Objective:To analyze the cost-effectiveness of high-flux hemodialysis compared to low-flux hemodialysis in the treat-ment of End-Stage Renal Disease(ESRD)patients.Methods:Based on a literature review,a cost-effectiveness analysis model was established,using the Incremental Cost-Effectiveness Ratio(ICER)as the outcome indicator to evaluate the economic value of high-flux versus low-flux hemodialysis.One-way sensitivity analysis and probabilistic sensitivity analysis were conducted to further assess the robustness of the results.Results:In the treatment of ESRD patients,compared to low-flux hemodialysis,the ICER of high-flux hemodialysis was 234 882 yuan per QALY.The key factors influencing the model results were the cost discount rate,ef-fect discount rate,utility value of high-flux hemodialysis,and treatment costs.Conclusion:Compared to low-flux hemodialysis,high-flux hemodialysis demonstrates a cost-effectiveness advantage at a willingness-to-pay threshold of three times GDP per capita.

Objective:To investigate the serum metabonomics of pancreatic cancer and chronic pancreatitis patients and screen the differential metabolites for differentiating pancreatic cancer from chronic pancreatis.Methods:From June 2021 to June 2022, the clinical data of 54 patients diagnosed with pancreatic ductal adenocarcinoma in the Department of Hepatobiliary, Pancreatic and Splenic Surgery of the First Affiliated Hospital of Naval Medical University were collected. A total of 54 patients with chronic pancreatitis who were admitted at the same time were selected as the control group. UHPLC/Q-TOF MS-based metabonomics techniques were applied to analyze the difference in serum metabolites in the two groups with multivariate and univariate statistical method, and the different metabolites were screened and identified in accordance with the molecular weight, metabolites databases and mass spectrometry (MS)/MS information. Two-thirds of the cases were randomly selected from patients with pancreatic cancer and chronic pancreatitis as the modeling population, and the remaining population was used as the validation population. In the modeled population, the receiver operating characteristic curve (ROC) of the screened differential metabolites was plotted and the area under the curve (AUC) was calculated. Differential metabolite variables with AUC ≥75%, a VIP value ≥1.5 were selected into the logistic multivariate regression analysis model, and the regression equation and the regression coefficients of each selected independent variable were obtained by stepwise regression by backward method. The final selected differential metabolites were evaluated by the formula P=1/{1+Exp[-(β0+β1X1+β1X1+…+βiXi)]} to establish a diagnostic model and predict the clinical application value of the model by evaluating it compared to the CA19-9 ROC curve. At the same time, the non-parametric Bootstrap method was used to verify the diagnostic performance of the model in the validation population. Results:There were 18 kinds of different serum metabolits in the final screening and identification in the two groups. The level of hypoxanthine, L-carnitine, acetylcarnitine, C16 sphinganine, linoleic acid, palmitoylcarnitine, linoleyl carnitine, uracil deoxynucleotide, glycocholic chenodeoxycholic acid in serum of pancreatic cancer patients were higher than that in the chronic pancreatitis patients; Uric acid, tryptophan, indoxylsulfuric acid, 1-palmitoyl lysophosphatidic acid, LPA(18∶2/0∶0), LysoPE (18∶1/0∶0), LysoPC (14∶0), LysoPC(15∶0), LysoPC(16∶1) in the serum were lower in patients with pancreatic cancer compared with that in chronic pancreatitis patients, and all the differences were statistically significant (all P value <0.05). In the modeled population, the ROC curve was established according to the peak intensity of 18 differential metabolites, and the metabolic differentiators with AUC of ≥75% and VIP value of ≥1.5 were selected for logistic multivariate analysis, and finally linoleoleic carnitine and LPA (18∶2/0∶0) were included in the logistic regression model. The prediction model of pancreatic cancer with two serum metabolites linoleyl carnitine and LPA (18∶2/0∶0) was established. The AUC value (95% CI) of the prediction model was 0.91 (0.85-0.97), which was higher than that of CA19-9 (0.85, 0.76-0.94), the sensitivity and specificity were 86.4% and 80.6%, respectively, and the sensitivity was higher than that of CA19-9 (77.3%), but the specificity was lower than that of CA19-9 (91.7%). Internal validation showed than the AUC value (95% CI) of the prediction model was 0.91 (0.79-0.94), which was higher than that of CA19-9 ( P<0.05). Conclusions:The serum metabolites linolein carnitine and LPA(18∶2/0∶0) may be potential diagnostic markers to distinguish pancreatic cancer from patients with chronic pancreatitis.

Objective:To investigate the serum metabonomics of pancreatic cancer and chronic pancreatitis patients and screen the differential metabolites for differentiating pancreatic cancer from chronic pancreatis.Methods:From June 2021 to June 2022, the clinical data of 54 patients diagnosed with pancreatic ductal adenocarcinoma in the Department of Hepatobiliary, Pancreatic and Splenic Surgery of the First Affiliated Hospital of Naval Medical University were collected. A total of 54 patients with chronic pancreatitis who were admitted at the same time were selected as the control group. UHPLC/Q-TOF MS-based metabonomics techniques were applied to analyze the difference in serum metabolites in the two groups with multivariate and univariate statistical method, and the different metabolites were screened and identified in accordance with the molecular weight, metabolites databases and mass spectrometry (MS)/MS information. Two-thirds of the cases were randomly selected from patients with pancreatic cancer and chronic pancreatitis as the modeling population, and the remaining population was used as the validation population. In the modeled population, the receiver operating characteristic curve (ROC) of the screened differential metabolites was plotted and the area under the curve (AUC) was calculated. Differential metabolite variables with AUC ≥75%, a VIP value ≥1.5 were selected into the logistic multivariate regression analysis model, and the regression equation and the regression coefficients of each selected independent variable were obtained by stepwise regression by backward method. The final selected differential metabolites were evaluated by the formula P=1/{1+Exp[-(β0+β1X1+β1X1+…+βiXi)]} to establish a diagnostic model and predict the clinical application value of the model by evaluating it compared to the CA19-9 ROC curve. At the same time, the non-parametric Bootstrap method was used to verify the diagnostic performance of the model in the validation population. Results:There were 18 kinds of different serum metabolits in the final screening and identification in the two groups. The level of hypoxanthine, L-carnitine, acetylcarnitine, C16 sphinganine, linoleic acid, palmitoylcarnitine, linoleyl carnitine, uracil deoxynucleotide, glycocholic chenodeoxycholic acid in serum of pancreatic cancer patients were higher than that in the chronic pancreatitis patients; Uric acid, tryptophan, indoxylsulfuric acid, 1-palmitoyl lysophosphatidic acid, LPA(18∶2/0∶0), LysoPE (18∶1/0∶0), LysoPC (14∶0), LysoPC(15∶0), LysoPC(16∶1) in the serum were lower in patients with pancreatic cancer compared with that in chronic pancreatitis patients, and all the differences were statistically significant (all P value <0.05). In the modeled population, the ROC curve was established according to the peak intensity of 18 differential metabolites, and the metabolic differentiators with AUC of ≥75% and VIP value of ≥1.5 were selected for logistic multivariate analysis, and finally linoleoleic carnitine and LPA (18∶2/0∶0) were included in the logistic regression model. The prediction model of pancreatic cancer with two serum metabolites linoleyl carnitine and LPA (18∶2/0∶0) was established. The AUC value (95% CI) of the prediction model was 0.91 (0.85-0.97), which was higher than that of CA19-9 (0.85, 0.76-0.94), the sensitivity and specificity were 86.4% and 80.6%, respectively, and the sensitivity was higher than that of CA19-9 (77.3%), but the specificity was lower than that of CA19-9 (91.7%). Internal validation showed than the AUC value (95% CI) of the prediction model was 0.91 (0.79-0.94), which was higher than that of CA19-9 ( P<0.05). Conclusions:The serum metabolites linolein carnitine and LPA(18∶2/0∶0) may be potential diagnostic markers to distinguish pancreatic cancer from patients with chronic pancreatitis.

Objective:To analyze the cost-effectiveness of high-flux hemodialysis compared to low-flux hemodialysis in the treat-ment of End-Stage Renal Disease(ESRD)patients.Methods:Based on a literature review,a cost-effectiveness analysis model was established,using the Incremental Cost-Effectiveness Ratio(ICER)as the outcome indicator to evaluate the economic value of high-flux versus low-flux hemodialysis.One-way sensitivity analysis and probabilistic sensitivity analysis were conducted to further assess the robustness of the results.Results:In the treatment of ESRD patients,compared to low-flux hemodialysis,the ICER of high-flux hemodialysis was 234 882 yuan per QALY.The key factors influencing the model results were the cost discount rate,ef-fect discount rate,utility value of high-flux hemodialysis,and treatment costs.Conclusion:Compared to low-flux hemodialysis,high-flux hemodialysis demonstrates a cost-effectiveness advantage at a willingness-to-pay threshold of three times GDP per capita.

Objective To investigate antigen optimization of Shisa like protein 1 (SHISAL1) for preparing mouse anti-human SHISAL1 polyclonal antibody and to identify the specificity of the prepared antibody. Methods Bioinformatics was employed to predict the antigenic epitope region of SHISAL1 protein, and then a polypeptide composed of amino acid residues from the site of 28 to 97 of SHISAL1, termed SHISAL1-N, was selected as the antigen. The coding region of SHISAL1-N was cloned by molecular cloning technique, and then it was inserted into pET-28a to generate pET28a-SHISAL1-N recombinant plasmid. The two recombinant plasmids pET28a-SHISAL1-N and pET28a-SHISAL1 were transformed into BL21 (DE3) bacteria and induced to express by IPTG. The two proteins were purified and immunized to female Kunming mice, respectively. The specificities and sensitivities of the acquired antibodies were detected by Western blot analysis, immunoprecipitation and immunofluorescent cytochemical staining. Results pET28a-SHISAL1-N recombinant plasmid was successfully constructed, and the two fused proteins, SHISAL1 and SHISAL1-N, were induced to express. Moreover, two types of SHISAL1 mouse polyclonal antibodies, derived from SHISAL1-N and SHISAL1 antigens, were obtained. Western blot results showed that the antibody prepared from SHISAL1 antigen was less specific and sensitive compared with the antibody prepared from SHISAL1-N antigen which could specifically identify different endogenous SHISAL1 protein. Immunoprecipitation results showed that SHISAL1-N antibody could specifically pull down SHIISAL1 protein in hepatocellular carcinoma cells and immunofluorescence results demonstrated that SHISAL1-N antibody could specifically bind to SHISAL1 protein in the cytoplasm. Conclusion We have optimized the SHISAL1 antigen and prepared the mouse anti-human SHISAL1 polyclonal antibodies successfully, which can be used for Western blot analysis, immunoprecipitation and immunofluorescence cytochemical staining.
Animals ; Female ; Humans ; Mice ; Antibodies ; Antibody Specificity ; Blotting, Western ; Cloning, Molecular ; Epitopes/genetics*

Objective To investigate the clinical manifestations,pathological diagnosis,treatment meth-od and prognosis of primary gastric adenosquamous carcinoma.Methods The clinical data of 20 patients with primary gastric adenosquamous carcinoma receiving the treatment in this hospital from January 1,2013 to No-vember 30,2022 were retrospectively analyzed,and their clinicopathological characteristics and prognosis were analyzed.Results Among the 20 patients,14 cases were male and 6 cases were female,with a median age of 59(36,74)years old.Upper abdominal discomfort,pain and weight loss were the main clinical symptoms.Ser-um carbohydrate antigen 19-9(CA19-9)levels were elevated in some patients.The image examination indica-ted the gastric occupation.Among 20 cases,the tumors were most common in the lower third of the stomach(14 cases),followed by the upper third(1 case)and the middle third(5 cases).The most common tumors were in the lower one-third(14 cases)of the stomach,followed by the middle one-third(5 cases)and upper one-third(1 case).In histomorphology,the gastric tumor cells contained two components,adenocarcinoma and squamous cell carcinoma,and squamous cell carcinoma accounted for more than 25％of tumor cells.Immuno-histochemistry showed that the partial tumor cells of adenocarcinoma expressed CK8/18 and partial tumor cells of squamous cell carcinoma expressed p40.All 20 cases performed the surgical treatment.Only 6 cases survived and the others died of tumor recurrence or metastasis.The adenosquamous carcinoma proportion and Ki-67 were correlated with the prognosis in the patients with gastric adenosquamous carcinoma(P＜0.05).The survival curve constructed by the Kaplan-Meier method showed that when the proportion of squamous carcinoma was more than 35％,the prognosis of the patients was good.Conclusion Primary gastric adenosquamous carcinoma,mainly composed of adenocarcinoma,may be correlated with a higher risk of metastasis.

Objective:To analyze the effect of age and number of oocytes obtained on the cumulative live birth rate per oocytes retrieval cycle in in vitro fertilization-embryo transfer (IVF-ET), and to explore the ideal number of oocytes obtained in IVF-ET. Methods:Totally 10 002 controlled ovarian stimulation cycles from March 2016 to December 2018 in the Reproductive Medicine Center of Henan Provincial People's Hospital were studied retrospectively. The general condition, clinical and laboratory indicators and clinical outcomes of the different oocytes obtained numbers were compared, and multivariate logistic regression analysis after adjusting confounding factors was used to investigate the effect of the number of oocytes obtained on the clinical outcomes, curve fitting and threshold effect analysis were performed to analyze the influence of the number of oocytes obtained on the cumulative live birth rate per oocytes retrieval cycle.Results:A total of 10 002 oocytes retrieval cycles were collected and a total of 5904 cycles of live births were obtained, with a total cumulative live birth rate of 59.03% (5904/10 002). The endometrial thickness on human chorionic gonadotropin (hCG) injection day was (10.31±3.09) mm, the median number of oocytes obtained was 8.00(5.00,12.00), the median number of mature oocytes was 7.00(4.00,11.00), and the median number of normal fertilization was 5.00(2.00,8.00), the median number of embryos available on day 3 (D3) was 4.00(2.00,7.00). The results of logistics regression analysis adjusted for confounding factors showed that the cumulative live birth rate per egg retrieval cycle in patients with 1-3 oocytes obtained ( OR=0.11, 95% CI=0.12-0.18), 4-6 oocytes obtained ( OR=0.32, 95% CI=0.33-0.44), 7-9 oocytes obtained ( OR=0.62, 95% CI=0.54-0.71) was significantly lower than that of patients with 10-15 oocytes obtained ( P<0.000 1), while it was significantly higher in patients with 16-20 oocytes ( OR=1.54, 95% CI=1.24-1.93) and ≥21 oocytes ( OR=2.49, 95% CI=1.76-3.52) than that in patients with 10-15 oocytes obtained ( P<0.000 1). The curve fitting and threshold effect analysis results showed that when the number of oocytes obtained was less than 19, the cumulative live birth rate increased significantly with the number of oocytes obtained, 16% increase in cumulative live birth rate for each additional oocytes ( OR=1.16, 95% CI=1.15-1.18, P<0.000 1). When the number of oocytes was ≥19, the cumulative live birth rate was stable and no longer increased ( OR=1.00, 95% CI=0.96-1.05, P=0.840 3). Conclusion:There is a curve relationship between the number of oocytes obtained and the cumulative live birth in IVF-ET cycle. When the number of oocytes obtained was <19, the cumulative live birth rate increased significantly with the increase of the number of oocytes obtained, but when the number of oocytes obtained was ≥19, the cumulative live birth rate did not increase significantly with it, but rather tend to be stable.

Objective:To analyze the effect of age and number of oocytes obtained on the cumulative live birth rate per oocytes retrieval cycle in in vitro fertilization-embryo transfer (IVF-ET), and to explore the ideal number of oocytes obtained in IVF-ET. Methods:Totally 10 002 controlled ovarian stimulation cycles from March 2016 to December 2018 in the Reproductive Medicine Center of Henan Provincial People's Hospital were studied retrospectively. The general condition, clinical and laboratory indicators and clinical outcomes of the different oocytes obtained numbers were compared, and multivariate logistic regression analysis after adjusting confounding factors was used to investigate the effect of the number of oocytes obtained on the clinical outcomes, curve fitting and threshold effect analysis were performed to analyze the influence of the number of oocytes obtained on the cumulative live birth rate per oocytes retrieval cycle.Results:A total of 10 002 oocytes retrieval cycles were collected and a total of 5904 cycles of live births were obtained, with a total cumulative live birth rate of 59.03% (5904/10 002). The endometrial thickness on human chorionic gonadotropin (hCG) injection day was (10.31±3.09) mm, the median number of oocytes obtained was 8.00(5.00,12.00), the median number of mature oocytes was 7.00(4.00,11.00), and the median number of normal fertilization was 5.00(2.00,8.00), the median number of embryos available on day 3 (D3) was 4.00(2.00,7.00). The results of logistics regression analysis adjusted for confounding factors showed that the cumulative live birth rate per egg retrieval cycle in patients with 1-3 oocytes obtained ( OR=0.11, 95% CI=0.12-0.18), 4-6 oocytes obtained ( OR=0.32, 95% CI=0.33-0.44), 7-9 oocytes obtained ( OR=0.62, 95% CI=0.54-0.71) was significantly lower than that of patients with 10-15 oocytes obtained ( P<0.000 1), while it was significantly higher in patients with 16-20 oocytes ( OR=1.54, 95% CI=1.24-1.93) and ≥21 oocytes ( OR=2.49, 95% CI=1.76-3.52) than that in patients with 10-15 oocytes obtained ( P<0.000 1). The curve fitting and threshold effect analysis results showed that when the number of oocytes obtained was less than 19, the cumulative live birth rate increased significantly with the number of oocytes obtained, 16% increase in cumulative live birth rate for each additional oocytes ( OR=1.16, 95% CI=1.15-1.18, P<0.000 1). When the number of oocytes was ≥19, the cumulative live birth rate was stable and no longer increased ( OR=1.00, 95% CI=0.96-1.05, P=0.840 3). Conclusion:There is a curve relationship between the number of oocytes obtained and the cumulative live birth in IVF-ET cycle. When the number of oocytes obtained was <19, the cumulative live birth rate increased significantly with the increase of the number of oocytes obtained, but when the number of oocytes obtained was ≥19, the cumulative live birth rate did not increase significantly with it, but rather tend to be stable.