Engineering of an electrically charged hydrogel implanted into a traumatic brain injury model for stepwise neuronal tissue reconstruction.

Neural regeneration is extremely difficult to achieve. In traumatic brain injuries, the loss of brain parenchyma volume hinders neural regeneration. In this study, neuronal tissue engineering was performed by using electrically charged hydrogels composed of cationic and anionic monomers in a 1:1 ratio (C1A1 hydrogel), which served as an effective scaffold for the attachment of neural stem cells (NSCs). In the 3D environment of porous C1A1 hydrogels engineered by the cryogelation technique, NSCs differentiated into neuroglial cells. The C1A1 porous hydrogel was implanted into brain defects in a mouse traumatic damage model. The VEGF-immersed C1A1 porous hydrogel promoted host-derived vascular network formation together with the infiltration of macrophages/microglia and astrocytes into the gel. Furthermore, the stepwise transplantation of GFP-labeled NSCs supported differentiation towards glial and neuronal cells. Therefore, this two-step method for neural regeneration may become a new approach for therapeutic brain tissue reconstruction after brain damage in the future.

Advanced observation of brain and nerve cells using two-photon microscopy with novel techniques.

Two-photon excitation fluorescence microscopy [two-photon microscopy (2PM)] is a robust technique for understanding physiological phenomena from the cellular to tissue level, attributable to the nonlinear excitation process induced by near-infrared ultrashort laser light pulses. Recently, we have been promoting the use of semiconductor lasers, adaptive optics, vector beams and nanomaterials to improve the observation depth or spatial resolution. The developed semiconductor-based laser light source successfully visualized the structure of the enhanced yellow fluorescent protein (EYFP)-expressing neurons at the hippocampal dentate gyrus without resecting the neocortex and neuronal activity in the hippocampal cornu ammonis (CA1) region in anesthetized mice at video rates. We also proposed using fluoropolymer nanosheets of 100-nm thickness for in vivo imaging and realized a wide field of view during anesthetized mouse brain imaging of 1-mm depth. Furthermore, the developed adaptive optical 2PM visualized single dendritic spines of EYFP-expressing neurons in cortical layer V of the secondary motor cortex, which had been difficult to observe due to the curvature of the brain surface. In addition, we combined 2PM and stimulated emission depletion microscopy to improve spatial resolution. This combined microscopy is noninvasive and has a superior spatial resolution, exceeding the diffraction limit of the conventional light. In this review, we describe our recent results and discuss the future of 2PM.

Focusing new light on brain functions: multiphoton microscopy for deep and super-resolution imaging.

Multiphoton microscopy has become a powerful tool for visualizing neurobiological phenomena such as the dynamics of individual synapses and the functional activities of neurons. Owing to its near-infrared excitation laser wavelength, multiphoton microscopy achieves greater penetration depth and is less invasive than single-photon excitation. Here, we review the principles of two-photon microscopy and its technical limitations (penetration depth and spatial resolution) on brain tissue imaging. We then describe the technological improvements of two-photon microscopy that enable deeper imaging with higher spatial resolution for investigating unrevealed brain functions.

3DeeCellTracker, a deep learning-based pipeline for segmenting and tracking cells in 3D time lapse images.

Despite recent improvements in microscope technologies, segmenting and tracking cells in three-dimensional time-lapse images (3D + T images) to extract their dynamic positions and activities remains a considerable bottleneck in the field. We developed a deep learning-based software pipeline, 3DeeCellTracker, by integrating multiple existing and new techniques including deep learning for tracking. With only one volume of training data, one initial correction, and a few parameter changes, 3DeeCellTracker successfully segmented and tracked ~100 cells in both semi-immobilized and 'straightened' freely moving worm's brain, in a naturally beating zebrafish heart, and ~1000 cells in a 3D cultured tumor spheroid. While these datasets were imaged with highly divergent optical systems, our method tracked 90-100% of the cells in most cases, which is comparable or superior to previous results. These results suggest that 3DeeCellTracker could pave the way for revealing dynamic cell activities in image datasets that have been difficult to analyze.

Microscopes have been used to decrypt the tiny details of life since the 17th century. Now, the advent of 3D microscopy allows scientists to build up detailed pictures of living cells and tissues. In that effort, automation is becoming increasingly important so that scientists can analyze the resulting images and understand how bodies grow, heal and respond to changes such as drug therapies. In particular, algorithms can help to spot cells in the picture (called cell segmentation), and then to follow these cells over time across multiple images (known as cell tracking). However, performing these analyses on 3D images over a given period has been quite challenging. In addition, the algorithms that have already been created are often not user-friendly, and they can only be applied to a specific dataset gathered through a particular scientific method. As a response, Wen et al. developed a new program called 3DeeCellTracker, which runs on a desktop computer and uses a type of artificial intelligence known as deep learning to produce consistent results. Crucially, 3DeeCellTracker can be used to analyze various types of images taken using different types of cutting-edge microscope systems. And indeed, the algorithm was then harnessed to track the activity of nerve cells in moving microscopic worms, of beating heart cells in a young small fish, and of cancer cells grown in the lab. This versatile tool can now be used across biology, medical research and drug development to help monitor cell activities.

Adaptive Optical Two-Photon Microscopy for Surface-Profiled Living Biological Specimens.

We developed adaptive optical (AO) two-photon excitation microscopy by introducing a spatial light modulator (SLM) in a commercially available microscopy system. For correcting optical aberrations caused by refractive index (RI) interfaces at a specimen's surface, spatial phase distributions of the incident excitation laser light were calculated using 3D coordination of the RI interface with a 3D ray-tracing method. Based on the calculation, we applied a 2D phase-shift distribution to a SLM and achieved the proper point spread function. AO two-photon microscopy improved the fluorescence image contrast in optical phantom mimicking biological specimens. Furthermore, it enhanced the fluorescence intensity from tubulin-labeling dyes in living multicellular tumor spheroids and allowed successful visualization of dendritic spines in the cortical layer V of living mouse brains in the secondary motor region with a curved surface. The AO approach is useful for observing dynamic physiological activities in deep regions of various living biological specimens with curved surfaces.

In vivo two-photon microscopic observation and ablation in deeper brain regions realized by modifications of excitation beam diameter and immersion liquid.

In vivo two-photon microscopy utilizing a nonlinear optical process enables, in living mouse brains, not only the visualization of morphologies and functions of neural networks in deep regions but also their optical manipulation at targeted sites with high spatial precision. Because the two-photon excitation efficiency is proportional to the square of the photon density of the excitation laser light at the focal position, optical aberrations induced by specimens mainly limit the maximum depth of observations or that of manipulations in the microscopy. To increase the two-photon excitation efficiency, we developed a method for evaluating the focal volume in living mouse brains. With this method, we modified the beam diameter of the excitation laser light and the value of the refractive index in the immersion liquid to maximize the excitation photon density at the focal position. These two modifications allowed the successful visualization of the finer structures of hippocampal CA1 neurons, as well as the intracellular calcium dynamics in cortical layer V astrocytes, even with our conventional two-photon microscopy system. Furthermore, it enabled focal laser ablation dissection of both single apical and single basal dendrites of cortical layer V pyramidal neurons. These simple modifications would enable us to investigate the contributions of single cells or single dendrites to the functions of local cortical networks.

Rational Engineering of XCaMPs, a Multicolor GECI Suite for In Vivo Imaging of Complex Brain Circuit Dynamics.

To decipher dynamic brain information processing, current genetically encoded calcium indicators (GECIs) are limited in single action potential (AP) detection speed, combinatorial spectral compatibility, and two-photon imaging depth. To address this, here, we rationally engineered a next-generation quadricolor GECI suite, XCaMPs. Single AP detection was achieved within 3-10 ms of spike onset, enabling measurements of fast-spike trains in parvalbumin (PV)-positive interneurons in the barrel cortex in vivo and recording three distinct (two inhibitory and one excitatory) ensembles during pre-motion activity in freely moving mice. In vivo paired recording of pre- and postsynaptic firing revealed spatiotemporal constraints of dendritic inhibition in layer 1 in vivo, between axons of somatostatin (SST)-positive interneurons and apical tufts dendrites of excitatory pyramidal neurons. Finally, non-invasive, subcortical imaging using red XCaMP-R uncovered somatosensation-evoked persistent activity in hippocampal CA1 neurons. Thus, the XCaMPs offer a critical enhancement of solution space in studies of complex neuronal circuit dynamics. VIDEO ABSTRACT.