OBJECTIVE To investigate the distribution of Candida and predict the detection trend in the southern and northern campuses of Affiliated Hospital of Jiangnan University,Wuxi,between 2021 and 2024.METHODS A total of 27 056 patients with common Candida infections from the southern and northern campuses of Affiliated Hospital of Jiangnan University between 2021 and 2024 were selected to analyze the distribution of Candida species and predict the detection trend.RESULTS Among the 27 056 patients,there were 11 061 males and 15 995 fe-males,aged from 1 to 101 years,with a median age of 68 years.Over the past four years,the top five most com-monly detected Candida species in the hospital were Candida albicans,Candida glabrata,Candida tropicalis,Candida parapsilosis and Candida krusei.Statistically significant differences were found in infection characteris-tics among patients with C.albicans and C.glabrata in terms of gender,age,specimen source and related diseases(P＜0.05).From 2021 to 2024,the number of detected cases declined in 2022 and then rebounded(P＜0.001).Among the detected patients,those aged 70 and above accounted for the highest proportion.Regarding the distribution of specific diseases,the top three were vaginitis(4 176 cases,15.43％),bacterial pneumonia(1 842 cases,6.81％)and cancer(1 279 cases,4.73％).Patients with vaginitis were mainly infected with C.albicans,while patients with bacterial pneumonia were predominantly infected with C.albicans and C.glabrata.The LSTM model showed a good fit to the training set,with an root-mean-square error(RMSE)of 145.03 and an mean absolute error(MAE)of 131.19.Model predictions indicated that the number of patients with Candida in-fections in the hospital would remain low from Jan.to May 2025,which was basically consistent with actual clini-cal observations(RMSE=94.71,MAE=84.00).CONCLUSIONS The common diseases associated with Candi-da infections in the hospital include vaginitis,bacterial pneumonia and cancer.C.albicans and C.glabrata are the main pathogenic species,and the infection situation is relatively severe.The LSTM model performs well in short-term prediction and dynamic analysis of Candida detection trends.

OBJECTIVE To explore the application of autoregressive integrated moving average model(ARIMA)in prediction of prevalence trends of carbapenem-resistant Klebsiella pneumoniae(CRKP)in intensive care unit(ICU)so as to provide scientific bases for formulating prevention strategies for CRKP infection in ICU.METHODS The number of CRKP strains that were monthly isolated from the ICU patients of Jiangnan University Affiliated Hospital between Jan.2021 and Jan.2024 was collected,the duplicate samples from the same patient were excluded,and totally 555 strains of CRKP were finally enrolled in the study.The time series differencing was performed by using R statistical software,the ARIMA model was established,the parameters of the model were determined by means of autocorrelation function(ACF)and partial autocorrelation function(PACF)images.The optimal model was screened out by Akaike information criterion(AIC)and root-mean-square error(RMSD),the robustness of the residual sequences was assessed by Box-Ljung test.The data that were detected from Sep.2023 to Jan.2024 were assigned as the validation set,the prediction accuracy of the model was assessed,and the dy-namic trend of the CRKP strains from Feb.2024 to Apr.2024 was predicted.RESULTS The isolation rate of CRKP strains in ICU showed dynamic change from 2021 to 2023(x2=66.906,P=0.001),sputum and midstream urine were the major sources.The minimal AIC of the optimal ARIMA model(8,1,10)was 222.1,with RMSE 3.67.Box-Ljung(x2=0.104,P=0.746)test indicated that there was no autocorrelation among the residual se-quences.Both the actual CRKP and the predictive value firstly rose then descended from Sep.2023 to Jan.2024,and the average relative error of the model was 9.62％for prediction.The number of isolated CRKP strains predic-ted by the model might reached to the lowest point in Feb.2024 and then showed an upward trend,and it might reach to a high peak in Apr.CONCLUSION ARIMA model is effective for short-term prediction and dynamic anal-ysis of prevalence trend of CRKP strains in the ICU so as to provide theoretical basis for early warning of hospital-associated infection and take corresponding prevention measures.

OBJECTIVE To investigate the distribution of Candida and predict the detection trend in the southern and northern campuses of Affiliated Hospital of Jiangnan University,Wuxi,between 2021 and 2024.METHODS A total of 27 056 patients with common Candida infections from the southern and northern campuses of Affiliated Hospital of Jiangnan University between 2021 and 2024 were selected to analyze the distribution of Candida species and predict the detection trend.RESULTS Among the 27 056 patients,there were 11 061 males and 15 995 fe-males,aged from 1 to 101 years,with a median age of 68 years.Over the past four years,the top five most com-monly detected Candida species in the hospital were Candida albicans,Candida glabrata,Candida tropicalis,Candida parapsilosis and Candida krusei.Statistically significant differences were found in infection characteris-tics among patients with C.albicans and C.glabrata in terms of gender,age,specimen source and related diseases(P＜0.05).From 2021 to 2024,the number of detected cases declined in 2022 and then rebounded(P＜0.001).Among the detected patients,those aged 70 and above accounted for the highest proportion.Regarding the distribution of specific diseases,the top three were vaginitis(4 176 cases,15.43％),bacterial pneumonia(1 842 cases,6.81％)and cancer(1 279 cases,4.73％).Patients with vaginitis were mainly infected with C.albicans,while patients with bacterial pneumonia were predominantly infected with C.albicans and C.glabrata.The LSTM model showed a good fit to the training set,with an root-mean-square error(RMSE)of 145.03 and an mean absolute error(MAE)of 131.19.Model predictions indicated that the number of patients with Candida in-fections in the hospital would remain low from Jan.to May 2025,which was basically consistent with actual clini-cal observations(RMSE=94.71,MAE=84.00).CONCLUSIONS The common diseases associated with Candi-da infections in the hospital include vaginitis,bacterial pneumonia and cancer.C.albicans and C.glabrata are the main pathogenic species,and the infection situation is relatively severe.The LSTM model performs well in short-term prediction and dynamic analysis of Candida detection trends.

OBJECTIVE To explore the application of autoregressive integrated moving average model(ARIMA)in prediction of prevalence trends of carbapenem-resistant Klebsiella pneumoniae(CRKP)in intensive care unit(ICU)so as to provide scientific bases for formulating prevention strategies for CRKP infection in ICU.METHODS The number of CRKP strains that were monthly isolated from the ICU patients of Jiangnan University Affiliated Hospital between Jan.2021 and Jan.2024 was collected,the duplicate samples from the same patient were excluded,and totally 555 strains of CRKP were finally enrolled in the study.The time series differencing was performed by using R statistical software,the ARIMA model was established,the parameters of the model were determined by means of autocorrelation function(ACF)and partial autocorrelation function(PACF)images.The optimal model was screened out by Akaike information criterion(AIC)and root-mean-square error(RMSD),the robustness of the residual sequences was assessed by Box-Ljung test.The data that were detected from Sep.2023 to Jan.2024 were assigned as the validation set,the prediction accuracy of the model was assessed,and the dy-namic trend of the CRKP strains from Feb.2024 to Apr.2024 was predicted.RESULTS The isolation rate of CRKP strains in ICU showed dynamic change from 2021 to 2023(x2=66.906,P=0.001),sputum and midstream urine were the major sources.The minimal AIC of the optimal ARIMA model(8,1,10)was 222.1,with RMSE 3.67.Box-Ljung(x2=0.104,P=0.746)test indicated that there was no autocorrelation among the residual se-quences.Both the actual CRKP and the predictive value firstly rose then descended from Sep.2023 to Jan.2024,and the average relative error of the model was 9.62％for prediction.The number of isolated CRKP strains predic-ted by the model might reached to the lowest point in Feb.2024 and then showed an upward trend,and it might reach to a high peak in Apr.CONCLUSION ARIMA model is effective for short-term prediction and dynamic anal-ysis of prevalence trend of CRKP strains in the ICU so as to provide theoretical basis for early warning of hospital-associated infection and take corresponding prevention measures.

Objective To explore the mechanism of hydroxyl safflower flavin A(HSYA)in the treatment of sepsis-induced liver injury by using metabolomics and network pharmacology.Methods A total of 50 male C57BL/6 mice were randomly divided into sham-operation group(10 mice),sepsis group(20 mice)and HSYA group(20 mice).Cecal ligation and puncture was conducted to establish the sepsis-induced liver injury mouse model.The mice in HSYA group were subcutaneously injected with HSYA after 2 hours of modeling.The content of serum inflammatory factors and liver function were detected,and the pathological changes of liver tissue were observed with HE staining,UPLC-Q-TOF-MS metabolomics was used to analyze liver tissue,screening for differential metabolites using multivariate statistical methods,network pharmacology was used to predict potential targets for HSYA treatment of sepsis-induced liver injury,and conduct GO and KEGG pathway enrichment analysis on potential targets,Metabo Analyst 5.0 database was used to match differential metabolites and potential targets between the model group and HSYA group,a targets metabolite-metabolism pathway network was constructed.AutoDock Vina software was used to perform molecular docking between HSYA and core genes,and finally RT-qPCR was used to verify the expression of core genes.Results HSYA can reduce the contents of IL-6,IL-1β and TNF-α in serum,restore liver function,and alleviate the morphological alternation in liver induced by sepsis.A total of 26 differential metabolites identified by metabolomics were screened out,including flufenamic acid,cryptolepine,opthalmic acid,fenpropathrin etc.,which were mainly involved in 5 metabolic pathways such as biosynthesis of unsaturated fatty acids and alpha-linolenic acid metabolism.Network pharmacology identified 81 potential targets,2 735 items enriched in GO and 124 signaling pathways enriched in KEGG;a total of 5 differential metabolites were matched for joint analysis,corresponding to 14 targets including IL1B,STAT3,PTGS2,TP53,etc.,involved in the regulation of metabolic disorders in sepsis-induced liver injury by HSYA.Molecular docking results showed that HSYA had good binding activity to IL1B,STAT3,PTGS2 and TP53 targets.RT-qPCR results showed that HSYA could inhibit the expressions of IL1B,STAT3 and PTGS2 in liver tissue.Conclusions HSYA may inhibit the release of inflammatory cytokines,maintain metabolic homeostasis,and alleviate sepsis-induced liver injury through modulating the expressions of IL1B,STAT3,and PTGS2.

Objective:To study the long-term clinical effect of transvaginal mesh (TVM) and pelvic floor reconstruction with native tissue repair (NTR) in the treatment of advanced pelvic organ prolapse (POP).Methods:Totally 207 patients with advanced POP who were treated in Hunan Provincial Maternal and Child Health Care Hospital from Jan. 2016 to Sep. 2019 were enrolled. The patient′s pelvic organ prolapse quantification were all at degree Ⅲ or above, and they all complained for different degree of symptoms. They were divided into two groups according to the different surgical methods, TVM group and NTR group. In TVM group, the mesh was implanted through the vagina for pelvic floor reconstruction, while in NTR group, the traditional transvaginal hysterectomy combined with uterosacral ligament suspension and anterior and posterior wall repair, as well as perineal body repair were performed. The median follow-up time was 60 months, during the follow up time, 164 cases (79.2%, 164/207) had completed follow-up, including 76 cases in TVM group and 88 cases in NTR group. The perioperative data and complication rates of the two groups were compared, and the subjective and objective outcomes of the two groups at 1, 3 and 5 years were observed, respectively. The objective efficacy was evaluated by three composite criteria, namely: (1) the distance from the farthest end of the prolapse of the anterior and posterior wall of the vagina to the hymen is ≤0 cm, and the descending distance of the top is ≤1/2 of the total length of the vagina; (2) determine the disappearance of relevant POP symptoms according to “Do you often see or feel vaginal mass prolapse？”; (3) no further operation or pessary treatment was performed due to prolapse. If the above three criteria were met at the same time, the operation is successful; otherwise, it was recurrence. The subjective efficacy was evaluated by the pelvic floor distress inventory-short form 20 (PFDI-20) and pelvic floor impact questionnaire-short form 7 (PFIQ-7).Results:The median follow-up time of the two groups was 60 months (range: 41-82 months). Five years after the operation, the subjective and objective cure rates of TVM group were 89.5% (68/76) and 94.7% (72/76), respectively. The subjective and objective cure rates in NTR group were 80.7% (71/88) and 85.2% (75/88), respectively. There were significant differences in the subjective and objective cure rates between the two groups ( χ2=9.869, P=0.002; χ2=3.969, P=0.046). The recurrence rate of TVM group was 5.3% (4/76), and that of NTR group was 14.8% (13/88). There was a significant difference between the two groups ( P=0.046). The postoperative PFDI-20 and PFIQ-7 scores of the two groups were significantly lower than those before surgery, and there were significant differences of the two groups before and after surgery (all P<0.05). Postoperative mesh exposure in TVM group was 1.3% (1/76). Conclusions:The long-term outcomes between the two groups show that the subjective and objective outcomes of pelvic floor reconstruction in TVM group are significantly higher than those in NTR group, and the recurrence rate is significantly lower than that in NTR group. TVM has certain advantages in the treatment of advanced POP.