To establish a complete technical solution for the automatic radiation biological dose estimation platform for biological dose estimation and classification of the wounded in large-scale radiation accidents, the “dose–effect curve by dicentric chromosome (DIC) automatic analysis” was established and its accuracy was verified. The effects of analyzed cell number and the special treatment of the culture on dose estimation by DIC automatic analysis were studied. Besides, sample processing capabilities of the special equipments were tested. The fitted “dose–effect curve by DIC automatic analysis” was presented as follows: Y = (0.01806 ± 0.00032) D 2 + (0.01279 ± 0.00084) D + (0.0004891 ± 0.0001358) (R 2 = 0.961). Three-gradient scanning method, culture refrigeration method, and interprofessional collaboration under extreme conditions were proposed to improve the detection speed, prolong the sample processing time window, and reduce the equipment investment. In addition, the optimized device allocation ratio for the automatic biological dose estimation laboratory was proposed to eliminate the efficiency bottleneck. The complete set of technical solutions for the high-throughput automatic biological dose estimation laboratory proposed in this study can meet the requirements of early classification and rapid biological dose assessment of the wounded during the large-scale nuclear radiation events, and it is worthy of further promotion.
There is a pressing need to establish automated solutions for the rapid, high-throughput, and automatic detection of chromosome aberrations (CAs) in the occupational health surveillance of large-scale radiation workers. Here, we described and verified the accuracy of a new measurement system based on the automatic scanning and analysis of dicentric chromosomes (DICs). The effects of cell number on DIC detection by automatic scanning and analysis were studied, and the distribution of DIC values per cell was calculated. In total, 1088 cases were detected by automatic DIC scanning and analysis in 26 663 radiation workers, and 73 cases were further confirmed by a technician, including 5 cases in which radiation exposure lead to harmful medical consequences. Our approach reduces the workload by 96% and increases the speed of assessment approximately 7-fold. Overall, this study validates the utility of a novel rapid and high-throughput CA detection procedure as a means of occupational health surveillance of large-scale radiation workers.
In recent decades, the rapid development of radiotherapy has dramatically increased the cure rate of malignant tumors. Heavy-ion radiotherapy, which is characterized by the “Bragg Peak” because of its excellent physical properties, induces extensive unrepairable DNA damage in tumor tissues, while normal tissues in the path of ion beams suffer less damage. However, there are few prognostic molecular biomarkers that can be used to assess the efficacy of heavy ion radiotherapy. In this study, we focus on non-small cell lung cancer (NSCLC) radiotherapy and use RNA sequencing and bioinformatic analysis to investigate the gene expression profiles of A549 cells exposed to X-ray or carbon ion irradiation to screen the key genes involved in the stronger tumor-killing effect induced by carbon ions. The potential ceRNA network was predicted and verified by polymerase chain amplification, western blotting analysis, colony formation assay, and apoptosis assay. The results of the experiments indicated that lncRNA EBLN3P plays a critical role in inhibiting carbon ion-induced cell proliferation and inducing apoptosis of NSCLC cells. These functions were achieved by the EBLN3P/miR-144-3p/TNPO1 (transportin-1) ceRNA network. In summary, the lncRNA EBLN3P functions as a ceRNA to mediate lung cancer inhibition induced by carbon ion irradiation by sponging miR-144-3p to regulate TNPO1 expression, indicating that EBLN3P may be a promising target for increasing the treatment efficacy of conventional radiotherapy for NSCLC.
Pancreatic cancer is one of the major reasons of cancer-associated deaths due to poor diagnosis, high metastasis and drug resistance. Therefore, it is important to understand the cellular and molecular mechanisms of pancreatic cancer to identify new targets for the treatment. TIPE2 is an essential regulator of tumor apoptosis, inflammation and immune homeostasis. However, the role of TIPE2 is still not fully understood in pancreatic cancer. In this study, we found the expression of TIPE2 was decreased in pancreatic cancer tissues compare to paracancerous tissues, which was negatively correlated with tumor size in patients. Overexpression of TIPE2 significantly decreased cell proliferation, metastasis and increased apoptotic events in pancreatic cancer cell lines. Moreover, the results obtained from real time PCR and western blot revealed that TIPE2 was also involved in inhibiting MMPs and N-Cadherin expression while increasing Bax expression in pancreatic cancer cells. Similarly, TIPE2 could inhibit tumor growth in vivo, decrease the expression of Ki-67 and N-Cadherin, and increase the expression of Bax by IHC analysis in tumor tissues isolated from tumor-bearing mice. Mechanistic studies exhibited that TIPE2 might suppress pancreatic cancer development through inhibiting PI3K/AKT and Raf/MEK/ERK signaling pathways triggered by TGFβ1. Moreover, the tumor-infiltrating lymphocytes from tumor-bearing mice were analyzed by flow cytometry, and showed that TIPE2 could promote T cell activation to exert an anti-tumor effect possibly through activation of DCs in a TGFβ1 dependent manner. In general, we described the multiple regulatory mechanisms of TIPE2 in pancreatic tumorigenesis and tumor microenvironment, which suggested TIPE2 may act as a potential therapeutic target in pancreatic cancer.
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