Objective:To develop a quality control model for anal sphincter ultrasound images and validate its diagnostic performance across multiple centers.Methods:A retrospective analysis was conducted on anal sphincter ultrasound images from seven medical centers in China between May 2019 and June 2022. A total of 7 040 images from 3 116 patients were included and divided into a training set（4 912 images）and a validation set（2 128 images）. The images were classified as standard or non-standard images by three experts. Three models were developed based on different image feature extraction methods：a single-branch model，a multi-branch weighted model，and a multi-branch ensemble model. The diagnostic performance of each model was evaluated using the area under the ROC curve（AUC），sensitivity，specificity，accuracy，positive predictive value，and negative predictive value，respectively. The optimal model was selected and compared with the performance of 4 doctors with varying experience levels. Sixty days later，the images with the assistance of the model's output were reassessed by the doctors to evaluate its impact on manual quality control.Results:① Among the 3 models，the multi-branch ensemble model demonstrated the highest AUC and sensitivity，with an AUC of 0.966（95% CI=0.958 - 0.974），a sensitivity of 91.83%，and a specificity of 91.41%. This model was named M quality. ② M quality's AUC was slightly lower than that of Senior A and B（0.966 vs. 0.976，0.976，and P<0.05），its sensitivity was slightly lower than that of Senior A（91.83% vs. 95.61%， P<0.001）but comparable to Senior B（91.83% vs. 92.89%， P=0.315），its specificity was slightly lower than Senior A and B（91.41% vs. 94.44%，98.18%，and P<0.05）. However，M quality significantly outperformed Junior A and B in AUC and sensitivity（AUC：0.966 vs. 0.850，0.818；sensitivity：91.83% vs. 84.90%，61.46%；all P<0.001），its specificity was higher than that of Junior A（91.41% vs. 80.28%， P<0.001）but lower than that of Junior B（91.41% vs. 95.96%， P<0.001）. ③ With model assistance，Senior B's sensitivity（92.89% vs. 94.20%， P=0.001）and Senior A's specificity（94.44% vs. 96.56%， P<0.001）improved significantly. Junior A and B showed significant improvements in AUC and sensitivity（AUC：0.931 vs. 0.850，0.914 vs. 0.818；sensitivity：91.83% vs. 84.90%，89.53% vs. 61.46%；all P<0.001）. After model assistance，Junior A's specificity increased（93.62% vs. 80.28%， P<0.001），while Junior B's specificity decreased（91.60% vs. 95.96%， P=0.013）. Conclusions:This study develops a quality control model for anal sphincter ultrasound images with robust diagnostic performance，approaching the level of seniors. The model significantly enhances the image quality assessment capabilities of juniors，demonstrating promising clinical application potential.

Objective:Acute kidney injury(AKI) is a common complication after cardiac surgery, and associated with increased risk of development of chronic kidney disease and mortality in the long term. Neutrophil percentage-to-albumin ratio(NPAR) is a new inflammatory marker that has been used to predict the poor prognosis of patients with cardiovascular disease or shock. However, the relationship between NPAR and AKI in patients with cardiac surgery has not been established. The aim was to evaluate the relationship between NPAR and AKI after cardiac surgery.Methods:Data of all adult patients underwent cardiac surgery with cardiopulmonary bypass from January 1, 2006 to December 31, 2018 were extracted from electronic medical record system of the Guangdong Provincial People's Hospital and retrospectively analyzed. The outcome of interest was AKI diagnosed by using the criteria of Kidney Disease Improving Global Outcomes. Logistic regression was used to assess the relationship between NPAR and postoperative AKI while adjust for potential confounders. In addition, restricted cubic spline(RCS) was utilized to provide a flexible description of the association of the preoperative NPAR and AKI. Results:Totally, 24 178 patients were analyzed. The incidence of AKI was 30.1%. Compared with patients without AKI, those with AKI were older and had higher rates of males, left ventricular ejection fraction(LVEF) less than or equal to 0.60, estimated glomerular filtration rate less than 90 ml·min -1·1.73 m -2, hypertension, diabetes, emergency surgery, preoperative critical illness, and reoperation. The baseline serum creatinine, serum uric acid, cardiopulmonary bypass time and postoperative mechanical ventilation time were higher or longer in AKI patients than those in none AKI patients. Then, patients were divided into four groups based on NPAR quartiles. After adjusting for confounding factors using logisitc regression, compared with patients with NPAR in group 3(1.551.97), respectively. The RCS showed a U-shaped nonlinear relationship( P for nonlinear less than 0.001) between NPAR and AKI after adjusting for potential confounding factors. RCS indicated the NPAR of 1.77 was the lowest risk for AKI. When NPAR less than 1.77, per 1-standard deviation(SD) increase in NPAR, the risk of AKI decreased by 23.2%( OR=0.768, 95% CI: 0.687, 0.859). Conversely, when NPAR above 1.77, per one SD increase in NPAR, the risk of AKI increased by 25.9%( OR=1.259, 95% CI: 1.166, 1.36). Conclusion:A U-shaped relationship between NPAR and AKI after cardiac surgery was shown. The appropriate value for NPAR might be 1.77. The risk of AKI might be increased, when less or above this value. NPAR might be used as an effective and economical tool to identify AKI risk among individuals with cardiac surgery, as well as to formulate individualized prevention and intervention strategy.

OBJECTIVES: To explore the value of serum cystatin C (CysC) levels in evaluating renal prognosis in IgA nephropathy (IgAN) patients. METHODS: We retrospectively collected the clinical data of IgAN patients diagnosed by renal biopsy at Guangdong Provincial People's Hospital from January, 2014 to December, 2018. Based on baseline serum CysC levels, the patients were divided into high serum CysC (>1.03 mg/L) group and normal serum CysC (≤1.03 mg/L) group. The composite endpoint for poor renal prognosis was defined as ≥50% decline in estimated glomerular filtration rate (eGFR) and/or progression to end-stage renal disease (ESRD). Lasso regression, multivariate Cox regression and Kaplan-Meier survival analysis were used to identify the risk factors and compare renal survival rates between the two groups. Smooth curves fitting and threshold effect analysis were used to explore the relationship between serum CysC levels and the outcomes. A nomogram model was constructed and its predictive performance was evaluated using concordance index, calibration curve, receiver operating characteristic (ROC) curve and the area under curve (AUC). RESULTS: A total of 356 IgAN patients were enrolled, who were followed up for 4.65±0.93 years. The composite endpoint occurred in 74 patients. High serum CysC was identified as an independent risk factor for poor renal prognosis in IgAN (HR=2.142, 95% CI 1.222 to 3.755), and the patients with high serum CysC levels had a lower renal survival rate (Log-rank χ²=47.970, P<0.001). In patients with serum CysC below 2.12 mg/L, a higher CysC level was associated with an increased risk of poor renal prognosis (β=3.487, 95% CI: 2.561-4.413, P<0.001), while above this level, the increase of the risk was not significant (β=0.676, 95% CI: -0.642-1.995, P=0.315). The nomogram model based on serum CysC and 3 other independent risk factors demonstrated good internal validity with a concordance index of 0.873 (95% CI: 0.839-0.907) and an AUC of 0.909 (95% CI: 0.873-0.945). CONCLUSIONS Serum CysC levels are associated with renal prognosis in IgAN patients, and high serum CysC an independent risk factor for poor renal prognosis.
Humans ; Glomerulonephritis, IGA/diagnosis* ; Cystatin C/blood* ; Prognosis ; Risk Factors ; Retrospective Studies ; Glomerular Filtration Rate ; Kidney Failure, Chronic ; Male ; Female ; Adult ; Nomograms ; Middle Aged

Objective To investigate the underlying mechanism of abnormal specification of spermatogonial stem cells(SSCs)in male mice following Rb1 conditional knockout in mitotic-arrested prospermatogonia.Methods ① R language was used to analyze the single-cell RNA sequencing(scRNA-seq)data of prospermatogonia derived from postnatal day 0.5(P0.5)male mice through the gene expression omnibus(GEO)public database(accession number:GSE124904).② Mitoti-arrested prospermatogonia Rb1 conditional knockout(cKO)mice as well as Rb1 cKO mice with Id4-gfp transgene were generated using Vasa-Cre mice crossed with Rb1flox/flox or Id4-gfpTg;Rb1flox/flox mice.PCR was employed to detect the deletion of Rb1 in order to distinguish the control and cKO male mice.The testes of male mice(n=3～8)within a few days after birth were collected.After that,flow cytometry was applied to divide the ID4-GFP cells into 3 communities based on the GFP fluorescence intensity,and then detect the number of cells and cell cycle in each community.③ Germ cell proliferation(Ki67 positive,Ki67+),SSCs specification(FOXO1 nuclear transition),and germ cell differentiation(STRA8+)were detected with immunofluorescence staining.④ TUNEL staining was utilized to detect cell apoptosis.Results ① The results of scRNA-seq showed that in the two set clusters of prospermatogonia,the prospermatogonia that further specifies to generate SSCs had enriched genes that are associated with cell proliferation.② Germ cell proliferation assay indicated that the average ratio of Ki67+germ cells in the testicular cross-section of the cKO mice was significantly higher than that of the control mice at P2.5[(46.10±6.21)%vs(11.22±3.27)%,P<0.01].③ Flow cytometry revealed that,among the brightest community of ID4-GFP cells,the percentage of the cells at S phase was obviously higher in the testicular cells derived from the cKO mice when compared to the control mice at P2.5[(12.05±1.22)%vs(5.05±1.46)%,P<0.05].④ TUNEL staining displayed that cell apoptosis was detected in the testicular cross-section of cKO mice rather than that of the control mice.⑤ The results of SSCs specification exploration showed that statistical difference was observed in the percentage of cytoplasmic FOXO1 in the testicular cross-section between the control and cKO mice[(20.57±2.15)%vs(45.08±2.45)%,P<0.01].Conclusion Rb1 knockout in mitotic-arrested prospermatogonia disrupts their postnatal cell cycle re-enter and induces cell apoptosis,which further results in abnormal SSC specification.

Objective:Acute kidney injury(AKI) is a common complication after cardiac surgery, and associated with increased risk of development of chronic kidney disease and mortality in the long term. Neutrophil percentage-to-albumin ratio(NPAR) is a new inflammatory marker that has been used to predict the poor prognosis of patients with cardiovascular disease or shock. However, the relationship between NPAR and AKI in patients with cardiac surgery has not been established. The aim was to evaluate the relationship between NPAR and AKI after cardiac surgery.Methods:Data of all adult patients underwent cardiac surgery with cardiopulmonary bypass from January 1, 2006 to December 31, 2018 were extracted from electronic medical record system of the Guangdong Provincial People's Hospital and retrospectively analyzed. The outcome of interest was AKI diagnosed by using the criteria of Kidney Disease Improving Global Outcomes. Logistic regression was used to assess the relationship between NPAR and postoperative AKI while adjust for potential confounders. In addition, restricted cubic spline(RCS) was utilized to provide a flexible description of the association of the preoperative NPAR and AKI. Results:Totally, 24 178 patients were analyzed. The incidence of AKI was 30.1%. Compared with patients without AKI, those with AKI were older and had higher rates of males, left ventricular ejection fraction(LVEF) less than or equal to 0.60, estimated glomerular filtration rate less than 90 ml·min -1·1.73 m -2, hypertension, diabetes, emergency surgery, preoperative critical illness, and reoperation. The baseline serum creatinine, serum uric acid, cardiopulmonary bypass time and postoperative mechanical ventilation time were higher or longer in AKI patients than those in none AKI patients. Then, patients were divided into four groups based on NPAR quartiles. After adjusting for confounding factors using logisitc regression, compared with patients with NPAR in group 3(1.551.97), respectively. The RCS showed a U-shaped nonlinear relationship( P for nonlinear less than 0.001) between NPAR and AKI after adjusting for potential confounding factors. RCS indicated the NPAR of 1.77 was the lowest risk for AKI. When NPAR less than 1.77, per 1-standard deviation(SD) increase in NPAR, the risk of AKI decreased by 23.2%( OR=0.768, 95% CI: 0.687, 0.859). Conversely, when NPAR above 1.77, per one SD increase in NPAR, the risk of AKI increased by 25.9%( OR=1.259, 95% CI: 1.166, 1.36). Conclusion:A U-shaped relationship between NPAR and AKI after cardiac surgery was shown. The appropriate value for NPAR might be 1.77. The risk of AKI might be increased, when less or above this value. NPAR might be used as an effective and economical tool to identify AKI risk among individuals with cardiac surgery, as well as to formulate individualized prevention and intervention strategy.

Objective:To develop a quality control model for anal sphincter ultrasound images and validate its diagnostic performance across multiple centers.Methods:A retrospective analysis was conducted on anal sphincter ultrasound images from seven medical centers in China between May 2019 and June 2022. A total of 7 040 images from 3 116 patients were included and divided into a training set（4 912 images）and a validation set（2 128 images）. The images were classified as standard or non-standard images by three experts. Three models were developed based on different image feature extraction methods：a single-branch model，a multi-branch weighted model，and a multi-branch ensemble model. The diagnostic performance of each model was evaluated using the area under the ROC curve（AUC），sensitivity，specificity，accuracy，positive predictive value，and negative predictive value，respectively. The optimal model was selected and compared with the performance of 4 doctors with varying experience levels. Sixty days later，the images with the assistance of the model's output were reassessed by the doctors to evaluate its impact on manual quality control.Results:① Among the 3 models，the multi-branch ensemble model demonstrated the highest AUC and sensitivity，with an AUC of 0.966（95% CI=0.958 - 0.974），a sensitivity of 91.83%，and a specificity of 91.41%. This model was named M quality. ② M quality's AUC was slightly lower than that of Senior A and B（0.966 vs. 0.976，0.976，and P<0.05），its sensitivity was slightly lower than that of Senior A（91.83% vs. 95.61%， P<0.001）but comparable to Senior B（91.83% vs. 92.89%， P=0.315），its specificity was slightly lower than Senior A and B（91.41% vs. 94.44%，98.18%，and P<0.05）. However，M quality significantly outperformed Junior A and B in AUC and sensitivity（AUC：0.966 vs. 0.850，0.818；sensitivity：91.83% vs. 84.90%，61.46%；all P<0.001），its specificity was higher than that of Junior A（91.41% vs. 80.28%， P<0.001）but lower than that of Junior B（91.41% vs. 95.96%， P<0.001）. ③ With model assistance，Senior B's sensitivity（92.89% vs. 94.20%， P=0.001）and Senior A's specificity（94.44% vs. 96.56%， P<0.001）improved significantly. Junior A and B showed significant improvements in AUC and sensitivity（AUC：0.931 vs. 0.850，0.914 vs. 0.818；sensitivity：91.83% vs. 84.90%，89.53% vs. 61.46%；all P<0.001）. After model assistance，Junior A's specificity increased（93.62% vs. 80.28%， P<0.001），while Junior B's specificity decreased（91.60% vs. 95.96%， P=0.013）. Conclusions:This study develops a quality control model for anal sphincter ultrasound images with robust diagnostic performance，approaching the level of seniors. The model significantly enhances the image quality assessment capabilities of juniors，demonstrating promising clinical application potential.

Objective:To study the risk factors of venous thromboembolism(VTE)and the predictive value of the improved VTE score model to identify the risk of VTE in gynecological surgery patients.Methods:From Janu-ary 1,2020 to December 31,2022,41 patients with VTE after gynecological surgery were selected as the VTE group,and a total of 164 patients with adjacent gynecological surgeries during the same period were selected as the non-VTE group with a ratio of 1 :4.Univariate and multivariate Logistic regression analysis were used to ana-lyze the risk factors of VTE after gynecological surgery,and a modified VTE risk factor rapid assessment model(referred to as the improved VTE score model)was constructed.The receiver operating characteristic(ROC)curve was used to study the predictive value for VTE for in gynecological surgery,and compared with the Caprini score model(Caprini table for short).Results:①Multivatiate Logistic regression analysis showed that there were independent risk factors for postoperative VTE in gynecology surgery(OR＞1,P＜0.05),including age≥60 years,BMI≥28 kg/m2,malignant tumors,surgery time＞3 hours,history of thrombosis,and the increased D-di-mer difference before and after surgery.②The Area under Curve(AUC)of ROC was 0.963 in the improved VTE score model with a Youden index 81.10％,sensitivity 87.80％and specificity 93.29％.The AUC of the Caprini score model was 0.888 with Youden index 63.41％,sensitivity 73.17％and specificity 90.24％.The improved VTE score model the Caprini score model identified 92.68％and 85.37％of VTE patients as high-risk or ex-tremely high-risk,respectively,but the difference was not statistically significant(P＜0.05).Conclusions:More attention should be paid to the six independent risk factors for postoperative VTE in gynecology surgery.The two score models showed a similar identified level.However,the improved VTE score model is more simple and easier to operate,has better practicality,and has certain clinical promotion value.

AIM:To investigate the effects of the compound ANBP on wound healing in diabetic rats and ex-plore its mechanism of action.METHODS:Ninety male SD rats were randomly divided into blank,model,compound ANBP,Beifuxin,and nicotinamide mononucleotide(NMN)groups,with 16 rats in each group.Wound healing in each group was observed and samples were taken on days 3,7 and 14 to analyze the wound healing rate.Local histopathological changes were observed using HE and Masson staining.The expressions of pyruvate dehydrogenase E1 subunit alpha 1(PDHA1),citrate synthase(CS),isocitrate dehydrogenase(IDH1)and oxoglutarate dehydrogenase(OGDH)were de-tected through immunofluorescence and Western blot.The number and morphology of mitochondria in the wound tissue were observed using transmission electron microscopy.RESULTS:Histomorphological changes revealed significant im-provement in diabetic wound healing in the blank and compound ANBP groups compared to that of the model group.The wound healing rates of the blank,compound ANBP,Beifuxin,and NMN groups were significantly increased on days 3,7,and 14(P<0.01).Compared to the model group,granulation tissue generation was higher in the other groups,cover-ing the wound defect and producing abundant collagen fibers.At 3,7,and 14 days after intervention,the blank,com-pound ANBP,Beifuxin,and NMN groups showed significantly enhanced fluorescence intensities of TCA cycling-related enzymes PDHA1,CS,IDH1,and OGDH indicating increased expression of these enzymes.The levels of the TCA cy-cling-related enzymes were significantly increased(P<0.01)in the compound ANBP,Beifuxin and NMN groups but were significantly decreased(P<0.01)in the model group.An increase in the number and density of mitochondria and a de-crease in the cavitation rate of mitochondria with improved morphology(P<0.05)was observed in the group treated with compound ANBP.CONCLUSION:Compound ANBP may increase the number of mitochondria,improve mitochondrial morphology and function,upregulate the expression levels of PDHA1,CS,IDH1,and OGDH proteins,and accelerate the regeneration of wound granulation tissue,thus promoting the healing of diabetic wounds in rats.

Objective:To construct a nomogram model for predicting the risk of leukopenia among tuberculosis patients receiving anti-tuberculosis therapy.Methods:A total of 2 681 tuberculosis patients admitted to the affiliated Dongyang Hospital of Wenzhou Medical University from Jan 2013 to Jun 2024，were enrolled in this study. All cases received first line anti-tuberculosis treatment and were randomly divided into training（ n=1 876）and validation groups（ n=805）at a ratio of 7∶3. The endpoint was the occurrence of leukopenia during anti-tuberculosis therapy. In the training group，the predictors were screened by Lasso regression and multivariable Logistic regression analysis，and used to establish a nomogram prediction model. The discrimination power，fitness and clinical applicability were evaluated using the receiver operating characteristic（ROC）curve，calibration curve and decision curve analysis，respectively. Several machine learning models based on different methods（random forest，support vector machine，extreme gradient boosting and naive Bayes）were also constructed in the validation group. Results:There were 15.0%（273/1 876）and 15.9%（128/805）of cases developing leukopenia during anti-tuberculosis therapy in the training group and validation groups，respectively. Following Lasso regression analysis，the multivariable Logistic regression analysis showed that age ≥65 years（ OR=2.997，95% CI 2.185-4.128），alcohol consumption（ OR=4.803，95% CI 3.502-6.593）and diabetes（ OR= 5.459，95% CI 3.914-7.621）were risk factors related to the occurrence of leukopenia；while the higher levels of baseline hemoglobin（ OR=0.979，95% CI 0.971-0.987）and platelet count（ OR=0.996，95% CI 0.995-0.998）were protective factors. Based on these five factors，a nomogram prediction model was developed. The areas under ROC curve（AUCs）were 0.836（95% CI 0.810-0.863）and 0.818（95% CI 0.776-0.860）in the training group and the validation group，respectively. Moreover，this model had good fitness and clinical applicability. The discrimination power of nomogram model was comparable to those of machine learning models. Conclusion:The established nomogram model in this study has good discrimination power，calibration ability and clinical applicability for predicting the risk of leucopenia in tuberculosis patients undergoing anti-tuberculosis therapy.

Objective:To construct a nomogram model for predicting the risk of leukopenia among tuberculosis patients receiving anti-tuberculosis therapy.Methods:A total of 2 681 tuberculosis patients admitted to the affiliated Dongyang Hospital of Wenzhou Medical University from Jan 2013 to Jun 2024，were enrolled in this study. All cases received first line anti-tuberculosis treatment and were randomly divided into training（ n=1 876）and validation groups（ n=805）at a ratio of 7∶3. The endpoint was the occurrence of leukopenia during anti-tuberculosis therapy. In the training group，the predictors were screened by Lasso regression and multivariable Logistic regression analysis，and used to establish a nomogram prediction model. The discrimination power，fitness and clinical applicability were evaluated using the receiver operating characteristic（ROC）curve，calibration curve and decision curve analysis，respectively. Several machine learning models based on different methods（random forest，support vector machine，extreme gradient boosting and naive Bayes）were also constructed in the validation group. Results:There were 15.0%（273/1 876）and 15.9%（128/805）of cases developing leukopenia during anti-tuberculosis therapy in the training group and validation groups，respectively. Following Lasso regression analysis，the multivariable Logistic regression analysis showed that age ≥65 years（ OR=2.997，95% CI 2.185-4.128），alcohol consumption（ OR=4.803，95% CI 3.502-6.593）and diabetes（ OR= 5.459，95% CI 3.914-7.621）were risk factors related to the occurrence of leukopenia；while the higher levels of baseline hemoglobin（ OR=0.979，95% CI 0.971-0.987）and platelet count（ OR=0.996，95% CI 0.995-0.998）were protective factors. Based on these five factors，a nomogram prediction model was developed. The areas under ROC curve（AUCs）were 0.836（95% CI 0.810-0.863）and 0.818（95% CI 0.776-0.860）in the training group and the validation group，respectively. Moreover，this model had good fitness and clinical applicability. The discrimination power of nomogram model was comparable to those of machine learning models. Conclusion:The established nomogram model in this study has good discrimination power，calibration ability and clinical applicability for predicting the risk of leucopenia in tuberculosis patients undergoing anti-tuberculosis therapy.