Rapid fabrication of hydrogel micropatterns by projection stereolithography for studying self-organized developmental patterning

Rapid Whole-Plate Cell and Tissue Micropatterning Using a Budget 3D Resin Printer

The ability to precisely pattern cells and proteins is crucial in various scientific disciplines, including cell biology, bioengineering, and materials chemistry. Current techniques, such as microcontact stamping, 3D bioprinting, and direct photopatterning, have limitations in terms of cost, versatility, and throughput. In this Article, we present an accessible approach that combines the throughput of photomask systems with the versatility of programmable light patterning using a low-cost consumer LCD resin printer. The method involves utilizing a bioinert hydrogel, poly(ethylene glycol) diacrylate (PEGDA), and a 405 nm sensitive photoinitiator (LAP) that are selectively cross-linked to form a hydrogel upon light exposure, creating specific regions that are protein and cell-repellent. Our result highlights that a low-cost LCD resin printer can project virtual photomasks onto the hydrogel, allowing for reasonable resolution and large-area printing at a fraction of the cost of traditional systems. The study demonstrates the calibration of exposure times for optimal resolution and accuracy and shape corrections to overcome the inherent challenges of wide-field resin printing. The potential of this approach is validated through widely studied 2D and 3D stem cell applications, showcasing its biocompatibility and ability to replicate complex tissue engineering patterns. We also validate the method with a cell-adhesive polymer (gelatin methacrylate; GelMA). The combination of low cost, high throughput, and accessibility makes this method broadly applicable across fields for enabling rapid and precise fabrication of cells and tissues in standard laboratory culture vessels.

Mesoscopic calcium imaging in a head-unrestrained male non-human primate using a lensless microscope

Mesoscopic calcium imaging enables studies of cell-type specific neural activity over large areas. A growing body of literature suggests that neural activity can be different when animals are free to move compared to when they are restrained. Unfortunately, existing systems for imaging calcium dynamics over large areas in non-human primates (NHPs) are table-top devices that require restraint of the animal's head. Here, we demonstrate an imaging device capable of imaging mesoscale calcium activity in a head-unrestrained male non-human primate. We successfully miniaturize our system by replacing lenses with an optical mask and computational algorithms. The resulting lensless microscope can fit comfortably on an NHP, allowing its head to move freely while imaging. We are able to measure orientation columns maps over a 20 mm2 field-of-view in a head-unrestrained macaque. Our work establishes mesoscopic imaging using a lensless microscope as a powerful approach for studying neural activity under more naturalistic conditions.

New Insights and Advanced Strategies for In Vitro Construction of Vascularized Tissue Engineering

Inadequate vascularization is a significant barrier to clinical application of large-volume tissue engineered grafts. In contrast to in vivo vascularization, in vitro prevascularization shortens the time required for host vessels to grow into the graft core and minimizes necrosis in the core region of the graft. However, the challenge of prevascularization is to construct hierarchical perfusable vascular networks, increase graft volume, and form a vascular tip that can anastomose with host vessels. Understanding advances in in vitro prevascularization techniques and new insights into angiogenesis could overcome these obstacles. In the present review, we discuss new perspectives on angiogenesis, the differences between in vivo and in vitro tissue vascularization, the four elements of prevascularized constructs, recent advances in perfusion-based in vitro prevascularized tissue fabrication, and prospects for large-volume prevascularized tissue engineering.

Real-time, deep-learning aided lensless microscope

Traditional miniaturized fluorescence microscopes are critical tools for modern biology. Invariably, they struggle to simultaneously image with a high spatial resolution and a large field of view (FOV). Lensless microscopes offer a solution to this limitation. However, real-time visualization of samples is not possible with lensless imaging, as image reconstruction can take minutes to complete. This poses a challenge for usability, as real-time visualization is a crucial feature that assists users in identifying and locating the imaging target. The issue is particularly pronounced in lensless microscopes that operate at close imaging distances. Imaging at close distances requires shift-varying deconvolution to account for the variation of the point spread function (PSF) across the FOV. Here, we present a lensless microscope that achieves real-time image reconstruction by eliminating the use of an iterative reconstruction algorithm. The neural network-based reconstruction method we show here, achieves more than 10000 times increase in reconstruction speed compared to iterative reconstruction. The increased reconstruction speed allows us to visualize the results of our lensless microscope at more than 25 frames per second (fps), while achieving better than 7 µm resolution over a FOV of 10 mm2. This ability to reconstruct and visualize samples in real-time empowers a more user-friendly interaction with lensless microscopes. The users are able to use these microscopes much like they currently do with conventional microscopes.