ObjectiveTo investigate the imaging features of calcium salt deposition and serological markers in patients with alveolar echinococcosis through a retrospective analysis， as well as independent risk factors for the degree of calcium salt deposition in lesions， and to provide a basis for assessing disease process. MethodsA retrospective analysis was performed for the imaging and clinical data of 107 patients with alveolar echinococcosis who were admitted to The First Affiliated Hospital of Shihezi University from December 2023 to June 2025， and according to the volume of calcium salt deposition， they were divided into non-deposition group with 16 patients， mild deposition group with 52 patients， moderate deposition group with 16 patients， and severe deposition group with 23 patients. A one-way analysis of variance or the Kruskal-Wallis H test was used for comparison of continuous data between groups， and the χ² test or Fisher’s exact test was used for comparison of categorical data between groups. The four groups were further combined into the low deposition group （no/mild deposition） and the high deposition group （moderate/severe deposition）. A binary logistic regression analysis was used to investigate the independent influencing factors for calcium salt deposition， and a predictive model was established. The receiver operating characteristic （ROC） curve was used to assess the predictive performance of the model， and the Bootstrap method was used for internal validation. ResultsThere were significant differences between the four groups in sex distribution， involvement of other sites， white blood cell count， lymphocyte percentage， fibrinogen， uric acid， sodium ion， chloride ion， and calcium ion （all P<0.05）. The univariate analysis showed that there were significant differences between the four groups in sex， involvement of other sites， white blood cell count， lymphocyte percentage， fibrinogen， alanine aminotransferase， albumin， creatinine， uric acid， sodium ion， chloride ion， and calcium ion （all P<0.1）. The multi-collinearity diagnosis showed that the VIF values for all continuous variables ranged from 1.104 to 1.760， suggesting that collinearity did not affect modeling. An ordinal logistic regression model was established based on sex， involvement of other sites， calcium ion， lymphocyte percentage， and uric acid. The multivariate analysis showed that lymphocyte percentage （odds ratio ［OR］=1.106， 95% confidence interval ［CI］： 1.041 — 1.174， P=0.001） and blood calcium level （OR=0.005， 95%CI： 0.000 —0.230， P=0.007） were independent influencing factors for the degree of calcium salt deposition. The regression equation was established as Logit（P）=8.231 + 0.100 × lymphocyte percentage -5.344 × calcium ion. The ROC curve analysis showed that the model had an area under the ROC curve of 0.716， with a Youden index of 0.353， a sensitivity of 1.000， and a specificity of 0.353. The Hosmer-Lemeshow test showed that the model had poor calibration （χ²=20.688， P=0.008）. The Bootstrap method with 1000 repeated samples showed that the estimated values of lymphocyte percentage （OR=1.106， 95%CI： 1.049 — 1.186， P=0.002） and calcium ion （OR=0.005， 95%CI： 0.000 — 0.214， P=0.010） were consistent with the original model， and the confidence intervals did not include 1， which further supported the reliability of the model. ConclusionBoth lymphocyte percentage and blood calcium level are independent influencing factors for calcium salt deposition in alveolar echinococcosis， and the degree of calcium salt deposition in alveolar echinococcosis lesions increases with the reduction in blood calcium level and the increase in lymphocyte percentage.

ObjectiveTo evaluate the clinical efficacy and economic value of the Jiangsu Traditional Chinese Medicine （TCM） Diagnosis and Treatment Protocol for Dominant Diseases （abbreviated as the Diagnosis and Treatment Protocol） in adult patients with non-severe community-acquired pneumonia （CAP） based on real-world clinical data. MethodsA retrospective real-world cohort study was conducted using electronic medical records of adult patients hospitalized for non-severe CAP from September 1st， 2023 to December 31st， 2024 across 10 TCM hospitals in Jiangsu province. Patients were classified into an exposure group and a non-exposure group based on whether they received Chinese herbal medicine （CHM） according to the Diagnosis and Treatment Protocol. The non-exposure group received only conventional western medicine， while the exposure group additionally received differentiated CHM for at least five consecutive days. Outcomes were compared between two patient groups， including cough resolution rate， sputum resolution rate （assessed by volume， color， and consistency）， incidence of abnormal C-reactive protein （CRP）， incidence of abnormal white blood cell （WBC） count， and radiographic resolution rate of pulmonary infiltrates on chest imaging. Multivariable logistic regression was performed to identify factors influencing clinical efficacy. Subgroup analyses were conducted according to age， gender， smoking status， history of hypertension， and pneumonia severity score （CURB-65）， and the efficacy of treatment for cough and sputum was analyzed within each subgroup. Cost-effectiveness analysis was conducted using cough resolution rate as the outcome measure， evaluating the pharmacoeconomics of the two groups. ResultsA total of 1688 patients were included with 1293 in the exposure group and 395 in the non-exposure group. Compared to the non-exposure group， the exposure group demonstrated significantly higher resolution rates of cough， sputum volume， color， and consistency， as well as a significantly lower incidence of abnormal CRP （P＜0.05）. No statistically significant difference was observed between the groups in terms of abnormal WBC count and radiographic resolution rate of pulmonary infiltrates （P＞0.05）. Logistic regression analysis showed that the cough resolution rate in the exposure group was 1.83 times that of the non-exposure group， while the probabilities of resolution in sputum volume， color， and consistency were 1.37， 2.09， and 1.56 times those of the non-exposure group， respectively （P＜0.05）. Subgroup analyses showed that the exposure group achieved significantly higher cough resolution rates across most subgroups except for populations with a CURB-65 score ≥2 or those with a history of hypertension （P＜0.05）. Specifically， among females， patients aged ≥18 and ＜65 years， non-smokers， those without hypertension， and those with a CURB-65 score of 0， the exposure group showed a higher cough resolution rate than the non-exposure group （P＜0.05）. From an economic perspective， total hospitalization cost， length of stay， antibiotic cost， and CHM cost all differed significantly between groups （P＜0.05）. The cost-effectiveness ratio （CER） was 10,788.80 CNY/case in the exposure group， while 22,513.80 CNY/case in the non-exposure group. This implies that， compared with the exposure group， the non-exposure group incurred an additional 17,302.27 CNY to achieve one case of cough resolution. When the willingness-to-pay threshold ranged from 0 to 50,000 CNY， the probability of economic advantage was consistently higher in the exposure group than in the non-exposure group. ConclusionOn the basis of conventional western medicine， the addition of CHM in accordance with the Diagnosis and Treatment Protocol can effectively improve clinical symptoms， reduce inflammatory markers， promote clinical recovery， and is more cost-effective in treating adults with non-severe CAP.

ObjectiveTo observe the real‑world effectiveness and economic outcomes of Weishi Qingjin Formula （苇石清金方， WQF） in the treatment of adult community‑acquired pneumonia （CAP） with phlegm‑heat obstructing the lung syndrome. MethodsBased on a multicenter， real-world retrospective cohort study， clinical data were collected from hospitalized adult patients diagnosed with non‑severe CAP and phlegm‑heat obstructing the lung syndrome in 10 traditional Chinese medicine （TCM） hospitals in Jiangsu province. Patients were divided into an exposure group （those who received oral WQF） and a non‑exposure group （those who did not）. The following outcomes were compared between the two groups before and after treatment， which were remission rates of clinical symptoms including cough， expectoration （sputum volume， color， consistency）， and chest pain， levels of inflammatory markers including C‑reactive protein （CRP） and white blood cell count （WBC）， and the rate of pulmonary inflammatory absorption on chest CT. Subgroup analyses were performed based on age， gender， smoking status， presence of hypertension， and the severity of community-acquired pneumonia （CURB‑65） score， comparing the two groups in terms of cough remission rate， chest pain remission rate， and chest CT absorption rate. For health economic evaluation， cost‑effectiveness analysis was used to calculate the cost‑effectiveness ratio （CER） and incremental cost‑effectiveness ratio （ICER）. Univariate sensitivity analysis and probabilistic sensitivity analysis were performed to test the robustness of the results. ResultsA total of 647 patients in the exposure group and 1491 patients in the non-exposure group were included in the final statistical analysis. There was no statistically significant difference in length of hospital stay， gender， marital status， smoking history， bronchoscopy history， and comorbidities between the groups （P＞0.05）， but age， CURB-65 score， and antibiotic use. The exposure group had significantly higher remission rates of cough and sputum consistency than the non-exposure group （P＜0.05）. After adjusting for confounders using propensity score matching and logistic regression， the cough remission rate in the exposure group was 1.49 times that of the non-exposure group （P＜0.01）. No significant difference was observed between groups in the reduction rates of CRP and WBC， and in the rate of pulmonary inflammatory absorption on chest CT （P＞0.05）. Subgroup analyses revealed that the cough remission rate in the exposure group was significantly better than that in the non-exposure group except for patients aged ≥65 years， smokers， hypertensive patients， those using other type antibiotics or not using antibiotics， and those with a CURB-65 score ≥1 （P＜0.05）. Among smokers， the chest pain remission rate in the exposure group was 4.38 times that of the non-exposure group （P＜0.01）. No significant difference in chest CT absorption rate was found between groups across subgroups of gender， age， hypertension status， or antibiotic type （P＞0.05）. In terms of economic evaluation， CER was 10,877.60 CNY/case in the exposure group and 16,773.10 CNY/case in the non-exposure group. Compared to the exposure group， the non-exposure group incurred an additional 15,034.26 CNY to achieve one case of cough resolution， indicating a more favorable cost-effectiveness profile. Probabilistic sensitivity analysis yielded results consistent with the cost-effectiveness analysis， confirming the robustness of the findings. ConclusionWQF demonstrates significant efficacy in improving cough symptoms in the treatment of adult CAP with phlegm-heat obstructing the lung syndrome， and also exhibits favorable economic benefits.

ObjectiveTo evaluate the clinical efficacy and economic value of the Jiangsu Traditional Chinese Medicine （TCM） Diagnosis and Treatment Protocol for Dominant Diseases （abbreviated as the Diagnosis and Treatment Protocol） in adult patients with non-severe community-acquired pneumonia （CAP） based on real-world clinical data. MethodsA retrospective real-world cohort study was conducted using electronic medical records of adult patients hospitalized for non-severe CAP from September 1st， 2023 to December 31st， 2024 across 10 TCM hospitals in Jiangsu province. Patients were classified into an exposure group and a non-exposure group based on whether they received Chinese herbal medicine （CHM） according to the Diagnosis and Treatment Protocol. The non-exposure group received only conventional western medicine， while the exposure group additionally received differentiated CHM for at least five consecutive days. Outcomes were compared between two patient groups， including cough resolution rate， sputum resolution rate （assessed by volume， color， and consistency）， incidence of abnormal C-reactive protein （CRP）， incidence of abnormal white blood cell （WBC） count， and radiographic resolution rate of pulmonary infiltrates on chest imaging. Multivariable logistic regression was performed to identify factors influencing clinical efficacy. Subgroup analyses were conducted according to age， gender， smoking status， history of hypertension， and pneumonia severity score （CURB-65）， and the efficacy of treatment for cough and sputum was analyzed within each subgroup. Cost-effectiveness analysis was conducted using cough resolution rate as the outcome measure， evaluating the pharmacoeconomics of the two groups. ResultsA total of 1688 patients were included with 1293 in the exposure group and 395 in the non-exposure group. Compared to the non-exposure group， the exposure group demonstrated significantly higher resolution rates of cough， sputum volume， color， and consistency， as well as a significantly lower incidence of abnormal CRP （P＜0.05）. No statistically significant difference was observed between the groups in terms of abnormal WBC count and radiographic resolution rate of pulmonary infiltrates （P＞0.05）. Logistic regression analysis showed that the cough resolution rate in the exposure group was 1.83 times that of the non-exposure group， while the probabilities of resolution in sputum volume， color， and consistency were 1.37， 2.09， and 1.56 times those of the non-exposure group， respectively （P＜0.05）. Subgroup analyses showed that the exposure group achieved significantly higher cough resolution rates across most subgroups except for populations with a CURB-65 score ≥2 or those with a history of hypertension （P＜0.05）. Specifically， among females， patients aged ≥18 and ＜65 years， non-smokers， those without hypertension， and those with a CURB-65 score of 0， the exposure group showed a higher cough resolution rate than the non-exposure group （P＜0.05）. From an economic perspective， total hospitalization cost， length of stay， antibiotic cost， and CHM cost all differed significantly between groups （P＜0.05）. The cost-effectiveness ratio （CER） was 10,788.80 CNY/case in the exposure group， while 22,513.80 CNY/case in the non-exposure group. This implies that， compared with the exposure group， the non-exposure group incurred an additional 17,302.27 CNY to achieve one case of cough resolution. When the willingness-to-pay threshold ranged from 0 to 50,000 CNY， the probability of economic advantage was consistently higher in the exposure group than in the non-exposure group. ConclusionOn the basis of conventional western medicine， the addition of CHM in accordance with the Diagnosis and Treatment Protocol can effectively improve clinical symptoms， reduce inflammatory markers， promote clinical recovery， and is more cost-effective in treating adults with non-severe CAP.

ObjectiveTo observe the real‑world effectiveness and economic outcomes of Weishi Qingjin Formula （苇石清金方， WQF） in the treatment of adult community‑acquired pneumonia （CAP） with phlegm‑heat obstructing the lung syndrome. MethodsBased on a multicenter， real-world retrospective cohort study， clinical data were collected from hospitalized adult patients diagnosed with non‑severe CAP and phlegm‑heat obstructing the lung syndrome in 10 traditional Chinese medicine （TCM） hospitals in Jiangsu province. Patients were divided into an exposure group （those who received oral WQF） and a non‑exposure group （those who did not）. The following outcomes were compared between the two groups before and after treatment， which were remission rates of clinical symptoms including cough， expectoration （sputum volume， color， consistency）， and chest pain， levels of inflammatory markers including C‑reactive protein （CRP） and white blood cell count （WBC）， and the rate of pulmonary inflammatory absorption on chest CT. Subgroup analyses were performed based on age， gender， smoking status， presence of hypertension， and the severity of community-acquired pneumonia （CURB‑65） score， comparing the two groups in terms of cough remission rate， chest pain remission rate， and chest CT absorption rate. For health economic evaluation， cost‑effectiveness analysis was used to calculate the cost‑effectiveness ratio （CER） and incremental cost‑effectiveness ratio （ICER）. Univariate sensitivity analysis and probabilistic sensitivity analysis were performed to test the robustness of the results. ResultsA total of 647 patients in the exposure group and 1491 patients in the non-exposure group were included in the final statistical analysis. There was no statistically significant difference in length of hospital stay， gender， marital status， smoking history， bronchoscopy history， and comorbidities between the groups （P＞0.05）， but age， CURB-65 score， and antibiotic use. The exposure group had significantly higher remission rates of cough and sputum consistency than the non-exposure group （P＜0.05）. After adjusting for confounders using propensity score matching and logistic regression， the cough remission rate in the exposure group was 1.49 times that of the non-exposure group （P＜0.01）. No significant difference was observed between groups in the reduction rates of CRP and WBC， and in the rate of pulmonary inflammatory absorption on chest CT （P＞0.05）. Subgroup analyses revealed that the cough remission rate in the exposure group was significantly better than that in the non-exposure group except for patients aged ≥65 years， smokers， hypertensive patients， those using other type antibiotics or not using antibiotics， and those with a CURB-65 score ≥1 （P＜0.05）. Among smokers， the chest pain remission rate in the exposure group was 4.38 times that of the non-exposure group （P＜0.01）. No significant difference in chest CT absorption rate was found between groups across subgroups of gender， age， hypertension status， or antibiotic type （P＞0.05）. In terms of economic evaluation， CER was 10,877.60 CNY/case in the exposure group and 16,773.10 CNY/case in the non-exposure group. Compared to the exposure group， the non-exposure group incurred an additional 15,034.26 CNY to achieve one case of cough resolution， indicating a more favorable cost-effectiveness profile. Probabilistic sensitivity analysis yielded results consistent with the cost-effectiveness analysis， confirming the robustness of the findings. ConclusionWQF demonstrates significant efficacy in improving cough symptoms in the treatment of adult CAP with phlegm-heat obstructing the lung syndrome， and also exhibits favorable economic benefits.

Background Platelet parameters are important indicators of cardiovascular risk, and environmental pollutants such as polychlorinated biphenyls (PCBs) may impair platelet function through oxidative stress. Objective To investigate the differential effects of single and mixed exposure to PCBs on platelet parameters among individuals with normal glucose tolerance (NGT), impaired fasting glucose (IFG), and type 2 diabetes mellitus (T2DM), and to evaluate the potential modifying role of a healthy lifestyle. Methods This study included 2249 participants (including 707 with NGT, 759 with IFG, and 783 with T2DM). Plasma PCB concentrations were measured using triple quadrupole gaschromatography-tandem mass spectrometry. Generalized linear regression was used to assess the associations between individual PCB congeners and platelet parameters. Quantile g-computation (QGC) and Bayesian kernel machine regression (BKMR) models were used to evaluate the overall effects of PCBs mixture exposure on platelet parameters across different glycemic states, as well as its interaction with healthy lifestyle score (HLS). Results Generalized linear regression analyses showed significant differences in the effects of PCBs on platelet parameters across different glycemic states (P<0.05). After adjusting for confounders, PCBs mixture exposure was significantly associated with lower platelet counts (PLT) in individuals with NGT (b=−10.60, 95%CI: −16.48, −4.71) and IFG (b=−12.91, 95%CI: −18.90, −6.92), whereas no significant association was observed in individuals with T2DM (P=0.051). Mean platelet volume (MPV) and platelet-large cell ratio (P-LCR) increased significantly with higher PCBs exposure levels across all three groups (P<0.05). BKMR analysis showed a positive association between PCBs mixture exposure and P-LCR, with the strongest association observed in the NGT group. Furthermore, a significant interaction was observed between HLS and PCBs mixture exposure, and a higher HLS attenuated the effects of PCBs on P-LCR. Conclusion Glycemic glycemic states may modify the effects of PCBs on platelets. Individuals with NGT appear more sensitive to PCBs exposure, whereas the T2DM state may attenuate this effect. Moreover, healthy lifestyles, including not smoking, moderate alcohol consumption, maintaining moderate-to-high physical activity, a healthy diet, and an appropriate body mass index (BMI), may mitigate the adverse effects of most PCBs on platelet parameters.

Background Platelet parameters are important indicators of cardiovascular risk, and environmental pollutants such as polychlorinated biphenyls (PCBs) may impair platelet function through oxidative stress. Objective To investigate the differential effects of single and mixed exposure to PCBs on platelet parameters among individuals with normal glucose tolerance (NGT), impaired fasting glucose (IFG), and type 2 diabetes mellitus (T2DM), and to evaluate the potential modifying role of a healthy lifestyle. Methods This study included 2249 participants (including 707 with NGT, 759 with IFG, and 783 with T2DM). Plasma PCB concentrations were measured using triple quadrupole gaschromatography-tandem mass spectrometry. Generalized linear regression was used to assess the associations between individual PCB congeners and platelet parameters. Quantile g-computation (QGC) and Bayesian kernel machine regression (BKMR) models were used to evaluate the overall effects of PCBs mixture exposure on platelet parameters across different glycemic states, as well as its interaction with healthy lifestyle score (HLS). Results Generalized linear regression analyses showed significant differences in the effects of PCBs on platelet parameters across different glycemic states (P<0.05). After adjusting for confounders, PCBs mixture exposure was significantly associated with lower platelet counts (PLT) in individuals with NGT (b=−10.60, 95%CI: −16.48, −4.71) and IFG (b=−12.91, 95%CI: −18.90, −6.92), whereas no significant association was observed in individuals with T2DM (P=0.051). Mean platelet volume (MPV) and platelet-large cell ratio (P-LCR) increased significantly with higher PCBs exposure levels across all three groups (P<0.05). BKMR analysis showed a positive association between PCBs mixture exposure and P-LCR, with the strongest association observed in the NGT group. Furthermore, a significant interaction was observed between HLS and PCBs mixture exposure, and a higher HLS attenuated the effects of PCBs on P-LCR. Conclusion Glycemic glycemic states may modify the effects of PCBs on platelets. Individuals with NGT appear more sensitive to PCBs exposure, whereas the T2DM state may attenuate this effect. Moreover, healthy lifestyles, including not smoking, moderate alcohol consumption, maintaining moderate-to-high physical activity, a healthy diet, and an appropriate body mass index (BMI), may mitigate the adverse effects of most PCBs on platelet parameters.

Objective To explore the efficiency improvement in segmenting neural network with the application of Transformer + U-Net artificial intelligence (AI) and modeling with the application of Python scripts in three-dimensional (3D) printing brachytherapy. Methods A Transformer + U-Net AI neural network model was constructed, and Adam optimizer was used to ensure rapid gradient descent. Computed tomography or magnetic resonance imaging data of patients were standardized and processed as self-made data sets. The training set was used to train AI and the optimal result weight parameters were saved. The test set was used to evaluate the AI ability. Python programming language was used to write an automated script to obtain the output segmentation image and convert it to the STL file for import. The source applicator and needle could be automatically modeled. The time of automatic segmentation and modeling and the time of manual segmentation and modeling were entered by two people, and the difference was verified by paired t-test. Results Dice similarity coefficient (DSC), mean intersection over union (MIOU), and Hausdorff distance (HD95) were used for evaluation. DSC was 0.9341, MIOU was 0.8762, and mean HD95 was 2.516. The mean time of manual segmentation was 1187 s, and the mean time of AI segmentation was 145 s (P < 0.01). The mean time of manual modeling was 321 s, and the mean time of modeling with Python automated scripts was 18 s (P < 0.01). Conclusion The application of Transformer + U-Net automatic segmentation and Python automated scripts can effectively improve work efficiency in the 3D printing brachytherapy for cervical cancer.

Objective:To investigate the application value of risk prediction model for acute kidney injury (AKI) after donation of cardiac death (DCD) liver transplantation based on machine learning algorithm.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 001 pairs of DCD liver transplant donors and recipients at five hospitals, including The First Affiliated Hospital of Zhejiang University School of Medicine et al, in the Chinese Liver Transplan-tation Registry from January 2015 to December 2023 were collected. Of the donors, there were 825 males and 176 females. Of the recipients, there were 806 males and 195 females, aged 52 (range, 18-75)years. There were 281 recipients included using oversampling technique, and all 1 282 recipients were divided to the training set of 897 recipients and the validation set of 385 recipients by a ratio of 7∶3 using computer-generated random numbers. Seven prediction models, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbors (KNN), and Categorical Boosting (CatBoost), were constructed for AKI after liver transplantation based on machine learning algorithm. Observation indicators: (1) comparison of clinicopathological characteristics between recipients with and without AKI and donors; (2) follow-up and survival of recipients with and without AKI; (3) construction and validation of nomogram prediction model of AKI after liver transplantation; (4) construction and validation of machine learning prediction model of AKI after liver transplantation. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test, and comparison among groups was conducted using the Kruskal-Wallis H test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. Kaplan-Meier method was used to calculate survival rates and plot survival curves. Logistic regression model was performed for univariate and multivariate analyses. The receiver operating characteristic (ROC) curve was plotted to calculate area under curve (AUC) and 95% confidence interval ( CI). The performance of prediction model was evaluated using DeLong test, accuracy, sensitivity, specificity. The calibration curve was plotted to evaluate the performance of predicted probability and actual probability. The interpretability analysis of machine learning algorithm and SHapley Additive exPlanations was used to explain the model decision separately. Results:(1) Comparison of clinicopathological characteristics between recipients with and without AKI and donors. Of 1 001 recipients, there were 360 cases with AKI and 641 cases without AKI after liver transplantation. There were significant differences in body mass index (BMI), hepatic encepha-lopathy, hepatitis B surfact antigen (HBsAg), hepatorenal syndrome (HRS) and donor diabetes, donor blood urea nitrogen, donor alanine aminotransferase, donor aspartate aminotransferase, mass of graft, volume of blood loss during liver transplantation, warm ischema time of donor liver, and operation time between recipients with and without AKI ( Z=-4.337, χ2=9.751, 9.088, H=11.142, χ2=5.286, Z=-3.360, -2.539, -3.084, -1.730, -3.497, -1.996, -2.644, P<0.05). (2) Follow-up and survival of recipients with and without AKI. All the 1 001 recipients received follow-up. The recipients with AKI after liver transplantation were followed up for 18.6(range, 0-102.3)months, and recipients without AKI after liver transplantation were followed up for 31.9(range, 0.1-105.5)months. The 1-, 3-, and 5-year overall survival rates were 72.1%, 63.5%, and 59.3% of recipients with AKI, versus 86.7%, 76.7%, and 72.5% of recipients without AKI, respectively, showing a significant difference in overall survival between them ( χ2=26.028, P<0.05). (3) Construction and validation of nomogram predic-tion model of AKI after liver transplantation. Results of multivariate analysis showed that recipient BMI, recipient creatinine, recipient HBsAg, recipient HRS, donor blood urea nitrogen, donor crea-tinine, anhepatic phase and volume of blood loss during liver transplantation were independent risk factors for AKI of recipients after liver transplantation ( odds ratio=1.113, 0.998, 0.605, 1.580, 1.047, 0.998, 1.006, 1.157, 95% CI as 1.070-1.157, 0.996-1.000, 0.450-0.812, 1.021-2.070, 1.021-1.074, 0.996-0.999, 1.000-1.012, 1.045-1.281, P<0.05). The nomogram prediction model of AKI after liver transplantation was constructed based on the results of multivariate analysis. Results of ROC curve showed that the AUC of 0.666 (95% CI as 0.637-0.696). (4) Construction and validation of machine learning prediction model of AKI after liver transplantation. Based on the Lasso regression analysis, seven machine learning algorithm prediction models, including RF, XGBoost, SVM, LR, DT, KNN, and CatBoost, were constructed, with ROC curves of the validation set plotted. The AUC of above models were 0.863, 0.841, 0.721, 0.637, 0.620, 0.708, 0.731, accuracies were 0.764, 0.782, 0.701, 0.592, 0.605, 0.605, 0.681, sensitivities were 0.764, 0.789, 0.719, 0.588, 0.694, 0.694, 0.704, specificities were 0.763, 0.774, 0.683, 0.597, 0.511, 0.511, 0.656, respectively. Delong test showed that the RF model with the highest AUC of 0.863(95% CI as 0.828-0.899). Calibration curve analysis showed the predicted probability closest to the actual probability of RF model, indicating the model with a good validation value. Further sorting of SHAP of different clinical factors based on RF model showed that recipient BMI, donor blood urea nitrogen, volume of blood loss during liver transplantation, donor age had large effects on the output outcomes. Conclusion:The nomogram prediction model and seven machine learning algorithm prediction models for AKI after DCD liver transplantation are constructed, and the RF model based on machine learning has a better predictive performance.

Aim To investigate the antidepressant mechanism of hyperforin via the utilization of single-cell sequencing technology.Methods C57BL/6 mice were randomly divided into the control group,depres-sion model group,and hyperforin intervention group.The chronic unpredictable mild stress(CUMS)model was induced and drug interventions were administered for 28 d.Behavioral experiments were conducted to as-sess depressive symptoms,and hippocampal tissue was collected for single-cell RNA sequencing.Key cell populations and differentially expressed genes across groups were identified,followed by PPI network,GO,and KEGG enrichment analysis.Results Behavioral experiments indicated that CUMS successfully induced depressive symptoms in mice,while hyperforin im-proved depressive behavior.In the depression model group,the proportion of brain perivascular macrophages(PVM)increased,and this proportion decreased after hyperforin intervention,approaching the level seen in the control group.The top 20 common differentially ex-pressed genes in the PVM subpopulation were Saa3,Hbb-bs and Ccl24.PPI network analysis identified core targets,including Ccl2,Dhx9,C3,Msr1,Cxcl2 and Cx3cr1.KEGG enrichment analysis revealed pathways related to chemokines,phagosome formation,and inosi-tol phosphate metabolism.Conclusion The antide-pressant mechanism of hyperforin may be related to the regulation of Ccl24 and its related chemokine signaling pathway by PVM.