Despite publishing and securing research grants being obligatory in research universities, the literature on the factors influencing academic productivity is relatively scarce. Thus, in this study, we aimed to determine the personal and behavioural-related factors that influence the culture of publishing and securing research grants among academicians with lower research-related performance. This cross-sectional study was conducted among 49 academic staff members of Universiti Kebangsaan Malaysia (UKM). A self-administered questionnaire consisting of personal, attitude and behavioural (barriers, perceived stress scale, work extrinsic and intrinsic motivation scale, psychological well-being scale, and basic needs satisfaction scale) questions were distributed during a workshop and online. Simple linear regression (SLR) analyses were performed for each variable, followed by multiple linear regression (MLR) to identify the associated factors of research output. After adjusting for covariates, having a doctoral degree (β=0.396, 95% CI=0.221-2.146, p<0.05) and integrated regulation (β=0.574, 95% CI=0.036-3.612, p<0.05) were found to be associated with research grant acquisition (R2=0.273). Moreover, increasing age (β=0.426, 95% CI=0.088-0.397, p<0.05), living alone (β=0.331, 95% CI=0.944-6.626, p<0.05), having a doctoral degree (β=0.248, 95% CI=0.174-6.747, p<0.05), environmental mastery (β=0.318, 95% CI=0.013-0.347, p<0.05), self-acceptance (β=0.284, 95% CI=0.010-0.242, p<0.05), satisfaction incompetence (β=0.273, 95% CI=0.001-0.200, p<0.05) and relatedness (β=0.280, 95% CI=0.001-0.116, p<0.05) were found to be the factors that influence the publications produced among participants (R2 =0.423). The findings of this study could be used by management to formulate effective strategies to increase the productivity of academics in their research-related performance.

Objective: Biportal endoscopic spine surgery (BESS) has emerged as a minimally invasive alternative for lumbar decompression, offering improved visualization with reduced tissue disruption. Therefore, this study aims to identify key anatomical considerations, particularly interlaminar-disc mismatch and the “banana-shaped” curvature of the lamina, and to examine their impact on portal trajectory, alignment of the surgical corridor, and preservation of spinal structures. Methods: A retrospective, video-based analysis was conducted on 23 BESS lumbar decompression cases performed between January and March 2024. Surgical levels included L3–4 (n=3), L4–5 (n=17), and L5–S1 (n=3). Intraoperative anatomical landmarks were assessed independently by 2 spine surgeons. Interobserver agreement was evaluated using Cohen kappa, based on the identification of 3 landmarks per case in 23 cases, calculated with unweighted kappa. Visualization quality was scored on a 3-point scale. Cranial and caudal interlaminar-disc mismatches were measured and averaged. Results: Interlaminar-disc mismatch was identified in 93% of cases, with cranial and caudal mismatches ranging from 5.5±1.02 mm to 8±1.2 mm. Laminar curvature was consistently observed at L4–5 and L5–S1, which required a medial-caudal portal. In addition, the superior articular process (SAP) served as a reliable fluoroscopic and endoscopic landmark, facilitating safe access to the intervertebral disc. A limited medial facetectomy provided adequate operating space. The findings also demonstrated high interobserver reliability for anatomical identification (κ=0.84), and the use of layer-specific flavectomy preserved the inner layer of the ligamentum flavum. Conclusion Successful BESS requires integrating detailed anatomical understanding with intraoperative adaptability. Recognizing interlaminar-disc mismatch, laminar curvature, and SAP orientation enables optimal portal placement and targeted decompression. These principles are essential for achieving reproducible and safe outcomes in BESS.

Objective: This study aims to describe histological manifestations and characterise the CDV strain in the tiger to determine its molecular epidemiology and postulate viral pathogenicity. Methods: Histopathology characterisation of the infected tissues were performed through haematoxylin and eosin and immunohistochemistry staining, respectively. We conducted virus isolation and titration in Chinese hamster ovarian expressing the dog signalling lymphocytic activation molecule (CHO-SLAM) cells. Reverse transcription polymerase chain reaction was performed to confirm the presence of CDV RNA, nucleotide and amino acid sequence analyses for comprehensive characterisation of the CDV strain. Results: Notable histopathological changes were observed primarily in the brain, lung, liver, kidney, spleen, and stomach, with viral antigens localised in the lung, liver, kidney, and stomach tissues. CDV-induced cell cytopathic effects yielding 4.27 × 10 6 TCID 50 /mL were observed at 48 h post-inoculation in CHO-SLAM cells. Phylogenetic analysis suggested that the virus originated from the Asia-1 clade. Notably, 549H and 519I mutations in the hemagglutinin protein were observed, indicating adaptation to a non-canid wildlife species. Conclusions and Relevance: Overall, this study enhances our understanding of the molecular characterisation and evolutionary dynamics of the CDV strain present in the Malayan tiger and serves as a benchmark for developing effective preventative measures to protect Malayan tigers and mitigate their risk of extinction.

Despite effective vaccination strategies, measles remains a global public health challenge. The study explored individual and contextual factors associated with measles infection in Malaysia from 2018 to 2022, informing the development of targeted public health interventions. Methods: This cross-sectional study utilised data from the Ministry of Health, the Department of Statistics, and the Department of Environment Malaysia. Multilevel logistic regression analysis was employed to examine individual-level factors, including age, sex, ethnicity, nationality, contact history, travel history, and vaccination status. Concurrently, contextual factors were assessed, encompassing district-level determinants such as population density, median household income, urbanisation, the number of health and rural clinics, vaccination rates, fine particulate matter less than 2.5 μm (PM2.5) levels, relative humidity, and temperature, to determine their impact on measles infection risk. Results: Measles infection was significantly associated with various individual factors. These included age (adjusted odds ratio [aOR], 1.02; 95% confidence interval [CI], 1.02–1.03), ethnicity, non-Malaysian nationality (aOR, 34.53; 95% CI, 8.42– 141.51), prior contact with a measles case (aOR, 2.36; 95% CI, 2.07–2.69), travel history (aOR, 2.30; 95% CI, 1.13–4.70), and vaccination status (aOR, 0.76; 95% CI, 0.72–0.79). Among contextual factors, urbanisation (aOR, 1.56; 95% CI, 1.16– 2.10) and the number of clinics (aOR, 0.98; 95% CI, 0.97–0.99) were significant determinants. Conclusion: This multilevel logistic regression analysis illuminates the complexities of measles transmission, advocating public health interventions tailored to individual and contextual vulnerabilities. The findings highlight the need for a synergistic approach that combines vaccination campaigns, healthcare accessibility improvements, and socioeconomic interventions to effectively combat measles.

Objectives: This study aimed to optimize early coronary heart disease (CHD) prediction using a genetic algorithm (GA)-based convolutional neural network (CNN) feature engineering approach. We sought to overcome the limitations of traditional hyperparameter optimization techniques by leveraging a GA for superior predictive performance in CHD detection. Methods: Utilizing a GA for hyperparameter optimization, we navigated a complex combinatorial space to identify optimal configurations for a CNN model. We also employed information gain for feature selection optimization, transforming the CHD datasets into an image-like input for the CNN architecture. The efficacy of this method was benchmarked against traditional optimization strategies. Results: The advanced GA-based CNN model outperformed traditional methods, achieving a substantial increase in accuracy. The optimized model delivered a promising accuracy range, with a peak of 85% in hyperparameter optimization and 100% accuracy when integrated with machine learning algorithms, namely naïve Bayes, support vector machine, decision tree, logistic regression, and random forest, for both binary and multiclass CHD prediction tasks. Conclusions The integration of a GA into CNN feature engineering is a powerful technique for improving the accuracy of CHD predictions. This approach results in a high degree of predictive reliability and can significantly contribute to the field of AI-driven healthcare, with the possibility of clinical deployment for early CHD detection. Future work will focus on expanding the approach to encompass a wider set of CHD data and potential integration with wearable technology for continuous health monitoring.

Objective: This study aimed to evaluate the effects of combination of curcumin and piperine supplementation on Fasting Plasma Glucose (FPG), Homeostatic Model of Insulin Resistance (HOMA-IR), Body Mass Index (BMI) in patients with prediabetes and type 2 Diabetes Mellitus (T2DM). This review was done to identify potential herbal remedies that may help improve glycemic parameters, leading to better health outcomes in combination with current antidiabetic treatment. Methodology: This systematic review was based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). It was conducted in 2023 with sources and databases from MEDLINE, EBSCO-Host, ScienceDirect and ProQuest. This paper included randomized-controlled trials exploring the effects of the combination of curcumin and piperine on patients with prediabetes and T2DM. Systematic reviews, observational studies, case reports, case series, conference abstracts, book sections, commentaries/editorials, non-human studies and articles with unavailable full-text and written in non-English language, were excluded. The key terms for the literature search were “curcumin,” “piperine,” “prediabetes” and “Type 2 Diabetes Mellitus.” We use Cochrane Risk of Bias (RoB) 2 for quality assessment of the included studies and Review Manager (RevMan) 5.4 to do the meta-analysis. Results: A total of three studies were included in this systematic review. Two studies from Neta et al., and Cicero et al., showed no significant difference in HOMA-IR, BMI and FPG levels between the curcumin, piperine and placebo groups. One study from Panahi et al. demonstrated a significant difference in BMI levels between the curcumin and piperine and placebo groups (p <0.01). The meta-analysis showed that FPG levels, HOMA-IR and BMI improved among patients with diabetes given in curcumin and piperine with reported mean differences (MD) of = -7.61, 95% CI [-15.26, 0.03], p = 0.05, MD = -0.36, 95% CI [-0.77 to 0.05], p = 0.09, and MD = -0.41, 95% CI [-0.85 to 0.03], p = 0.07, respectively). Conclusions The supplementation of curcumin and piperine showed a numerical reduction in FPG, HOMA-IR and BMI, but were not statistically significant. Further research is needed as there is a paucity of studies included in the review.
Curcumin ; Prediabetic State ; Diabetes Mellitus, Type 2

Despite effective vaccination strategies, measles remains a global public health challenge. The study explored individual and contextual factors associated with measles infection in Malaysia from 2018 to 2022, informing the development of targeted public health interventions. Methods: This cross-sectional study utilised data from the Ministry of Health, the Department of Statistics, and the Department of Environment Malaysia. Multilevel logistic regression analysis was employed to examine individual-level factors, including age, sex, ethnicity, nationality, contact history, travel history, and vaccination status. Concurrently, contextual factors were assessed, encompassing district-level determinants such as population density, median household income, urbanisation, the number of health and rural clinics, vaccination rates, fine particulate matter less than 2.5 μm (PM2.5) levels, relative humidity, and temperature, to determine their impact on measles infection risk. Results: Measles infection was significantly associated with various individual factors. These included age (adjusted odds ratio [aOR], 1.02; 95% confidence interval [CI], 1.02–1.03), ethnicity, non-Malaysian nationality (aOR, 34.53; 95% CI, 8.42– 141.51), prior contact with a measles case (aOR, 2.36; 95% CI, 2.07–2.69), travel history (aOR, 2.30; 95% CI, 1.13–4.70), and vaccination status (aOR, 0.76; 95% CI, 0.72–0.79). Among contextual factors, urbanisation (aOR, 1.56; 95% CI, 1.16– 2.10) and the number of clinics (aOR, 0.98; 95% CI, 0.97–0.99) were significant determinants. Conclusion: This multilevel logistic regression analysis illuminates the complexities of measles transmission, advocating public health interventions tailored to individual and contextual vulnerabilities. The findings highlight the need for a synergistic approach that combines vaccination campaigns, healthcare accessibility improvements, and socioeconomic interventions to effectively combat measles.

Despite effective vaccination strategies, measles remains a global public health challenge. The study explored individual and contextual factors associated with measles infection in Malaysia from 2018 to 2022, informing the development of targeted public health interventions. Methods: This cross-sectional study utilised data from the Ministry of Health, the Department of Statistics, and the Department of Environment Malaysia. Multilevel logistic regression analysis was employed to examine individual-level factors, including age, sex, ethnicity, nationality, contact history, travel history, and vaccination status. Concurrently, contextual factors were assessed, encompassing district-level determinants such as population density, median household income, urbanisation, the number of health and rural clinics, vaccination rates, fine particulate matter less than 2.5 μm (PM2.5) levels, relative humidity, and temperature, to determine their impact on measles infection risk. Results: Measles infection was significantly associated with various individual factors. These included age (adjusted odds ratio [aOR], 1.02; 95% confidence interval [CI], 1.02–1.03), ethnicity, non-Malaysian nationality (aOR, 34.53; 95% CI, 8.42– 141.51), prior contact with a measles case (aOR, 2.36; 95% CI, 2.07–2.69), travel history (aOR, 2.30; 95% CI, 1.13–4.70), and vaccination status (aOR, 0.76; 95% CI, 0.72–0.79). Among contextual factors, urbanisation (aOR, 1.56; 95% CI, 1.16– 2.10) and the number of clinics (aOR, 0.98; 95% CI, 0.97–0.99) were significant determinants. Conclusion: This multilevel logistic regression analysis illuminates the complexities of measles transmission, advocating public health interventions tailored to individual and contextual vulnerabilities. The findings highlight the need for a synergistic approach that combines vaccination campaigns, healthcare accessibility improvements, and socioeconomic interventions to effectively combat measles.

Despite effective vaccination strategies, measles remains a global public health challenge. The study explored individual and contextual factors associated with measles infection in Malaysia from 2018 to 2022, informing the development of targeted public health interventions. Methods: This cross-sectional study utilised data from the Ministry of Health, the Department of Statistics, and the Department of Environment Malaysia. Multilevel logistic regression analysis was employed to examine individual-level factors, including age, sex, ethnicity, nationality, contact history, travel history, and vaccination status. Concurrently, contextual factors were assessed, encompassing district-level determinants such as population density, median household income, urbanisation, the number of health and rural clinics, vaccination rates, fine particulate matter less than 2.5 μm (PM2.5) levels, relative humidity, and temperature, to determine their impact on measles infection risk. Results: Measles infection was significantly associated with various individual factors. These included age (adjusted odds ratio [aOR], 1.02; 95% confidence interval [CI], 1.02–1.03), ethnicity, non-Malaysian nationality (aOR, 34.53; 95% CI, 8.42– 141.51), prior contact with a measles case (aOR, 2.36; 95% CI, 2.07–2.69), travel history (aOR, 2.30; 95% CI, 1.13–4.70), and vaccination status (aOR, 0.76; 95% CI, 0.72–0.79). Among contextual factors, urbanisation (aOR, 1.56; 95% CI, 1.16– 2.10) and the number of clinics (aOR, 0.98; 95% CI, 0.97–0.99) were significant determinants. Conclusion: This multilevel logistic regression analysis illuminates the complexities of measles transmission, advocating public health interventions tailored to individual and contextual vulnerabilities. The findings highlight the need for a synergistic approach that combines vaccination campaigns, healthcare accessibility improvements, and socioeconomic interventions to effectively combat measles.

Despite effective vaccination strategies, measles remains a global public health challenge. The study explored individual and contextual factors associated with measles infection in Malaysia from 2018 to 2022, informing the development of targeted public health interventions. Methods: This cross-sectional study utilised data from the Ministry of Health, the Department of Statistics, and the Department of Environment Malaysia. Multilevel logistic regression analysis was employed to examine individual-level factors, including age, sex, ethnicity, nationality, contact history, travel history, and vaccination status. Concurrently, contextual factors were assessed, encompassing district-level determinants such as population density, median household income, urbanisation, the number of health and rural clinics, vaccination rates, fine particulate matter less than 2.5 μm (PM2.5) levels, relative humidity, and temperature, to determine their impact on measles infection risk. Results: Measles infection was significantly associated with various individual factors. These included age (adjusted odds ratio [aOR], 1.02; 95% confidence interval [CI], 1.02–1.03), ethnicity, non-Malaysian nationality (aOR, 34.53; 95% CI, 8.42– 141.51), prior contact with a measles case (aOR, 2.36; 95% CI, 2.07–2.69), travel history (aOR, 2.30; 95% CI, 1.13–4.70), and vaccination status (aOR, 0.76; 95% CI, 0.72–0.79). Among contextual factors, urbanisation (aOR, 1.56; 95% CI, 1.16– 2.10) and the number of clinics (aOR, 0.98; 95% CI, 0.97–0.99) were significant determinants. Conclusion: This multilevel logistic regression analysis illuminates the complexities of measles transmission, advocating public health interventions tailored to individual and contextual vulnerabilities. The findings highlight the need for a synergistic approach that combines vaccination campaigns, healthcare accessibility improvements, and socioeconomic interventions to effectively combat measles.