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Purpose: When exact information regarding the treatment head and initial electron beam is available, the Monte Carlo (MC) approach can properly simulate any linear accelerator. However, manufacturers seldom offer information such as the incident electron beam's energy, radial intensity (spot size), or angular spread. This research aims to forecast these features and verify an MC-simulated linear accelerator model using measurements. Materials and Methods: The BEAMnrc code simulated a 6 MV photon beam from a Radixact™ Tomotherapy Linac. Percentage depth dose and beam profile calculations were conducted using DOSYXZnrc by various electron energies and spot sizes and compared to measurements using a Gamma index with two distinct criterion sets. Furthermore, the fine-tuned electron energy and spot size profiles were created to minimize any disparities using distinct angle spreads. Finally, the output factors (OFs) for various field sizes were compared. Results: The MC model's fine-tuned electron energy was determined to be 5.8 MeV, with 88.6% of the calculation points passing the 1%/1 mm γ test. A circular radial intensity of 1.4 mm best represented the 6 MV photon beam regarding spot size. Furthermore, a mean angular spread of 0.05 reduced the disparity in cross-field profile between computation and measurement. The most considerable disparities between the MC model OFs and observations were 1.5%. Conclusion: Using the BEAMnrc code, a reliable MC model of the Radixact™ Tomotherapy Linac can be created, as shown in this paper. This model can be used to compute dose distributions with confidence. Keywords: BEAMnrc, DOSXYZnrc, Monte Carlo, tomotherapy, Author(s): Danial Seifi Makrani [1,2]; Hassan Ali Nedaei (corresponding author) [1,2]; Ghazale Geraily [1,2]; Alireza Khorami-Moghaddam [3]; Nooshin Banaee [4]; Hussam Jassim [1,2,5] INTRODUCTION In the past few years, intensity-modulated [...]

Objectives: Stroke is a major cause of disability in adults, necessitating consistent patient-therapist interactions and diligent adherence to home-based rehabilitation programs to achieve substantial functional recovery. This study assessed audio-based telerehabilitation's (TR) preliminary effect and feasibility in promoting home-based upper extremity exercises among stroke survivors. Methods: A 4-week parallel two-arm pilot study design was employed. Fourteen stroke survivors (seven each in the experimental and control groups) were recruited. Individuals in the control group received standard care consisting of visits to physiotherapy outpatient clinics, while the intervention group received standard care in addition to audio-based TR. The independent t-test and chi-square test were used to analyze differences in the clinical and sociodemographic data. The independent t-test was used to measure the treatment effect on the upper limb motor function (Fugl-Meyer upper extremity [FMA-UE] and Wolf motor function test [WMFT]), quality of life (QOL) (the World Health Organization (WHO) QOL brief, [WHOQOL-BREF]), and activities of daily living (Barthel index [BI]). Results: The overall Mean±SD age of the participants is 50±8.2 years. The FMA-UE and WMFT scores changed from 17.57 to 25.86 (P=0.02) and 28.14 to 43.71 (P=0.03). No significant improvements in physical health, psychological, and social relationships domains of WHOQOL-BREF were recorded after the intervention. However, the environmental domain showed significant improvement (P=0.001). Scores of BI did not change significantly (P=0.49). Discussion: The findings of this study provided preliminary evidence to support the feasibility and benefits of audio-based TR in promoting functional regain after the stroke. However, further studies with a robust design are needed to validate the reported effectiveness.

Abstract Background: The learning management system (LMSs) are online platforms that are used to conduct and support teaching and training at various institutions worldwide. Therefore, this study aimed to assess the perception towards the use of Moodle and Google classrooms LMS tools in the training among the National Health Emergency Operation Center (NHEOC) staff and compare their perceptions. Methods: This was a cross-sectional study with a post-test design conducted at NHEOC in Saudi Arabia in 2023. A training program regarding crises and disaster situations was delivered via Moodle and Google classrooms. At the end of each session, participants were invited to fill a questionnaire regarding their perception towards these tools. Results: A total of 72 and 65 individuals responded to the questionnaire after the end of Moodle class and Google classrooms, respectively. There were no statistically significant differences in the mean perception scores between Moodle and Google classrooms by; the easy access to the browser (4.18 ± 1.24 versus 4.14 ± 1.09, p-value = 0.692), the easy access to the App (4.02 ± 1.31 versus 4.11 ± 1.08 , p-value = 0.658), the ease of browsing the educational content (4.17 ± 1.13 versus 4.14 ± 1.06, p-value = 0.872), and the ease of dealing with the system functions (4.08 ± 1.14 versus 4.09 ± 1.16, p-value = 0.889). Conclusion: Participants reported similar perception towards the use of Moodle and Google classrooms in training programs. Meanwhile, majority reported that they preferred Moodle to Google classrooms. [SJEMed 2024; 5(2.000): 095-100]

Abstract Background: All the existing frameworks of Health-Emergency Disaster Risk Management have put great emphasis on the use of educational strategies to be used as a mean of disaster risk reduction (DRR). Thus, this study was conducted to formulate experts' consensus on DRR educational strategies for Middle East/North Africa (MENA) countries. Methods: A Delphi study on expert's opinion for DRR educational strategies was carried out through surveys in two consecutive rounds through convenient sampling technique. Results: A total of 60 responses were included in this study. Most of the participants were Saudi nationals, physicians (36.7% vs. 33.3% in round 1 and round 2, respectively), and males (73.3%) with experience in disaster management (56.7%) of 5-10 years (60% vs. 53.3% in round 1 and round 2, respectively). Around 80% participants suggested that graduate health professional education should be through problem based learning (PBL) approach (36.7%) (P-value = 0.007). Universal Design for Learning (UDL) framework implementation required provision of multiple means of engagement as priority (P-value = 0.007). Best learning situation category was institution based (60%) with best approach for DRR learning as planned scheduled learning (P-value = 0.000). It was found that best learning situations were lectures and small group sessions (73.3% each) (P-value = 0.165) that were delivered through learning management system (90%) (P-value = 0.103), while the major stakeholders that should be involved in national DRR educational planning were Ministry of Health (90%) (P-value = 0.881). Conclusion: Experts have consensus opinion on DRR Educational strategies in MENA countries. [SJEMed 2024; 5(2.000): 064-072]

Abstract Background Several computational and mathematical models of protein synthesis have been explored to accomplish the quantitative analysis of protein synthesis components and polysome structure. The effect of gene sequence (coding and non-coding region) in protein synthesis, mutation in gene sequence, and functional model of ribosome needs to be explored to investigate the relationship among protein synthesis components further. Ribosomal computing is implemented by imitating the functional property of protein synthesis. Result In the proposed work, a general framework of ribosomal computing is demonstrated by developing a computational model to present the relationship between biological details of protein synthesis and computing principles. Here, mathematical abstractions are chosen carefully without probing into intricate chemical details of the micro-operations of protein synthesis for ease of understanding. This model demonstrates the cause and effect of ribosome stalling during protein synthesis and the relationship between functional protein and gene sequence. Moreover, it also reveals the computing nature of ribosome molecules and other protein synthesis components. The effect of gene mutation on protein synthesis is also explored in this model. Conclusion The computational model for ribosomal computing is implemented in this work. The proposed model demonstrates the relationship among gene sequences and protein synthesis components. This model also helps to implement a simulation environment (a simulator) for generating protein chains from gene sequences and can spot the problem during protein synthesis. Thus, this simulator can identify a disease that can happen due to a protein synthesis problem and suggest precautions for it.

Construction projects are prone to accidents and injuries, necessitating a focus on implementing safety programs. However, the implementation of such programs is influenced by various factors. Developing countries often have poor safety performance in their building sectors, with limited research in this area. This study aimed to identify essential safety program activities (SPAs) specific to the building sector. Through a literature review and survey, 25 SPAs were identified and validated via a pilot survey involving building sector experts. A questionnaire survey was conducted with 105 participants from the construction industry and academia. They were then categorized into four interconnected measurements using Exploratory Factor Analysis (EFA): Safety Program Management and Development (SPMD), Safety Culture Development (SCD), Safety Risk and Hazard Management (SRHM), and Safety Leadership, Responsibility, and Commitment (SLRC). The impact of safety implementation (SI) on overall project success (OPS) was analyzed using Partial Least Square- Structural Equation Modelling (PLS-SEM). Subsequently, Synthetic Fuzzy Evaluation (SFE) was employed to determine the criticality and importance of each SPA grouping for construction projects. The PLS-SEM analysis indicates that SI has a moderate impact on OPS, with an R2 value of 45.4%. Moreover, the findings of the SFE highlight that the SLRC group is the most significant in enhancing the safety implementation of the construction industry.

This study examines stress biomarkers over the process of teaching and their associations with demographics, emotions, and mental health of 56 English as Foreign Language teachers. Participating teachers were invited to complete a questionnaire packet and provide saliva samples over three-time points (i.e., before, during, and end of teaching). Afterward, the saliva samples were assayed for cortisol and [alpha]-amylase as stress biomarkers. The results showed a significant change in the concentrations of cortisol and [alpha]-amylase over the teaching process. In addition, being female, younger, more educated, and having more teaching experience were significantly associated with a higher level of [alpha]-amylase, particularly before and during class time, thereby reflecting a greater level of stress. However, emotions and general mental health were not significantly associated with cortisol and [alpha]-amylase over time. The findings highlighted the changes of biomarkers over the process of teaching and their relationships with other variables.

This study investigated fluoride contamination in groundwater and associated health risks in the Badin district of Pakistan. Fifty-seven groundwater samples were analyzed for fluoride, turbidity, iron, and total dissolved solids (TDS). Pollution indices and health risk models were employed to assess contamination levels and potential health impacts. Results showed that 47 % of samples exceeded the WHO fluoride limit of 1.5 mg/L, with a mean concentration of 1.92 mg/L. Spatial analysis revealed high contamination in northern and southern areas. Health risk assessments indicated that children, particularly females, faced the highest risk of fluorosis. TDS, turbidity, and iron levels also exceeded WHO limits in significant portions of the samples. This investigation uniquely combines multiple pollution indicators, spatial analysis, and age-specific health risk assessments, presenting vibrant insights for targeted interventions, policy development, and resource allocation to address this critical public health issue in fluoride-endemic regions.

Purpose: When exact information regarding the treatment head and initial electron beam is available, the Monte Carlo (MC) approach can properly simulate any linear accelerator. However, manufacturers seldom offer information such as the incident electron beam’s energy, radial intensity (spot size), or angular spread. This research aims to forecast these features and verify an MC-simulated linear accelerator model using measurements. Materials and Methods: The BEAMnrc code simulated a 6 MV photon beam from a Radixact™ Tomotherapy Linac. Percentage depth dose and beam profile calculations were conducted using DOSYXZnrc by various electron energies and spot sizes and compared to measurements using a Gamma index with two distinct criterion sets. Furthermore, the fine-tuned electron energy and spot size profiles were created to minimize any disparities using distinct angle spreads. Finally, the output factors (OFs) for various field sizes were compared. Results: The MC model’s fine-tuned electron energy was determined to be 5.8 MeV, with 88.6% of the calculation points passing the 1%/1 mm γ test. A circular radial intensity of 1.4 mm best represented the 6 MV photon beam regarding spot size. Furthermore, a mean angular spread of 0.05 reduced the disparity in cross-field profile between computation and measurement. The most considerable disparities between the MC model OFs and observations were 1.5%. Conclusion: Using the BEAMnrc code, a reliable MC model of the Radixact™ Tomotherapy Linac can be created, as shown in this paper. This model can be used to compute dose distributions with confidence.

Abstract Nuclear receptors (NRs) function as crucial transcription factors in orchestrating essential functions within the realms of development, host defense, and homeostasis of body. NRs have garnered increased attention due to their potential as therapeutic targets, with drugs directed at NRs demonstrating significant efficacy in impeding chronic disease progression. Consequently, these pharmacological agents hold promise for the treatment and management of various diseases. Accumulating evidence emphasizes the regulatory role of exosome-derived microRNAs (miRNAs) in chronic inflammation, disease progression, and therapy resistance, primarily by modulating transcription factors, particularly NRs. By exploiting inflammatory pathways such as protein kinase B (Akt)/mammalian target of rapamycin (mTOR), nuclear factor kappa-B (NF-κB), signal transducer and activator of transcription 3 (STAT3), and Wnt/β-catenin signaling, exosomes and NRs play a pivotal role in the panorama of development, physiology, and pathology. The internalization of exosomes modulates NRs and initiates diverse autocrine or paracrine signaling cascades, influencing various processes in recipient cells such as survival, proliferation, differentiation, metabolism, and cellular defense mechanisms. This comprehensive review meticulously examines the involvement of exosome-mediated NR regulation in the pathogenesis of chronic ailments, including atherosclerosis, cancer, diabetes, liver diseases, and respiratory conditions. Additionally, it elucidates the molecular intricacies of exosome-mediated communication between host and recipient cells via NRs, leading to immunomodulation. Furthermore, it outlines the implications of exosome-modulated NR pathways in the prophylaxis of chronic inflammation, delineates current limitations, and provides insights into future perspectives. This review also presents existing evidence on the role of exosomes and their components in the emergence of therapeutic resistance.