Objective To investigate the regulative characterisitics of growth factors on proliferation of retinal pigment epithelial (RPE) cells in vitro. Methods Primary culture and subculture of RPE cells were establised in vitro Tumor.necrosis factor-alpha;(TNF-alpha;),interleukin-1beta;(IL-1beta;) and basic fibroblast growth factor (bFGF) in different concentrations were added to the RPE cells.3 H-thymidine(3 H-TdR) incorporation and a hemocytometer measured DNA synthesis and cell number separately. Results After RPE cells were separately treated with TNF-alpha;,IL-1beta; and bFGF,DNA synthesis was increased by 2.74,2.66 and 1.69 folds and cell number was increased by 54%,22% and 7amp; (Plt;0.05) respectively. When two growth factors were combined (TNF-alpha;+bFGF, IL-1beta;+bFGF),3.14,2.84 and 2.57 folds increased DNA synthesis significantly in each group (Plt;0.05). Compared with value by effect of two growth factors,the combination effect of three growth factors (TNF-alpha;+IL-1beta;+bFGF) was still ber (Plt;0.05). Conclusion The synergism of growth factors in their action might be one of the important roles in modulating the proliferation of RPE cells. (Chin J Ocul Fundus Dis,1998,14:95-97)
目的 建立重组人内皮抑素（恩度）联合顺铂一线治疗肿瘤进展的小鼠模型，继续应用内皮抑素联合紫杉醇二线治疗，研究内皮抑素协同紫杉醇抗肿瘤的作用及其机制。 方法 建立小鼠Lewis 肺癌移植瘤动物模型，内皮抑素联合顺铂治疗后观察肿瘤生长情况，遴选出肿瘤进展小鼠16只，随机留取1只，余15只小鼠随机分成紫杉醇组和联合用药组治疗，观察疗效。另取上述肿瘤进展小鼠1只，剥离肿瘤组织，重新接种，将成瘤小鼠随机分成生理盐水组，紫杉醇组及联合用药组治疗，观察疗效。治疗结束后24 h处死所有小鼠，采用免疫组织化学CD31单克隆抗体标记检测微血管密度（MVD），采用原位末端转移酶（TUNEL）检测细胞凋亡。 结果 只肿瘤进展小鼠中，联合用药组相比紫杉醇组生存时间无明显延长，但肿瘤体积增长较慢；而在重新接种成瘤的小鼠中，联合用药组较其余各组微血管密度明显减低（P＜0.05），凋亡指数明显增加（P＜0.05），肿瘤体积抑制明显。 结论 在内皮抑素联合顺铂治疗肿瘤进展的小鼠模型中，继续应用内皮抑素治疗与紫杉醇有较明显的协同抗肿瘤作用。
ObjectiveTo investigate the inhibitory effect of heat shock protein 90 (HSP90) inhibitors of 17-propylene amino-17-demethoxy geldanamycin (17-AAG) combining with paclitaxel on human anaplastic thyroid cancer FRO cell line. Method①The proliferation inhibition rates of FRO cells were detected by mmethyl thiazolyl tetrazolium (MTT) assay in different concentration groups (17-AAG: 0.312 5, 0.625 0, 1.2500, 2.5000, and 5.0000 μmol/L; paclitaxel: 0.001 0, 0.0100, 0.1000, and 1.0000 μmol/L; combination group, 17-AAG: 0.625 0 μmol/L, paclitaxel: 0.001 0, 0.0100, 0.1000, and 1.0000 μmol/L) and at different time points (24, 48, and 72 hours). ②The change of cell cycle and apoptosis rates of FRO cells were detected in 17-AAG group (0.625 0 μmol/L), paclitaxel group (0.1000 μmol/L), and combination group (17-AAG: 0.625 0 μmol/L, paclitaxel: 0.1000 μmol/L) by flow cytometry at 24 hours after treatment. ③activity of Caspase-3 and Caspase-9 in FRO cells of 17-AAG group (0.625 0 μmol/L), paclitaxel group (0.1000 μmol/L), and combination group (17-AAG: 0.625 0 μmol/L, paclitaxel: 0.1000 μmol/L) was detected by Caspase-3 detection reagent box and Caspase-9 detection reagent box respectively. FRO cells of normal control group were treated without any drug, but culture solution. Results①The proliferation inhibition rates of FRO cells increased with the increase of concentra-tion (17-AAG, paclitaxel, combination of 17-AAG and paclitaxel), there was significant difference between any 2 groups (normal control group included), P<0.05. In addition, the proliferation inhibition rates of FRO cells in any concentration group (normal control group excluded) increased over time (24, 48, and 72 hours), there was significant difference between any 2 time points (P<0.05). The proliferation inhibition rates of FRO cells in combination group were all higher than those of 17-AAG group and paclitaxel group in condition of same time point and same concentration (P<0.05). The q value of combination group was higher than 1.15 at 3 time points in all concentration, that meant 17-AAG could increase the efficiency of paclitaxel. ②The apoptosis rate of FRO cells in normal control group was lower than those of 17-AAG group, paclitaxel group, and combination group (P<0.05), and apoptosis rate of FRO cells in combination group was higher than those of 17-AAG group and paclitaxel group (P<0.05). ③Activity of Caspase-3 and Caspase-9 of FRO cells in normal control group were lower than those of 17-AAG group, paclitaxel group, and combination group (P<0.05), and activity of Caspase-3 and Caspase-9 of FRO cells in combination group were higher than those of 17-AAG group and paclitaxel group (P<0.05). Conclusions17-AAG and paclitaxel can significantly inhibit the proliferation and induce the apoptosis of FRO cells. The combination of the two kinds of drugs may generate synergy, with dose-dependence effect.
Dose-response meta-analysis serves an important role in investigating the dose-response relationship between independent variables (e.g. dosage) and disease outcomes. Traditional dose-response meta-analysis model is based on one independent variable to consider its own dose-specific effect on the outcome. However, for drug clinical trials, it generally involves two-dimensions of the treatment, such as dosage and course of treatment. These two-dimensions tend to be associated with each other. When neglecting their correlations, the results may be at risk of bias. Moreover, taking account of the "combined effect” of dosage and time on outcome has more clinical value. Therefore, in this article, based on traditional dose-response meta-analysis model, we propose a three-dimension model for dose-response meta-analysis which considers both the effect of dosage and time, to provide a solution for the above-mentioned problems in a traditional model.
Objective To explore the effect of salbutamol combined with Rho associated coiled-coil forming protein kinase (ROCK) inhibitor Y-27632 on airway smooth muscle and to find a new way for drug treatment of asthma. Methods Pig tracheal smooth muscle tissue strips were prepared, and after treatment they were divided into an electrical stimulation group (Fmax, 50%Fmax) and a blank group. The smooth muscle tissue strips were quickly frozen to determine the expression level of Rock-Ⅱ and the phosphorylation level of MLC20. The Fmax and 50%Fmax electrical stimulation groups were divided into a blank group, a salbutamol group, a Y-27632 group, and a salbutamol combined with Y-27632 group according to different intervention drugs. The relaxation of smooth muscle strips was observed. Results In the blank group, 50%Fmax group and Fmax group, the expression level of Rock-Ⅱ and the phosphorylation of MLC20 in smooth muscle tissue showed an increasing trend, with statistically significant differences (P<0.05). In the 4 subgroups of the 50%Fmax group intervention with different drugs (blank group, salbutamol group, Y-27632 group, salbutamol plus Y-27632 group), the diastolic ratio smooth muscle tissue strips showed an increasing trend. When the time reaches 10 min, the diastolic ratios were 0.7%, 2.5%, 6.0%, and 15.0%. the diastolic ratios were 1.8%, 4.5%, 7.5%, and 21.0% at the time of 20 min. the diastolic ratios were 1.9%, 7.5%, 7.9% and 22.0% at the time of 40 min. the diastolic ratios were 2.0%, 8.0%, 8.8%, and 22.5% at the time of 60 min. In the four subgroups of the Fmax electrical stimulation group, the relaxation ratio of smooth muscle tissue strips also showed an increasing trend. When the time reaches 10 min, the diastolic ratios were 1.0%, 3.0%, 7.0%, and 17.0%. the diastolic ratios were 2.6%, 5.5%, 9.0%, and 24.0% at the time of 20 min. the diastolic ratios were 2.8%, 9.0%, 9.5%, and 27.5% at the time of 40 min. diastolic ratios were 2.9%, 10.5%, 10.5%, and 28.0% at the time of 60 min. The analysis of difference between groups showed that at the same time, the diastolic ratio of smooth muscle in salbutamol combined with Y-27632 group was significantly higher than that in salbutamol alone group and Y-27632 group (P<0.05). In addition, the smooth muscle diastolic ratio of combined intervention was also better than the the mathematical sum effect of both single drug intervention (P<0.05). Conclusions The contractility and intensity of smooth muscle are positively correlated with the expression level of ROCK and the phosphorylation level of MLC20. Salbutamol combined with Y-27632 can enhance the relaxation of porcine airway smooth muscle, which may have a synergistic effect.
The synergistic effect of drug combinations can solve the problem of acquired resistance to single drug therapy and has great potential for the treatment of complex diseases such as cancer. In this study, to explore the impact of interactions between different drug molecules on the effect of anticancer drugs, we proposed a Transformer-based deep learning prediction model—SMILESynergy. First, the drug text data—simplified molecular input line entry system (SMILES) were used to represent the drug molecules, and drug molecule isomers were generated through SMILES Enumeration for data augmentation. Then, the attention mechanism in the Transformer was used to encode and decode the drug molecules after data augmentation, and finally, a multi-layer perceptron (MLP) was connected to obtain the synergy value of the drugs. Experimental results showed that our model had a mean squared error of 51.34 in regression analysis, an accuracy of 0.97 in classification analysis, and better predictive performance than the DeepSynergy and MulinputSynergy models. SMILESynergy offers improved predictive performance to assist researchers in rapidly screening optimal drug combinations to improve cancer treatment outcomes.