Mild cognitive impairment (MCI) is a clinical syndrome characterized by the onset and evolution of cognitive impairments, often considered a transitional stage to Alzheimer’s disease (AD). The genetic traits of MCI patients who experience a rapid progression to AD can enhance early diagnosis capabilities and facilitate drug discovery for AD. While a genome-wide association study (GWAS) is a standard tool for identifying single nucleotide polymorphisms (SNPs) related to a disease, it fails to detect SNPs with small effect sizes due to stringent control for multiple testing. Additionally, the method does not consider the group structures of SNPs, such as genes or linkage disequilibrium blocks, which can provide valuable insights into the genetic architecture. To address the limitations, we propose a Bayesian bi-level variable selection method that detects SNPs associated with time of conversion from MCI to AD. Our approach integrates group inclusion indicators into an accelerated failure time model to identify important SNP groups. Additionally, we employ data augmentation techniques to impute censored time values using a predictive posterior. We adapt Dirichlet-Laplace shrinkage priors to incorporate the group structure for SNP-level variable selection. In the simulation study, our method outperformed other competing methods regarding variable selection. The analysis of Alzheimer’s Disease Neuroimaging Initiative (ADNI) data revealed several genes directly or indirectly related to AD, whereas a classical GWAS did not identify any significant SNPs.

Tong Nibong is a Bidayuh village located at Sarawak Kalimantan border. Since the year 2004 to 2009, a total of 537 cases of malaria were recorded in Serian District of which 14 cases were reported from Kampung Tong Nibong. Community empowerment programme for malaria infection prevention showed tremendous improvement in implementation. This intervention study aims to gauge the effectiveness of community empowerment approach in malaria elimination programme in Kampung Tong Nibong Serian. An intervention study was conducted with pre and post data collection. Data was collected using validated questionnaire by face to face interview. Universal sampling method was used to select respondents from head of household and post data was collected after intervention activities were carried out within a year of study period. The study showed significant difference on level of knowledge of respondents on vector of malaria between pre and post data with a P < 0.05. There was significant difference between pre and post data on practices on control and prevention of malaria with a P < 0.05. The same goes to level of positive attitude of respondents towards malaria control. In conclusion, the study can be considered successful because there is significant difference in knowledge, attitude and practice among the respondents between pre and post data. This indicates that community empowerment (voluntary participation) measures can be implemented in high risk or endemic areas where malaria is a persistent problem to the community and health institutions faces many limiting factors.​

Background: In the Philippines, 34 Filipinos are killed daily due to road injuries. Of the reported road traffic fatalities, 25% in the world, 34% in South East Asia, and 53% in the Philippines are riders of motorized two- or three-wheeled vehicles. Objectives: Considering that motorcycle drivers are most affected by road-related injuries in Metro Manila, this study aimed to determine the prevalence of helmet use, identify the factors affecting the intent to use helmets, and determine the factors associated with consistent helmet use among motorcycle drivers in District IV, Quezon City. Methods: Eight barangays were included in the sample and respondents were chosen through systematic random sampling. Results: A self-administered questionnaire was used. There were 421 respondents with a prevalence for consistent helmet-use of 67.46% (CI 95%: 62.81-71.78). It was found that the aggregate belief score was associated with the intention to use helmets. Meanwhile, every unit increase in knowledge score increased the odds of consistent helmet use by 1.21 (95% CI: 1.06-1.37). In addition, those with intention were 7.48 times more likely to consistently wear helmets than those who do not (95% CI: 2.80- 19.97). Conclusion Various sub-factors such as experience, formal driving education, perceived behavioral control, benefits, and ergonomic barriers may have contributed to the result; however, further studies are needed to establish these relationships.
Intention ; Health Belief Model ; Theory of Planned Behavior