Objective: To develop a quantitative PCR method for detecting hookworm infection and quantification. Methods:A real-time PCR method was designed based on the intergenic region II of ribosomal DNA of the hookworm Necator americanus. The detection limit of this method was compared with the microscopy-based Kato-Katz method. The real-time PCR method was used to conduct an epidemiological survey of hookworm infection in southern Fujian Province of China. Results:The real-time PCR method was specific for detecting Necator americanus infection, and was more sensitive than conventional PCR or microscopy-based method. A preliminary survey for hookworm infection in villages of Fujian Province confirmed the high prevalence of hookworm infections in the resident populations. In addition, the infection rate in women was significantly higher than that of in men. Conclusions: A real-time PCR method is designed, which has increased detection sensitivity for more accurate epidemiological studies of hookworm infections, especially when intensity of the infection needs to be considered.

The main aim of this study was to transform the enhanced green fluorescent protein gene (egfp) into biocontrol fungus Paecilomyces lilacinus strain 9410. We constructed the expression vector pUPNGT of the fusion gene nptII-egfp using pcDNA3.1(-) as a helper plasmid. The egfp gene was then transformed into P. lilacinus strain 9410 via Agrobacterium tumefaciens-mediated transformation. PCR and Southern blotting analysis showed that the egfp gene was integrated into the genomes of the tested transformants and the integration manner was single-copy. The transformants could generate green fluorescence when they were excited by 488 nm blue laser. These results indicated that the egfp gene had been successfully transformed into P. lilacinus 9410 and expressed in the tested transformants. Our work may provide a new approach to assess environmental safety and practical biocontrol efficacy ofP. lilacinus under different conditions.
Agrobacterium tumefaciens ; genetics ; Green Fluorescent Proteins ; genetics ; Paecilomyces ; genetics ; metabolism ; Polymerase Chain Reaction ; methods ; Transformation, Genetic

OBJECTIVE To evaluate the accuracy of three individualized drug delivery tools， i.e. JPKD， SmartDose and NextDose， in predicting tacrolimus dose and blood concentration after kidney transplantation， and analyze the influential factors of prediction accuracy. METHODS The clinical data of adult hospitalized patients treated with tacrolimus after kidney transplantation from January 2021 to June 2023 were retrospectively collected. Three individualized dosing tools， i.e. JPKD， SmartDose and NextDose， were used to predict the dose and plasma concentration of tacrolimus. The absolute prediction error （APE） and prediction error （PE） between the measured value and the predicted value， and prediction success rate were calculated （APE＜30% indicating a good forecast）. Pearson assay or Spearman assay was used to analyze the correlation between the predicted dosage and actual dosage， as well as the predicted and measured blood concentration values using three software； univariate analysis was used to investigate the influential factors for prediction accuracy of JPKD， SmartDose and NextDose. RESULTS A total of 110 hospitalized patients were included in this study， and tacrolimus doses and plasma concentrations were monitored. The predicted doses of JPKD， SmartDose and NextDose were （2.0±0.7）， （2.7±1.9）， （1.8±0.8） mg， their measured value was （1.9±0.6） mg， and the correlation coefficients between the predicted values and the measured value were 0.841， 0.450， 0.247 （P＜0.001）； the median APEs were 6.00%， 52.07% and 30.40%， and the median PEs were 5.00%， 18.50% and －3.50%； the prediction success rates were 98.45%， 30.05% and 49.22%. The predicted values of tacrolimus concentrations using JPKD， SmartDose， NextDose were （6.74±3.36）， （6.93±5.02）， 9.00（5.80±12.60） ng/mL， the measured value was 8.64（7.11，9.77） ng/mL， and the correlation coefficients between the predicted values and the measured value were 0.997 （P＜0.001）， －0.066 （P＝0.360）， 0.920 （P＜0.001）. The median APEs were 5.54%， 45.91% and 35.56%， and PEs were －4.94% （median）， －17.050% （median） and 36.93% （average value）； the prediction success rates were 97.93%， 32.64% and 37.31%. Univariate analysis showed that the dosage， blood concentration， body weight， transplantation time and others were related to the prediction accuracy （P＜0.05）. CONCLUSIONS The good prediction rates of tacrolimus dose and blood concentration in kidney transplant patients using three personalized drug delivery tools， from high to low， are JPKD， NextDose， and SmartDose， suggesting that JPKD can be prioritized in clinical use.