ObjectiveTo investigate the effect and mechanism of transplantation of human umbilical cord mesenchymal stem cell （hUC-MSC） with overexpression of the Numb gene in the treatment of cholestatic liver fibrosis （CLF）. MethodsThe technique of lentiviral transfection was used to induce the overexpression of the Numb gene in hUC-MSC （hUC-MSC^Numb-OE）， and hUC-MSC transfected with empty vector （hUC-MSC^OE-EV） was used as negative control. Bile duct ligation （BDL） was performed to establish a rat model of CLF， and then the rats were randomly divided into BDL group， hUC-MSC group， hUC-MSC^OE-EV group， and hUC-MSC^Numb-OE group， while a sham-operation group was also established. The rats in the intervention groups were given a single splenic injection of the corresponding cells after BDL， and samples were collected at the end of week 4. Related indicators were measured， including serum biochemistry， liver histopathology， the content of hydroxyproline （Hyp） in the liver， hepatic stellate cell activation， ductular reaction， liver regeneration， and the expression levels of key molecules in the Numb-p53 signaling axis. A one-way analysis of variance was used for comparison of continuous data between multiple groups， and the least significant difference t-test was used for further comparison between two groups. ResultsCompared with the BDL group， the hUC-MSC group and the hUC-MSC^OE-EV group had significant reductions in the levels of serum biochemical parameters （aspartate aminotransferase， gamma-glutamyl transpeptidase， total bile acid， total bilirubin， and direct bilirubin）， liver fibrosis markers （the content of Hyp and the expression levels of alpha-smooth muscle actin， tumor necrosis factor-α， and transforming growth factor-beta 1）， and ductular reaction markers （the expression levels of CK7 and CK19） （all P <0.05）， and compared with the hUC-MSC^OE-EV group， the hUC-MSC^Numb-OE group had significantly greater improvements in the above indicators （all P <0.05）. In addition， compared with the hUC-MSC^OE-EV group， the hUC-MSC^Numb-OE group had significant improvements in the expression levels of liver regeneration-related markers （albumin and hepatocyte nuclear factor 4α） and the molecules associated with the Numb-p53 signaling axis （Numb， pNumb， Mdm2， and p53） （all P <0.05）. ConclusionOverexpression of the Numb gene can enhance the therapeutic effect of hUC-MSC on CLF， possibly by activating the Numb-PTB^L-p53-HNF4α axis， promoting the hepatic differentiation of hUC-MSCs and subsequently enhancing liver regeneration.

Objective:To investigate the application of time series models in forecasting pre-hospital emergency ambulance trips in Handan City and develop the LPro ensemble model for improved prediction accuracy to support emergency resource allocation.Methods:Pre-hospital emergency data from Handan Emergency Medical Command Center (2019-2023) were retrospectively analyzed. From 324 799 original records, 289 949 valid records were included after cleaning. The training set (2019-2022: 215 918 records) included 35 527 records in 2019, 52 015 in 2020, 61 836 in 2021, and 66 540 in 2022. The validation set (2023) contained 74 031 records. ARIMA, linear trend seasonal, exponential smoothing, and Prophet models were fitted to the training set. The LPro ensemble model was constructed using MAPE-based weighting (linear trend seasonal model: 0.38, Prophet: 0.62). Performance metrics included MAPE, RMSE, MAE, and R 2. Results:Data showed annual growth (compound annual growth rate 23.27%) and seasonal patterns (October peaks, February troughs). Ambulance dispatches increased annually with monthly cyclical patterns. For 2023 validation predictions: ARIMA (MAPE 8.76%, RMSE 619, MAE 491, R 2 0.4563), linear trend seasonal (MAPE 9.83%, RMSE 671, MAE 545, R 2 0.3608), Prophet (MAPE 8.43%, RMSE 562, MAE 503, R 2 0.5513), exponential smoothing (MAPE 8.08%, RMSE 643, MAE 410, R 2 0.4124). LPro model showed superior performance (MAPE 7.05%, RMSE 491, MAE 393, R 2 0.6570), with 16.37% lower MAPE, 12.63% lower RMSE, 21.87% lower MAE, and 19.17% higher R 2 versus Prophet. Conclusion:The LPro ensemble model substantially enhances prediction accuracy and reliability, offering scientific support for emergency resource optimization and dispatch scheduling in Handan City.

OBJECTIVES: To investigate the effect of avitinib for suppressing NLRP3 inflammasome activation and alleviating septic shock and explore the underlying mechanism. METHODS: Mouse bone marrow-derived macrophages (BMDM), human monocytic leukemia cell line THP-1, and peripheral blood mononuclear cells (PBMC) isolated from healthy volunteers were pre-treated with avitinib, followed by activation of the canonical NLRP3 inflammasome using agonists including nigericin, monosodium urate (MSU) crystals, or adenosine triphosphate (ATP). Non-canonical NLRP3 inflammasome activation was induced via intracellular transfection of lipopolysaccharide (LPS). Western blotting was used to detect the secretory protein markers of NLRP3 inflammasome activation and assess pyroptosis, and the levels of inflammatory cytokines in cell culture supernatant were determined with ELISA. In a mouse model of LPS-induced septic shock, the effect of avitinib treatment on the levels of inflammatory cytokines in serum and peritoneal lavage fluid were examined with ELISA, and survival curves of the mice were plotted using the Kaplan-Meier method. RESULTS: Avitinib significantly inhibited NLRP3 inflammasome activation in multiple cell types, and dose-dependently reduced IL-1β secretion and caspase-1 cleavage while suppressing GSDMD-mediated pyroptosis without obviously affecting IL-6 or TNF-α levels. In the mouse models of LPS-induced septic shock, avitinib significantly lowered IL-1β levels in serum and peritoneal fluid and extended survival time of the mice. CONCLUSIONS Avitinib suppresses NLRP3 inflammasome activation and alleviates septic shock in mice.
Animals ; Shock, Septic/metabolism* ; Mice ; NLR Family, Pyrin Domain-Containing 3 Protein ; Inflammasomes/drug effects* ; Humans ; Macrophages/metabolism* ; Interleukin-1beta/metabolism* ; Lipopolysaccharides

Lumbar disc (LD) herniation and aging are prevalent conditions that can result in substantial morbidity. This study aimed to clarify the mechanisms connecting the LD aging and herniation, particularly focusing on cellular senescence and molecular alterations in the nucleus pulposus (NP). We performed a detailed analysis of NP samples from a diverse cohort, including individuals of varying ages and those with diagnosed LD herniation. Our methodology combined histological assessments with single-nucleus RNA sequencing to identify phenotypic and molecular changes related to NP aging and herniation. We discovered that cellular senescence and a decrease in nucleus pulposus progenitor cells (NPPCs) are central to both processes. Additionally, we found an age-related increase in NFAT1 expression that promotes NPPC senescence and contributes to both aging and herniation of LD. This research offers fresh insights into LD aging and its associated pathologies, potentially guiding the development of new therapeutic strategies to target the root causes of LD herniation and aging.
Intervertebral Disc Displacement/metabolism* ; Humans ; Aging/pathology* ; Nucleus Pulposus/pathology* ; Male ; Female ; Transcriptome ; Middle Aged ; Lumbar Vertebrae/pathology* ; Adult ; Cellular Senescence ; Stem Cells/pathology* ; Aged ; Intervertebral Disc Degeneration/metabolism*

The Blow-Fill-Seal(BFS)technology is a highly automated aseptic manufacturing process that significantly reduces contamination risks by integrating container blowing,filling,and sealing operations.First,this article introduced the core technical features of BFS equipment and its advantages in aseptic production,followed by a comparative analysis of regulatory requirements for BFS technology across different jurisdictions.Finally,in light of pharmaceutical industry trends,it explored the future development prospects of BFS technology in intelligent manufacturing and high-barrier material applications,while examining its potential value in personalized medicine and specialized drug production.

Purpose To investigate the feasibility of a deep learning framework to automatically analyze echocardiographic color Doppler videos in detecting valvular regurgitation.Materials and Methods This study retrospectively collected echocardiographic images of 1 109 patients with valvular regurgitation in the Fourth Medical Center of PLA General Hospital,from June 2015 to September 2019 as the training and validation sets.A prospective continuous collection of 1 562 echocardiography images was used as the test set in the Fourth Medical Center of PLA General Hospital from May 13 to June 13,2023,including 378 cases of mitral regurgitation and 223 cases of aortic regurgitation.This study developed deep learning networks to establish view classification model and valvular regurgitation recognition model,including the efficiency of section classification of deep learning models.Results The deep learning view classification model in this study could automatically identify two views for diagnosing mitral regurgitation and aortic regurgitation.The recognition accuracy for the parasternal long axis color Doppler view and the apical four chamber mitral color Doppler view was 1.00 and 0.93,respectively.The sensitivity,specificity,accuracy and area under the curve of the deep learning model for diagnosing mitral regurgitation were 0.847,0.852,0.849 and 0.930,respectively.The sensitivity,specificity,accuracy and area under the curve of the deep learning model in diagnosing aortic regurgitation were 0.857,0.861,0.859 and 0.940,respectively.Conclusion Deep learning algorithms can automatically identify valvular regurgitation and have the potential to become a screening tool for valvular heart disease.

The cellular and molecular components of the tumor immune microenvironment (TIME) and their information exchange processes significantly influence the trends of anti-tumor immunity. In recent years, numerous studies have begun to evaluate TIME in the context of previous cancer treatment strategies. This review will systematically summarize the compositional characteristics of TIME and, based on this foundation, explore the impact of current cancer therapies on the remodeling of TIME, aiming to provide new insights for the development of innovative immune combination therapies that can convert TIME into an anti-tumor profile.
Tumor Microenvironment/immunology* ; Humans ; Neoplasms/therapy* ; Immunotherapy/methods* ; Animals

Objective To investigate the inhibitory effects of formononetin on sortase A(SrtA)of Staphylococcus epidermidis(S.epi-dermidis)and its biofilm formation.Methods Biofilm-producing S.epidermidis standard strain RP62A and biofilm-producing S.epider-midis clinical strains were collected.The minimal inhibitory concentration(MIC)of formononetin against S.epidermidis was investigated using the two-fold dilution method.The inhibitory effects of different concentrations of formononetin on the growth of S.epidermidis in vitro were studied by growth curve analysis using microplate reader.The cytotoxicity of formononetin was measured by cell culture.The biocompatibility of formononetin was studied by hemolysis assay.The inhibitory effect of formononetin on the activity of SrtA was deter-mined by fluorescence resonance energy transfer(FRET)assay.The effect of formononetin on the ability of S.epidermidis binding fi-bronectin was assessed by fibronectin binding assay.The effect of formononetin on the anchoring of serine-rich repeat proteins(SRRPs)in S.epidermidis was assessed by immunofluorescence staining.The effect of formononetin on the biofilm formation of S.epidermidis was measured by crystal violet staining.Results The MICs of formononetin against S.epidermidis were greater than 512 μg/mL.Compared with the control group,32 μg/mL of formononetin did not significantly affect the growth of S.epidermidis or reduce the viability of hu-man aortic endothelial cells.The hemolysis rate of human red blood cells was less than 5%.The inhibition rate of SrtA activity was ap-proximately 53.8%.The binding capacity of S.epidermidis to fibronectin was reduced by approximately 45.4%.Microscopic observation revealed a significant reduction in the anchoring of SRRP in S.epidermidis,and the formation of biofilm of S.epidermidis was inhibited by approximately 41.7%.Conclusion Formononetin inhibits the activity of SrtA in S.epidermidis,reduce its fibronectin-binding ca-pacity and biofilm formation,and thus represents a promising candidate for the prevention of S.epidermidis infections.

Purpose To investigate the value of intratumoral and different ranges of peritumoral radiomics features of the primary lesion of breast cancer based on ultrasound images in predicting axillary lymph node metastasis(ALNM),and to explore the best peritumoral range.Materials and Methods A total of 312 cases confirmed by pathology in breast cancer patients with preoperative ultrasound images from June 2022 to February 2024 in Binzhou Medical University Hospital were retrospectively enrolled,and were randomly divided into training set and testing set according to the 7∶3 proportion.The tumor border of the ultrasound images was manually delineated as the intratumoral region of interest,and the peritumoral region of interest was obtained by conformal automatically extended different range(1,2,3,4 and 5 mm).The radiomics features were screened.Based on the selected optimal radiomics features,random forest classifier was used to construct three types of radiomics models(intratumoral model,5 peritumoral models,and 5 intratumoral+peritumoral models).The performance and clinical practicability of the models was assessed the area under the curve(AUC)and decision curve analysis.Results The AUCs of the intratumoral+peritumoral radiomics models for predicting ALNM in the training set and test set were 0.807-0.873,0.728-0.780,respectively,which were superior to those of the single intratumoral radiomics models(0.822,0.758)and peritumoral radiomics models(0.722-0.768,0.650-0.710).The intratumoral+peritumoral 3 mm radiomics model showed the best predictive performance,with AUC of 0.873 in the training set and 0.780 in the test set,respectively,and the decision curve showed that the model had a good clinical net benefit.Conclusion The combined intratumoral and peritumoral radiomics features of the primary lesion of breast cancer based on ultrasound images can effectively predict ALNM,and 3 mm peritumoral may be the best peritumoral range for predicting ALNM.