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The impact of dental environment stress on caries experience, salivary flow rate and uric acid
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Background: Several pathologies of the oral cavity have been associated with stress. Dental students need to gain assorted proficiencies as theoretical knowledge, clinical proficiencies, and interpersonal dexterity which is accompanied with high level of stress. Uric acid is the major antioxidant in saliva. The aim of this study is to assess the dental caries experience among dental students with different levels of dental environment stress in relation to physicochemical characteristics of whole unstimulated saliva.

Materials and Methods: the total sample is composed of 300 dental students (73 males, 227 female) aged 22-23 years old, from collage of dentistry / university of Baghdad, from the 4th and 5th grade. The total sample was classified into three categories (mild stress, moderate stress and severe stress) according to Dental environment stress questionnaire (DESQ); Diagnosis and recording of dental caries were assessed according to Decay, Missed, Filled surface and teeth index (DMFS, DMFT) of WHO criteria in 1987. Unstimulated salivary samples were collected from the 95 dental students from the mild stress group (27 male, 28 female) and from the severe stress group (11 male, 29 female). Then, salivary flow rate was measured and chemically analyzed to determine salivary uric acid concentration. All data were analyzed using statistical package for social science (SPSS) version 21.

Results: The mean value of the DMFT and DS fraction was higher among severe stress group of dental environment stress scale with no significant differences (P≥ 0.05), while DMFS, FS and MS fractions were higher among moderate stress group of dental environment stress scale with no significant differences (P≥ 0.05). The data from salivary analysis showed that the mean value of salivary flow rate was lower among severe dental environment stress category than mild dental environment stress category but the difference was statistically not significant, while the mean value of uric acid was higher among students with severe dental environment stress than students with mild dental environment stress with statistically significant difference. The flow rate was negatively correlated with caries experience among both mild and severe stress groups except for the DS was positively correlated with flow rate among students with mild stress. The correlation of uric acid with DMFT was negative among students with mild stress while among severe stress group was positive; however all these correlations were not statistically significant.

Conclusion: Dental environment stress appears to affect oral health, shown by higher caries prevalence among dental students with moderate and severe dental environment stress level by affecting the normal level of salivary flow rate and uric acid.

Keywords: Dental environment stress, stress, dental caries, flow rate, uric acid.

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Publication Date
Sat Aug 01 2015
Journal Name
Materials Science And Engineering: C
Antibacterial activity of magnetic iron oxide nanoparticles synthesized by laser ablation in liquid
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In this study, (50–110 nm) magnetic iron oxide (α-Fe2O3) nanoparticles were synthesized by pulsed laser ablation of iron target in dimethylformamide (DMF) and sodium dodecyl sulfate (SDS) solutions. The structural properties of the synthesized nanoparticles were investigated by using Fourier Transform Infrared (FT-IR) spectroscopy, UV–VIS absorption, scanning electron microscopy (SEM), atomic force microscopy (AFM), and X-ray diffraction (XRD). The effect of laser fluence on the characteristics of these nanoparticles was studied. Antibacterial activities of iron oxide nanoparticles were tested against Gram-positive; Staphylococcus aureus and Gram-negative; Escherichia coli, Pseudomonas aeruginosa and Serratia marcescens. The results sh

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Sun Apr 12 2026
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Publication Date
Wed Dec 01 2010
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Publication Date
Sat Oct 01 2022
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Design of a Simple Dust Removal System for a Solar Street Light System
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Recognizing Different Foot Deformities Using FSR Sensors by Static Classification of Neural Networks
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