Multiple-scattering simulator-trained neural network for intensity diffraction tomography

Recent Advances and Current Trends in Transmission Tomographic Diffraction Microscopy

Optical microscopy techniques are among the most used methods in biomedical sample characterization. In their more advanced realization, optical microscopes demonstrate resolution down to the nanometric scale. These methods rely on the use of fluorescent sample labeling in order to break the diffraction limit. However, fluorescent molecules' phototoxicity or photobleaching is not always compatible with the investigated samples. To overcome this limitation, quantitative phase imaging techniques have been proposed. Among these, holographic imaging has demonstrated its ability to image living microscopic samples without staining. However, for a 3D assessment of samples, tomographic acquisitions are needed. Tomographic Diffraction Microscopy (TDM) combines holographic acquisitions with tomographic reconstructions. Relying on a 3D synthetic aperture process, TDM allows for 3D quantitative measurements of the complex refractive index of the investigated sample. Since its initial proposition by Emil Wolf in 1969, the concept of TDM has found a lot of applications and has become one of the hot topics in biomedical imaging. This review focuses on recent achievements in TDM development. Current trends and perspectives of the technique are also discussed.

DBlink: dynamic localization microscopy in super spatiotemporal resolution via deep learning

Single-molecule localization microscopy (SMLM) has revolutionized biological imaging, improving the spatial resolution of traditional microscopes by an order of magnitude. However, SMLM techniques require long acquisition times, typically a few minutes, to yield a single super-resolved image, because they depend on accumulation of many localizations over thousands of recorded frames. Hence, the capability of SMLM to observe dynamics at high temporal resolution has always been limited. In this work, we present DBlink, a deep-learning-based method for super spatiotemporal resolution reconstruction from SMLM data. The input to DBlink is a recorded video of SMLM data and the output is a super spatiotemporal resolution video reconstruction. We use a convolutional neural network combined with a bidirectional long short-term memory network architecture, designed for capturing long-term dependencies between different input frames. We demonstrate DBlink performance on simulated filaments and mitochondria-like structures, on experimental SMLM data under controlled motion conditions and on live-cell dynamic SMLM. DBlink's spatiotemporal interpolation constitutes an important advance in super-resolution imaging of dynamic processes in live cells.

Advances in volumetric bioprinting

The three-dimensional (3D) bioprinting technologies are suitable for biomedical applications owing to their ability to manufacture complex and high-precision tissue constructs. However, the slow printing speed of current layer-by-layer (bio)printing modality is the major limitation in biofabrication field. To overcome this issue, volumetric bioprinting (VBP) is developed. VBP changes the layer-wise operation of conventional devices, permitting the creation of geometrically complex, centimeter-scale constructs in tens of seconds. VBP is the next step onward from sequential biofabrication methods, opening new avenues for fast additive manufacturing in the fields of tissue engineering, regenerative medicine, personalized drug testing, and soft robotics, etc. Therefore, this review introduces the printing principles and hardware designs of VBP-based techniques; then focuses on the recent advances in VBP-based (bio)inks and their biomedical applications. Lastly, the current limitations of VBP are discussed together with future direction of research.

Mid-infrared chemical imaging of intracellular tau fibrils using fluorescence-guided computational photothermal microscopy

Amyloid proteins are associated with a broad spectrum of neurodegenerative diseases. However, it remains a grand challenge to extract molecular structure information from intracellular amyloid proteins in their native cellular environment. To address this challenge, we developed a computational chemical microscope integrating 3D mid-infrared photothermal imaging with fluorescence imaging, termed Fluorescence-guided Bond-Selective Intensity Diffraction Tomography (FBS-IDT). Based on a low-cost and simple optical design, FBS-IDT enables chemical-specific volumetric imaging and 3D site-specific mid-IR fingerprint spectroscopic analysis of tau fibrils, an important type of amyloid protein aggregates, in their intracellular environment. Label-free volumetric chemical imaging of human cells with/without seeded tau fibrils is demonstrated to show the potential correlation between lipid accumulation and tau aggregate formation. Depth-resolved mid-infrared fingerprint spectroscopy is performed to reveal the protein secondary structure of the intracellular tau fibrils. 3D visualization of the β-sheet for tau fibril structure is achieved.

Focus Issue Introduction: 3D Image Acquisition and Display: Technology, Perception and Applications

This Feature Issue of Optics Express is organized in conjunction with the 2022 Optica conference on 3D Image Acquisition and Display: Technology, Perception and Applications which was held in hybrid format from 11 to 15, July 2022 as part of the Imaging and Applied Optics Congress and Optical Sensors and Sensing Congress 2022 in Vancouver, Canada. This Feature Issue presents 31 articles which cover the topics and scope of the 2022 3D Image Acquisition and Display conference. This Introduction provides a summary of these published articles that appear in this Feature Issue.