Objective To understand the utilization of immunization program vaccines in Liaoning Province and evaluate the vaccine management mode, and to provide a scientific basis for optimizing immunization strategies. Methods The vaccine collection data and vaccine administration data of vaccination units (including obstetric clinics) in the province from 2021 to 2024 were collected, and the vaccine utilization rate of immunization program was calculated. SPSS 13.0 software was used for data analysis, and χ² test was used for comparison. A two-sided P value of <0.05 was considered statistically significant. Results (1) From 2021 to 2024, vaccination units and obstetric clinics received a total of 15 993 884 doses of immunization program vaccines, with a total utilization rate of 79.34%. The highest utilization rate was the single-dose vaccine MPSV-AC (94.02%), followed by JE-L (91.92%). The lowest rate of use was the 5-dose strength vaccine MPSV-A (48.12%), followed by the 4-dose strength vaccine DT (63.13%). (2) Comparing MPSV-A and DT in different years, the utilization rate of MPSV-A and DT was the highest in 2021, 59.53% and 67.71%, respectively. From 2021 to 2024, the utilization rate of MPSV-A had a decreasing trend year by year, with the lowest being 38.65% (2024), and the loss coefficient of MPSV-A in each year was higher than that of DT. (3) Comparison of vaccine utilization rates in immunization programs around 2020, the utilization rate of single-dose vaccines increased significantly compared with before, while the utilization rate of multi-dose vaccines decreased compared with before 2020. Conclusion After 2020, the vaccine utilization rate of the immunization program in Liaoning Province has increased significantly, and the optimized vaccine management strategies has achieved remarkable results. Multi-dose vaccines remain highly susceptible to formulation-related factors and vaccination density. It is recommended to formulate precise vaccination strategies to reduce the loss of multi-dose vaccines.

ObjectiveTo investigate the mechanism by which Jianpi Xiao'ai prescription （JPXAP） inhibits colorectal cancer progression by regulating the inducible nitric oxide synthase-arginase 1 （iNOS-ARG1） metabolic axis and inducing mitochondrial reactive oxygen species （mito-ROS）-mediated mitochondrial structural and functional impairment. MethodsAn arginine metabolism disorder model of human colorectal cancer HCT116 cells was established by combined treatment with recombinant human interferon-γ （IFN-γ， 10 μg·L^-1） and N（ω）-hydroxy-L-arginine （Nor-NOHA， 200 μmol·L^-1） for 24 h， followed by intervention with 5%， 10%， or 20% JPXAP-containing serum. Cell proliferation was assessed using cell counting kit-8 （CCK-8）， 5-ethynyl-2′-deoxyuridine （EdU） staining， and colony formation assays. Cell invasion and migration were evaluated using Transwell chamber and wound healing assays. Mitochondrial membrane potential （MMP） and ROS levels were assessed by JC-1 and MitoSOX staining， respectively. Mitochondrial ultrastructure was observed by transmission electron microscopy （TEM）. The expression of iNOS， ARG1， and mitochondrial dynamics-related proteins， including mitofusin 2 （MFN2） and dynamin-related protein 1 （DRP1）， was analyzed by Western blot and immunofluorescence. The levels of L-arginine， citrulline， and urea were determined by colorimetric methods and enzyme-linked immunosorbent assay （ELISA）. ResultsCompared with the blank group， the model group exhibited significantly upregulated iNOS expression， downregulated ARG1 expression， a decreased ARG1/iNOS ratio， reduced L-arginine and urea levels， and increased citrulline levels （P<0.05）. Meanwhile， mito-ROS accumulation was significantly increased， the JC-1 red/green fluorescence ratio was decreased， and mitochondria showed swelling and cristae disruption， indicating that metabolic disorder induced mitochondrial injury. Compared with the model group， all JPXAP-treated groups further decreased the ARG1/iNOS ratio， enhanced nitric oxide （NO） and reactive nitrogen species accumulation， further reduced L-arginine and urea levels， and increased citrulline levels （P<0.01）. EdU-positive rate， colony formation rate， wound healing rate， and Transwell invasion number all decreased significantly with increasing serum concentration （P<0.01）. Mito-ROS levels were further elevated， and the JC-1 red/green ratio further decreased. TEM revealed aggravated mitochondrial swelling and vacuolization. MFN2 expression was downregulated and DRP1 expression was upregulated （P<0.01），in a dose-dependent manner. ConclusionJPXAP further activates NO-mediated oxidative/nitrosative stress under arginine metabolism imbalance， inducing mito-ROS accumulation， MMP collapse， and mitochondrial dynamics imbalance， thereby inhibiting colorectal cancer cell proliferation and migration. These findings reveal an antitumor mechanism of JPXAP based on coordinated targeting of the "metabolism-mitochondria" axis.

Purpose: This study aimed to evaluate the safety and efficacy of gemcitabine and cisplatin (GP) regimen in combination with immune checkpoint inhibitor sintilimab as neoadjuvant therapy for muscle-invasive bladder cancer (MIBC) patients and the feasibility of the following selective bladder sparing surgery. Materials and Methods: Patients with histopathologically confirmed urothelial carcinoma without distant metastases (T2-4a, N ≤ 1, M0, American Joint Committee of Cancer 8th) and with adequate organ function will be enrolled. The therapeutic regimen was sintilimab 200 mg once on day 8, gemcitabine 1,000 mg/m2 and cisplatin 35 mg/m2 once on days 1 and 8, every 21 days for four cycles. The primary endpoint was pathologic complete response (pCR, pT0N0) rate. The secondary end points were ypT < 2 rate, R0 resection rate, event-free survival, and safety. Results: From May 4, 2020, to May 20, 2023, 55 patients were enrolled. Forty-six patients were evaluated for efficacy. Among the 42 patients who underwent surgery, 16 patients (38.0%) achieved pCR. Thirty-three patients (78.6%) achieved pT < 2. With a median follow-up of 15.7 months, the 1-year event-free survival was 91.3%. Notwithstanding the poor pathological baseline characteristic of a high T3-T4a proportion (39.1%), a promising bladder preservation (including 22 patients transurethral resection of bladder tumor, 5 patients partial cystectomy, and 4 surveillances) rate was achieved (67.4%). The most common grade ≥ 3 treatment-related adverse events was neutropenia (n=15, 27.3%), which was related to chemotherapy. There were no grade 3 immune-related adverse events. Conclusion Neoadjuvant GP plus sintilimab is a promising regimen for MIBC patients, with relatively high pT < 2 rate and triggering the emerging roles for the multi-disciplinary team decision-making for bladder sparing surgery.

ObjectiveTo investigate the intervention effect of Tengli Kangliu prescription （TKP） on the carcinogenesis of colorectal adenoma （CRA） induced by azoxymethane （AOM）/dextran sulphate sodium salt （DSS） in C57BL/6 mice and decipher the potential mechanism through regulating the signal transducer and activator of transcription 3 （STAT3） pathway to target M2-type macrophages. MethodsA total of 55 male C57BL/6 mice were randomized into a blank group （n=10）， a model group （n=15）， a celecoxib （0.02 g·kg^-1·d^-1） group （n=15）， a TKP （42.43 g·kg^-1·d^-1） group （n=15）. The mice in the model， TKP， and celecoxib groups were modeled for CRA lesions through the AOM/DSS three-cycle protocol. The intervention in each group began one week after free access to DSS and lasted for 12 weeks， and the blank group received 20 mL·kg^-1·d^-1 normal saline through gavage. Throughout the study period， changes in body mass and survival rate were recorded， alongside measurements of colorectal length and spleen mass. Histological changes of the colonic tissue were observed by HE staining. Immunohistochemical （IHC） staining was performed to detect the positive expression of CD68 and CD11c in the colorectal tissue. Western blot was employed to assess the protein levels of STAT3， phosphorylated （p）-STAT3， B-cell lymphoma 2 （Bcl-2）， and Bcl-2-associated X protein （Bax） in the intestinal tissue. Real-time quantitative PCR was employed to analyze the mRNA levels of arginase 1 （Arg1）， CD206， and vascular endothelial growth factor （VEGF）. Enzyme-linked Immunosorbent assay（ELISA） was employed to measure the serum concentrations of Th2-type cytokines interleukin （IL）-4， IL-6， and IL-13 in mice. ResultsCompared with the blank group， the model group exhibited symptoms including diarrhea， hematochezia， and body mass loss， accompanied by shortened colon length， mucosal damage， and multiple tumors. In addition， the model group showcased up-regulated protein levels of STAT3， p-STAT3， and Bcl-2， down-regulated protein level of Bax， increased positive expression of CD68 and CD11c， and up-regulated mRNA levels of Arg1， CD206， and VEGF in the colon tissue， together with elevated serum levels of IL-4， IL-13， and IL-6 （P<0.05）. Compared with the model group， the above-mentioned indicators were partially reversed in both TKP group and celecoxib group， with superior effects observed in the TKP group （P<0.05）. ConclusionTKP significantly improves the survival quality of the mouse model of AOM/DSS-induced CRA by reducing intestinal inflammation and decreasing colorectal tumor number and size. It may delay the progression of AOM/DSS-induced colorectal tumor-like lesions by inhibiting activation of the STAT3/p-STAT3 signaling pathway in the intestinal tissue， targeting regulation of M2-type macrophages， and improving the tumor microenvironment， thereby suppressing CRA carcinogenesis.

ObjectiveTo analyze the current status of traditional Chinese medicine （TCM） prediction model research for emerging acute infectious diseases， in order to provide reference for subsequent model construction and optimization. MethodsEight databases， including PubMed， Cochrane Library， and Embase， were systematically searched to comprehensively collect Chinese and English literature on TCM prediction models for emerging acute infectious diseases. The search period ranged from database inception to July 5， 2024. Reporting quality compliance was evaluated using the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis—Traditional Chinese Medicine （TRIPOD-TCM） guideline. Risk of bias and applicability were assessed using the Prediction Model Risk of Bias Assessment Tool （PROBAST）. ResultsA total of 21 studies were included， comprising 11 early warning model studies， 5 diagnostic model studies， 3 prognostic model studies， and 2 prescription prediction model studies， involving 84 models in total. The diseases involved were mainly viral infectious diseases such as coronavirus disease 2019 （COVID-19） and hepatitis B. The most frequently applied TCM theory was the "five movements and six climates" theory. The most commonly used modeling method was neural network-based approaches. The most frequently reported predictive factors were meteorological variables， including daily mean temperature， wind speed， precipitation， relative humidity， and vapor pressure. In terms of reporting quality， the included studies showed poor item-level compliance， with only 13 sub-items achieving compliance rates above 50%. Overall compliance ranged from 27% to 59% across studies. Although the included studies showed relatively good applicability， all were assessed as having a high risk of bias. The main sources of bias included inappropriate handling of missing data， absence of calibration methods， and unreasonable validation strategies， indicating deficiencies across multiple stages of model development. ConclusionCurrent research on TCM prediction models for emerging acute infectious diseases exhibits distinctive modeling characteristics. These models are based on traditional TCM theories such as the "five movements and six climates"， incorporate TCM-specific features as predictive variables， and use TCM syndromes as outcomes. However， they generally suffer from low reporting compliance and a high risk of bias. Future studies should systematically design model development and validation processes， adhere to TRIPOD-TCM reporting standards， and apply PROBAST or develop dedicated bias risk assessment tools for TCM prediction models to improve methodological quality and promote their translation into clinical practice.

The water-sediment interface is an important zone for the migration and transformation of chemical substances,but traditional sampling methods make in situ sampling challenging,thus it is difficult to capture information on environmental processes at the micro-scale.In this study,diffusive gradients in thin films(DGT)probe technique was used as in situ tool to detect 18 kinds of typical per-and polyfluoroalkyl substances(PFAS)in the water-sediment system,elucidating their vertical distribution characteristics and patterns.The results showed that different PFAS exhibited distinct variation patterns with depth in water and sediment.Short-chain PFAS exhibited greater mobility,while the migration of long-chain PFAS was restricted in sediment and pore water due to their strong hydrophobicity and adsorption capacity,resulting in relatively small concentration changes in the sediment column.The PFAS concentrations measured by DGT ranged from 11.2 μg/L to 1305 μg/L.For long-chain PFAS,the concentrations measured by DGT were higher than those obtained from direct measurement of water and pore water,while the opposite results were obtained for short-chain PFAS.The DGT results indicated that although long-chain PFAS exhibited strong adsorption to sediment particles,the adsorbed PFAS were still bioavailable.DGT probe technique,with its advantages of in situ sampling and high spatial resolution,provides deep insights into the complex environmental processes occurring at the microscale in the water-sediment systems.DGT offers important technical support and scientific evidence for assessing the adsorption-desorption behavior,bioavailability,and ecological risks of these emerging pollutants in aquatic environment.

Objective:To investigate the the differential expression of EIF5A2 in intrahepatic cholangiocarcinoma cell lines RBE,HCCC9810,and HUCCT1,and its effects on HCCC9810 cell migration and invasion,epithelial mesenchymal transition,and PI3K/AKT signaling pathway.Methods:The differential expression of EIF5A2 in RBE,HCCC9810,and HUCCT1 cell lines was detected using WB method.The HCCC9810 cell line,with the highest expression of EIF5A2,was selected for this experiment.The expression of EIF5A2 in HCCC9810 cell line was silenced by transient transfection of small interfering RNA.The best silencing effect of small interfering RNA was screened by WB.Scratch assay and Tran-swell migration invasion assay were used to detect the effect of silencing EIF5A2 on the migration and invasion ability of HCCC9810 cells.WB was used to detect the effect of silencing EIF5A2 on PI3K/AKT signaling pathway and epithelial mesenchymal transition in HCCC9810 cells.Results:The WB results showed that EIF5A2 had the highest expression in the HCCC9810 cell line,and siRNA1 had the best silencing effect on EIF5A2 in the HCCC9810 cell line.Scratch assay and Transwell migration invasion assay results showed that silencing EIF5A2 in the HCCC9810 cell line resulted in a decrease in cell invasion and metastasis ability(P＜0.05).At the same time,the expression of p-PI3K and p-AKT in the PI3K/AKT signaling pathway was significantly decreased(P＜0.05),while the epithelial cell marker E-cadherin expression increased(P＜0.05)and the stromal cell marker N-cadherin expression decreased(P＜0.05).Conclusion:EIF5A2 may promote epi-thelial mesenchymal transition and enhance the migration and invasion ability of intrahepatic cholangiocarcinoma cells through the PI3K/AKT signaling pathway.

Objectives:This study aims to evaluate the causal relationship between plasma proteins and myocardial infarction(MI)using two-sample bidirectional Mendelian randomization(MR)analysis,identify key biomarkers,and validate their expression.Methods:The study utilized publicly available genome-wide association study(GWAS)data of 4 907 plasma proteins as the exposure factor,with single nucleotide polymorphisms(SNPs)as instrumental variables,and four MI datasets as outcomes.Two-sample MR analysis was performed using the inverse variance weighted(IVW)method,complemented by simple model,weighted model,weighted median estimator(WME),and MR-Egger regression methods to assess the causal relationship between exposure factors and outcomes.Venn diagrams and word clouds were used to screen proteins associated with MI as candidate biomarkers.Reverse MR analysis was conducted to evaluate reverse causality.Sensitivity analysis was performed to assess the robustness of the results.Immunohistochemistry(IHC)was used to validate the expression of proteasome activator subunit 1(PSME1)and vacuolar protein sorting 29(VPS29)in the aorta of mice,and enzyme-linked immunosorbent assay(ELISA)was used to verify the expression of PSME1 and VPS29 in plasma from patients with acute myocardial infarction(AMI).Results:The two-sample MR analysis indicated that PSME1 was significantly negatively associated with myocardial infarction in all four datasets,with OR(95%CI)of 0.684(0.557-0.839),0.990(0.987-0.993),0.579(0.448-0.748),and 0.993(0.990-0.996),respectively,with all P<0.001.Similarly,VPS29 also showed a significant negative association with MI in all four datasets,with OR(95%CI)of 0.902(0.862-0.945),0.998(0.997-0.999),0.866(0.808-0.929),and 0.998(0.997-0.999),respectively,with all P<0.001.Reverse MR analysis did not detect reverse causality,and sensitivity analysis confirmed the robustness of the results.IHC results showed significantly reduced expression of PSME1 and VPS29 in the aortas of AMI mice with an atherosclerotic background compared to control mice(both P<0.05).ELISA results indicated significantly lower plasma levels of PSME1 and VPS29 in AMI patients compared to healthy controls(both P<0.05).Conclusions:Higher levels of PSME1 and VPS29 are negatively associated with the risk of MI,suggesting that PSME1 and VPS29 may serve as protective biomarkers for cardiovascular diseases.

A sandglass ladder residual network(SLRN)is proposed for multi-label chest X-ray classification,thereby improving the accuracy of clinical diagnosis.SLRN consists of 3 key modules:(1)a sandglass convolutional module to simultaneously extract inter-channel and spatial information;(2)a ladder self attention block to achieve different window divisions through shift operations,expand the receptive field,and realize multi-scale feature extraction and fusion;(3)class specific residual attention in the multi-label classification stage to capture the correlation between different labels and the importance of features for accomplishing more accurate classification by adjusting the weights of different features.The proposed model is validated using the IU X-Ray dataset collected by Indiana University and the publicly available Chest X-Ray14 dataset collected by the National Institutes of Health in the United States;and the results demonstrate that SLRN which combines the advantages of convolutional neural network and vision transformer enables the capture of local features and global correlations in images,better handles long-distance dependencies,and assists doctors in clinical diagnosis.

Delirium is a common cause and complication of hospitalization in the elderly and is associated with higher risk of future dementia and progression of existing dementia, of which 70% is Alzheimer's disease (AD). AD and delirium, which are known to be aggravated by one another, represent significant societal challenges, especially in light of the absence of effective treatments. The intricate biological mechanisms have led to numerous clinical trial setbacks and likely contribute to the limited efficacy of existing therapeutics. Artificial intelligence (AI) presents a promising avenue for overcoming these hurdles by deploying algorithms to uncover hidden patterns across diverse data types. This review explores the pivotal role of AI in revolutionizing drug discovery for AD and delirium from target identification to the development of small molecule and protein-based therapies. Recent advances in deep learning, particularly in accurate protein structure prediction, are facilitating novel approaches to drug design and expediting the discovery pipeline for biological and small molecule therapeutics. This review concludes with an appraisal of current achievements and limitations, and touches on prospects for the use of AI in advancing drug discovery in AD and delirium, emphasizing its transformative potential in addressing these two and possibly other neurodegenerative conditions.