Objective To establish a method for detection folylpolyglutamate syntbetase (FPGS),explore the change of FPGS in the drug-resistant A549 cells induced by methotrexate(MTX) enantiomer,and provide new tools to further investigate drug resistant mechanism. Methods A549 cell lines induced by L-( + )-MTX and D-( - )-MTX (25 μmol/L) were chosen to raise three cell lines as compared with MTX-sensitive cell line. Then FPGS were extracted for the CEIA-LIF and western blot was performed. After validation, FPGS antibodies were labeled by fluoreacein isothiocyanate (FITC) and produced a immune response with former-extracted FPGS. CELA-LIF can separate and detect labeled proteins according ruination time of the protein with different size and detect FPGS in drug resistant cell lines induced with L-(+)-MTX and D-(- )-MTX. The accuracy was evaluated as compared with western blot assay. Results The separation time of CEIA-LIF for labeled FPGS antibody and the immune complexes were7. 1 min and 8.9 min, and the resolving power was 4. 5. The process of protein separation and detection can be accomplished in less than 10 minutes. Western blot analysis showed there was no non-specific bands appears in the extract of these three cell lines after the freeze-thaw in liquid nitrogen. The minimum detection level in sensitive cell strains was 0. 68 mg/μl. The consent of FPGS in L-(+)-MTX and D-( - )-MTX induced cells were 46. 59% and 48. 36% compared with drug sensitive cell strains with CELA-LIF. Conclusions CELA-LIF was established in this experiment. It is efficient and sensitive for detecting of FPGS, which is similar to western blot method. The level of FPGS in L-( + )-MTX and D-( - )-MTX induced drug resistant cell lines is significantly lower, indicating the expression of FPGS is damaged.

AIM:To determine the biological feature of circulating endothelial cells (CECs) in acute promye-locytic leukemia ( APL) patients before and after treatment , and to analyze the relationship between CECs and the clinical characteristics .METHODS: The CECs were sorted from peripheral blood by magnetic-activated cell sorting and then counted by 3-color flow cytometry.The cells were identified by immunofluorescence staining for the expression of CD 146, CD31, CD144, VEGFR-2, CD45 and CD133.The CECs were cultured in vitro, and the tube formation and colony-forming rate were determined .RESULTS:Increased quantity of CECs was observed in CD 34 positive group and group with WBC >10 ×109/L (P<0.05).The quantity of CECs had a significant difference among low risk , medium risk and high risk groups (P<0.05).The positive rate of CD133 and quantity of CECs significantly reduced in 32 APL patients when they gain complete remission after treatment (P<0.05).The amount of tube formation and colony-forming rate were significant-ly reduced after treatment (P<0.05).The ratio of CECs quantity from APL patients after treatment to that before treatment had a negative correlation with arsenic concentration in urine on day 7 during As2O3 treatment (P<0.05).CONCLU-SION:Accurately counting CECs may be helpful for evaluating prognosis and designing treatment strategy .

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.