Calcifying odontogenic cyst is considered as a rare lesion and accounts for 1% of jaw cysts. It represents a heterogeneous group of lesions which exhibit a variety of clinicopathologic and behavioral features. It has been categorized as cyst and neoplasm. Even after several classification and subclassification, COC remains an enigma. WHO classification 2005 has reclassified the lesion as calcifying cystic odontogenic tumor (CCOT). Ameloblastomatous COC is a rare variant which is not much described in the literature. This report describes one such case which was large multicystic, involved the coronoid and condylar process of the mandible, and treated by subhemimandibulectomy. The case was recurrence free even after 1 year of followup.
Aim: The present study was aimed to assess the fasting and postprandial gingival crevicular blood (GCB) glucose and finger stick blood glucose measurements using a glucometer.
Materials and methods:A total of 30 subjects with periodontitis and positive bleeding on probing were considered. Subjects were instructed to report to the department after overnight fasting. Gingival crevicular blood samples were collected from anterior region showing bleeding on probing followed by finger stick blood sample collection. Then, the patients were instructed to take 75 gm of glucose and after 2 hours blood samples from two sites were collected similarly. Results were analyzed using unpaired t test and Pearson's correlation.
Results:Mean glucose levels form GCB and finger stick blood did not differ either during fasting or postprandial (p > 0.05). Significant correlation was found between GCB glucose levels and capillary finger stick blood (CFB) glucose levels during fasting
Conclusion:Periodontal probing can be considered as an alternate noninvasive method of blood glucose estimation for screening of diabetes mellitus (DM). The technique described is safe, easy to perform, and helps to increase the frequency of diabetes screening in dental office.Clinical significance: The GCB from probing can be a good source of blood for estimating blood glucose levels and screening for diabetes using portable glucose monitors. Also, it will be a simple and relatively inexpensive in office screening procedure for any patient suspected to have diabetes.
This paper proposes Computerized Aided Detection System (CAD) which uses Content Based Image Retrieval (CBIR) to detect cancer nodules present in an image. The CAD system is concerned for the radiologists to identify lung cancer at premature stages, which are very tiny nodules that are not able to seen by naked eye. In modern years, Image processing techniques play a key role in predicting diseases at early stages in particular in various cancer types such as liver cancer, breast cancer etc. This paper comprises of four steps: i) preprocessing an image in order to lessen the noise level and the accuracy of the image is to be improved, so that the accuracy in detection will be higher. ii) The image is segmented based on Marker-Controlled Watershed Segmentation. iii) The features of the nodules present in the image are extracted using GLCM. iv) The nodules are classified based on the extracted features using KNN classifier. The Content Based Image Retrieval Technique is used which is used to redeem query based images in the database by combining feature extraction and similarity matching methods. For experimentation of proposed technique, CT images are used which are extracted from Lung Image Database Consortium database (LIDC).
Tremendous need of data over cellular network increases the development of new communication technology 6G. 5G mobile networks cannot fulfil the technological requirements required for various applications like deep sea and space tourism, collaborative robots and in holographic tele-presence. Development of 6G systems and applications has been an admired theme in the research community. The new generation communication system developed in every 10 years improves the quality of service metrics by incorporating new features and services. Even though 5G is not been a commercial reality, 6G is expected to be available in 2030. This paper enlightens a vision on 6G technologies and network design principles.
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