Breast cancer (BC) is a serious threat to women's health worldwide. Non-SMC condensin I complex subunit D2 (NCAPD2) is a regulatory subunit of the coagulin I complex, which is mainly involved in chromosome coagulation and separation. The clinical significance, biological behavior, and potential molecular mechanism of NCAPD2 in BC were investigated in this study. We found that NCAPD2 was frequently overexpressed in BC, and it had clinical significance in predicting the prognosis of BC patients. Moreover, loss-of-function assays demonstrated that NCAPD2 knockdown restrained the progression of BC by inhibiting proliferation and migration and enhancing apoptosis in vitro. It was further confirmed that the downregulation of NCAPD2 inhibited tumor growth in vivo. NCAPD2 promoted the progression of BC through the extracellular signal-regulated kinase 5 (ERK5) signaling pathway. Additionally, NCAPD2 could transcriptionally activate CDK1 by interacting with E2F transcription factor 1 (E2F1) in MDA-MB-231 cells. Overexpression of CDK1 alleviated the inhibitory effects of NCAPD2 knockdown in BC cells. In summary, the NCAPD2/E2F1/ CDK1 axis may play a role in promoting the progression of BC, which may provide a blueprint for molecular therapy.
Breast cancer is the most common cancer diagnosed in women. Breast cancer research is currently based mainly on animal models and traditional cell culture. However, the inherent species gap between humans and animals, as well as differences in organization between organs and cells, limits research advances. The breast cancer organoid can reproduce many of the key features of human breast cancer, thereby providing a new platform for investigating the mechanisms underlying the development, progression, metastasis and drug resistance of breast cancer. The application of organoid technology can also promote drug discovery and the design of individualized treatment strategies. Here, we discuss the latest advances in the use of organoid technology for breast cancer research.
Real-time analysis of UAV low-altitude remote sensing images at airborne terminals facilitates the timely monitoring of weeds in the farmland. Aiming at the real-time identification of rice weeds by UAV low-altitude remote sensing, two improved identification models, MobileNetV2-UNet and FFB-BiSeNetV2, were proposed based on the semantic segmentation models U-Net and BiSeNetV2, respectively. The MobileNetV2-UNet model focuses on reducing the amount of calculation of the original model parameters, and the FFB-BiSeNetV2 model focuses on improving the segmentation accuracy of the original model. In this study, we first tested and compared the segmentation accuracy and operating efficiency of the models before and after the improvement on the computer platform, and then transplanted the improved models to the embedded hardware platform Jetson AGX Xavier, and used TensorRT to optimize the model structure to improve the inference speed. Finally, the real-time segmentation effect of the two improved models on rice weeds was further verified through the collected low-altitude remote sensing video data. The results show that on the computer platform, the MobileNetV2-UNet model reduced the amount of network parameters, model size, and floating point calculations by 89.12%, 86.16%, and 92.6%, and the inference speed also increased by 2.77 times, when compared with the U-Net model. The FFB-BiSeNetV2 model improved the segmentation accuracy compared with the BiSeNetV2 model and achieved the highest pixel accuracy and mean Intersection over Union ratio of 93.09% and 80.28%. On the embedded hardware platform, the optimized MobileNetV2-UNet model and FFB-BiSeNetV2 model inferred 45.05 FPS and 40.16 FPS for a single image under the weight accuracy of FP16, respectively, both meeting the performance requirements of real-time identification. The two methods proposed in this study realize the real-time identification of rice weeds under low-altitude remote sensing by UAV, which provide a reference for the subsequent integrated operation of plant protection drones in real-time rice weed identification and precision spraying.
BackgroundThe weak antitumor efficacy and limited lifespan are the main obstacles that hinder the therapeutic effect of cytokine-induced killer (CIK) cell immunotherapy. In the study, we enhanced the persistence and the antitumor efficacy of CIK cell through PD-1 knockout and hTERT transduction.Material/MethodsCIK cells were cultured from patients with hepatocellular carcinoma and PD-1 gene was knocked out through the Cas9 ribonucleoproteins (Cas9 RNPs) electroporation. TIDE assay, T7E1 mismatch cleavage assay, and clone Sanger sequencing were used to detect PD-1 knockout efficiency. The immunophenotype was analyzed by flow cytometry. After PD-1 knockout, the hTERT gene was transduced into PD-1 KO/CIK cells with lentiviral transduction. The hTERT expression and persistence of hTERT/PD-1 KO/CIK cells were evaluated by Western blotting and proliferation curve. The antitumor efficacy was detected by ELISPOT and cytotoxicity assay. The telomere length was measured by the Q-FISH and qPCR method. The karyotype assay was used to analyze the chromosome structural stability.ResultsThe optimal knockout efficiency of PD-1 gene in CIK cells could reach 41.23±0.52%. PD-1 knockout did not affect the immunophenotype of CIK cells. The hTERT transduction enhanced persistence and increased the telomere length. ELISPOT and cytotoxicity assay showed hTERT/PD-1 KO/CIK cells had an enhanced antitumor efficacy. Meanwhile, PD-1 KO/CIK cells transduced with hTERT showed a normal karyotype.ConclusionsPD-1 knockout combined with hTERT transduction could prolong the lifespan and enhance antitumor efficacy of CIK cells against hepatocellular carcinoma cell line.
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