Role of induced nitric oxide synthases in orofacial nociception/discomfort after dental tooth bleaching with hydrogen peroxide

OBJECTIVE

To evaluate the role of induced nitric oxide synthase (iNOS) in nociception/orofacial discomfort in rats submitted to tooth whitening with hydrogen peroxide (H₂O₂).

DESIGN

Wistar rats were divided into three groups (n = 24/group): a sham group not submitted to whitening treatment, a saline group submitted to whitening treatment, and a test group submitted to whitening treatment and blockade of iNOS with aminoguanidine 50 mg/kg/day. After 24 and 48 h, and 7 days, the animals were euthanized to collect trigeminal ganglia and maxillae to histomorphometric analysis (size of neuronal bodies and percentage of pulp area filled by vessels) and behavior/nociception (Grimace scales, scratching and biting counting, weight loss and nociception assay). ANOVA-1- or - 2-way tests were used (p < 0.05, GraphPadPrism 5.0).

RESULTS

The aminoguanidine-treated group showed a reduction in nociceptive threshold in the masseteric region (p < 0.001), Grimace scale scores (p < 0.001), number of scratching (p = 0.011) and body mass loss (p = 0.007). After 24 and 48 h of tooth bleaching, the saline group showed a significant increase in the mean area of the blood vessels (p = 0.020) and iNOS immunostaining in odontoblasts (p = 0.002) and non-odontoblasts cells (p = 0.025). Aminoguanidine reversed both increases. Tooth bleaching reduced the mean area of neuronal bodies, and aminoguanidine significantly reversed it (p = 0.019), but an increase in GFAP immunostaining in neuronal bodies did not reduce after seven-days or after aminoguanidine treatment (p = 0.003).

CONCLUSION

iNOS blockage by aminoguanidine plays an important role in nociception and orofacial discomfort by control of inflammation in dental pulp after tooth bleaching with hydrogen peroxide (H₂O₂) 35%.

Development and professional validation of an App to support Oral Cancer Screening

The objective of this study was to develop and validate an App for identifying risk factors for oral cancer. To this end, we developed an App (OCS: Oral Cancer Screening) with predictors of Oral Cancer (OC) and algorithm assembly to estimate the risk of its development.

METHODOLOGY

Simulated clinical cases were designed so that 40 professionals with expertise in oral diagnostics could validate the algorithm and test its usability (SUS: System Usability Score) and acceptability (TAM: Technology Acceptance Model). Cronbach's alpha coefficient, Friedman/Dunn tests, and Spearman correlation evaluated the SUS and TAM scales. ROC curve was plotted to estimate the cutoff point of the algorithm in suggesting a high risk for OCS of the simulated cases. Chi-square and Fisher's exact tests were additionally used (p<0.05, SPSS v20.0).

RESULTS

Professionals with expertise in oral diagnosis had usability of 84.63±10.66 and acceptability of 84.75±10.62, which correlated positively (p<0.001, r=0.647). Acting in clinical areas of dentistry (p=0.034) and history of performing OC risk factor orientation (p=0.048) increased acceptability while acting in higher education increased usability (p=0.011). The cutoff point suggested by the App after validation of the simulated clinical cases showed high sensitivity of 84.8% and lower specificity of 58.4%.

CONCLUSION

The OCS was effective and with adequate sensitivity, usability, and acceptability and may contribute to the detection of early oral lesions.