Objective: To investigate the efficacy of magnesium-strontium co-doped hydroxyapatite mineralized collagen (MSHA/Col) in improving the bone repair microenvironment and enhancing bone regeneration capacity, providing a strategy to address the insufficient biomimetic composition and limited bioactivity of traditional hydroxyapatite mineralized collagen (HA/Col) scaffolds. Methods: A high-molecular-weight polyacrylic acid-stabilized amorphous calcium magnesium strontium phosphate precursor (HPAA/ACMSP) was prepared. Its morphology and elemental distribution were characterized by high-resolution transmission electron microscopy (TEM) and energy-dispersive spectroscopy. Recombinant collagen sponge blocks were immersed in the HPAA/ACMSP mineralization solution. Magnesium-strontium co-doped hydroxyapatite was induced to deposit within collagen fibers (experimental group: MSHA/Col; control group: HA/Col). The morphological characteristics of MSHA/Col were observed using scanning electron microscopy (SEM). Its crystal structure and chemical composition were analyzed by X-ray diffraction and Fourier transform infrared spectroscopy, respectively. The mineral phase content was evaluated by thermogravimetric analysis. The scaffold's porosity, ion release, and in vitro degradation performance were also determined. For cytological experiments, CCK-8 assay, live/dead cell staining, alkaline phosphatase staining, alizarin red S staining, RT-qPCR, and western blotting were used to evaluate the effects of the MSHA/Col scaffold on the proliferation, viability, early osteogenic differentiation activity, late mineralization capacity, and gene and protein expression levels of key osteogenic markers [runt-related transcription factor 2 (Runx2), collagen type Ⅰ (Col-Ⅰ), osteopontin (Opn), and osteocalcin (Ocn)] in mouse embryonic osteoblast precursor cells (MC3T3-E1). Results: HPAA/ACMSP appeared as amorphous spherical nanoparticles under TEM, with energy spectrum analysis showing uniform distribution of carbon, oxygen, calcium, phosphorus, magnesium, and strontium elements. SEM results of MSHA/Col indicated successful complete intrafibrillar mineralization. Elemental analysis showed the mass fractions of magnesium and strontium were 0.72% (matching the magnesium content in natural bone) and 2.89%, respectively. X-ray diffraction revealed characteristic peaks of hydroxyapatite crystals (25.86°, 31°-34°). Infrared spectroscopy results showed characteristic absorption peaks for both collagen and hydroxyapatite. Thermogravimetric analysis indicated a mineral phase content of 78.29% in the material. The scaffold porosity was 91.6% ± 1.1%, close to the level of natural bone tissue. Ion release curves demonstrated sustained release behavior for both magnesium and strontium ions. The in vitro degradation rate matched the ingrowth rate of new bone tissue. Cytological experiments showed that MSHA/Col significantly promoted MC3T3-E1 cell proliferation (130% increase in activity at 72 h, P < 0.001). MSHA/Col exhibited excellent efficacy in promoting osteogenic differentiation, significantly upregulating the expression of osteogenesis-related genes and proteins (Runx2, Col-Ⅰ, Opn, Ocn) (P < 0.01). Conclusion The MSHA/Col scaffold achieves dual biomimicry of natural bone in both composition and structure, and effectively promotes osteogenic differentiation at the genetic and protein levels, breaking through the functional limitations of pure hydroxyapatite mineralized collagen. This provides a new strategy for the development of functional bone repair materials

To evaluate the application value of the Peyton four-step teaching method in the standardized training of intestinal ultrasound and compare it with traditional teaching methods, so as to provide an optimized approach for clinical ultrasound training.

ObjectiveTo explore the role of the histone deacetylase Sirtuin-1 （SIRT1）/p53 signaling pathway in promoting apoptosis of non-small cell lung cancer cells （NSCLC） induced by the co-stimulatory molecule B7 homolog 3 （B7-H3）. MethodsThe GEPIA 2 platform was used for survival analysis of NSCLC patients based on B7⁃H3 gene expression levels. The Gene Enrichment Analysis （GSEA） method was used to analyze the enrichment characteristics of B7⁃H3 molecules in the gene set of cell apoptosis. In the non-small cell lung cancer A549 cell line， B7⁃H3 was knocked down， and the protein expression levels of SIRT1 and p53 were detected by Western blot. B7⁃H3 was overexpressed in A549 cells and the apoptosis rate was analyzed by flow cytometry after Annexin V/PI double staining. Overexpression of B7⁃H3 and knockdown of SIRT1 were performed in A549 cell line. The expression levels of p53 and apoptosis-related proteins B-cell lymphoma/leukemia-2 （Bcl-2） and Bcl-2-associated X protein （Bax） were detected respectively by Western blot. Cell apoptosis rate was analyzed by flow cytometry after Annexin V/PI double staining. ResultsThe overall survival of the B7-H3 high-expression group was significantly lower than that of the low-expression group （P<0.01）. B7-H3 was significantly enriched in the cell apoptosis signaling pathway and the p53 signaling pathway （P<0.05）. Compared with the control group， the expression of SIRT1 was significantly downregulated， and p53 was significantly upregulated in the B7⁃H3 knockdown group （both P<0.001）. Overexpression of B7-H3 significantly up-regulated SIRT1 protein expression （P<0.05）， down-regulated p53 expression （P<0.01）， and markedly increased the Bcl-2/Bax ratio of apoptosis-related proteins （P<0.001）. The results of Annexin V/PI double staining showed that the apoptosis rate of A549 cells with overexpressed B7⁃H3 decreased （the apoptosis rate of the control group was 26.72%±4.13%， while that of the B7⁃H3 overexpression group was 13.87%±0.82%； P<0.01）. In B7-H3-overexpressing cell lines， SIRT1 knockdown significantly reversed apoptosis （P<0.05）， up-regulated p53 protein expression （P<0.001）， and markedly reduced the Bcl-2/Bax ratio （P<0.001）. ConclusionB7-H3 molecule inhibits the apoptosis of non-small cell lung cancer cells via the SIRT1/p53 signaling pathway.

Background Ozone (O₃) is a major air pollutant. The existing monitoring system has uneven distribution of sites, insufficient coverage in underdeveloped areas, and low temporal resolution, making it difficult to obtain hourly data. This limits the dynamic identification of pollution and the formulation of prevention and control strategies. Objective To construct an hourly O₃ concentration estimation model based on ensemble machine learning, aiming to improve the accuracy of pollution exposure assessment and explore O₃ health impacts. Methods This study integrated land use regression modeling with modern machine learning techniques, employing random forest and XGBoost algorithms to construct base models, and stacking integration using non-negative least squares. The ensemble model was trained and validated across China using high-resolution, multi-source geographic data (e.g., meteorologicaldata, population density, land cover types, and aerosol optical thickness). It was tested in Taiyuan City, combined with a distributed lag non-linear model to analyze the association between O₃ and emergency admissions. Results The constructed ensemble model performed well in predicting O₃ concentration, with a higher coefficient of determination (R²) and a lower root-mean-square deviation (RMSE) compared to the single models. The R² improved from 0.90 to 0.92, and the RMSE decreased from 11.41 to 10.62, enhancing both prediction accuracy and generalization ability. In the application to Taiyuan City, the model successfully imputed the hourly-level data for the entire year. The distributed lag non-linear model analysis revealed that the relative risk (RR) values for the 6th to 8th days following O₃ exposure were 1.14 (95%CI: 1.01, 1.29), 1.16 (95%CI: 1.02, 1.31), and 1.14 (95%CI: 1.01, 1.29), respectively, which were significantly higher than 1, indicating a significant lagged association (lagged 6-8 d) between O₃ and the number of emergency room visits. Conclusion A high-precision, hourly-level O₃ concentration estimation model is successfully constructed by combining the land use regression model with an ensemble machine learning approach to provide a scientific basis for environmental policy formulation and public health intervention. The application of the model verifies its generalization ability and practical application value, which can provide a new technical framework for subsequent environmental health research.

OBJECTIVE To investigate the clinical characteristics of euglycemic diabetic ketoacidosis （euDKA） induced by empagliflozin， and provide references for safe medication. METHODS Case reports of euDKA induced by empagliflozin were retrieved and analyzed from PubMed， Web of Science， CNKI， and Wanfang Data. The Naranjo’s scale was adopted to assess the causal relationship between empagliflozin and euDKA. RESULTS A total of 29 patients were enrolled， including 16 males and 13 females，with a median age of 58 years. All patients were diagnosed with type 2 diabetes mellitus； 22 patients had at least one comorbidity. The median time to euDKA onset was 60 days after administration， and 7 cases occurred within 2 weeks of treatment. Perioperative periods，fasting，and low-carbohydrate or ketogenic diets were the main predisposing factors. Common presentations included nausea，vomiting， fatigue， tachypnea，and tachycardia. The causal relationship between empagliflozin and euDKA was assessed as “probable” in all cases. According to adverse reaction severity grading， 13 cases were grade 3 （severe） and 16 cases were grade 4 （life-threatening）. All patients discontinued empagliflozin and recovered after corresponding treatment. CONCLUSIONS euDKA is a serious adverse reaction to empagliflozin， which mostly occurs early in treatment. Perioperative periods， fasting， and ketogenic diets are prone to induce euDKA. Elderly patients and those with comorbidities are at higher risk. Risk assessment should be conducted before clinical administration； blood ketones and acid-base monitoring should be strengthened in the early medication period； withhold the drug before elective surgery， avoid prolonged fasting；upon diagnosis， discontinue empagliflozin and initiate intravenous insulin， provide fluid resuscitation promptly， and use other treatments to improve patient prognosis.

To summarize the clinical experience of Professor WANG Jie in treating palpitation using the method of tonifying the kidneys and invigorating blood. It is believed that kidney yang deficiency and heart vessel stasis are the key pathogenesis of palpitation， and it is advocated to treat palpitation by tonifying the kidney and invigorating the blood. Meanwhile，the methods of draining water， dissolving phlegm， and fortifying the spleen to supplement the blood should be applied. For palpitation with kidney yang deficiency and heart vessel stasis with upward water， the treatment could use self-prescribed Bushen Huoxue Lishui Formula （补肾活血利水方）； for palpitation with phlegm obstruction in blood vessel， the treatment could use self-prescribed Bushen Huoxue Huatan Formula （补肾活血化痰方）； for palpitation with spleen yang deficiency， the treatment could use self-prescribed Bushen Huoxue Jianpi Formula （补肾活血健脾方）.

This research aims to construct a stable epithelial cell senescence model for screening and e-valuation of senolytics.We explored the optimal conditions for doxorubicin-induced senescence of non-transformed epithelial cells MCF 10A,including the optimal induction concentration,the optimal inter-vention time,and the optimal senescence duration,and confirmed the feasibility of MCF 10A as an epi-thelial senescence model by multiple ways.The optimal condition for Doxorubicin-induced senescence of MCF 10A cells was treatment with 0.6 μmol/L Doxorubicin for 16 h to achieve the best senescence state on the 8th day.Under the optimal induction conditions,the positive rate of senescence-associated β-gal-actosidase(SA-β-gal)staining in the treated group reached 97％.At the same time,biochemical results of detecting the expression of mRNA,proteins,and immunofluorescence demonstrated that the expression levels of senescence-associated secretory phenotype(SASP),p16,p21 and p53 in the treated group were significantly higher than those in the control cells,and Lamin B1 was significantly decreased(P＜0.001),which were consistent with the specific characteristics of senescence.In summary,an epithelial senescence model was successfully induced in MCF 10A cells by Doxorubicin in this study,which will promote the screening of senolytics for senescent epithelial cells.

Objective:To develop and evaluate a deep learning-based automatic measurement model for panoramic ultrasound biomicroscopy (UBM) images.Methods:A diagnostic test study was conducted.Preoperative UBM examination results of 372 patients who underwent implantable collamer lens (ICL) implantation were collected at the Eye Center of Renmin Hospital of Wuhan University between February 2021 and March 2023.A total of 1 368 panoramic UBM images were obtained to establish an image database.The dataset was divided into a training set (760 images), a validation set (86 images) and an internal test set (522 images).An expert panel consisting of three ophthalmologists annotated the images.The UNet+ + network was used to automatically segment anterior segment tissues, such as the cornea, lens and iris.In addition, image processing techniques and geometric localization algorithms were developed to automatically identify the anatomical landmarks of pupil diameter (PD), anterior chamber depth (ACD), angle-to-angle distance (ATA) and sulcus-to-sulcus distance (STS) to complete the measurement of these parameters.Additionally, 480 panoramic UBM images of 135 patients (240 eyes) from Aier Eye Hospital of Wuhan University were used as an external test set to further evaluate the performance of the model in different centers.The consistency between the measurements from the model and expert panel, the Pentacam system was assessed.Finally, 150 images were randomly selected from the external test set for a human-machine comparison to further evaluate the model's performance.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Renmin Hospital of Wuhan University (No.WDRY-2022-K109) and Aier eye Hospital of Wuhan University (No.2023IRBKY120903).Written informed consent was obtained from each subject.Results:In the internal test dataset and external test dataset, with manual labeling as the reference standard, the model achieved a mean Dice coefficient of not less than 0.882.At least 95.65% of the anatomical landmark localization results had Euclidean distance differences within 250 μm.The intraclass correlation coefficients (ICCs) for the measurements of PD, ACD, angle-to-angle ATA, and STS were at least 0.958, with mean relative errors not exceeding 2.407%.With the Pentacam measurements as the reference standard, the ICCs for PD in the internal and external test sets were 0.540 and 0.466, respectively, while the ICCs for ACD were 0.946 and 0.908, respectively.In the human-machine comparison, the ICCs between the model's measurements and those of senior experts were all not lower than 0.969.Conclusions:The deep learning-based model can automatically measure anterior segment parameters from preoperative panoramic UBM images of patients undergoing ICL surgery.The model demonstrates a consistency comparable to that of senior experts, while providing higher efficiency.In terms of ACD measurement, the model shows good agreement between the measurements obtained from the model and Pentacam system.

Aim To investigate the role of RNF8 in the proliferation,invasion and migration of hepatocellular carcinoma and in the promotion of epithelial-mesenchy-mal transition(EMT);to clarify the regulatory mecha-nism of RNF8 on hepatocellular carcinoma cells.Methods Immunohistochemistry was used to detect the expression of RNF8 and RhoA in human hepatocel-lular carcinoma tissues and adjacent tissues;Western blot and RT-PCR were used to detect the expression levels of RNF8 and RhoA in human normal hepatocytes and hepatocellular carcinoma cells.RNF8 was overex-pressed in HepG2 cells,and siRNA interference was used to downregulate the expression of RNF8.The cell experimental groups were as follows:control group(Control,normal HepG2 cells),RNF8 overexpression group,RNF8 low expression group(siRNA RNF8),RNF8 overexpression+Rhosin(20 μmol·L-1,RhoA blocker)group.The cell proliferation ability was detected by CCK-8 method;the cell migration ability was detected by scratch test;the cell invasion ability was detected by Transwell test;finally,the expression levels of RNF8,RhoA,PCNA,CyclinD1,N-cadherin,vimentin,Slug,and E-cadherin proteins and mRNA were detected by Western blot and RT-PCR.Results The expression of RNF8 and RhoA in liver cancer tissues and liver cancer cells significantly increased;after RNF8 knockdown,the proliferation,migration,in-vasion and EMT of liver cancer cells were significantly inhibited,while overexpression of RNF8 significantly increased the proliferation,migration,invasion ability of liver cancer cells and promoted EMT.RhoA showed a positive correlation with knockdown and overexpression of RNF8.When RNF8 was overexpressed and RhoA blocker was given at the same time,the phenomenon of overexpression of RNF8 increasing the proliferation,mi-gration,invasion ability and promoting EMT of liver cancer cells was significantly reversed.Conclusions RNF8 can promote the proliferation,migration,invasion and EMT of liver cancer cells,and at the same time promote the expression of RhoA.RNF8 promotes the progression of hepatocellular carcinoma by regulating RhoA to promote EMT.

This review aims to summarize the progress of multi-omics technologies in the study of antibi-otic resistance in Cronobacter,with the goal of gaining a deep understanding of its resistance mechanisms and providing a scientific basis for the development of new treatment methods and prevention strategies.By integrating genomics,transcriptomics,proteomics,and metabolomics,the study analyzes gene varia-tions,expression patterns,protein function changes,and metabolic pathway adjustments in Cronobacter.This includes the use of whole-genome sequencing to reveal gene variations related to antibiotic resist-ance,RNA-seq technology to monitor changes in gene expression patterns,proteomics to study protein expression and function,and metabolomics to analyze dynamic changes in metabolites.The research has found that factors such as biofilm formation and outer membrane proteins significantly affect the antibiotic resistance of Cronobacter.In addition,new potential influencing factors have been identified,including the expression changes of multidrug efflux pump genes,which may play a key role in enhancing antibiotic efflux and reducing intracellular antibiotic concentrations.Multi-omics technologies provide a comprehen-sive and in-depth perspective for the study of antibiotic resistance in Cronobacter,revealing multiple fac-tors and potential mechanisms that affect resistance.Although some new influencing factors have been i-dentified,their specific molecular mechanisms still require further investigation.The application pros-pects of multi-omics technologies are broad,and they are expected to provide important support for the development of new treatment methods and prevention strategies.