Objective To explore the prognostic predictors of patients with chromophobe renal cell carcinoma(ChRCC),and to construct a nomogram model and prognostic risk staging.Methods The data of this study were derived from the Surveillance,Epidemiology,and End Results(SEER)database.Cox regression analysis was used to determine the independent prognostic factors,and a nomogram model was constructed to predict the survival period of patients with ChRCC.The discrimination and accuracy of the model were evaluated using the consistency index and calibration curve.Prognostic risk staging was established and compared with the TNM staging system.Results A total of 6382 patients with ChRCC were included.They were randomly divided into training group(n=4467)and validation group(n=1915)in a 7:3 ratio.The results of the Cox regression analysis showed that age,gender,race,place of residence,lymph node metastasis,bone metastasis,lung metastasis,tumor breaking through the renal capsule,major vein invasion,pathological appearance of sarcomatous features,and surgical method were all independent influencing factors for the prognosis of ChRCC(P＜0.05).The C-index of this nomogram prognostic model was significantly higher than that of the TNM staging system(0.790 vs.0.617).The same trend was also observed in the validation group.The K-M survival curve based on the prognostic risk staging by the nomogram showed that there was a significant difference among the populations in each stage(P＜0.001),and the discrimination was superior to the TNM staging of renal cancer.Conclusion The prognostic nomogram model for ChRCC patients constructed based on comprehensive pathological factors can achieve high accuracy and stability.The prognostic risk staging established by this model can serve as a practical supplementary tool for evaluating the prognosis of ChRCC patients in clinical practice.

Objective To examine the level of sperm flagellar tubulin glycosylation(Gly-Tubulin)in asthenospermia patients(AP)and discuss its significance.Methods According to the principle of inclusion and exclusion criteria,108 patients treated in the Department of Andrology in Xinjiang Uygur Autonomous Region Maternal and Child Health Hospital from June 2021 to May 2022 were rolled in this study.According to the results of semen examine,they were divided into group AP(n=74),and normal control(NC)group(n=34).Colleced the clinical date of both group,such as the age,the sterility period.The levels of sex hormones were detected by chemiluminescence method.The glycosylated Tubulin levels of the sperm were detected by Western blot and immunofluorescence was used for localization analysis,and the relationship between the Gly-Tubulin of sperm flagellar and asthenospermia was analyzed by Multivariate Logistic regression analysis.Results Compared to NC group,the sterility period of group AP was prolong(3.98±0.30 vs 0.78±0.08),the percent of forward sperm motility was decreased(18.55±0.97 vs 46.24±1.89)and the expression level of Gly-Tubulin in the sperm flagellar was decreased(0.64±0.11 vs 1.00±0.00),the differences with statistical significance(t=62.038,χ2=14.394,3.148,all P＜0.05).There were no significant differences in follicle-stimulating hormone(FSH),luteinizing hormone(LH),prolactin(PRL),estradiol(E2),testosterone,semen volume,sperm concentration and total sperm between the two groups(t/χ2=0.043～1.503,all P>0.05).Multivariate Logistic regression analysis showed that the percent of forward sperm motility and the sperm flagellar Gly-Tubulin expression level were independent risk factors for male asthenospermia(Wald χ2=4.406,7.492,P<0.05).Conclusion Abnormal level of Gly Tubulin in sperm flagella may be closely related to the occurrence and development of asthenospermia.

Objective To examine the level of sperm flagellar tubulin glycosylation(Gly-Tubulin)in asthenospermia patients(AP)and discuss its significance.Methods According to the principle of inclusion and exclusion criteria,108 patients treated in the Department of Andrology in Xinjiang Uygur Autonomous Region Maternal and Child Health Hospital from June 2021 to May 2022 were rolled in this study.According to the results of semen examine,they were divided into group AP(n=74),and normal control(NC)group(n=34).Colleced the clinical date of both group,such as the age,the sterility period.The levels of sex hormones were detected by chemiluminescence method.The glycosylated Tubulin levels of the sperm were detected by Western blot and immunofluorescence was used for localization analysis,and the relationship between the Gly-Tubulin of sperm flagellar and asthenospermia was analyzed by Multivariate Logistic regression analysis.Results Compared to NC group,the sterility period of group AP was prolong(3.98±0.30 vs 0.78±0.08),the percent of forward sperm motility was decreased(18.55±0.97 vs 46.24±1.89)and the expression level of Gly-Tubulin in the sperm flagellar was decreased(0.64±0.11 vs 1.00±0.00),the differences with statistical significance(t=62.038,χ2=14.394,3.148,all P＜0.05).There were no significant differences in follicle-stimulating hormone(FSH),luteinizing hormone(LH),prolactin(PRL),estradiol(E2),testosterone,semen volume,sperm concentration and total sperm between the two groups(t/χ2=0.043～1.503,all P>0.05).Multivariate Logistic regression analysis showed that the percent of forward sperm motility and the sperm flagellar Gly-Tubulin expression level were independent risk factors for male asthenospermia(Wald χ2=4.406,7.492,P<0.05).Conclusion Abnormal level of Gly Tubulin in sperm flagella may be closely related to the occurrence and development of asthenospermia.

Objective To explore the prognostic predictors of patients with chromophobe renal cell carcinoma(ChRCC),and to construct a nomogram model and prognostic risk staging.Methods The data of this study were derived from the Surveillance,Epidemiology,and End Results(SEER)database.Cox regression analysis was used to determine the independent prognostic factors,and a nomogram model was constructed to predict the survival period of patients with ChRCC.The discrimination and accuracy of the model were evaluated using the consistency index and calibration curve.Prognostic risk staging was established and compared with the TNM staging system.Results A total of 6382 patients with ChRCC were included.They were randomly divided into training group(n=4467)and validation group(n=1915)in a 7:3 ratio.The results of the Cox regression analysis showed that age,gender,race,place of residence,lymph node metastasis,bone metastasis,lung metastasis,tumor breaking through the renal capsule,major vein invasion,pathological appearance of sarcomatous features,and surgical method were all independent influencing factors for the prognosis of ChRCC(P＜0.05).The C-index of this nomogram prognostic model was significantly higher than that of the TNM staging system(0.790 vs.0.617).The same trend was also observed in the validation group.The K-M survival curve based on the prognostic risk staging by the nomogram showed that there was a significant difference among the populations in each stage(P＜0.001),and the discrimination was superior to the TNM staging of renal cancer.Conclusion The prognostic nomogram model for ChRCC patients constructed based on comprehensive pathological factors can achieve high accuracy and stability.The prognostic risk staging established by this model can serve as a practical supplementary tool for evaluating the prognosis of ChRCC patients in clinical practice.

Objective:To investigate the mortality-related factors affecting patients with gastrointestinal perforation who are transferred to the intensive care unit (ICU) and to establish a prediction model, and to evaluate the predictive performance of the model.Methods:A retrospective analysis was performed on the medical records of 306 patients who underwent gastrointestinal perforation surgery in Shanxi Bethune Hospital (Shanxi Academy of Medical Sciences) from January 2021 to January 2024 and were transferred to intensive care unit after surgery, including 176 males and 130 females, aged from 28 to 92 years with the average of (66.07±16.03) years. According to the prognosis, patients were divided into survival group ( n=264) and death group ( n=42). Clinical characteristics of the two groups were compared, univariate and multivariate Logistic regression was used to analyze the risk factors of perioperative death, and the related risk factors were selected to establish a nomogram prediction model, the subject work curve was drawn, and the area under the curve (AUC) was calculated. Evaluate its predictive effectiveness; The calibration chart and clinical decision curve were further used to evaluate the prediction accuracy and clinical application value of the model. Results:Clinical data analysis showed that age, white blood cell count, procalcitonin, lactic acid level, preoperative shock, preoperative underlying diseases (cerebral infarction, hormone history), intraoperative blood loss, postoperative lung infection in the death group were higher than those in the survival group ( P<0.05), and hemoglobin was lower than those in the survival group ( P<0.05). Multivariate Logistic regression analysis showed age ( OR=1.422, 95% CI: 1.205-1.680, P<0.001), hemoglobin ( OR=0.945, 95% CI: 0.904-0.987, P=0.012), white blood cell count ( OR=1.832, 95% CI: 1.341-2.501, P<0.001), procalcitonin ( OR=1.099, 95% CI: 1.012-1.192, P=0.024), lactic acid level ( OR=16.435, 95% CI: 3.729-72.425, P<0.001), reoperative shock ( OR=172.358, 95% CI: 13.059-2274.773, P<0.001), intraoperative blood loss ( OR=1.041, 95% CI: 1.017-1.065, P=0.001) and postoperative pulmonary infection ( OR=38.670, 95% CI: 3.449-433.553, P=0.003) was an independent risk factor for perioperative death in intensive care patients after DTP. Based on the screened independent risk factors ( P<0.05), a nomogram model was established and receiver operating characteristic (ROC) curve was drawn. The model area under the curve was 0.985. The accurate graph shows that the predicted results of the model are in good agreement with the actual clinical results, and the analysis of clinical decision curve indicates that the model has high clinical prediction value. Conclusion:Age>71.5 years, hemoglobin< 109 g/L, white blood cell count>17.9×10 9/L, procalcitonin>6.225 ng/mL, lactate level>2.25 mmol/L, preoperative shock, intraoperative blood loss>45 mL and postoperative pulmonary infection are independent risk factors for perioperative death in intensive care patients after DTP.

Objective:To evaluate the prognostic value of thromboelastography maximum amplitude(MA)and arterial blood lactate levels for sepsis in elderly patients.Methods:A retrospective analysis was performed on clinical data of 63 sepsis patients(≥60 years old)admitted to the Intensive Care Unit(ICU)of Bethune Hospital of Shanxi Province from December 2018 to February 2020.MA values, white blood cell counts, lymphocyte counts, platelets, acute physiology and chronic health evaluation Ⅱ(APACHE Ⅱ)scores, sequential organ failure assessment(SOFA)scores, underlying diseases, body mass index, laboratory test results and other related treatments were analyzed.The subjects were divided into the survival group and the death group according to the 28-day survival outcome.Differences in MA, APACHE Ⅱ scores, SOFA scores and laboratory test results between the two groups were analyzed, and the correlations of MA with infection parameters and age were examined.Influencing factors of survival outcomes were analyzed using multivariate Logistic regression.The receiver operating characteristic curve(ROC)was used to calculate the prognostic value of MA and arterial lactate for sepsis in elderly patients.Results:The main sources of infections were pulmonary and abdominal(79.4%, 50/63)in 63 elderly patients with sepsis.The incidences of positive blood cultures and deaths were 15.9%(10/63)and 66.7%(42/63), respectively.There existed significant differences in lymphocyte counts, arterial lactate levels, MA and lengths of stay in the ICU between the survival group and the death group( t=3.847, 2.153, 2.745, -3.574, respectively, all P<0.05).MA was correlated with arterial lactate, SOFA score and survival outcome( r=-0.498, -0.506, and -0.358, respectively, all P<0.05).Multivariate Logistic regression analysis showed that MA and arterial lactate were independent factors for the survival outcome( OR=1.626, 0.766, all P<0.05).The area under the ROC curve(AUC, 95% CI)for the combination of MA and arterial lactate was larger than that of either MA or arterial lactate alone(0.89, range: 0.763-0.846; 0.58, range: 0.574-0.730; 0.77, range: 0.521-0.832; all P<0.05). Conclusions:The combination of thromboelastography maximum amplitude and lactate in arterial blood has important clinical value in assessing the prognosis of elderly patients with sepsis.

Objective:To analyze the changes of serum lipidomics in patients with sepsis and healthy controls, search for the differences of lipid metabolites, and reveal the changes of lipidomics in the process of sepsis.Methods:A prospective observational study was conducted. From September 2019 to April 2020, morning blood samples of upper extremity superficial veins were collected from 30 patients with definite sepsis diagnosed in intensive care unit (ICU) of Shanxi Bethune Hospital and 30 age-matched healthy subjects during the same period. Serum lipid metabolites were analyzed by ultra-high performance liquid chromatography-mass spectrometry/mass spectrometry (UPLC-MS/MS), and the quality control samples were analyzed by base peak spectroscopy (BPC) and verified experimental repetition. Student t-test and fold change (FC) were used for screening significant differences in lipid metabolites and determining their expression changes. Principal component analysis (PCA) and orthogonal projectionto latent structure discriminant analysis (OPLS-DA) were used to determine the entire allocation of experimental groups apiece, access the quality of being near to the true value of model, and screen the differential lipid metabolites with variable importance of projection (VIP). Finally, Metabo Analyst platform database was used to analyze lipid molecular metabolic pathways. Results:BPC results showed that the experimental repeatability was good and the experimental data was reliable. The main parameter model interpretation rate of PCA model R 2X = 0.511, indicating that the model was reliable. The main parameter model interpretation rate of OPLS-DA model R 2Y = 0.954, Q 2 = 0.913, indicating that the model was stable and reliable. With FC > 2.0 or FC < 0.5, P < 0.05, a total of 72 differential lipid metabolites were obtained based on VIP > 1. Based on Metabo Analyst 5.0, 24 distinguishable lipid metabolites were identified including 8 phosphatidylethanolamine (PE), 7 lysophosphatidylcholine (LPC), 6 phosphatidylcholine (PC), 2 lysophosphatidylethanolamine (LPE) and 1 phosphatidylserine (PS). Compared with healthy volunteers, the lipid molecules expression proved down-regulated in most sepsis patients, including PC, LPC, LPE, and some PE, while some PE and PS were up-regulated, which was mainly related to the PE (18∶0p/20∶4), PC (16∶0/16∶0) and LPC (18∶1) metabolic pathways in glycerophospholipids. Conclusions:There are significant differences in lipid metabolites between the sera of sepsis patients and healthy volunteers. PE (18∶0p/20∶4), PC (16∶0/16∶0) and LPC (18∶1) may be new targets for sepsis prediction and intervention.

Objective:To screen lipid biomarker in sepsis patients with different survival outcome based on ultra high performance liquid chromatography-mass spectrometry(UHPLC-MS/MS) technique.Methods:From September 2019 to April 2020, 30 septic patients admitted in Department of Intensive Care Unit and 30 cases of physical examination at the same time in Shanxi Bethune Hospital were studied. Lipid metabolite in serum were detected by UHPLC-MS/MS technique. According to the 28 day survival outcome of sepsis patients, they were divided into survival group (21 cases) and death group (9 cases). The baseline data of case group and control group, survival group and death group were compared respectively. Independent sample t-test and orthogonal partial least squares discriminant analysis (OPLS-DA) were further performed to identify lipid biomarkers related to sepsis survival outcome. Receiver operating characteristic (ROC) curve to evaluate the predictive efficacy of differential lipids on the survival outcome of biomarker sepsis patients. Results:There were 32 lipid subclasses and 1 437 differential lipid molecules in the sepsis group compared with the control group. 196 differential lipid molecules in the sepsis survival group and the death group were screened according to the OPLS-DA model (variable weight of projection (VIP)>1), which were glycerophosphingolipids (129), sphingolipids (52), glycerides (14), and sterols (1).All the original data were statistically analyzed by univariate independent sample t-test. There were statistically significant differences in 15 lipid molecules between the two groups. Combined with VIP > 1 and P < 0.01, three lipid molecules were finally screened, which were sphingomyelin (SM) lipid molecules, SM (d30∶1), SM (d32∶2), SM (d32∶1). ROC curve analysis showed that the areas under curves of the above three lipid molecular were 0.915, 0.892, 0.898, respectively. The sensitivity was 77.27%, 95.45%,72.73%. The specificity was 100.0%, 87.5%,100.0%. Further Z-test showed that there was no significant difference in the area under the ROC curve ( Z(SM (d30∶1) and SM (d32∶1)) =0.36, P=0.722; Z(SM (d30∶1) and SM (d32∶2))=0.34, P=0.732; Z(SM (d32∶1) and SM (d32∶1))=0.07, P=0.942). Conclusions:Sphingomyelin may be involved in the formation of different clinical outcomes of sepsis, and has a good predictive effect on the survival outcome of sepsis.

Objective: To study the effect of low-to-moderate dose glucocorticoid therapy on viral clearance time in patients with COVID-19. Methods: A total of 72 patients diagnosed with COVID-19 from January 19 to February 17, 2020 at the First Affiliated Hospital, School of Medicine, Zhejiang University were recruited. All patients received oral abidol and/or combined lopinavir/ritonavir, darunavir antiviral, and symptomatic supportive care. Among them, 51 patients received methylprednisolone (0.75-1.50 mg·kg^-1·d^-1) (glucocorticoid treatment group), and 21 patients who did not use glucocorticoid were the control group. The time of stable virologic conversion insputumand the time of radiologic recovery in lungsince onset were compared between the two groups and among the normal patients.The Kruskal-Wallis test or Fisher exact test was used to compare the difference between groups. Results: The median ages of the glucocorticoid group and the control group were 52 [interquartile range (IQR):45, 62] years and 46 (IQR: 32, 56)years, and the differences were significant (P<0.05). The clinical conditions at hospital admission were different between the two groups (P<0.01). There were 52.0% critical ill patients in the glucocorticoid treatment group, compared to that of 71.4% normal patients in the control group. The median times from the onset tostable virologic conversion to negative in the two groups were 15 (IQR:13,20) days and 14 (IQR:12,20) days (P>0.05), and the difference was no statistically significant. The median times from onset to radiologic recovery were 13 (IQR: 11,15) days and 13 (IQR:12,17) days in the two groups, and there was no difference (P>0.05). In ordinary patients, the median timesfrom the onset tostable virologic conversion insputum were no difference (P>0.05), with 13 (IQR:11,18) days in the glucocorticoid group and 13 (IQR:12,15) days in the control group; The median times from onset to radiologic recovery in lungwere also no difference (P>0.05), with 12 (IQR: 10,15)days in the glucocorticoid group and 13 (IQR: 12,17) days inthe control group. Conclusions Low-to-moderate glucocorticoid treatment has no effect on the time of virus clearance in patients with different clinical types of COVID-19. The glucocorticoid is not recommended since no effectiveness on accelerating the improvement of radiologic recovery in lung has been observed.

Objective:To study the effect of low-to-moderate dose glucocorticoid therapy on viral clearance in patients with COVID-19.Methods:A total of 72 patients diagnosed with COVID-19 from January 19 to February 17, 2020 at the First Affiliated Hospital, Zhejiang University School of Medicine were recruited. All patients received oral arbidol and combination of lopinavir/ritonavir or darunavir/cobistitat for antiviral therapy, and symptomatic supportive care. Among them, 51 patients received methylprednisolone (0.75-1.50 mg·kg -1·d -1) (glucocorticoid treatment group), and 21 patients did not use glucocorticoid (control group). The time of virologic negative conversion in sputum and the time of radiologic recovery in lung since onset were compared between the two groups. The Kruskal-Wallis test or Fisher exact test was used to compare the difference between groups. Results:The median ages of the glucocorticoid group and the control group were 52 (45, 62) and 46 (32, 56) years ( χ2=4.365, P<0.05). The clinical conditions at hospital admission were different between the two groups ( P<0.01). The severe cases accounted for 52.0%, while moderate cases in the control group accounted for 71.4%. The median times from the onset to virologic negative conversion in the two groups were 15 (13, 20) and 14 (12, 20) days ( P>0.05). The median times from onset to radiologic recovery were 13 (11, 15) and 13 (12, 17) days in the two groups ( P>0.05). In moderate cases, the median times from the onset to virologic conversion in sputum were 13 (11, 18) days in the glucocorticoid group and 13 (12, 15) days in the control group ( P>0.05). The median times from onset to radiologic recovery in lung were 12 (10, 15) and 13 (12, 17) days, respectively ( P>0.05). Conclusions:Low-to-moderate glucocorticoid treatment has no effect on the time of virus clearance in patients with different clinical types of COVID-19, and also no effect on accelerating radiologic recovery in lung, so it is not recommended.