Deep learning-based aberration compensation improves contrast and resolution in fluorescence microscopy.

Optical aberrations hinder fluorescence microscopy of thick samples, reducing image signal, contrast, and resolution. Here we introduce a deep learning-based strategy for aberration compensation, improving image quality without slowing image acquisition, applying additional dose, or introducing more optics. Our method (i) introduces synthetic aberrations to images acquired on the shallow side of image stacks, making them resemble those acquired deeper into the volume and (ii) trains neural networks to reverse the effect of these aberrations.

A Type I Photosensitizer-Polymersome Boosts Reactive Oxygen Species Generation by Forcing H-Aggregation for Amplifying STING Immunotherapy.

Activation of the innate immune Stimulator of Interferon Genes (STING) pathway potentiates antitumor immunity. However, delivering STING agonists systemically to tumors presents a formidable challenge, and resistance to STING monotherapy has emerged in clinical trials with diminishing natural killer (NK) cell proliferation. Here, we encapsulated the STING agonist diABZI within polymersomes containing a Type I photosensitizer (NBS), creating a nanoagonist (PNBS/diABZI) for highly responsive tumor immunotherapy.

A radiomics-boosted deep-learning for risk assessment of synchronous peritoneal metastasis in colorectal cancer.

Objectives: Synchronous colorectal cancer peritoneal metastasis (CRPM) has a poor prognosis. This study aimed to create a radiomics-boosted deep learning model by PET/CT image for risk assessment of synchronous CRPM.

Methods: A total of 220 colorectal cancer (CRC) cases were enrolled in this study.

Three-dimensional spatio-angular fluorescence microscopy with a polarized dual-view inverted selective-plane illumination microscope (pol-diSPIM).

Polarized fluorescence microscopy is a valuable tool for measuring molecular orientations, but techniques for recovering three-dimensional orientations and positions of fluorescent ensembles are limited. We report a polarized dual-view light-sheet system for determining the and diffraction-limited positions of ensembles of fluorescent dipoles that label biological structures, and we share a set of visualization, histogram, and profiling tools for interpreting these positions and orientations. We model our samples, their excitation, and their detection using coarse-grained representations we call (ODFs).

Phase diversity-based wavefront sensing for fluorescence microscopy.

Fluorescence microscopy is an invaluable tool in biology, yet its performance is compromised when the wavefront of light is distorted due to optical imperfections or the refractile nature of the sample. Such optical aberrations can dramatically lower the information content of images by degrading image contrast, resolution, and signal. Adaptive optics (AO) methods can sense and subsequently cancel the aberrated wavefront, but are too complex, inefficient, slow, or expensive for routine adoption by most labs.

Deep learning-based aberration compensation improves contrast and resolution in fluorescence microscopy.

Optical aberrations hinder fluorescence microscopy of thick samples, reducing image signal, contrast, and resolution. Here we introduce a deep learning-based strategy for aberration compensation, improving image quality without slowing image acquisition, applying additional dose, or introducing more optics into the imaging path. Our method (i) introduces synthetic aberrations to images acquired on the shallow side of image stacks, making them resemble those acquired deeper into the volume and (ii) trains neural networks to reverse the effect of these aberrations.

3D-printed biomimetic scaffolds with precisely controlled and tunable structures guide cell migration and promote regeneration of osteochondral defect.

Untreated osteochondral defects will develop into osteoarthritis, affecting patients' quality of life. Since articular cartilage and subchondral bone exhibit distinct biological characteristics, repairing osteochondral defects remains a major challenge. Previous studies have tried to fabricate multilayer scaffolds with traditional methods or 3D printing technology.

Augmented Super-Resolution Radial Fluctuations (aSRRF) Pushing the Limits of Structured Illumination Microscopy.

Structured illumination microscopy (SIM) is a versatile super-resolution technique known for its compatibility with a wide range of probes and fast implementation. While 3D SIM is capable of achieving a spatial resolution of ∼120 nm laterally and ∼300 nm axially, attempting to further enhance the resolution through methods such as nonlinear SIM or 4-beam SIM introduces complexities in optical configurations, increased phototoxicity, and reduced temporal resolution. Here, we have developed a novel method that combines SIM with augmented super-resolution radial fluctuations (aSRRF) utilizing a single image through image augmentation.

Three-dimensional structured illumination microscopy with enhanced axial resolution.

The axial resolution of three-dimensional structured illumination microscopy (3D SIM) is limited to ∼300 nm. Here we present two distinct, complementary methods to improve axial resolution in 3D SIM with minimal or no modification to the optical system. We show that placing a mirror directly opposite the sample enables four-beam interference with higher spatial frequency content than 3D SIM illumination, offering near-isotropic imaging with ∼120-nm lateral and 160-nm axial resolution.

Incorporating the image formation process into deep learning improves network performance.

We present Richardson-Lucy network (RLN), a fast and lightweight deep learning method for three-dimensional fluorescence microscopy deconvolution. RLN combines the traditional Richardson-Lucy iteration with a fully convolutional network structure, establishing a connection to the image formation process and thereby improving network performance. Containing only roughly 16,000 parameters, RLN enables four- to 50-fold faster processing than purely data-driven networks with many more parameters.

Practical considerations for quantitative light sheet fluorescence microscopy.

Fluorescence microscopy has evolved from a purely observational tool to a platform for quantitative, hypothesis-driven research. As such, the demand for faster and less phototoxic imaging modalities has spurred a rapid growth in light sheet fluorescence microscopy (LSFM). By restricting the excitation to a thin plane, LSFM reduces the overall light dose to a specimen while simultaneously improving image contrast.

Multiscale fluorescence imaging of living samples.

Fluorescence microscopy is a highly effective tool for interrogating biological structure and function, particularly when imaging across multiple spatiotemporal scales. Here we survey recent innovations and applications in the relatively understudied area of multiscale fluorescence imaging of living samples. We discuss fundamental challenges in live multiscale imaging and describe successful examples that highlight the power of this approach.

The strategy for estrogen receptor mediated-risk assessment in environmental water: A combination of species sensitivity distributions and in silico approaches.

Risk assessment for molecular toxicity endpoints of environmental matrices may be a pressing issue. Here, we combined chemical analysis with species sensitivity distributions (SSD) and in silico docking for multi-species estrogen receptor mediated-risk assessment in water from Dongjiang River, China. The water contains high levels of phenolic endocrine-disrupting chemicals (PEDCs) and phthalic acid esters (PAEs).

Cytonemes coordinate asymmetric signaling and organization in the Drosophila muscle progenitor niche.

Asymmetric signaling and organization in the stem-cell niche determine stem-cell fates. Here, we investigate the basis of asymmetric signaling and stem-cell organization using the Drosophila wing-disc that creates an adult muscle progenitor (AMP) niche. We show that AMPs extend polarized cytonemes to contact the disc epithelial junctions and adhere themselves to the disc/niche.

Ecological and AhR-mediated risk assessment of polycyclic aromatic hydrocarbons and polybrominated diphenyl ethers on multiple aquatic species in river water: A combined chemical analysis and in silico approach.

Assessing the adverse health risks at molecular endpoints to various aquatic organisms could be an urgent issue. In this manuscript, the ecological and AhR-mediated risk of sixteen polycyclic aromatic hydrocarbons (PAHs) and six polybrominated diphenyl ethers (PBDEs) in surface water of Dongjiang River, Southern China was evaluated using chemical analysis and in silico approaches. Average concentrations of ∑PAHs and ∑PBDEs were 586.

Multiview confocal super-resolution microscopy.

Confocal microscopy remains a major workhorse in biomedical optical microscopy owing to its reliability and flexibility in imaging various samples, but suffers from substantial point spread function anisotropy, diffraction-limited resolution, depth-dependent degradation in scattering samples and volumetric bleaching. Here we address these problems, enhancing confocal microscopy performance from the sub-micrometre to millimetre spatial scale and the millisecond to hour temporal scale, improving both lateral and axial resolution more than twofold while simultaneously reducing phototoxicity. We achieve these gains using an integrated, four-pronged approach: (1) developing compact line scanners that enable sensitive, rapid, diffraction-limited imaging over large areas; (2) combining line-scanning with multiview imaging, developing reconstruction algorithms that improve resolution isotropy and recover signal otherwise lost to scattering; (3) adapting techniques from structured illumination microscopy, achieving super-resolution imaging in densely labelled, thick samples; (4) synergizing deep learning with these advances, further improving imaging speed, resolution and duration.

Differential adhesion regulates neurite placement via a retrograde zippering mechanism.

During development, neurites and synapses segregate into specific neighborhoods or layers within nerve bundles. The developmental programs guiding placement of neurites in specific layers, and hence their incorporation into specific circuits, are not well understood. We implement novel imaging methods and quantitative models to document the embryonic development of the brain neuropil and discover that differential adhesion mechanisms control precise placement of single neurites onto specific layers.

Interplay of Forces and the Immune Response for Functional Tendon Regeneration.

Tendon injury commonly occurs during sports activity, which may cause interruption or rapid decline in athletic career. Tensile strength, as one aspect of tendon biomechanical properties, is the main parameter of tendon function. Tendon injury will induce an immune response and cause the loss of tensile strength.

Three-dimensional residual channel attention networks denoise and sharpen fluorescence microscopy image volumes.

We demonstrate residual channel attention networks (RCAN) for the restoration and enhancement of volumetric time-lapse (four-dimensional) fluorescence microscopy data. First we modify RCAN to handle image volumes, showing that our network enables denoising competitive with three other state-of-the-art neural networks. We use RCAN to restore noisy four-dimensional super-resolution data, enabling image capture of over tens of thousands of images (thousands of volumes) without apparent photobleaching.

Lithography-Based 3D Bioprinting and Bioinks for Bone Repair and Regeneration.

The fabrication of scaffolds that precisely mimic the natural structure and physiochemical properties of bone is still one of the most challenging tasks in bone tissue engineering. 3D printing techniques have drawn increasing attention due to their ability to fabricate scaffolds with complex structures and multiple bioinks. For bone tissue engineering, lithography-based 3D bioprinting is frequently utilized due to its printing speed, mild printing process, and cost-effective benefits.

Structural and developmental principles of neuropil assembly in C. elegans.

Neuropil is a fundamental form of tissue organization within the brain, in which densely packed neurons synaptically interconnect into precise circuit architecture. However, the structural and developmental principles that govern this nanoscale precision remain largely unknown. Here we use an iterative data coarse-graining algorithm termed 'diffusion condensation' to identify nested circuit structures within the Caenorhabditis elegans neuropil, which is known as the nerve ring.

Rapid image deconvolution and multiview fusion for optical microscopy.

The contrast and resolution of images obtained with optical microscopes can be improved by deconvolution and computational fusion of multiple views of the same sample, but these methods are computationally expensive for large datasets. Here we describe theoretical and practical advances in algorithm and software design that result in image processing times that are tenfold to several thousand fold faster than with previous methods. First, we show that an 'unmatched back projector' accelerates deconvolution relative to the classic Richardson-Lucy algorithm by at least tenfold.

Author Correction: Faster, sharper, and deeper: structured illumination microscopy for biological imaging.

In the version of this Perspective originally published, Fig. 4g included an incorrect inset adapted from a different figure than the main image in the panel. This error has been corrected in the PDF and HTML versions of the paper.

Faster, sharper, and deeper: structured illumination microscopy for biological imaging.

Structured illumination microscopy (SIM) allows rapid, super-resolution (SR) imaging in live specimens. We review recent technical advances in SR-SIM, with emphasis on imaging speed, resolution, and depth. Since its introduction decades ago, the technique has grown to offer myriad implementations, each with its own strengths and weaknesses.

A Genetically Encoded Biosensor Strategy for Quantifying Non-muscle Myosin II Phosphorylation Dynamics in Living Cells and Organisms.

Complex cell behaviors require dynamic control over non-muscle myosin II (NMMII) regulatory light chain (RLC) phosphorylation. Here, we report that RLC phosphorylation can be tracked in living cells and organisms using a homotransfer fluorescence resonance energy transfer (FRET) approach. Fluorescent protein-tagged RLCs exhibit FRET in the dephosphorylated conformation, permitting identification and quantification of RLC phosphorylation in living cells.