恶性黑色素瘤分数顺序数学模型与稳定模糊滑动模式控制
David Amilo1, Khadijeh Sadri1, Evren Hincal1
1Department of Mathematics, Near East University TRNC, Mersin 10, Nicosia, 99010, Turkey; Mathematics Research Center, Near East University TRNC, Mersin 10, Nicosia, 99010, Turkey.
Computer methods and programs in biomedicine
|July 13, 2025
概括
本研究引入了分数顺序模型和稳定模糊滑动模式控制 (SFSMC) 以有效管理恶性黑色素瘤. 这种方法显著减少了瘤细胞和改善了瘤微环境,显示了适应性黑色素瘤治疗的前景.
科学领域:
- 数学瘤学数学瘤学
- 控制理论 控制理论
- 生物医学工程 生物医学工程
背景情况:
- 恶性黑色素瘤由于快速进展和治疗耐药性而存在挑战.
- 了解瘤免疫相互作用,ECM重塑和营养动力学至关重要.
- 现有的模型可能无法完全捕捉黑色素瘤进展中的复杂,远程依赖性.
研究的目的:
- 为黑色素瘤动态开发一个小数序数学模型.
- 引入稳定模糊滑动模式控制 (SFSMC) 策略用于瘤抑制.
- 恢复微环境平衡,改善治疗结果.
主要方法:
- 使用卡普托衍生品捕捉记忆效应的分数顺序模型.
- 瑞士金融服务中心集成模糊逻辑用于不确定性管理.
- 理论分析模型的正确位置,稳定性和复制数 (R0).
- 数字模拟与临床数据校准使用预测-校正方法.
主要成果:
- 当R0 < 1时,模型稳定性得到实现,表明瘤抑制.
- SFSMC减少了78%的瘤细胞和65%的循环瘤细胞.
- 观察到免疫反应 (+45%) 和营养物质可用性 (+30%) 的显著改善.
- 灵敏度分析确定了影响R0和瘤生长的关键参数.
结论:
- 分数顺序建模和SFSMC为黑色素瘤控制提供了一个强大的框架.
- 开发的SFSMC战略表明了恶性黑色素瘤适应性治疗的潜力.
- 研究结果表明,对个性化和适应性治疗策略有潜在的临床影响.
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