RESUMO
Citri Reticulatae Pericarpium, especially the pericarp of Citrus reticulata Blanco cv. Chachiensis (PCRC), is an important edible and medicinal ingredient for health and pharmacological properties. Citrus Huanglongbing, a devastating disease that currently threatens the citrus industry worldwide, is caused by a phloem-limited alpha-proteobacterium, "Candidatus Liberibacter asiaticus" (CLas). The industry of cultivar Chachiensis has been suffering from HLB. Although HLB affected the quality of citrus fruit, whether the quality of PCRC was affected by HLB remains unclear. In this study, we compared the metabolite profiles between HLB-affected and healthy PCRC from three sources: fresh, 6-month-old, and 9-year-old PCRC, through the untargeted LC-MS method. Compared to healthy controls, various types of bioactive compounds, mainly flavonoids, terpenoids, alkaloids, coumarins, polysaccharides, and phenolic acids, accumulated in HLB-affected PCRC, especially in the HLB-affected 9-year PCRC. In particular, isorhamnetin, isoliquiritigenin, luteolin 7-O-beta-D-glucoside, limonin, geniposide, pyrimidodiazepine, scoparone, chitobiose, m-coumaric acid, malonate, and pantothenic acid, which contributed to the pharmacological activity and health care effects of PCRC, were highly accumulated in HLB-affected 9-year-old PCRC compared to the healthy control. Multibioassay analyses revealed that HLB-affected 9-year-old PCRC had a higher content of total flavonoids and total polyphenols and exhibited similar antioxidant capacity as compared to healthy controls. The results of this study provided detailed information on the quality of HLB-affected PCRC.
RESUMO
PURPOSE: The aim of this study is to determine intratumoral habitat regions from multi-sequences magnetic resonance imaging (MRI) and to assess the value of those regions for prediction of patient response to neoadjuvant chemotherapy (NAC) in nasopharyngeal carcinoma (NPC). MATERIALS AND METHODS: Two hundred and ninety seven patients with NPC were enrolled. Multi-sequences MRI data were used to outline three-dimensional volumes of interest (VOI) of the whole tumor. The original imaging data were divided into two groups, which were resampled to an isotropic resolution of 1 × 1 × 1 mm3 (group_1mm) and 3 × 3 × 3 mm3 (group_3mm). Nineteen radiomics features were computed for each voxel of three sequences in group_3mm, within the tumor region to extract local information. Then, k-means clustering was implemented to segment the whole tumor regions in two groups. After radiomics features were extracted and dimension reduction, habitat models were built using Multi-Layer Perceptron (MLP) algorithm. RESULTS: Only T stage was included as the clinical model. The habitat3mm model, which included 10 radiomics features, achieved AUCs of 0.752 and 0.724 in the training and validation cohorts, respectively. Given the slightly better outcome of habitat3mm model, nomogram was developed in combination with habitat3mm model and T stage with the AUC of 0.749 and 0.738 in the training and validation cohorts. The decision curve analysis provides further evidence of the nomogram's clinical practicality. CONCLUSIONS: A nomogram based on intratumoral habitat predicts the efficacy of NAC in NPC patients, offering the potential to improve both the treatment plan and patient outcomes.