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Copyright of Fudan University Journal of Medical Sciences is the property of Fudan University Journal of Medical Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[Objective] Trehalase (Tre) is a key enzyme in trehalose metabolism of Conopomorpha sinensis Bradley, which plays an important role in energy metabolism and growth development by specifically hydrolyzing trehalose into glucose. The study aims to clone two trehalase genes (CsTre1 and CsTre2) from Conopomorpha sinensis Bradley, to clarify its expression patterns in different developmental stages and tissues, and to analyze the molecular characteristics of the two genes and their enzyme proteins.[Method] Based on the transcriptome data of C. sinensis, the full-length cDNA sequences of CsTre1 and CsTre2 were cloned with the rapid amplification of cDNA ends (RACE)-PCR. Bioinformatics analysis was performed with software such as ORF Finder, ProtParam, SignalP 4.1, ProtScale, NetPhos2.0 Server and IQ TREE. The mRNA expression patterns of CsTre1 and CsTre2 in different developmental stages and tissues of C. sinensis were detected by using real-time quantitative PCR (RT-qPCR).[Result] The open reading frame of CsTre1 was 1 701 bp, encoding 566 amino acids, and the protein molecular weight was 64.53 kD. The open reading frame length of CsTre2 was 1 821 bp, encoding 606 amino acids, and the protein molecular weight was 69.08 kD. Signal peptide prediction analysis showed that both front-ends of CsTre1 and CsTre2 had a signal peptide, with positions of 1-16 and 1-17, respectively. The analysis on the secondary structure of the sequence showed that both CsTre1 and CsTre2 were mainly composed of α-helix and random coil, CsTre1 had 24 Sers, 15 Tyrs, and 10 Thrs that may serve as binding sites for protein kinases, while CsTre2 had 27 Sers, 10 Tyrs, and 13 Thrs that may serve as binding sites for protein kinases. The RT-qPCR results revealed that CsTre was expressed throughout all developmental stages of C. sinensis. In the expression pattern of adult stage, the expression level of CsTre1 was much higher than that of CsTre2, and the expression level of male adults of CsTre1 dropped sharply after the fourth day.[Conclusion] The study successfully cloned two trehalose genes of Conopomorpha sinensis Bradley. According to the results of analysis on their molecular characteristics and expression patterns, CsTre1 may be the main gene regulating trehalose metabolism in Conopomorpha sinensis Bradley. The research results provide important clues for elucidating the function of trehalase genes, which lay a solid foundation for the development pest control strategies. [ABSTRACT FROM AUTHOR]

[Significance] The crop phenotype is the visible result of the complex interplay between crop genes and the environment. It reflects the physiological, ecological, and dynamic aspects of crop growth and development, serving as a critical component in the realm of advanced breeding techniques. By systematically analyzing crop phenotypes, researchers can gain valuable insights into gene function and identify genetic factors that influence important crop traits. This information can then be leveraged to effectively harness germplasm resources and develop breakthrough varieties. Utilizing data-driven, intelligent, dynamic, and non-invasive methods for measuring crop phenotypes allows researchers to accurately capture key growth traits and parameters, providing essential data for breeding and selecting superior crop varieties throughout the entire growth cycle. This article provides an overview of intelligent identification technologies for crop agronomic traits and morphological structural phenotypes. [Progress] Crop phenotype acquisition equipment serves as the essential foundation for acquiring, analyzing, measuring, and identifying crop phenotypes. This equipment enables detailed monitoring of crop growth status. The article presents an overview of the functions, performance, and applications of the leading high-throughput crop phenotyping platforms, as well as an analysis of the characteristics of various sensing and imaging devices used to obtain crop phenotypic information. The rapid advancement of high-throughput crop phenotyping platforms and sensory imaging equipment has facilitated the integration of cutting-edge imaging technology, spectroscopy technology, and deep learning algorithms. These technologies enable the automatic and high-throughput acquisition of yield, resistance, quality, and other relevant traits of large-scale crops, leading to the generation of extensive multi-dimensional, multiscale, and multi-modal crop phenotypic data. This advancement supports the rapid progression of crop phenomics. The article also discusses the research progress of intelligent recognition technologies for agronomic traits such as crop plant height acquisition, crop organ detection, and counting, as well as crop ideotype recognition, crop morphological information measurement, and crop three-dimensional reconstruction for morphological structure intelligent recognition. Furthermore, this article outlines the main challenges faced in this field, including: difficulties in data collection in complex environments, high requirements for data scale, diversity, and preprocessing, the need to improve the lightweight nature and generalization ability of models, as well as the high cost of data collection equipment and the need to enhance practicality. [Conclusions and Prospects] Finally, this article puts forward the development directions of crop phenotype intelligent recognition technology, including: developing new and low cost intelligent field equipment for acquiring and analyzing crop phenotypes, enhancing the standardization and consistency of field crop phenotype acquisition, strengthening the generality of intelligent crop phenotype recognition models, researching crop phenotype recognition methods that involve multi-perspective, multimodal, multi-point continuous analysis, and spatiotemporal feature fusion, as well as improving model interpretability. [ABSTRACT FROM AUTHOR]

Objective To evaluate the imaging characteristics of congenital portosystemic shunt (PSS) in children. Methods Data of children diagnosed with congenital PSS during Mar 2008 to Dec 2022 in Children’s Hospital of Fudan University were collected. The clinical and imaging findings were retrospectively analyzed. The morphology of the portal vein and its branches, the route of PSS, and the distribution of collateral vessels were observed by two radiologists independently. Results Twenty-six children with congenital PSS were enrolled. CTA showed extrahepatic PSS in 16 cases (Ⅰb=4，Ⅱ=12), draining into inferior vena cava in 2 cases, left renal vein in 5 cases, internal iliac vein in 6 cases, and gastric coronary vein in 3 cases. The patients with shunts into internal iliac vein and gastric coronary vein all presented with upper or lower gastrointestinal bleeding.The remaining 10 cases were intrahepatic PSS (Ⅰ= 5，Ⅱ=2，Ⅲ=2 and Ⅳ=1). The development of portal vein and intrahepatic branches were normal. Two cases of extrahepatic type Ⅱ diagnosed by digital subtraction angiography (DSA) were misdiagnosed as extrahepatic type Ⅰb, because the CTA did not clearly show the branches of the intrahepatic portal vein. Two children with extrahepatic PSS type Ⅱ underwent magnetic resonance angiography (MRA) at the same time, and the findings were consistent with CTA, but the fine branches of the intrahepatic portal vein were poorly displayed. Conclusion The anatomy of congenital PSS is diverse and CTA/MRA is an accurate imaging technique. However, for extrahepatic type Ⅰ PSS, DSA should be taken as the golden standard. [ABSTRACT FROM AUTHOR]

Postmenopausal osteoporosis (PMOP) is a disease characterized by bone mass reduction and the destruction of bone microstructure, which is caused by the lack of estrogen. In recent years, more and more people believe that the immune microenvironment is closely related to the occurrence and development of this disease. A variety of immune cells and their secreted cytokines regulate the biological functions of osteoblasts and osteoclasts through RANK/RANKL/OPG signaling pathways, thereby affecting the imbalance of bone homeostasis. Therefore, immune microenvironment based on bone immunology have gradually become one of the main targets in the prevention and treatment of PMOP. This article reviews the effects of immune cells related to bone metabolism such as T cells, B cells, macrophages, mast cells and monocytes on the occurrence and development of PMOP and fracture healing, and summarizes the therapeutic targets of PMOP based on bone immunology, in order to provide new ideas for the drug development and clinical application of PMOP in the future. [ABSTRACT FROM AUTHOR]

Copyright of Journal of South China Agricultural University is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)