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Radha, V.
- Genetic Basis of Monogenic Diabetes
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1 Department of Molecular Genetics, Madras Diabetes Research Foundation, #20, Golden Jubilee Biotech Park for Women Society, SIPCOT, Siruseri, Chennai 603 103, IN
1 Department of Molecular Genetics, Madras Diabetes Research Foundation, #20, Golden Jubilee Biotech Park for Women Society, SIPCOT, Siruseri, Chennai 603 103, IN
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Current Science, Vol 113, No 07 (2017), Pagination: 1277-1286Abstract
Advances in the understanding of monogenic causes of diabetes and the discovery of single-gene mutations responsible for different phenotypes have greatly increased our knowledge of β-cell physiology. Such advances have had implications for the individual patient diagnosed with the specific monogenic cause of diabetes, especially in maturity onset diabetes of the young (MODY) and neonatal diabetes mellitus (NDM). Genetic diagnosis of MODY is also likely to have important prognostic and therapeutic implications in majority of the patients with confirmed HNF1A and HNF4A mutations. Genetic screening and analyses have helped several neonatal infants carrying mutations in the KCNJ11 and ABCC8 genes to shift from insulin treatment to oral sulphonylurea drugs. The progress in genomics of monogenic diabetic forms has helped in translating the discoveries from bench to bedside in clinical care. Therefore, there is an urgent need to incorporate genetic testing for the genes implicated in monogenic diabetes like MODY and NDM in the diabetes clinics. Discoveries in genetic research methodology and understanding of genetic etiology will have great translational implications for disease treatment and follow-up.Keywords
Genetic Screening, Maturity Onset Diabetes of the Young, Monogenic Diabetes, Neonatal Diabetes, Precision Medicine.References
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- Morphological Characteristics of Root Surfaces after Root Planing with Curettes under Microscope, Dental Loupes and Naked Eye-A SEM Study
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Authors
Affiliations
1 Department of Periodontics, Saveetha Dental College, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, IN
1 Department of Periodontics, Saveetha Dental College, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, IN
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Research Journal of Pharmacy and Technology, Vol 12, No 4 (2019), Pagination: 1547-1550Abstract
Aim: To analyze the morphological characteristics of the ischolar_main surfaces with scanning electron microscope after scaling and ischolar_main planing with curettes under microscope, dental loupes, and naked eye. Material and Methods: Extracted teeth were randomly allocated to Group 1: SRP under Naked eye, Group 2: SRP with dental loupes (x3.5), Group 3: SRP under microscope (x12) where N=18 (6 in each group). Presence or absence of smear layer was compared with chi square test and to compare Remaining calculus index (RCI) and Roughness and loss of tooth substance index (RLTSI) between the groups, One way ANOVA was used. Results: The one-way ANOVA test showed statistically significant differences favoring group 3, as to RCI on ischolar_main surfaces (p = 0.007) and RLTSI (p=0.00). The Chi-square test also showed statistically significant difference favoring group 3 (p=0.05) as to the presence or absence of smear layer. Conclusion: Considering the obtained results and the methodology used in this study, it may be concluded that scaling and ischolar_main planing with curettes under microscope of x12 magnification provided smoother ischolar_main surface with nearly no smear layer remaining calculus when compared with SRP done under naked eye and dental loupes of x3.5 magnification.Keywords
Root Planing, Root Surface Morphology, Root Surface, Microsurgery, Surface Roughness.References
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- Comparison of Naive Bayes and SVM Classifiers for Detection of Spam SMS using Natural Language Processing
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Authors
N. Krishnaveni
1,
V. Radha
2
Affiliations
1 Department of Information Technology, Avinashilingam Institute for Home Science and Higher Education for Women, IN
2 Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, IN
1 Department of Information Technology, Avinashilingam Institute for Home Science and Higher Education for Women, IN
2 Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, IN
Source
ICTACT Journal on Soft Computing, Vol 11, No 2 (2021), Pagination: 2260-2265Abstract
Day today’s innovative world observers an extraordinary possibility in the communication sector. Individuals will in general utilize various approaches to speak with individuals around the world. The regular methods for sharing short data in an exceptionally simple manner and is cases recorded now a days. This desires a need to recognize Spam SMS to stay away from digital wrongdoing robbery and extortion exercises. A labeled dataset is utilized for recognition reason and two classifiers to be specific Support Vector Machine and Naïve Bayes are utilized to make a correlative examination for the location of spam accomplished by utilizing of Short Message Service. SMS doesn’t require any web charges yet, it is unsurpassed utilized methods for remote correspondence. Each versatile client has this office of course. It has an incredible monetary effect on the clients just as the specialist co-ops. Then again SMS spam is one of the major digital wrong doing SMS and the exhibition of classifiers are thought about.Keywords
Spam SMS, Support Vector Machine, Naïve Bayes, Classification, Natural Language Processing.References
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