125 strains of the symbiotic and epiphyte microorganisms were isolated from marine organisms (sea cucumber, sea urchin,anemone, sea actinia, Ulra, Sargassum, Undaria). Among them,21 strains of bacteria,8 strains of actinomycetes and 2 strains of fungi showed antagonistic activity on bacterial or fungal growth. In the 21 strains of bacteria, 7 strains belong to Bacillus sp., 11 strains Vibrio sp., and 3 strains Pseudomonas sp.. In the 8 strains of actinomycetes, 5 strains belong to Streptomyces sp., 3 strains Micromonospora sp., 2 strains fungi Penicillum sp..

Objective To evaluate islet cells functional recovery and clinical effects of dynamic blood sugar monitoring combined with insulin pump in newly diagnosed type 2 diabetes mellitus in the elderly.Methods 300 cases with newly diagnosed type 2 diabetes mellitus were randomly divided into treatment group (n=150) and control group (n=150) accompanying with three months follow-up.Body mass indexes (BMI),levels of hemoglobin A1c (HbA1c),fasting plasma glucose (FPG),2-h postprandial blood glucose,fasting insulin,2-h postprandial insulin,fasting C-peptide,2-h postprandial C peptide,and the percentage of patients who took oral hypoglycemic drugs alone without insulin could well control the blood glucose were compared between the two groups before versus after treatment.Results The levels of BMI,HbA1c,FPG,2-h postprandial blood glucose,fasting insulin,2-h postprandial insulin,fasting C peptide,2-h postprandial C peptide in the two groups were significantly decreased after treatment as compared with the pretreatment (P ＜ 0.05).The improvement of blood sugar spectrum was better in treatment group than in control group(P＜0.05) and the percentage of patients who took oral hypoglycemic drugs alone without insulin could well control the blood glucose was significantly higher in treatment group than in control group(21％ vs.3％,x2 =22.475,P＜0.05).Conclusions The clinical effects of dynamic blood sugar monitoring combined with insulin pump on newly diagnosed type 2 diabetes mellitus in the elderly is definite and can improve the recovery of islet cells function.It is worthy of clinical promotion.

Objective:To explore clinical value of multi-phase scan of spiral computed tomography(CT)combined with tumor markers in the diagnosis of gastric cancer.Methods:A total of 80 patients with highly suspected gastric cancer admitted to hospital from September 2019 to September 2023 were selected.All patients underwent multi-phase(arterial phase,venous phase,delayed phase)scan of spiral CT,and the tumor markers[carcinoembryonic antigen(CEA),carbohydrate antigen 724(CA724)and carbohydrate antigen 199(CA199)]of them were detected,as well as pathological examination.Based on the results of pathological examination,the CT values of multi-phase scan of spiral CT and tumor marker levels between patients with malignant tumor and patients with benign tumor were compared.The receiver operating characteristic(ROC)curve was drawn to analyze the diagnostic cut-off values of various parameters,and also analyze the diagnostic value of multi-phase scans of spiral CT combined with tumor markers for gastric cancer.Results:In 80 patients with highly suspected gastric cancer,62 cases were confirmed as malignant tumor by pathological examination.The CT values of arterial phase,venous phase and delayed phase,CEA,CA724 and CA199 levels in patients with malignant tumor were higher than those in patients with benign tumor(P＜0.05),respectively,and the differences of them were significant(t=10.322,15.195,19.123,17.115,14.494,14.041,P＜0.05).The results of ROC curve indicated that the area under curve(AUC)values of the CT values of arterial phase,venous phase and delayed phase of spiral CT examination,single CEA,single CA724,single CA199 and combination of them were all greater than 0.70 in diagnosing gastric cancer,and all of them had diagnostic value but the diagnostic value of combined detection was highest.The optimal diagnostic value could be obtained when the cut-off values of above indicators were respectively 82.275 HU,74.975 HU,50.445 HU,5.970ng/ml,8.385μg/l and 41.315U/ml.According to the results of pathological examination,the sensitivity,specificity and accuracy of multi-phase scan of spiral CT combined with tumor markers were respectively 96.77％,94.44％and 96.25％in diagnosing gastric cancer,and the consistency between the combined examination and the pathological examination was favorable(Kappa=0.895).Conclusion:The combination of multi-phase scan of spiral CT and tumor markers has higher diagnostic value for gastric cancer,which can be used as important auxiliary scheme for the diagnosis of gastric cancer.

Establishing fever clinic was an important achievement of the fight against severe acute respiratory syndrome (SARS) in 2003, and played an important role in the subsequent outbreaks of H1N1, H7N9 and Middle East respiratory syndrome (MERS). Fever clinics have significant emergency characteristics, but there are no rescue conditions in the fever clinics. Consequently, the problem of establishment and management of fever clinics is still outstanding. Based on the development of fever clinics, this paper analyzes the operational dilemma of fever clinics, explores the measures of establishment and management of fever clinics, and constructs the operational mechanism of fever clinics in order to provide the basis for the emergency management system of public health emergencies, which is suitable for Chinese health system.

Objective:To explore the predictive value of pre-biopsy serum inflammatory markers on positive prostate biopsy results, establish a nomogram model based on pre-biopsy inflammatory markers combined with other parameters, and evaluate its predictive ability for prostate biopsy results.Methods:The clinical data of 601 patients undergoing transperineal prostate biopsy who were admitted to the Second Hospital of Tianjin Medical University from August 2019 to August 2021 were retrospectively analyzed. The median age was 68(35, 89)years, and the median tPSA was 9.56(4.01, 19.95)ng/ml. The median fPSA was 1.36(0.88, 2.02)ng/ml, the median PSAD was 0.16(0.11, 0.26)ng/ml 2, and the median platelet-to-lymphocyte ratio(PLR)was 129.90(98.95, 169.89). PI-RADS v2.1 score<3 points in 189 cases(31.45%), 3 points in 174 cases(28.95%), 4 points in 190 cases(31.61%), and 5 points in 48 cases(7.99%). A simple randomization method was used to obtain 421 cases(70.00%)in the modeling group and 180 cases(30%)in the validation group.There was no significant difference in the clinical data between the two groups ( P>0.05). Univariate and multivariate logistic regression analysis were performed in the modeling group to screen independent influencing factors for the prediction of positive prostate biopsy results. A nomogram model was established and internal verification was conducted. External validation of the model was performed in the validation group. Receiver operating characteristic(ROC)curve was used to verify model discrimination, Hosmer-Lemeshow goodness-of-fit test was used to verify model calibration, and decision curve analysis (DCA) was used to evaluate the net benefit and clinical utility of the predictive model. Results:The results of univariate analysis showed that the age( OR=1.060, P<0.01), histological inflammation( OR=0.312, P<0.01), the number of biopsy needles( OR=0.949, P=0.009), f/tPSA( OR=0.954, P=0.003), PV( OR=0.973, P<0.01), PSAD( OR=29.260, P<0.01), PI-RADS v2.1 score(3-point OR=3.766, P=0.001; 4-point OR=11.800, P<0.01; 5-point OR=57.033, P<0.01), lymphocyte count( OR=1.535, P=0.013), NLR( OR=0.848, P=0.044), PLR( OR=0.994, P=0.005)and SII( OR=0.999, P=0.009)were statistically different between the prostate patients and non-prostate cancer patients in the modeling group; Multivariate analysis showed that age( OR=1.094, P<0.001), fPSA( OR=0.605, P=0.002), histological inflammation ( OR=0.241, P<0.001), PSAD ( OR=7.57, P=0.013), PLR ( OR=0.994, P=0.005) and PI-RADS v2.1 Score(3-point OR=2.737, P=0.016; 4-point OR=8.621, P<0.001; 5-point OR=47.65, P<0.001) was an independent influencing factor for prostate cancer at initial biopsy; a nomogram model based on age, fPSA, PSAD, PLR and PI-RADS v2.1 scores was established. The AUC of the modeling group was 0.849(95% CI 0.810-0.888), and the sensitivity was 80.9%, and the specificity was 76.1%; the AUC of the validation group was 0.862(95% CI 0.809-0.915), and the sensitivity was 91.9%, and the specificity was 67.8%, suggesting that the diagnostic prediction model had a good discrimination. The calibration curve showed that the prediction model was well calibrated ( χ2=6.137, P=0.632). The decision curve analysis (DCA) of the modeling and validation groups indicated a larger net benefit of the predictive model. Conclusions:The nomogram model established in this study based on age, fPSA, PSAD, PLR and PI-RADS v2.1 score showed good predictive efficacy for prostate biopsy in patients with PSA between 4-20 ng/ml.