一种微流控系统，用于模拟生理脉冲剪切应力与振荡性高血糖下的内皮功能障碍
May 12th, 2026
本文介绍了一种方法，用于制造和操作一种微流控系统，使内皮细胞暴露于同步振荡性高血糖和脉动剪切应力之下。该方法为研究糖尿病内皮功能障碍提供了具有生理学意义的 体外模型。该方案能够定量测量氧化应激和内皮细胞反应。
本研究探讨同步振荡性高血糖与脉动剪切应力如何共同驱动糖尿病血管疾病中的内皮功能障碍。现有模型使用高血糖起始或稳定层流。我们研究脉冲剪切应力如何抵消振荡性葡萄糖损伤。
首先，使用计算机辅助设计软件设计微流控芯片结构。通过商业公司制作SU-8主模具。在一个干净的搅拌杯中，将聚二甲基硅氧烷固化剂和预聚合物以10：1的重量比例混合，并用手用力搅拌五分钟。
然后将容器放入真空室，压力为0.08兆帕，至少浸泡15分钟，以去除混合过程中被困的气泡。将聚二甲基硅氧烷倒在放入玻璃培养皿中的晶圆上。脱气时，聚二甲基硅氧烷在干燥器中倒在晶圆上，额外浸泡15分钟，以去除铸造过程中产生的气泡。
将装有模具和聚合物的培养皿放入加热烤箱，温度定为80摄氏度，烤两小时。用手术刀小心地将凝固的聚合物板从主模具上剥离。使用核心冲孔工具，在聚合物板上指定的通道端部创建进出口口。
用胶带清洁玻璃罩滑腻和聚合物板的花纹面。接着，用等离子清洁剂在室内空气下以65瓦电量处理聚合物板和玻璃盖滑层60秒。立即将聚合物通道面与玻璃盖滑入处理过的一侧对齐。
然后轻轻按压，形成永久闭合的微流控通道。将结合的微流控芯片放入装满去离子水的硼化玻璃瓶中。在121摄氏度、每平方英寸15磅的高温消毒20分钟。
将消毒后的芯片放入一个60毫米培养皿中，内含等摩尔PBS和低血糖DMEM混合物。然后用一毫升注射器，将每毫升100微克纤维内联素注入通道，并在37摄氏度下孵育四小时。接着，将24.5毫莫拉去曼尼醇加入低葡萄糖DMEM以提升渗透压。
将5毫莫尔D-葡萄糖加入高葡萄糖DMEM，最终浓度为30毫莫尔葡萄糖。准备普通葡萄糖培养基和高葡萄糖培养基，辅以20%FBS和1%青霉素链霉素。然后在37摄氏度的水浴中加热PBS、胰蛋白酶、正常葡萄糖培养基和高葡萄糖培养基。
从培养皿中提取90%汇聚率的人类脐静脉内皮细胞。用0.25%胰蛋白酶-EDTA溶液分离细胞。在37摄氏度下培养细胞30秒后，计数采集的细胞，并分别以1乘10的6细胞每毫升浓度分别悬浮在正常葡萄糖和高葡萄糖培养基中。
使用一毫升注射器，将100微升细胞悬浮液注入微流控芯片的入口口，对照组使用正常葡萄糖培养基，实验组使用高葡萄糖培养基。将微流控芯片放入37摄氏度加5%二氧化碳的加湿孵化箱中，浸泡48小时。利用所示方程计算实现目标脉冲剪切应力所需的流量。
将压力源连接到压力控制器。然后将压力控制器连接到计算机的阀门控制器，实现压力波形的自动控制。填充两个100毫升的储液槽，一个是正常葡萄糖培养基，另一个是高葡萄糖培养基。
将水库连接到压力控制器的相应通道。然后用硅胶管连接储液槽和两档三通磁阀。设定目标生理脉冲剪应力，流量约为每分钟200微升。
编程可编程空气泵生成正弦波函数以维持脉冲剪切应力。接下来，编程阀门控制器每五分钟切换一次通道，在动态刺激期间产生方波葡萄糖振荡。用硅胶管连接两档三路磁阀和微流控芯片。
然后启动可编程泵系统，给管子预热。接着，使用直径1.3毫米、90度角的不锈钢连接器，将微流控芯片的进出口端口连接到管子上。将微流控芯片出口连接到废物储存槽，然后重新启动泵，以提供振荡葡萄糖和脉冲剪切应力的综合作用，共计30分钟。
在进行流场验证后，按照实验端点的制造商说明制备钙化素AM和碘化丙苯的工作溶液。通道用PBS冲洗一次后，将钙化素AM和碘化丙烷工作液注入通道，并在37摄氏度与5%二氧化碳下在黑暗中孵育30分钟。立即使用配备10倍物镜的倒置荧光显微镜拍摄染色细胞的荧光图像。
立即使用配备10倍物镜的倒置荧光显微镜拍摄染色细胞的荧光图像。对于钙化物AM，使用荧光素异硫氰酸酯绿色滤光片，用于检测碘化丙蓷，使用四甲基胡胺或罗丹胺红色滤光片。在用PBS冲洗通道三次后，将活细胞氧化应激荧光探针溶液注入通道并如前所述培养。
用PBS冲洗通道三次以去除未绑定的探头。立即使用远红滤光片通过20倍物镜拍摄荧光图像，同时保持所有组间相同的曝光参数。在ImageJ中打开采集的钙化素AM绿色和碘化物丙化物红图像。
手动调整每个通道的阈值，以区分荧光信号和背景信号。使用细胞计数器量化荧光细胞，根据观察调整最小细胞大小，以确定多个视场上的活细胞和死细胞计数。使用电子表格软件计算每种实验条件的活细胞百分比。
然后利用统计分析软件计算多个视野的均值和标准差，以比较各组。把喜欢的图片拖入ImageJ。选择分析并选择设置缩放，利用显微镜元数据校准像素大小。
然后通过选择“过程”并选择“减去背景”，使用背景减法函数去除整个图像中的非特异均匀背景信号。接下来，选择图片并选择“调整”，再选择阈值，手动调整阈值滑块并定义细胞内活性氧信号。通过选择“分析”并选择“Set measurements”以包含面积和平均灰值来设置测量值。
选择“分析”和“分析粒子”，根据观察到的单元尺寸确定最小单元大小，并测量单元单层ROI内分段信号的平均强度。报告每个实验条件下的活性氧浓度，作为每个芯片至少随机选定三个视场得出的测量值的平均值。将定量结果输入数据分析和绘图软件。
通过双向方差分析比较实验组与对照组，随后进行Tukey事后检验，显著性水平为0.05，确定统计显著性。使用该软件进行分析，生成带有代表标准差的误差条的图。代表性荧光图像显示，正常葡萄糖组和脉动剪切应激组正常组中细胞死亡率极低，而振荡葡萄糖组和振荡性葡萄糖组中，丧死细胞数量明显增加。
定量分析显示，振荡性葡萄糖暴露导致细胞存活率显著降低，且在振荡性葡萄糖条件下施加的脉动剪切应力显著提升了振荡性葡萄糖的存活率。在正常葡萄糖条件下，细胞内活性氧水平较低，且在剪切应激作用下进一步降低。而振荡性葡萄糖条件则导致红色荧光强度显著增加，表明活性氧含量升高。
在剪切应激施加后，振荡性葡萄糖诱导的细胞内活性氧物种增加被减弱。定量分析显示，剪切应激在正常葡萄糖条件下显著降低了活性氧的水平。相比之下，振荡性葡萄糖条件导致活性氧物种水平显著增加，相较于正常葡萄糖。
此外，剪切应力显著降低活性氧物种水平，即使在振荡葡萄糖条件下也是如此。该方案能够量化ROS水平和细胞可用性，以研究振荡性高血糖和脉冲剪切应力下的内皮功能障碍。在此程序之后，可以进行分子分析，如NRF2通路或iNOS信号传导，以去核内皮保护机制。
未来的研究可能利用该系统探索机械生物学通路，结合流动几何结构或平滑肌细胞共培养。
View the full transcript and gain access to thousands of scientific videos
Overview
This protocol describes a programmable microfluidic platform designed to model endothelial dysfunction under physiologically relevant conditions that mimic diabetic vascular complications. By integrating synchronized oscillatory hyperglycemia and physiological pulsatile shear stress (PSS), the system enables precise investigation of the combined metabolic and mechanical factors affecting endothelial cells. The approach allows for detailed mechanistic studies and drug screening relevant to diabetic vascular disease.
Key Study Components
Area of Science
- Vascular biology
- Diabetes research
- Microfluidics
- Cellular mechanobiology
Background
- Endothelial dysfunction is a key contributor to diabetic vascular complications.
- Oscillatory glucose (OG) and pulsatile shear stress (PSS) are important factors in diabetic vasculature.
- Traditional models often use static high-glucose or simplified laminar flow, lacking physiological relevance.
- Integrated spatiotemporal coupling of metabolic and mechanical stimuli is critical for accurate modeling.
Purpose of Study
- To develop a microfluidic platform that synchronizes OG and PSS for endothelial cell studies.
- To model endothelial dysfunction under coupled metabolic and mechanical conditions.
- To enable mechanistic studies and drug screening for diabetic vascular disease.
Methods Used
- Programmable microfluidic platform with polydimethylsiloxane (PDMS) chip.
- Pressure-driven control system for independent modulation of flow and glucose profiles.
- Validation of hemodynamic fidelity using Micro-Particle Image Velocimetry (Micro-PIV).
- Quantitative assessment of intracellular reactive oxygen species (ROS) and cell viability.
Main Results
- Physiological PSS attenuates oxidative injury induced by oscillatory glucose.
- Reduced intracellular ROS levels observed under combined OG and PSS stimulation.
- Improved cell viability under physiologically relevant coupled conditions.
- System parameters such as shear stress, glucose oscillation, and channel geometry are adjustable.
Conclusions
- The platform effectively models the integrated effects of metabolic and mechanical stress on endothelial cells.
- Physiological PSS can mitigate oxidative damage from oscillatory hyperglycemia.
- This method is a versatile tool for mechanistic studies and therapeutic screening in diabetic vascular disease.
Frequently Asked Questions
Executive Industry Relevance
Modeling endothelial dysfunction under physiologically relevant, coupled metabolic and mechanical stressors is critical for predictive confidence in diabetic vascular disease research. This microfluidic system enables precise interrogation of mechanobiological pathways by integrating oscillatory hyperglycemia and pulsatile shear stress, directly addressing a key translational bottleneck in vascular target validation. The platform's quantitative outputs and tunable parameters support risk-adjusted decision-making across early discovery and preclinical pipelines.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Enables mechanistic de-risking by modeling disease-relevant endothelial dysfunction under synchronized metabolic and hemodynamic conditions.
- Supports functional target validation through quantitative assessment of oxidative stress and cell viability.
- Facilitates hypothesis-driven interrogation of vascular pathways implicated in diabetic complications.
Screening & Assay Development
- Provides a validated, programmable system for generating reproducible, physiologically relevant flow and glucose profiles.
- Delivers quantitative readouts (ROS, viability) suitable for compound screening and assay standardization.
- Enables scalability and platform reuse by allowing adjustment of shear stress, glucose oscillation, and channel geometry.
Translational & Preclinical Research
- Aligns in vitro modeling with disease-relevant vascular stressors for improved translational continuity.
- Supports biomarker discovery and mechanistic studies relevant to diabetic vascular disease progression.
- Reduces late-stage biological risk by providing predictive, quantitative endpoints for preclinical evaluation.
Pipeline & Workflow Integration
This microfluidic system bridges early discovery and preclinical research by enabling hypothesis testing, target validation, and assay development within a single, tunable platform.
- Discovery Biology: Supports mechanistic studies of endothelial dysfunction under coupled metabolic and mechanical stress.
- Screening: Provides reproducible, quantitative outputs for compound evaluation and assay optimization.
- Analytics: Enables direct measurement of ROS and viability for comparative analysis across experimental conditions.
- Translational Research: Facilitates alignment of in vitro findings with disease-relevant vascular phenotypes.
- Enterprise Reuse: Offers a flexible, programmable system adaptable to diverse vascular research and screening needs.
Operational & Enterprise Impact
- Scientific Value: Increases predictive confidence and reduces mechanistic ambiguity in vascular target validation.
- Operational Value: Standardizes complex flow and metabolic conditions for reproducible, scalable experimentation.
- Strategic Value: Improves go/no-go decisions and capital efficiency by providing robust, quantitative endpoints.
- Portfolio Impact: Enables risk-adjusted prioritization of vascular targets and therapeutic candidates.
Implementation Considerations
- Requires expertise in microfluidics, vascular biology, and quantitative cell-based assays.
- Needs access to programmable flow control systems and Micro-PIV for hemodynamic validation.
- Demands cross-team standardization of experimental parameters and data analysis workflows.
- Adaptable to various channel geometries and flow/glucose profiles for different research questions.
- Practical limitations include the need for specialized instrumentation and technical training.