Objective To investigate the effect of T149-C and A163-G polymorphism of osteoprotegerin promoter region combined with low-body weight on bone mineral density (BMD) of postmenopausal osteoporosis women and postmenopausal healthy women. Methods Seventy-three postmenopausal osteoporosis women and 61 postmenopausal healthy women were enrolled. The shifted patterns were searched from randomly selected 25 samples by SSCP-PCR and their sequences were determined by cycle sequencing. The T149-C and A163-G polymorphisms were determined by PCR-RFLP. BMD of lumbar spines and femoral neck, Ward and trochanteric areas were measured by dual energy X-ray absorptiometry. Results T149-C and A163-G polymorphisms in the postmenopausal osteoporosis women and the postmenopausal healthy women were through Hardy Weinberg equilibrium. Both single and combined genotype frequencies of the T149-C and A163-G polymorphism did not show any difference between postmenopausal osteoporosis women and postmenopausal healthy women. The BMD levels of the postmenopausal osteoporosis women were significantly lower than those of the postmenopausal healthy women in lumbar spines and femoral neck, and BMI levels of the postmenopausal osteoporosis women was significantly lower than those of the postmenopausal healthy women. Conclusions The T149-C and A163-G polymorphism has no synergistic effect on bone mass in both the postmenopausal osteoporosis women and the postmenopausal healthy women. The single and combined genotypes of the T149-C and A163-G polymorphism may not be used as genetic markers in predicting their risk of developing osteoporosis in Chinese women of the Han nationality, but may be susceptible gene of osteoporosis.

Objective To construct the human osteoblast-like cell model with estrogen receptor α(ERα)subunit gene knocked down. Methods According to the computer-aided design(CAD),ERα-specific small interference RNA(siRNA)gene was synthesized and cloned into the expression vector pSilencer 4.1-CMV. The recombinant ERα siRNA plasmid was transfected into human osteoblast-like cell line MG63 by lipofectin,the cloned MG63 ceils were selected by hygromycin,and the cloned MG63 cell was cultured more than 20 passages after transfection.The expression of ERα mRNA in MG63 cells was detected by reverse transcription-polymerase chain reaction(RT-PCR).The expression and location of ERα protein were identified by immunocytochemistry.Compared with control groups,proliferation rate,growth cycle and expression did not show significant difference.Results The recombinant eukaryote plasmid vector was constructed.Furthermore,the recombinant plasmid knocked down ERα protein in human osteoblast-like cells. Conclusions The human osteoblast-like cell model with RNAi-knocked down ERα gene is constructed successfully.This model appears to be very useful for the future research on ERα biological characters and on molecular mechanism of bone metabolism.

Objective To investigate the changes and significance of early immune response in specific T cell with invasive pulmonary aspergillosis(IPA) patients. Methods Peripheral blood mononuclear cells (PBMCs) were separated from whole blood of 8 cases of healthy individuals (healthy group) and 24 cases of IPA patients (IPA group, including 6 cases of pathological diagnosis, 9 cases of clinical diagnosis and 9 cases of tentative diagnosis), and the heat-inactivated Aspergillus fumigatus spores (Conidia) was used as an antigen to stimulate PBMCs produce Aspergillus-specific T lymphocytes. Interferon-gamma (IFN-γ) secreation, type and ratio of cytokine synthesis was examined. Results In IPA group, dot enzyme linked immunosorbent assay(ELISPOT) showed that the positive rate of IFN-γin pathological diagnosis patients and clinical diagnosis patients (5/6,7/9) was higher than that in tentative diagnosis patients (3/9). The positive rate of IFN-γin IPA group was 62.5%(15/24), in healthy group was 0 (0/8), and there was significant difference (P<0.05). The levels of CD4+T and CD4+T/CD8+T in IPA group were 0.202 0±0.085 6 and 1.01±0.34, in healthy group were 0.3853±0.1265 and 1.55±0.41. The levels of CD4+T and CD4+T/CD8+T in IPA group were significantly lower than those in healthy group ( P<0.05 or<0.01). The level of CD 8+T in IPA group was 0.298 5±0.069 1, and in healthy group was 0.257 6±0.102 6. The level of CD8+T in IPA group was 05). Conclusion Conidia as antigen can induce the specific Th1-type immune response of IPA, and display the immune status of the IPA patients, and can provide new ideas and methods for the diagnosis and assessment of the disease.

BACKGROUND: superparamagnetic ferric oxide nanoparticle exhibits small diameter, good water solubility, histocompatibility, superparamagnetism and surface area effect, allowing the application in nuclear magnetic resonance and biomacromolecule as carriers. OBJECTIVE: To construct superparamagnetic iron oxide nanoparticles coated by dextran (DCIONP), determine its physical and magnetic properties and evaluate the magnetic properties of tumor cells labeled by DCIONP in vitro. METHODS: The DCIONP was obtained by means of classical coprecipitation in dextran solution. Its size was determined by the transmission electron microscopy, and the crystal formation in DCIONP was measured by X-ray diffraction analysis. T2 values as well as relaxation rate were evaluated with a 1.5T MR system. After ostecsarcoma cell line MG63, hepatocellular carcinoma cell line HGP2 and rat bone marrow-derived mesenchymal cells were labeled by DCIONP in vitro, the perls blue staining and the transmission electron microscopy were performed to observe intracellular iron. In addition, the change of magnetic signal intensity was measured by 1.5T MR. RESULTS AND CONCLUSION: The iron size was 10 nm and the formation of Fe_3O_4 crystal in DCIONP was confirmed by X-ray diffraction analysis. These nanoparticles possessed some characteristic of superparamagnetic and showed the spin-spin relaxation rate of 3.936×10~6 mol/s. After three kinds of cells were labeled by DCIONP, the nanoparticles were mainly located in nucleus, and partially in cytoplasm confirmed. The spin-spin relaxations were shortened gradually compared with increasing labeled cells. Obvious magnetic attenuation was measured at 2×10~9/L and 2×10~(10)/L labeled cells. Results show that the prepared nanoparticle with stable physical and magnetic prosperities was developed, and it is able to product characteristic magnetic attenuation on the magnetic labeled tumor cells by 1.5T MR.

Objective:To explore the feasibility of a classification prediction model for gamma pass rates (GPRs) under different intensity-modulated radiation therapy techniques for pelvic tumors using a radiomics-based machine learning approach, and compare the classification performance of four integrated tree models.Methods:With a retrospective collection of 409 plans using different IMRT techniques, the three-dimensional dose validation results were adopted based on modality measurements, with a GPR criterion of 3%/2 mm and 10% dose threshold. Then prediction were built models by extracting radiomics features based on dose documentation. Four machine learning algorithms were used, namely random forest (RF), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM). Their classification performance was evaluated by calculating sensitivity, specificity, F1 score, and AUC value. Results:The RF, AdaBoost, XGBoost, and LightGBM models had sensitivities of 0.96, 0.82, 0.93, and 0.89, specificities of 0.38, 0.54, 0.62, and 0.62, F1 scores of 0.86, 0.81, 0.88, and 0.86, and AUC values of 0.81, 0.77, 0.85, and 0.83, respectively. XGBoost model showed the highest sensitivity, specificity, F1 score, and AUC value, outperforming the other three models. Conclusions:To build a GPR classification prediction model using a radiomics-based machine learning approach is feasible for plans using different intensity-modulated radiotherapy techniques for pelvic tumors, providing a basis for future multi-institutional collaborative research on GPR prediction.