Interaction between TCF7L2 rs7903146 Genotype, HbA1c Levels, and the Periodontal Status of Dental Patients

Publisher Copyright: © 2021 Georg Thieme Verlag. All rights reserved.Objective The aim of the study was to investigate the potential interaction between TCF7L2 rs7903146 genotype, which is implicated for type-2 diabetes mellitus genetic susceptibility, HbA1c levels, and the periodontal status of dental patients. Materials and Methods HbA1c levels, clinical periodontal parameters (probing depth, clinical attachment level, bleeding on probing, and plaque index), and several parameters (such as body mass index [BMI], smoking habits, education level, and age) were recorded in 150 patients who fulfilled the criteria for screening for prediabetes/diabetes of the Centers for Disease Control and Prevention. DNA was extracted and the TCF7L2 single nucleotide polymorphism (SNP) rs7903146 was genotyped in all participants. Results Thirty-one patients out of 150 tested were found with unknown hyperglycemia (20.7%). Regarding sex, education, parent with diabetes, normal BMI, smoking, age ≥45 years and prior testing for diabetes, no differences were observed between patients displaying HbA1c 0.05). Regarding periodontal parameters and differences between subgroups (HbA1c levels ≥ 5.7 and HbA1c levels 5.7 and HbA1c 0.05). Statistical AnalysisPatient characteristics and their association with prediabetes were tested by Pearson's Chi-square test (asymptotic, two sided). Differences of periodontal parameters between subgroups were tested with the Mann-Whitney U-test. The associations of allele and genotype frequencies in the patient and control groups were analyzed using the Fisher's exact test of independence.The significance level was set at the 0.05 for all tests. Conclusion A statistically significant association between TCF7L2 rs7903146 genotype and periodontal condition or HbA1c levels was not observed in contrast to statistically significant differences of clinical parameters of periodontitis in patients with hyperglycemia.Peer reviewe

A deep learning approach for identifying sarcasm in text

The aim of this work is to evaluate the performance of deep learning, specifically models of Recurrent Neural Networks (RNN) and Convolutional Neural Networks (CNN), on the problem of detecting sarcasm in tweets. This is done partly by comparing our results to current state-of-the art performance, and partly by making a qualitative analysis of network functionality. In addition to this, we also conduct a survey to examine the human ability to detect sarcasm in tweets for result comparison. We examine three models: Two RNNs, one with Long Short Term Memory (LSTM) cells and one with Gated Recurrent Unit (GRU) cells, and also a CNN. Sarcasm detection is done by binary classification on the same datasets used by related works, and our performance is then compared to that of those works’. The main questions we aim to answer by analyzing the network functionality are what features affect the outcome, and how. By comparing our classifications with those of a basic bag-of-words model, scrambling the word content in tweets and looking at repeatedly misclassified tweets we are able to get a deeper understanding of the networks’ decisions. Experimental results suggest that the networks’ predictions mainly are based on word occurrence in the tweets. The best performance reach an F1-score of 0.842 when using the RNN with LSTM-cells. This network performed better overall among our models, indicating it might be the best option for this particular task. When conducting the survey, the model performed with an F1-score of 0.775 whereas humans reached an average score of 0.701. The model also performed better than a basic bag-of-words model, indicating that deep neural networks might be a feasible approach in tackling the problem of sarcasm detection in text

Prediabetes/Diabetes Can Be Screened at the Dental Office by a Low-Cost and Fast Chair-Side/Point-of-Care aMMP-8 Immunotest

Pre-diabetes and diabetes are strongly associated with periodontal disease (gingivitis and periodontitis), and these conditions are known to upregulate aMMP-8 in inflamed gingiva and oral fluids. Thus, it would be feasible to screen for prediabetes and diabetes at the dental office by chairside tests. Chair-side assessment of HbA1c and a quantitative point-of-care (PoC) active matrix metalloproteinase (aMMP)-8 oral rinse immunotest developed for periodontal diseases, were performed on patients (n = 69) attending a Periodontology University Clinic who fulfilled the criteria for testing according to the screening questionnaire of the Centers for Disease Control and Prevention, USA. Clinical parameters of periodontal disease were also recorded with an automated probe. Twenty seven-point-five percent of the subjects were found with previously unknown hyperglycemia (HbA1c ≥ 5.7%). There was a statistically-significant positive association between the aMMP-8test and prediabetes (p < 0.05, unadjusted and adjusted for BMI and age ≥ 45 years logistic regression models). The dental setting is suitable for opportunistic screening for undiagnosed diabetes and pre-diabetes and point-of-care HbA1c, especially when combined with aMMP-8 assessment by dental professionals, being convenient and effective

Prediabetes/Diabetes Can Be Screened at the Dental Office by a Low-Cost and Fast Chair-Side/Point-of-Care aMMP-8 Immunotest

Pre-diabetes and diabetes are strongly associated with periodontal disease (gingivitis and periodontitis), and these conditions are known to upregulate aMMP-8 in inflamed gingiva and oral fluids. Thus, it would be feasible to screen for prediabetes and diabetes at the dental office by chairside tests. Chair-side assessment of HbA1c and a quantitative point-of-care (PoC) active matrix metalloproteinase (aMMP)-8 oral rinse immunotest developed for periodontal diseases, were performed on patients (n = 69) attending a Periodontology University Clinic who fulfilled the criteria for testing according to the screening questionnaire of the Centers for Disease Control and Prevention, USA. Clinical parameters of periodontal disease were also recorded with an automated probe. Twenty seven-point-five percent of the subjects were found with previously unknown hyperglycemia (HbA1c ≥ 5.7%). There was a statistically-significant positive association between the aMMP-8test and prediabetes (p < 0.05, unadjusted and adjusted for BMI and age ≥ 45 years logistic regression models). The dental setting is suitable for opportunistic screening for undiagnosed diabetes and pre-diabetes and point-of-care HbA1c, especially when combined with aMMP-8 assessment by dental professionals, being convenient and effective

Prediabetes/diabetes screening strategy at the periodontal clinic

Objective: The aim of the study was to propose an efficient chairside clinical strategy for the identification of undiagnosed hyperglycaemia in periodontal clinics. Material and methods: Alpha chairside system was used for assessment of glycated hemoglobin 1c (HbA1c) and active Matrix Metalloproteinase-8 levels (aMMP-8) were analyzed by immunotest in patients (n = 150) who fulfilled the criteria for screening of the Centers for Disease Control and Prevention. Full-mouth periodontal parameters were assessed and various data such as Body Mass Index (BMI), smoking and education were recorded. Results: Thirty-one patients out of 150 tested were found with unknown hyperglycaemia (20.7%). Regarding sex, education, parent with diabetes, normal BMI, smoking, age >= 45 years and prior testing for diabetes, no differences were observed between subjects displaying HbA1c = 5.7% (Pearson's Chi-square test, p > .05). Subgroups differed regarding BMI (kg/m(2)), tooth count, percentages of 4 and 5 mm pockets (Mann-Whitney and z-test, p = 5.7 was tested by Receiving Operator Characteristic curves and Areas Under the Curve (AUC) for the following: age >= 45 years and BMI (AUC 0.651, p = .010), the above and aMMP-8 (AUC 0.660, p = .006), age >= 45 years, BMI and Stage of Periodontitis (AUC 0.711, p = 45 years, BMI, aMMP-8 and stage of periodontitis (AUC 0.713, p <.001). Conclusions: Findings of the study suggest that the combination of stage of periodontitis, increasing age, BMI and aMMP-8, without chairside HbA1c assessment appears to be a viable screening strategy for referring dental patients for testing for prediabetes/diabetes.Peer reviewe

Is There a Link between COVID-19 and Periodontal Disease? A Narrative Review

Publisher Copyright: © 2022 Georg Thieme Verlag. All rights reserved.The coronavirus disease 2019 (COVID-19) pandemic greatly affected human well-being, social behavior, global economy, and healthcare systems. Everyday clinical practice in dentistry has been adjusted to the increased hazards of aerosol production by routine dental procedures. The objective of this study was to assess the existing literature to determine possible mechanisms of a relationship between COVID-19 and periodontitis, as well as describe findings from relevant epidemiological studies.Scarce data exist in the literature that directly addresses the relationship between the two diseases. However, several data describe the role of the oral cavity and periodontal tissues as portals of entry of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), and the contribution of cytokines known to be produced in periodontal disease to severe forms of COVID-19. It is also suggested from the current literature that periodontal disease, shown to be associated with systemic diseases such as diabetes mellitus, cardiovascular and respiratory diseases, shares common risk factors with-especially-severe forms of COVID-19.Further clinical studies are required to establish the relationship between these diseases. Oral hygiene performance and intact periodontal tissues can assist in mitigating the pandemic, and it is suggested that dental practitioners can contribute to identifying at-risk patients.Peer reviewe

Active matrix metalloproteinase-8 : A potential biomarker of oral systemic link

Objectives: This mini review aims to address some possible gaps in periodontal diagnosis in clinical studies particularly involving the oral-systemic connection with a view to minimize such gaps, and thus improve patient treatment experiences and outcomes. Methods: The conventional assessment of periodontitis has traditionally been by clinical and radiographic oral parameters. We reviewed numerous studies published mainly within the past decade, to affirm the oral-systemic link, the contribution of periodontitis to the inflammatory burden in various systemic diseases and conditions, and the potential role of active matrix metalloproteinase-8 (aMMP-8). Results: While it is established that periodontal pathogens in dental plaque biofilm are the primary initiating agents in periodontitis, it has become clear from the appraisal of recent studies that the host inflammation, including biomarkers such as aMMP-8 play a major role, being the driving underlying pathological mechanism in both periodontitis and systemic diseases. Conclusions: The apparent limitations of conventional diagnostic tools have led researchers to seek alternative methods of evaluation such as the quantification of biomarkers including aMMP-8, which can be a bridge between oral/periodontal and systemic diseases; aMMP-8 can form a mouth-body connection.Peer reviewe

Linking oral microbial proteolysis to aMMP-8 PoC diagnostics along with the stage and grade of periodontitis : A cross-sectional study

Peer reviewe

Active MMP-8 (aMMP-8) as a Grading and Staging Biomarker in the Periodontitis Classification

The aim of this study was to investigate the utility of incorporating active matrix metalloproteinase-8 (aMMP-8) as a biomarker into the new periodontitis classification system (stage/grade) presented in 2018. This study included 150 Greek adults aged 25–78, of whom 74 were men and 76 women. Participants were tested with an aMMP-8 point-of-care mouthrinse test, after which a full-mouth clinical examination was performed to assess their periodontal and oral health. The aMMP-8 levels in mouthrinse were significantly lower among healthy patients compared with patients in more severe periodontitis stages and grades (Kruskal–Wallis test and Dunn–Bonferroni test for pairwise post-hoc comparisons; p < 0.01 and p < 0.05, respectively). Furthermore, aMMP-8 levels were less correlated with plaque levels than bleeding on probing (BOP) (Spearman’s rho = 0.269, p < 0.001; Spearman’s rho = 0.586, p < 0.001); respectively). Thus, aMMP-8 was more robust to the confounding effects of oral hygiene than traditional periodontal parameter bleeding on probing. The aMMP-8 point-of-care mouthrinse test can be utilized as an adjunctive and preventive diagnostic tool to identify periodontal disease, classified by stage and grade, and ongoing periodontal breakdown chairside in clinical practice in only 5 min. Overall, integrating aMMP-8 into the new periodontitis classification system seems beneficial