Broadband nonlinear modulation of incoherent light using a transparent optoelectronic neuron array

Nonlinear optical processing of ambient natural light is highly desired in computational imaging and sensing applications. A strong optical nonlinear response that can work under weak broadband incoherent light is essential for this purpose. Here we introduce an optoelectronic nonlinear filter array that can address this emerging need. By merging 2D transparent phototransistors (TPTs) with liquid crystal (LC) modulators, we create an optoelectronic neuron array that allows self-amplitude modulation of spatially incoherent light, achieving a large nonlinear contrast over a broad spectrum at orders-of-magnitude lower intensity than what is achievable in most optical nonlinear materials. For a proof-of-concept demonstration, we fabricated a 10,000-pixel array of optoelectronic neurons, each serving as a nonlinear filter, and experimentally demonstrated an intelligent imaging system that uses the nonlinear response to instantly reduce input glares while retaining the weaker-intensity objects within the field of view of a cellphone camera. This intelligent glare-reduction capability is important for various imaging applications, including autonomous driving, machine vision, and security cameras. Beyond imaging and sensing, this optoelectronic neuron array, with its rapid nonlinear modulation for processing incoherent broadband light, might also find applications in optical computing, where nonlinear activation functions that can work under ambient light conditions are highly sought.Comment: 20 Pages, 5 Figure

Hydrophilic nanofibers with aligned topography modulate macrophage-mediated host responses via the NLRP3 inflammasome

Abstract Successful biomaterial implantation requires appropriate immune responses. Macrophages are key mediators involved in this process. Currently, exploitation of the intrinsic properties of biomaterials to modulate macrophages and immune responses is appealing. In this study, we prepared hydrophilic nanofibers with an aligned topography by incorporating polyethylene glycol and polycaprolactone using axial electrospinning. We investigated the effect of the nanofibers on macrophage behavior and the underlying mechanisms. With the increase of hydrophilicity of aligned nanofibers, the inflammatory gene expression of macrophages adhering to them was downregulated, and M2 polarization was induced. We further presented clear evidence that the inflammasome NOD-like receptor thermal protein domain associated protein 3 (NLRP3) was the cellular sensor by which macrophages sense the biomaterials, and it acted as a regulator of the macrophage-mediated response to foreign bodies and implant integration. In vivo, we showed that the fibers shaped the implant-related immune microenvironment and ameliorated peritendinous adhesions. In conclusion, our study demonstrated that hydrophilic aligned nanofibers exhibited better biocompatibility and immunological properties

D-LMBmap: a fully automated deep-learning pipeline for whole-brain profiling of neural circuitry.

Acknowledgements: This work was supported by the Medical Research Council, as part of United Kingdom Research and Innovation (UK Research and Innovation) (MC_UP_1201/22). For the purpose of open access, the Medical Research Council Laboratory of Molecular Biology has applied a CC BY public copyright license to any Author Accepted Manuscript version arising. This work was also partially funded by NARSAD Young Investigator Award (2020, BBRF) to J.R. and Ministry of Science and Technology (2022ZD0206700) and the Beijing Municipal Government of P.R.C. to R.L. We thank D. Friedmann for advice on Adipo-Clear, J. Kebschull and D. Friedmann for data sharing, and L. Luo, M. Hastings, A.M.J. Adams and J. Song for critique on the manuscript.Funder: Medical Research Council, as part of the United Kingdom Research and Innovation, MC_UP_1201/22Recent proliferation and integration of tissue-clearing methods and light-sheet fluorescence microscopy has created new opportunities to achieve mesoscale three-dimensional whole-brain connectivity mapping with exceptionally high throughput. With the rapid generation of large, high-quality imaging datasets, downstream analysis is becoming the major technical bottleneck for mesoscale connectomics. Current computational solutions are labor intensive with limited applications because of the exhaustive manual annotation and heavily customized training. Meanwhile, whole-brain data analysis always requires combining multiple packages and secondary development by users. To address these challenges, we developed D-LMBmap, an end-to-end package providing an integrated workflow containing three modules based on deep-learning algorithms for whole-brain connectivity mapping: axon segmentation, brain region segmentation and whole-brain registration. D-LMBmap does not require manual annotation for axon segmentation and achieves quantitative analysis of whole-brain projectome in a single workflow with superior accuracy for multiple cell types in all of the modalities tested

Broadband nonlinear modulation of incoherent light using a transparent optoelectronic neuron array.

Nonlinear optical processing of ambient natural light is highly desired for computational imaging and sensing. Strong optical nonlinear response under weak broadband incoherent light is essential for this purpose. By merging 2D transparent phototransistors (TPTs) with liquid crystal (LC) modulators, we create an optoelectronic neuron array that allows self-amplitude modulation of spatially incoherent light, achieving a large nonlinear contrast over a broad spectrum at orders-of-magnitude lower intensity than achievable in most optical nonlinear materials. We fabricated a 10,000-pixel array of optoelectronic neurons, and experimentally demonstrated an intelligent imaging system that instantly attenuates intense glares while retaining the weaker-intensity objects captured by a cellphone camera. This intelligent glare-reduction is important for various imaging applications, including autonomous driving, machine vision, and security cameras. The rapid nonlinear processing of incoherent broadband light might also find applications in optical computing, where nonlinear activation functions for ambient light conditions are highly sought