Nanomedicine facilitated cell signaling blockade: difficulties and strategies to overcome glioblastoma.

Glioblastoma (GBM) is a highly aggressive and lethal type of brain tumor with complex and diverse molecular signaling pathways involved that are in its development and progression. Despite numerous attempts to develop effective treatments, the survival rate remains low. Therefore, understanding the molecular mechanisms of these pathways can aid in the development of targeted therapies for the treatment of glioblastoma. Nanomedicines have shown potential in targeting and blocking signaling pathways involved in glioblastoma. Nanomedicines can be engineered to specifically target tumor sites, bypass the blood-brain barrier (BBB), and release drugs over an extended period. However, current nanomedicine strategies also face limitations, including poor stability, toxicity, and low therapeutic efficacy. Therefore, novel and advanced nanomedicine-based strategies must be developed for enhanced drug delivery. In this review, we highlight risk factors and chemotherapeutics for the treatment of glioblastoma. Further, we discuss different nanoformulations fabricated using synthetic and natural materials for treatment and diagnosis to selectively target signaling pathways involved in GBM. Furthermore, we discuss current clinical strategies and the role of artificial intelligence in the field of nanomedicine for targeting GBM.

Automated Gait Analysis Based on a Marker-Free Pose Estimation Model.

Gait analysis is an essential tool for detecting biomechanical irregularities, designing personalized rehabilitation plans, and enhancing athletic performance. Currently, gait assessment depends on either visual observation, which lacks consistency between raters and requires clinical expertise, or instrumented evaluation, which is costly, invasive, time-consuming, and requires specialized equipment and trained personnel. Markerless gait analysis using 2D pose estimation techniques has emerged as a potential solution, but it still requires significant computational resources and human involvement, making it challenging to use. This research proposes an automated method for temporal gait analysis that employs the MediaPipe Pose, a low-computational-resource pose estimation model. The study validated this approach against the Vicon motion capture system to evaluate its reliability. The findings reveal that this approach demonstrates good (ICC(2,1) > 0.75) to excellent (ICC(2,1) > 0.90) agreement in all temporal gait parameters except for double support time (right leg switched to left leg) and swing time (right), which only exhibit a moderate (ICC(2,1) > 0.50) agreement. Additionally, this approach produces temporal gait parameters with low mean absolute error. It will be useful in monitoring changes in gait and evaluating the effectiveness of interventions such as rehabilitation or training programs in the community.

Modelling Analysis on Dietary Patterns and Oral Health Status among Adolescents.

Adolescence is a crucial stage between childhood and adulthood during which an individual learns new behaviours and practices including dietary patterns. This study aimed to examine the diet and oral health status among adolescents, and employed a structured questionnaire with three sections, namely, demographic, Adolescents' Food Habits Checklist (AFHC) and the Kayser-Jones Brief Oral Health Status Examination (BOHSE). The AFHC was formulated consisting of 23 items to collect information about dietary patterns with respect to food purchase, preparation and consumption habits. Meanwhile, the BOHSE contained nine items to evaluate the oral conditions of adolescents. The relationship between dietary pattern and oral health in adolescents was investigated. A total of 160 adolescents were randomly selected in this study. The data analysis was presented in the form of tables. This study adhered to the STROBE checklist's Guidelines for Systematic Reporting of Examination. According to the findings, food consumption dietary patterns among adolescents had the highest mean score (4.475). This demonstrates that adolescents practiced healthy food consumption. A significant positive correlation was found between food purchase, food preparation, food consumption and dietary patterns. Moreover, females had a slightly higher mean score than males, showing that females have a healthier diet status than males. This study can serve as points of reflection and recommendations on dietary patterns and oral health status.

Dataset of driving behaviours in Selangor, Malaysia.

Road traffic accidents have been recognised as a leading cause of death, and one of the prominent public health problems. The human factor, which is the driving behaviour in particular, is said to be the main cause. In line with this, the objective of this research is to present a data article on the response of driving behaviours among drivers. Driving behaviours have been classified into five dimensions, which are speeding, improper overtaking, mobile phone use while driving, tail-gating and disobeying traffic lights. A quantitative study was conducted with a sample size of 160 drivers consisting of residents in a suburban of Selangor, Malaysia. A stratified random sampling method was adopted to identify the respondents. Data analysis was presented in the form of descriptive statistics and tables. The findings show that the majority of respondents agreed that they have driving behaviours that involve improper overtaking, tail-gating and disobeying traffic lights.

Measuring Availability, Prices and Affordability of Ischaemic Heart Disease Medicines in Bangi, Selangor, Malaysia.

BACKGROUND: This study is aimed to analyse the availability, prices and affordability of medicines for ischaemic heart disease (IHD) in Bangi, Selangor, Malaysia. METHODS: A quantitative research was carried out using the methodology developed by the World Health Organization and Health Action International (WHO/HAI). The prices were compared with international reference prices (IRPs) to obtain a median price ratio. The daily wage of the lowest paid unskilled government worker was used as the standard of the affordability for the medicines. In this study, ten medicines of the IHD were included. The data were collected from 10 private medicine outlets for both originator brand (OB) and lowest-priced generic brand (LPG) in Bangi, Selangor. RESULTS: From the results, the mean availability of OB and LPG were 30% and 42%, respectively. Final patient prices for LPG and OB were about 10.77 and 24.09 times their IRPs, respectively. Medicines that consumes more than a day's wage are considered unaffordable. Almost half of the IHD medications cost more than one day's wage. For example, the lowest paid unskilled government worker would need 1.4 days' wage for captopril, while 1.2 days' wage to purchase enalapril for LPG. Meanwhile, for OB, the costs rise to 3.4 days' wage for amlodipine and 3.3 days' wage for simvastatin. CONCLUSION: The findings of this study emphasise the need of focusing and financing, particularly in the private sector, on making chronic disease medicines accessible. This requires multi-faceted interventions, as well as the review of policies and regulations.

Optimal estimated process parameters side sensitive group runs chart based on expected average run length.

The side sensitive group runs (SSGR) chart is better than both the Shewhart and synthetic charts in detecting small and moderate process mean shifts. In practical circumstances, the process parameters are seldom known, so it is necessary to estimate them from in-control Phase-I samples. Research has discovered that a large number of in-control Phase-I samples are needed for the SSGR chart with estimated process parameters to behave similarly to a chart with known process parameters. The common metric to evaluate the performance of the control chart is average run length (ARL). An assumption for the computation of the ARL is that the shift size is assumed to be known. In reality however, the practitioners may not know the following shift size in advance. In light of this, the expected average run length (EARL) will be considered to measure the performance of the SSGR chart. Moreover, the standard deviation of the ARL (SDARL) will be studied, which is used to quantify the between-practitioner variability in the SSGR chart with estimated process parameters. This paper proposes the optimal design of the estimated process parameters SSGR chart based on the EARL criterion. The application of the optimal SSGR chart with estimated process parameters is demonstrated with actual data taken from a manufacturing company.