https://www.selleckchem.com/products/stattic.html To describe the caries lesion transition pattern in permanent tooth surfaces over 2years among a convenience sample of children in a fluoridated (0.8ppm F) low-socioeconomic community of Brazil. One hundred forty-nine schoolchildren (7-12years) were examined for caries using Nyvad criteria at baseline and after 2years. Descriptive analysis was used to evaluate caries lesion transition patterns. Less than 1% of sound surfaces and non-cavitated caries lesions at baseline progressed to cavitation stage within 2years. 12.7% of the active non-cavitated (ANC) lesions became inactive, 34.7% regressed to sound, 48.0% remained active, and 4.6% progressed to cavitated/filled stages at follow-up. Similarly, 55.2% of the inactive non-cavitated (INC) lesions at baseline remained inactive, 33.3% regressed to sound, 8.0% progressed to cavitated/filled lesions, while only 3.5% progressed to ANC lesions. The caries lesion transition pattern in this child population exposed to water fluoride and fluoride toothpaste showed that a low proportion of sound surfaces and non-cavitated lesions progressed to cavitation within the 2-year follow-up. Caries arrest was mainly ascribed to a high proportion of active non-cavitated lesions regressing to sound or inactive lesions. Caries activity can be controlled by regular exposure to fluoridated water and fluoridated toothpaste. Caries activity can be controlled by regular exposure to fluoridated water and fluoridated toothpaste. Machine learning (ML) algorithm can improve risk prediction because ML can select features and segment continuous variables effectively unbiased. We generated a risk score model for mortality with ML algorithms in East-Asian patients with heart failure (HF). From the Korean Acute Heart Failure (KorAHF) registry, we used the data of 3683 patients with 27 continuous and 44 categorical variables. Grouped Lasso algorithm was used for the feature selection, and a novel continu