Objective:To construct a "local-systemic" dual-track prediction model integrating the resistance index (RI) score of bilateral sacroiliac joints and the systemic immune-inflammation index (SII), and to evaluate its predictive efficacy for the active stage of ankylosing spondylitis (AS).Methods:A total of 205 patients with ankylosing spondylitis (AS) from the Second Hospital of Lanzhou University between April 2022 and April 2025 were retrospectively enrolled and categorized into an active group ( n=113) and a remission group ( n=92). Hematological parameters and ultrasound data were collected. The resistance index (RI) of the synovial area in bilateral sacroiliac joints was measured by Doppler ultrasound and scored as follows: RI < 0.5: 3 points; RI 0.5~0.55: 2 points; RI > 0.55: 1 point; undetectable blood flow: 0 points. A total bilateral RI score (range 0 to 6) was calculated. The systemic immune-inflammation index (SII) was derived as (neutrophils× platelets)/lymphocytes. Normality was tested for all continuous variables; normally distributed data were compared using the t-test, while non-normally distributed data were analyzed with the Mann-Whitney U test. Categorical variables were compared using the χ2 test or analysis of variance.Variable selection was performed using Lasso regression, and a multivariate logistic regression model was developed to assess predictive performance. Results:The proportion of patients with a bilateral RI total score≥5 was significantly higher in the active group compared to the remission group (50 of 113, 44.3% vs 2 of 92, 2.2%, χ2=55.63, P<0.001). Multivariate logistic regression analysis, after adjustment for confounding variables, identified the SII [ OR(95% CI)=1.01(1.00, 1.01), P<0.001], bilateral RI total score [ OR(95% CI)=1.67(1.29, 2.26), P<0.001], erythrocyte sedimentation rate [ OR(95% CI)=1.19(1.11, 1.30), P<0.001], and mean corpuscular hemoglobin concentration [ OR(95% CI)=1.09(1.03, 1.17), P<0.001] as independent risk factors for active AS. Conversely, lymphocyte count [ OR(95% CI)=0.42(0.18, 0.92), P=0.030] and globulin [ OR(95% CI)=0.89(0.80, 0.99), P=0.040] were significantly associated with protective effects. The bilateral RI total score demonstrated the strongest predictive effect, with each 1-point increase associated with a 67% elevation in the risk of active disease. ROC curve analysis indicated that the area under the curve (AUC) for predicting whether AS is in the active disease phase was 0.94 for the combined model (SII+bilateral RI total score), compared with 0.93 for the SII-alone model and 0.92 for the bilateral RI total score-alone model, demonstrating superior predictive performance of the combined model (SII+bilateral RI total score). An online prediction tool has been developed based on the combined model. Conclusion:The dual-track prediction model, which integrates local joint hemodynamic characteristics and systemic immune-inflammatory status, facilitates a multidimensional assessment of the risk of active AS and provides an objective basis for early identification.

To summarize the distribution characteristics of human papillomavirus(HPV) infection types in patients with cervical squamous intraepithelial lesion(SIL) and cervical cancer(CC), and to explore the impact of HPV vaccination, HPV infection types, and general clinical data on different grades of cervical lesions.

Objective:To construct a "local-systemic" dual-track prediction model integrating the resistance index (RI) score of bilateral sacroiliac joints and the systemic immune-inflammation index (SII), and to evaluate its predictive efficacy for the active stage of ankylosing spondylitis (AS).Methods:A total of 205 patients with ankylosing spondylitis (AS) from the Second Hospital of Lanzhou University between April 2022 and April 2025 were retrospectively enrolled and categorized into an active group ( n=113) and a remission group ( n=92). Hematological parameters and ultrasound data were collected. The resistance index (RI) of the synovial area in bilateral sacroiliac joints was measured by Doppler ultrasound and scored as follows: RI < 0.5: 3 points; RI 0.5~0.55: 2 points; RI > 0.55: 1 point; undetectable blood flow: 0 points. A total bilateral RI score (range 0 to 6) was calculated. The systemic immune-inflammation index (SII) was derived as (neutrophils× platelets)/lymphocytes. Normality was tested for all continuous variables; normally distributed data were compared using the t-test, while non-normally distributed data were analyzed with the Mann-Whitney U test. Categorical variables were compared using the χ2 test or analysis of variance.Variable selection was performed using Lasso regression, and a multivariate logistic regression model was developed to assess predictive performance. Results:The proportion of patients with a bilateral RI total score≥5 was significantly higher in the active group compared to the remission group (50 of 113, 44.3% vs 2 of 92, 2.2%, χ2=55.63, P<0.001). Multivariate logistic regression analysis, after adjustment for confounding variables, identified the SII [ OR(95% CI)=1.01(1.00, 1.01), P<0.001], bilateral RI total score [ OR(95% CI)=1.67(1.29, 2.26), P<0.001], erythrocyte sedimentation rate [ OR(95% CI)=1.19(1.11, 1.30), P<0.001], and mean corpuscular hemoglobin concentration [ OR(95% CI)=1.09(1.03, 1.17), P<0.001] as independent risk factors for active AS. Conversely, lymphocyte count [ OR(95% CI)=0.42(0.18, 0.92), P=0.030] and globulin [ OR(95% CI)=0.89(0.80, 0.99), P=0.040] were significantly associated with protective effects. The bilateral RI total score demonstrated the strongest predictive effect, with each 1-point increase associated with a 67% elevation in the risk of active disease. ROC curve analysis indicated that the area under the curve (AUC) for predicting whether AS is in the active disease phase was 0.94 for the combined model (SII+bilateral RI total score), compared with 0.93 for the SII-alone model and 0.92 for the bilateral RI total score-alone model, demonstrating superior predictive performance of the combined model (SII+bilateral RI total score). An online prediction tool has been developed based on the combined model. Conclusion:The dual-track prediction model, which integrates local joint hemodynamic characteristics and systemic immune-inflammatory status, facilitates a multidimensional assessment of the risk of active AS and provides an objective basis for early identification.

Background Amid global climate change, extreme environmental events are occurring more frequently, and it is imperative to investigate the impacts of combined exposure to fine particluate matter (PM_2.5) and cold spells (CS) on population mortality. Objective To analyze the association between sequential extreme PM_2.5-cold spell (EP-CS) events and non-accidental mortality among residents in Zigong City from 2016 to 2021. Methods Using time-series study design, meteorological data in Zigong were collected from the Zigong Meteorological Bureau for the period from January 1, 2016 to December 31, 2021, while daily non-accidental mortality data were obtained from the mortality surveillance system of the Zigong Center for Disease Control and Prevention. We adopted the percentile method to define extreme PM_2.5 events and cold spells. We analyzed the risk effect of EP-CS events on non-accidental mortality among residents in this city and explored the potential amplification of damage resulting from different patterns of consecutive extreme events by using distributed lag nonlinear model (DLNM). We also conducted stratified analyses based on age, gender, education level, and marital status. Results The EP-CS events demonstrated a significant impact on non-accidental mortality among the local residents, exhibiting a certain lagged effect. The effects on the overall residents lasted from lag0 (RR=1.030, 95%CI: 1.013, 1.048) to lag14 (RR=1.035, 95%CI: 1.019, 1.052). Notably, the effects were more pronounced among females, individuals aged 65 years and above, and those who were never married, divorced, or widowed. Different patterns of EP-CS events all associated with adverse effects, the health impact of EP-CS events was significantly greater than that of individual PM_2.5 pollution or CS events. The analysis of lag effects across different event patterns revealed that the overall effect of EP-CS events with shorter intervals (0–7 d) had a stronger effect compared to EP-CS with longer intervals (8–14 d), and the RR values of lag14 were 1.034 (95%CI: 1.015, 1.054) and 1.017 (95%CI: 1.007, 1.027), suggesting that the damaging effect of compound events occurring in the short term was more significant. Conclusion All sequential extreme EP-CS events have an impact on non-accidental mortality among residents in this city, with compound events demonstrating a stronger effect. Females, individuals aged ≥65 years, and those who were never married, divorced, or widowed are more sensitive to EP-CS events.

Objective:To explore the heterogeneity in the trajectories ofperinatal depressive symptoms and identify the related factors.Methods:A longitudinal follow-up study was conducted from January 2020 to June 2021.Baseline information,marriage satisfaction and social support status were collected at enrolment.Perinatal de-pressive symptoms were measured using the Edinburgh Postnatal Depression Scale(EPDS)at five time-points from second trimester to three-months postpartum.A Latent Class Growth Model(LCGM)was used to identify sub-groups of perinatal depressive symptoms trajectories and logistic regression was applied to examine associated risk and protective factors.Results:Two latent depression trajectory subgroups were identified A majority(72.2％,n=1 023)followed a curvilinear trajectory with low baseline scores that increased over time(curvilinear group),while 27.8％(n=393)maintained high,stable scores(linear group).Older age,higher marital satisfaction,and stronger social support were associated with a lower likelihood of belonging to the linear group(OR=0.96,0.94,0.89,re-spectively),while a personal or family history of depression increased this likelihood(OR=2.50,6.51).Conclusion:Trajectories of perinatal depressive symptoms vary significantly among individuals.The risk of persis-tent high-level symptoms is lowered by older age,stronger marital satisfaction,and greater social support,and heightened by a personal or family history of depression.

Objective To explore the biological effects and changes of metabolites of Guilu erxian glue(GLE)in vivo in the pre-vention and treatment of postmenopausal osteoporosis(PMO),based on non-targeted metabolomics.Methods Fifty SD female rats were divided into five groups using the random number table method:sham group,model group(OVX),and low-,medium-,and high-dose GLE(GLE-L,GLE-M and GLE-H)groups,with ten mice in each group.After 1 week of modeling,the drug was given by gavage,and samples were collected 8 weeks later.Bone microstructure was detected by MicroCT,bone metabolism-related indices were analyzed by immunohistochemistry(IHC),and a serum metabolite atlas was constructed using the LC-MS/MS technique to observe the distribution differences of metabolites and related pathways.Results The MicroCT results showed that GLE could increase the percentage of bone trabeculae and restore bone microstructure(P<0.05,GLE-M group vs.OVX group).IHC analysis showed that GLE could increase Runx2 expression in femur(P<0.05,GLE-M group vs.OVX group).There were four co-regulated metabolites in the sham group,GLE-H group,and OVX group,including 3-(3-methoxyphenyl)propionic acid,acetamide,Equol,and 1-oleoacyl-SN-glycerol-3-phosphocholine,which showed high expression in the sham group,low expression in the OVX group,and high expression in the GLE-M group.The KEGG pathway result showed that the main pathways involved between the sham group and OVX group were steroid hormone biosynthesis and cortisol synthesis and secretion.Tryptophan metabolism and phenylalanine metabolism were observed in the GLE group and OVX group.Conclusion GLE may prevent PMO by regulating metabolites in the body.

Objective:To explore the heterogeneity in the trajectories ofperinatal depressive symptoms and identify the related factors.Methods:A longitudinal follow-up study was conducted from January 2020 to June 2021.Baseline information,marriage satisfaction and social support status were collected at enrolment.Perinatal de-pressive symptoms were measured using the Edinburgh Postnatal Depression Scale(EPDS)at five time-points from second trimester to three-months postpartum.A Latent Class Growth Model(LCGM)was used to identify sub-groups of perinatal depressive symptoms trajectories and logistic regression was applied to examine associated risk and protective factors.Results:Two latent depression trajectory subgroups were identified A majority(72.2％,n=1 023)followed a curvilinear trajectory with low baseline scores that increased over time(curvilinear group),while 27.8％(n=393)maintained high,stable scores(linear group).Older age,higher marital satisfaction,and stronger social support were associated with a lower likelihood of belonging to the linear group(OR=0.96,0.94,0.89,re-spectively),while a personal or family history of depression increased this likelihood(OR=2.50,6.51).Conclusion:Trajectories of perinatal depressive symptoms vary significantly among individuals.The risk of persis-tent high-level symptoms is lowered by older age,stronger marital satisfaction,and greater social support,and heightened by a personal or family history of depression.

Objective To explore the biological effects and changes of metabolites of Guilu erxian glue(GLE)in vivo in the pre-vention and treatment of postmenopausal osteoporosis(PMO),based on non-targeted metabolomics.Methods Fifty SD female rats were divided into five groups using the random number table method:sham group,model group(OVX),and low-,medium-,and high-dose GLE(GLE-L,GLE-M and GLE-H)groups,with ten mice in each group.After 1 week of modeling,the drug was given by gavage,and samples were collected 8 weeks later.Bone microstructure was detected by MicroCT,bone metabolism-related indices were analyzed by immunohistochemistry(IHC),and a serum metabolite atlas was constructed using the LC-MS/MS technique to observe the distribution differences of metabolites and related pathways.Results The MicroCT results showed that GLE could increase the percentage of bone trabeculae and restore bone microstructure(P<0.05,GLE-M group vs.OVX group).IHC analysis showed that GLE could increase Runx2 expression in femur(P<0.05,GLE-M group vs.OVX group).There were four co-regulated metabolites in the sham group,GLE-H group,and OVX group,including 3-(3-methoxyphenyl)propionic acid,acetamide,Equol,and 1-oleoacyl-SN-glycerol-3-phosphocholine,which showed high expression in the sham group,low expression in the OVX group,and high expression in the GLE-M group.The KEGG pathway result showed that the main pathways involved between the sham group and OVX group were steroid hormone biosynthesis and cortisol synthesis and secretion.Tryptophan metabolism and phenylalanine metabolism were observed in the GLE group and OVX group.Conclusion GLE may prevent PMO by regulating metabolites in the body.

Objective:To explore the value of the vesical imaging-reporting and data system (VI-RADS) score based on multiparametric MRI (mpMRI) combined with quantitative tumor MRI parameters in assessing the muscle invasion of bladder cancer.Methods:The study was a case-control study. The data of 87 bladder cancer patients confirmed by pathology who underwent mpMRI of the bladder were retrospectively collected from the First Medical Center of Chinese PLA General Hospital between January 2019 and April 2023 The pathological findings were used as the gold standard to categorize them into the muscle invasive bladder cancer (MIBC) group (29 cases) and non-muscle invasive bladder cancer (NMIBC) group (58 cases). Quantitative parameters were measured based on preoperative mpMRI images, including the length of tumor bladder wall contact, the perpendicular distance between the bladder tumor and the tangent of the bladder wall, the maximal diameter of the bladder tumor, and the volume of the bladder tumor. Bladder cancer was classified according to the VI-RADS scoring criteria. The Mann-Whitney U test was used for intergroup comparisons. Multivariate logistic regression analysis was performed to obtain the independent risk factors related to muscle invasion of bladder cancer and to establish the model. The receiver operating characteristic curves were analyzed for MRI quantitative parameters and logistic regression models, and area under the curve (AUC) comparisons were performed using the DeLong test. Results:The differences in tumor bladder wall contact length, perpendicular distance from the tumor to the tangent line of the bladder wall, maximum diameter, bladder tumor volume, and the VI-RADS scores were statistically significant between the MIBC group and the NMIBC group ( P<0.05). Multifactorial logistic regression analysis showed that tumor bladder wall contact length ( OR=21.07, 95% CI 3.56-124.89, P=0.001) and VI-RADS score ( OR=11.90, 95% CI 3.53-40.12, P<0.001) were the independent risk factors for evaluating the muscle invasion of bladder cancer. The difference between the VI-RADS score and the tumor bladder wall contact length for assessing muscular infiltration of bladder cancer had AUCs of 0.802 (95% CI 0.704-0.899) and 0.759 (95% CI 0.652-0.865). The combined model of VI-RADS score combined with tumor bladder wall contact length had an AUC of 0.891 (95% CI 0.812-0.970), which was higher than the diagnostic efficacy of applying tumor bladder wall contact length or VI-RADS score alone ( Z=3.05, 2.37, P=0.002, 0.018). Conclusion:Tumor contact length with the bladder wall is an independent risk factor for assessing muscle invasion of bladder cancer and the combination of VI-RADS score may enhances diagnostic accuracy.

Due to the specificity of radiopharmaceuticals for targeted α radionuclide therapy, such as radioactivity and radiation damage risk, it is necessary to estimate the internal radiation dose in preclinical evaluation to correctly evaluate the efficacy and safety of the drug, as well as in subsequent clinical studies. This review illustrates current research status of estimating internal radiation dose of targeted α radionuclide therapeutic radiopharmaceuticals based on preclinical studies, in order to add insights for understanding estimation of radiopharmaceuticals internal radiation dose and provide reference for the preclinical evaluation of radiopharmaceuticals.