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 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.

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.

Water-soluble silver nanoclusters(DHLA-AgNCs)with red fluorescence emission were synthesized using silver nitrate(AgNO3)as silver source,dihydrolipoic acid(DHLA)as ligand and sodium borohydride(NaBH4)as reducing agent by one-pot method.Based on the selective quenching of DHLA-AgNCs by tetracycline(TC),a rapid and selective fluorescence analysis method for detection of TC was constructed by monitoring the fluorescence intensity change at 650 nm.Under the optimal detection conditions,the fluorescence quenching efficiency of DHLA-AgNCs showed good linear relationship with concentration of TC within the range of 10.0-120.0 μmol/L,and the limit of detection(LOD)was 0.39 μmol/L.This method was successfully applied to detection of TC in milk samples,with spiked recoveries ranging from 99.5%to 102.5%,and relative standard deviations(RSDs)less than 5%.This method had the advantages of simplicity,rapidity,strong specificity and low cost,and thus provided a simple and feasible strategy for selective detection of TC.

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.

Objective: To investigate the mechanism of Yishen Tongluo Formula in ameliorating renal pyroptosis in diabetic nephropathy mice by regulating the toll-like receptor 4 (TLR4)/myeloid differentiation factor 88 (MyD88)/nuclear factor-κB (NF-κB) signaling pathway. Methods: Sixty C57BL/6 male mice were randomly divided into control (10 mice) and intervention groups (50 mice) using random number table method. The diabetes nephropathy model was established by intraperitoneally injecting streptozotocin(50 mg/kg). After modeling, the intervention group was further divided into model, semaglutide (40 μg/kg), and high-, medium-, and low-dose Yishen Tongluo Formula groups (15.6, 7.8, and 3.9 g/kg, respectively) using random number table method. The high-, medium-, and low-dose Yishen Tongluo Formula groups were administered corresponding doses of medication by gavage, the semaglutide group received a subcutaneous injection of semaglutide injection, and the control group and model groups were administered distilled water by gavage for 12 consecutive weeks. Random blood glucose levels of mice in each group were monitored, and the 24-h urinary protein content was measured using biochemical method every 4 weeks; after treatment, the serum creatinine and urea nitrogen levels were measured using biochemical method. The weight of the kidneys was measured, and the renal index was calculated. Hematoxylin and eosin, periodic acid-Schiff, periodic Schiff-methenamine, and Masson staining were used to observe the pathological changes in renal tissue. An enzyme-linked immunosorbent assay was used to detect urinary β2-microglobulin (β2-MG), neutrophil gelatinase-associated lipocalin (NGAL), and kidney injury molecule-1 (KIM-1) levels. Western blotting and real-time fluorescence PCR were used to detect the relative protein and mRNA expression levels of nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3), Caspase-1, gasdermin D (GSDMD), interleukin-1β (IL-1β), and interleukin-18 (IL-18) in renal tissue. Immunohistochemistry was used to detect the proportion of protein staining area of the TLR4, MyD88, and NF-κB in renal tissue. Results: Compared with the control group, the random blood glucose, 24-h urinary protein, serum creatinine, urea nitrogen, and renal index of the model group increased, and the urine β2-MG, NGAL, and KIM-1 levels increased. The relative protein and mRNA expression levels of NLRP3, Caspase-1, GSDMD, IL-1β, and IL-18 in renal tissue increased, and the proportion of TLR4, MyD88, and NF-κB protein positive staining areas increased (P<0.05). Pathological changes such as glomerular hypertrophy were observed in the renal tissue of the model group. Compared with the model group, the Yishen Tongluo Formula high-dose group showed a decrease in random blood glucose after 12 weeks of treatment (P<0.05). The Yishen Tongluo Formula high- and medium-dose groups showed a decrease in 24-h urinary protein, creatinine, urea nitrogen, and renal index, as well as decreased β2-MG, NGAL, and KIM-1 levels. NLRP3, Caspase-1, GSDMD, IL-1 β, and IL-18 relative protein and mRNA expression levels were also reduced, and the proportion of TLR4, MyD88, and NF-κB protein positive staining areas was reduced (P<0.05). Pathological damage to renal tissue was ameliorated. Conclusion Yishen Tongluo Formula may exert protective renal effects by inhibiting renal pyroptosis and alleviating tubular interstitial injury in diabetic nephropathy mice by regulating the TLR4/MyD88/NF-κB signaling pathway.

ObjectiveTo investigate the effect and mechanism of Yishen Tongluo prescription in protecting mice from oxidative stress injury in diabetic kidney disease （DKD） via the nuclear factor erythroid 2-related factor 2 （Nrf2）/heme oxygenase-1 （HO-1）/NAD（P）H quinone oxidoreductase 1 （NQO1） signaling pathway. MethodsSpecific pathogen-free （SPF） male C57BL/6 mice were assigned into a control group （n=10） and a modeling group （n=50）. The DKD model was established by intraperitoneal injection of streptozotocin. The mice in the modeling group were randomized into a model group， a semaglutide （40 μg·kg^-1） group， and high-， medium-， and low-dose （18.2， 9.1， 4.55 g·kg^-1， respectively） Yishen Tongluo prescription groups， with 10 mice in each group. The treatment lasted for 12 weeks. Blood glucose and 24-h urine protein levels were measured， and the kidney index （KI） was calculated. Serum levels of creatinine （SCr）， blood urea nitrogen （BUN）， alanine aminotransferase （ALT）， and aspartate aminotransferase （AST） were assessed. The pathological changes in the renal tissue were evaluated by hematoxylin-eosin， periodic acid-Schiff， periodic acid-silver methenamine， and Masson’s trichrome staining. Enzyme-linked immunosorbent assay kits were used to measure the levels of β2-microglobulin （β2-MG）， neutrophil gelatinase-associated lipocalin （NGAL）， kidney injury molecule-1 （KIM-1）， liver fatty acid-binding protein （L-FABP）， nitric oxide synthase （NOS）， glutathione （GSH）， total antioxidant capacity （T-AOC）， and 8-hydroxy-2'-deoxyguanosine （8-OHdG）. Immunohistochemical staining was performed to examine the expression of Kelch-like ECH-associated protein 1 （Keap1） and malondialdehyde （MDA）. Real-time fluorescence quantitative polymerase chain reaction (Real-time PCR） and Western blot were employed to determine the mRNA and protein levels， respectively， of factors in the Nrf2/HO-1/NQO1 signaling pathway. ResultsCompared with the control group， the DKD model group showed rises in blood glucose， 24-h urine protein， KI， SCr， BUN， and ALT levels， along with glomerular hypertrophy， renal tubular dilation， thickened basement membrane， mesangial expansion， and collagen deposition. Additionally， the model group showed elevated levels of β2-MG， NGAL， KIM-1， L-FABP， NOS， and 8-OHdG， lowered levels of GSH and T-AOC， up-regulated expression of MDA and Keap1， and down-regulated expression of Nrf2， HO-1， NQO1， and glutamate-cysteine ligase catalytic subunit （GCLC） （P<0.05）. Compared with the model group， the semaglutide group and the medium- and high-dose Yishen Tongluo prescription groups showed reductions in blood glucose， 24-h urine protein， KI， SCr， BUN， and ALT levels， along with alleviated pathological injuries in the renal tissue. In addition， the three groups showed lowered levels of β2-MG， NGAL， KIM-1， L-FABP， NOS， and 8-OHdG， elevated levels of GSH and T-AOC， down-regulated expression of MDA and Keap1， and up-regulated expression of Nrf2， HO-1， NQO1， and GCLC （P<0.05）. ConclusionYishen Tongluo prescription exerts renoprotective effects in the mouse model of DKD by modulating the Nrf2/HO-1/NQO1 signaling pathway， mitigating oxidative stress， and reducing renal tubular injuries.

Objective To establish an acute rejection model of cervical heart transplantation in mice and evaluate the survival and dynamic rejection process post-transplantation. Methods Mice were randomly divided into sham operation group (n=10), syngeneic transplantation group (n=21), and allogeneic transplantation group (n=65). Sham operation, syngeneic cervical heart transplantation, and allogeneic cervical heart transplantation were performed respectively. The survival of recipient mice and grafts, histopathological changes of graft tissues, subpopulations of splenic lymphocytes, and expression of inflammatory factors in serum and grafts were observed. Results The survival rate and graft survival rate of the sham operation group and syngeneic transplantation group were 100% at 7 days after surgery. In the allogeneic transplantation group, 5 cases failed and died on the first day after surgery. The survival rate at 7 days after surgery was 86%, and all surviving mice had grafts that stopped beating at 7 days after surgery. The allogeneic transplantation group showed significant rejection at 7 days after surgery, accompanied by tissue damage and CD8⁺ T cell infiltration. The proportion of CD8⁺ T cells in the spleen continued to rise post-operation, while the proportion of CD4⁺ T cells showed a downward trend. The expression of interferon-γ in serum and grafts peaked at 5 days after surgery, while the expression of tumor necrosis factor-α showed no statistical significance. Conclusions Acute rejection following heart transplantation in mice intensifies between 5 to 7 days after surgery, which may be a critical time window for immunological intervention.