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When it hits close to home

Khoo SY

J Palliat Med, 2013 Jun;16(6):703.
PMID: 23614714 DOI: 10.1089/jpm.2012.0428
An Insight Into the Experiences of Malaysian Patients With Advanced Cancer and Their Preferences in End-of-Life Care: A Qualitative Study

Chung I, Khoo SY, Low LL

Am J Hosp Palliat Care, 2025 Jan;42(1):5-13.
PMID: 38394223 DOI: 10.1177/10499091241233599

BACKGROUND: Preferences of patients with advanced cancer are well studied in Western countries but less so in Asian communities where end-of-life discussions can be seen as taboo. This may lead to patients receiving care that is incongruent with their wishes as their disease progress. It is important for healthcare providers to have a better understanding of patients' experiences and preferences especially in a multicultural country like Malaysia with its diverse beliefs and values to facilitate better planning for future medical care.
OBJECTIVES: To explore the experiences and preferences of Malaysian patients with advanced cancer.
DESIGN: Qualitative study of semi-structured interviews with thematic analysis.
SETTING/SUBJECTS: Purposive sampling of 19 patients with Stage 4 cancer recruited from inpatient and outpatient settings in National Cancer Institute Malaysia.
RESULTS: Three major themes emerged in the exploration of patients' experiences and care preferences in facing advanced cancer namely: 1) Dealing with poor prognosis 2) Spirituality as a source of strength and 3) Enablers of advance care planning.
CONCLUSION: This study highlighted the preference for healthcare providers to be culturally sensitive during end-of-life care discussion and the need for improved spiritual care for Malaysian patients with advanced cancer. Further studies exploring the role of spiritual and cultural factors in advance care planning among Malaysians would be helpful in guiding these efforts.
Dynamic characterisation of Össur Flex-Run prosthetic feet for a more informed prescription

Noroozi S, Ong ZC, Khoo SY, Aslani N, Sewell P

Prosthet Orthot Int, 2019 Feb;43(1):62-70.
PMID: 30051756 DOI: 10.1177/0309364618789449

BACKGROUND:: The current method of prescribing composite running-specific energy-storing-and-returning feet is subjective and is based only on the amputee's static body weight/mass.
OBJECTIVES:: The aim was to investigate their dynamic characteristics and create a relationship between these dynamic data and the prescription of foot.
STUDY DESIGN:: Experimental Assessment.
METHODS:: This article presents the modal analysis results of the full range of Össur Flex-Run™ running feet that are commercially available (1LO-9LO) using experimental modal analysis technique under a constant mass at 53 kg and boundary condition.
RESULTS:: It was shown that both the undamped natural frequency and stiffness increase linearly from the lowest to the highest stiffness category of foot which allows for a more informed prescription of foot when tuning to a matched natural frequency. The low damping characteristics determined experimentally that ranged between 1.5% and 2.0% indicates that the feet require less input energy to maintain the steady-state cyclic motion before take-off from the ground. An analysis of the mode shapes also showed a unique design feature of these feet that is hypothesised to enhance their performance.
CONCLUSION:: A better understanding of dynamic characteristics of the feet can help tune the feet to the user's requirements in promoting a better gait performance.
CLINICAL RELEVANCE: The dynamic data determined from this study are needed to better inform the amputees in predicting the natural frequency of the foot prescribed. The amputees can intuitively tune the cyclic body rhythm during walking or running to match with the natural frequency. This could eventually promote a better gait performance.
Fulltext Real-time IoT-powered AI system for monitoring and forecasting of air pollution in industrial environment

Ramadan MNA, Ali MAH, Khoo SY, Alkhedher M, Alherbawi M

Ecotoxicol Environ Saf, 2024 Sep 15;283:116856.
PMID: 39151373 DOI: 10.1016/j.ecoenv.2024.116856

Air pollution in industrial environments, particularly in the chrome plating process, poses significant health risks to workers due to high concentrations of hazardous pollutants. Exposure to substances like hexavalent chromium, volatile organic compounds (VOCs), and particulate matter can lead to severe health issues, including respiratory problems and lung cancer. Continuous monitoring and timely intervention are crucial to mitigate these risks. Traditional air quality monitoring methods often lack real-time data analysis and predictive capabilities, limiting their effectiveness in addressing pollution hazards proactively. This paper introduces a real-time air pollution monitoring and forecasting system specifically designed for the chrome plating industry. The system, supported by Internet of Things (IoT) sensors and AI approaches, detects a wide range of air pollutants, including NH3, CO, NO2, CH4, CO2, SO2, O3, PM2.5, and PM10, and provides real-time data on pollutant concentration levels. Data collected by the sensors are processed using LSTM, Random Forest, and Linear Regression models to predict pollution levels. The LSTM model achieved a coefficient of variation (R²) of 99 % and a mean absolute percentage error (MAE) of 0.33 for temperature and humidity forecasting. For PM2.5, the Random Forest model outperformed others, achieving an R² of 84 % and an MAE of 10.11. The system activates factory exhaust fans to circulate air when high pollution levels are predicted to occur in the next hours, allowing for proactive measures to improve air quality before issues arise. This innovative approach demonstrates significant advancements in industrial environmental monitoring, enabling dynamic responses to pollution and improving air quality in industrial settings.
Adsorption and self-assembly in methyl ester sulfonate surfactants, their eutectic mixtures and the role of electrolyte

Xu H, Li P, Ma K, Welbourn RJL, Doutch J, Penfold J, et al.

J Colloid Interface Sci, 2018 Apr 15;516:456-465.
PMID: 29408135 DOI: 10.1016/j.jcis.2018.01.086

The α-methyl ester sulfonate, MES, anionic surfactants are a potentially important class of sustainable surfactants for a wide range of applications. The eutectic-like Kraft point minimum in the C16 and C18-MES mixtures is an important feature of that potential. Understanding their individual adsorption properties and the surface mixing of the eutectic mixtures are key to their wider exploitation. Neutron reflectivity has been used to investigate the adsorption at the air-water interface of the C16 and C18-MES surfactants and the eutectic mixture of C16 and C18-MES, in aqueous solution and in electrolyte. The micelle mixing of the eutectic mixture is investigated using small angle neutron scattering. The adsorption isotherms for C14 to C18-MES are found to scale with their critical micelle concentration value. The surface and micelle compositions of the C16 and C18-MES eutectic mixture differ from the eutectic composition; with compositions in the limit of high concentrations richer in C16-MES. The mixing properties are described by the pseudo phase approximation with a repulsive interaction between the two surfactants. The impact of the multivalent ions Al3+ on the adsorption at the air-water interface results in a transition from monolayer to multilayer adsorption.
Fulltext Resting-state electroencephalography (EEG) microstates of healthy individuals following mild sleep deprivation

Khoo SY, Lai WH, On SH, On YY, Adam BM, Law WC, et al.

Sci Rep, 2024 Jul 22;14(1):16820.
PMID: 39039219 DOI: 10.1038/s41598-024-67902-0

Mild sleep deprivation is widespread in many societies worldwide. Electroencephalography (EEG) microstate analysis provides information on spatial and temporal characteristics of resting brain network, serving as an indicator of neurophysiological activities at rest. This study seeks to investigate potential neural markers in EEG following mild sleep deprivation of a single night using EEG microstate analysis. Six-minute resting EEG was conducted on thirty healthy adults within 6 hours of waking in the morning and after at least 18 h of sleep deprivation. Translated and validated Malay language Karolinska Sleepiness Scale was used to assess the participants' degree of sleepiness. Microstate characteristics analysis was conducted on the final 24 subjects based on four standard microstate maps. Microstate C shows a significant increase in mean duration, coverage and occurrence, while microstate D has significantly higher occurrence after sleep deprivation. This study demonstrates notable changes in resting state EEG microstates following mild sleep deprivation. Present findings deepen our understanding of the brain's spatiotemporal dynamics under this condition and suggest the potential utility of neural markers in this domain as components of composite markers for sleep deprivation.