The zebrafish intestine and liver, as in other vertebrates, are derived from the endoderm. Great effort has been devoted to deciphering the molecular mechanisms controlling the specification and development of the zebrafish intestine and liver; however, genome-wide comparison of the transcriptomes between these two organs at the larval stage remains unexplored. There is a lack of extensive identification of feature genes marking specific cell types in the zebrafish intestine and liver at 5 days post-fertilization, when the larval fish starts food intake. In this report, through RNA sequencing and single-cell RNA sequencing of intestines and livers separately dissected from wild-type zebrafish larvae at 5 days post-fertilization, together with the experimental validation of 47 genes through RNA whole-mount in situ hybridization, we identified not only distinctive transcriptomes for the larval intestine and liver, but also a considerable number of feature genes for marking the intestinal bulb, mid-intestine and hindgut, and for marking hepatocytes and cholangiocytes. Meanwhile, we identified 135 intestine- and 97 liver-enriched transcription factor genes in zebrafish larvae at 5 days post-fertilization. Our findings provide rich molecular and cellular resources for studying cell patterning and specification during the early development of the zebrafish intestine and liver.
Xeroderma pigmentosum complementation group C (XPC) protein recognizes bulky DNA adducts to initiate global genomic nucleotide excision repair (GG-NER). Humans carrying germline mutations in the XPC gene display strong susceptibility to skin and certain internal cancers. In addition to its role in NER, recent studies have indicated that XPC is also involved in other DNA damage repair pathways and transcription regulation. In this report, we generated a zebrafish xpc knockout mutant. Zebrafish xpc−/− mutant fish develop relative normally and are fertile. However, the mutant embryos were more sensitive to ultraviolet (UV) irradiation. Upon UV irradiation, compared with the wild type embryos, mutant embryos accumulated significantly higher levels of unrepaired DNA damages and apoptotic cells, which led to more severe abnormal development. Transcriptome analysis showed that the p53 signal pathway and apoptosis were enriched in the over upregulated genes in UV-irradiated mutant embryos, suggesting that high levels of unrepaired DNA lesions activated p53 to trigger apoptotic activity in mutant embryos. More interestingly, up to 972 genes in the untreated mutant embryos were differentially expressed, compared with those in the untreated WT. Among these differentially expressed genes (DEGs), 379 genes did not respond to UV irradiation, indicating that Xpc plays a role in addition of DNA damage repair. Our results demonstrate that Xpc is an evolutionally conserved factor in NER repair. Zebrafish xpc−/− mutant also provides a platform to study other functions of Xpc beyond the DNA damage repair.
Bruising is one of the main problems in the post-harvest grading and processing of ‘Zaozhong 6’ loquats, reducing the economic value of loquats, and even food quality and safety problems are caused by it. Therefore, one of the main tasks in the post-harvest processing of loquats is to detect whether loquats are bruised, as well as the degree of bruising of loquats, to reduce the loss by proper treatment. An appropriate dimensionality reduction method can be used to reduce the redundancy of variables and improve the detection speed. The multispectral analysis method (MAM) has the advantage of accurate, rapid, and nondestructive detection, which was proposed to identify the different bruising degrees of loquats in this study. Firstly, the visible and near-infrared region (Vis–NIR, 400–1000 nm), the visible region (Vis, 400–780 nm), and the near-infrared region (NIR, 781–1000 nm) were analyzed using principal component analysis (PCA) to obtain the spectral regions and PC vectors, which could be used to effectively distinguish bruised loquats from normal loquats. Then, based on the selected second PC (PC2) score images, a morphological segmentation method (MSM) was proposed to distinguish bruised loquats from normal loquats. Furthermore, the weight coefficients of corresponding wavelength points of different degrees of bruising of loquats were analyzed, and the local extreme points and both sides of the interval were selected as the characteristic wavelength points for multi-spectral image processing. A gray level co-occurrence matrix (GLCM) was used to extract texture features and gray information from two-band ratio images K782/999. Finally, the MAM was proposed to detect the degree of bruising of loquats, which included the spectral data of three characteristic wavelength points in the NIR region coupled with texture features of the two-band ratio images, and the classification accuracy was 91.3%. This study shows that the MAM can be used as an effective dimensionality reduction method. The method not only improves the effect of prediction but also simplifies the process of prediction and ensures the accuracy of classification. The MSM can be used for rapid detection of normal and bruised fruits, and the MAM can be used to classify the degree of bruising of bruised fruits. Consequently, the processed methods are effective and can be used for the rapid and nondestructive detection of the degree of bruising of fruit.
Background and objectives Skin defects are one of the primary problems that occur in post-harvest grading and processing of loquats. The loquats with skin defects will lead to the loquat being easily destroyed during transportation and storage, which will cause the risk of other loquats being infected, affecting the selling price of loquat. Materials and Methods In this paper, a method combining band radio image with improved three-phase level set segmentation algorithm (ITPLSSM) is proposed to achieve high accuracy, rapid, and non-destructive detection of skin defects of loquats. Principal component analysis (PCA) was used to find the characteristic wavelength and PC images to distinguish between four types of skin defects. Determine the best band ratio image based on characteristic wavelength. Results The band ratio image (Q782/944) based on PC2 image is the best segmented image. Based on Pseudo-color image enhancement, morphological processing, and local clustering criteria, the band ratio image (Q782/944) has better contrast between defective area and normal area in loquat. Finally, the ITPLSSM was used to segment the processing band ratio image (Q782/944), with the accuracy is 95.28 %. Conclusions The proposed ITPLSSM method is effective in distinguishing with four types of skin defects. Meanwhile, it also effectively segments the images with intensity inhomogeneities.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.