FRaeppli, a multispectral imaging toolbox for cell tracing and dense tissue analysis in zebrafish

Visualizing cell shapes, interactions and lineages of differentiating cells is instrumental for understanding organ development and repair. Across species, strategies for stochastic multicolour labelling have greatly facilitated tracking cells in in vivo and mapping neuronal connectivity. Nevertheless, integrating multi-fluorophore information into the context of developing tissues in zebrafish is challenging given their cytoplasmic localization and spectral incompatibility with commonly used fluorescent markers. Here, we developed FRaeppli (Fish-Raeppli) expressing bright membrane- or nuclear-targeted fluorescent proteins for efficient cell shape analysis and tracking. High spatiotemporal activation flexibility is provided by the Gal4/UAS system together with Cre/lox and/or PhiC31integrase. The distinct spectra of the FRaeppli fluorescent proteins allow simultaneous imaging with GFP and infrared subcellular reporters or tissue landmarks. By tailoring hyperspectral protocols for time-efficient acquisition, we demonstrate FRaeppli s suitability for live imaging of complex internal organs, like the liver. Combining FRaeppli with polarity markers revealed previously unknown canalicular topologies between differentiating hepatocytes, reminiscent of the mammalian liver, suggesting shared developmental mechanisms. The multispectral FRaeppli toolbox thus enables the comprehensive analysis of intricate cellular morphologies, topologies and tissue lineages at single-cell resolution in zebrafish.

Multispectral Imaging Using Fluorescent Properties of Indocyanine Green and Methylene Blue in Colorectal Surgery—Initial Experience

Introduction: Image-guided surgery is becoming a new tool in colorectal surgery. Intraoperative visualisation of different structures using fluorophores helps during various steps of operations. In our report, we used two fluorophores—indocyanine green (ICG), and methylene blue (MB)—during different steps of colorectal surgery, using one camera system for two separate near-infrared wavelengths. Material and methods: Twelve patients who underwent complex open or laparoscopic colorectal surgeries were enrolled. Intravenous injections of MB and ICG at different time points were administered. Visualisation of intraoperative ureter position and fluorescent angiography for optimal anastomosis was performed. A retrospective analysis of patients treated in our departments during 2020 was performed, and data about ureter injury and anastomotic site complications were collected. Results: Intraoperative localisation of ureters with MB under fluorescent light was possible in 11 patients. The mean signal-to-background ratio was 1.58 ± 0.71. Fluorescent angiography before performing anastomosis using ICG was successful in all 12 patients, and none required a change in position of the planned colon resection for anastomosis. The median signal-to-background ratios was 1.25 (IQR: 1.22–1.89). Across both centres, iatrogenic injury of the ureter was found in 0.4% of cases, and complications associated with anastomosis was found in 5.5% of cases. Conclusions: Our study showed a substantial opportunity for using two different fluorophores in colorectal surgery, whereby the visualisation of one will not change the possible quantification analysis of the other. Using two separate dyes during one procedure may help in optimisation of the fluorescent properties of both dyes when using them for different applications. Visualisation of different structures by different fluorophores seems to be the future of image-guided surgery, and shows progress in optical technologies used in image-guided surgery.

Improve Soybean Variety Selection Accuracy Using UAV-Based High-Throughput Phenotyping Technology

The efficiency of crop breeding programs is evaluated by the genetic gain of a primary trait of interest, e.g., yield, achieved in 1 year through artificial selection of advanced breeding materials. Conventional breeding programs select superior genotypes using the primary trait (yield) based on combine harvesters, which is labor-intensive and often unfeasible for single-row progeny trials (PTs) due to their large population, complex genetic behavior, and high genotype-environment interaction. The goal of this study was to investigate the performance of selecting superior soybean breeding lines using image-based secondary traits by comparing them with the selection of breeders. A total of 11,473 progeny rows (PT) were planted in 2018, of which 1,773 genotypes were selected for the preliminary yield trial (PYT) in 2019, and 238 genotypes advanced for the advanced yield trial (AYT) in 2020. Six agronomic traits were manually measured in both PYT and AYT trials. A UAV-based multispectral imaging system was used to collect aerial images at 30 m above ground every 2 weeks over the growing seasons. A group of image features was extracted to develop the secondary crop traits for selection. Results show that the soybean seed yield of the selected genotypes by breeders was significantly higher than that of the non-selected ones in both yield trials, indicating the superiority of the breeder's selection for advancing soybean yield. A least absolute shrinkage and selection operator model was used to select soybean lines with image features and identified 71 and 76% of the selection of breeders for the PT and PYT. The model-based selections had a significantly higher average yield than the selection of a breeder. The soybean yield selected by the model in PT and PYT was 4 and 5% higher than those selected by breeders, which indicates that the UAV-based high-throughput phenotyping system is promising in selecting high-yield soybean genotypes.

Multispectral Image under Tissue Classification Algorithm in Screening of Cervical Cancer

The objectives of this study were to improve the efficiency and accuracy of early clinical diagnosis of cervical cancer and to explore the application of tissue classification algorithm combined with multispectral imaging in screening of cervical cancer. 50 patients with suspected cervical cancer were selected. Firstly, the multispectral imaging technology was used to collect the multispectral images of the cervical tissues of 50 patients under the conventional white light waveband, the narrowband green light waveband, and the narrowband blue light waveband. Secondly, the collected multispectral images were fused, and then the tissue classification algorithm was used to segment the diseased area according to the difference between the cervical tissues without lesions and the cervical tissues with lesions. The difference in the contrast and other characteristics of the multiband spectrum fusion image would segment the diseased area, which was compared with the results of the disease examination. The average gradient, standard deviation (SD), and image entropy were adopted to evaluate the image quality, and the sensitivity and specificity were selected to evaluate the clinical application value of discussed method. The fused spectral image was compared with the image without lesions, it was found that there was a clear difference, and the fused multispectral image showed a contrast of 0.7549, which was also higher than that before fusion (0.4716), showing statistical difference ( P < 0.05 ). The average gradient, SD, and image entropy of the multispectral image assisted by the tissue classification algorithm were 2.0765, 65.2579, and 4.974, respectively, showing statistical difference ( P < 0.05 ). Compared with the three reported indicators, the values of the algorithm in this study were higher. The sensitivity and specificity of the multispectral image with the tissue classification algorithm were 85.3% and 70.8%, respectively, which were both greater than those of the image without the algorithm. It showed that the multispectral image assisted by tissue classification algorithm can effectively screen the cervical cancer and can quickly, efficiently, and safely segment the cervical tissue from the lesion area and the nonlesion area. The segmentation result was the same as that of the doctor's disease examination, indicating that it showed high clinical application value. This provided an effective reference for the clinical application of multispectral imaging technology assisted by tissue classification algorithm in the early screening and diagnosis of cervical cancer.

Van der Waals two-color infrared photodetector

With the increasing demand for multispectral information acquisition, infrared multispectral imaging technology that is inexpensive and can be miniaturized and integrated into other devices has received extensive attention. However, the widespread usage of such photodetectors is still limited by the high cost of epitaxial semiconductors and complex cryogenic cooling systems. Here, we demonstrate a noncooled two-color infrared photodetector that can provide temporal-spatial coexisting spectral blackbody detection at both near-infrared and mid-infrared wavelengths. This photodetector consists of vertically stacked back-to-back diode structures. The two-color signals can be effectively separated to achieve ultralow crosstalk of ~0.05% by controlling the built-in electric field depending on the intermediate layer, which acts as an electron-collecting layer and hole-blocking barrier. The impressive performance of the two-color photodetector is verified by the specific detectivity (D*) of 6.4 × 109 cm Hz1/2 W−1 at 3.5 μm and room temperature, as well as the promising NIR/MWIR two-color infrared imaging and absolute temperature detection.

Smart Farming enabled by IoT and Spectral Imaging

Smart Farming System is an emerging concept which utilizes sensors in the field enabled through IoT to get live data from the farm. This paper aims at developing such a Smart Farming system using the highly advanced technology of Texas instruments microcontrollers, MSP430 and TIVA C Series TM4C1294. Along with IoT the system uses Multispectral Imaging in conjunction with Wireless Soil Embedded Sensor Networks. The goal of the system is to provide reliable live data which is obtained from the multiple sensor nodes placed throughout the farm, that use the sink nodes to transfer the data to the cloud. The farmer can access this data using the Blynk Mobile app and can thus take further calculated actions towards maintaining the farm and further monitor the soil/crop health to increase the ultimate yield from his farm.

Multispectral Imaging Algorithm Predicts Breslow Thickness of Melanoma

Breslow thickness is a major prognostic factor for melanoma. It is based on histopathological evaluation, and thus it is not available to aid clinical decision making at the time of the initial melanoma diagnosis. In this work, we assessed the efficacy of multispectral imaging (MSI) to predict Breslow thickness and developed a classification algorithm to determine optimal safety margins of the melanoma excision. First, we excluded nevi from the analysis with a novel quantitative parameter. Parameter s’ could differentiate nevi from melanomas with a sensitivity of 89.60% and specificity of 88.11%. Following this step, we have categorized melanomas into three different subgroups based on Breslow thickness (≤1 mm, 1–2 mm and >2 mm) with a sensitivity of 78.00% and specificity of 89.00% and a substantial agreement (κ = 0.67; 95% CI, 0.58–0.76). We compared our results to the performance of dermatologists and dermatology residents who assessed dermoscopic and clinical images of these melanomas, and reached a sensitivity of 60.38% and specificity of 80.86% with a moderate agreement (κ = 0.41; 95% CI, 0.39–0.43). Based on our findings, this novel method may help predict the appropriate safety margins for curative melanoma excision.

Conventional histological and cytological staining with simultaneous immunohistochemistry enabled by invisible chromogens

Conventional histological stains, such as hematoxylin plus eosin (H&E), and immunohistochemistry (IHC) are mainstays of histology that provide complementary diagnostic information. H&E and IHC currently require separate slides, because the stains would otherwise obscure one another. This consumes small specimen, limiting the total amount of testing. Additionally, performing H&E and IHC on different slides does not permit comparison of staining at the single cell level, since the same cells are not present on each slide, and alignment of tissue features can be problematic due to changes in tissue landscape with sectioning. We have solved these problems by performing conventional staining and IHC on the same slide using invisible IHC chromogens, such that the chromogens are not visible when viewing the conventional stain and the conventional stain is excluded from images of the IHC. Covalently deposited chromogens provided a convenient route to invisible chromogen design and are stable to reagents used in conventional staining. A dual-camera brightfield microscope system was developed that permits simultaneous viewing of both visible conventional stains and invisible IHC chromogens. Simultaneous staining was demonstrated on several formalin-fixed paraffin-embedded tissue specimens using single and duplex IHC, with chromogens that absorb ultraviolet and near infrared light, followed by H&E staining. The concept was extended to other conventional stains, including mucicarmine special stain and Papanicoulou stain, and further extended to cytology specimens. In addition to interactive video review, images were recorded using multispectral imaging and image processing to provide flexible production of color composite images and enable quantitative analysis.