Construction and optimization of a novel plasma membrane model for membrane affinity assay based on polydiacetylene vesicles / 药学学报

Most drugs need to interact with cell membrane to reach the biological target, so that membrane affinity assay is an important early screening step in drug discovery. However, at present, the traditional oil-water distribution method is still used, a new, simple and accurate method for membrane affinity assay is urgently needed. In this study, according to the colorimetric principle, a new assay model based on polydiacetylene vesicles was optimized through a series of experiments including different concentrations of vesicle solution, temperature, or pH reaction environment. On this basis, tetracaine hydrochloride, 2-methylimidazole and histamine were used as model drugs to measure the membrane affinity constants and verify the between-batch precision of the optimized assay model (relative standard deviation less than 5%). In addition, polydiacetylene vesicles were stable for up to 180 days, demonstrating the potential application of the assay model. This strategy is simple, stable, reliable, with high reproducibility, low cost and easy to promote, which provided a new tool and a new direction for the high-throughput assay of membrane affinity.

Rapid Quantitative Detection and Model Optimization of Trans Fatty Acids in Edible Vegetable Oils by Near Infrared Spectroscopy / 分析化学

Near infrared spectroscopy (NIR) was used to detect trans fatty acids (TFA) in edible vegetable oils quantitatively. And prediction model of TFA was optimized through band selection, pretreatment method, variable selection and modeling method. NIR spectra of 98 edible vegetable oil samples were collected in spectral range of 4000-10000 cm-1 using an Antaris Ⅱ Fourier transform near infrared spectrometer, and the true content of TFA was measured by gas chromatography. First, optimization of waveband and pretreatment method was conducted on original spectra. On this basis, competitive adaptive reweighted sampling (CARS) was used to select important variables that related to TFA. Finally, the prediction models of TFA content in edible vegetable oils were established using principal component regression ( PCR), partial least square (PLS) and least square support vector machine (LS-SVM). The results indicated that NIR spectroscopy was feasible for detecting TFA content in edible vegetable oils, R2 of the best prediction model after optimized in calibration and prediction sets were 0. 992 and 0. 989, and root mean square error of calibration (RMSEC) and root mean square error of prediction ( RMSEP) were 0. 071% and 0. 075% , respectively. Only 26 variables were used in the best prediction model, accounting for 0. 854% of the whole waveband variables. In addition, compared with the full waveband PLS prediction model, the R2 in prediction set increased from 0. 904 to 0. 989, and RMSEP decreased from 0. 230% to 0. 075% . It shows that model optimization is very necessary, CARS method can select important variables related to TFA effectively and immensely reduce the number of modeling variables, so it can simplify the prediction model, and greatly improve the accuracy and stability of prediction model.

Optimization and application of standardized basic clinical skill training model at teaching hospitals / 中华医院管理杂志

This article focused on basic clinical skill training of Changhai Hospital,in such aspects as courses,teaching infrastructure,faculty competence,teaching pattern,evaluation system and incentives mechanism.These efforts aim at exploring the establishment of a new clinical skills teaching model,which prove satisfactory and improving the standardized residents basic clinical skill training system.