Effects of alpha fetoprotein on escape of Bel 7402 cells from attack of lymphocytes

BACKGROUND: Involvement of AFP against apoptosis of tumor cell has been implicated in its evasion of immune surveillance. However, the molecular events of immune escape mechanisms are still unknown. The major observations reported here relate to a possible mechanism by which heptoloma Bel 7402 cells escape immune surveillance in vitro. METHODS: Western blotting and a well-characterized cofocal scanning image were performed to analyze the expression of Fas/FasL and caspase-3 in co-cultured Bel 7402 and Jurkat cells. RESULTS: After co-culture with Jurkat cells, up-regulated Fas and reduced FasL expression could be observed. Treatment with AFP could remarkably inhibit the elevated Fas and, whereas, induce the FasL expression in co-cultured Bel 7402 cells. Cells co-culture could induce the expression of caspase-3 in both cells line. The elevated caspase-3 in Bel 7402 cells was abolished following the treatment of AFP. The expression of caspase-3 was elevated in co-cultured Jurkat cells treated with AFP. No detectable change on the expression of survivin was examined in both cells line. Monoclonal antibody against AFP treatment alone did not obviously influence the growth of cells, as well as the expression of Fas/FasL and caspase-3. However, the effect of AFP could be blocked by antibody. CONCLUSIONS: our results provide evidence that AFP could promote the escape of liver cancer cells from immune surveillance through blocking the caspase signal pathway of tumor cells and triggering the Fas/FasL interaction between tumor cells and lymphocytes

Simultaneous Elimination of Formaldehyde and Ozone Byproduct Using Noble Metal Modified TiO2 Films in the Gaseous VUV Photocatalysis

Simultaneous removal of low concentration formaldehyde (HCHO) and ozone byproduct was investigated in the gaseous VUV (vacuum ultraviolet) photocatalysis by using noble metal modified TiO2 films. Noble metal (Pt, Au, or Pd) nanoparticles were deposited on TiO2 films with ultrafine particle size and uniform distribution. Under 35 h VUV irradiation, the HCHO gas (ca. 420 ppbv) was dynamically degraded to a level of 10~45 ppbv without catalyst deactivation, and over 50% O3 byproduct was in situ decomposed in the reactor. However, under the same conditions, the outlet HCHO concentration remained at 125~178 ppbv in the O3 + UV254 nm photocatalysis process and 190~260 ppbv in the UV254 nm photocatalysis process. And the catalyst deactivation also appeared under UV254 nm irradiation. Metallic Pt or Au could simultaneously increase the elimination of HCHO and ozone, but the PdO oxide seemed to inhibit the HCHO oxidation in the UV254 nm photocatalysis. Deposition of metallic Pt or Au reduces the recombination of h+/e− pairs and thus increases the HCHO oxidation and O3 reduction reactions. In addition, adsorbed O3 may be partly decomposed by photogenerated electrons trapped on metallic Pt or Au nanoparticles under UV irradiation

Prediction and Optimization of Blasting-Induced Ground Vibration in Open-Pit Mines Using Intelligent Algorithms

Prediction and parameter optimization are effective methods for mine personnel to control blast-induced ground vibration. However, the challenge of effective prediction and optimization lies in the multi-factor and multi-effect nature of open-pit blasting. This study proposes a hybrid intelligent model to predict ground vibrations using a least-squares support vector machine (LSSVM) optimized by a particle swarm algorithm (PSO). Meanwhile, multi-objective particle swarm optimization (MOPSO) was used to optimize the blast design parameters by considering the vibration of particular areas and the bulk rate of blast fragmentation. To compare the prediction performance of PSO-LSSVM, a genetic-algorithm-optimized BP neural network (GA-BP), unoptimized LSSVM, and BP were used, by applying the same database. In addition, the root-mean-squared error (RMSE), the mean absolute error (MAE), and the correlation coefficient (r) were regarded as the evaluation indicators. Furthermore, the optimization results of the blasting parameters were obtained by quoting the established vibration prediction model and bulk rate proxy model in MOPSO and verified by field tests. The results indicated that the PSO-LSSVM model provided the highest efficiency in predicting vibrations with an RMSE of 1.954, MAE of 1.717, and r of 0.965. Furthermore, the blasting vibration can be controlled by using the two-objective optimization model to obtain the best blasting parameters. Consequently, this study can provide more specific recommendations for vibration hazard control