RESUMO
Salivary biomarkers can be used as diagnostic and predictive aids in early detection of oral cancer or potentially malignant disorders. A cross-sectional comparative study was conducted over a period of one year from August 2016 to August 2017 in a multicentre setting in Islamabad. A total of 60 patients were recruited and divided into two equal groups of naswar users and non-users. Un-stimulated saliva samples were collected and analysed by using an enzyme-linked immunosorbent assay (ELISA) technique. Data was entered in SPSS version 22.0. The results were then analysed by using independent t-test. Statistically significant difference was found regarding the levels of salivary IL-8 between the naswar users and non-users (p <0.001). The levels of salivary IL-8 in non-users were 33.39 ±22.44 pg/ml, while the increased levels of salivary IL-8 in naswar users were found to be 173.48 ±46.52 pg/ml.
Assuntos
Carcinoma de Células Escamosas/metabolismo , Interleucina-8/metabolismo , Neoplasias Bucais/metabolismo , Saliva/metabolismo , Tabaco sem Fumaça , Adulto , Biomarcadores/metabolismo , Carcinoma de Células Escamosas/diagnóstico , Estudos Transversais , Humanos , Masculino , Pessoa de Meia-Idade , Neoplasias Bucais/diagnóstico , Paquistão , Valor Preditivo dos Testes , Adulto JovemRESUMO
Modelling 3D objects in CAD software requires special skills which require a novice user to undergo a series of training exercises to obtain. To minimize the training time for a novice user, the user-dependent factors must be studied. we have presented a comparative analysis of novice/expert information flow patterns. We have used Normalized Transfer Entropy (NTE) and Electroencephalogram (EEG) to investigate the differences. The experiment was divided into three cognitive states i.e., rest, drawing, and manipulation. We applied classification algorithms on NTE matrices and graph theory measures to see the effectiveness of NTE. The results revealed that the experts show approximately the same cognitive activation in drawing and manipulation states, whereas for novices the brain activation is more in manipulation state than drawing state. The hemisphere- and lobe-wise analysis showed that expert users have developed an ability to control the information flow in various brain regions. On the other hand, novice users have shown a continuous increase in information flow activity in almost all regions when doing drawing and manipulation tasks. A classification accuracy of more than 90% was achieved with a simple K-nearest neighbors (k-NN) to classify novice and expert users. The results showed that the proposed technique can be used to develop adaptive 3D modelling systems.
