Background. Oral health is a substantial subject in human health which poor hygiene can cause a disturbance in the body. Periodontitis is an inflammatory oral disease that etiology factors have a critical role in it; like microorganisms and host immune response. Fluctuation expression of Immune biomarkers in developmental of this disease is beneficial in periodontitis diagnostic. Methods. Published articles were accomplished from PubMed, Google Scholar, Wiley, Springer, Science Direct and Elsevier from 2012 to June 2019. Entirely, 45 articles were found and related ones reviewed. Results. Not only microorganisms have a key role in the initiation of this disease but also immune response affects like double edge knife in progression and recurrence. Biomarkers are an imperative mediator in the immune system that accomplishes many functions in the body can initiate or promote periodontitis disease. Varied Cytokines such as IL-1β , IL-6, IL-17, IL-18, IL-21, and TNF-β are a critical diagnostic marker in diagnostic of PERIODONTAL disease. It is proved that with the severity of periodontitis the IL-1β and IL-6 levels increased, whereas the TNF-β levels decreased. Also, post stimulation IL-1 β and IL-6 levels were higher in patients with improved treatment outcome. Conclusions. Periodontitis is a convoluted inflammatory disease that affects the quality of life which immune biomarkers have a critical role in the procedure and stage of this disease. Study and assessment of these immunomodulators in laboratory can help to rapid DIAGNOSIS and specificity treatment of periodontitis in clinic.

Background: Artificial neural networks (ANNs) can be used in various medical cases due to their high performance in learning the relationship between variables. PERIODONTAL diseases are common oral infectious diseases that can cause tooth loss, if not treated. Objectives: The current study aimed at evaluating the role of ANNs in PERIODONTAL disease DIAGNOSIS. Methods: The data were collected from 190 PERIODONTAL disease cases in Zahedan dentistry school from 2015 to 2016. Five variables including age, gender, plaque index, probing pocket depth, and clinical attachment loss index were evaluated. The patients were divided into two groups of training (n = 160), and testing (n = 30). In the current study model, two Levenberg-Marquardet (LM) and scaled conjugate gradient (SCG) algorithms were used, and the results were compared in terms of the number of iterations and the mean square error (MSE). Results: The obtained results showed that the LM algorithm with fewer iterations and a minimum MSE, had a better performance than the SCG algorithm. Conclusions: ANNs can be used with low error as an effective tool to diagnose PERIODONTAL diseases.

Introduction. For DIAGNOSIS and treatment planing and detection the quality of remaining Alveolar bone the radiography is very useful so the type of radiography is very important. The purpose of this study is the comparison between panoramic, periapical (bisecting technique) and vertical bitewing radiographs in DIAGNOSIS of periodontitis. Methods. Twelve patients (3 male and 9 female) with a mean age of 35, with a moderate to advanced periodontitis were evaluated. At the time of PERIODONTAL surgery, in the posterior site of two jaws (in 6 and 7 teeth), the bone loss was measured from CEJ to the base of alveolar bone, and compared with the radiographic findings of proximal bone loss.Results. The average of distance between CEJ and alveolar bone in 48 surfaces were 4.27 in clinic, 4.80 in panoramic, 2.62 in periapical (bisecting technique), 2.98 in vertical bitewing and 4.05 in panoramic without magnification.Discussion. In this research we cancluded that both techniques (periapical and vertical bitewing) are not accurate in detection of proximal bone loss and there was significant difference between quantity of proximal bone in clinical measurment than radiographic measurment and this study showed that the panoramic (specially panoramic without magnification) is more careful than other radiographic techniques in detection of proximal bone loss.

Background: Tracking various biomarkers in serum, gingival crevicular fluid (GCF), and saliva has been introduced as a diagnostic tool for PERIODONTAL disease detection.Objectives: The aim of this study was to compare salivary lactate dehydrogenase (LDH) levels in subjects with PERIODONTAL disease and levels in subjects without PERIODONTAL disease.Materials and Methods: In this case-control study, 170 patients at Hamadan faculty of Dentistry, including patients with PERIODONTAL disease and patients with normal periodontium, were selected and divided into test and control groups. Unstimulated saliva was collected in the same situation from the test and control groups. Each saliva sample was analyzed to measure salivary LDH level on the day of collection, by using commercially available kits according to the manufacturers’ instructions. A statistical T-test was employed to evaluate significant differences among groups.Results: The mean LDH levels in the test and control groups were 1071.67731.004 and 550.91217.215, respectively. As the level of statistical significance was set at P<0.05, data analysis showed a significant difference between the LDH enzymatic level in the test and control groups (P=0.000). Comparison of the LDH enzymatic level in subjects with different genders in the test and control groups showed no significant differences (P=0.340).Conclusions: Salivary LDH levels can be used as marker of PERIODONTAL disease for screening periodontitis in large populations.

Background. The new classification of PERIODONTAL and peri-implant diseases can have a profound and lasting impact on clinical practice in periodontology and implant dentistry. Clinicians have an opportunity to use this model to increase consistency in diagnosing PERIODONTAL conditions and educating patients on their PERIODONTAL treatment needs. The aim of this review is to present new protocols in the DIAGNOSIS and management of PERIODONTAL disease for clinical practice and education. Methods. This review was based on most recent published articles related to the new classification of PERIODONTAL diseases and conditions in databases such as PubMed, Medline and Web of Science in 2018-2019. The complete review and consensus reports, published in both the Journal of Clinical Periodontology (EFP) and the Journal of Periodontology (AAP), were also used. Results. According to the new classification system, clinical health is defined for the first time and PERIODONTAL diseases are divided into three main categories: 1) PERIODONTAL health, gingival diseases and conditions; 2) Periodontitis; and 3) Other conditions affecting the periodontium. Periodontitis is also divided into three forms: Necrotizing periodontitis, periodontitis as a manifestation of systemic disease, and a single category of periodontitis with staging and grading criteria (removal of the Aggressive and Chronic Periodontitis terms). Some case reports have demonstrated that staging and grading system can be an effective method in management of patient with periodontitis. Conclusions. An overview of new classification of PERIODONTAL and peri-implant diseases can provide new clinical information for dentists to refine their diagnoses and treatment planning procedures and ultimately improve outcomes for patients.

Background. Elevated temperature has been recognized as an inflammatory sign. It is the only indication that can be both objectively and quantitatively evaluated and is considered as a potential indicator of PERIODONTAL disease. Assessing gingival surface temperature (GST) could be a diagnostic parameter to determine PERIODONTAL health. This pilot clinical study aimed to validate gingival surface temperature (GST) as a clinical diagnostic tool to measure PERIODONTAL disease activity by correlating with the PERIODONTAL inflamed surface area (PISA). Methods. A cross-sectional mono-center pilot study was conducted with a convenient sample of 50 participants with a mean age of 34. 14± 13. 7 years. Clinical parameters such as probing pocket depth (PPD) clinical attachment loss (CAL) and bleeding on probing (BOP) were measured. GST was recorded with a single lead of the bedside patient monitor and correlated with PISA. Results. The results showed a positive correlation between PISA and GST (P=0. 46). Conclusion. This study showed a rise in GST of inflamed sites, but the results did not support the hypothesis that increased GST is an indicator of PERIODONTAL disease. As this is a pilot study, further studies with more larger sample sizes need to be undertaken to confirm its use as a diagnostic tool in clinical trials.

Objective(s): To determine application of the PRECEDE model for increasing coping behaviors against anxiety in Tehran firemen.Methods: This was a quasi experimental study. 118 firemen (59 in experimental group and 59 in control group) from Tehran fire stations were selected as the subjects of the study through a multistage sampling. Data collection tool was a questionnaire developed by author including demographic characteristics and PRECEDE model components.Results: Comparing to the control group, after educational intervention in the study group, the mean scores of knowledge, attitude, self efficacy (predisposing factors), skill of the relaxation (enabling factor), behavior increased significantly (P<0.0001) and use of 3 educational resources (enabling factor) in area of relaxation increased significantly (P<0.03). Also, verbal persuasion and positive experiences after doing relaxation (reinforcing factors) were reported by experimental group.Conclusion: The finding of the study illustrates effective application of PRECEDE model in increasing predisposing, enabling, reinforcing factors and coping behaviors against anxiety in Tehran firemen.