Traditional Chinese medicine （TCM）， through its multi-target and systematic regulatory effects， has demonstrated unique advantages in the treatment of gastric precancerous lesions （GPL）. At present， TCM theoretical research on GPL is mainly reflected in three aspects， the integration of macroscopic syndrome differentiation， the inflammation-carcinoma transformation mechanism， as well as the systematization and scientization of theoretical inheritance from famous TCM practitioners. High-quality evidence-based research findings serve as the foundation for clinical practice guidelines on GPL， and TCM has gained international academic recognition in the field of GPL prevention and treatment. Research on TCM mechanisms has yielded a series of important outcomes in the aspects of signaling pathways， gene expression regulation， cellular epigenetics， histone modification， and intestinal microecology. It is proposed that future research on GPL should focus on four key directions， establishing multi-omics data， exploring targeted intervention strategies on key regulatory nodes， advancing the standardization process of integrated traditional Chinese and western medicine prevention and treatment technologies， and constructing stratified screening and intervention platforms. The in-depth integration of TCM microcosmic mechanism of action with its macroscopic syndrome differentiation and treatment system， coupled with interdisciplinary research， will provide valuable references for the clinical treatment and scientific research of GPL.

Objective: To explore the influencing factors of blood transfusion volume in obstetric patients based on the national health development strategy, and to provide evidence for clinical transfusion management and maternal and infant safety. Methods: A total of 1 203 obstetric patients who received blood transfusion in a tertiary hospital in Beijing from 2013 to 2023 were enrolled retrospectively. Seventeen indicators including age, body mass index (BMI), hemoglobin and prothrombin time were selected as research variables. Descriptive analysis was conducted firstly. Scatter plot matrix was used to analyze the correlation between continuous variables and transfusion volume, and box plots were used to analyze the relationship between categorical variables and transfusion volume. Linear regression, logistic regression and random forest models were established for empirical analysis, and ROC curves and AUC values were compared to evaluate model performance. Results: Descriptive analysis showed that the distribution of obstetric blood transfusion volume was right-skewed, and multiple indicators were significantly correlated with transfusion volume. Linear regression indicated that 9 variables such as age, BMI and hemoglobin had linear correlation with transfusion volume. Logistic regression confirmed that 7 variables including BMI and hemoglobin were statistically correlated with the probability of massive blood transfusion. Random forest model screened the core influencing factors, which were ranked by importance: hemoglobin, prothrombin time, hematocrit, BMI, activated partial thromboplastin time, platelet count and age. The AUC values of logistic regression and random forest were 0.78 and 0.81 respectively, and the latter had better predictive performance. Conclusion: Prenatal anemia, coagulation disorders, advanced age, obesity, gestational hypertension, placental abnormalities and organ damage can increase the risk of massive blood transfusion in obstetric patients. The random forest model has better analytical and predictive ability in this study. The results can provide reference for accurate blood transfusion and risk prediction in obstetrics.

Objective: To investigate the molecular mechanism of ABO blood type gene c. 899G>A leading to the occurrence of subtype A. Methods: Serological methods were used to identify ABO blood types. Genotyping was performed using polymerase chain reaction sequence specific (PCR-SSP) kits, and Sanger sequencing was used to analyze the ABO gene exons 1-7. PacBio third-generation sequencing was employed for ABO gene full-length haplotype analysis. AlphaFold3 was used to predict protein structure, and ChimeraX software was used to analyze the impact of amino acid changes caused by base mutations on protein structure. Results: The patient exhibited group O of forward typing and group A of reverse typing. Weak A. antigen was detected by absorption-elution test. Molecular biology detection revealed three mutation sites, c. 261delG, c. 297A>G, and c. 899G>A. Third-generation sequencing showed that one haplotype was recombinant ABO O.01.01 and the other haplotype was recombinant ABO B.01-O.01.01, with c. 297A>G and c. 899G>A located on this recombinant haplotype. Protein structure prediction indicated that c. 899G>A resulted in premature termination codons and translation interruption of ABO blood group genes, leading to a 55 amino acid deletion at the C-terminus. Conclusion: The c. 899G>A mutation in the ABO gene of the patient resulted in reduced A antigen expression and an A subtype phenotype.

Objective To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.

Objective To explore a deep learning network model suitable for bone age estimation using shoulder joint X-ray images in Chinese Han adolescents.Methods A retrospective collection of 1 286 shoulder joint X-ray images of Chinese Han adolescents aged 12.0 to<18.0 years(708 males and 578 females)was conducted.Using random sampling,approximately 80%of the samples(1 032 cases)were selected as the training and validation sets for model learning,selection and optimization,and the other 20%samples(254 cases)were used as the test set to evaluate the model's generalization ability.The original single-channel shoulder joint X-ray images and dual-channel inputs combining original images with segmentation labels(manually annotated shoulder joint regions multiplied pixel-by-pixel with original images,followed by segmentation via the U-Net++network to retain only key shoulder joint region information)were respectively input into four network models,namely VGG16,ResNet18,ResNet50 and DenseNet121 for bone age estimation.Additionally,manual bone age estimation was con-ducted on the test set data,and the results were compared with the four network models.The mean absolute error(MAE),root mean square error(RMSE),coefficient of determination(R2),and Pear-son correlation coefficient(PCC)were used as main evaluation indicators.Results In the test set,the bone age estimation results of the four models with dual-channel input of shoulder joint X-ray images outperformed those with single-channel input in all four evaluation indicators.Among them,DenseNet121 with dual-channel input achieved best results with MAE of 0.54 years,RMSE of 0.82 years,R2 of 0.76,and PCC(r)of 0.88.Manual estimation yielded an MAE of 0.82 years,ranking second only to dual-channel DenseNet121.Conclusion The DenseNet121 model with dual-channel input combined with original images and segmentation labels is superior to manual evaluation results,and can effectively estimate the bone age of Chinese Han adolescents.

Objective To establish a rapid analysis method for cyanide based on a ratiometric fluores-cent probe,providing a quantitative strategy for on-site visual and rapid detection of cyanide.Methods A dual-emission ratiometric fluorescent probe(AuNCs-FL)was constructed by using bovine serum al-bumin(BSA)-stabilized gold nanoclusters(AuNCs,fluorescence emission at 660 nm)as the responsive signal unit and fluorescein(FL,emission at 515 nm)as the internal reference.Results The etching effect of cyanide on AuNCs resulted in fluorescence quenching at 660 nm,while the fluorescence inten-sity of FL at 515 nm remained unchanged,enabling a rapid response analysis of cyanide shift from red to green fluorescence.The developed probe enabled rapid analysis of cyanide within 3 min,with a limit of detection(LOD)of 3.4 mg/L and a visual detection range of 10-100 mg/L.Conclusion The AuNCs-FL fluorescent probe is structurally simple,low-cost,and easy to operate,delivering rapid and accurate results.It also avoids the interference from sulfides encountered in commercial cyanide test kits,making it suitable for the on-site rapid detection of suspected powder samples in cyanide poisoning cases.

Gallbladder cancer(GBC)is a relatively rare malignant tumor with poor prognosis,which is usually diagnosed in the late stage due to the lack of obvious early symptoms and specific clinical manifestations.Surgery is the only possible cure for gallbladder cancer,but the choice of surgical approach and scope is still controversial.In recent years,the application of targeted therapy and immunotherapy in advanced gallbladder cancer has brought new hope to patients.This article reviews the epidemiologic features,risk factors,pathologic characteristics,and current diagnostic and therapeutic strategies of gallbladder cancer,and discusses several controversial topics,aiming to provide a reference for clinical management.

Myocardial infarction is a cardiovascular disease (CVD) with high morbidity and mortality, which can trigger a cascade of cardiac pathophysiological changes, including fibrosis, inflammation, ischemia-reperfusion injury (IRI), and ventricular remodeling, ultimately leading to heart failure (HF). While conventional pharmacological treatments and clinical reperfusion therapy may enhance short-term prognoses and emergency survival rates, both approaches have limitations and adverse effects. Natural products (NPs) are extensively utilized as therapeutics globally, with some demonstrating potentially favorable therapeutic effects in preclinical and clinical pharmacological studies, positioning them as potential alternatives to modern drugs. This review comprehensively elucidates the pathophysiological mechanisms during myocardial infarction and summarizes the mechanisms by which NPs exert cardiac beneficial effects. These include classical mechanisms such as inhibition of inflammation and oxidative stress, alleviation of cardiomyocyte death, attenuation of cardiac fibrosis, improvement of angiogenesis, and emerging mechanisms such as cardiac metabolic regulation and histone modification. Furthermore, the review emphasizes the modulation by NPs of novel targets or signaling pathways in classical mechanisms, including other forms of regulated cell death (RCD), endothelial-mesenchymal transition, non-coding ribonucleic acids (ncRNAs) cascade, and endothelial progenitor cell (EPC) function. Additionally, NPs influencing a particular mechanism are categorized based on their chemical structure, and their relevance is discussed. Finally, the current limitations and prospects of NPs therapy are considered, highlighting their potential for use in myocardial infarction management and identifying issues that require urgent attention.
Humans ; Myocardial Infarction/genetics* ; Biological Products/therapeutic use* ; Animals ; Oxidative Stress/drug effects* ; Signal Transduction/drug effects*

OBJECTIVE: To investigate the association between long-term glycemic control and cerebral infarction risk in patients with diabetes through a large-scale cohort study. METHODS: This prospective, community-based cohort study included 12,054 patients with diabetes. From 2006 to 2012, 38,272 fasting blood glucose (FBG) measurements were obtained from these participants. FBG trajectory patterns were generated using latent mixture modelling. Cox proportional hazards models were applied to assess the subsequent risk of cerebral infarction associated with different FBG trajectory patterns. RESULTS: At baseline, the mean age of the participants was 55.2 years. Four distinct FBG trajectories were identified based on FBG concentrations and their changes over the 6-year follow-up period. After a median follow-up of 6.9 years, 786 cerebral infarction events were recorded. Different trajectory patterns were associated with significantly varied outcome risks (Log-Rank P < 0.001). Compared with the low-stability group, Hazard Ratio ( HR) adjusted for potential confounders were 1.37 for the moderate-increasing group, 1.23 for the elevated-decreasing group, and 2.08 for the elevated-stable group. CONCLUSION Sustained high FBG levels were found to play a critical role in the development of ischemic stroke among patients with diabetes. Controlling FBG levels may reduce the risk of cerebral infarction.
Humans ; Cerebral Infarction/blood* ; Middle Aged ; Male ; Female ; Blood Glucose/analysis* ; Fasting/blood* ; Aged ; Prospective Studies ; Risk Factors ; Diabetes Mellitus/blood* ; Adult ; Proportional Hazards Models

Objective:To systematically analyze the definition, development, conceptual application, characteristic attributes, extension, and similar concepts of family avoidance of communication about cancer through the conceptual analysis method, so as to clarify the conceptual connotation of family avoidance of communication about cancer.Methods:Literature on family avoidance of communication about cancer was searched in WanFang Data, VIP, China National Knowledge Infrastructure, China Biomedical Database, CINAHL, Embase, PubMed, PsycINFO and so on. The search period was from database establishment to December 31, 2023. Walker and Avant's conceptual analysis method was used for analysis.Results:Through a compilation and analysis of relevant literature, the conceptual characteristics of family avoidance of communication about cancer were summarized, including bidirectional influence (both the cancer patient and family members tend to conceal their self-emotions and influence each other), information concealment (lack of communicative behaviors on both sides) and the desire to protection (aiming to hopefully protect each other) .Conclusions:The conceptual attributes of family avoidance of communication about cancer compiled can provide a basis for the proper understanding of related concepts within the subject area and provide conceptual support for the practice and research of family avoidance of communication about cancer.