Flavonoid 3-O-glucosyltransferase (3GT) is a key enzyme in the glucosidation of anthocyanins. To investigate the 3GT gene in rhododendron, we cloned an open reading frame (ORF) of 3GT gene (named Rh3GT) from Rhododendron hybridum Hort (Red cultivar) and then characterized this gene and the deduced protein in terms of the biochemical characteristics, expression level, and enzymatic function. The results showed that Rh3GT had a full length of 993 bp and encoded 330 amino acid residues. The deduced protein was hydrophilic, stable, weak acid, belonging to the glycosyltransferase family (GT-B type), with glutamine (Q) at position 44 in the PSPG box. The phylogenetic analysis showed that Rh3GT was most closely related to Vc3GT from Vaccinium corymbosum and Vm3GT from Vaccinium myrtillus. Rh3GT was expressed in the stems, leaves, and flowers and almost not expressed in the roots, with the highest expression level in petals during full blooming stage. Introduction of pCAMBIAL1302-Rh3GT into petals significantly up-regulated the expression level of Rh3GT and increased the total anthocyanin accumulation. Rh3GT was successfully expressed in Escherichia coli BL21 in the form of inclusion bodies with a size of about 36 kDa. The results of HPLC showed that the recombinant Rh3GT after denaturation, purification, and dilution could catalyze the synthesis of cyanidin and UDP-glucose to synthesize cyanidin 3-O-glucoside, indicating that the expressed protein had 3GT activity. This study provides basic data for further studying the molecular regulation mechanism of anthocyanin biosynthesis and theoretical support for molecular breeding of rhododendron.
Rhododendron/classification* ; Glucosyltransferases/metabolism* ; Cloning, Molecular ; Escherichia coli/metabolism* ; Recombinant Proteins/biosynthesis* ; Anthocyanins/biosynthesis* ; Phylogeny ; Plant Proteins/metabolism* ; Amino Acid Sequence

Objective:To explore the value of deep learning (DL) models based on conventional MRI in differentiating orbital solitary fibrous tumors (SFT) from schwannomas.Methods:This was a case-control study. A retrospective analysis was conducted on patients with pathologically confirmed orbital SFT and schwannoma admitted to Eye & ENT Hospital, Fudan University (institution 1) from December 2014 to January 2022 and Ninth People′s Hospital, Shanghai Jiao Tong University School of Medicine (institution 2) from July 2015 to May 2022. A total of 140 patients were included, with 104 patients from institution 1 comprising the training cohort for building DL models and 36 patients from institution 2 comprising the external validation cohort for assessing model performance. Based on the preoperative cross-sectional fat-suppressed T 2WI and contrast-enhanced T 1WI (ceT 1WI), tumor contours were outlined on all tumor-containing slices. Six diagnostic models were constructed using residual networks (ResNet) and split-attention residual networks (ResNeSt) with 18 layers (ResNet-18 and ResNeSt-18), based solely on individual T 2WI and ceT 1WI, as well as a combination of both. A radiology resident and an attending radiologist independently reviewed conventional MRI images to determine the tumor type. The performance of the DL models and radiologists in differentiating orbital SFT from schwannoma in the external validation cohort was evaluated using receiver operating characteristic curves, and the areas under the curves (AUC) were compared using the DeLong test. Results:In the external validation cohort, the AUC (95% CI) of the ResNet-18 models based on T 2WI, ceT 1WI, and their combination were 0.861 (0.719-1), 0.896 (0.774-1), and 0.885 (0.755-1), respectively, while the AUC (95% CI) of the ResNeSt-18 models were 0.889 (0.748-1), 0.872 (0.726-1), and 0.910 (0.801-1), respectively. Among these, the ResNeSt-18 model based on the combined sequences achieved the best performance in differentiating the two tumors. The AUC (95% CI) for the individual interpretation of the radiology resident and attending radiologist were 0.729 (0.571-0.887) and 0.771 (0.618-0.923), respectively. The AUC of the ResNeSt-18 model based on the combined sequences was statistically significantly higher than those of the resident and attending radiologist ( Z=1.96, P=0.049; Z=2.00, P=0.045). Conclusion:The ResNeSt-18 model based on conventional MRI can effectively differentiate orbital SFT from schwannoma, demonstrating better performance than those of the radiology resident and the attending radiologist.

Objective:To explore the value of deep learning (DL) models based on conventional MRI in differentiating orbital solitary fibrous tumors (SFT) from schwannomas.Methods:This was a case-control study. A retrospective analysis was conducted on patients with pathologically confirmed orbital SFT and schwannoma admitted to Eye & ENT Hospital, Fudan University (institution 1) from December 2014 to January 2022 and Ninth People′s Hospital, Shanghai Jiao Tong University School of Medicine (institution 2) from July 2015 to May 2022. A total of 140 patients were included, with 104 patients from institution 1 comprising the training cohort for building DL models and 36 patients from institution 2 comprising the external validation cohort for assessing model performance. Based on the preoperative cross-sectional fat-suppressed T 2WI and contrast-enhanced T 1WI (ceT 1WI), tumor contours were outlined on all tumor-containing slices. Six diagnostic models were constructed using residual networks (ResNet) and split-attention residual networks (ResNeSt) with 18 layers (ResNet-18 and ResNeSt-18), based solely on individual T 2WI and ceT 1WI, as well as a combination of both. A radiology resident and an attending radiologist independently reviewed conventional MRI images to determine the tumor type. The performance of the DL models and radiologists in differentiating orbital SFT from schwannoma in the external validation cohort was evaluated using receiver operating characteristic curves, and the areas under the curves (AUC) were compared using the DeLong test. Results:In the external validation cohort, the AUC (95% CI) of the ResNet-18 models based on T 2WI, ceT 1WI, and their combination were 0.861 (0.719-1), 0.896 (0.774-1), and 0.885 (0.755-1), respectively, while the AUC (95% CI) of the ResNeSt-18 models were 0.889 (0.748-1), 0.872 (0.726-1), and 0.910 (0.801-1), respectively. Among these, the ResNeSt-18 model based on the combined sequences achieved the best performance in differentiating the two tumors. The AUC (95% CI) for the individual interpretation of the radiology resident and attending radiologist were 0.729 (0.571-0.887) and 0.771 (0.618-0.923), respectively. The AUC of the ResNeSt-18 model based on the combined sequences was statistically significantly higher than those of the resident and attending radiologist ( Z=1.96, P=0.049; Z=2.00, P=0.045). Conclusion:The ResNeSt-18 model based on conventional MRI can effectively differentiate orbital SFT from schwannoma, demonstrating better performance than those of the radiology resident and the attending radiologist.

Flavanone 3-hydroxylase (F3H) is a key enzyme in the synthesis of phycocyanidins. In this experiment, the petals of red Rhododendron hybridum Hort. at different developmental stages were used as experimental materials. The R. hybridum flavanone 3-hydroxylase (RhF3H) gene was cloned using reverse transcription PCR (RT-PCR) and rapid-amplification of cDNA ends (RACE) techniques, and bioinformatics analyses were performed. Petal RhF3H gene expression at different developmental stages were analyzed by using quantitative real-time polymerase chain reaction (qRT-PCR). A pET-28a-RhF3H prokaryotic expression vector was constructed for the preparation and purification of RhF3H protein. A pCAMBIA1302-RhF3H overexpression vector was constructed for genetic transformation in Arabidopsis thaliana by Agrobacterium-mediated method. The results showed that the R. hybridum Hort. RhF3H gene is 1 245 bp long, with an open reading frame of 1 092 bp, encoding 363 amino acids. It contains a Fe²⁺ binding motif and a 2-ketoglutarate binding motif of the dioxygenase superfamily. Phylogenetic analysis showed that the R. hybridum RhF3H protein is most closely related to the Vaccinium corymbosum F3H protein. qRT-PCR analysis showed that the expression level of the red R. hybridum RhF3H gene tended to increase and then decrease in the petals at different developmental stages, with the highest expression at middle opening stage. The results of the prokaryotic expression showed that the size of the induced protein of the constructed prokaryotic expression vector pET-28a-RhF3H was about 40 kDa, which was similar to the theoretical value. Transgenic RhF3H Arabidopsis thaliana plants were successfully obtained, and PCR identification and β-glucuronidase (GUS) staining demonstrated that the RhF3H gene was integrated into the genome of A. thaliana plants. qRT-PCR, total flavonoid and anthocyanin contentanalysis showed that RhF3H was significantly higher expressed in the transgenic A. thaliana relative to that of the wild type, and its total flavonoid and anthocyanin content were significantly increased. This study provides a theoretical basis for investigating the function of RhF3H gene, as well as for studying the molecular mechanism of flower color in R. simsiib Planch.
Arabidopsis/metabolism* ; Rhododendron/metabolism* ; Amino Acid Sequence ; Anthocyanins/metabolism* ; Phylogeny ; Flavonoids/metabolism* ; Cloning, Molecular ; Gene Expression Regulation, Plant ; Plant Proteins/metabolism*