Altered miRNA expression profiling in enamel organ of fluoride affected rat embryos.

Evidence has shown that miRNAs could play a role in dental fluorosis, but there is no study has investigated the global expression miRNA profiles of fluoride-exposed enamel organ. In this study, we analysed the differentially expressed (DE) miRNAs between fluoride-treated and control enamel organ for the first time and found several candidate miRNAs and signaling pathways worthy of further research. Thirty Wistar rats were randomly distributed into three groups and exposed to drinking water with different fluoride contents for 10 weeks and during the gestation. The three groups were a control group (distilled water), medium fluoride group (75 mg/L NaF), and high fluoride group (150 mg/L NaF). On the embryonic day 19.5, the mandible was dissected for histological analysis, and the enamel organ of the mandibular first molar tooth germ was collected for miRNA sequencing (miRNA-seq) and quantitative real-time PCR analysis (qRT-PCR). Typical dental fluorosis was observed in the incisors of the prepregnant rats. In addition to the disorganized structure of enamel organ cells, 39 DE miRNAs were identified in the fluoride groups compared with the control group, and good agreement between the miRNA-seq data and qRT-PCR data was found. The functional annotation of the target genes of 39 DE miRNAs showed significant enrichment in metabolic process, cell differentiation, calcium signaling pathway, and mitogen-activated protein kinase(MAPK) signaling pathway terms. This study provides a theoretical reference for an extensive understanding of the mechanism of fluorosis and potential valuable miRNAs as therapeutic targets in fluorosis.

Association between occlusal support and cognitive impairment in older Chinese adults: a community-based study.

Introduction: The loss of occlusal support due to tooth loss is associated with systemic diseases. However, there was little about the association between occlusal support and cognitive impairment. The cross-sectional study aimed to investigate their association. Methods: Cognitive function was assessed and diagnosed in 1,225 community-dwelling adults aged 60 years or older in Jing'an District, Shanghai. Participants were diagnosed with mild cognitive impairment (MCI) by Peterson's criteria, or dementia, according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. We determined the number of functional occlusal supporting areas according to Eichner classifications. We used multivariate logistic regression models to analyze the relationship between occlusal support and cognitive impairment and mediation effect models to analyze the mediation effect of age. Results: Six hundred sixty participants were diagnosed with cognitive impairment, averaging 79.92 years old. After adjusting age, sex, education level, cigarette smoking, alcohol drinking, cardiovascular disease, and diabetes, individuals with poor occlusal support had an OR of 3.674 (95%CI 1.141-11.829) for cognitive impairment compared to those with good occlusal support. Age mediated 66.53% of the association between the number of functional occlusal supporting areas and cognitive impairment. Discussion: In this study, cognitive impairment was significantly associated with the number of missing teeth, functional occlusal areas, and Eichner classifications with older community residents. Occlusal support should be a significant concern for people with cognitive impairment.

Association of occlusal support with type 2 diabetes: A community-based study.

Occlusal support was proved to be associated with type 2 diabetes. Our aim was to investigate the association between the Eichner index and the prevalence of type 2 diabetes. We included 715 participants with oral health examinations in the Shanghai Aging Study. The occlusal support status was determined by the number of functional occlusal support areas and Eichner index classifications. Those with fasting plasma glucose ≥126 mg/dL and/or hemoglobin A1c ≥6.5% and/or current medications for type 2 diabetes with relevant medical history were diagnosed with type 2 diabetes. Multiple logistic regression models were used to analyze the relationship between occlusal support status and type 2 diabetes. The average age of 715 participants was 73.74 ± 6.49 years old. There were 84 diabetics with 1.71 occlusal supporting areas on average. Seven hundred and fifteen participants were divided into 3 groups according to Eichner classifications: Eichner group A with 4 occlusal functional areas, Eichner group B with 1-3 occlusal functional areas or 0 area with anterior occlusal contact, and Eichner group C with no functional occlusal contact. Blood glucose level was significantly lower in participants of Eichner group A compared to those in group B or C. The ordinal logistic regression showed more occlusal supporting areas were significantly associated with less type 2 diabetes cases with an Odds Ratio(OR) of 0.253(95%CI 0.108-0.594) after adjusting covariates. Participants in Eichner group A had a significantly much lower OR of 0.078 for type 2 diabetes (95%CI 0.009-0.694) compared to those in Eichner group C after adjustment. The number of functional occlusal support areas might be inversely related to the blood glucose level and the prevalence of type 2 diabetes.

Active neural networks to detect mentions of changes to medication treatment in social media.

OBJECTIVE: We address a first step toward using social media data to supplement current efforts in monitoring population-level medication nonadherence: detecting changes to medication treatment. Medication treatment changes, like changes to dosage or to frequency of intake, that are not overseen by physicians are, by that, nonadherence to medication. Despite the consequences, including worsening health conditions or death, 50% of patients are estimated to not take medications as indicated. Current methods to identify nonadherence have major limitations. Direct observation may be intrusive or expensive, and indirect observation through patient surveys relies heavily on patients' memory and candor. Using social media data in these studies may address these limitations. METHODS: We annotated 9830 tweets mentioning medications and trained a convolutional neural network (CNN) to find mentions of medication treatment changes, regardless of whether the change was recommended by a physician. We used active and transfer learning from 12 972 reviews we annotated from WebMD to address the class imbalance of our Twitter corpus. To validate our CNN and explore future directions, we annotated 1956 positive tweets as to whether they reflect nonadherence and categorized the reasons given. RESULTS: Our CNN achieved 0.50 F1-score on this new corpus. The manual analysis of positive tweets revealed that nonadherence is evident in a subset with 9 categories of reasons for nonadherence. CONCLUSION: We showed that social media users publicly discuss medication treatment changes and may explain their reasons including when it constitutes nonadherence. This approach may be useful to supplement current efforts in adherence monitoring.