Objective We reviewed and analyzed the epidemiological data of 83 imported dengue fever cases reported in Fengtai District, Beijing, from 2007 to 2025, to delineate their epidemiological characteristics and guide the dengue fever prevention and control strategy in the future. Methods Data on dengue fever cases in Fengtai District from 2007 to 2025 were collected to identify the epidemic factors and characteristics using descriptive epidemiological method. Results All 83 dengue fever cases reported in this region over the past two decades have been imported from abroad or other domestic areas, with Southeast Asian countries being identified as the primary source of imported infections, accounting for 42 cases (50.60%), followed by 15 cases (18.07%) from Chinese provinces other than Beijing. The remaining import sources included 13 cases from South Asia,8 from African countries, and each from Oceania, South America, and Europe. Disease onset was found concentrated between May and November. The sex ratio (male-to-female) is 1.59:1. The age of onset ranged from 14 to 61 years old, with a median age of 36. The largest proportion of cases was observed among cadres and office workers (31 cases, 37.35%), followed by businessmen (13 cases, 15.67%), and householders or the unemployed (10 cases,12.05%). Travel visit was identified as the primary reason for their exposure history. Conclusions All dengue fever cases reported in Fengtai from 2007 to 2025 were imported, with an increasing trend of imported cases in Beijing originating from other Chinese provinces. It is essential to strengthen health education for foreign travelers and returning residents, enhance clinical diagnosis and treatment training for medical personnel, eliminate mosquito breeding sites, and reduce mosquito density through active patriotic health campaigns.

This case report describes a 68-year-old male patient diagnosed with primary hepatocellular carcinoma (HCC). After receiving Yttrium-90 microsphere selective internal radiation therapy (⁹⁰Y-SIRT), the tumor significantly reduced in size, and tumor markers alpha fetoprotein (AFP) and abnormal prothrombin (PIVKA-Ⅱ) decreased. Postoperative pathological results showed minimal residual tumor cells, indicating that ⁹⁰Y-SIRT has good efficacy and safety in downstaging and conversion of HCC, thereby facilitating subsequent surgical resection.

Objective To observe the therapeutic effects of different doses of methylprednisolone(MP)on smoke inhalation-induced acute lung injury(SI-ALI)in rats,and to explore the changes in the expression of aquaporins(AQPs)and the underlying mechanisms for alleviating lung injury.Methods A total of 86 healthy adult male Sprague-Dawley(SD)rats were randomly divided into five groups:control group(n=6),smoke inhalation injury(SI)group(n=20),low-dose MP group(LMP,SI+0.4 mg/kg MP,n=20),medium-dose MP group(MMP,SI+4 mg/kg MP,n=20),and high-dose MP group(HMP,SI+40 mg/kg MP,n=20).A model of smoke inhalation-induced lung injury was established.The survival status of the rats in each group was monitored.Lung tissues were collected 24 hours after injury to determine the wet-to-dry(W/D)ratio of the lung tissues,arterial oxygen partial pressure(PaO2),and the expression levels of inflammatory cytokines TNF-α and IL-6.The degree of lung injury was evaluated using HE staining,and the mRNA and protein expression levels of AQP1 and AQP5 in the lung tissues were detected.Results Compared with control group,the survival rate of the rats in SI group was significantly decreased(P<0.05);compared with SI group,the survival rates of the rats in MMP and HMP groups were significantly increased(P<0.05).Compared with control group,the PaO2 of the Rats in SI group was significantly decreased(P<0.05),and the wet-to-dry(W/D)ratio and lung injury scores were significantly increased(P<0.05).Compared with SI group,the PaO2 of the rats in LMP,MMP,and HMP groups(P<0.05)was significantly increased(P<0.05),and the lung W/D ratio and injury scores in MMP and HMP groups were significantly decreased(P<0.05).ELISA results showed that compared with control group,the serum concentrations of TNF-α and IL-6 in SI group were significantly increased(P<0.05);compared with SI group,the concentrations of TNF-α and IL-6 in MMP and HMP groups were significantly decreased(P<0.05).HE staining revealed that the alveolar structure of the rats in SI group was severely damaged;compared with SI group,the damage to the alveolar structure in MMP and HMP groups was alleviated.Real-time PCR and Western blotting analysis results showed that compared with control group,the mRNA and protein expression levels of AQP1 and AQP5 in lung tissues in SI group were significantly decreased(P<0.05);however,compared with SI group,these levels in LMP,MMP,and HMP groups were significantly increased(P<0.05).Conclusions Smoke inhalation can induce acute lung injury in rats and down-regulate the expression levels of AQP1 and AQP5 in the lung tissues.Methylprednisolone can alleviate pulmonary edema and tissue damage in rats caused by smoke inhalation,and induce the up-regulation of the expression of AQP1 and AQP5.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

BACKGROUND: T cell dysfunction, which includes exhaustion, anergy, and senescence, is a distinct T cell differentiation state that occurs after antigen exposure. Although T cell dysfunction has been a cornerstone of cancer immunotherapy, its potential in transplant research, while not yet as extensively explored, is attracting growing interest. Interferon regulatory factor 4 (IRF4) has been shown to play a pivotal role in inducing T cell dysfunction. METHODS: A novel ultra-low-dose combination of Trametinib and Rapamycin, targeting IRF4 inhibition, was employed to investigate T cell proliferation, apoptosis, cytokine secretion, expression of T-cell dysfunction-associated molecules, effects of mitogen-activated protein kinase (MAPK) and mammalian target of rapamycin (mTOR) signaling pathways, and allograft survival in both in vitro and BALB/c to C57BL/6 mouse cardiac transplantation models. RESULTS: In vitro , blockade of IRF4 in T cells effectively inhibited T cell proliferation, increased apoptosis, and significantly upregulated the expression of programmed cell death protein 1 (PD-1), Helios, CD160, and cytotoxic T lymphocyte-associated antigen (CTLA-4), markers of T cell dysfunction. Furthermore, it suppressed the secretion of pro-inflammatory cytokines interferon (IFN)-γ and interleukin (IL)-17. Combining ultra-low-dose Trametinib (0.1 mg·kg -1 ·day -1 ) and Rapamycin (0.1 mg·kg -1 ·day -1 ) demonstrably extended graft survival, with 4 out of 5 mice exceeding 100 days post-transplantation. Moreover, analysis of grafts at day 7 confirmed sustained IFN regulatory factor 4 (IRF4) inhibition, enhanced PD-1 expression, and suppressed IFN-γ secretion, reinforcing the in vivo efficacy of this IRF4-targeting approach. The combination of Trametinib and Rapamycin synergistically inhibited the MAPK and mTOR signaling network, leading to a more pronounced suppression of IRF4 expression. CONCLUSIONS Targeting IRF4, a key regulator of T cell dysfunction, presents a promising avenue for inducing transplant immune tolerance. In this study, we demonstrate that a novel ultra-low-dose combination of Trametinib and Rapamycin synergistically suppresses the MAPK and mTOR signaling network, leading to profound IRF4 inhibition, promoting allograft acceptance, and offering a potential new therapeutic strategy for improved transplant outcomes. However, further research is necessary to elucidate the underlying pharmacological mechanisms and facilitate translation to clinical practice.
Animals ; Mice ; Mice, Inbred BALB C ; Mice, Inbred C57BL ; Interferon Regulatory Factors/metabolism* ; Heart Transplantation/methods* ; T-Lymphocytes/immunology* ; Sirolimus/therapeutic use* ; Pyridones/therapeutic use* ; Graft Survival/drug effects* ; Pyrimidinones/therapeutic use* ; Cell Proliferation/drug effects* ; Apoptosis/drug effects* ; Male ; Signal Transduction/drug effects*

In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(National Center for ADR Monitoring) from August 2021 to August 2022. According to the batch reporting rate, the samples of Reduning Injection were classified into those with potential risks and those being safe. No processing, random oversampling(ROS), random undersampling(RUS), and synthetic minority over-sampling technique(SMOTE) were then employed to balance the unbalanced data. After the samples were classified according to appropriate sampling methods, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), uninformative variables elimination(UVE), and genetic algorithm(GA) were respectively adopted to screen the features of spectral data. Then, support vector machine(SVM), logistic regression(LR), k-nearest neighbors(KNN), naive bayes(NB), random forest(RF), and artificial neural network(ANN) were adopted to establish the risk prediction models. The effects of the four feature extraction methods on the accuracy of the models were compared. The optimal method was selected, and bayesian optimization was performned to optimize the model parameters to improve the accuracy and robustness of model prediction. To explore the correlations between potential risks of clinical use and quality test data, TreeNet was employed to identify potential quality parameters affecting the clinical safety of Reduning Injection. The results showed that the models established with the SVM, LR, KNN, NB, RF, and ANN algorithms had the F1 scores of 0.85, 0.85, 0.86, 0.80, 0.88, and 0.85 and the accuracy of 88%, 88%, 88%, 85%, 91%, and 88%, respectively, and the prediction time was less than 5 s. The results indicated that the established models were accurate and efficient. Therefore, near infrared spectroscopy combined with machine learning algorithms can quickly predict the potential risks of clinical use of Reduning Injection in batches. Three key quality parameters that may affect clinical safety were identified by TreeNet, which provided a scientific basis for improving the safety standards of Reduning Injection.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/administration & dosage* ; Machine Learning ; Algorithms ; Humans ; Quality Control

Following the release of the Technical Requirements on Quality Control and Standard Establishment of Traditional Chinese Medicine Formula Granules by the National Medical Products Administration in 2021, Chinese Pharmacopoeia Commission has promulgated 296 national drug standards so far, and most provinces have started the work of establishing provincial standards as supplements. The promulgation of standards fostered high-quality development of the industry. Since the implementation of national and provincial standards for more than three years, enterprises have gained deep understanding and hands-on experiences on the characteristics, technical requirements, production process, and quality control of traditional Chinese medicine(TCM) formula granules. Meanwhile, challenges have emerged restricting the high-quality development of this industry, including how to formulate quality control strategies for medicinal materials and decoction pieces, how to reduce manufacturing costs, and how to improve the pass rate and product stability under high standards. Based on the work experiences from standard management and process research, this article analyzed the distribution of sources, processing methods, dry extract rate ranges, process requirements for volatile oil-containing decoction pieces, control measures of safety indices, characteristics and trends of setting characteristic chromatograms or fingerprints, characteristics and trends of setting content ranges, and main differences between national standards and provincial standards. On the one hand, this article aims to present main characteristics for deeply understanding different indicators in standards and provide basic ideas for establishing quality and process control systems. On the other hand, from the perspective of industrial practice, suggestions are put forward on the important aspects that need to be focused on in the quality and process control of TCM formula granules.
Drugs, Chinese Herbal/chemistry* ; Quality Control ; Medicine, Chinese Traditional/standards* ; China ; Drug Industry/standards*

The chemical constituents were systematically separated from the roots of Berberis polyantha by various chromatographic methods, including silica gel column chromatography, HP20 column chromatography, polyamide column chromatography, reversed-phase C_(18) column chromatography, and preparative high-performance liquid chromatography. The structures of the compounds were identified by physicochemical properties and spectroscopic techniques(1D NMR, 2D NMR, UV, MS, and CD). Four phenylpropanoids were isolated from the methanol extract of the roots of B. polyantha, and they were identified as(2R)-1-(4-hydroxy-3,5-dimethoxyphenyl)-1-propanone-O-β-D-glucopyranoside(1), methyl 4-hydroxy-3,5-dimethoxybenzoate(2),(+)-syringaresinol(3), and syringaresinol-4-O-β-D-glucopyranoside(4). Compound 1 was a new compound, and other compounds were isolated from this plant for the first time. The anti-inflammatory activity of these compounds was evaluated based on the release of nitric oxide(NO) in the culture of lipopolysaccharide(LPS)-induced RAW264.7 macrophages. At a concentration of 10 μmol·L~(-1), all the four compounds inhibited the LPS-induced release of NO in RAW264.7 cells, demonstrating potential anti-inflammatory properties.
Plant Roots/chemistry* ; Animals ; Mice ; Berberis/chemistry* ; RAW 264.7 Cells ; Macrophages/immunology* ; Drugs, Chinese Herbal/isolation & purification* ; Nitric Oxide/metabolism* ; Molecular Structure ; Anti-Inflammatory Agents/isolation & purification*

OBJECTIVE: To explore the accuracy of human-computer interaction software in identifying and locating type C1 distal radius fractures. METHODS: Based on relevant inclusion and exclusion criteria, 14 cases of type C1 distal radius fractures between September 2023 and March 2024 were retrospectively analyzed, comprising 3 males and 11 females(aged from 27 to 82 years). The data were assigned randomized identifiers. A senior orthopedic physician reviewed the films and measured the ulnar deviation angle, radial height, palmar inclination angle, intra-articular step, and intra-articular gap for each case on the hospital's imaging system. Based on the reduction standard for distal radius fractures, cases were divided into reduction group and non-reduction group. Then, the data were sequentially imported into a human-computer interaction intelligent software, where a junior orthopedic physician analyzed the same radiological parameters, categorized cases, and measured fracture details. The categorization results from the software were consistent with manual classifications (6 reduction cases and 8 non-reduction cases). For non-reduction cases, the software performed further analyses, including bone segmentation and fracture recognition, generating 8 diagnostic reports containing fracture recognition information. For the 6 reduction cases, the senior and junior orthopedic physicians independently analyzed the data on the hospital's imaging system and the AI software, respectively. Bone segments requiring reduction were identified, verified by two senior physicians, and measured for displacement and rotation along the X (inward and outward), Z (front and back), and Y (up and down) axes. The AI software generated comprehensive diagnostic reports for these cases, which included all measurements and fracture recognition details. RESULTS: Both the manual and AI software methods consistently categorized the 14 cases into 6 reduction and 8 non-reduction groups, with identical data distributions. A paired sample t-test revealed no statistically significant differences (P>0.05) between the manual and software-based measurements for ulnar deviation angle, radial ulnar bone height, palmar inclination angle, intra-articular step, and joint space. In fracture recognition, the AI software correctly identified 10 C-type fractures and 4 B-type fractures. For the 6 reduction cases, a total of 24 bone fragments were analyzed across both methods. After verification, it was found that the bone fragments identified by the two methods were consistent. A paired sample t-tests revealed that the identified bone fragments and measured displacement and rotation angles along the X, Y, and Z axes were consistent between the two methods. No statistically significant differences(P>0.05) were found between manual and software measurements for these parameters. CONCLUSION Human-computer interaction software employing AI technology demonstrated comparable accuracy to manual measurement in identifying and locating type C1 distal radius fractures on CT imaging.
Humans ; Male ; Female ; Radius Fractures/surgery* ; Middle Aged ; Adult ; Aged ; Aged, 80 and over ; Tomography, X-Ray Computed/methods* ; Retrospective Studies ; Software ; Wrist Fractures