A study on ODE-based model of risk breast cancer with body mass

Abdulkream Alharbi, Sana; Dehingia, Kaushik; Jahman Alqarni, Awatif; Alsulami, Mona; Al Qarni, AA; Das, Anusmita; Hinçal, Evren

doi:10.1080/27690911.2023.2259059

Cited by 4 publications

(1 citation statement)

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“…The authors created a modified immune-tumor-normal cell model, taking into account competitions of the Lotka-Volterra type between the cell populations and the chemotherapeutic medications 38 . In order to explore the impact of body mass, estrogen, and the immune system on the development of cancer cells, authors provide a mathematical model of fat, estrogen, and breast cancer 39 . After first exposing patients to chemotherapy and virotherapy alone, and then both at once, the authors examine the behaviors displayed by a modified mathematical model that depicts interactions between immune cells, uninfected tumor cells, infected tumor cells, and normal cells 40 .…”

Section: Introductionmentioning

confidence: 99%

Fractional order cancer model infection in human with CD8+ T cells and anti-PD-L1 therapy: simulations and control strategy

Nisar,

Kulachi,

Ahmad

et al. 2024

Sci Rep

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In order to comprehend the dynamics of disease propagation within a society, mathematical formulations are essential. The purpose of this work is to investigate the diagnosis and treatment of lung cancer in persons with weakened immune systems by introducing cytokines ($$ IL_{2} \& IL_{12}$$ I L 2 & I L 12 ) and anti-PD-L1 inhibitors. To find the stable position of a recently built system TCD$$IL_{2} IL_{12}$$ I L 2 I L 12 Z, a qualitative and quantitative analysis are taken under sensitive parameters. Reliable bounded findings are ensured by examining the generated system’s boundedness, positivity, uniqueness, and local stability analysis, which are the crucial characteristics of epidemic models. The positive solutions with linear growth are shown to be verified by the global derivative, and the rate of impact across every sub-compartment is determined using Lipschitz criteria. Using Lyapunov functions with first derivative, the system’s global stability is examined in order to evaluate the combined effects of cytokines and anti-PD-L1 inhibitors on people with weakened immune systems. Reliability is achieved by employing the Mittag-Leffler kernel in conjunction with a fractal-fractional operator because FFO provide continuous monitoring of lung cancer in multidimensional way. The symptomatic and asymptomatic effects of lung cancer sickness are investigated using simulations in order to validate the relationship between anti-PD-L1 inhibitors, cytokines, and the immune system. Also, identify the actual state of lung cancer control with early diagnosis and therapy by introducing cytokines and anti-PD-L1 inhibitors, which aid in the patients’ production of anti-cancer cells. Investigating the transmission of illness and creating control methods based on our validated results will both benefit from this kind of research.

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Section: Introductionmentioning

confidence: 99%