1.Analysis of Th1-Th2-Th3 related gene expressions in the thymus of mice irradiated with different doses
Hui GAO ; Siyao ZUO ; Zhengji HUANG ; Hailing HAN ; Juancong DONG ; Haiqin ZHANG ; Shunzi JIN
Chinese Journal of Radiological Medicine and Protection 2015;35(4):248-251
Objective To analyze the effect of high and low dose radiation on the expressions of Th1,Th2 and Th3 /Tr1 related-genes in mice thymocytes and investigate the possible underlying molecular mechanism.Methods ICR mice were randomly divided into low-dose group (0.075 Gy),high-dose group (2.0 Gy) and sham-control group.The mouse thymus tissue was extracted at 16 hours after irradiation and the expressions of Th1-Th2-Th3 related genes were measured by PCR array.Results Eight genes were up-regulated and five genes were down-regulated after low dose radiation (0.075 Gy);while 54 genes were up-regulated and three genes were down-regulated after high dose (2.0 Gy) radiation.These genes included Th1 cell related genes,Th2 cell related genes,Th3/Tr1 cell related genes,Th1/Th2 immune response genes and transcription factor related genes.Low dose radiation induced up-regulation of Stat4 and Socs1 of genes related to the Th1 cells,and it induced down-regulation of IL-4ra,Cebpb,Gata3 and Tgfb3 associated with Th2 and Th3 cells,which lead to Sftpd genes up-regulation of Th1 immune response eventually.The high dose radiation up-regulated all of Th1,Th2 and Th3/Tr related genes and also enhanced the expressions of Cd86,IL-18,IL-10 and Irf4 genes related to Th2 immune response,but it did not alter the gene expression of Th1 immune response.Conclusions Low-dose radiation induces Th1-type immune response,while high doses radiation triggers Th2 type immune response.
2.Near-infrared Spectroscopic Quality Control on Coating Process of Vitamin C Yinqiao Tablets
Qing TAO ; Li JIANG ; Youbing ZHONG ; Zhengji JIN ; Xiaoyong RAO ; Wei LIU ; Yan HE ; Yongkun GUO ; Xiaojian LUO
Chinese Journal of Experimental Traditional Medical Formulae 2024;30(14):184-190
ObjectiveTo construct a quantitative prediction model of three indicators(moisture absorption rate, film thickness and coating weight gain) during the coating process of Vitamin C Yinqiao tablets(VCYT) by near-infrared spectroscopy(NIRS), and to realize the endpoint judgment. MethodReal-time NIRS data of 4 batches of VCYT during the coating process were collected by diffuse reflection method. The coating method employed was the rolling coating method, and the samples were obtained at the spray stage from the coater's sampling port every 10 minutes, and 57 batches of samples(about 1 800 tablets) were collected at various coating times, the tablets were embedded in molten paraffin, cut longitudinally, and observed by stereomicroscope. The film thickness, with a target value of 38 μm, was then measured using Motic Images Advanced 3.2 software. Furthermore, the mositure absorption rate of samples, aiming for a target value of 3%, was determined in accordance with guiding principles for drug hygroscopicity testing in the 2020 edition of Chinese Pharmacopoeia, and 3 samples were randomly selected from each batch(10 tablets per batch), and the coating weight gain was calculated(target value of 4%). Partial least squares regression(PLSR) was used to construct a quantitative model of the 3 coating indicators, and the predicted values of the coating indicators were smoothed using the moving average method and used to determine the coating endpoints. ResultThe prediction determination coefficients(Rp2) for moisture absorption rate, film thickness and coating weight gain were 0.933 4, 0.932 6 and 0.965 9, the root mean square errors of prediction(RMSEP) were 0.163 5%, 1.870 9 μm and 0.240 3%, the relative percent deviations(RPD) were 3.711 0, 2.760 7 and 5.415 8, respectively. The results of the external validation set demonstrated that the real-time predicted values obtained by the models exhibited the same trend as the measured values, and the coating endpoint could be accurately predicted(with a prediction error of less than 7.32 min and a relative error of less than 5.63%). ConclusionThe established NIRS model exhibits excellent predictive performance and can be used for quality control of VCYT during the coating process.