Objective To systematically analyze the literature characteristics of Journal of Organ Transplantation since its inception. Methods Using the China National Knowledge Infrastructure (CNKI) academic journal full-text database as the data source, all articles published in the Journal of Organ Transplantation from January 2010 to August 2025 were retrieved. After excluding non-academic papers, a total of 1 568 research papers were included. R language 4.3.0, Bibliometrix package 3.2.1, and Citespace software were used to analyze the number of publications, publishing institutions, authors, keywords and other aspects. Results The number of publications in Journal of Organ Transplantation increased from an average of 82 articles per year in the early years after its inception to 113 articles per year in recent years, a growth of 37.8%. The geographical distribution of publishing institutions covers 32 provinces, cities and autonomous regions nationwide, mainly concentrated in the South China, East China and North China regions, and has now basically covered the central and western regions in recent years. The author collaboration network includes 45 authors distributed across 7 major collaboration clusters, forming a stable multi-level national research system centered on key university-affiliated hospitals. The high-frequency keywords are dominated by "liver transplantation" (425 times) and "kidney transplantation" (396 times). The theme evolution shows a clear three-stage characteristic: initially focusing on clinical technology application, deepening to immune mechanism exploration in the middle stage, and recently (since 2022) focusing on cutting-edge research areas such as xenotransplantation. Conclusions Journal of Organ Transplantation has witnessed the rapid development of China's organ transplantation cause, fully reflecting the research status and trends in China's organ transplantation field, and has provided an important platform for the future development and international cooperation in China's organ transplantation field.

Objective To explore the epidemiological characteristics of gouty arthritis in Northwest China from 2023 to 2025, and to formulate preventive intervention measures. Methods By retrospectively analyzing the case data of medical institutions in Northwest China from January 2023 to June 2025 (a total of 8 139 cases), the incidence trend and population distribution characteristics of gouty arthritis in this area were analyzed. Multivariate logistic regression analysis was performed to identify risk factors. Results From 2023 to 2025, the prevalence rate of gouty arthritis in adult residents in Northwest China was 3.74% (304/8 139). Among the sites affected by gouty arthritis, the metatarsophalangeal joint accounted for the highest proportion (P<0.05). From the perspective of age distribution, the prevalence rate was the highest in 40-59 years old group (5.90%), followed by 66-80 years old group (4.21%) and >80 years old group (2.75%). The incidence rate in 40-65 years old group was higher than that in the other age groups (P<0.05). High blood uric acid and creatinine, alcohol drinking, obesity, high purine diet, concurrent chronic kidney disease and metabolic syndrome were risk factors affecting gouty arthritis in Northwest China (P<0.05). Conclusion High blood uric acid level, high creatinine level, alcohol drinking, obesity, high purine diet, concurrent chronic kidney disease and metabolic syndrome are risk factors influencing gouty arthritis in Northwest China. Based on the above factors, this study proposes comprehensive prevention strategies from the individual, community and public health levels to provide a scientific basis for reducing the incidence rate of gouty arthritis.

ObjectiveTo investigate the mechanism by which Tianxiang pills （TXP） alleviates myocardial cell pyroptosis in the rat model of myocardial ischemia/reperfusion （I/R） injury through modulating the reactive oxygen species （ROS）/cysteinyl aspartate-specific proteinase-1 （Caspase-1）/gasdermin D （GSDMD） signaling pathway. MethodsA total of 54 SPF-grade adult male Sprague-Dawley rats were randomized into six groups （n=9）： sham （thoracotomy only without ligation）， I/R （left anterior descending coronary artery ligation for 30 min followed by reperfusion）， NAC （positive control， N-acetylcysteine， 150 mg·kg^-1， by gavage）， low-dose Tianxiang pills （TXP-L， 2.5 g·kg^-1， by gavage）］， medium-dose Tianxiang pills （TXP-M， 5 g·kg^-1， by gavage）， and high-dose Tianxiang pills （TXP-H， 10 g·kg^-1， by gavage）. The fluorescent probe method was employed to measure the ROS level. Biochemical assay kits were employed to determine the Caspase-1 activity， superoxide dismutase （SOD） activity， malondialdehyde （MDA） content， and glutathione peroxidase （GSH-Px） activity. Myocardial infarct size was assessed by 2，3，5-triphenyltetrazolium chloride （TTC） staining. Western blot analysis was performed to evaluate the expression levels of proteins in the ROS/Caspase-1/GSDMD pathway， including GSDMD， cleaved Caspase-1/Caspase-1 ratio， the N-terminal domain of GSDMD （GSDMD-N）， and the p22-phox subunit of the reduced nicotinamide adenine dinucleotide phosphate （NADPH） oxidase complex. Enzyme-linked immunosorbent assay （ELISA） was utilized to determine the concentration of interleukin-1β （IL-1β）. Transmission electron microscopy （TEM） was employed to observe mitochondrial structure and to score the degree of mitochondrial swelling. ResultsCompared with the Sham group， the I/R group exhibited elevated the levels of ROS， Caspase-1 activity， GSDMD expression， IL-1β concentration， MDA content， infarct area， mitochondrial swelling score， cleaved Caspase-1/Caspase-1， GSDMD-N， and p22phox and decreased activities of SOD and GSH-Px （P<0.05）. Compared with the I/R group， NAC and different doses of TXP significantly reduced the ROS level， Caspase-1 activity， GSDMD expression， IL-1β concentration， MDA content， infarct area， and mitochondrial swelling score. Moreover， they downregulated the expression of cleaved Caspase-1/Caspase-1， GSDMD-N， and p22phox and increased the activities of SOD and GSH-Px （P<0.05）. Furthermore， TXP exerted effects on ROS， MDA， SOD， GSH-Px， Caspase-1 activity， GSDMD expression， IL-1β concentration， cleaved Caspase-1/Caspase-1， GSDMD-N， p22phox， infarct area， and mitochondrial swelling score in a dose-dependent manner （P<0.05）. ConclusionTianxiang pills alleviates myocardial I/R injury by mitigating oxidative stress and cell pyroptosis through the inhibition of the ROS/Caspase-1/GSDMD signaling pathway.

Chronic hepatitis B virus （HBV） infection is a major cause of hepatocellular carcinoma （HCC）， with a population-attributable fraction of 57.1% for HCC globally and 76.1% for HCC in China. Identifying the early molecular mechanisms of HBV-driven hepatocarcinogenesis can facilitate precise HCC prevention. Persistent HBV replication， HBV mutation， HBV integration， and the synergistic interplay among them are the main mechanisms of HBV-driven hepatocarcinogenesis. HBV replication activates and sustains a chronic hepatic inflammatory microenvironment， providing conditions for accumulation of viral mutations； under the conditions of chronic inflammation， inflammatory factors cause the imbalance between apolipoprotein B messenger RNA editing enzyme catalytic polypeptide-like 3B and uracil-DNA glycosylase， which promotes HBV mutations and human genomic mutations and enhances the carcinogenic effect of HBV mutations， and the inflammatory microenvironment can promote dedifferentiation of mutated cells and acquisition of stemness； HBV genome integration can cause “gate-keeper” mutations including telomerase reverse transcriptase （TERT） promoter mutation， thereby triggering chromosomal instability and epigenetic reprogramming. The three events of HBV replication， mutation， and integration work synergistically under the evolutionary principle of “variation-selection-adaptation” and jointly drive the development and progression of HCC. The high-risk HBV mutation profile， circulating HBV integration fragments， and the TERT promoter mutations can be used to guide precision HCC prevention via antiviral prophylaxis and assist in early screening and monitoring of postoperative recurrence， which provides a scientific basis for refining stratified prevention and control strategies against HCC.

Objective To investigate the imaging characteristics of patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy （CADASIL）carrying cysteine-altering versus non-cysteine-altering NOTCH3 mutations. Methods A retrospective analysis was performed for 19 patients with CADASIL who attended Department of Neurology，The Affiliated Hospital of Guizhou Medical University， among whom there were 16 patients with cysteine-altering mutations and 3 with non-cysteine-altering mutations， and PubMed database was searched to obtain 192 cases （158 patients with cysteine-altering mutations and 34 with non-cysteine-altering mutations）. The impact of these two types of mutations on lesion distribution in the temporal pole and external capsule was analyzed. Results The cysteine-altering mutation group had a significantly higher risk of temporal pole lesions compared with the non-cysteine-altering mutation group （OR=2.99，95%CI 1.37‒6.51，P=0.006）， and there was no significant difference in external capsule lesions between the two groups （OR=2.31，95%CI 0.75‒6.48，P=0.12）. External capsule lesions were associated with age （OR=1.04，95%CI 1.01‒1.07， P=0.02）.Sex showed no significant influence on lesion distribution（OR=1.72，95%CI 0.67‒4.67，P=0.27；temporal pole：OR=0.54，95%CI 0.27‒1.05， P=0.07）. Conclusion Cysteine-altering NOTCH3 mutations are an independent risk factor for temporal pole lesions，while external capsule lesions are closely associated with age. This suggests that temporal pole lesions might be a specific imaging marker for cysteine-altering mutations， whereas external capsule lesions can reflect age-related disease progression.

Objective To explore the relationship between intestinal flora imbalance and pulmonary function in patients with chronic obstructive pulmonary disease (COPD), and to analyze the related influencing factors. Methods A total of 310 patients with COPD who were admitted to Air Force Military Medical University Tangdu Hospital from June 2022 to December 2024 were retrospectively analyzed. Based on intestinal flora status, the enrolled patients were classified into imbalance group (n=83) and non-imbalance group (n=227). Logistic regression analysis was conducted to analyze the independent related factors of intestinal flora imbalance in COPD patients. Based on the above factors, a prediction model was constructed, and ROC curve analysis model was applied to analyze the predictive value of the model on intestinal flora imbalance. Results Logistic regression analysis revealed that age, IL-6, albumin, pulmonary function, long-term bed rest and long-term use of antibiotics were related to intestinal flora imbalance in COPD patients (all P<0.05). ROC results of the Logistic prediction model showed that the area under the curve, sensitivity, specificity and 95%CI were 0.961, 0.880, 0.996 and 0.932-0.989 respectively. Conclusion The intestinal flora imbalance in patients with COPD is closely related to lung function, age, inflammatory status, nutritional indicators, activity ability and antibiotic use.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

AIM To explore the effects of Dahuang Lingxian Recipe on Th1/Th2 cell immune imbalance in a rat model of cholestatic liver fibrosis(CLF).METHODS 20 SD rats were randomly divided into the normal group,the model group,the ursodeoxycholic acid group(0.063 g/kg)and the Dahuang Lingxian Recipe group(4.8 g/kg),with 5 rats in each group.Except for those of the normal group,the rats of all other groups had open surgery of common bile duct ligation,followed by the gavage of corresponding drug two days later,and the procurement of the samples after gavage in the third week.The rats had their degree of liver fibrosis observed by HE and Masson stainings;their levels of serum total bile acid(TBA),alkaline phosphatase(AKP),γ-glutamyltransferase(γ-GT),alanine aminotransferase(ALT),aspartate aminotransferase(AST)and total bilirubin(TBil)measured by the kit;their hepatic percentage of TGF-β1,p-Smad2 and p-Smad3 positive cells detected by immunofluorescence and immunohistochemical staining;their.hepatic expressions of TGF-β1,Smad4,NF-κB p65,Collagen Ⅰ and Collagen Ⅲ protein and mRNA detected by Western blot and RT-qPCR;their levels of helper T cell 1(Th1)and helper T cell 2(Th2)in peripheral blood detected by flow cytometry,and their ratio of Th1/Th2 calculated as well.RESULTS Compared with the model group,the groups intervened with either ursodeoxycholic acid or Dahuang Lingxian Recipe displayed well-ordered liver cells,hepatic lobules and hepatic cords;a small amount of fatty degeneration;significantly reduced connective hyperplasia of hepatic fibers;significantly narrowed fibrous cords;a small amount of blue fibrous septa;greatly improved pathological injuries including inflammatory infiltration of central vein and portal area;decreased levels of serum TBA,TBil,AKP,γ-GT,ALT and AST(P＜0.05);decreased hepatic expressions of TGF-β1,p-Smad2 and p-Smad3(P＜0.05);decreased hepatic expressions of TGF-β1,Smad4,NF-κB p65,Collagen Ⅰ and Collagen Ⅲ protein and mRNA(P＜0.05);and increased counts of Th1 cells in peripheral blood,decreased counts of Th2 cells,resultsing increased Th1/Th2 ratio(P＜0.05).And an even better effect was observed in the Dahuang Lingxian Recipe group.CONCLUSION Dahuang Lingxian Recipe can reduce or reverse CLF by inhibiting hepatic stellate cell activation through maintaining Th1/Th2 cell immune balance via the NF-κB/TGF-β1 signaling pathway.

Objective To construct 5 machine-learning models and compare their performance in predicting the associations between pre-pregnancy socio-psycho-behavioral exposures of both spouses and preconception outcomes.Methods Based on Chongqing Preconception Reproductive Health and Birth Outcome Cohort of volunteers recruited from Chongqing Health Center for Women and Children during January 2019 and March 2022,5 447 couples were recruited and surveyed through interviewer-interview for the demographic and social-psychological-behavioral data of both spouses(221 variables).According to the inclusion and exclusion criteria,4 097 couples were finally included,and randomly assigned into a training set(n=2 867 spouses)and a validation set(n=1 230 spouses)at a ratio of 7∶3.Feature analysis and collinear screening were applied to select the potential exposure factors.In consideration of difficulty to carry out semen parameters analysis in primary healthcare institutions,feature Set 1 including sperm parameters and feature Set 2 excluding semen parameters were constructed by including or excluding sperm quality simultaneously in the training set and the validation set.Five algorithms,that is,Logistic Regression,Naive Bayes,Random Forest,Gradient Boosting Machine,and Support Vector Machine,were used to construct preconception outcome prediction models,and the parameters of each model were optimized using random search combined with grid search.The predictive performance of each model was compared using precision,recall,F1 score,area under the receiver operating characteristic curve(AUC),and calibration curve.The optimal model was then selected by comparing the changes in the predictive ability of the questionnaire data for fertility outcomes with or without semen parameters.Results There were 24 variables screened out in feature Set 1,and 16 variables in feature Set 2.In feature Set 1,the gradient boosting machine performed better,with a relatively higher AUC value(0.651)and better F1 score(0.61).The logistic regression model performed stably(AUC value=0.647)and was suitable as the reference model.The random forest(AUC value=0.641),Naive Bayes(AUC value=0.641),and support vector machine(AUC value=0.634)performed second-best.By utilizing the gradient boosting machine,comparable results were found between the predictions from feature sets with or without semen parameters,as in feature Set 1,the AUC value of its validation set was 0.651(95%CI:0.629～0.681),the prediction accuracy was 0.63,the recall rate was 0.65,and the average precision value F1 was 0.61;and in feature Set 2,the AUC value of its validation set was 0.649(95%CI:0.624～0.663),and both the calibration curves were close to the ideal curve.The prediction results indicated that in feature Set 1,the features highly negatively correlated with preconception outcomes were female age,male age,and no pregnancy within 1 year without contraception,while the features highly positively correlated with preconception outcomes were female pregnancy history,total sperm vitality,and use of contraceptive measures before enrollment.Conclusion Among the 5 machine-learning algorithms performed in this cohort data,the gradient boosting machine shows slightly better performance.There are 24 factors being associated with preconception outcomes in both spouses,and the performance of the simplified model excluding semen parameters is not significantly declined.It is feasible to use machine-learning methods to predict human preconception outcomes through social-psychological-behavioral questionnaires.

Near infrared spectroscopy(NIRS)analysis technology has become an important process analysis tool in industrial and agricultural production,and has been widely used for qualitative and quantitative analysis in the fields of tobacco,agriculture,and pharmaceuticals.To address issues such as poor generalization ability and low prediction accuracy in NIRS modeling,a two-dimensional convolutional neural network(2DCNN)quantitative analysis model based on competitive adaptive reweighted sampling(CARS)and Gramian angular difference field(GADF)(CARS-GADF-2DCNN)was proposed.CARS-GADF-2DCNN used the CARS method to select an optimal wavelength set from the full spectrum,then employed GADF to encode the selection results into two-dimensional images,and finally used 2DCNN for prediction analysis.The 2DCNN model consisted of convolutional layers,parallel convolution modules,flattening layer,and fully connected layers.Simulation experiments were conducted on three public near-infrared(NIR)spectral datasets encompassing soil,tablet,and grain datasets to evaluate the CARS-GADF-2DCNN model.The results demonstrated that,compared to the one-dimensional convolutional neural network(1DCNN),the GADF-2DCNN model achieved 16.74％,23.40％,and 7.13％improvement in prediction accuracy for the soil,tablet,and grain datasets,respectively.Compared to GADF-2DCNN,VCPA-GADF-2DCNN,and IRIV-GADF-2DCNN models,the CARS-GADF-2DCNN model further improved prediction accuracy.For the soil dataset,prediction accuracy improved by 39.00％,30.78％and 4.13％;for the tablet dataset,the improvements were 9.52％,6.94％and 2.56％;for the grain dataset,the improvements were 20.57％,9.85％and 15.66％.In conclusion,CARS-GADF-2DCNN effectively selected the optimal wavelength subset from near infrared spectra,and revealed the latent features between different wavelengths.CARS-GADF-2DCNN addresses the issues of high complexity in prediction models and low prediction accuracy in near infrared spectral modeling,and could be effectively applied to near infrared spectral prediction analysis of different substances.