Objective:To investigate the predictive value of preoperative coagulation function and inflammation response biomarkers for postoperative recurrence of non-muscle-invasive bladder cancer (NMIBC) patients.Methods:The clinical data of 390 NMIBC patients underwent surgical treatment from May 2014 to May 2021 in the Second Affiliated Hospital of Xi′an Jiaotong University were retrospectively analyzed. The baseline characteristics coagulation function, inflammation response indexes and tumor characteristics were recorded. The baseline characteristics included gender, age and smoking history; the coagulation function included prothrombin time (PT), activated partial thromboplastin time (APTT), fibrinogen (FIB) and D-dimer; the inflammation response indexes included neutrophil count, lymphocyte count, platelet count and monocyte count, and the systemic inflammatory response index (SIRI) and systemic immune-inflammation index (SII) were calculated; tumor characteristics included TNM stage, pathological grade, tumor length, tumor amount and postoperative instillation drugs. The patients were followed up until May 2022, with recurrence records and grouping. The "pROC" package was used to draw the receiver operating characteristic (ROC) curve, and calculate the optimal cutoff values of biomarkers. Multivariate Cox regression analysis was used to analyze the independent risk factors of recurrence in patients with NMIBC (variables were selected with P<0.1). The nomogram and its calibration curve were drawn by the "survival" and "rms" packages, and the area under the curve (AUC) was calculated with the "pROC" package for assessing the predictive ability of the model. The "caret" package was used for ten-fold cross-validation to evaluate the external applicability of the nomogram. Results:The ROC curve analysis result showed that the optimal cutoff values of PT, APTT, FIB, D-dimer, SIRI and SII were 11.95 s, 17.65 s, 0.233 mg/L, 565 ng/L, 0.62 and 291.5, respectively. The 390 patients with NMIBC were followed up 29 to 71 months, with a median follow-up time of 49 months. Among them, 113 patients experienced postoperative recurrence (recurrence group), and the recurrence rate was 29.0%; while 277 patients did not experience recurrence (non-recurrence group). The rate of FIB≥0.233 mg/L, D-dimmer ≥565 ng/L, SIRI≥0.62 and SII≥291.5, T 1 stage, high-grade tumor, tumor length ≥2.3 cm and multiple tumor in recurrence group were significantly higher than those in non-recurrence group: 90.3% (102/113) vs. 71.5% (198/277), 33.6% (38/113) vs. 23.5% (65/277), 74.3% (84/113) vs. 56.7% (157/277), 84.1% (95/113) vs. 60.6% (168/277), 77.9% (88/113) vs. 38.6% (107/277), 25.7% (29/113) vs. 8.3% (23/277), 49.6% (56/113) vs. 32.1% (89/277) and 41.6% (47/113) vs. 19.9% (55/277), and there were statistical differences ( P<0.01 or <0.05); there were no statistical differences in gender ratio, age, smoking history, PT, APTT and postoperative instillation drugs between the two groups ( P>0.05). Multivariate Cox regression analysis result showed that FIB≥0.233 mg/L, SII≥291.5, T 1 stage, high pathological grade, tumor length≥2.3 cm and multiple tumor were independent risk factors of postoperative recurrence in patients with NMIBC ( HR = 2.186, 1.627, 3.182, 1.675, 1.775 and 2.052; 95% CI 1.149 to 4.159, 0.913 to 2.902, 1.988 to 5.095, 1.067 to 2.630, 1.208 to 2.608 and 1.388 to 3.033; P<0.1). A nomogram model was constructed to predict postoperative 1-, 3- and 5-year non-recurrence based on FIB, SII, T stage, tumor length, pathological grade and tumor amount. The calibration curve analysis result showed that the nomogram model predicted good consistency between the postoperative 1-, 3-, 5-year non-recurrence rates and the actual incidence rate in patients with NMIBC. ROC curve analysis result showed that the AUC of the nomogram model for predicting postoperative 1-, 3- and 5-year non-recurrence in patients with NMIBC were 0.746, 0.789 and 0.835 (95% CI 0.695 to 0.832, 0.703 to 0.875 and 0.756 to 0.915). The ten-fold cross-validation result showed that the nomogram model had good external applicability for predicting postoperative 1-, 3- and 5-year non-recurrence in patients with NMIBC, with AUC of 0.754, 0.781 and 0.832 (95% CI 0.689 to 0.817, 0.724 to 0.832 and 0.778 to 0.879). Conclusions:The nomogram model based on FIB, SII, T stage, tumor length, pathological grade and tumor amount can accurately predict the postoperative 1-, 3- and 5-year recurrence risks in patients with NMIBC. The model helps clinical doctors early identify high-risk recurrent NMIBC patients, and provides reference for the development of individualized treatment plans.

Objective:To investigate the predictive value of preoperative coagulation function and inflammation response biomarkers for postoperative recurrence of non-muscle-invasive bladder cancer (NMIBC) patients.Methods:The clinical data of 390 NMIBC patients underwent surgical treatment from May 2014 to May 2021 in the Second Affiliated Hospital of Xi′an Jiaotong University were retrospectively analyzed. The baseline characteristics coagulation function, inflammation response indexes and tumor characteristics were recorded. The baseline characteristics included gender, age and smoking history; the coagulation function included prothrombin time (PT), activated partial thromboplastin time (APTT), fibrinogen (FIB) and D-dimer; the inflammation response indexes included neutrophil count, lymphocyte count, platelet count and monocyte count, and the systemic inflammatory response index (SIRI) and systemic immune-inflammation index (SII) were calculated; tumor characteristics included TNM stage, pathological grade, tumor length, tumor amount and postoperative instillation drugs. The patients were followed up until May 2022, with recurrence records and grouping. The "pROC" package was used to draw the receiver operating characteristic (ROC) curve, and calculate the optimal cutoff values of biomarkers. Multivariate Cox regression analysis was used to analyze the independent risk factors of recurrence in patients with NMIBC (variables were selected with P<0.1). The nomogram and its calibration curve were drawn by the "survival" and "rms" packages, and the area under the curve (AUC) was calculated with the "pROC" package for assessing the predictive ability of the model. The "caret" package was used for ten-fold cross-validation to evaluate the external applicability of the nomogram. Results:The ROC curve analysis result showed that the optimal cutoff values of PT, APTT, FIB, D-dimer, SIRI and SII were 11.95 s, 17.65 s, 0.233 mg/L, 565 ng/L, 0.62 and 291.5, respectively. The 390 patients with NMIBC were followed up 29 to 71 months, with a median follow-up time of 49 months. Among them, 113 patients experienced postoperative recurrence (recurrence group), and the recurrence rate was 29.0%; while 277 patients did not experience recurrence (non-recurrence group). The rate of FIB≥0.233 mg/L, D-dimmer ≥565 ng/L, SIRI≥0.62 and SII≥291.5, T 1 stage, high-grade tumor, tumor length ≥2.3 cm and multiple tumor in recurrence group were significantly higher than those in non-recurrence group: 90.3% (102/113) vs. 71.5% (198/277), 33.6% (38/113) vs. 23.5% (65/277), 74.3% (84/113) vs. 56.7% (157/277), 84.1% (95/113) vs. 60.6% (168/277), 77.9% (88/113) vs. 38.6% (107/277), 25.7% (29/113) vs. 8.3% (23/277), 49.6% (56/113) vs. 32.1% (89/277) and 41.6% (47/113) vs. 19.9% (55/277), and there were statistical differences ( P<0.01 or <0.05); there were no statistical differences in gender ratio, age, smoking history, PT, APTT and postoperative instillation drugs between the two groups ( P>0.05). Multivariate Cox regression analysis result showed that FIB≥0.233 mg/L, SII≥291.5, T 1 stage, high pathological grade, tumor length≥2.3 cm and multiple tumor were independent risk factors of postoperative recurrence in patients with NMIBC ( HR = 2.186, 1.627, 3.182, 1.675, 1.775 and 2.052; 95% CI 1.149 to 4.159, 0.913 to 2.902, 1.988 to 5.095, 1.067 to 2.630, 1.208 to 2.608 and 1.388 to 3.033; P<0.1). A nomogram model was constructed to predict postoperative 1-, 3- and 5-year non-recurrence based on FIB, SII, T stage, tumor length, pathological grade and tumor amount. The calibration curve analysis result showed that the nomogram model predicted good consistency between the postoperative 1-, 3-, 5-year non-recurrence rates and the actual incidence rate in patients with NMIBC. ROC curve analysis result showed that the AUC of the nomogram model for predicting postoperative 1-, 3- and 5-year non-recurrence in patients with NMIBC were 0.746, 0.789 and 0.835 (95% CI 0.695 to 0.832, 0.703 to 0.875 and 0.756 to 0.915). The ten-fold cross-validation result showed that the nomogram model had good external applicability for predicting postoperative 1-, 3- and 5-year non-recurrence in patients with NMIBC, with AUC of 0.754, 0.781 and 0.832 (95% CI 0.689 to 0.817, 0.724 to 0.832 and 0.778 to 0.879). Conclusions:The nomogram model based on FIB, SII, T stage, tumor length, pathological grade and tumor amount can accurately predict the postoperative 1-, 3- and 5-year recurrence risks in patients with NMIBC. The model helps clinical doctors early identify high-risk recurrent NMIBC patients, and provides reference for the development of individualized treatment plans.

[Objective] To analyze factors influencing the postoperative progression-free survival (PFS) in patients with renal cell carcinoma (RCC), construct a nomogram model for predicting PFS, and compare it with other predictive models. [Methods] A retrospective analysis was conducted on the general and clinical data of 263 RCC patients who underwent surgery at the Department of Urology, the Second Affiliated Hospital of Xi'an Jiaotong University, during Apr.2014 and Nov.2021.Patients were divided into the progression group (n=34) and non-progression group (n=229). The data of the two groups were analyzed to identify prognostic variables associated with PFS, and a nomogram model was constructed.The performance of this model was compared with that of the University of California, Los Angeles Integrated Staging System (UISS) score, tumor staging, tumor size, tumor pathological grade, and tumor necrosis scoring system (SSIGN score), and Leibovich score by plotting receiver operating characteristic (ROC) curve and calculating the area under the curve (AUC). Calibration curve of the nomogram was used to validate the model's performance, and K-fold cross-validation was employed to assess its external validity. [Results] Multivariate Cox regression analysis revealed that age (HR=2.255, 95%CI: 1.032-4.926), T stage (HR=5.766, 95%CI: 2.351-14.142), pathological grade (HR=3.100, 95%CI: 1.445-6.651), and pathological necrosis (HR=2.656, 95%CI: 1.253-5.629) were independent risk factors of PFS (P<0.05). The nomogram model based on these four independent variables had AUCs (95%CI) of 0.750 (0.630-0.870), 0.803 (0.705-0.902), and 0.847 (0.757-0.937) for 1, 3, and 5 years, respectively, which were higher than those of UISS score, SSIGN score, and Leibovich score.The calibration curve of the nomogram showed good consistency between predicted and actual probabilities.In K-fold cross-validation, the average AUCs of the nomogram at 1, 3, and 5 years were 0.761, 0.808, and 0.842, indicating good external validity of the nomogram. [Conclusion] The nomogram based on age, T stage, pathological grade and pathological necrosis can accurately predict the risk of postoperative PFS in RCC patients at 1, 3, and 5 years, which can aid clinicians in the early identification of high-risk progression.

【Objective】 To investigate the effects of preoperative lipid metabolism level on the postoperative prognosis of non-muscular invasive bladder cancer (NMIBC). 【Methods】 Clinical data of NMIBC patients who underwent surgical treatment in our hospital during Mar.2014 and May 2021 were retrospectively analyzed. Based on receiver operating characteristic (ROC) curve, the optimal cutoff values of all lipid metabolism indicators were determined and patients were classified accordingly. The independent risk factors for postoperative recurrence were identified with Cox regression model. The survival was analyzed with Kaplan-Meier, and recurrence-free survival (RFS) was compared using log-rank tests. A recurrence risk prediction model was established based on the high-density lipoprotein (HDL) and other clinic pathological factors and the accuracy of prediction was evaluated with the area under the ROC curve (AUC). 【Results】 Cox multivariate analysis showed HDL, tumor number, tumor size and histological grade were independent risk factors for recurrence (P<0.05). Kaplan-Meier analysis showed that RFS was significantly longer in the high-HDL group than in the low-HDL group (P<0.001). Incorporating HDL, tumor number, tumor size, histological grade, and tumor stage into the recurrence risk model, the AUC was 0.706, and internal cross validation showed the AUC was 0.711. 【Conclusion】 Preoperative HDL is an independent risk factor affecting the RFS of patients with NMIBC, and combining it with clinic pathological factors will improve the prediction of tumor recurrence.

【Objective】 To construct an easy-to-use individual survival prognostic tool based on competing risk analyses to predict the risk of 1-, 2- and 3- year recurrence for patients with non-muscle invasive bladder cancer (NMIBC). 【Methods】 The follow-up data of 419 NMIBC patients were obtained. The patients were randomly divided into training cohort (n=293) and validation cohort (n=126). The variables included age at diagnosis, sex, history of smoking, tumor number, tumor size, histolo-gic grade, pathological stage, and bladder perfusion drug. The cumulative incidence function (CIF) of recurrence was estimated using all variables in the training cohort and potential prognostic variables were determined with Gray’s test. The Fine-Gray subdistribution proportional hazard approach was used as a multivariate competitive risk analysis to identify independent pro-gnostic variables. A competing risk nomogram was developed to predict the recurrence. The performance of the competing risk model was evaluated with the area under the receiver operating characteristic curve (AUC), calibration curve, and Brier score. 【Results】 Five independent prognostic factors including age, number of tumors, tumor size, histologic grade and pathological stage were used to construct the competing risk model. In the validation cohort, the AUC of 1-, 2- and 3- year recurrence were 0.895 (95%CI: 0.831-0.959), 0.861(95%CI: 0.774-0.948) and 0.827(95%CI: 0.721-0.934), respectively, indicating that the model had a high predictive performance. 【Conclusion】 We successfully constructed a competing risk model to predict the risk of 1-, 2- and 3-year recurrence for NMIBC patients. It may help clinicians to improve the postoperative management of patients.

Antiviral Agents/pharmacology* ; COVID-19 ; Coronavirus 3C Proteases ; Humans ; Lactams ; Leucine ; Molecular Docking Simulation ; Molecular Dynamics Simulation ; Nitriles ; Proline ; Protease Inhibitors/pharmacology* ; SARS-CoV-2

A new coronavirus (SARS-CoV-2) has been identified as the etiologic agent for the COVID-19 outbreak. Currently, effective treatment options remain very limited for this disease; therefore, there is an urgent need to identify new anti-COVID-19 agents. In this study, we screened over 6,000 compounds that included approved drugs, drug candidates in clinical trials, and pharmacologically active compounds to identify leads that target the SARS-CoV-2 papain-like protease (PLpro). Together with main protease (M
Antiviral Agents/therapeutic use* ; Binding Sites ; COVID-19/virology* ; Coronavirus Papain-Like Proteases/metabolism* ; Crystallography, X-Ray ; Drug Evaluation, Preclinical ; Drug Repositioning ; High-Throughput Screening Assays/methods* ; Humans ; Imidazoles/therapeutic use* ; Inhibitory Concentration 50 ; Molecular Dynamics Simulation ; Mutagenesis, Site-Directed ; Naphthoquinones/therapeutic use* ; Protease Inhibitors/therapeutic use* ; Protein Structure, Tertiary ; Recombinant Proteins/isolation & purification* ; SARS-CoV-2/isolation & purification*

OBJECTIVE：To provide reference f or the qualit y sta ndard establishment of Amaranthus retroflexus. METHODS ： Taking 7 batches of A. retroflexus medicinal materials as the research object ，the appearance properties of the medicinal materials were investigated ，and the microscopic characteristics of the medicinal powders were observed. TLC method was adopted to qualitatively identify rutin ，valine and leucine in A. retroflexus medicinal materials. According to the relevant methods of the 2015 edition of Chinese Pharmacopoeia （part Ⅳ），water content ，total ash content ，acid-insoluble ash content and water-soluble extract content were determined. HPLC method was used to determine the content of rutin in the medicinal material of A. retroflexus . The determination was performed on Agilent 5 TC-C18（2）column with mobile phase consisted of methanol- 0.3％ phosphoric acid solution（40∶60，V/V），at the flow rate of 1.0 mL/min. The detection wavelength was set at 358 nm，and the column temperature was 30 ℃. The sample size was 10 μL. RESULTS：The appearance and microstructure characteristics of the medicinal materials were consistent with the existing description. The identification results of TLC meth od showed that 7 batches of medicinal materials and each reference substance （rutin，valine，leucine）showed spots of the same color at the same position. The moisture content of 7 batches of A. retroflexus medicinal materials was 7.43％-8.72％，the total ash content was 11.82％-13.78％，the acid-insoluble ash content was 0.15％-0.55％，and the water-soluble extract content was 17.27％-24.74％. The linear range of rutin was 10-200 μg/mL（R 2＝1.000 0）. RSDs of precision test ，stability test （24 h）and repeatability test were all less than 2.0％ （n＝6）. The average recovery rates of rutin were 99.14％，97.98％ and 98.80％ in low ，medium and high concentration of samples，and RSDs were 0.97％，0.95％，0.96％（n＝3）. The contents of rutin in 7 batches of A. retrophylla were 0.314-1.102 mg/g. CONCLUSIONS：In this study ，character observation ，microscopic identification ，moisture content ，total ash content ，acid- insoluble ash content and water-soluble extract content of A. retroflexus are investigated ；TLC method was established for qualitative identification of leucine ，valine and rutin in A. retroflexus ，and the HPLC method was established for content determination of rutin. It provides reference for the quality standard establishment of A. retroflexus .