Stockslager Max A, Capocasale Christopher M, Holst Gregory L, Simon Michael D, Li Yuanda, McGruder Dustin J, Rousseau Erin B, Stoy William A, Sulchek Todd, Forest Craig R
G. W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, 315 Ferst Drive, Atlanta, GA 30332.
SUNY Polytechnic Institute, Colleges of Nanoscale Science and Engineering, 257 Fuller Rd, Albany, NY 12203.
Precis Eng. 2016 Oct;46:88-95. doi: 10.1016/j.precisioneng.2016.04.003. Epub 2016 Apr 2.
Many experimental biological techniques utilize hollow glass needles called micropipettes to perform fluid extraction, cell manipulation, and electrophysiological recordings For electrophysiological recordings, micropipettes are typically fabricated immediately before use using a "pipette puller", which uses open-loop control to heat a hollow glass capillary while applying a tensile load. Variability between manufactured micropipettes requires a highly trained operator to qualitatively inspect each micropipette; typically this is achieved by viewing the pipette under 40-100x magnification in order to ensure that the tip has the correct shape (e.g., outer diameter, cone angle, taper length). Since laboratories may use hundreds of micropipettes per week, significant time demands are associated with micropipette inspection. Here, we have automated the measurement of micropipette tip outer diameter and cone angle using optical microscopy. The process features repeatable constraint of the micropipette, quickly and automatically moving the micropipette to bring its tip into the field of view, focusing on the tip, and computing tip outer diameter and cone angle measurements from the acquired images by applying a series of image processing algorithms. As implemented on a custom automated microscope, these methods achieved, with 95% confidence, ±0.38 µm repeatability in outer diameter measurement and ±5.45° repeatability in cone angle measurement, comparable to a trained human operator. Accuracy was evaluated by comparing optical pipette measurements with measurements obtained using scanning electron microscopy (SEM); optical outer diameter measurements differed from SEM by 0.35 ± 0.36 µm and optical cone angle measurements differed from SEM by -0.23 ± 2.32°. The algorithms we developed are adaptable to most commercial automated microscopes and provide a skill-free route to rapid, quantitative measurement of pipette tip geometry with high resolution, accuracy, and repeatability. Further, these methods are an important step toward a closed-loop, fully-automated micropipette fabrication system.
许多实验生物学技术利用称为微量移液器的空心玻璃针来进行液体提取、细胞操作和电生理记录。对于电生理记录,微量移液器通常在使用前立即使用“拉针器”制造,该拉针器使用开环控制在施加拉伸载荷的同时加热空心玻璃毛细管。制造的微量移液器之间的差异需要训练有素的操作员对每个微量移液器进行定性检查;通常通过在40-100倍放大倍数下观察移液器来实现,以确保尖端具有正确的形状(例如,外径、锥角、锥度长度)。由于实验室每周可能使用数百个微量移液器,因此微量移液器检查需要大量时间。在这里,我们使用光学显微镜实现了微量移液器尖端外径和锥角的自动化测量。该过程的特点是对微量移液器进行可重复约束,快速自动地移动微量移液器,将其尖端带入视野,聚焦于尖端,并通过应用一系列图像处理算法从采集的图像中计算尖端外径和锥角测量值。在定制的自动显微镜上实施时,这些方法在95%的置信度下,外径测量的重复性为±0.38 µm,锥角测量的重复性为±5.45°,与训练有素的人类操作员相当。通过将光学移液器测量结果与使用扫描电子显微镜(SEM)获得的测量结果进行比较来评估准确性;光学外径测量值与SEM的差异为0.35±0.36 µm,光学锥角测量值与SEM的差异为-0.23±2.32°。我们开发的算法适用于大多数商用自动显微镜,并提供了一条无需技能的途径,可快速、定量地测量移液器尖端几何形状,具有高分辨率、准确性和重复性。此外,这些方法是朝着闭环、全自动微量移液器制造系统迈出的重要一步。