL ± P cohort. Computational analyses were then used to predict the mechanism by which these variants could result in increased risks for nsCL ± P.We discovered damaging mutations within the AFDN gene, a cell adhesion molecule (CAMs) that was previously shown to contribute to cleft palate in mice. These mutations include p.Met1164Ile, p.Thr453Asn, p.Pro1638Ala, p.Arg669Gln, p.Ala1717Val, and p.Arg1596His. We also discovered a novel splicing p.Leu1588Leu mutation in this protein. Computational analysis suggests that these amino acid changes affect the interactions with other cleft-associated genes including nectins (PVRL1, PVRL2, PVRL3, and PVRL4) CDH1, CTNNA1, and CTNND1.This is the first report on the contribution of AFDN to the risk for nsCL ± P in humans. AFDN encodes AFADIN, an important CAM that forms calcium-independent complexes with nectins 1 and 4 (encoded by the genes PVRL1 and PVRL4). This discovery shows the power of NGS analysis of multiethnic cleft samples in combination with a computational approach in the understanding of the pathogenesis of nsCL ± P.

Systematic review and meta-analysis of oral squamous cell carcinoma associated oral microbiome.

The intersection between the human oral microbiome and oral health is an emerging area of study which has gained momentum over the last decade. This momentum has motivated a search for associations between the oral microbiome and oral cancer, in hopes of identifying possible biomarkers that facilitate earlier diagnosis and improved prognosis for patients with that disease. The present study examined the relationship between the microbiome in the human oral cavity and oral squamous cell carcinoma (OSCC). We searched the literature for case-control studies which focused on the relationship between the human oral microbiome and OSCC. We aggregated three types of data from these studies: bacteriome data at the genus level, predicted functional pathway data, and gene abundance data. From these data, we noted several microbial genera which may be associated with oral cancer status, including Fusobacterium. We also identified functional pathways which merit further investigation, including RNA degradation (ko03018) and primary immunodeficiency (ko05340). In addition, our analysis of gene abundance data identified the gene K06147 (ATP-binding cassette, subfamily B, bacterial) as being over abundant in OSCC samples. Our results are generalizations which identified some currents that we believe could guide further research. Our work faced several limitations related to the heterogeneity of the available data. Wide variation in methods for sample collection, methods for controlling for known behavioral risk factors, computing platform choice, and methods for case-control design all posed confounding factors in this work. We examined the current methods of data collection, data processing, and data reporting in order to offer suggestions toward the establishment of best practices within this field. We propose that these limitations should be addressed through the implementation of standardized data analytic practices that will conform to the rigor and reproducibility standards required of publicly funded research.

Antimicrobial Peptides and Biomarkers Induced by Ultraviolet Irradiation Have the Potential to Reduce Endodontic Inflammation and Facilitate Tissue Healing.

BACKGROUND: Ultraviolet (UV) irradiation can modulate host immune responses and this approach is a novel application for treating endodontic infections and inflammation in root canals. METHODS: A dataset of UV-induced molecules was compiled from a literature search. A subset of this dataset was used to calculate expression log2 ratios of endodontic tissue molecules from HEPM cells and gingival fibroblasts after 255, 405, and 255/405 nm UV irradiation. Both datasets were analyzed using ingenuity pathway analysis (IPA, Qiagen, Germantown, MD, USA). Statistical significance was calculated using Fisher's exact test and z-scores were calculated for IPA comparison analysis. RESULTS: The dataset of 32 UV-induced molecules contained 9 antimicrobial peptides, 10 cytokines, 6 growth factors, 3 enzymes, 2 transmembrane receptors, and 2 transcription regulators. These molecules were in the IPA canonical pathway annotations for the wound healing signaling pathway (9/32, p = 3.22 × 10-11) and communication between immune cells (6/32, p = 8.74 × 10-11). In the IPA disease and function annotations, the 32 molecules were associated with an antimicrobial response, cell-to-cell signaling and interaction, cellular movement, hematological system development and function, immune cell trafficking, and inflammatory response. In IPA comparison analysis of the 13 molecules, the predicted activation or inhibition of pathways depended upon the cell type exposed, the wavelength of the UV irradiation used, and the time after exposure. CONCLUSIONS: UV irradiation activates and inhibits cellular pathways and immune functions. These results suggested that UV irradiation can activate innate and adaptive immune responses, which may supplement endodontic procedures to reduce infection, inflammation, and pain and assist tissues to heal.

Whole-genome sequencing reveals de-novo mutations associated with nonsyndromic cleft lip/palate.

The majority (85%) of nonsyndromic cleft lip with or without cleft palate (nsCL/P) cases occur sporadically, suggesting a role for de novo mutations (DNMs) in the etiology of nsCL/P. To identify high impact protein-altering DNMs that contribute to the risk of nsCL/P, we conducted whole-genome sequencing (WGS) analyses in 130 African case-parent trios (affected probands and unaffected parents). We identified 162 high confidence protein-altering DNMs some of which are based on available evidence, contribute to the risk of nsCL/P. These include novel protein-truncating DNMs in the ACTL6A, ARHGAP10, MINK1, TMEM5 and TTN genes; as well as missense variants in ACAN, DHRS3, DLX6, EPHB2, FKBP10, KMT2D, RECQL4, SEMA3C, SEMA4D, SHH, TP63, and TULP4. Many of these protein-altering DNMs were predicted to be pathogenic. Analysis using mouse transcriptomics data showed that some of these genes are expressed during the development of primary and secondary palate. Gene-set enrichment analysis of the protein-altering DNMs identified palatal development and neural crest migration among the few processes that were significantly enriched. These processes are directly involved in the etiopathogenesis of clefting. The analysis of the coding sequence in the WGS data provides more evidence of the opportunity for novel findings in the African genome.

Tooth Agenesis Patterns in Orofacial Clefting Using Tooth Agenesis Code: A Meta-Analysis.

Individuals with orofacial clefting (OFC) have a higher prevalence of tooth agenesis (TA) overall. Neither the precise etiology of TA, nor whether TA occurs in patterns that differ by gender or cleft type is yet known. This meta-analysis aims to identify the spectrum of tooth agenesis patterns in subjects with non-syndromic OFC and controls using the Tooth Agenesis Code (TAC) program. An indexed search of databases (PubMed, EMBASE, and CINAHL) along with cross-referencing and hand searches were completed from May to June 2019 and re-run in February 2022. Additionally, unpublished TAC data from 914 individuals with OFC and 932 controls were included. TAC pattern frequencies per study were analyzed using a random effects meta-analysis model. A thorough review of 45 records retrieved resulted in 4 articles meeting eligibility criteria, comprising 2182 subjects with OFC and 3171 controls. No TA (0.0.0.0) was seen in 51% of OFC cases and 97% of controls. TAC patterns 0.2.0.0, 2.0.0.0, and 2.2.0.0 indicating uni- or bi-lateral missing upper laterals, and 16.0.0.0 indicating missing upper right second premolar, were more common in subjects with OFC. Subjects with OFC have unique TA patterns and defining these patterns will help increase our understanding of the complex etiology underlying TA.

High Molecular Weight Poly(glutamic acid) to Improve BMP2-Induced Osteogenic Differentiation.

FDA-approved bone morphogenetic protein 2 (BMP2) has serious side effects due to the super high dose requirement. Heparin is one of the most well-studied sulfated polymers to stabilize BMP2 and improve its functionality. However, the clinical use of heparin is questionable because of its undesired anticoagulant activity. Recent studies suggest that poly(glutamic acid) (pGlu) has the potential to improve BMP2 bioactivity with less safety concerns; however, the knowledge on pGlu's contribution remains largely unknown. Therefore, we aimed to study the role of pGlu in BMP2-induced osteogenesis and its potential application in bone tissue engineering. Our data, for the first time, indicated that both low (L-pGlu) and high molecular weight pGlu (H-pGlu) were able to significantly improve the BMP2-induced early osteoblastic differentiation marker (ALP) in MC3T3-E1 preosteoblasts. Importantly, the matrix mineralization was more rapidly enhanced by H-pGlu compared to L-pGlu. Additionally, our data indicated that only α-H-pGlu could significantly improve BMP2's activity, whereas γ-H-pGlu failed to do so. Moreover, both gene expression and mineralization data demonstrated that α-H-pGlu enabled a single dose of BMP2 to induce a high level of osteoblastic differentiation without multiple doses of BMP2. To study the potential application of pGlu in tissue engineering, we incorporated the H-pGlu+BMP2 nanocomplexes into the collagen hydrogel with significantly elevated osteoblastic differentiation. Furthermore, H-pGlu-coated 3D porous gelatin and chitosan scaffolds significantly enhanced osteogenic differentiation through enabling sustained release of BMP2. Thus, our findings suggest that H-pGlu is a promising new alternative with great potential for bone tissue engineering applications.

RNA-Seq Experiment and Data Analysis.

With the ability to obtain several millions of reads per sample, high-throughput RNA sequencing (RNA-Seq) enables investigation of any transcriptome at a fine resolution. Not just the messenger RNA (mRNA), but a wide variety of different RNA populations (e.g., total RNA, microRNA, long ncRNA, pre-mRNA) can also be investigated using RNA-Seq. While facilitating accurate quantification of gene expression, RNA-Seq offers the opportunity to estimate abundance of isoforms and find novel transcripts and allele-specific transcripts. In this chapter, we describe a protocol to construct an RNA-Seq library for sequencing on Illumina NGS platforms and a computational pipeline to perform RNA-Seq data analysis. The protocols described in this chapter can be applied to the analysis of differential gene expression in control versus 17ß-estradiol treatment of in vivo or in vitro systems.

Genome-Wide Scan for Parent-of-Origin Effects in a sub-Saharan African Cohort With Nonsyndromic Cleft Lip and/or Cleft Palate (CL/P).

OBJECTIVE: Nonsyndromic cleft lip and/or cleft palate (NSCL/P) have multifactorial etiology where genetic factors, gene-environment interactions, stochastic factors, gene-gene interactions, and parent-of-origin effects (POEs) play cardinal roles. POEs arise when the parental origin of alleles differentially impacts the phenotype of the offspring. The aim of this study was to identify POEs that can increase risk for NSCL/P in humans using a genome-wide dataset. METHODS: The samples (174 case-parent trios from Ghana, Ethiopia, and Nigeria) included in this study were from the African only genome wide association studies (GWAS) that was published in 2019. Genotyping of individual DNA using over 2 million multiethnic and African ancestry-specific single-nucleotide polymorphisms from the Illumina Multi-Ethnic Genotyping Array v2 15070954 A2 (genome build GRCh37/hg19) was done at the Center for Inherited Diseases Research. After quality control checks, PLINK was employed to carry out POE analysis employing the pooled subphenotypes of NSCL/P. RESULTS: We observed possible hints of POEs at a cluster of genes at a 1 mega base pair window at the major histocompatibility complex class 1 locus on chromosome 6, as well as at other loci encompassing candidate genes such as ASB18, ANKEF1, AGAP1, GABRD, HHAT, CCT7, DNMT3A, EPHA7, FOXO3, lncRNAs, microRNA, antisense RNAs, ZNRD1, ZFAT, and ZBTB16. CONCLUSION: Findings from our study suggest that some loci may increase the risk for NSCL/P through POEs. Additional studies are required to confirm these suggestive loci in NSCL/P etiology.

Dataset-chemokines, cytokines, and biomarkers in the saliva of children with Sjögren's syndrome.

Sjögren's syndrome is an autoimmune disease that can also occur in children. The disease is not well defined and there is limited information on the presence of chemokines, cytokines, and biomarkers (CCBMs) in the saliva of children that could improve their disease diagnosis. In a recent study [1], we reported a large dataset of 105 CCBMs that were associated with both lymphocyte and mononuclear cell functions [2] in the saliva of 11 children formally diagnosed with Sjögren's syndrome and 16 normal healthy children. Here, we extend those findings and use the Mendeley dataset [2] to identify CCBMs that have predictive power for Sjögren's syndrome in female children. Datasets of CCBMs from all saliva samples and female children saliva samples were standardized. We used machine learning methods to select Sjögren's syndrome associated CCBMs and assessed the predictive power of selected CCBMs in these two datasets using receiver operating characteristic (ROC) curves and associated areas under curve (AUC) as metrics. We used eight classifiers to identify 16 datasets that contained from 2 to 34 CCBMs with AUC values ranging from 0.91 to 0.94.

Students' perceptions and attitudes about digital dental technology is associated with their intention to use it.

PURPOSE/OBJECTIVES: To investigate factors associated with predoctoral students' intention to use dental technology in future practice using the theory of planned behavior. METHODS: A comprehensive survey was developed consisting of 29 questions grouped in three main domains: knowledge, perception, and suggestions. After students had completed their digital dentistry didactic courses in 2019, the University of Iowa-College of Dentistry and Dental Clinics D2, D3, and D4 classes completed the survey. The D1 class was excluded because they had not finished their digital dentistry didactic courses. The survey data were tabulated for each class separately to compare trends among classes. Each response was analyzed individually before creating scores for the various subdomains. A linear regression analysis was used to create the final model for the outcome variable (intention to use technology). RESULTS: The response rate was 95% (n = 232). The mean age of participants was 25.7 years (SD = 2.7). There were significant differences between the classes in their knowledge (p < 0.0001), perceived quality of training (p < 0.0001), and all perceptions related to digital dentistry. Controlling for significant covariates among higher level students, there were significant associations between intention to use dental technology and greater knowledge scores (p = 0.05), attitude (p < 0.0001), subjective social norms (p = 0.02), and perceived control on the future use of technology (p < 0.0001). CONCLUSIONS: Students may be motivated to use digital technology when they have good knowledge, feel that others are using it or endorsing its use, and perceive that they have control in their future practice.

A distinguishing profile of chemokines, cytokines and biomarkers in the saliva of children with Sjögren's syndrome.

OBJECTIVE: SS is an autoimmune disease most commonly diagnosed in adults but can occur in children. Our objective was to assess the presence of chemokines, cytokines and biomarkers (CCBMs) in saliva from these children that were associated with lymphocyte and mononuclear cell functions. METHODS: Saliva was collected from 11 children diagnosed with SS prior to age 18 years and 16 normal healthy children. A total of 105 CCBMs were detected in multiplex microparticle-based immunoassays. ANOVA and t test (0.05 level) were used to detect differences. Ingenuity Pathway Analysis (IPA) was used to assess whether elevated CCBMs were in annotations associated with immune system diseases and select leukocyte activities and functions. Machine learning methods were used to evaluate the predictive power of these CCBMs for SS and were measured by receiver operating characteristic (ROC) curve and area under curve (AUC). RESULTS: Of the 105 CCBMs detected, 43 (40.9%) differed in children with SS from those in healthy study controls (P < 0.05) and could differentiate the two groups (P < 0.05). Elevated CCBMs in IPA annotations were associated with autoimmune diseases and with leukocyte chemotaxis, migration, proliferation, and regulation of T cell activation. The best AUC value in ROC analysis was 0.93, indicating that there are small numbers of CCBMs that may be useful for diagnosis of SS. CONCLUSION: While 35 of these 43 CCBMs have been previously reported in SS, 8 CCBMs had not. Additional studies focusing on these CCBMs may provide further insight into disease pathogenesis and may contribute to diagnosis of SS in children.