Objective To construct a dynamic prediction model for JC polyomavirus (JCV) reactivation after kidney transplantation. Methods A retrospective analysis was conducted on the clinical data of 128 recipients who met the inclusion criteria and received kidney transplantation in Nanfang Hospital, Southern Medical University, from June 2021 to December 2024. Dynamic Cox regression and dynamic restricted mean survival time (RMST) regression based on the landmark method were adopted to establish the dynamic prediction models, and Monte Carlo cross-validation was used to evaluate model performance. Results The dynamic models could predict the incidence and onset time of JCV reactivation within the subsequent 3 months according to covariates at each landmark time point from the 1st to the 6th month after transplantation. Remuzzi score, body mass index and warm ischemia time were independent risk factors for JCV reactivation, while a history of urinary BK polyomavirus reactivation served as a protective factor. The median values of the area under the curve, C-index and Brier score of the dynamic Cox model were 0.873, 0.851 and 0.065 respectively, and the C-index of the dynamic RMST model was 0.829, all of which were superior to those of the static model. Conclusions The landmark-based dynamic models exhibit excellent predictive performance, which may integrate baseline data and post-transplant follow-up information to realize dynamic assessment of the risk and time window of JCV reactivation, thereby providing evidence for optimizing post-operative monitoring and individualized intervention strategies.

Objective This research aims to establish a scientific research performance evaluation indicator system for public hospital staff,providing evaluation standards and assessment criteria for their research performances.Methods An indica-tor pool was developed through literature review.The indicators were determined through two rounds of Delphi expert consultations.Analytic Hierarchy Process(AHP)was used to calculate their weights and thus establish an indicator system.Results The indica-tor system consists of 8 primary indicators-research projects(0.193 3),talent cultivation(0.264 3),patents(0.046 2),publica-tions(0.118 5),monographs(0.068 1),awards(0.147 2),standards(0.094 3),and research errors(0.068 1)-encompassing 29 secondary indicators.The response rate of the second-round expert consultation was 0.85;the authority coefficient was 0.94;the importance rating of indicators was 4.44,and Kendall's coefficient was 0.260(P＜0.05).The consistency index(CI)and consistency ratio(CR)values were＜0.1,indicating good results.Conclusion The indicator system demonstrates scientifically good validity and feasibility.Thus it can be used to evaluate the research performances of public hospital staff,providing decision support for resource allocation and the optimization of incentive mechanisms.

Objective To investigate the expression and clinical significance of 12 plasma cytokines in patients with pancreatic cancer.Methods The study included 120 patients with pancreatic cancer diagnosed and treated at Qingdao University Affiliated Hospital and 68 healthy controls from March 2023 to June 2024.The levels of 12 plasma cytokines,including interleukin(IL)-1 β,IL-2,IL-4,IL-5,IL-6,IL-8,IL-10,IL-12P,IL-17,interferon(IFN)-α,IFN-γ,and tumor necrosis factor(TNF)-α,were detected using mul-tiplex bead-based flow immunoassay.The levels of tumor markers carcinoembryonic antigen(CEA),carbohydrate antigen 19-9(CA19-9)and carbohydrate antigen 72-4(CA 72-4)in the serum of pancreatic cancer patients were detected by electrochemilumines-cence,while carbohydrate antigen 242(CA242)were detected by chemiluminescence methods.The correlation between the expression levels of differentially expressed cytokines and those of tumor markers was analyzed using Spearman's rank correlation.Results The plasma levels of 9 cytokines(IL-1 β,IL-4,IL-5,IL-6,IL-8,IL-10,IL-17,IFN-α,and IFN-γ)in the patients with pancreatic canc-er were significantly higher than those in controls(all P＜0.05).The levels of IL-1 β,IL-6,IL-8,IL-10,and IL-17 in the advanced pancreatic cancer group were significantly higher than those in the early-stage group(P＜0.05).The plasma IL-6 level in the poorly dif-ferentiated pancreatic cancer group was significantly higher than that in the well-differentiated group(P＜0.05).The serum levels of CEA,CA19-9,CA242,and CA72-4 in the advanced pancreatic cancer group were significantly higher than those in the early-stage group(P＜0.05).The serum CEA level in the poorly differentiated pancreatic cancer group was significantly higher than that in the moderately differentiated pancreatic cancer group(P＜0.05).After four cycles of chemotherapy,IL-8 levels in the disease control group were significantly reduced compared to pre-treatment levels(P＜0.05),while IL-6,IL-8,and IL-10 levels in the disease progression group were significantly elevated compared to pre-treatment levels(all P＜0.05).In the patients with pancreatic cancer,plasma IL-6 levels were positively correlated with serum CEA levels(rs=0.238,P＜0.01)and serum CA19-9 levels(rs=0.186,P＜0.05).The plasma IL-10 levels were positively correlated with serum CA72-4(rs=0.220,P＜0.05)levels in the patients.Conclusion Nine cyto-kines in plasma,such as IL-6,etc.may be involved in the formation of the inflammatory microenvironment of pancreatic cancer,as well as in the proliferation and differentiation of tumor cells.The determination of their plasma levels should be helpful for the assessing disease conditions and therapeutic effects.

Objective To investigate the expression and clinical significance of 12 plasma cytokines in patients with pancreatic cancer.Methods The study included 120 patients with pancreatic cancer diagnosed and treated at Qingdao University Affiliated Hospital and 68 healthy controls from March 2023 to June 2024.The levels of 12 plasma cytokines,including interleukin(IL)-1 β,IL-2,IL-4,IL-5,IL-6,IL-8,IL-10,IL-12P,IL-17,interferon(IFN)-α,IFN-γ,and tumor necrosis factor(TNF)-α,were detected using mul-tiplex bead-based flow immunoassay.The levels of tumor markers carcinoembryonic antigen(CEA),carbohydrate antigen 19-9(CA19-9)and carbohydrate antigen 72-4(CA 72-4)in the serum of pancreatic cancer patients were detected by electrochemilumines-cence,while carbohydrate antigen 242(CA242)were detected by chemiluminescence methods.The correlation between the expression levels of differentially expressed cytokines and those of tumor markers was analyzed using Spearman's rank correlation.Results The plasma levels of 9 cytokines(IL-1 β,IL-4,IL-5,IL-6,IL-8,IL-10,IL-17,IFN-α,and IFN-γ)in the patients with pancreatic canc-er were significantly higher than those in controls(all P＜0.05).The levels of IL-1 β,IL-6,IL-8,IL-10,and IL-17 in the advanced pancreatic cancer group were significantly higher than those in the early-stage group(P＜0.05).The plasma IL-6 level in the poorly dif-ferentiated pancreatic cancer group was significantly higher than that in the well-differentiated group(P＜0.05).The serum levels of CEA,CA19-9,CA242,and CA72-4 in the advanced pancreatic cancer group were significantly higher than those in the early-stage group(P＜0.05).The serum CEA level in the poorly differentiated pancreatic cancer group was significantly higher than that in the moderately differentiated pancreatic cancer group(P＜0.05).After four cycles of chemotherapy,IL-8 levels in the disease control group were significantly reduced compared to pre-treatment levels(P＜0.05),while IL-6,IL-8,and IL-10 levels in the disease progression group were significantly elevated compared to pre-treatment levels(all P＜0.05).In the patients with pancreatic cancer,plasma IL-6 levels were positively correlated with serum CEA levels(rs=0.238,P＜0.01)and serum CA19-9 levels(rs=0.186,P＜0.05).The plasma IL-10 levels were positively correlated with serum CA72-4(rs=0.220,P＜0.05)levels in the patients.Conclusion Nine cyto-kines in plasma,such as IL-6,etc.may be involved in the formation of the inflammatory microenvironment of pancreatic cancer,as well as in the proliferation and differentiation of tumor cells.The determination of their plasma levels should be helpful for the assessing disease conditions and therapeutic effects.

Objective This research aims to establish a scientific research performance evaluation indicator system for public hospital staff,providing evaluation standards and assessment criteria for their research performances.Methods An indica-tor pool was developed through literature review.The indicators were determined through two rounds of Delphi expert consultations.Analytic Hierarchy Process(AHP)was used to calculate their weights and thus establish an indicator system.Results The indica-tor system consists of 8 primary indicators-research projects(0.193 3),talent cultivation(0.264 3),patents(0.046 2),publica-tions(0.118 5),monographs(0.068 1),awards(0.147 2),standards(0.094 3),and research errors(0.068 1)-encompassing 29 secondary indicators.The response rate of the second-round expert consultation was 0.85;the authority coefficient was 0.94;the importance rating of indicators was 4.44,and Kendall's coefficient was 0.260(P＜0.05).The consistency index(CI)and consistency ratio(CR)values were＜0.1,indicating good results.Conclusion The indicator system demonstrates scientifically good validity and feasibility.Thus it can be used to evaluate the research performances of public hospital staff,providing decision support for resource allocation and the optimization of incentive mechanisms.

Objective:To investigate the prevalence and risk factors of cornea guttata in patients with age-related cataract.Methods:A cross-sectional study was conducted.A total of 1 472 patients aged 50-89 years with complete medical records, who were diagnosed with age-related cataract and to undergo surgery, were enrolled at Peking University People's Hospital from August 2018 to July 2019.The presence of guttata was determined according to the specular microscopy images and the overall prevalence of guttata was calculated, as well as the prevalence rates of different gender, eye, and age distribution.Patients were divided into a guttata group (96 cases 130 eyes) and a non-guttata group (1 376 cases 2 814 eyes), and the differences in general information between groups were compared.The corneal endothelial cell density (CD), coefficient of variation of cell size (CV), fraction of hexagonal cells (6A), axial length (AL), white to white (WTW), anterior chamber depth, and corneal vertex thickness were compared between the two groups, and only the right eye of the patient with both eyes affected was included for analysis.The risk factors of guttata were analyzed by multivariate logistic regression.Differences in influencing factors among different guttata grades were compared, and the differences in biometric parameters of each eye in both eyes of guttata patients were compared.This study adhered to the Declaration of Helsinki, and the study protocol was approved by the Ethics Committee of Peking University People's Hospital (No.2023PHB198-001).Results:Of the 1 472 patients, 96(6.52%) patients had cornea guttata.The prevalence rate of guttata in males was 4.04%, which was significantly lower than 8.20% in females ( χ2=10.058, P=0.002).The average age of patients in the guttata group was (71.19±8.57) years old, with 24 males and 72 females, including 62 patients with monocular guttata and 39 patients with isolated guttata.Multivariate logistic regression analysis showed that female (odds ratio [ OR]=2.124, 95% confidence interval [ CI]: 1.306-3.455), greater AL ( OR=1.201, 95% CI: 1.083-1.332), shallow anterior chamber depth ( OR=0.439, 95% CI: 0.252-0.766), and greater corneal vertex thickness ( OR=1.008, 95% CI: 1.001-1.015) were risk factors for guttata.There were statistically significant differences in the proportion of monocular guttata and biocular guttata among different grades groups, and between isolated guttata and non-isolated guttata ( χ2=25.492, 15.362; both P<0.05).Differences in CD and corneal vertex thickness among different grades groups were statistically significant ( F=3.264, 5.784; both P<0.05).The CD was significanty higher and the corneal vertex thickness was significantly thinner in the grade 1 than in the grade ≥3 (both P<0.017).There was no statistically significant difference in binocular CD, CV, 6A, AL, WTW, anterior chamber depth, and corneal vertex thickness between both eyes of monocular or binocular guttata patients (all P>0.05). Conclusions:The risk factors of guttata include female, long AL, shallow anterior chamber depth, and thick corneal vertex thickness.The guttata grade of monocular guttata and isolated guttata patients is lower.With the increase of grade, the corneal vertex thickness increases.There is no difference in ocular structure between both eyes of guttata patients.

Objective:To investigate the prevalence and risk factors of cornea guttata in patients with age-related cataract.Methods:A cross-sectional study was conducted.A total of 1 472 patients aged 50-89 years with complete medical records, who were diagnosed with age-related cataract and to undergo surgery, were enrolled at Peking University People's Hospital from August 2018 to July 2019.The presence of guttata was determined according to the specular microscopy images and the overall prevalence of guttata was calculated, as well as the prevalence rates of different gender, eye, and age distribution.Patients were divided into a guttata group (96 cases 130 eyes) and a non-guttata group (1 376 cases 2 814 eyes), and the differences in general information between groups were compared.The corneal endothelial cell density (CD), coefficient of variation of cell size (CV), fraction of hexagonal cells (6A), axial length (AL), white to white (WTW), anterior chamber depth, and corneal vertex thickness were compared between the two groups, and only the right eye of the patient with both eyes affected was included for analysis.The risk factors of guttata were analyzed by multivariate logistic regression.Differences in influencing factors among different guttata grades were compared, and the differences in biometric parameters of each eye in both eyes of guttata patients were compared.This study adhered to the Declaration of Helsinki, and the study protocol was approved by the Ethics Committee of Peking University People's Hospital (No.2023PHB198-001).Results:Of the 1 472 patients, 96(6.52%) patients had cornea guttata.The prevalence rate of guttata in males was 4.04%, which was significantly lower than 8.20% in females ( χ2=10.058, P=0.002).The average age of patients in the guttata group was (71.19±8.57) years old, with 24 males and 72 females, including 62 patients with monocular guttata and 39 patients with isolated guttata.Multivariate logistic regression analysis showed that female (odds ratio [ OR]=2.124, 95% confidence interval [ CI]: 1.306-3.455), greater AL ( OR=1.201, 95% CI: 1.083-1.332), shallow anterior chamber depth ( OR=0.439, 95% CI: 0.252-0.766), and greater corneal vertex thickness ( OR=1.008, 95% CI: 1.001-1.015) were risk factors for guttata.There were statistically significant differences in the proportion of monocular guttata and biocular guttata among different grades groups, and between isolated guttata and non-isolated guttata ( χ2=25.492, 15.362; both P<0.05).Differences in CD and corneal vertex thickness among different grades groups were statistically significant ( F=3.264, 5.784; both P<0.05).The CD was significanty higher and the corneal vertex thickness was significantly thinner in the grade 1 than in the grade ≥3 (both P<0.017).There was no statistically significant difference in binocular CD, CV, 6A, AL, WTW, anterior chamber depth, and corneal vertex thickness between both eyes of monocular or binocular guttata patients (all P>0.05). Conclusions:The risk factors of guttata include female, long AL, shallow anterior chamber depth, and thick corneal vertex thickness.The guttata grade of monocular guttata and isolated guttata patients is lower.With the increase of grade, the corneal vertex thickness increases.There is no difference in ocular structure between both eyes of guttata patients.

Objective:To explore the trend of influenza positive rate in Beijing by using classic autoregressive integrated moving average (ARIMA) model, autoregressive integrated moving average model with exogenous variables (ARIMAX) and vector autoregression model (VAR) to compare the performance of three models in influenza prediction and select the most suitable one for Beijing.Methods:The weekly positive rate of influenza virus nucleic acid test and meteorological data in Beijing from week 1 of 2013 to week 40 of 2024 were collected. The data were divided into four groups with expanding training sets and corresponding testing sets. The training set of the first group was from week 1 of 2013 to week 40 of 2016, and the testing set was from week 41 of 2016 to week 40 of 2017. Subsequent groups extended the training set by one year each time. Data from 2020 to 2023 were excluded due to COVID-19 pandemic. The fourth group used data from the week 1 of 2013 to week 40 of 2023 for training and from the week 41 of 2023 to week 40 of 2024 for testing.Results:The incidence of influenza had seasonality in Beijing with higher incidence in winter and spring. The positive rate of influenza virus was positively correlated with the weekly average atmospheric pressure ( r=0.482, P<0.001) and weekly average wind speed ( r=0.003, P=0.034), and negatively correlated with the weekly average temperature ( r=-0.541, P<0.001). The ARIMAX model incorporating meteorological factors had the best prediction performance, with test set's root mean square error ( RMSE) of 0.115 3 and mean absolute error ( MAE) of 0.076 7 (the RMSE and MAE values for ARIMA and VAR models were 0.117 1 and 0.163 8, and 0.078 6 and 0.122 3, respectively). The prediction results of the optimal model showed that the positive rate of influenza virus would continue to rise in Beijing after October 2024 and reach peak in the second week of 2025, but the peak positive rate would be lower than that of previous influenza season. Conclusions:Compared with the ARIMA model and the VAR model,the ARIMAX model which used meteorological parameters is more suitable for prediction of long-term influenza trend in Beijing. The influenza trend peak was predicted to occur in the second week of 2025, but lower than that in previous influenza season.

Objective:To explore the trend of influenza positive rate in Beijing by using classic autoregressive integrated moving average (ARIMA) model, autoregressive integrated moving average model with exogenous variables (ARIMAX) and vector autoregression model (VAR) to compare the performance of three models in influenza prediction and select the most suitable one for Beijing.Methods:The weekly positive rate of influenza virus nucleic acid test and meteorological data in Beijing from week 1 of 2013 to week 40 of 2024 were collected. The data were divided into four groups with expanding training sets and corresponding testing sets. The training set of the first group was from week 1 of 2013 to week 40 of 2016, and the testing set was from week 41 of 2016 to week 40 of 2017. Subsequent groups extended the training set by one year each time. Data from 2020 to 2023 were excluded due to COVID-19 pandemic. The fourth group used data from the week 1 of 2013 to week 40 of 2023 for training and from the week 41 of 2023 to week 40 of 2024 for testing.Results:The incidence of influenza had seasonality in Beijing with higher incidence in winter and spring. The positive rate of influenza virus was positively correlated with the weekly average atmospheric pressure ( r=0.482, P<0.001) and weekly average wind speed ( r=0.003, P=0.034), and negatively correlated with the weekly average temperature ( r=-0.541, P<0.001). The ARIMAX model incorporating meteorological factors had the best prediction performance, with test set's root mean square error ( RMSE) of 0.115 3 and mean absolute error ( MAE) of 0.076 7 (the RMSE and MAE values for ARIMA and VAR models were 0.117 1 and 0.163 8, and 0.078 6 and 0.122 3, respectively). The prediction results of the optimal model showed that the positive rate of influenza virus would continue to rise in Beijing after October 2024 and reach peak in the second week of 2025, but the peak positive rate would be lower than that of previous influenza season. Conclusions:Compared with the ARIMA model and the VAR model,the ARIMAX model which used meteorological parameters is more suitable for prediction of long-term influenza trend in Beijing. The influenza trend peak was predicted to occur in the second week of 2025, but lower than that in previous influenza season.

Hypoxia is associated with the occurrence and development of many diseases in clinical settings.Cell hypoxia not only serves as a vital marker for disease advancement,but also plays a pivotal role in exacerbating the disease process,and improving tissue hypoxia may thus provide new strategies for the treatment of related diseases.Further investigation of these diseases at the cellular and molecular levels requires the establishment of a cellular hypoxia model.Current extensively employed hypoxic cell models can be categorized primarily into three types:chemical hypoxia,physical hypoxia,and glucose deprivation hypoxia models.This article reviews the various types of hypoxic cell models and scrutinizes their applications and limitations in disease research.