两级自相似分形微流控浓度梯度芯片设计及性能分析
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摘要
浓度梯度被广泛应用于趋化分析、细胞生长、DNA检测和毒性评价等诸多领域。传统浓度梯度生成方法具有效率低、梯度不精确、稳定性差等不足。本文基于经典圣诞树模型,设计了一种反应速度快、精度高,可生成稳定浓度梯度的两级自相似分形微流控浓度梯度芯片,并进行了仿真与实验研究。建立了多物理场耦合模型,在不同进样条件下,使用COMSOL Multiphysics进行了数值模拟。通过对归一化进样流量矩阵与浓度矩阵的耦合设置,得到丰富种类的浓度梯度分布。以去离子水和红色染料为样本进行实验验证,结果与仿真模拟具有较好的一致性,证明了两级自相似分形微流控浓度梯度芯片设计的合理性,其优势在于,无需重新设计微流道构型而只是简单调节进样流量比,便可以实现生成不同浓度梯度的实际需求。
Concentration gradients was applied in many biological applications with the performance of chemotaxis analysis,cell growth,DNA detection and toxicity evaluation. Traditional methods for concentration gradient generation are usually with the characteristic of inefficient,inexact and unstable. To overcome the boundedness,a self-similar fractal microfluidic concentration gradient chip with rapid response,high precision and stable concentration gradient was demonstrated based on the classical Christmas tree model. The performance were tested by using both numerical simulation models and experimental research. First,a multi-physical field coupling model was established and simulated by a software named Comsol Multiphysics under different sample introduction conditions.Then,a variety of concentration gradient distributions were obtained by coupled setting the normalized injection flow matrix with the concentration matrix. Finally,the experimental results from deionized water and red dyes were in good agreement with the simulation results,which proved the rationality of the design of two-stage self-similar fractal microfluidic concentration gradient chip. The advantage of the chip is that it can generate flexible concentration gradients by simply adjusting the injection flow ratio without redesigning the configuration of the microfluidic device.
Concentration gradients was applied in many biological applications with the performance of chemotaxis analysis,cell growth,DNA detection and toxicity evaluation. Traditional methods for concentration gradient generation are usually with the characteristic of inefficient,inexact and unstable. To overcome the boundedness,a self-similar fractal microfluidic concentration gradient chip with rapid response,high precision and stable concentration gradient was demonstrated based on the classical Christmas tree model. The performance were tested by using both numerical simulation models and experimental research. First,a multi-physical field coupling model was established and simulated by a software named Comsol Multiphysics under different sample introduction conditions.Then,a variety of concentration gradient distributions were obtained by coupled setting the normalized injection flow matrix with the concentration matrix. Finally,the experimental results from deionized water and red dyes were in good agreement with the simulation results,which proved the rationality of the design of two-stage self-similar fractal microfluidic concentration gradient chip. The advantage of the chip is that it can generate flexible concentration gradients by simply adjusting the injection flow ratio without redesigning the configuration of the microfluidic device.
引文
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18 Anielski A,Pfannes E K,Beta C.Adaptive microfluidic gradient generator for quantitative chemotaxis experiments[J].Review of Scientific Instruments,2017,88(3):034301
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2 Kukhtevich I V,Belousov K I,Bukatin A S,et al.Microfluidic chips for the study of cell migration under the effect of chemicals[J].Technical Physics Letters,2016,42(5):478-481
3 Sonmez U M,Leduc P R,Pawel K,et al.Chemotaxis of immune cells in microfluidic flow-free concentration gradient generator[J].Biophysical Journal,2018,114(3):217a
4 Hu C F,Lin Y S,Chen H M,et al.Concentration gradient generator for H460 lung cancer cell sensitivity to resist the cytotoxic action of curcumin in microenvironmental pH conditions[J].RSC Advances,2016,6:107310-107316
5 Shen Q L,Zhou Q W,Lu Z G,et al.Generation of linear and parabolic concentration gradients by using a christmas tree-shaped microfluidic network[J].Wuhan University Journal of Natural Sciences,2018,23(3):244-250
6 Hu Z L,Chen X Y,Wang L.Design and fabrication of concentration-gradient generator with two and three inlets in microfluidic chips[J].Chemical Engineering Technology,2017,41(3):489-495
7 Zaidon N,Mansor A F M,Mak W C,et al.Microfluidic concentration gradient for toxicity studies of lung carcinoma cells[J].Procedia Technology,2017,27:153-154
8 Liu W T,Chen H M,Nie F Q.Cell migration with microfluidic chips[J].Chinese Science Bulletin,2016,61(3):364
9 Xiong B,Ren K N,Shu Y W,et al.Recent developments in microfluidics for cell studies[J].Advanced Materials,2015,26(31):5525-5532
10 Yue W Q,Yang M S.Microfluidics for DNA and protein analysis with multiplex microbead-based assays[M].Germany:Springer Link,2016:161-187
11 Park J W,Shin H S,Kim H J,et al.Concentration gradient generation and control[M].New York:Springer Science+Business Media New York,2015
12 Du G S,Fang Q,Den Toonder J M J.Microfluidics for cell-based high throughput screening platforms-a review[J].Analytica Chimica Acta,2016,903:36-50
13 Schaumburg F,Urteaga R,Kler P A,et al.Design keys for paperbased concentration gradient generators[J].Journal of Chromatography A,2018,1561:83-91
14 Gielen F,Buryska T,Vliet L V,et al.Interfacing microwells with nanoliter compartments:a sampler generating high-resolution concentration gradients for quantitative biochemical analyses in droplets[J].Analytical Chemistry,2015,87(1):624-632
15 Khoo B L,Grenci G,Jing T,et al.Liquid biopsy and therapeutic response:circulating tumor cell cultures for evaluation of anticancer treatment[J].Science Advances,2016,2(7):e1600274
16 Federico S,Urteaga R,Kler P A,et al.Design keys for paperbased concentration gradient generators[J].Journal of Chromatography A,2018,1561:83-91
17 Somaweera H,Ibraguimov A,Pappas D.A review of chemical gradient systems for cell analysis[J].Analytica Chimica Acta,2016,907:7-17
18 Anielski A,Pfannes E K,Beta C.Adaptive microfluidic gradient generator for quantitative chemotaxis experiments[J].Review of Scientific Instruments,2017,88(3):034301
19 Yehezkel T B,Rival A,Raz O,et al.Synthesis and cell-Free cloning of DNA libraries using programmable microfluidics[J].Nucleic Acids Research,2015,44(4):e35
20 Lifton V A.Microfluidics:an enabling screening technology for enhanced oil recovery(EOR)[J].Lab on a Chip,2016,16(10):1777-1796