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• W2912300181 abstract "It has been shown that bacteria in periodontally diseased patients can be recognized by the detection of volatile metabolites in the headspace of saliva by real-time ambient mass spectrometry. The aim of this study was to use this detection method to analyze the oral metabolome in diseased periodontitis patients before and after therapy to monitor disease evolution and healing events. Twelve patients with advanced chronic periodontal disease and 12 periodontally healthy controls served as test and control groups, respectively. Clinical data, subgingival plaque samples and saliva samples were collected at baseline (BL) and 3 months after treatment. The test group received non-surgical scaling and root planing using systemic antibiotics and the control group received one session of supragingival cleaning. Saliva samples from all subjects were analyzed with ambient mass spectrometry. Significant metabolic alterations were found in the headspace of saliva of periodontitis patients 3 months after the non-surgical periodontal treatment. Furthermore, the diseased group showed metabolic features after the treatment that were similar to the healthy control group. In addition, 29 metabolic features correlated with A. actinomycetemcomitans, 17 features correlated with P. gingivalis and one feature correlated with T. denticola. It was shown that headspace secondary electrospray ionization - mass spectrometry allows the detection of different volatile metabolites in healthy and diseased patients. It can be concluded that this rapid and minimally invasive method could have the potential to routinely diagnose and monitor periodontal diseases in the headspace of saliva samples and, eventually, in exhaled breath." @default.
• W2912300181 created "2019-02-21" @default.
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• W2912300181 date "2019-09-01" @default.
• W2912300181 modified "2023-10-16" @default.
• W2912300181 title "Metabolic changes during periodontitis therapy assessed by real-time ambient mass spectrometry" @default.
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• W2912300181 doi "https://doi.org/10.1016/j.clinms.2019.01.001" @default.
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