Patient's need for endodontic treatment in a short period is on the rise nowadays. Technological developments in instruments and materials are allowing single-visit endodontic treatment to be performed. The success of an endodontic treatment is also influenced by the restoration, in consideration of the remaining tooth structure. This becomes a challenge for the clinician if the cavities are large or if minimal tooth structure remains, so it needs a
minimally invasive restoration like morphology-driven preparation technique. This case report aims to describe the single-visit endodontic treatment and minimally invasive indirect restoration of the mandibular first molar. A 13-year-old girl came to the Dental Hospital of Hasanuddin University with complaints of cavities in the mandibular left posterior tooth and pain for one month. The patient had taken analgesic medication but was afforded no relief. Intraoral examination showed tooth #36 with extensive cavities reaching the proximal area, a positive thermal test, and no pain to percussion. The case diagnosis was asymptomatic irreversible pulpitis. The treatment plan was a single-visit endodontic treatment and minimally invasive indirect restoration.

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.

Voltage-gated sodium channels (VGSCs) play pivotal roles in cancer progression and have emerged as promising therapeutic targets and biomarkers. VGSCs comprise multiple subtypes with distinct tissue distributions, influencing tumour characteristics in different ways. Among these, the tetrodotoxin-sensitive α-subunits and the β1 subunit, commonly found in breast cancer, have been implicated in metastasis and tumour aggressiveness. The NaV1.5 channel and its neonatal variant (nNaV1.5) are overexpressed in aggressive cancers such as breast, prostate, colorectal, and lung cancers, thereby enhancing their invasive capacity. nNaV1.5 is particularly significant due to its tumour-specific expression and strong association with poor prognosis, especially in breast cancer, where it regulates cell proliferation, invasion, and tumour microenvironment remodelling. This review highlights nNaV1.5 as a critical ion channel that drives metastasis through ion regulation, extracellular acidification, and cytoskeletal remodelling. We further evaluate current therapeutic strategies, including siRNA, monoclonal antibodies, and small-molecule inhibitors, while addressing translational challenges such as tumour heterogeneity, drug delivery limitations, and off-target cardiotoxicity due to its similarity with the adult isoform. In addition, we explore the potential of nNaV1.5 as a biomarker subject to epigenetic regulations by factors including RE1-silencing transcription factor (REST) and histone deacetylase 2 (HDAC2), which may facilitate patient stratification and treatment optimization. By integrating mechanistic insights, therapeutic opportunities, and translational challenges, this review goes beyond descriptive summaries to provide a framework for advancing nNaV1.5 research from preclinical studies toward clinical application in cancer therapy.

Introduction: Sleep quality has become a public health concern due to serious impacts on individual’s health outcomes. Thus, this cross-sectional study aimed to determine the sleep quality and its associated factors among adults living in the province of Terengganu, Malaysia. Materials and Methods: Socio-demographic information was self-reported whilst anthropometric measurements were measured by trained researchers. Sleep quality was assessed using the validated Pittsburgh Sleep Quality Index (PSQI) whilst eating behavior was measured using the Dutch Eating Behavior Questionnaire (DEBQ). Descriptive statistics and multivariable linear regression models were employed using IBM SPSS version 25.0. Results: A total of 580 participants were enrolled (mean age = 29.1 ± 10.0 years; 51.2% female), of which 74.7% (n = 433) had poor sleep quality (PSQI global score > 5) with a total sleep duration per night of 6.2 ± 1.6 hours. Gender (p-value=0.044), educational level (p-value=0.001), emotional level (p-value=0.005) and external eating (p-value=0.026) were significantly associated with poorer sleep quality. Conclusion: This study underscored the high prevalence of poor sleep quality among adults living in Terengganu, Malaysia. The findings could serve as a basis for developing sleep education strategies that are tailored to improve sleep quality among adults.

Cost-Effectiveness of Mobile Application Use in Managing Type 2 Diabetes Mellitus: A Systematic Review Introduction Type 2 diabetes mellitus (T2DM) is a debilitating condition that imposes a significant economic burden on its management. This study aims to systematically review the published evidence on the cost-effectiveness of mobile health (mHealth) application interventions for T2DM. Methods A search strategy was conducted using electronic bibliographic databases, including PubMed, Web of Science and Scopus for published studies. The inclusion criteria included original articles that reporting cost-effectiveness evaluation studies on mHealth application interventions directed at patients diagnosed or at risk of T2DM, English-language articles and published in the year 2016 to 2020. Results A total of 6 eligible studies were selected. The cost savings per person for treating T2DM ranged from USD 1,346 to USD 3,781 per year. The major contributor to cost savings was reduced complication management resulting from good glycaemic control. The direct impacts of the intervention include reduced hospitalisation and fewer unplanned clinic visits, while diabetes- related mortality was indirectly reduced usingmHealth. Conclusions The mHealth intervention was cost-effective in managing patients with T2DM. Implementation can be extended to other disease management areas to not only reduce total healthcare expenditure but also improve patients’ quality of life.

Objectives: Hypertension, commonly known as high blood pressure, is a prevalent and serious condition affecting a significant portion of the adult population globally. It is a chronic medical issue that, if left unaddressed, can lead to severe health complications, including kidney problems, heart disease, and stroke. This study aims to develop a feature selection model using the XGBoost algorithm to identify specific single nucleotide polymorphisms (SNPs) as biomarkers for detecting hypertension risk. Methods: We propose using the high dimensionality of genetic variations (i.e., SNPs) to build a classifier model for prediction. In this study, SNPs were used as markers for hypertension in patients. We utilized the OpenSNP dataset, which includes 19,697 SNPs from 2,052 samples. Extreme gradient boosting (XGBoost) is an ensemble machine learning method employed here for feature selection, which incrementally adjusts weights in a series of steps. Results: The experimental results identified 292 SNPs that exhibited high performance, with an F1-score of 98.55%, precision of 98.73%, recall of 98.38%, and overall accuracy of 98%. This study provides compelling evidence that the XGBoost feature selection method outperforms other representative feature selection methods, such as genetic algorithms, analysis of variance, chi-square, and principal component analysis, in predicting hypertension risk, demonstrating its effectiveness. Conclusions We developed a model for predicting hypertension using the SNPs dataset. The high dimensionality of SNP data was effectively managed to identify significant features as biomarkers using the XGBoost feature selection method. The results indicate high performance in predicting the risk of hypertension.