Effect of Tricalcium Phosphate and Calcium Sucrose Phosphate on the Inhibition of Streptococcus mutans: An In Vivo Study.

AIM: To determine the efficacy of tricalcium phosphate (TCP) and calcium sucrose phosphate (CSP) on the inhibition of Streptococcus mutans (SM). MATERIALS AND METHODS: Thirty healthy children between 13 and 18 years of age were divided into two groups of 15 each; Group I receiving TCP-containing cream and Group II receiving calcium sucrose phosphate-containing cream. On the first day of the study, 30 minutes after breakfast, baseline plaque samples were taken from the buccal surface of first mandibular permanent molar using a sterile wedge which was immediately transferred to sterile container containing 1 mL of saline, and were subjected to microbiological examination. On the following days, both the creams were applied to the respective groups. On the 16th day, plaque samples were collected from the same site, and colony forming units were recorded using agar plate as a culture medium. RESULTS: The mean of S. mutans count before application of TCP-containing paste was 16.27 cfu per mL and before calcium sucrose phosphate-containing paste was 15.33 cfu per mL. The mean after application of TCP-containing paste and calcium sucrose phosphate-containing paste was 3.53 and 9.87 cfu per mL, respectively. And, there was a statistically significant difference found within the groups. CONCLUSION: Both TCP and CSP have an inhibitory effect on S. mutans. CLINICAL SIGNIFICANCE: This can be an effective preventive tool for children with high caries risk and even for special child. Both TCP and CSP deposit the mineral reservoir in plaque and saliva; it may help resist the future cariogenic challenges.

The increased risk of microvascular complications in South Asians with type 1 diabetes is influenced by migration.

AIM: We aimed to explore the association between South Asian ethnicity and complications of type 1 diabetes, and whether this is affected by migration. METHODS: In this retrospective cohort study, data on diabetes control and complications were obtained for South Asians in India (South AsiansIndia , n = 2592) and the UK (South AsiansUK , n = 221) and white Europeans in the UK (n = 1431). Multivariable logistic regression was used to identify associations between ethnicity and diabetic kidney disease, retinopathy and neuropathy adjusting for age, sex, BMI, disease duration, HbA1c , blood pressure (BP) and cholesterol. RESULTS: South AsiansIndia had significantly greater adjusted odds of diabetic kidney disease [odds ratio (OR) 5.0, 95% confidence intervals (CI) 3.6-7.1] and retinopathy (OR 1.8, 95% CI 1.2-2.5), but lower odds of neuropathy (OR 0.5, 95% CI 0.4-0.6) than white Europeans. South AsiansIndia had significantly greater adjusted odds of diabetic kidney disease (OR 3.0, 95% 1.8-5.3) than South AsiansUK , but there was no significant difference in the odds of other complications. CONCLUSIONS: In this hypothesis-generating study, we report that South Asian ethnicity is associated with greater risk of diabetic kidney disease and retinopathy, and lower risk of neuropathy than white European ethnicity. Part of the excess diabetic kidney disease risk is reduced in South AsiansUK . These associations cannot be accounted for by differences in vascular risk factors. Our findings in South Asians with type 1 diabetes mirror previous findings in type 2 diabetes and now need to be validated in a study of the effect of ethnicity on type 1 diabetes complications where healthcare is provided in the same setting.

A novel approach for the prediction of treadmill test in cardiology using data mining algorithms implemented as a mobile application.

OBJECTIVE: To develop a mobile app called "TMT Predict" to predict the results of Treadmill Test (TMT), using data mining techniques applied to a clinical dataset using minimal clinical attributes. To prospectively test the results of the app in realtime to TMT and correlate with coronary angiogram results. METHODS: In this study, instead of statistics, data mining approach has been utilized for the prediction of the results of TMT by analyzing the clinical records of 1000 cardiac patients. This research employed the Decision Tree algorithm, a new modified version of K-Nearest Neighbor (KNN) algorithm, K-Sorting and Searching (KSS). Furthermore, curve fitting mathematical technique was used to improve the Accuracy. The system used six clinical attributes such as age, gender, body mass index (BMI), dyslipidemia, diabetes mellitus and systemic hypertension. An Android app called "TMT Predict" was developed, wherein all three inputs were combined and analyzed. The final result is based on the dominating values of the three results. The app was further tested prospectively in 300 patients to predict the results of TMT and correlate with Coronary angiography. RESULTS: The accuracy of predicting the result of a TMT using data mining algorithms, Decision Tree and K-Sorting & Searching (KSS) were 73% and 78%, respectively. The mathematical method curve fitting predicted with 82% accuracy. The accuracy of the mobile app "TMT Predict", improved to 84%. Age-wise analysis of the results show that the accuracy of the app dips when the age is more than 60years indicating that there may be other factors like retirement stress that may have to be included. This gives scope for future research also. In the prospective study, the positive and negative predictive values of the app for the results of TMT and coronary angiogram were found to be 40% and 83% for TMT and 52% and 80% for coronary angiogram. The negative predictive value of the app was high, indicating that it is a good screening tool to rule out coronary artery heart disease (CAHD). CONCLUSION: "TMT Predict" is a simple user-friendly android app, which uses six simple clinical attributes to predict the results of TMT. The app has a high negative predictive value indicating that it is a useful tool to rule out CAHD. The "TMT Predict" could be a future digital replacement for the manual TMT as an initial screening tool to rule out CAHD.

Lipid Profile in Childhood-and Youth-Onset Type 2 Diabetes and their Association with Microvascular Complications.

AIM: To assess the lipid profiles in childhood and youth onset type 2 diabetes (T2DM) and study their association with microvascular complications. METHODS: Clinical details of individuals with childhood and youth onset T2DM, age at diagnosis between 10 and 25 yrs (n=1340) were retrieved from electronic medical records. Lipid abnormalities were classified based on the NCEP (ATP III) guidelines and management of dyslipidemia in children and adolescents with diabetes. Retinopathy was assessed by retinal photography; nephropathy, if albumin excretion was ≥300 mg/g of creatinine or if the 24 hour protein excretion was >500 mg and neuropathy by elevated vibration perception threshold (≥20 V) on biothesiometry. RESULTS: Out of 1,340 individuals with childhood and youth with T2DM, 53.3% of them were male. The mean age and duration of diabetes were 28.4 ± 10.4 and 7.4 ± 9.5 years respectively. Overall, the prevalence of dyslipidemia was 82.1%. Prevalence of hypercholesterolemia, hypertriglyceridemia, low HDL-C and high LDL-C were 40.7%, 52.8%, 59.1 % and 64.5% respectively. In logistic regression, both in unadjusted and adjusted model, hypercholesterolemia, and hypertriglyceridemia were associated with diabetic retinopathy [OR:1.8, CI:1.4-2.4, p<0.001 and 1.7, 1.3-2.2, p<0.001] and nephropathy [OR:1.7, CI:1.1-2.5, p=0.015 and 1.8, 1.2-2.8, p=0.007]. Additionally, hypercholesterolemia was associated with neuropathy, even after adjusting for age at diagnosis of diabetes and glycated hemoglobin [OR1.6, 1.0-2.5, p=0.041]. CONCLUSIONS: Lipid abnormalities are common and associated with microvascular complications among these T2DM individuals. This underscores the need for effective control of lipids among childhood and youth onset T2DM.

Clinical and molecular characterization of neonatal diabetes and monogenic syndromic diabetes in Asian Indian children.

Mutations in the pancreatic ATP sensitive K(+) channel proteins [sulfonyluea receptor 1 (SUR1) and inward rectifier K(+) channel Kir6.2 (Kir6.2), encoded by ATP-binding cassette transporter subfamily C member 8 (ABCC8) and potassium channel J11 (KCNJ11), respectively], are the most common cause of neonatal diabetes. We describe the clinical presentation and molecular characterization of Asian Indian children with neonatal diabetes mellitus and monogenic syndromes of diabetes. We sequenced KCNJ11, ABCC8 and insulin (INS) genes in 33 unrelated Indian probands with onset of diabetes below one year of age. A total of 12 mutations were identified which included ABCC8 mutations in seven, KCNJ11 mutations in three and INS mutations in two children. The Asp212Tyr mutation in ABCC8 was novel. We also detected two novel mutations (Val67Met and Leu19Arg) in children with syndromic forms of diabetes like Berardinelli Seip syndrome [1-acyl-sn-glycerol-3-phosphate acyltransferase beta (AGPAT2)] and Fanconi Bickel syndrome [solute carrier family 2A2 (SLC2A2)]. Children carrying the KCNJ11 (Cys42Arg, Arg201Cys) and ABCC8 (Val86Ala, Asp212Tyr) mutations have been successfully switched over from insulin therapy to oral sulfonylurea. Our study is the first large genetic screening study of neonatal diabetes in India.