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包含功能性反应的高危型人乳头瘤病毒病毒体、基底细胞、淋巴细胞T细胞的宿主体内密度依赖性模型

In-host density-dependent model of high-risk HPV virions, basal cells, lymphocytes t-cells incorporating functional responses.

作者信息

Makena Elosy, Ngari Cyrus Gitonga, Kimani Patrick Mwangi, Kilonzi Jeremiah Savali

机构信息

Department of Mathematics and Statistics, University of Embu, 6-60100 Embu, Kenya.

Department of Pure and Applied Sciences, Kirinyaga University, 143-10300 Kerugoya, Kenya.

出版信息

Heliyon. 2024 Jul 25;10(16):e35038. doi: 10.1016/j.heliyon.2024.e35038. eCollection 2024 Aug 30.

Abstract

Cervical cancer is one of the most common types of cancer and it is caused mostly by high-risk Human Papillomavirus (HPV) and continues to spread at an alarming rate. While HPV impacts have been investigated before, there are currently only a scanty number of mathematical models that account for HPV's dynamic role in cervical cancer. The objectives were to develop an in-host density-dependent deterministic model for the dynamics implications of basal cells, virions, and lymphocytes incorporating immunity and functional responses. Analyze the model using techniques of epidemiological models such as basic reproduction number and simulate the model using Matlab ODE solver. Six compartments are considered in the model that is; Susceptible cells (S), Infected cells (I), Precancerous cells (P), Cancerous cells (C), Virions (V), and Lymphocytes (L). Next generation matrix (NGM), survival function, and characteristic polynomial method were used to determine the basic reproduction number denoted as was obtained using three methods because NGM has some weaknesses hence the need for the other two methods. The findings from this research indicated that Disease-Free Equilibrium point is locally asymptotically stable whenever and globally asymptotically stable if and the Endemic Equilibrium is globally asymptotically stable if The results obtained shows that the progression rate of precancerous cells to cancerous cells ( has the most direct impact on the model. The model was able to estimate the longevity of a patient as 10 days when ( increases by . The findings of this research will help healthcare providers, public health authorities, and non-governmental health groups in creating effective prevention strategies to slow the development of cervical cancer. More research should be done to determine the exact number of cancerous cells that can lead to the death of a cervical cancer patient since this paper estimated a proportion of .

摘要

宫颈癌是最常见的癌症类型之一,主要由高危型人乳头瘤病毒(HPV)引起,且仍在以惊人的速度蔓延。虽然此前已对HPV的影响进行过研究,但目前仅有少数数学模型考虑到了HPV在宫颈癌中的动态作用。目标是建立一个宿主内密度依赖的确定性模型,用于研究包含免疫和功能反应的基底细胞、病毒粒子及淋巴细胞的动态影响。使用诸如基本再生数等流行病学模型技术对该模型进行分析,并使用Matlab常微分方程求解器对模型进行模拟。模型中考虑了六个区室,即:易感细胞(S)、感染细胞(I)、癌前细胞(P)、癌细胞(C)、病毒粒子(V)和淋巴细胞(L)。使用下一代矩阵(NGM)、生存函数和特征多项式方法来确定基本再生数,记为 ,使用三种方法来获得该值,因为NGM存在一些弱点,所以需要其他两种方法。本研究结果表明,当 时,无病平衡点局部渐近稳定,当 时全局渐近稳定,当 时地方病平衡点全局渐近稳定。所得结果表明,癌前细胞向癌细胞的进展率( )对模型的影响最为直接。当( )增加 时,该模型能够估计患者的寿命为10天。本研究结果将有助于医疗保健提供者、公共卫生当局和非政府卫生组织制定有效的预防策略,以减缓宫颈癌的发展。由于本文估计的比例为 ,因此应开展更多研究以确定可导致宫颈癌患者死亡的癌细胞的确切数量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/20c8/11381724/16d318028ce0/gr1.jpg

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