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Perceived barriers to and ideas for weight control interventions in Malay homemakers: results from focus groups

Ng LW, Malhotra R, Lai D, Tai ES, Østbye T

Asia Pac J Public Health, 2015 Mar;27(2):NP552-61.
PMID: 23482708 DOI: 10.1177/1010539513479966

To develop a better understanding of perceived barriers to and ideas for weight loss and maintenance among Malay homemakers in Singapore.
Preparation and photodynamic bactericidal effects of curcumin-β-cyclodextrin complex

Lai D, Zhou A, Tan BK, Tang Y, Sarah Hamzah S, Zhang Z, et al.

Food Chem, 2021 Nov 01;361:130117.
PMID: 34058659 DOI: 10.1016/j.foodchem.2021.130117

To overcome the poor water solubility of curcumin, a curcumin-β-cyclodextrin (Cur-β-CD) complex was prepared as a novel photosensitizer. Fourier-transform infrared spectroscopy (FT-IR), differential scanning calorimetry (DSC), and X-ray diffraction (XRD) were used to verify the formation of Cur-β-CD. Furthermore, the ROS generation capacity and photodynamic bactericidal effect were measured to confirm this Cur-β-CD complex kept photodynamic activity of curcumin. The result showed Cur-β-CD could effectively generate ROS upon blue-light irradiation. The plate count assay demonstrated Cur-β-CD complex possess desirable photodynamic antibacterial effect against food-borne pathogens including Staphylococcus aureus, Listeria monocytogenes and Escherichia coli. The cell morphology determined by scanning electron microscope (SEM) and transmission electron microscope (TEM) showed Cur-β-CD could cause cell deformation, surface collapse and cell structure damage of the bacteria, resulting in the leakage of cytoplasmic; while agarose gel electrophoresis and SDS-PAGE further illustrated the inactivation mechanisms by Cur-β-CD involve bacterial DNA damage and protein degradation.
Fulltext Survival Rates and Associated Factors of Colorectal Cancer Patients in Brunei Darussalam

Leong E, Ong SK, Madli F, Tan A, Lai D, Basir N, et al.

Asian Pac J Cancer Prev, 2020 Jan 01;21(1):259-265.
PMID: 31983194 DOI: 10.31557/APJCP.2020.21.1.259

BACKGROUND: Colorectal cancer (CRC) is the third most common cancer in both men and women. In most Asian countries, both the incidence and mortality rates of CRC are gradually increasing. In Brunei Darussalam, CRC ranks first and second in lifetime risk among men and women respectively. This study aims to report the overall survival rates and associated factors of CRC in Brunei Darussalam.
METHODS: This is a retrospective study examining CRC data for the period 2007 to 2017 retrieved from a population based cancer registry in Brunei Darussalam. A total of 728 patients were included in the analysis. Kaplan Meier method was used to estimate survival rates. Univariate analysis using log-rank test was used to examine the differences in survival between groups. Multivariate analysis using Cox PH regression was used to estimate hazard of death and obtain significant predictors that influence CRC patients' survival.
RESULTS: The median survival time for colorectal, colon and rectal cancer patients were 57.0, 85.8 and 40.0 months respectively. The overall 1-, 3- and 5- year survival rates for CRC patients were 78.0%, 57.7% and 49.6% respectively. In univariate analysis, age at diagnosis, ethnicity, cancer stage, tumour location and histology were found to have significant difference in CRC patients' survival. In the Cox PH analysis, older age (≥70 years), cancer stage, ethnicity and other histological type were determined as associated factors of CRC patients' survival.
CONCLUSION: This study found the overall 5-year survival rate of CRC in Brunei Darussalam is similar to that in some Asian countries such as Singapore and Malaysia. However, more efforts need to be carried out in order to raise awareness of CRC and improve the survival of CRC patients.
Comprehensive properties of photodynamic antibacterial film based on κ-Carrageenan and curcumin-β-cyclodextrin complex

Lai D, Zhou F, Zhou A, Hamzah SS, Zhang Y, Hu J, et al.

Carbohydr Polym, 2022 Apr 15;282:119112.
PMID: 35123747 DOI: 10.1016/j.carbpol.2022.119112

In this study, a biodegradable photodynamic antibacterial film (Car-Cur) was prepared using casting method with κ-Carrageenan (κ-Car) as film-forming substrate and curcumin-β-cyclodextrin (Cur-β-CD) complex as photosensitizer. The comprehensive performance of this Car-Cur film was investigated. The obtained results showed that the concentration of Cur-β-CD was an important factor determining the properties of film including tensile strength (TS) elongation at break (EB), water vapor permeability (WVP), water content (WC) and thermal stability. When the concentration of Cur-β-CD is 1%, the film demonstrated the maximum TS and EB, increased thermal stability, with desirable WVP and WC. Furthermore, this film also showed good photodynamic antibacterial potential against Staphylococcus aureus and Escherichia coli upon irradiation of blue LED light. Moreover, the film can be degraded in the soil in one week. In conclusion, our results suggested Car-Cur photodynamic film could be developed as biodegradable antimicrobial packaging material for food preservation.
Fulltext An Automatic Premature Ventricular Contraction Recognition System Based on Imbalanced Dataset and Pre-Trained Residual Network Using Transfer Learning on ECG Signal

Ullah H, Heyat MBB, Akhtar F, Muaad AY, Ukwuoma CC, Bilal M, et al.

Diagnostics (Basel), 2022 Dec 28;13(1).
PMID: 36611379 DOI: 10.3390/diagnostics13010087

The development of automatic monitoring and diagnosis systems for cardiac patients over the internet has been facilitated by recent advancements in wearable sensor devices from electrocardiographs (ECGs), which need the use of patient-specific approaches. Premature ventricular contraction (PVC) is a common chronic cardiovascular disease that can cause conditions that are potentially fatal. Therefore, for the diagnosis of likely heart failure, precise PVC detection from ECGs is crucial. In the clinical settings, cardiologists typically employ long-term ECGs as a tool to identify PVCs, where a cardiologist must put in a lot of time and effort to appropriately assess the long-term ECGs which is time consuming and cumbersome. By addressing these issues, we have investigated a deep learning method with a pre-trained deep residual network, ResNet-18, to identify PVCs automatically using transfer learning mechanism. Herein, features are extracted by the inner layers of the network automatically compared to hand-crafted feature extraction methods. Transfer learning mechanism handles the difficulties of required large volume of training data for a deep model. The pre-trained model is evaluated on the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) Arrhythmia and Institute of Cardiological Technics (INCART) datasets. First, we used the Pan-Tompkins algorithm to segment 44,103 normal and 6423 PVC beats, as well as 106,239 normal and 9987 PVC beats from the MIT-BIH Arrhythmia and IN-CART datasets, respectively. The pre-trained model employed the segmented beats as input after being converted into 2D (two-dimensional) images. The method is optimized with the using of weighted random samples, on-the-fly augmentation, Adam optimizer, and call back feature. The results from the proposed method demonstrate the satisfactory findings without the using of any complex pre-processing and feature extraction technique as well as design complexity of model. Using LOSOCV (leave one subject out cross-validation), the received accuracies on MIT-BIH and INCART are 99.93% and 99.77%, respectively, suppressing the state-of-the-art methods for PVC recognition on unseen data. This demonstrates the efficacy and generalizability of the proposed method on the imbalanced datasets. Due to the absence of device-specific (patient-specific) information at the evaluating stage on the target datasets in this study, the method might be used as a general approach to handle the situations in which ECG signals are obtained from different patients utilizing a variety of smart sensor devices.
Fulltext Feasibility of monitoring Global Breast Cancer Initiative Framework key performance indicators in 21 Asian National Cancer Centers Alliance member countries

Ong SK, Haruyama R, Yip CH, Ngan TT, Li J, Lai D, et al.

EClinicalMedicine, 2024 Jan;67:102365.
PMID: 38125964 DOI: 10.1016/j.eclinm.2023.102365

BACKGROUND: The Global Breast Cancer Initiative (GBCI) Framework, launched by the World Health Organisation (WHO) in 2023, emphasises assessing, strengthening, and scaling up services for the early detection and management of breast cancer. This study aims to determine the feasibility of monitoring the status of breast cancer control in the 21 Asian National Cancer Centers Alliance (ANCCA) countries based on the three GBCI Framework key performance indicators (KPIs): stage at diagnosis, time to diagnosis, and treatment completion.
METHODS: We reviewed published literature on breast cancer control among 21 ANCCA countries from May to July 2023 to establish data availability and compiled the latest descriptive statistics and sources of the indicators using a standardised data collection form. We performed bivariate Pearson's correlation analysis to measure the strength of correlation between stage at diagnosis, mortality and survival rates, and universal health coverage.
FINDINGS: Only 12 (57%) ANCCA member countries published national cancer registry reports on breast cancer age-standardised incidence rate (ASIR) and age-standardised mortality rate (ASMR). Indonesia, Myanmar, and Nepal had provincial data and others relied on WHO's Global Cancer Observatory (GLOBOCAN) estimates. GLOBOCAN data differed from the reported national statistics by 5-10% in Bhutan, Indonesia, Iran, the Republic of Korea, Singapore, and Thailand and >10% in China, India, Malaysia, Mongolia, and Sri Lanka. The proportion of patients diagnosed in stages I and II strongly correlated with the five-year survival rate and with the universal health coverage (UHC) index. Three countries (14%) reported national data with >60% of invasive breast cancer patients diagnosed at stages I and II, and a five-year survival rate of >80%. Over 60% of the ANCCA countries had no published national data on breast cancer staging, the time interval from presentation to diagnosis, and diagnosis to treatment. Five (24%) countries reported data on treatment completion. The definition of delayed diagnosis and treatment completion varied across countries.
INTERPRETATION: GBCI's Pillar 1 KPI correlates strongly with five-year survival rate and with the UHC index. Most ANCCA countries lacked national data on cancer staging, timely diagnosis, and treatment completion KPIs. While institutional-level data were available in some countries, they may not represent the nationwide status. Strengthening cancer surveillance is crucial for effective breast cancer control. The GBCI Framework indicators warrant more detailed definitions for standardised data collection. Surrogate indicators which are measurable and manageable in country-specific settings, could be considered for monitoring GBCI indicators. Ensuring UHC and addressing health inequalities are essential to early diagnosis and treatment of breast cancer.
FUNDING: Funding for this research article's processing fee (APC) will be provided by the affiliated institution to support the open-access publication of this work. The funding body is not involved in the study design; collection, management, analysis and interpretation of data; or the decision to submit for publication. The funding body will be informed of any planned publications, and documentation provided.