ObjectiveTo evaluate the in vivo biological safety of porous zinc oxide (ZnO)/hydroxyapatite (HA) composite materials.MethodsThe porous ZnO/HA composite materials and porous HA materials were prepared by the spark plasma sintering technology. First, the materials were characterized, including scanning electron microscopy to observe the material structure, in vitro degradation experiments to detect the degradation rate of the materials, and inductively coupled plasma emission spectrometer to detect the concentration of Zn2+ dissolved out of the composite material degradation. Then the two kinds of material extracts were prepared for acute systemic toxicity test. Fifteen male Kunming mice were randomly divided into groups A, B, and C (n=5) and injected intraperitoneally with normal saline, HA extracts, and ZnO/HA extracts, respectively. The body mass of the mice was recorded before injection and at 24, 48, and 72 hours after injection. The liver and kidney tissues were taken at 72 hours for HE staining to evaluate the safety of the composite material. Finally, the biological safety of the material in vivo was evaluated by implantation experiment. The eighteen male New Zealand white rabbits were randomly divided into HA group and ZnO/HA group (n=9); a bilateral radius defect model (1 cm) was established, and the right forelimbs of the two groups were implanted with porous HA materials and porous ZnO/HA composite materials, respectively; the left untreated as a blank control. The general condition of the animals were observed after operation. The rabbit blood was collected at 1 day before operation and at 1 day, 1 week, 4 weeks, and 8 weeks after operation for routine blood test (inflammation-related indicators) and blood biochemistry (liver and kidney function-related indicators). X-ray films were taken at 4, 8, and 12 weeks after operation to observe the repair of bone defects.ResultsMaterial characterization showed that porous ZnO/HA composite materials had interconnected large and small pore structures with a pore size between 50 and 500 μm, which degraded faster than porous HA materials, and continuously and slowly dissolved Zn2+. The acute systemic toxicity test showed that the mice in each group had no abnormal performance after injection, and the body mass increased (P<0.05). HE staining showed that the cells shape and structure of liver and kidney tissue were normal. Animal implantation experiments showed that all rabbits survived until the experiment was completed; routine blood tests showed inflammation in each group (neutrophils, monocytes, and lymphocytes increased) at 1 day after operation, and all returned to normal at 8 weeks (P>0.05); compared with 1 day before operation, the content of inflammatory cells in the HA group increased at 1 day, 1 week, and 4 weeks after operation (P<0.05), and the ZnO/HA group increased at 1 day after operation (P<0.05); blood biochemistry showed that the liver and kidney function indexes were in the normal range; X-ray films showed that the ZnO/HA group had better osseointegration than the HA group at 4 weeks after operation.ConclusionThe porous ZnO/HA composite material has good in vivo biological safety and good bone repair ability, which is a potential bone repair material.
ObjectiveTo analyze the clinical characteristics and survival of pulmonary fibrosis (PF) patients complicated with lung cancer (LC) (PL-LC).
MethodsFifty-three patients with PF diagnosed as LC from January 2008 to March 2014 in Nanjing Drum Tower Hospital were included in this study. Univariate analysis and Cox regression analysis were used to detect the effects of clinical variables on survival. Kaplan-Meier method was used to calculate the median survival time (MST) and overall survival (OS).
ResultsMale patients (n=48, 90.6%) and patients with a history of smoking (n=42, 79.2%) were more easily suffered from PF-LC. The average age was 68.6±9.5 years. Cox multivariate analysis revealed that Velcro crackles (P=0.009) and clinical stage (P=0.013) were the independent risk factors of survival in the patients with PF-LC. The MST of 53 patients was 6.0 months.The survival rates of 1-year and 2-year were 34.1% and 22.0%, respectively. Forty-two (79.2%) patients were idiopathic pulmonary fibrosis (IPF) complicated with LC, and 11 (20.8%) patients were secondary pulmonary fibrosis (SPF) complicated with LC. OS difference between two groups was not significant (P=0.610). OS of NSCLC group (n=37) was significantly prolonged than that of SCLC group (n=6) and unclassified pathological pattern group (n=10) (P=0.035). OS of Ⅰ and Ⅱstage patients (n=13) was significantly longer than that of Ⅲ and Ⅳ stage patients (n=40) (P=0.002). MST and OS of patients with LC treated (n=31) were significantly better than those of untreated patients (n=22) (P < 0.001) and OS of patients treated by comprehensive therapy (n=11) was significantly prolonged than that of patients treated by mono-therapy (n=20) (P=0.036).
ConclusionsVelcro crackles and clinical stages are the independent risk factors of prognosis in PF-LC patients. It is beneficial to survival if the PF patients with LC were treated by comprehensive therapy.
The in-vivo electron paramagnetic resonance (EPR) method can be used for on-site, rapid, and non-invasive detection of radiation dose to casualties after nuclear and radiation emergencies. For in-vivo EPR spectrum analysis, manual labeling of peaks and calculation of signal intensity are often used, which have problems such as large workload and interference by subjective factors. In this study, a method for automatic classification and identification of in-vivo EPR spectra was established using support vector machine (SVM) technology, which can in-batch and automatically identify and screen out invalid spectra due to vibration and dental surface water interference during in-vivo EPR measurements. In this study, a spectrum analysis method based on genetic algorithm optimization neural network (GA-BPNN) was established, which can automatically identify the radiation-induced signals in in-vivo EPR spectra and predict the radiation doses received by the injured. The experimental results showed that the SVM and GA-BPNN spectrum processing methods established in this study could effectively accomplish the automatic spectra classification and radiation dose prediction, and could meet the needs of dose assessment in nuclear emergency. This study explored the application of machine learning methods in EPR spectrum processing, improved the intelligence level of EPR spectrum processing, and would help to enhance the efficiency of mass EPR spectra processing.
