The objectives of this study were 1) to provide an estimate of the value of the intraclass correlation coefficient (ICC) for dental caries data at tooth and surface level, 2) to provide an estimate of the design effect (DE) to be used in the determination of sample size estimates for future dental surveys, and 3) to explore the usefulness of multilevel modeling of cross-sectional survey data by comparing the model estimates derived from multilevel and single-level models. Using data from the United Kingdom Adult Dental Health Survey 2009, the ICC and DE were calculated for surfaces within a tooth, teeth within the individual, and surfaces within the individual. Simple and multilevel logistic regression analysis was performed with the outcome variables carious tooth or surface. ICC estimated that 10% of the variance in surface caries is attributable to the individual level and 30% of the variance in surfaces caries is attributable to variation between teeth within individuals. When comparing multilevel with simple logistic models, β values were 4 to 5 times lower and the standard error 2 to 3 times lower in multilevel models. All the fit indices showed multilevel models were a better fit than simple models. The DE was 1.4 for the clustering of carious surfaces within teeth, 6.0 for carious teeth within an individual, and 38.0 for carious surfaces within the individual. The ICC for dental caries data was 0.21 (95% confidence interval [CI], 0.204-0.220) at the tooth level and 0.30 (95% CI, 0.284-0.305) at the surface level. The DE used for sample size calculation for future dental surveys will vary on the level of clustering, which is important in the analysis-the DE is greatest when exploring the clustering of surfaces within individuals. Failure to consider the effect of clustering on the design and analysis of epidemiological trials leads to an overestimation of the impact of interventions and the importance of risk factors in predicting caries outcome.
The post-natal dental pulp tissue contains a population of multipotent mesenchymal progenitor cells known as dental pulp stromal/stem cells (DPSCs), with high proliferative potential for self-renewal. In this investigation, we explored the potential of DPSCs to differentiate into pancreatic cell lineage resembling islet-like cell aggregates (ICAs). We isolated, propagated, and characterized DPSCs and demonstrated that these could be differentiated into adipogenic, chondrogenic, and osteogenic lineage upon exposure to an appropriate cocktail of differentiating agents. Using a three-step protocol reported previously by our group, we succeeded in obtaining ICAs from DPSCs. The identity of ICAs was confirmed as islets by dithiozone-positive staining, as well as by expression of C-peptide, Pdx-1, Pax4, Pax6, Ngn3, and Isl-1. There were several-fold up-regulations of these transcription factors proportional to days of differentiation as compared with undifferentiated DPSCs. Day 10 ICAs released insulin and C-peptide in a glucose-dependent manner, exhibiting in vitro functionality. Our results demonstrated for the first time that DPSCs could be differentiated into pancreatic cell lineage and offer an unconventional and non-controversial source of human tissue that could be used for autologous stem cell therapy in diabetes.
Non-syndromic cleft lip, with or without cleft palate, is a heterogeneous, complex disease with a high incidence in the Asian population. Several association studies have been done on cleft candidate genes, but no reports have been published thus far on the Orofacial Cleft 1 (OFC1) genomic region in an Asian population. This study investigated the association between the OFC1 genomic region and non-syndromic cleft lip with or without cleft palate in 90 Malay father-mother-offspring trios. Results showed a preferential over-transmission of a 101-bp allele of marker D6S470 in the allele- and haplotype-based transmission disequilibrium test (TDT), as well as an excess of maternal transmission. However, no significant p-value was found for a maternal genotype effect in a log-linear model, although single and double doses of the 101-bp allele showed a slightly increased cleft risk (RR = 1.37, 95% CI, 0.527-3.4, p-value = 0.516). Carrying two copies of the 101-bp allele was significantly associated with an increased cleft risk (RR = 2.53, 95% CI, 1.06-6.12, p-value = 0.035). In conclusion, we report evidence of the contribution of the OFC1 genomic region to the etiology of clefts in a Malay population.
Policymakers' understanding of and ability to reduce health disparities are pivotal for health promotion worldwide. This study aimed to verify the behavioral pathways leading to oral health disparities. Oral examinations were conducted for 1782 randomly selected preschoolers (3-6 yrs), and 1576 (88.4%) participants were followed up after 12 months. Parents were surveyed on their knowledge (K), attitude (A), and practices (P) regarding their children's oral health homecare (infant feeding, diet, and oral hygiene) and dental attendance. Structural equation modeling substantiated the links between specific KAs and corresponding practices, while generic KA did not affect practices. KAP pathways partly explained the ethnic and socio-economic disparities in oral health. Deprivation had a direct effect (not mediated by KA) on dental attendance, but not on oral health homecare. Ethnicity directly influenced oral health homecare practices, but not dental attendance. These behavioral pathways, furthering our understanding of health disparity, may have practical implications for health promotion and policy-making.
Much research on children's oral health has focused on proximal determinants at the expense of distal (upstream) factors. Yet, such upstream factors-the so-called structural determinants of health-play a crucial role. Children's lives, and in turn their health, are shaped by politics, economic forces, and social and public policies. The aim of this study was to examine the relationship between children's clinical (number of decayed, missing, and filled teeth) and self-reported oral health (oral health-related quality of life) and 4 key structural determinants (governance, macroeconomic policy, public policy, and social policy) as outlined in the World Health Organization's Commission for Social Determinants of Health framework. Secondary data analyses were carried out using subnational epidemiological samples of 8- to 15-y-olds in 11 countries ( N = 6,648): Australia (372), New Zealand (three samples; 352, 202, 429), Brunei (423), Cambodia (423), Hong Kong (542), Malaysia (439), Thailand (261, 506), United Kingdom (88, 374), Germany (1498), Mexico (335), and Brazil (404). The results indicated that the type of political regime, amount of governance (e.g., rule of law, accountability), gross domestic product per capita, employment ratio, income inequality, type of welfare regime, human development index, government expenditure on health, and out-of-pocket (private) health expenditure by citizens were all associated with children's oral health. The structural determinants accounted for between 5% and 21% of the variance in children's oral health quality-of-life scores. These findings bring attention to the upstream or structural determinants as an understudied area but one that could reap huge rewards for public health dentistry research and the oral health inequalities policy agenda.
Head and neck cancer (HNC)-derived cell lines represent fundamental models for studying the biological mechanisms underlying cancer development and precision therapies. However, mining the genomic information of HNC cells from available databases requires knowledge on bioinformatics and computational skill sets. Here, we developed a user-friendly web resource for exploring, visualizing, and analyzing genomics information of commonly used HNC cell lines. We populated the current version of GENIPAC with 44 HNC cell lines from 3 studies: ORL Series, OPC-22, and H Series. Specifically, the mRNA expressions for all the 3 studies were derived with RNA-seq. The copy number alterations analysis of ORL Series was performed on the Genome Wide Human Cytoscan HD array, while copy number alterations for OPC-22 were derived from whole exome sequencing. Mutations from ORL Series and H Series were derived from RNA-seq information, while OPC-22 was based on whole exome sequencing. All genomic information was preprocessed with customized scripts and underwent data validation and correction through data set validator tools provided by cBioPortal. The clinical and genomic information of 44 HNC cell lines are easily assessable in GENIPAC. The functional utility of GENIPAC was demonstrated with some of the genomic alterations that are commonly reported in HNC, such as TP53, EGFR, CCND1, and PIK3CA. We showed that these genomic alterations as reported in The Cancer Genome Atlas database were recapitulated in the HNC cell lines in GENIPAC. Importantly, genomic alterations within pathways could be simultaneously visualized. We developed GENIPAC to create access to genomic information on HNC cell lines. This cancer omics initiative will help the research community to accelerate better understanding of HNC and the development of new precision therapeutic options for HNC treatment. GENIPAC is freely available at http://genipac.cancerresearch.my/ .
Since its inception in 1919, the Journal of Dental Research has continually published high-quality articles that span the breadth of research topics relevant to dentistry, oral surgery, and medicine. As part of the journal's centennial celebration, we conducted an electronic search on Scopus to identify and analyze the top 100 most cited articles from 1919 to 2018. Since Scopus does not capture older citations, we conducted an additional analysis by Google Scholar to identify key articles published in the first 50 y of the journal. Based on Scopus, the articles were ranked in descending order per their citation counts. The citation counts of the 100 most cited articles varied from 262 to 1,503. The year in which the largest number of top 100 articles were published was 2004 (n = 6). Within the top 100, the majority of articles originated from the United States (n = 52). Research Reports-Biomaterials & Bioengineering was the most frequent category of cited articles (n = 35). There was no significant association between total citation count and time since publication (correlation coefficient = -0.051, P = 0.656). However, there was a significant negative association of citation density (correlation coefficient = -0.610, P < 0.01) with time since publication. Our analyses demonstrate the broad reach of the journal and the dynamics in citation patterns and research agenda over its 100-y history. There is considerable evidence of the high variance in research output, when measured via citations, across the globe. Moreover, it remains unclear how patients' priorities and dental health care needs are aligned with the perceived influence of single research pieces identified by our search. Our findings may help to inspire future research in tackling these inequalities and highlight the need for conceptualizing research priorities.