Maternal Salivary miR-423-5p Is Linked to Neonatal Outcomes and Periodontal Status in Cardiovascular-High-Risk Pregnancies.

Periodontal disease (PD) during pregnancy may trigger systemic inflammation, increasing the risk of developing cardiometabolic disease (CMD). As a consequence, PD may result in the activation of cellular and molecular pathways, affecting the disease course and pregnancy outcome. Although microRNAs (miRNAs) are considered ideal biomarkers for many diseases, few studies have investigated salivary miRNAs and their role in pregnancy or neonatal outcomes. In this study, we sought to investigate the associations between salivary miRNAs of pregnant women with oral diseases and their effects on neonatal outcomes. Eleven (n = 11) salivary miRNAs from a cohort of pregnant women with oral diseases (n = 32; oral health, H; gingivitis, G; and periodontitis, P) were detected using a previous profiling analysis with an FDR < 0.20 and a fold change (FC) < 0.5 or FC > 2 for the most highly expressed miRNAs. Spearman correlations were performed for 11 salivary microRNAs associated with oral-derived inflammation, which could affect neonatal outcomes during pregnancies at risk for cardiometabolic disease (CMD), defined by the presence of a high pregestational BMI. In addition, ROC curves demonstrated the diagnostic accuracy of the markers used. Upregulation of miR-423-5p expression and a decrease in miR-27b-3p expression were detected in the P-group (p < 0.05), and ROC analysis revealed the diagnostic accuracy of miR-423-5p for discriminating oral diseases, such as gingivitis versus periodontitis (P vs. G, AUC = 0.78, p < 0.05), and for discriminating it from the healthy oral cavity (P vs. H, AUC = 0.9, p < 0.01). In addition, miR-27b-3p and miR-622 were also able to discriminate the healthy group from the P-group (AUC = 0.8, p < 0.05; AUC = 0.8, p < 0.05). miR-483-5p was able to discriminate between the G-group (AUC = 0.9, p < 0.01) and the P-group (AUC = 0.8, p < 0.05). These data support the role of salivary miRNAs as early biomarkers for neonatal outcomes in pregnant women with periodontal disease at high risk for CMD and suggest that there is cross-talk between salivary miRNAs and subclinical systemic inflammation.

Deep learning based approach: automated gingival inflammation grading model using gingival removal strategy.

Gingival inflammation grade serves as a well-established index in periodontitis. The aim of this study was to develop a deep learning network utilizing a novel feature extraction method for the automatic assessment of gingival inflammation. T-distributed Stochastic Neighbor Embedding (t-SNE) was utilized for dimensionality reduction. A convolutional neural network (CNN) model based on DenseNet was developed for the identification and evaluation of gingival inflammation. To enhance the performance of the deep learning (DL) model, a novel teeth removal algorithm was implemented. Additionally, a Grad-CAM + + encoder was applied to generate heatmaps for computer visual attention analysis. The mean Intersection over Union (MIoU) for the identification of gingivitis was 0.727 ± 0.117. The accuracy rates for the five inflammatory degrees were 77.09%, 77.25%, 74.38%, 73.68% and 79.22%. The Area Under the Receiver Operating Characteristic (AUROC) values were 0.83, 0.80, 0.81, 0.81 and 0.84, respectively. The attention ratio towards gingival tissue increased from 37.73% to 62.20%, and within 8 mm of the gingival margin, it rose from 21.11% to 38.23%. On the gingiva, the overall attention ratio increased from 51.82% to 78.21%. The proposed DL model with novel feature extraction method provides high accuracy and sensitivity for identifying and grading gingival inflammation.

Burden of oral diseases predicts development of excess weight in early adolescence: a 2-year longitudinal study.

Dental caries, gingivitis, and excess weight are highly prevalent, interconnected chronic conditions. The association of oral health with the development of adiposity among children is sparsely addressed. We examined the association of oral health to the development of excess weight and central obesity in early adolescence during a 2-year follow-up period. This prospective study was conducted with 2702 children aged 9-12 years at baseline from the Finnish Health in Teens study. Their weight development was followed up for 2 years. Body mass index with age- and sex-specific cut-offs and the waist-height ratio indicated weight status and central obesity. Oral health data (caries experience and gingivitis/calculus) were collected from outpatient records of public dental services. Having both caries experience and gingivitis/calculus was considered burden of oral diseases. Of the sample, 74% were caries-free but 70% exhibited gingivitis and/or calculus, and 20% had both caries experience and gingivitis/calculus. During the follow-up period, 5.3% (n = 124) and 4.7% (n = 118) of the children became overweight/obese or centrally obese, respectively. Having both caries experience and gingivitis/calculus associated with the development of excess weight in a fully adjusted model (HR 1.75, 95% CI 1.03-2.97) but not of central obesity. Caries experience or gingivitis/calculus alone did not associate with adiposity development. CONCLUSION: Having burden of oral diseases without excess weight at early adolescence could imply future weight gain; thus, normal-weight individuals with both caries experience and gingivitis/calculus could be targeted with preventive measures. Our findings warrant further research to explore whether oral diseases and the development of obesity merely share risk factors or if their relationship is of causal nature. WHAT IS KNOWN: • Association of excess weight with caries experience and gingivitis is known to exist both cross-sectionally and longitudinally in children and adolescents. WHAT IS NEW: • Burden of oral diseases, that is, having both caries experience and gingivitis/calculus, was associated with becoming overweight or obese 2 years later during early adolescence. • Normal-weight individuals with burden of oral diseases at early adolescence could be targeted with preventive measures against excess weight gain.

Determination of dysbiosis by the method of multiplex real-time polymerase chain reaction in chronic catarrhal gingivitis in children.

OBJECTIVE: Aim: The aim of the study was to determine the quantitative and qualitative characteristics of the microbiota of dento-gingival plaque in children to improve the quality of treatment of chronic catarrhal gingivitis. PATIENTS AND METHODS: Materials and Methods: It was examined 16 children aged 9-16 years with a diagnosis of K05.1: chronic gingivitis and 10 persons with intact gums were taken as a comparison group. A clinical dental examination was performed on the study participants and a sample was taken to determine the bacteria in the periodontal plaque. RESULTS: Results: The results of statistical processing of the research data allowed us to establish that in patients with chronic gingivitis, quantitative indicators of the total bacterial mass, Lactobacillus spp., Enterobacteriaceae, Gardnerella vaginalis/Prevotella bivia/Porphyromonas spp. in the sample of periodontal plaque significantly exceeded the indicators of healthy patients. It was determined that the examined children with chronic gingivitis, the total number of Lactobacillus spp. significantly exceeds its amount in people with intact gums. CONCLUSION: Conclusions: The changes in the quantitative and qualitative characteristics of the main representatives of the microf i lm of dento-gingival plaque, which characterize dysbiosis, are of signif i cant clinical signif i cance. Study of the quantitative characteristics of Lactobacterium spp., Enterobacterium spp., Streptococcacea spp., Gardnerella spp., Prevotella spp., Porphyromonas spp., Eubacteridacea spp., Mycoplasma (hominis + genitalium), Candida spp. is a diagnostic factor in determining the condition of the mucous membrane of the oral cavity.

Evaluation of transfer ensemble learning-based convolutional neural network models for the identification of chronic gingivitis from oral photographs.

BACKGROUND: To evaluate the performances of several advanced deep convolutional neural network models (AlexNet, VGG, GoogLeNet, ResNet) based on ensemble learning for recognizing chronic gingivitis from screening oral images. METHODS: A total of 683 intraoral clinical images acquired from 134 volunteers were used to construct the database and evaluate the models. Four deep ConvNet models were developed using ensemble learning and outperformed a single model. The performances of the different models were evaluated by comparing the accuracy and sensitivity for recognizing the existence of gingivitis from intraoral images. RESULTS: The ResNet model achieved an area under the curve (AUC) value of 97%, while the AUC values for the GoogLeNet, AlexNet, and VGG models were 94%, 92%, and 89%, respectively. Although the ResNet and GoogLeNet models performed best in classifying gingivitis from images, the sensitivity outcomes were not significantly different among the ResNet, GoogLeNet, and Alexnet models (p>0.05). However, the sensitivity of the VGGNet model differed significantly from those of the other models (p < 0.001). CONCLUSION: The ResNet and GoogLeNet models show promise for identifying chronic gingivitis from images. These models can help doctors diagnose periodontal diseases efficiently or based on self-examination of the oral cavity by patients.

Serum vitamin D, hemoglobin A1c and vitamin B12 levels in patients with gingivitis and periodontitis stages.

Aim: To compare the serum vitamin D, hemoglobin A1c (HbA1c) and vitamin B12 levels in patients with gingivitis and four different periodontitis stages diagnosed according to the 2017 Periodontal Disease Classification. Materials & methods: A total of 606 patients were included in the study who were diagnosed with gingivitis and stage I-IV periodontitis. Patients were divided into groups based on disease stage, and the HbA1c, vitamin D and B12 levels of the patients were compared and analyzed. Result: The highest HbA1c level and the lowest vitamin D level were seen in stage III-IV periodontitis. The highest vitamin D and B12 levels were seen in the gingivitis group. Conclusion: Serum HbA1c, vitamin D and B12 levels might vary depending on the presence or severity of periodontitis.Clinical Trial Registration: NCT05745779 (This study was registered and approved by www.clinicaltrials.gov).

[Box: see text].

The Association between Salivary Metabolites and Gingival Bleeding Score in Healthy Subjects: A Pilot Study.

Periodontal diseases, including gingivitis and periodontitis, are among the most prevalent diseases in humans. Gingivitis is the mildest form of periodontal disease, characterized by inflammation of the gingiva caused by the accumulation of dental plaque. Salivary diagnostics are becoming increasingly popular due to the variation in saliva composition in response to pathological processes. We used a metabolomics approach to investigate whether a specific saliva metabolic composition could indicate preclinical stage of gingivitis. 1H-NMR spectroscopy was used to obtain the salivary metabolite profiles of 20 healthy subjects. Univariate/multivariate statistical analysis evaluated the whole saliva metabolite composition, and the Full-Mouth Bleeding Score (FMBS) was employed as a classification parameter. Identifying a signature of specific salivary metabolites could distinguish the subjects with high FMBS scores but still within the normal range. This set of metabolites may be due to the enzymatic activities of oral bacteria and be associated with the early stages of gingival inflammation. Although this analysis is to be considered exploratory, it seems feasible to establish an FMBS threshold that distinguishes between the absence and presence of early inflammatory alterations at the salivary level.

Non-invasive assessment of periodontal inflammation by continuum-removal hemodynamic spectral indices.

BACKGROUND: Hyperspectral techniques have aroused great interest in non-invasively measuring periodontal tissue hemodynamics. However, current studies mainly focused on three typical inflammation stages (healthy, gingivitis and periodontitis) and practical approaches for using optical spectroscopy for early and precisely detection of periodontal inflammation at finer disease stages have not been well studied. METHODS: This study provided novel spectroscopic insights into periodontitis at different stages of disease, and developed six simple but physically meaning hemodynamic spectral indices (HSIs) including four spectral absorption depths of oxyhemoglobin ( D HbO 2 ), deoxyhemoglobin ( D Hb ), total hemoglobin ( t Hb ) and tissue water ( D water ), and two normalized difference indices of oxyhemoglobin( N D HbO 2 I ) and deoxyhemoglobin ( N D Hb I ) from continuum-removal spectra (400-1700 nm) of periodontal tissue collected from 47 systemically healthy subjects over different severities from healthy, gingivitis, slight, moderate to severe periodontitis for early and precision diagnostics of periodontitis. Typical statistical analyses were conducted to explore the effectiveness of the proposed HSIs. RESULTS: D Hb and t Hb exerted significant increasing trends as inflammation progressed, whereas D HbO 2 exhibited significant difference (P < 0.05) from the healthy sites only at moderate and severe periodontitis and D water presented unstable sensitives to disease severity. By contrast, N D HbO 2 I and N D Hb I showed more steadily downward trends as severity increased, and demonstrated the highest correlations with clinical gold standard parameters. Particularly, the proposed normalized HSIs ( N D HbO 2 I and N D Hb I ) yielded high correlations of - 0.49 and - 0.44 with probing depth, respectively, far outperforming results achieved by previous studies. The performances of the HSIs were also confirmed using the periodontal therapy group. CONCLUSIONS: These results indicated great potentials of combination optical spectroscopy and smart devices to non-invasively probe periodontitis at earlier stages using the simple and practical HSIs. Trial registration This study was retrospectively registered in the Chinese Clinical Trial Registry on October 24, 2021, and the clinical registration number is ChiCTR2100052306.

Anti-melanoma Differentiation-associated Gene 5 Antibody-positive Dermatomyositis Presenting as Refractory Gingivitis at the First Clinical Manifestation.

We herein report a case of melanoma differentiation-associated gene 5 (MDA5) antibody-positive dermatomyositis that developed in a patient with refractory gingivitis. The diagnosis of anti-MDA5 antibody-positive dermatomyositis was made based on a characteristic skin rash, weakness of proximal muscles, interstitial pneumonia, and positivity for anti-MDA5 antibody. The patient was started on triple therapy with high-dose prednisolone, tacrolimus, and intravenous cyclophosphamide. After treatment, the refractory gingivitis disappeared, and the other skin rash and interstitial lung disease also improved. In the diagnosis and treatment of anti-MDA5 antibody-positive dermatomyositis, it is necessary to pay attention to the intraoral findings, including the gingiva.

Evaluation of a Thiol-Detection Test to Assess Tooth Brushing Efficacy in Dogs.

Periodontal disease affects more than 80% of dogs over 3 years of age, making it the most common disease in dogs seen in veterinary clinics. Gingivitis, the early-stage of periodontal disease, may be reversible with tooth brushing. Thiol, a sulfuric compound, has previously been shown to correlate with the degree of periodontal disease. In this study, a thiol-detection test was used to investigate daily tooth brushing efficacy in dogs. Twenty-two beagle dogs were subjected to daily tooth brushing for 2 weeks. Gingival index (GI), plaque index (PI), calculus index (CI) and thiol were assessed before treatment (day 1), after 1 week (day 7), after last treatment (day 14), and 2 weeks after treatment finished (day 29). Degree of stress was also assessed using a fear, anxiety and stress (FAS) scale. Both 7 and 14 days of daily tooth brushing showed an improvement in oral health. Thiol decreased significantly and GI and PI improved significantly after 1 and 2 weeks of brushing. No significant improvement in CI was shown. After an additional 2 weeks without brushing, GI and PI had returned to baseline levels. Stress levels decreased from day 1 to day 14. This study suggests that a thiol-detection test can be used to assess tooth brushing efficacy. Tooth brushing has a positive effect on the oral health in dogs as soon as 7 days after commencement.

The evaluation of salivary leucine-rich alpha-2 glycoprotein (LRG) and C-reactive protein (CRP) in humans with periodontal health or periodontal disease.

OBJECTIVE: The purpose of the present research is to evaluate the salivary levels of leucine-rich alpha-2 glycoprotein (LRG) and C-reactive protein (CRP) in periodontal health and disease (gingivitis and stage III periodontitis) and also to compare the discriminative efficiencies of both biomarkers in periodontal disease. BACKGROUND: LRG is a new acute-phase protein whose functions are still being investigated. LRG and CRP are both biomarkers that are increased by inflammation. No clinical study has yet investigated the comparison of the level of LRG and CRP in periodontal health, gingivitis and periodontitis in saliva samples. METHODS: A total of 60 individuals, including 20 periodontally healthy (control group/group C), 20 with gingivitis (group G), and 20 with Stage III periodontitis (group P), who were systemically healthy and non-smokers, participated in this study. Periodontal charts were used for recording clinical periodontal parameters and saliva LRG and CRP levels were measured by ELISA. Analyzing the area under the curve (AUC) was performed by the receiver-operating characteristics curve. RESULTS: Salivary levels of LRG and CRP were significantly higher in disease groups than in group C (p < .05). Positive statistically significant correlations were observed between both biomarkers and clinical parameters (p < .05). There was also a strong positive correlation between two biomarkers (p < .05). In distinguishing periodontal disease from periodontal health, LRG (AUC = 0.833) and CRP (AUC = 0.826) were found to have similar accuracy (p = .923). CONCLUSION: LRG and CRP may be useful and similarly effective biomarkers in the diagnosis of periodontal diseases based on the findings of this study.

Gingival crevicular fluid levels of apelin correlates with clinical periodontal diagnosis.

OBJECTIVES: Limitations of clinical periodontal measurements have led to the search for reliable biomarkers that can be used in diagnosis and monitoring of periodontal diseases. Considering the relationship of adipokines with periodontal disease, diabetes, and obesity, apelin may be a biomarker for periodontal diseases due to its modulating effects on inflammation. The present study was conducted to determine gingival crevicular fluid (GCF) apelin levels in systemically healthy individuals and to evaluate the potential of apelin as a biomarker for periodontal diagnosis. MATERIALS AND METHODS: Ten individuals with clinically healthy periodontal tissues, 10 patients diagnosed with gingivitis, and 10 patients with periodontitis were included in the present study. Whole mouth clinical periodontal measurements were recorded and GCF samples were obtained from the buccal approximal regions of single-rooted teeth with features that would represent clinical periodontal diagnosis. Apelin level in the samples was determined by ELISA. Clinical and biochemical findings were statistically analyzed. Possible relationship between the variables was evaluated with Pearson correlation analysis. RESULTS: Apelin level in the gingivitis group was higher than that in the clinically healthy group (p = 0.000) and lower than that in the periodontitis group (p = 0.000). A positive correlation was found between GCF apelin concentration and plaque score, bleeding on probing, and probing depth (p = 0.000). CONCLUSIONS: Within the limits of this study, it can be suggested that GCF apelin concentration may be a biomarker that can distinguish between healthy periodontal tissues, gingivitis, and periodontitis patients. CLINICAL RELEVANCE: Apelin concentration in the gingival crevicular fluid may aid in the diagnosis of periodontal disease.

Evaluation of perfusion parameters of gingival inflammation using laser Doppler flowmetry and tissue spectrophotometry- a prospective comparative clinical study.

BACKGROUND: The aim of this study was to determine the values of different perfusion parameters- such as oxygen saturation, the relative amount of hemoglobin, and blood flow- in healthy subjects compared to patients with gingivitis as a non-invasive measurement method. METHODS: A total of 114 subjects were enrolled in this study and separated into subjects with gingivitis (50) and without gingivitis (64) based on clinical examination. Gingival perfusion was measured at 22 points in the maxilla and mandible using laser Doppler flowmetry and tissue spectrophotometry (LDF-TS) with the "oxygen to see" device. All patients underwent measurement of gingival perfusion, followed by the clinical evaluation (measurement of probing depths, evaluation of bleeding on probing, plaque level, and biotype). Perfusion parameters were compared between the groups, associations between the non-invasive and clinical measurements were analyzed, and theoretical optimal cut-off values for predicting gingivitis were calculated with receiver operating characteristics. RESULTS: The mean oxygen saturation, mean relative amount of hemoglobin, and mean blood flow all significantly differed between the groups with and without gingivitis (p = 0.005, p < 0.001, and p < 0.001, respectively). The cut-off value for predicting gingivitis was > 40 AU (p < 0.001; sensitivity 0.90, specificity 0.67). CONCLUSIONS: As a non-invasive method, LDF-TS can help determine gingival hyperemia. Flow values above 40 AU indicate a higher risk of hyperemia, which can be associated with inflammation. The LDF-TS method can be used for the objective evaluation of perfusion parameters during routine examinations and can signal the progression of hyperperfusion before any change in clinical parameters is observed. TRIAL REGISTRATION: All procedures performed in this study involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the institutional Clinical Research Ethics Committee (Ethik-Kommission der Medizinischen Fakultät der RWTH Aachen, Decision Number 286/20) and retrospectively registered by the German Clinical Trials Register (File Number DRKS00024048, registered on the 15th of October 2021).

Comparing gingivitis diagnoses by bleeding on probing (BOP) exclusively versus BOP combined with visual signs using large electronic dental records.

The major significance of the 2018 gingivitis classification criteria is utilizing a simple, objective, and reliable clinical sign, bleeding on probing score (BOP%), to diagnose gingivitis. However, studies report variations in gingivitis diagnoses with the potential to under- or over-estimating disease occurrence. This study determined the agreement between gingivitis diagnoses generated using the 2018 criteria (BOP%) versus diagnoses using BOP% and other gingival visual assessments. We conducted a retrospective study of 28,908 patients' electronic dental records (EDR) from January-2009 to December-2014, at the Indiana University School of Dentistry. Computational and natural language processing (NLP) approaches were developed to diagnose gingivitis cases from BOP% and retrieve diagnoses from clinical notes. Subsequently, we determined the agreement between BOP%-generated diagnoses and clinician-recorded diagnoses. A thirty-four percent agreement was present between BOP%-generated diagnoses and clinician-recorded diagnoses for disease status (no gingivitis/gingivitis) and a 9% agreement for the disease extent (localized/generalized gingivitis). The computational program and NLP performed excellently with 99.5% and 98% f-1 measures, respectively. Sixty-six percent of patients diagnosed with gingivitis were reclassified as having healthy gingiva based on the 2018 diagnostic classification. The results indicate potential challenges with clinicians adopting the new diagnostic criterion as they transition to using the BOP% alone and not considering the visual signs of inflammation. Periodic training and calibration could facilitate clinicians' and researchers' adoption of the 2018 diagnostic system. The informatics approaches developed could be utilized to automate diagnostic findings from EDR charting and clinical notes.

Developing diagnostic tools for canine periodontitis: combining molecular techniques and machine learning models.

BACKGROUND: Dental plaque microbes play a key role in the development of periodontal disease. Numerous high-throughput sequencing studies have generated understanding of the bacterial species associated with both canine periodontal health and disease. Opportunities therefore exist to utilise these bacterial biomarkers to improve disease diagnosis in conscious-based veterinary oral health checks. Here, we demonstrate that molecular techniques, specifically quantitative polymerase chain reaction (qPCR) can be utilised for the detection of microbial biomarkers associated with canine periodontal health and disease. RESULTS: Over 40 qPCR assays targeting single microbial species associated with canine periodontal health, gingivitis and early periodontitis were developed and validated. These were used to quantify levels of the respective taxa in canine subgingival plaque samples collected across periodontal health (PD0), gingivitis (PD1) and early periodontitis (PD2). When qPCR outputs were compared to the corresponding high-throughput sequencing data there were strong correlations, including a periodontal health associated taxa, Capnocytophaga sp. COT-339 (rs =0.805), and two periodontal disease associated taxa, Peptostreptococcaceae XI [G-4] sp. COT-019 (rs=0.902) and Clostridiales sp. COT-028 (rs=0.802). The best performing models, from five machine learning approaches applied to the qPCR data for these taxa, estimated 85.7% sensitivity and 27.5% specificity for Capnocytophaga sp. COT-339, 74.3% sensitivity and 67.5% specificity for Peptostreptococcaceae XI [G-4] sp. COT-019, and 60.0% sensitivity and 80.0% specificity for Clostridiales sp. COT-028. CONCLUSIONS: A qPCR-based approach is an accurate, sensitive, and cost-effective method for detection of microbial biomarkers associated with periodontal health and disease. Taken together, the correlation between qPCR and high-throughput sequencing outputs, and early accuracy insights, indicate the strategy offers a prospective route to the development of diagnostic tools for canine periodontal disease.

Investigation of volatile sulfur compound level and halitosis in patients with gingivitis and periodontitis.

This study aimed to measure the levels of volatile sulfur compounds and investigate the occurrence of halitosis in patients with gingivitis and periodontitis. Additionally, the incidence rates of gingivitis and periodontitis in patients with halitosis were investigated. Through various statistical analyses, we attempted to determine the relationship between periodontal disease and halitosis. One-hundred-and-four participants (52 females and 52 males, mean age: 46.49 ± 16.03 years) were enrolled in this cross-sectional study, comprising 33 healthy controls, 43 patients with gingivitis, and 28 patients with periodontitis. Gas chromatography was used to measure hydrogen sulfide (H2S) and methyl mercaptan (CH3SH), which are representative VSCs. The VSC cut-off values for diagnosing halitosis were 65.79 ppb for women and 79.94 ppb for men. Total VSC level was significantly higher in the gingivitis than the healthy control group (186.72 ± 374.83 ppb vs. 19.80 ± 40.19 ppb, p = 0.035). There was no significant difference between the gingivitis and periodontitis (153.79 ± 278.51 ppb) groups. H2S level was significantly higher in the gingivitis (100.51 ± 183.69 ppb) and periodontitis (91.57 ± 132.06 ppb) groups than in healthy controls (14.97 ± 31.22 ppb), and CH3SH level was significantly higher in gingivitis group (29.31 ± 59.16 ppb) than in the healthy control (5.73 ± 14.10 ppb) (all p < 0.05). Halitosis was found in 3% of healthy controls and 39.5% and 42.9% of patients with gingivitis and periodontitis patients, respectively, making it significantly higher in the gingivitis and periodontitis groups than the healthy controls (p = 0.005). Conversely, among participants with halitosis, 53.1% had gingivitis, 37.5% had periodontitis, and 90.6 incidence had periodontal disease. Multivariate logistic regression analysis to predict the presence of halitosis, found periodontal disease was a significant predictor of halitosis (OR = 3.607, 95% CI 1.023-12.718, p = 0.046). Considering area under curve value for halitosis, the cut-off value of healthy control (H2S:61.5 ppb, CH3SH:3.5 ppb), gingivitis (H2S:50.0 ppb, CH3SH:6 ppb), and periodontitis (H2S:62.0 ppb, CH3SH:3.5 ppb) were (all p < 0.05). Our results emphasize the close and strong relationship between periodontal disease and halitosis through human clinical evidence based on the high co-occurrence rate of mutual diseases. Additionally, the presence of periodontal disease increased the probability of halitosis by 3.607 times. These results suggest that H2S can be used as a biomarker of halitosis in patients with periodontal disease.

An unusual case of linear IgA disease affecting only the oral gingiva: a case report.

BACKGROUND: We present a case report on desquamative gingivitis diagnosed as linear IgA disease (LAD), which is a rare autoimmune bullous disease exclusively affecting the oral gingiva. The oral mucosa can be impacted by various autoimmune bullous diseases, and our report focuses on this particular manifestation of LAD. CASE PRESENTATION: This patient presented with atypical symptoms, as frequent blister formation on the gingiva was the primary clinical manifestation. A combination of systemic and local treatment was administered to the patient. Following the treatment, there was a significant improvement observed in both the erythema and the bullous lesions on the gingiva. CONCLUSIONS: A more suitable local treatment strategy should be formulated for patients presenting with oral topical lesions, which clinicians can employ effectively.

Computer-assisted periodontal classification vs manual classification among dental students: a comparative pilot study.

OBJECTIVE: The objective of the study was to assess whether computer-assisted periodontal diagnosis can improve the accuracy and homogeneity of classification results obtained by dental students using the 2017 classification of periodontal diseases. METHOD AND MATERIALS: All final year predoctoral dental students from two dental schools were invited to participate in the study. Participants who volunteered for the study were randomly divided into two groups for digital or manual diagnosis, and each participant classified 48 cases. A group of three experienced periodontists provided the reference or gold standard diagnosis. RESULTS: Overall, 27 students completed the evaluation of all cases; 14 students comprised the digital application group and 13 the manual group. The accuracy of the classification results compared with the gold standard committee was 82% for the digital group compared to 50% of the manual group in terms of the extent of gingivitis; 71% vs 56% for the stage of periodontitis; 67% vs 62% for grade of periodontitis; 76% vs 63% for extent of periodontitis; and 43% vs 30% for overall diagnosis accuracy of periodontitis cases respectively. CONCLUSIONS: Computer-assisted classification using newly developed software, within the boundaries of this study, was shown to be a sensible support tool for dental practitioners to use when diagnosing periodontal disease. This digital tool can the clinicians' accuracy of diagnosis primarily in the extent and staging of periodontitis.

"Plasma cell gingivitis" encompasses multiple entities: a retrospective series of 37 cases.

BACKGROUND: Plasma cell gingivitis is defined as gingival inflammation comprised of plasma cell infiltrates. This diagnostic criterion is non-specific and underlying mechanisms remain unknown. OBJECTIVES: We performed a multidisciplinary clinico-pathological review of cases previously identified as "gingivitis with plasma cell infiltrates", with assessment of putative contributing factors and critical appraisal of the final diagnosis. MATERIALS & METHODS: Cases previously identified as "gingivitis with plasma cell infiltrates" between 2000 and 2020 were included from archives from the GEMUB group, a French multidisciplinary network of physicians with expertise on oral mucosa. RESULTS: Among the 37 included cases, multidisciplinary clinico-pathological review allowed differential diagnosis in seven cases (oral lichen planus n=4, plasma cell granuloma n=1, plasmacytoma n=1, and mucous membrane pemphigoid n=1). The remaining cases were classified as "reactive plasma cell gingivitis" (induced by drugs, trauma/irritation or periodontal disease) (n=18) or "idiopathic plasma cell gingivitis" when no contributing factors were identified (n=12). Clinico-pathological characteristics did not differ significantly between "reactive" and "idiopathic" cases, preventing us from identifying specific features of "idiopathic" plasma cell gingivitis. CONCLUSION: "Plasma cell gingivitis" is a polymorphous, non-specific entity with various aetiologies, of which the diagnosis requires multidisciplinary anatomo-clinical correlation for exclusion of secondary causes of plasma cell infiltration. Although our study was limited by its retrospective design, most cases of "plasma cell gingivitis" appeared to be associated with an underlying cause. We propose a diagnostic algorithm to properly investigate such cases.