Extracellular vesicles (EV) are widely distributed, rich in content, and fully participate in the regulation of important cellular physiological activities. As a new technology for tumor diagnosis, the natural advantages of EV include protecting its contents, being easy to obtain from various biofluids, having the potential to be truly non-invasive and high tissue fidelity. In order to transfer EV for clinical use, many isolation technologies such as microfluidics, immunochips, nano-flow cytometry and acoustic capture have been continuously developed. At present, several EV tumor diagnostic products have been applied in the clinical setting. However, due to the great differences in detection methods and platforms, there are still some technical difficulties in its clinical applications. With the accumulation of clinical evidence and the continuous improvement of clinical diagnostic methods, the liquid biopsy based on EV can finally be applied in the clinic.

As a new type of intercellular signaling rector, extracellular vesicles (EV) are involved in almost the whole process of tumorigenesis, progression, metastasis, and drug resistance. Therefore, EV have become the ideal biomarker candidates and research hotspots for cancer diagnosis and treatment. However, EV tumor biomarker research mainly focused on RNA and protein, and a small part of the research focused on lipids at the early stage. EV DNA has received little attention and its diagnostic value has gradually been recognized in recent years. Study on the biological characteristics and function of EV DNA may highlight its potential in tumor diagnosis.

Objective: To investigate the effects of prostate cancer exosomes on the migration and invasion ability of stromal cells (WPMY-1), and to explore its mechanism. Methods: Exosomes in LNCaP-AI+F prostate cancer cell supernatant were isolated by ultracentrifugation and the typical structure of exosome was captured by electron microscope. The particle size distribution was analyzed by Zetaview, and Wb was used to identify the marker proteins and other proteins.After co-incubation of WPMY-1 cells and prostate cancer exosomes (40 µg/ml), laser confocal microscope was used to observe the uptake of PKH67-labeled exosomes by WPMY-1 cells; Transwell assay was used to detect the migration and invasion ability of WPMY-1 cells; qPCR was performed to detect the expression of three cancer-associated fibroblast (CAF)-related molecules (IL-8, PDGFB and MMP9) at mRNA level; and the phosphorylation of EGFR and ERK1/2 was analyzed by Wb. Results: Typical cup-shaped structure of exosomes was observed under electron microscope. The Zetaview results showed that the particle size distribution was concentrated at about 100 nm. The expression of exosome marker proteins CD63 andALIX further verified that the isolated particles were exosomes. Besides, EGFR, HER2 and SRC, which were related to the progression of prostate cancer, were also enriched in exosomes. After co-incubation, confocal microscope imaging showed a number of PKH67 labeled exosomes in recipient WPMY-1 cells. Transwell experiments showed that exosomes could significantly enhance the migration and invasion ability of WPMY-1 cells (all P<0.01). Compared with the control group, increased secretion of IL-8, PDGFB and MMP9 was observed after exosome treatment (40 µg/ml) (P<0.05 or P<0.01). Wb indicated that exosomes could promote the phosphorylation of EGFR and ERK1/2 of WPMY-1 cells (P<0.01). Conclusion: Prostate cancer cell exosomes could act on the stromal cell WPMY-1 to highly express multiple CAF-related molecules, promote the phosphorylation of EGFR and ERK1/2 and enhance the migration and invasion ability of WPMY-1 cells.

ObjectiveTo elucidate the principles and methods of the Bayesian probabilistic linkage model， and to demonstrate the effect of applying the model in linking birth and death data. MethodsThrough the Shanghai birth and death registration system， data of 199 025 infants born in 2017 and 1 512 infants who died in 2017 and 2018 were collected. After cleaning the data， the data were divided into monthly blocks and fully linked. The Jaro-Winkler algorithm and Euclidean distance were employed to measure the similarity of fields for matching. A Bayesian probabilistic linkage model was constructed and the linking effect was evaluated using a confusion matrix. ResultsUsing the Bayesian probabilistic linkage model， the birth and death data of infants were effectively linked， revealing that 36.71% of infants who died in Shanghai were born outside the city， and the probability of infant death was 2.6‰. The confusion matrix of the test set showed a recall rate of 0.86， precision of 0.76， and an F-score of 0.81. ConclusionThe practical application of Bayesian probabilistic linkage demonstrates a good model performance， enabling the establishment of birth-death cohorts that more accurately reflect the true levels of infant mortality. Utilizing this technique to integrate data from different departments can effectively improve research efficiency in the field of public health.