High-fidelity and high-speed wavefront shaping by leveraging complex media.

High-precision light manipulation is crucial for delivering information through complex media. However, existing spatial light modulation devices face a fundamental speed-fidelity tradeoff. Digital micromirror devices have emerged as a promising candidate for high-speed wavefront shaping but at the cost of compromised fidelity due to the limited control degrees of freedom. Here, we leverage the sparse-to-random transformation through complex media to overcome the dimensionality limitation of spatial light modulation devices. We demonstrate that pattern compression by sparsity-constrained wavefront optimization allows sparse and robust wavefront representations in complex media, improving the projection fidelity without sacrificing frame rate, hardware complexity, or optimization time. Our method is generalizable to different pattern types and complex media, supporting consistent performance with up to 89% and 126% improvements in projection accuracy and speckle suppression, respectively. The proposed optimization framework could enable high-fidelity high-speed wavefront shaping through different scattering media and platforms without changes to the existing holographic setups, facilitating a wide range of physics and real-world applications.

Spectral-temporal-spatial customization via modulating multimodal nonlinear pulse propagation.

Multimode fibers (MMFs) are gaining renewed interest for nonlinear effects due to their high-dimensional spatiotemporal nonlinear dynamics and scalability for high power. High-brightness MMF sources with effective control of the nonlinear processes would offer possibilities in many areas from high-power fiber lasers, to bioimaging and chemical sensing, and to intriguing physics phenomena. Here we present a simple yet effective way of controlling nonlinear effects at high peak power levels. This is achieved by leveraging not only the spatial but also the temporal degrees of freedom during multimodal nonlinear pulse propagation in step-index MMFs, using a programmable fiber shaper that introduces time-dependent disorders. We achieve high tunability in MMF output fields, resulting in a broadband high-peak-power source. Its potential as a nonlinear imaging source is further demonstrated through widely tunable two-photon and three-photon microscopy. These demonstrations provide possibilities for technology advances in nonlinear optics, bioimaging, spectroscopy, optical computing, and material processing.

Roadmap on Deep Learning for Microscopy.

Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep neural networks, and machine learning are all niche terms describing computational methods that have gained a pivotal role in microscopy-based research over the past decade. This Roadmap is written collectively by prominent researchers and encompasses selected aspects of how machine learning is applied to microscopy image data, with the aim of gaining scientific knowledge by improved image quality, automated detection, segmentation, classification and tracking of objects, and efficient merging of information from multiple imaging modalities. We aim to give the reader an overview of the key developments and an understanding of possibilities and limitations of machine learning for microscopy. It will be of interest to a wide cross-disciplinary audience in the physical sciences and life sciences.

Three-stage full-wave simulation architecture for in-depth analysis of microspheres in microscopy.

Over a decade, considerable development has been achieved in microsphere microscopy; the popularity of this method is attributable to its compatibility with biomedical applications. Although microscopy has been used extensively, insufficient analyses and simulation approaches capable of explaining the experimental observations have hampered its theoretical development. In this paper, a three-stage full-wave simulation architecture has been presented for the in-depth analysis of the imaging properties of microspheres. This simulation architecture consists of forward and backward propagation mechanisms, following the concept of geometric optics and strictly complying to wave optics at each stage. Three numerical simulation methods, including FDTD, NTFF, and ASPW, are integrated into this simulation architecture to encompass near-field and far-field behaviors and relieve the computational burden. We validated this architecture by comparing our simulation results with the experimental data provided in literature. The results confirmed that the proposed architecture exhibits high consistency both qualitatively and quantitatively. By using this architecture, we demonstrated the near-field effect of the samples on the resolution and provided evidence to explain the conflicts in literature. Moreover, the flexibility and versatility of the proposed architecture in modeling allow adaptation to various scenarios in microsphere microscopy. The results of this study, as an imaging analysis and system design platform, may facilitate the development of microsphere microscopy for biomedical imaging, wafer inspection, and other potential applications.

Comparative effects of bone marrow mesenchymal stem cells on lipopolysaccharide-induced microglial activation.

After injury to the CNS, microglia are rapidly activated and concentrated and trigger inflammatory reaction at the sites of injury. Bone marrow mesenchymal stem cells (BMMSC) represent attractive cell sources for treating CNS injury. Although anti-inflammatory and paracrine effects of grafted BMMSC have been shown, direct modulation of BMMSC on microglia in situ remains unclear. The present work employs in vitro transwell assay to characterize the effects of BMMSC on LPS-stimulated microglia. BMMSC are cultivated in serum and serum-free (sf) conditions, namely, BMMSC and BMMSC-sf. Both cultures express major surface markers specific for mesenchymal stem cells. However, the BMMSC-sf exhibit sphere-like structure with reduced expression of two adherent cell markers, CD29 and CD90. Compared to BMMSC-sf, BMMSC are fibroblast like and have faster differentiation potential into neural-like cells. Furthermore, BMMSC release significant levels of TIMP-1 and VEGF, regardless of being alone or in coculture. The downregulated MMP-9 mRNA may be caused by TIMP-1 secretion from BMMSC. Our cell culture system provides a powerful tool for investigating the molecular and cellular changes in microglia-BMMSC cocultures.