For decades, cancer has remained a persistent health challenge; this project represents a significant stride towards refining treatment approaches and prognostic insights. Proton beam therapy, a radiation therapy modality employing high-energy protons to target various malignancies while minimizing damage to adjacent healthy tissue, holds immense promise. This study analyzes the relationship between delivered radiation doses and patient outcomes, using various approximation functions and graphical representations for comparison. Statistical analysis is performed through the Monte Carlo method based on repeated sampling to estimate the variables of interest in this analysis, namely, the survival rates, financial implications, and medical effectiveness of proton beam therapy. To this end, open-source data from research centers that publish patient outcomes were utilized. The second study considered the estimation of pay gaps that can have long-lasting effects, leading to differences in retirement savings, wealth accumulation, and overall financial security. After finding a representative sample containing the relevant variables that contribute to pay gaps, such as gender, race, experience, education, and job role, MC modeling is used to simulate a range of possible pay gap estimates. Based on the Monte Carlo results, a sensitivity analysis is performed to identify which variables have the most significant impact on pay gaps.

Resistance to chemotherapy is a problem of major social and economic importance, when looking at factors like the decrease in life expectancy, the associated therapeutic costs, and a significant number of cancers that resist current chemotherapy. The development of chemotherapeutics for all theoretically possible tumor variants is an approach that requires unreasonable resources. We propose a theoretical model that serves the purpose of overcoming resistance to chemotherapeutic agents used in cancer therapy. The model describes a gene delivery system based on liposomes, which are optically guided to the tumor’s location. The main aim of the gene delivery system is inhibiting the activity of enzymes involved in drug metabolism, hence offering the opportunity to use inexpensive chemotherapeutics that are already on the market. This model will reduce the costs of chemotherapy and will assure a positive outcome for patients.

The immune system is a vital defense network within the body, where lymph and lymph nodes play pivotal roles. Lymph is a transparent fluid containing white blood cells, specifically lymphocytes, which circulate through the lymphatic system, rapidly multiplying to fight viruses and bacteria. Lymph nodes function as filters, capturing and eliminating infections and abnormal cells found in the lymphatic fluid prior to its reentry into the circulatory system. A thorough meta-analysis of research publications in the topic is conducted utilizing Bibliometrix to comprehensively assess the current literature. The paper is centered on understanding the intricate relationship between interferons, dendritic cells, and macrophages in the lymphatic system during hepatitis virus infection. A nonlinear model for the development of the virus is used, together with the initial conditions, for a much better understanding of a hepatitis-C infection. The associated Cauchy problem is numerically solved and graphs are depicted. The interpretation of the figures explains the dynamics of interferons, dendritic cells, and macrophages as well as their interaction with other factors. By adopting an interdisciplinary approach, this study offers fresh perspectives and uncovers new research areas to better comprehend and battle hepatitis virus infections.

This paper focuses on a statistical analysis performed on data sets from diabetes prevention research, starting with aspects on people's health and their correlation with diabetes, continuing with a proposal to optimize a continuous glucometer. Through examination of various health factors such as age, gender, BMI, hypertension, heart disease, and smoking history, alongside key biomarkers like blood glucose and hemoglobin A1c, the study uncovers correlations crucial for early detection and prevention strategies. The analysis utilizes hypothesis testing, correlation, regression, and clustering methods to identify patterns and relationships that aid in the classification and diagnosis of diabetes. These insights are essential for developing effective management strategies and increasing awareness of diabetes risk factors. Additionally, the paper explores a simplified and cost-effective model for a Continuous Glucose Monitor (CGM) featuring LEDs for immediate visual feedback on glucose levels. This proposed design addresses the financial barriers associated with current high-end CGMs by incorporating economical materials such as stainless steel or graphite for electrodes and a replaceable lithium battery. The simplified CGM aims to improve accessibility while maintaining functionality for real-time glucose monitoring. By combining statistical evidence with innovative design considerations, this study emphasizes the importance of affordable and reliable CGM technology in enhancing diabetes management and prevention.