Real-Time analysis of exosome secretion of single cells with single molecule imaging

The exosome-mediated response can promote or restrain the diseases by regulating the intracellular pathways, making the exosome become an effective marker for diagnosis and therapeutic control at the single-cell level. However, real-time analysis is hard to be achieved with traditional approaches because the exosomes usually need to be enriched by ultracentrifugation for a measurable signal-to-noise ratio. Recently developed label-free single-molecule imaging approaches may become an real-time quantitative tool for the analysis of single exosomes and related secretion behaviors of single living cells owing to their extreme sensitivity.     

Stress field and damage evolution in C/SiC woven composites: Image-based finite element analysis and in situ X-ray computed tomography tests

The construction and examination of meso-structural finite element models of a Chemical-Vapor-Infiltrated (CVI) C/SiC composite is carried out based on X-ray microtomography digital images (IB-FEM). The accurate meso-structural features of the C/SiC composites, which are consisted of carbon fiber tows and CVI-SiC matrix, in particular the cavity defects, are reconstructed. With the IB-FEM, the damage evolution and fracture behaviors of the C/SiC composite are investigated. At the same time, an in situ tensile test is applied to the C/SiC composite under a CT real-time quantitative imaging system, aiming to investigate the damage and failure features of the material as well as to verify the IB-FEM. The IB-FEM results indicate that material damage initially occur at the defects, followed by propagating toward the fiber-tow/SiC-matrix interfaces, ultimately, combined into macro-cracks, which is in good agreement with the in situ CT experiment results.     

A Bio-Conjugated Fullerene as a Subcellular-Targeted and Multifaceted Phototheranostic Agent

Fullerenes are candidates for theranostic applications because of their high photodynamic activity and intrinsic multimodal imaging contrast. However, fullerenes suffer from low solubility in aqueous media, poor biocompatibility, cell toxicity, and a tendency to aggregate. C₇₀@lysozyme is introduced herein as a novel bioconjugate that is harmless to a cellular environment, yet is also photoactive and has excellent optical and optoacoustic contrast for tracking cellular uptake and intracellular localization. The formation, water-solubility, photoactivity, and unperturbed structure of C₇₀@lysozyme are confirmed using UV-visible and 2D ¹H, ¹⁵N NMR spectroscopy. The excellent imaging contrast of C₇₀@lysozyme in optoacoustic and third harmonic generation microscopy is exploited to monitor its uptake in HeLa cells and lysosomal trafficking. Last, the photoactivity of C₇₀@lysozyme and its ability to initiate cell death by means of singlet oxygen (¹O₂) production upon exposure to low levels of white light irradiation is demonstrated. This study introduces C₇₀@lysozyme and other fullerene-protein conjugates as potential candidates for theranostic applications.     

Organic Semiconducting Luminophores for Near-Infrared Afterglow,Chemiluminescence, and Bioluminescence Imaging

Optical imaging has played a pivotal role in deciphering in vivo bioinformatics but is limited by shallow penetration depth and poor imaging performance owing to interfering tissue autofluorescence induced by concurrent photoexcitation. The emergence of near-infrared (NIR) self-luminescence imaging independent of real-time irradiation has timely addressed these problems. There are two main kinds of self-luminescent agents, namely inorganic and organic luminophores. Inorganic luminophores usually suffer from long-term biotoxicity concerns resulting from potential heavy-metal ions leakage and nonbiodegradability, which hinders their further translational application. In contrast, organic luminophores, especially organic semiconducting luminophores (OSLs) with good biodegradable potential, tunable design, and outstanding optical properties, are preferred in biological applications. This review summarizes the recent progress of OSLs used in NIR afterglow, chemiluminescence, and bioluminescence imaging. Molecular manipulation and nanoengineering approaches of OSLs are discussed, with emphasis on strategies that can extend the emission wavelength from visible to NIR range and amplify luminescence signals. This review concludes with a discussion of current challenges and possible solutions of OSLs in the self-luminescence field.     

Preclinical Evaluation of 99mTc-ZHER2:41071, a Second-Generation Affibody-Based HER2-Visualizing Imaging Probe with a Low Renal Uptake

Radionuclide imaging of HER2 expression in tumours may enable stratification of patients with breast, ovarian, and gastroesophageal cancers for HER2-targeting therapies. A first-generation HER2-binding affibody molecule [^99mTc]Tc-ZHER2:V2 demonstrated favorable imaging properties in preclinical studies. Thereafter, the affibody scaffold has been extensively modified, which increased its melting point, improved storage stability, and increased hydrophilicity of the surface. In this study, a second-generation affibody molecule (designated ZHER2:41071) with a new improved scaffold has been prepared and characterized. HER2-binding, biodistribution, and tumour-targeting properties of [^99mTc]Tc-labelled ZHER2:41071 were investigated. These properties were compared with properties of the first-generation affibody molecules, [^99mTc]Tc-ZHER2:V2 and [^99mTc]Tc-ZHER2:2395. [^99mTc]Tc-ZHER2:41071 bound specifically to HER2 expressing cells with an affinity of 58 ± 2 pM. The renal uptake for [^99mTc]Tc-ZHER2:41071 and [^99mTc]Tc-ZHER2:V2 was 25–30 fold lower when compared with [^99mTc]Tc-ZHER2:2395. The uptake in tumour and kidney for [^99mTc]Tc-ZHER2:41071 and [^99mTc]Tc-ZHER2:V2 in SKOV-3 xenografts was similar. In conclusion, an extensive re-engineering of the scaffold did not compromise imaging properties of the affibody molecule labelled with ^99mTc using a GGGC chelator. The new probe, [^99mTc]Tc-ZHER2:41071 provided the best tumour-to-blood ratio compared to HER2-imaging probes for single photon emission computed tomography (SPECT) described in the literature so far. [^99mTc]Tc-ZHER2:41071 is a promising candidate for further clinical translation studies.     

Display illumination with modulated directional backlight

Illumination is essential for modern life as colorful world is perceived by human visionary system. Display technology has been developing rapidly in recent decades, and the basic principle is related to the way that the image is illuminated and light is emanated. Traditional illumination is provided by different types of light sources, and the display image is visible in large viewing space until the emanating light decays to zero. This work proposes and demonstrates a novel illumination scheme for a display in which the displaying images are visible only in specific spatial regions. The directional backlight ensures the image propagating to specific direction while imaging visibility can be controlled to terminate abruptly at certain distance from the display screen while exerting no influence to nearby regions. The working principle for such an illumination scheme is the use of the modulated coherent directional backlight through an axicon lens. It is shown that the illumination scheme can robustly deliver carried image information to the designated viewing region. This new illumination scheme has many advantages over conventional illumination, including its usage for personal display, very lower energy consumption, as well as minimizing light hazard pollution.     

Retinal microaneurysms detection using adversarial pre-training with unlabeled multimodal images

The detection of retinal microaneurysms is crucial for the early detection of important diseases such as diabetic retinopathy. However, the detection of these lesions in retinography, the most widely available retinal imaging modality, remains a very challenging task. This is mainly due to the tiny size and low contrast of the microaneurysms in the images. Consequently, the automated detection of microaneurysms usually relies on extensive ad-hoc processing. In this regard, although microaneurysms can be more easily detected using fluorescein angiography, this alternative imaging modality is invasive and not adequate for regular preventive screening.In this work, we propose a novel deep learning methodology that takes advantage of unlabeled multimodal image pairs for improving the detection of microaneurysms in retinography. In particular, we propose a novel adversarial multimodal pre-training consisting in the prediction of fluorescein angiography from retinography using generative adversarial networks. This pre-training allows learning about the retina and the microaneurysms without any manually annotated data. Additionally, we also propose to approach the microaneurysms detection as a heatmap regression, which allows an efficient detection and precise localization of multiple microaneurysms. To validate and analyze the proposed methodology, we perform an exhaustive experimentation on different public datasets. Additionally, we provide relevant comparisons against different state-of-the-art approaches. The results show a satisfactory performance of the proposal, achieving an Average Precision of 64.90%, 31.36%, and 33.55% in the E-Ophtha, ROC, and DDR public datasets. Overall, the proposed approach outperforms existing deep learning alternatives while providing a more straightforward detection method that can be effectively applied to raw unprocessed retinal images.     

Improving accuracy of automatic optical inspection with machine learning

Electronic devices require the printed circuit board(PCB)to support the whole structure,but the assembly of PCBs suffers from welding problem of the electronic components such as surface mounted devices(SMDs)resistors.The automated optical inspection(AOI)machine,widely used in industrial production,can take the image of PCBs and examine the welding issue.However,the AOI machine could commit false negative errors and dedicated technicians have to be employed to pick out those misjudged PCBs.This paper proposes a machine learning based method to improve the accuracy of AOI.In particular,we propose an adjacent pixel RGB value based method to pre-process the image from the AOI machine and build a customized deep learning model to classify the image.We present a practical scheme including two machine learning procedures to mitigate AOI errors.We conduct experiments with the real dataset from a production line for three months,the experimental results show that our method can reduce the rate of misjudgment from 0.3%–0.5%to 0.02%–0.03%,which is meaningful for thousands of PCBs each containing thousands of electronic components in practice.     

Fabrication of high-efficiency Yb:Y2O3 laser ceramics without photodarkening

High-efficiency Yb:Y₂O₃ laser ceramics were fabricated using the vacuum-sintering plus hot isostatic pressing (HIP) without sintering additives. High-purity well-dispersed nanocrystalline Yb:Y₂O₃ powder was synthesized using a modified co-precipitation method in-house. The green bodies were first vacuum sintered at a temperature as low as 1430°C and then HIPed at 1450°C. Finally, the samples were air annealed at 800°C for 10 h. Although no sintering aids were used, full density of the samples with excellent optical homogeneity and an inline transmission of 80% at 400 nm could be obtained. Moreover, photodarkening phenomenon was not detected in the ceramics. Preliminary laser experiment with the fabricated ceramics in a two-mirror cavity has demonstrated 32 W continuous-wave (CW) output at ∼1077 nm with an optical-to-optical conversion efficiency of 58.2%. To the best of our knowledge, this is so far the highest CW output power and optical-to-optical conversion efficiency achieved with the Yb³⁺-doped sesquioxide ceramics in a simple two-mirror cavity.