Clinical Study and Microbiological Analysis of Periodontopathogenic Microflora Analyzed among Children and Adolescents with Cardiovascular Diseases Compared to Group with Good General Status.

Periodontal diseases, as an important part of oral pathology, present different characteristics when affecting children and adolescents or young adults. Studies have shown that adolescence and childhood are closely related to a high risk of periodontal disease, but the follow-up for periodontal health or damage at this age has been insufficiently appreciated until now. The aim of this study was to identify subgingival microorganisms using a real-time polymerase chain reaction (PCR) in a group of children and adolescents aged 7-17 years with and without cardiovascular disease. The group of 62 subjects with gingival inflammation and poor hygiene was divided into two groups according to general condition: 31 subjects with carduivascular disease (group A) and 31 subjects without cardiovascular disease (group C). Subjects were examined in the initial consultation, the state of hygiene and periodontal inflammation was assessed using the plaque index (PI) and gingival index (GI), and samples were taken from the gingival sulcus using sterile paper cones to determine nine subgingival microorganisms. Nine subgingival microorganisms were identified: Aggregatibacter actinomycetemcomitans (Aa), Porphyromonas gingivalis (Pg), Treponema denticola (Td), Tannerella forsythias (Tf), Prevotella intermedia (Pi), Peptostreptococcus (Micromonas) micros (Pm), Fusobacterium nucleatum (Fn), Eubacterium nodatum (En), and Capnocytophaga gingivalis (Cg). The patients were included in a specialist treatment program which aimed to relieve the inflammatory condition, remove local irritative factors, and train the patients to perform proper oral hygiene at home by using primary and secondary oral hygiene products. Subjects were reevaluated 3 months after treatment, when measurements for the PI and GI and microbiological determinations were repeated. The results showed a predominance of subjects aged 16-17 years (12.4%). Among the subjects with marked gingival inflammation, the male gender was predominant (58.06%). The PI values changed considerably after treatment, with lower values in patients presenting a general condition without cardiovascular disease (PI = 8.10%) compared with the patients with cardiovascular disease (PI = 13.77%). After treatment, the GI showed considerable changes in both groups. Red, orange, and purple complex microorganisms were found before treatment and decreased considerably after treatment in both groups. The highest values were found for Treponema denticola (140,000 (1.4 × 105)) in patients with cardiovascular disease and generalized gingival inflammation. Of the pathogenic microorganisms, the most common was Tannerella forsythia in 52 patients before treatment, and red microorganisms considerably appeared in only 10 patients after treatment. Capnocytophaga gingivalis remained constant both in the diseased state and after treatment and was consistent with periodontal health. Children with cardiovascular diseases had a higher prevalence of gingival manifestations. The composition of the subgingival microbial plaque was directly influenced by the degree of oral hygiene, but the response to specialized treatment was also influenced by the general health status. The results of this study support the conclusion that periodontal pathogens appear and multiply in the absence of proper hygiene in childhood after the eruption of permanent teeth, and their action leads to the initiation of periodontal diseases.

Comparative Clinical Study on Periodontal Health Status and Early Diagnosis of Periodontal Diseases Quantified through Clinical Periodontal Indices on a Group of Children and Adolescents with and without Cardiovascular Diseases.

It is well known that bacterial plaque is the main etiological factor that causes the appearance of periodontal diseases and carious disease. Periodontal diseases can affect children and adolescents and are manifested in the form of gingivitis, but also the early form of chronic periodontitis as well as aggressive marginal periodontitis associated with local or general factors. Early periodontitis is frequently undiagnosed by clinicians due to a lack of knowledge of the specific symptoms. Certain systemic diseases, such as cardiovascular diseases, can create favorable conditions for the appearance and progression of severe manifestations of periodontal disease; also, recent research highlights that individuals with periodontal disease present an increased risk of developing cardiovascular diseases. Children with congenital or acquired cardiovascular diseases are at increased risk for complications resulting from the growth of microorganisms in the oral cavity, presenting a risk of infective endocarditis. The specific aim was to highlight the existing differences between the periodontal health of children with cardiovascular diseases and that of children without these diseases. The analyzed group included 124 patients, represented by children and adolescents, aged between 7 and 17 years, who were divided into four subgroups depending on the presence or absence of cardiovascular diseases and periodontal disease. A specialized clinical examination was performed for each patient, and periodontal clinical parameters were quantified (plaque index, gingival bleeding index, gingival index, community periodontal index of treatment needs) and associated with the diagnosis of general condition. Patients diagnosed with periodontal disease underwent specialized treatment and were called to a control visit 3 months after treatment. Statistical analysis showed significant differences between subgroups with much higher values of clinical parameters for patients with cardiovascular disease. Also, the response to the treatment was better in the case of patients in the control subgroup without cardiovascular diseases. The present study highlighted the interaction of three factors in the progression of periodontal diseases: subgingival microbiota, immune system response and environmental factors.

Combining unsupervised and supervised artificial neural networks to predictaquatic toxicity.

Most quantitative structure-activity relationship (QSAR) models are linear relationships and significant for only a limited domain of compounds. Here we propose a data-driven approach with a flexible combination of unsupervised and supervised neural networks able to predict the toxicity of a large set of different chemicals while still respecting the QSAR postulates. Since QSAR is applicable only to similar compounds, which have similar biological and physicochemical properties, large numbers of compounds are clustered before building local models, and local models are ensembled to obtain the final result. The approach has been used to develop models to predict the fish toxicity of Pimephales promelas and Tetrahymena pyriformis, a protozoan.