Objective To estimate the anticoagulant and thrombolytic effects of a novel fibrinolytic enzyme with a low molecular weight for further carrying on animal test and clinic research.Methods Using pH7.4,0.9 % NaCl as negative control and lumbrukinase as positive control,the anticoagulant and thrombolytic effects of the novel marine fibrinolytic enzyme were investigated in vitro with fresh blood from wistar rat and rabbit,respectively.Results The results showed that there were apparent anticoagulant effect as well as thrombolytic effects in the self-made marine fibrinolytic enzyme,and the status of the released blood cells from thrombus using this enzyme was also better than that of using lumbrukinase.Conclusion The novel self-made fibrinolytic enzyme is a potent thrombolytic agent.

Objective To study the acute toxicity of slow-release (poly lactic-co-glycolic acid) PLGA-gemcitabine microsphere and gemcitabine on mice.Methods Up and down procedure (UDP) was used to determine the median lethal dose (LD50) of PLGA-gemcitabine microsphere and gemcitabine on mice respectively.Results The LD50 of PLGA-gemcitabine microsphere on mice was 256.30 mg/kg,gemcitabine was 8.91 mg/kg.The difference was 28.8 times.Conclusion PLGA-gemcitabine microsphere can markedly reduce the acute toxicity of gemcitabine.

Objective To establish a rapid,accurate,specific quantitative assay for detecting B.pertussis,and apply to clinical diagnosis.Methods According to the specific sequence of B.pertussis IS481 gene,the primers and the fluorescence probe were designed and synthesized.Then a fluorescence quantitative PCR for detecting B.pertussis was developed.The specificity,sensitivity and reproducibility of the method were evaluated.255 specimens including 225 nasopharyngeal swabs from suspected pertussis patients and 30 normal nasopharyngeal swabs were detected by fluorescence quantitative PCR.Results A rapid specific quantitative method for detecting B.pertussis was established.The standard curve of the method indicated that there was a good linear relationship between the CT value and the template concentration with the correlation coefficient being 0.998.The linear range of the system was from 102 to 108 copies/μl and the minimum was 102 copies.It had a high sensitivity and good specificity.The intra.and inter-assay coefficients of variation were 5.78%-16.7% and 8.25%-14.9% respectively.The fluorescence quantitative PCR identified 41 positive results for specimens from suspected pertussis patients and results of 30 normal specimens were all negative.Conclusions The method can quantitatively detect the B.pertussis rapidly with high sensitivity and specificity,it can be applied to clinical diagnosis.

Objective To evaluate wall histological abnormalities 2 to 3 cm to the end in high or intermediate anal atresia in order to identify features that explain postoperative bowel dysfunctions.Methods Sixty anal atresia patients treated in the Capital Pediatric Institution between January 2008 and December 2012 were recruited in our study.36 patients were resected the terminal anal segment (3 cm).Compared with those 24 cases who were not.Resected samples were fixed for HE and immuno-histochemical stainings.Clinical data including sacral ratio (SR),age at operation,gender,bowel function were evaluated.Results There was no significant difference in patients' SR value,gender and age at operation between resected group and control group.The median follow-up period was 4.5 years.The rates of voluntary bowel movement,soiling (grade 1,2,3) were similar in both groups,however,the rates of severe constipation in resection group was significantly lower that in control group (3 ％ vs.21％,P ＜ 0.05) In the bowel wall of distal 2 cm anrectal canal,the connective tissue was found to be irregular and abnormally represented.Muscle coat was abnormal in all cases,showing the dysplasia circular and longitudinal layers.The number of enteric nervous system was significant fewer in distal 2cm anrectal canal than that in distal 3 cm(1.6 ±0.9 vs.5.6 ±1.8,t=11.715,P＜0.01).Conclusions Resection of terminal 3 cm at least of the atresia anal canal benefits postoperative bowel defecation function.

In this study, the natural biological inducer, rat regenerating pancreatic extract (RPE), was used to induce human amniotic mesenchymal stem cells (hAMSCs) into insulin-secreting cells. We excised 60% of rat pancreas in order to stimulate pancreatic regeneration. RPE was extracted and used to induce hAMSCs at a final concentration of 20 microg/mL. The experiment methods used were as follows: morphological-identification, dithizone staining, immumofluorescence analysis, reverse transcription-PCR (RT-PCR) and insulin secretion stimulated by high glucose. The results show that the cell morphology of passge3 hAMSCs changed significantly after the induction of RPE, resulting in cluster shape after induction for 15 days. Dithizone staining showed that there were scarlet cell masses in RPE-treated culture. Immumofluorescence analysis indicated that induced cells were insulin-positive expression. RT-PCR showed the positive expression of human islet-related genes Pdx1 and insulin in the induced cells. The result of insulin secretion stimulated by high glucose indicated that insulin increasingly secreted and then kept stable with prolongation of high glucose stimulation. In conclusion, hAMSCs had the potential to differentiate into insulin-secreting cells induced by RPE in vitro.
Amnion ; cytology ; Animals ; Cell Differentiation ; physiology ; Cells, Cultured ; Humans ; Insulin-Secreting Cells ; cytology ; Mesenchymal Stromal Cells ; cytology ; Pancreas ; physiology ; surgery ; Pancreatic Extracts ; pharmacology ; Rats ; Regeneration

Objective:Peripheral nerve invasion (PNI) is associated with local recurrence and poor prognosis in patients with advanced gastric cancer. A risk-assessment model based on preoperative indicators for predicting PNI of gastric cancer may help to formulate a more reasonable and accurate individualized diagnosis and treatment plan.Methods:Inclusion criteria: (1) electronic gastroscopy and enhanced CT examination of the upper abdomen were performed before surgery; (2) radical gastric cancer surgery (D2 lymph node dissection, R0 resection) was performed; (3) no distant metastasis was confirmed before and during operation; (4) postoperative pathology showed an advanced gastric cancer (T2-4aN0-3M0), and the clinical data was complete. Those who had other malignant tumors at the same time or in the past, and received neoadjuvant radiochemotherapy or immunotherapy before surgery were excluded. In this retrospective case-control study, 550 patients with advanced gastric cancer who underwent curative gastrectomy between September 2017 and June 2019 were selected from the Affiliated Hospital of Qingdao University for modeling and internal verification, including 262 (47.6%) PNI positive and 288 (52.4%) PNI negative patients. According to the same standard, clinical data of 50 patients with advanced gastric cancer who underwent radical surgery from July to November 2019 in Qingdao Municipal Hospital were selected for external verification of the model. There were no statistically significant differences between the clinical data of internal verification and external verification (all P>0.05). Univariate analysis and multivariate logistic regression analysis were used to determine the independent risk factors for PNI in advanced gastric cancer, and the clinical indicators with statistically significant difference were used to establish a preoperative nomogram model through R software. The Bootstrap method was applied as internal verification to show the robustness of the model. The discrimination of the nomogram was determined by calculating the average consistency index (C-index). The calibration curve was used to evaluate the consistency of the predicted results with the actual results. The Hosmer-Lemeshow test was used to examine the goodness of fit of the discriminant model. During external verification, the corresponding C-index index was also calculated. The area under ROC curve (AUC) was used to evaluate the predictive ability of the nomogram in the internal verification and external verification groups. Results:A total of 550 patients were identified in this study, 262 (47.6%) of which had PNI. Multivariate logistic regression analysis revealed that carcinoembryonic antigen level ≥ 5 μg/L (OR=5.870, 95% CI: 3.281-10.502, P<0.001), tumor length ≥5 cm (OR=5.539,95% CI: 3.165-9.694, P<0.001), mixed Lauren classification (OR=2.611, 95%CI: 1.272-5.360, P=0.009), cT3 stage (OR=13.053, 95% CI: 5.612-30.361, P<0.001) and the presence of lymph node metastasis (OR=4.826, 95% CI: 2.729-8.533, P<0.001) were significant independent risk factors of PNI in advanced gastric cancer (all P<0.05). Based on these results, diffused Lauren classification and cT4 stage were included to establish a predictive nomogram model. CEA ≥ 5 μg/L was for 68 points, tumor length ≥ 5 cm was for 67 points, mixed Lauren classification was for 21 points, diffused Lauren classification was for 38 points, cT3 stage was for 75 points, cT4 stage was for 100 points, and lymph node metastasis was for 62 points. Adding the scores of all risk factors was total score, and the probability corresponding to the total score was the probability that the model predicted PNI in advanced gastric cancer before surgery. The internal verification result revealed that the AUC of nomogram was 0.935, which was superior than that of any single variable, such as CEA, Lauren classification, cT stage, tumor length and lymph node metastasis (AUC: 0.731, 0.595, 0.838, 0.757 and 0.802, respectively). The external verification result revealed the AUC of nomogram was 0.828. The C-ndex was 0.931 after internal verification. External verification showed a C-index of 0.828 from the model. The calibration curve showed that the predictive results were good in accordance with the actual results ( P=0.415). Conclusion:A nomogram model constructed by CEA, tumor length, Lauren classification (mixed, diffuse), cT stage, and lymph node metastasis can predict the PNI of advanced gastric cancer before surgery.

Objective:Peripheral nerve invasion (PNI) is associated with local recurrence and poor prognosis in patients with advanced gastric cancer. A risk-assessment model based on preoperative indicators for predicting PNI of gastric cancer may help to formulate a more reasonable and accurate individualized diagnosis and treatment plan.Methods:Inclusion criteria: (1) electronic gastroscopy and enhanced CT examination of the upper abdomen were performed before surgery; (2) radical gastric cancer surgery (D2 lymph node dissection, R0 resection) was performed; (3) no distant metastasis was confirmed before and during operation; (4) postoperative pathology showed an advanced gastric cancer (T2-4aN0-3M0), and the clinical data was complete. Those who had other malignant tumors at the same time or in the past, and received neoadjuvant radiochemotherapy or immunotherapy before surgery were excluded. In this retrospective case-control study, 550 patients with advanced gastric cancer who underwent curative gastrectomy between September 2017 and June 2019 were selected from the Affiliated Hospital of Qingdao University for modeling and internal verification, including 262 (47.6%) PNI positive and 288 (52.4%) PNI negative patients. According to the same standard, clinical data of 50 patients with advanced gastric cancer who underwent radical surgery from July to November 2019 in Qingdao Municipal Hospital were selected for external verification of the model. There were no statistically significant differences between the clinical data of internal verification and external verification (all P>0.05). Univariate analysis and multivariate logistic regression analysis were used to determine the independent risk factors for PNI in advanced gastric cancer, and the clinical indicators with statistically significant difference were used to establish a preoperative nomogram model through R software. The Bootstrap method was applied as internal verification to show the robustness of the model. The discrimination of the nomogram was determined by calculating the average consistency index (C-index). The calibration curve was used to evaluate the consistency of the predicted results with the actual results. The Hosmer-Lemeshow test was used to examine the goodness of fit of the discriminant model. During external verification, the corresponding C-index index was also calculated. The area under ROC curve (AUC) was used to evaluate the predictive ability of the nomogram in the internal verification and external verification groups. Results:A total of 550 patients were identified in this study, 262 (47.6%) of which had PNI. Multivariate logistic regression analysis revealed that carcinoembryonic antigen level ≥ 5 μg/L (OR=5.870, 95% CI: 3.281-10.502, P<0.001), tumor length ≥5 cm (OR=5.539,95% CI: 3.165-9.694, P<0.001), mixed Lauren classification (OR=2.611, 95%CI: 1.272-5.360, P=0.009), cT3 stage (OR=13.053, 95% CI: 5.612-30.361, P<0.001) and the presence of lymph node metastasis (OR=4.826, 95% CI: 2.729-8.533, P<0.001) were significant independent risk factors of PNI in advanced gastric cancer (all P<0.05). Based on these results, diffused Lauren classification and cT4 stage were included to establish a predictive nomogram model. CEA ≥ 5 μg/L was for 68 points, tumor length ≥ 5 cm was for 67 points, mixed Lauren classification was for 21 points, diffused Lauren classification was for 38 points, cT3 stage was for 75 points, cT4 stage was for 100 points, and lymph node metastasis was for 62 points. Adding the scores of all risk factors was total score, and the probability corresponding to the total score was the probability that the model predicted PNI in advanced gastric cancer before surgery. The internal verification result revealed that the AUC of nomogram was 0.935, which was superior than that of any single variable, such as CEA, Lauren classification, cT stage, tumor length and lymph node metastasis (AUC: 0.731, 0.595, 0.838, 0.757 and 0.802, respectively). The external verification result revealed the AUC of nomogram was 0.828. The C-ndex was 0.931 after internal verification. External verification showed a C-index of 0.828 from the model. The calibration curve showed that the predictive results were good in accordance with the actual results ( P=0.415). Conclusion:A nomogram model constructed by CEA, tumor length, Lauren classification (mixed, diffuse), cT stage, and lymph node metastasis can predict the PNI of advanced gastric cancer before surgery.