Objective:To construct and validate a predictive model for the risk of cerebrogenic multiple organ dysfunction syndrome (CMODS) in patients with acute cerebral hemorrhage.Methods:Clinical data of 93 patients with acute cerebral hemorrhage admitted to Wannan Rehabilitation Hospital from January 2019 to June 2023 were retrospectively analyzed. Data included baseline information, disease severity score, laboratory examination indicators, cerebral hemorrhage status, treatment status, etc. Patients were divided into CMODS group and non-CMODS group according to whether CMODS occurred during hospitalization. The clinical data of the two groups were compared. Multivariate Logistic regression was used to analyze the risk factors of CMODS in patients with acute cerebral hemorrhage. A nomogram model was constructed to predict the risk of CMODS in patients with acute cerebral hemorrhage, and the model was validated. Receiver operator characteristic curve (ROC curve) was used to evaluate the predictive efficiency of nomogram model for CMODS in patients with acute cerebral hemorrhage.Results:A total of 93 patients with acute cerebral hemorrhage were enrolled, including 26 patients in CMODS group and 67 patients in non-CMODS group. Compared with the non-CMODS group, the ratio of diabetes, acute physiological and chronic health evaluationⅡ(APACHEⅡ)≥35 score, cerebral hemorrhage volume ≥30 mL, endotoxemia, and national institutes of health stroke scale (NIHSS) and intracranial pressure of patients in the CMODS group were significantly higher, while the Glasgow coma score (GCS) was significantly lower and the length of hospital stay was significantly longer, with statistically significant differences (all P < 0.05). Multivariate Logistic regression analysis showed that diabetes mellitus [odds ratio ( OR) = 3.615, 95% confidence interval (95% CI) was 1.487-8.785, P = 0.000], APACHEⅡscore ( OR = 4.697, 95% CI was 1.933-11.416, P = 0.000), endotoxemia ( OR = 4.577, 95% CI was 1.883-11.123, P = 0.000), and cerebral hemorrhage volume ( OR = 4.039, 95% CI was 1.662-9.816, P = 0.000) were the risk factors for CMODS in patients with acute cerebral hemorrhage. Taking the above risk factors as predictive variables, a nomogram prediction model was established. The verification results of the nomogram model showed that the C index was 0.804 (95% CI was 0.768-0.841), and the calibration curve was close to the ideal curve with good fit ( P > 0.05). ROC curve results showed that the sensitivity and specificity of the nomogram model in predicting CMODS in patients with acute cerebral hemorrhage were 76.92%, 86.57%, respectively, and the area under the ROC curve (AUC) was 0.855 (95% CI was 0.776-0.935). Conclusions:Diabetes mellitus, APACHEⅡscore, endotoxemia and intracerebral hemorrhage are risk factors for CMODS in patients with acute cerebral hemorrhage. The risk prediction model based on these risk factors is effective in evaluating the risk of CMODS in patients with acute cerebral hemorrhage.

The potential effects of recombinant shark hepatical stimulator analogue (r-sHSA) in liver disease have been revealed in our previous studies. In order to further evaluate its clinic application, we carried out high cell-density fermentation in 5 L fermentor to get enough products. Based on the trials in shaking flask, we optimized the parameters for 5 L fermentor, including medium composition, medium supplement, inducer concentration and induction time, etc. In detail, the improved LB medium (0.97% glycerol, 0.91% yeast extract, 0.72% tryptone, 0.782% KH2PO4, 0.267% K2HPO4.3H2O, 0.062% MgSO4.7H2O, 0.5% NaCl, pH 7.0) is chosen to cultivate the engineering bacteria with the constant fermentation condition (pH 7.0, and the dissolved oxygen concentration is about 25%-30%). When bacterial culture reaches exponential phase, the modified feeding medium (620 g/L glycerol, 94.8 g/L tryptone, 3.3 mL/L trace elements, and 7.5 g/L MgSO4.7H2O) is then supplied through the method of exponential fed-batch mode. After the optical density (OD600) of engineering bacterial culture reaches to 23, the ultimately concentration of 0.5 mmol/L IPTG is added to induce the expression of r-sHSA for 6 h. Results show that the amount of r-sHSA production is (2.662 +/- 0.041) g/L, which is about 13.7 folds of the one optimized before.
Animals ; Cloning, Molecular ; Escherichia coli ; genetics ; metabolism ; Fermentation ; Liver ; chemistry ; Peptides ; genetics ; metabolism ; Recombinant Proteins ; biosynthesis ; genetics ; Sharks ; metabolism