Objective:To explore the value of a deep learning model based on MRI in predicting the methylation status of MGMT in WHO Ⅱ, Ⅲ gliomas.Methods:The clinical and imaging data of 121 patients with WHO grade Ⅱ, Ⅲ glioma confirmed by surgical pathology and molecular pathology in the Second Hospital of Lanzhou University from June 2016 to June 2020 were retrospectively analyzed. Among them, the MGMT promoter was methylated. A total of 78 cases were metabolized and 43 cases were unmethylated. T 2WI and T 1WI enhanced sequence images of 121 cases of WHO Ⅱ, Ⅲ gliomas were collected, and all the images of each patient including the lesion level were selected manually, and were randomly divided into training set and validation set according to 7∶3. The EfficientNet-B3 convolutional neural network was used to build independent prediction models (T 2-net, T 1C-net, TS-net) based on T 2WI, T 1WI enhancement, T 2WI combined with T 1WI enhancement, and the prediction performance of each model was evaluated separately through the ROC curve. Results:The T 2-net model in the validation set presented an accuracy of 72.3%, a sensitivity of 64.7%, a specificity of 73.3%, and an area under the curve (AUC) of 0.72 for predicting the methylation status of the MGMT promoter in WHO Ⅱ, Ⅲ gliomas. The T 1C-net model showed an accuracy of 66.8%, a sensitivity of 68.3%, a specificity of 66.9%, and an AUC of 0.72. The TS-net model showed an accuracy of 81.8%, a sensitivity of 63.1%, a specificity of 85.0%, and AUC of 0.78. Conclusions:The EfficientNet-B3 convolutional neural network based on MRI can predict the methylation status of the MGMT promoter of WHO Ⅱ, Ⅲ gliomas; the TS-net model has the best prediction performance.

Carotenoids are secondary metabolite responsible for colored pigments in plants and microbes (Li et al., 2022). They are a class of C₄₀ tetraterpenoids consisting of eight isoprenoid units, and can be classified into carotenes and xanthophylls on the basis of their functional groups (Saini et al., 2015). Carotenes can be linear (phytoene, phytofluene, and ζ‍-carotene) or branched (β‍-carotene and α‍-carotene). Xanthophylls comprise β,β‍-xanthophylls (β‍-cryptoxanthin, zeaxanthin, violaxanthins, and neoxanthin) and β,ε‍-xanthophylls (α-cryptoxanthin, α-carotene, and lutein). Citrus fruits are complex sources of carotenoids, which are the principal pigments responsible for the typical orange color of most types (Chen, 2020). The difference in total carotenoid content and the diversity of carotenoid isomer proportion also accounts for other colors of citrus fruits, such as yellow, red, and pink (Chen, 2020).
Citrus/metabolism* ; Carotenoids ; Xanthophylls ; Lutein/metabolism* ; Zeaxanthins/metabolism* ; Fruit

Incorporation of multiple functions into one nanoplatform can improve cancer diagnostic efficacy and enhance anti-cancer outcomes. Here, we constructed doxorubicin (DOX)-loaded silk fibroin-based nanoparticles (NPs) with surface functionalization by photosensitizer (N770). The obtained nanotheranostics (N770-DOX@NPs) had desirable particle size (157 nm) and negative surface charge (-25 mV). These NPs presented excellent oxygen-generating capacity and responded to a quadruple of stimuli (acidic solution, reactive oxygen species, glutathione, and hyperthermia). Surface functionalization of DOX@NPs with N770 could endow them with active internalization by cancerous cell lines, but not by normal cells. Furthermore, the intracellular NPs were found to be preferentially retained in mitochondria, which were also efficient for near-infrared (NIR) fluorescence imaging, photothermal imaging, and photoacoustic imaging. Meanwhile, DOX could spontaneously accumulate in the nucleus. Importantly, a mouse test group treated with N770-DOX@NPs plus NIR irradiation achieved the best tumor retardation effect among all treatment groups based on tumor-bearing mouse models and a patient-derived xenograft model, demonstrating the unprecedented therapeutic effects of trimodal imaging-guided mitochondrial phototherapy (photothermal therapy and photodynamic therapy) and chemotherapy. Therefore, the present study brings new insight into the exploitation of an easy-to-use, versatile, and robust nanoplatform for programmable targeting, imaging, and applying synergistic therapy to tumors.