Electrically tunable lenses - eliminating mechanical axial movements during high-speed 3D live imaging

Laser axial scanning microdissection for high-efficiency dissection from uneven biological samples

Fast and efficient separation of target samples is crucial for the application of laser-assisted microdissection in the molecular biology research field. Herein, we developed a laser axial scanning microdissection (LASM) system with an 8.6 times extended depth of focus by using an electrically tunable lens. We showed that the ablation quality of silicon wafers at different depths became homogenous after using our system. More importantly, for those uneven biological tissue sections within a height difference of no more than 19.2 µm, we have demonstrated that the targets with a size of microns at arbitrary positions can be dissected efficiently without additional focusing and dissection operations. Besides, dissection experiments on various biological samples with different embedding methods, which were widely adopted in biological experiments, also have shown the feasibility of our system.

Opportunities and challenges for deep learning in cell dynamics research

The growth of artificial intelligence (AI) has led to an increase in the adoption of computer vision and deep learning (DL) techniques for the evaluation of microscopy images and movies. This adoption has not only addressed hurdles in quantitative analysis of dynamic cell biological processes but has also started to support advances in drug development, precision medicine, and genome-phenome mapping. We survey existing AI-based techniques and tools, as well as open-source datasets, with a specific focus on the computational tasks of segmentation, classification, and tracking of cellular and subcellular structures and dynamics. We summarise long-standing challenges in microscopy video analysis from a computational perspective and review emerging research frontiers and innovative applications for DL-guided automation in cell dynamics research.

Volumetric light sheet imaging with adaptive optics correction

Light sheet microscopy has developed quickly over the past decades and become a popular method for imaging live model organisms and other thick biological tissues. For rapid volumetric imaging, an electrically tunable lens can be used to rapidly change the imaging plane in the sample. For larger fields of view and higher NA objectives, the electrically tunable lens introduces aberrations in the system, particularly away from the nominal focus and off-axis. Here, we describe a system that employs an electrically tunable lens and adaptive optics to image over a volume of 499 × 499 × 192 μm3 with close to diffraction-limited resolution. Compared to the system without adaptive optics, the performance shows an increase in signal to background ratio by a factor of 3.5. While the system currently requires 7s/volume, it should be straightforward to increase the imaging speed to under 1s per volume.

Novel Optofluidic Imaging System Integrated with Tunable Microlens Arrays

Optofluidic tunable microlens arrays (MLAs) can manipulate and control light propagation using fluids. Lately, their applicability to miniature lab-on-a-chip systems is being extensively researched. However, it is difficult to incorporate 3D MLAs directly in a narrow microfluidic channel using common techniques. This has resulted in limited research on variable focal length imaging with optofluidic 3D MLAs. In this paper, we propose a method for fabricating MLAs in polydimethylsiloxane (PDMS)-based microchannels via electrohydrodynamic jet (E-jet) printing to achieve optofluidic tunable MLAs. Using this method, MLAs of diameters 15 to 80 μm can be fabricated in microfluidic channels with widths of 200 and 300 μm. By alternately using solutions with different refractive indices in the microchannel, the optofluidic microlenses exhibit reversible modulation properties while retaining the morphologies and refractive indices of the microlenses. The focal length of the resulting optofluidic chip can have threefold tunability, thereby achieving an imaging depth of approximately 450 μm. This outstanding advantage is useful in observing microspheres and cells flowing in the microfluidic system. Thus, the proposed optofluidic chip exhibits great potential for cell counting and imaging applications.