Advancements in the Biotransformation and Biosynthesis of the Primary Active Flavonoids Derived from Epimedium.

Epimedium is a classical Chinese herbal medicine, which has been used extensively to treat various diseases, such as sexual dysfunction, osteoporosis, cancer, rheumatoid arthritis, and brain diseases. Flavonoids, such as icariin, baohuoside I, icaritin, and epimedin C, are the main active ingredients with diverse pharmacological activities. Currently, most Epimedium flavonoids are extracted from Epimedium plants, but this method cannot meet the increasing market demand. Biotransformation strategies promised huge potential for increasing the contents of high-value Epimedium flavonoids, which would promote the full use of the Epimedium herb. Complete biosynthesis of major Epimedium flavonoids by microbial cell factories would enable industrial-scale production of Epimedium flavonoids. This review summarizes the structures, pharmacological activities, and biosynthesis pathways in the Epimedium plant, as well as the extraction methods of major Epimedium flavonoids, and advancements in the biotransformation and complete microbial synthesis of Epimedium flavonoids, which would provide valuable insights for future studies on Epimedium herb usage and the production of Epimedium flavonoids.

Key Molecules in Bladder Cancer Affect Patient Prognosis and Immunotherapy Efficacy: Further Exploration for CNTN1 and EMP1.

PURPOSE: Immunotherapy has been widely used in bladder cancer (BCa) in recent years and has significantly improved the prognosis of patients with BCa. However, further identification of immunotherapy-sensitive individuals to improve the efficacy of immunotherapy remains an important unmet need. MATERIALS AND METHODS: The key genes were screened and identified from Gene Expression Omnibus database and The Cancer Genome Atlas database to construct the risk prediction function (risk scores). Real-time polymerase chain reaction, immunohistochemistry, and IMvigor210 data sets were used to verify the roles of key molecules and efficacy of risk scores. The biologic function of CNTN1 and EMP1 was further explored through cell proliferation experiments. RESULTS: Five key genes, CNTN1, MAP1A, EMP1, MFAP5, and PTGIS, which were significantly related to the prognosis and immune checkpoint molecules of patients, were screened out. CNTN1 and EMP1 were further experimentally confirmed for their significant tumor-promoting effects. Besides, the constructed risk scores on the basis of these five key genes can accurately predict the prognosis and immunotherapy efficacy of patients with BCa. Interestingly, the high-risk patients identified by the risk scores have significantly worse prognosis and immunotherapy effects than low-risk patients. CONCLUSION: The key genes we screened can affect the prognosis of BCa, tumor microenvironment immune infiltration, and the efficacy of immunotherapy. The risk scores tool we constructed will contribute to the development of individualized treatment for BCa.

Biomass partitioning and ionomics of Macadamia with high manganese and low phosphorus concentrations.

Knowledge of the ionome of plant organs helps us understand a plant's nutritional status. However, the ionome of Macadamia (Proteaceae), which is an important nut-producing tree, remains unknown. We aimed to characterise the allocation of biomass and nutrient-partitioning patterns in three macadamia genotypes. We excavated 15 productive trees (three cultivars at 21years of age; two cultivars at 16years of age) in an orchard. Biomass, nutrient concentrations, and contents of roots, stems, branches, and leaves were analysed. Dry weight of roots, stems, branches and leaves accounted for 14-20%, 19-30%, 36-52%, and 12-18% of total plant weight, respectively. No significant difference was found in the total biomass among the cultivars at the same age. Compared with most crop plants, macadamia had low phosphorus (P) concentrations in all organs (<1gkg-1 ), and low leaf zinc (Zn) concentration (8mgkg-1 ). In contrast, macadamia accumulated large amounts of manganese (Mn), with a 20-fold higher leaf Mn concentration than what is considered sufficient for crop plants. Leaves exhibited the highest nutrient concentrations, except for iron and Zn, which exhibited the highest concentrations in roots. The organ-specific ionomics of Macadamia is characterised by low P and high Mn concentrations, associated with adaptation to P-impoverished habitats.

Rad54L promotes bladder cancer progression by regulating cell cycle and cell senescence.

Bladder cancer (BCa) is the most prevalent cancer of the urinary system, but its pathogenesis is still poorly understood. Several reports have suggested that gene damage repair is highly correlated with tumor development and drug resistance, in which homologous recombination repair gene Rad54L seems to play an important role, through yet unclear mechanisms. Therefore, this study stratified cancer patients by Rad54L expression in BCa tissue, and high Rad54L expression was associated with a poor prognosis. Mechanistically, we demonstrate that high Rad54L expression promotes abnormal bladder tumor cell proliferation by changing the cell cycle and cell senescence. In addition, this study also suggests that Rad54L may be associated with p53, p21, and pRB in BCa tissue. In summary, this study exposes Rad54L as potential a prognostic biomarker and precision treatment target in BCa.

MobileYOLO: Real-Time Object Detection Algorithm in Autonomous Driving Scenarios.

Object detection is one of the key tasks in an automatic driving system. Aiming to solve the problem of object detection, which cannot meet the detection speed and detection accuracy at the same time, a real-time object detection algorithm (MobileYOLO) is proposed based on YOLOv4. Firstly, the feature extraction network is replaced by introducing the MobileNetv2 network to reduce the number of model parameters; then, part of the standard convolution is replaced by depthwise separable convolution in PAnet and the head network to further reduce the number of model parameters. Finally, by introducing an improved lightweight channel attention modul-Efficient Channel Attention (ECA)-to improve the feature expression ability during feature fusion. The Single-Stage Headless (SSH) context module is introduced to the small object detection branch to increase the receptive field. The experimental results show that the improved algorithm has an accuracy rate of 90.7% on the KITTI data set. Compared with YOLOv4, the parameters of the proposed MobileYOLO model are reduced by 52.11 M, the model size is reduced to one-fifth, and the detection speed is increased by 70%.