Aim:The aim was to evaluate knowledge, attitude and practices of soft drink consumption and their dental health between age group 18-25 years students. Materials and Methods: A cross-sectional questionnaire survey was conducted among the students studying MBA between age group 18-25 years students. Information, thus obtained from above questionnaire was entered in MS Excel spreadsheet, and the percentage was calculated. Results: About 58% of the students consumed carbonated beverages twice per day and only 39% of the students' experienced ill-effects of these beverages. It was surprising to note that only 48% of the students felt discomfort within few minutes of consuming the beverage. Conclusion: The prevalence of tooth erosion in the students was high, and the frequency of consumption of potentially erosive soft drinks with low pH values was the only plausible risk factor identified for the development of dental erosion. Most of the students preferred to drink carbonated drinks over the fruit juices in spite of being aware of the ill-effects of carbonated beverages.
The transformation of normal cervix to cervicitis as well as to cervical cancer is accompanied with biochemical alterations at cellular level. Laser induced fluorescence can reflect those changes either as variations in the fluorescence intensity or as shift in the fluorescence maxima of bio fluorophores present in tissues. The curve resolved fluorescence investigation of tissues under 325 nm excitation provides Collagen, bound NADH and free NADH as the discrimination factors between normal, cervicitis and cervical cancer. Even though the fluorescence emission intensity derived from collagen fiber is comparable in both normal and cervicitis, a considerable reduction was observed for the cervical cancer tissues compared to the former. Fluorescence corresponding to bound NADH is found to be reduced during the progression from normal to cervicitis and to cervical cancer, whereas the free NADH shows an opposite trend. The principal component analysis (PCA) was performed to obtain classification of spectral data from different categories on a reduced dimensional space. Furthermore, to test the usefulness of the recorded fluorescence spectra in discriminating the malignant and non-malignant (cervicitis and normal) samples, a supervised machine learning model based on Support Vector Machine (SVM) was built using the PCA-reduced data. The proposed SVM model was able to detect the malignant samples with a Sensitivity of 94.19% and Specificity of 96.51%. Moreover, the Raman spectral data from the corresponding tissue sites corroborate well with the observations derived from the fluorescence measurement. The results obtained in the present pilot study strongly suggests the potential of laser induced fluorescence technique combined with multivariate data analysis tool for the diagnosis of cervicitis and cervical malignancy.
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