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Diagnostic potential of salivary interleukin‐17, RANKL, and OPG to differentiate between periodontal health and disease and discriminate stable and unstable periodontitis: A case‐control study
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Abstract<sec><title>Background and Aims

Limitations of the conventional diagnostic techniques urged researchers to seek novel methods to predict, diagnose, and monitor periodontal disease. Use of the biomarkers available in oral fluids could be a revolutionary surrogate for the manual probing/diagnostic radiograph. Several salivary biomarkers have the potential to accurately discriminate periodontal health and disease. This study aimed to determine the diagnostic sensitivity and specificity of salivary interleukin (IL)‐17, receptor activator of nuclear factor‐κB ligand (RANKL), osteoprotegerin (OPG), RANKL/OPG for differentiating (1) periodontal health from disease and (2) stable and unstable periodontitis.

Methods

Participants with periodontitis (n = 50) and gingivitis (n = 25), both diseases represented the cases, and subjects with healthy periodontium (n = 15) as a control were recruited for this study. Periodontitis cases were further equally subdivided into stable and unstable. Whole unstimulated salivary sample were collected from all participants. Periodontal parameters including bleeding on probing, probing pocket depth, clinical attachment loss, and number of missing teeth were recorded. The protein levels of salivary IL‐17, RANKL, and OPG were determined by using enzyme‐linked immunosorbent assays technique.

Results

Salivary IL‐17, OPG, RANKL, and RANKL/OPG showed high sensitivity and specificity to differentiate periodontal health from gingivitis and periodontitis. Similar pattern was observed in discriminating stable and unstable periodontitis. Salivary IL‐17 and RANKL showed a good accuracy to differentiate gingivitis from periodontitis. However, OPG and RANKL/OPG did not exhibit enough sensitivity and specificity to differentiate the latter conditions.

Conclusion

Salivary IL‐17, RANKL, OPG, and RANKL/OPG system are potential candidates for differentiating periodontal health and disease and discriminate stable and unstable periodontitis.

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Publication Date
Mon Nov 30 2020
Journal Name
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In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne

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Mon Oct 31 2022
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Formulating Inhibited Fluids for Stable Drilling Operations into Tanuma and Zubair Shales, Zubair Oilfield, Southern Iraq
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Gene expression of Interleukin-10 and Foxp3 as critical biomarkers in rheumatoid arthritis patients
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Tue Nov 01 2022
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Publication Date
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Media and democracy between propaganda and incitement
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Mon Dec 20 2021
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STUDY THE PHYSICAL AND CHEMICAL PROPERTIES AND DETERMINATION THE CYTOTOXICITY OF KOJIC ACID PRODUCED FROM THE LOCAL ISOLATE ASPERGILLUS FLAVUS WJF81 AND THEIR EFFECTS ON CONSUMER HEALTH.: STUDY THE PHYSICAL AND CHEMICAL PROPERTIES AND DETERMINATION THE CYTOTOXICITY OF KOJIC ACID PRODUCED FROM THE LOCAL ISOLATE ASPERGILLUS FLAVUS WJF81 AND THEIR EFFECTS ON CONSUMER HEALTH.
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