Background/Objectives: Nonsurgical periodontal treatment (NSPT) is the gold-standard technique for treating periodontitis. However, an individual’s susceptibility or the inadequate removal of subgingival biofilms could lead to unfavorable responses to NSPT. This study aimed to assess the potential of salivary and microbiological biomarkers in predicting the site-specific and whole-mouth outcomes of NSPT. Methods: A total of 68 periodontitis patients exhibiting 1111 periodontal pockets 4 to 6 mm in depth completed the active phase of periodontal treatment. Clinical periodontal parameters, saliva, and subgingival biofilm samples were collected from each patient at baseline and three months after NSPT. A quantitative PCR assay was used to detect the presence of Fusobaterium nucleatum and Porphyromonas gingivalis in the biofilm samples. Salivary biomarkers including matrix metalloproteinase (MMP)-9, glutathione S-transferase (GST), and Annexin-1 were assayed both qualitatively (Western blot analysis) and quantitively (ELISA). Results: NSPT yielded significant improvements in all clinical parameters, including a reduction in bacterial load and decreased levels of MMP-9 together with increased concentrations of GST and Annexin-1. The binary logistic regression suggested that the overall accuracy of P. gingivalis identification, probing pocket depth, and interproximal sites was 71.1% in predicting successful site-specific outcomes. The salivary biomarker model yielded an overall accuracy of 79.4% in predicting whole-mouth outcomes following NSPT. Conclusions: At baseline, the presence of shallow periodontal pockets at interdental locations with a lower abundance of P. gingivalis is predictive of a favorable response to NSPT at the site level. Decreased salivary MMP-9 associated with increased GST and Annexin-1 levels can predict successful whole-mouth outcomes following NSPT.
The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of
... Show MoreThis study was aimed to explore the impact of a practical program on supporting and reducing
symptoms of school bulling victims in a sample of student in the sixth grade. The study sample consisted of (18)
students that have been chosen from two schools (Al-Abass and Alataa’) it was an intended sample, because
there were enough student with high scores in bulling victims diagnostics test, the sample was divided into two
groups: the control group of (9) student from (Alataa’) school, and the experimental group consisted of (9)
student from Alabass) school keeping in mind to keep the two groups equivalent in maintaining equal controls.
The researcher applied the practical program which is based on cognitive behavioral
One of the unique properties of laser heating applications is its powerful ability for precise pouring of energy on the needed regions in heat treatment applications. The rapid rise in temperature at the irradiated region produces a high temperature gradient, which contributes in phase metallurgical changes, inside the volume of the irradiated material. This article presents a comprehensive numerical work for a model based on experimentally laser heated AISI 1110 steel samples. The numerical investigation is based on the finite element method (FEM) taking in consideration the temperature dependent material properties to predict the temperature distribution within the irradiated material volume. The finite element analysis (FEA) was carried
... Show MoreAim of the study: This study's goal was to determine how laser surface alteration affected wettability of injectable thermoplastic acrylic and heat cure acrylic denture base materials. Materials and methods: Injectable thermoplastic acrylic resin (Deflex) and heat cure acrylic (Procryla) were used in this study to produce forty-disc shaped specimens, 20 specimens for each material type. The control group was made up of ten samples of each type of plastic denture base material. The other ten samples were treated with a nano-pulse fiber-optic lens Nd:YAG laser. The results were looked at with the Kruskal-Wallis test and the unpaired t-test (a=.05). Results: Compared to the control groups, the laser-treated groups were more likely to sti
... Show MoreObjective: to evaluate the increase in weight after biological agents and the association of weight gain with the body mass index among a sample of patients attending Baghdad Teaching Hospital Methods: A prospective study is carried out in Baghdad teaching hospital biological units and outpatient clinic of rheumatology for a period of one year starting On April 2015 and ending on March 2016. 120 patients were included in the study 40 psoriatic arthritis .40 ankylosing spondylitis and 40 rheumatoid arthritis Results : The study findings indicate that significance differences are seen regarding weight gain and b
Water quality planning relies on Biochemical Oxygen Demand BOD. BOD testing takes five days. The Particle Swarm Optimization (PSO) is increasingly used for water resource forecasting. This work designed a PSO technique for estimating everyday BOD at Al-Rustumiya wastewater treatment facility inlet. Al-Rustumiya wastewater treatment plant provided 702 plant-scale data sets during 2012-2022. The PSO model uses the daily data of the water quality parameters, including chemical oxygen demand (COD), chloride (Cl-), suspended solid (SS), total dissolved solids (TDS), and pH, to determine how each variable affects the daily incoming BOD. PSO and multiple linear regression (MLR) findings are compared, and their perfor
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