Suppr超能文献

神经类器官中坏死的计算建模。

Computational modeling of necrosis in neural organoids.

作者信息

Pantula Aishwarya, Zhou Bo, Morales Pantoja Itzy E, Fedotova Alisa, George Derosh, Alam El Din Dowlette-Mary, Lysinger Alexandra, Smirnova Lena, Gracias David H

出版信息

bioRxiv. 2025 May 6:2025.04.30.651571. doi: 10.1101/2025.04.30.651571.

Abstract

Neural organoids (NOs), also known as brain organoids, are derived from human-induced pluripotent stem cells and are Microphysiological Systems (MPS) of the brain that can recapitulate key aspects of neurodevelopment. They enable studies of brain development and disease mechanisms, providing disease models for various neurodegenerative or neurodevelopmental/degenerative disorders like Alzheimer's disease, microcephaly, and autism. There are many protocols to generate NOs with different complexities and sizes, varying from 400 μm to several mm in diameter, with a starvation-induced necrotic core eventually forming depending on the diameter and culture conditions. Thus, they can benefit from vascularization and more optimal culture conditions. There have been several attempts to decrease necrosis while growing larger NOs, such as by using orbital shaking or 2D/3D microfluidic chips, but only with limited success. In this study, we describe a 3D finite element model to simulate O starvation-induced necrosis in NOs using the Damköhler Number ( ) and the Michaelis-Menten kinetics. We measured the necrotic areas in NOs using fluorescent imaging and used them to calibrate the model with a specific . Using these calibrated values, we systematically compared simulations of different NO culture methods-static, orbital shaking, and microfluidic flow around organoids-highlighting their relative impacts on nutrient diffusion and necrosis. We observed that these culture strategies cannot prevent necrosis beyond a diameter of ∼800 μm. Based on these findings, we propose that 3D spatial perfusion, achieved through uniformly distributed fluidic capillaries within the NO, could significantly reduce necrosis. We conducted parametric studies on capillary spacing, density, and layout. Our calibrated model offers insights for designing next-generation microfabricated bioreactors and culture devices, not just for NOs but also for all 3D tissue engineering and organoid research.

摘要

神经类器官(NOs),也被称为脑类器官,源自人类诱导多能干细胞,是大脑的微生理系统(MPS),能够概括神经发育的关键方面。它们有助于研究大脑发育和疾病机制,为各种神经退行性或神经发育/退行性疾病(如阿尔茨海默病、小头畸形和自闭症)提供疾病模型。有许多方案可用于生成具有不同复杂性和大小的NOs,直径从400μm到几毫米不等,最终会根据直径和培养条件形成饥饿诱导的坏死核心。因此,它们可以从血管化和更优化的培养条件中受益。已经有几次尝试在培养更大的NOs时减少坏死,例如通过使用轨道振荡或二维/三维微流控芯片,但只取得了有限的成功。在本研究中,我们描述了一个三维有限元模型,使用达姆科勒数( )和米氏动力学来模拟NOs中氧饥饿诱导的坏死。我们使用荧光成像测量了NOs中的坏死区域,并使用它们以特定的 校准模型。使用这些校准值,我们系统地比较了不同NO培养方法(静态、轨道振荡和类器官周围的微流控流动)的模拟结果,突出了它们对营养物质扩散和坏死的相对影响。我们观察到,这些培养策略无法防止直径超过约800μm时的坏死。基于这些发现,我们提出,通过在NO内均匀分布的流体毛细管实现的三维空间灌注可以显著减少坏死。我们对毛细管间距、密度和布局进行了参数研究。我们校准的模型不仅为设计下一代微制造生物反应器和培养装置提供了见解,不仅适用于NOs,也适用于所有三维组织工程和类器官研究。

相似文献

1
Computational modeling of necrosis in neural organoids.神经类器官中坏死的计算建模。
bioRxiv. 2025 May 6:2025.04.30.651571. doi: 10.1101/2025.04.30.651571.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验