Non-Equilibrium Thermodynamics: A Theoretical and Computational Framework for Complex Biological Systems-A Recent Literature Review
December 1, 2025Analyzing Pseudomonas aeruginosa Isolates from Diwaniyah Hospitals, Iraq, for Beta-Lactamase Genetic and Behavioral Resistance Mechanisms Via Genetic Detection
December 1, 20251Saba Hameed Alshebani, 2Athraa Shakir Khozan, 3Rihab qusay Hakim, 4Huda Hayder
Abed 5Hawraa kareem mohammed, 6Anwar Ibraheem Faisal, 7Haneen Husham abboodi
8Hodaa Qassim
1Department of Basic Sciences, College of Dentistry, University of Al-Qadisiyah
2,3,4,5,6,7College of Dentistry, University of Al-Qadisiyah
8Biology Department, Education College, University of Al-Qadisiyah
Abstract
This study aimed to investigate the prevalence of Porphyromonas gingivalis and Prevotella intermedia in gingivitis and periodontitis patients in Diwaniyah, and to analyze their virulence genes (fimA and adpC) using real-time PCR and sequencing. A total of 120 clinical isolates were obtained from patients aged 16–65 years with suspected gingivitis or periodontitis. Samples were analyzed by quantitative real-time PCR for detection of P. gingivalis and P. intermedia, followed by sequencing of fimA and adpC genes for phylogenetic analysis. Statistical tests (Pearson correlation and ANOVA) were used to evaluate associations between bacterial loads, clinical parameters, and demographic factors. P. intermedia was detected in 78.33% of patients, while P. gingivalis was present in 37.5%. Sequencing revealed significant genetic diversity among isolates, with multiple genotypes identified for both species. Phylogenetic analysis indicated local clustering of some strains, while others formed independent evolutionary lineages, suggesting possible new variants. The high prevalence of P. intermedia compared to P. gingivalis highlights its prominent role in the studied population. Genetic heterogeneity of virulence genes suggests ongoing bacterial adaptation, which may contribute to disease severity. Real-time PCR and molecular typing provide reliable tools for early detection and epidemiological tracking of periodontal pathogens.
