OBJECTIVE To investigate the influence of CYP2C19 gene polymorphism on platelet function and inflammatory cytokines in elderly patients with ischemic stroke， and to analyze potential factors associated with poor prognosis. METHODS A retrospective study was conducted on elderly patients with ischemic stroke admitted to our hospital from June 2024 to June 2025， wh o underwent CYP2C19 genotype testing and received antiplatelet therapy with clopidogrel. The levels of platelet function indicators and inflammatory cytokines before and after treatment were compared among patients with different metabolic phenotypes. Based on the prognosis at 6 months post-treatment， patients were divided into poor prognosis group and good prognosis group. Univariate analysis was performed on general data， metabolic phenotype， the levels of platelet function indicators and inflammatory cytokines. Variables with P ＜0.05 and the levels of inflammatory cytokines before treatment were included in a multivariate Logistic regression analysis to identify independent risk factors for poor prognosis. Multiple linear regression was used to further analyze the relationship between metabolic phenotypes and inflammatory cytokines. RESULTS A total of 448 elderly patients with ischemic stroke were included； among them， 162 cases were normal metabolic phenotype， 218 were intermediate metabolic phenotype， and 68 were poor metabolic phenotype. No rapid or ultrarapid metabolic phenotypes were observed. After treatment， platelet aggregation rate， the levels of P-selectin and platelet activated complex-1 （PAC-1）， high-sensitivity C-reactive Protein （hs-CRP）， interleukin-1β （IL-1β）， IL-6 and tumor necrosis factor-α （TNF-α） in the normal metabolic phenotype group， intermediate metabolic phenotype group， and poor metabolic phenotype group （except for platelet aggregation rate， and the levels of P-selectin and PAC-1 in the poor metabolic phenotype group） were significantly lower than those before treatment in the same group. Moreover， the above indicators in the normal metabolic phenotype group were significantly lower than those in the intermediate and poor metabolic phenotype groups at the corresponding time， and the levels of platelet function indicators in the intermediate metabolic phenotype group were significantly lower than those in the poor metabol ic phenotype group at the corresponding time （ P ＜0.05）. Univariate and multivariate Logistic regression analyses showed that combined with hypertension， combined with diabetes mellitus， and intermediate or poor metabolic genotypes were independent risk factors for poor prognosis in elderly patients with ischemic stroke （ P ＜0.05）. Multiple linear regression analysis showed that serum levels of hs-CRP， IL-1β， IL-6 and TNF-α before treatment were significantly higher in patients with intermediate and poor metabolic genotypes compared to those with normal metabolic genotype （ P ＜0.05）， with a greater magnitude of increase in inflammatory cytokines observed in the patients with poor metabolic genotype. CONCLUSIONS The elderly ischemic stroke patients with CYP2C19 intermediate and poor metabolic genotypes have poor inhibition effect on platelet and higher levels of inflammatory cytokines than normal metabolic genotype； CYP2C19 gene polymorphism， and in combination with hypertension and diabetes， can be used as independent predictors of poor prognosis.

Objective: To retrospectively analyze the early monitoring indicators before and after admission, the use of coagulation/anticoagulant medications, and the red blood cell transfusion within 24 hours in emergency trauma patients, and to identify the indicators related to the volume of red blood cells transfused during the first 24 hours of hopitalization, thereby assisting clinical judgment of the probability and required quantity of red blood cell transfusion. Methods: Data of 117 emergency trauma patients admitted to intensive care unit (ICU) from January 2022 to March 2024 were retrospectively analyzed. Patients were categorized according to whether the volume of red blood cells transfused within 24 hours exceeded specific quartile thresholds (Q1, Q2, Q3). Non-parametric tests were used for numerical variables and Chi-square tests were used for categorical variables to identify statistically significant single-factor indicators, which were subsequently incoporated into a binary logistic regression model to obtain a combined predictive probability. ROC curve analysis was performed on the multi-factor indicators and their combined predictive probability derived from the binary logistic regression model. Results: 1) The initial hemoglobin (Hb) and hematocrit (Hct) levle were independent influencing factors in the group with red blood cell transfusion volume exceeded Q1 (P<0.05), and the combined predictive probability demostrated by ROC curve analysis was AUC=0.858 (P<0.05). 2) In the group of red blood cell transfusion volume exceeding Q2, the initial Fib, transhulitic acid, human prothrombin complex, trauma category and primary trauma site were independent influencing factors (P<0.05), and the combined predictive probability of ROC curve analysis was AUC=0.966 (P<0.05). 3) Pulse pressure and trauma category were independent influencing factors in the group with red blood cell transfusion volume exceeding Q3 (P<0.05), and ROC curve analysis revealed that combined prediction probability was AUC=0.944 (P<0.05). Conclusion: Early monitoring indicators and the use of coagulation medications, before and after admission in emergency trauma patients show diagnostic value in predicting the amount of red blood cells transfused on the first day of admission. Early warning alerts established through patient monitoring indicators can reduce incidents of untimely blood supply from the blood transfusion department (blood bank) for emergency trauma patients with massive hemorrhage, especially for patients with rare blood types or during blood supply shortage.

Hypercoagulable state (HCS) after kidney transplantation is one of the common and serious complications in kidney transplant recipients, which has attracted increasing attention in recent years. HCS refers to the abnormal and excessive activation of blood coagulation function, leading to the increased risk of thrombosis. After kidney transplantation, the combined effects of hemodynamic changes, surgical trauma and severe rejection increase the incidence of HCS, not only raising the risk of thrombosis but also potentially causing graft failure and affecting the postoperative survival rate of patients. This article reviews the influencing factors, clinical manifestations, diagnostic methods and preventive strategies of HCS after kidney transplantation, aiming to provide a theoretical basis for optimizing perioperative management and improving the prognosis of patients.

OBJECTIVE To evaluate the cost-effectiveness of finerenone combined with standard of care （SoC） in the treatment of heart failure with mildly reduced ejection fraction （HFmrEF） or preserved ejection fraction （HFpEF）. METHODS Based on a phase Ⅲ clinical trial， a Markov model was constructed from the perspective of China’s healthcare system to compare the treatment outcomes of finerenone combined with SoC regimen versus SoC regimen alone in the treatment of different cardiac functional statuses of HFmrEF/HFpEF. Using quality-adjusted life year （QALY） as the health output index， 3 times China’s per capita GDP in 2023 as the willingness-to-pay （WTP） threshold， a simulation was conducted with a 3-month cycle length and a 10- year time horizon， incorporating an annual discount rate of 5%. The dynamic changes across various stages of HFmrEF/HFpEF treated with finerenone combined with SoC versus SoC alone were simulated to evaluate the long-term effectiveness and costs of the two treatment strategies. Additionally， one-way sensitivity analysis and probabilistic sensitivity analysis were performed， to test the robustness of the results. RESULTS The incremental cost-effectiveness ratio （ICER） of the finerenone combined with SoC regimen versus SoC regimen alone was 179 504.75 yuan/QALY， which was below the WTP threshold set in this study， indicating that the finerenone combined with SoC regimen possessed certain economic advantages. The results of one-way sensitivity analysis showed that the utility value of NYHA Ⅱ status， the drug price of finerenone， the discount rate， and the probability of hospital transfer for both groups had a great influence on ICER， but did not affect the robustness of the model. The probabilistic sensitivity analysis also confirmed the robustness of the model. CONCLUSIONS Under the WTP threshold set in this study， finerenone combined with SoC is cost-effective in the treatment of HFmrEF/HFpEF， compared with the SoC regimen.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

ObjectiveTo explore the construction of a risk assessment indicator system for common infectious diseases in Shanghai’s childcare institutions, and to provide a reference standard for the prevention and control of infectious diseases, staff training and system construction in childcare institutions. MethodsBy combining the Delphi method with the literature review and expert consultation, the hierarchical dimensions and items at all levels of the risk assessment indicator system for common infectious diseases in Shanghai’s childcare institutions were constructed, and the weighting coefficients were determined by analytic hierarchy process. ResultsA total of 14 experts from the field of childcare institutions, infectious disease control, child healthcare and health supervision participated in the Delphi consultation. The system consisted of four core dimensions: organizational management, team building, hardware equipment, and infectious disease surveillance and disposal, with the weighting coefficients of 0.285 9, 0.261 6, 0.204 3 and 0.248 2, respectively. The evaluation indicator system consisted of 4 primary indicators, 15 secondary indicators and 45 tertiary items. The positivity coefficients of the two rounds of Delphi consultation were 0.93 and 1.00, the authority coefficients were both 0.81, and the Kendall’s coefficient of concordance were 0.44 and 0.49, respectively (P<0.01). ConclusionThe high expert engagement and coordination indicate that organizational management and team building remain the critical priorities for infectious disease prevention and control in Shanghai’s childcare institutions. It is recommended to strengthen financial investment, improve institutional mechanisms, and enhance personnel reserves and capacity building for healthcare teachers, thereby systematically upgrading the infectious disease control capabilities of childcare institutions.

This study investigated the therapeutic effects and mechanisms of Modified Yiyi Fuzi Baijiang Powder on ulcerative colitis(UC) in rats from the perspective of dampness. SD rats were randomly allocated into six groups(n=10): control, model, mesalazine, and Modified Yiyi Fuzi Baijiang Powder at low(3.96 g·kg~(-1)·d~(-1)), medium(7.92 g·kg~(-1)·d~(-1)), and high(15.84 g·kg~(-1)·d~(-1)) doses. UC was induced in all groups except the control by administration with 3% dextran sulfate sodium(DSS) solution for 7 days. The disease activity index(DAI) was recorded, and the colon tissue was collected for analysis. Histopathological changes were assessed by hematoxylin-eosin staining. Serum levels of D-lactic acid(D-LA) and diamine oxidase(DAO) were measured by ELISA. Immunohistochemistry and PCR were employed to evaluate the expression of aquaporins(AQP3, AQP4) and tight junction proteins [zonula occludens-1(ZO-1) and occludin] at both protein and mRNA levels. Compared with the control group, the model group showed an increased DAI scores(P<0.05), intestinal mucosal damage, elevated serum levels of DAO and D-LA(P<0.05), and decreased expression of AQP3, AQP4, ZO-1, and occludin(P<0.05). Treatment with Modified Yiyi Fuzi Baijiang Powder reduced the DAI scores(P<0.05), lowered the serum levels of D-LA and DAO(P<0.05), and upregulated the expression of AQP3, AQP4, ZO-1, and occludin at both protein and mRNA levels compared with the model group. These findings suggest that Modified Yiyi Fuzi Baijiang Powder exerts therapeutic effects on UC by reducing the intestinal mucosal permeability, promoting colonic mucosal repair, and regulating abnormal intestinal water metabolism, which may involve the upregulation of AQP3 and AQP4 expression.
Animals ; Colitis, Ulcerative/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Rats ; Intestinal Mucosa/metabolism* ; Male ; Aquaporin 3/metabolism* ; Aquaporin 4/metabolism* ; Permeability/drug effects* ; Humans ; Powders ; Intestinal Barrier Function

OBJECTIVE: To explore the clinical significance of circulating tumor DNA (ctDNA) in response evaluation and relapse monitoring for patients with primary mediastinal large B-cell lymphoma (PMBCL). METHODS: The clinical characteristics, efficacy and survival of 38 PMBCL patients in our hospital from January 2010 to April 2020 were retrospectively analyzed. The ctDNA monitoring was conducted by targeted next-generation sequencing (NGS). RESULTS: Among the 38 patients, 26 cases were female, and 32 cases were diagnosed with Ann Arbor stage I-II. The 5-year overall survival (OS) rate and progression-free survival (PFS) rate were 74.7% and 61.7%, respectively. Males and those with high aaIPI scores (3 points) had a relatively poor prognosis. The NGS results of 23 patients showed that STAT6 (65.2%), SOCS1 (56.5%), and TNFAIP3 (56.5%) were the most common mutated genes. Patients with stable disease (SD)/progressive disease (PD) exhibited enrichment in cell cycle, FoxO, and TNF signaling pathways. A total of 29 patients underwent end-of-treatment PET/CT (EOT PET/CT), and 16 of them received ctDNA monitoring with 12 negative. Among 6 patients with EOT PET/CT positive (Deauville 4), 4 underwent ctDNA monitoring, and 3 of them were negative, being still in continuous remission without any subsequent anti-tumor therapy. CONCLUSION CtDNA may be combined with PET/CT to assess efficacy, monitor relapse, and guide treatment of PMBCL.
Humans ; Circulating Tumor DNA/blood* ; Female ; Mediastinal Neoplasms ; Male ; Retrospective Studies ; High-Throughput Nucleotide Sequencing ; Prognosis ; Lymphoma, Large B-Cell, Diffuse/genetics* ; Middle Aged ; Adult ; Aged ; Neoplasm Recurrence, Local ; Mutation