Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

ObjectiveThis paper aims to investigate the traditional Chinese medicine syndrome types in patients with chronic hepatitis B （CHB） complicated by metabolic dysfunction-associated fatty liver disease （MAFLD） and explore the correlations between these syndrome types and clinical indicators， as well as ocular manifestation characteristics， thereby providing a reference for syndrome differentiation and treatment strategies in traditional Chinese medicine. MethodsGeneral data， information from the four diagnostic methods of traditional Chinese medicine， clinical indicators， and ocular manifestation data were collected from 506 patients with CHB complicated by MAFLD enrolled at the Public Health Clinical Center of Chengdu between June 2024 and December 2024. Cluster analysis， principal component analysis， and complex network models were employed to identify the distribution patterns of traditional Chinese medicine syndromes. Correlations between different syndrome types and clinical indicators， as well as ocular manifestation characteristics， were further analyzed. ResultsThe predominant syndromes identified in patients with CHB complicated by MAFLD were dampness and heat accumulation （51.58%）， liver depression with spleen deficiency （31.62%）， blood stasis obstructing collaterals （8.89%）， and Qi-Yin deficiency （7.91%）. No statistically significant differences were found among the four syndrome types in routine blood tests and liver function indicators. However， patients with the dampness and heat accumulation type exhibited significantly higher levels of total cholesterol （TC）， triglycerides （TG）， low-density lipoprotein cholesterol （LDL-C）， liver stiffness measurement （LSM）， controlled attenuation parameter （CAP）， and alpha-fetoprotein （AFP）， along with lower levels of high-density lipoprotein cholesterol （HDL-C）， compared with those with other syndrome types. Regarding ocular manifestations， the incidence of moon halo signs was significantly higher in patients with the blood stasis obstructing collaterals type than in those with other syndrome types. Additionally， the incidence in scleral zone 3 （corresponding to the large intestine） was higher in patients with the damp and heat accumulation type. ConclusionDampness and heat accumulation is the core syndrome type in patients with CHB complicated by MAFLD， commonly accompanied by spleen deficiency， liver depression， blood stasis， and Yin deficiency. A complex syndrome pattern characterized by a predominance of dampness and heat， along with a mixture of deficiency and excess， is formed. Different traditional Chinese medicine syndrome types are associated with distinct clinical indicators and ocular manifestation characteristics. Among them， patients with the dampness and heat accumulation type exhibit more pronounced metabolic disturbances and liver injury， whereas those with the blood stasis type show a higher incidence of moon halo signs. Abnormalities in scleral zone 3 are also more prevalent in patients with dampness and heat type.

Objective To construct prostate cancer(PCa)prediction models based on machine learning algorithms, so as to improve the accuracy of early diagnosis of PCa. Methods A retrospective analysis was performed on the clinical data of 504 patients who underwent prostate biopsy at our hospital during Jan. 2020 and Nov. 2024. Patients' age, body mass index(BMI), history of hypertension, diabetes and smoking, total prostate-specific antigen(tPSA), free prostate-specific antigen(fPSA), f/tPSA, prostate volume(PV), neutrophil count, lymphocyte count, neutrophil-to-lymphocyte ratio(NLR), Prostate Imaging Reporting and Data System(PI-RADS)score, digital rectal examination(DRE)results, and pathological findings were collected. The patients were divided into the training and testing sets at a ratio of 7:3. Ten early diagnosis prediction models of PCa were constructed using 10 supervised machine learning algorithms. Model performance was evaluated and validated using metrics including area under the receiver operating characteristic curve(AUC), accuracy, sensitivity, specificity, calibration curves, and decision curve analysis(DCA). SHAP analysis was used to interpret the models, and to clarify the importance of each feature and the basis for model decisions. Results All models showed good predictive value, with the gradient boosting machine(GBM)model performing the best(AUC=0.905, accuracy=84.1%, sensitivity=90.2%, specificity=80.0%). Calibration curves indicated good calibration and fitting of the GBM model, while DCA demonstrated favorable clinical net benefits. SHAP analysis identified the most significant features affecting PCa occurrence in descending order:tPSA, f/tPSA, PIRADS score, PV, age, and DRE. Conclusion The GBM model exhibits the optimal performance among the 10 models. The importance of features for predicting the occurrence of PCa, from the highest to the lowest, is as follows:tPSA, f/tPSA, PIRADS score, PV, age, and DRE.

Osteonecrosis of femoral head （ONFH） is a disease that causes osteocyte death due to interruption of blood supply of the femoral head， which may cause symptoms such as joint movement disorders， pain， and even femoral head collapse. Currently， the commonly used methods for treating ONFH in clinical practice are accompanied by problems such as long-term side effects， inaccurate efficacy， technical limitations， and complication risks. Traditional Chinese medicine （TCM） has shown unique advantages of holistic regulation， mild side effects， and symptom alleviation. A review of the related literature shows that Salviae Miltiorrhizae Radix et Rhizoma， as a representative Chinese herbal medicine for activating blood and resolving stasis， has the effects of activating blood， resolving stasis， dredging meridians， and relieving pain. Its active ingredients （such as salvianolic acid B， tanshinone Ⅱ_A， and tanshinone Ⅰ） interfere with bone metabolism balance， osteogenesis and differentiation， and improve bone microcirculation and bone microstructure. Salviae Miltiorrhizae Radix et Rhizoma is often combined with the herbal medicines with the effects of tonifying the liver and spleen or activing blood to form herb pairs （such as Salviae Miltiorrhizae Radix et Rhizoma-Angelicae Sinensis Radix， Salviae Miltiorrhizae Radix et Rhizoma-Chuanxiong Rhizoma， and Salviae Miltiorrhizae Radix et Rhizoma-Drynariae Rhizoma）， which enhances the efficacy through synergistic effects. In the application of TCM compound formulas， Bushen Huoxue prescription， Bushen Huoxue capsules， Gubi Tongxiao granules， and Shenggu Zaizao pills can regulate signaling pathways such as Wnt/β-catenin， Hedgehog， Notch， transforming growth factor（TGF）-β₁/Smads， and mitogen-activated protein kinase （MAPK） through multiple targets to significantly improve bone metabolism and hip joint function， playing an important role in preventing and treating ONFH. Through a review of available studies， this paper systematically explains the outstanding advantages of the active ingredients， herb pairs， and compound formulas of Salviae miltiorrhizae Radix et Rhizoma in the prevention and treatment of ONFH. The mechanisms may be related to factors such as promoting osteoblast generation and inhibiting osteoclast formation， increasing osteogenic differentiation， promoting angiogenesis， increasing bone density， inhibiting inflammatory response， and regulating signaling pathways. In the future， modern technology can be employed to optimize dosage forms， and high-quality clinical research should be conducted to further clarify its mechanism of action and promote the precise application of TCM. This review aims to provide more thinking directions for the application of Salviae miltiorrhizae Radix et Rhizoma in preventing and treating ONFH.

Epigallocatechin gallate (EGCG), the most abundant catechin in green tea, possesses various biomedical activities and has garnered significant attention because of its notable anticancer properties. This article reviews the research progress on the antitumor mechanisms of EGCG, focusing on its roles in inducing tumor cell apoptosis; inhibiting tumor cell proliferation, angiogenesis, invasion and metastasis; modulating the tumor microenvironment; and influencing epigenetic modifications. Given its natural origin, safety, and low cost, EGCG could be a preferred option for the development of new cancer therapeutic drugs or enhancing the efficacy of combination therapies. This work aims to provide a theoretical foundation for further research and development of EGCG and scientific evidence for its application in cancer prevention and treatment.

BACKGROUND: The protective effect of mesenchymal stem cells (MSCs) on cardiac ischemia-reperfusion (I/R) injury has been widely reported. Dental pulp-derived mesenchymal stem cells (DP-MSCs) have therapeutic effects on various diseases, including diabetes and cirrhosis. This study aimed to determine the therapeutic effects of DP-MSCs on I/R injury and elucidate the underlying mechanism. METHODS: Myocardial I/R injury model mice were treated with DP-MSCs or a miR-19a-3p mimic. The infarct volume, fibrotic area, pyroptosis, inflammation level, and cardiac function were measured. Cardiomyocytes exposed to hypoxia-reoxygenation were transfected with the miR-19a-3p mimic, miR-19a-3p inhibitor, or negative control. Pyroptosis and protein expression in the interferon regulatory factor 8/mitogen-activated protein kinase (IRF-8/MAPK) pathway were measured. RESULTS: DP-MSCs protected cardiac function in cardiac I/R-injured mice and inhibited cardiomyocyte pyroptosis. The upregulation of miR-19a-3p protected cardiac function, inhibited cardiomyocyte pyroptosis, and inhibited IRF-8/MAPK signaling in cardiac I/R-injured mice. DP-MSCs inhibited cardiomyocyte pyroptosis and the IRF-8/MAPK signaling by upregulating the miR-19a-3p levels in cardiomyocytes injured by I/R. CONCLUSION DP-MSCs protected cardiac function by inhibiting cardiomyocyte pyroptosis through miR-19a-3p under I/R conditions.
Animals ; MicroRNAs/metabolism* ; Pyroptosis/genetics* ; Mesenchymal Stem Cells/metabolism* ; Myocytes, Cardiac/cytology* ; Mice ; Male ; Mice, Inbred C57BL ; Dental Pulp/cytology* ; Myocardial Reperfusion Injury/therapy* ; MAP Kinase Signaling System/physiology*

The accurate prediction of drug absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties represents a crucial step in early drug development for reducing failure risk. Current deep learning approaches face challenges with data sparsity and information loss due to single-molecule representation limitations and isolated predictive tasks. This research proposes molecular properties prediction with parallel-view and collaborative learning (MolP-PC), a multi-view fusion and multi-task deep learning framework that integrates 1D molecular fingerprints (MFs), 2D molecular graphs, and 3D geometric representations, incorporating an attention-gated fusion mechanism and multi-task adaptive learning strategy for precise ADMET property predictions. Experimental results demonstrate that MolP-PC achieves optimal performance in 27 of 54 tasks, with its multi-task learning (MTL) mechanism significantly enhancing predictive performance on small-scale datasets and surpassing single-task models in 41 of 54 tasks. Additional ablation studies and interpretability analyses confirm the significance of multi-view fusion in capturing multi-dimensional molecular information and enhancing model generalization. A case study examining the anticancer compound Oroxylin A demonstrates MolP-PC's effective generalization in predicting key pharmacokinetic parameters such as half-life (T0.5) and clearance (CL), indicating its practical utility in drug modeling. However, the model exhibits a tendency to underestimate volume of distribution (VD), indicating potential for improvement in analyzing compounds with high tissue distribution. This study presents an efficient and interpretable approach for ADMET property prediction, establishing a novel framework for molecular optimization and risk assessment in drug development.
Deep Learning

Objective To investigate the relationship between peripheral blood receptor-interacting protein kinase 1(RIPK1),bone morphogenetic protein-7(BMP-7),glucose-regulated protein 78(GRP78),NOD-like receptor pyrin domain-containing protein 3(NLRP3)inflammasome and prognosis in children with severe Mycoplasma pneumoniae pneumonia(SMPP).Methods A total of 228 children with SMPP admitted to Guangyuan Maternal and Child Health Hospital from June 2020 to June 2024 were selected as SMPP group.Based on prognosis,they were divided into a poor prognosis group(48 cases)and a good prognosis group(180 cases).Additionally,228 healthy children who underwent physical examinations during the same period were selected as control group.Peripheral blood levels of RIPK1,BMP-7,GRP78,and NLRP3 inflammasome-relat-ed factors[NLRP3,cysteinyl aspartate specific proteinase 1(Caspase-1),and apoptosis-associated speck-like protein containing a caspase recruitment domain(ASC)]mRNA were detected and compared between two groups.Pearson method was used to analyze the correlation between peripheral blood RIPK1,BMP-7,GRP78,and the expression of NLRP3 inflammasome-related factors in children with SMPP.Multivariate Logistic re-gression analysis was performed to determine the influencing factors of poor prognosis in children with SMPP.Receiver operating characteristic(ROC)curve analysis was used to evaluate the predictive value of pe-ripheral blood RIPK1,BMP-7,and GRP78 for poor prognosis in children with SMPP.Results The levels of RIPK1,GRP78,NLRP3 mRNA,Caspase-1 mRNA,and ASC mRNA in the SMPP group were higher than those in the control group(P＜0.05),while the level of BMP-7 was lower than that in the control group(P＜0.05).In children with SMPP,peripheral blood RIPK1 and GRP78 were positively correlated with NLRP3 mRNA,caspase-1 mRNA,and ASC mRNA(P＜0.05),whereas BMP-7 was negatively correlated with NLRP3 mRNA,caspase-1 mRNA,and ASC mRNA(P＜0.05).The body temperature upon admission,C-reactive protein,procalcitonin,NLRP3 mRNA,Caspase-1 mRNA,ASC mRNA,peripheral blood RIPK1,and GRP78 levels in the poor prognosis group were all higher than those in the good prognosis group(P＜0.05),while BMP-7 level was lower than that in the good prognosis group(P＜0.05).High peripheral blood levels of RIPK1 and GRP78,along with low BMP-7 level,were identified as independent risk factors for poor prognosis in children with SMPP(P＜0.05).The area under the curve(AUC)of the single detection of RIPK1,BMP-7,and GRP78 for predicting the poor prognosis was 0.786,0.781,and 0.767,respectively,while the combined detection yielded an AUC of 0.904.Conclusion High peripheral blood levels of RIPK1 and GRP78 and low level of BMP-7 are closely associated with NLRP3 inflammasome activation and poor prognosis in children with SMPP.The combined detection of RIPK1,BMP-7,and GRP78 in peripheral blood has high predictive val-ue for the prognosis in children with SMPP.

Objective To assay the salivary ANG-2 level of oral lichen planus(OLP)patients,and analyze its correlation with in-flammatory activity of OLP.Methods Eighty-nine OLP patients were included,and divided into four subgroups as non-erosive asymp-tomatic(NEA),non-erosive symptomatic(NES),minor-erosive(MIE)and major-erosive(MAE)groups.Fifteen healthy adults were recruited as controls.Whole unstimulated saliva was collected from each participant,and the salivary ANG-2 level was measured by chemiluminescence immunoassays(CLIA)for analysis.Normal oral mucosal tissue,non-erosive and erosive OLP tissues were collected to detect and analyze the expression of ANG-2 positive blood vessels by immunohistochemistry(IHC).Results The base-lines of age and gender between OLP and control groups showed no significant difference.Compared to controls,the salivary ANG-2 levels of OLP group,non-erosive and erosive OLP subgroups were significantly higher(P＜0.05),in which erosive OLP group was higher than non-erosive OLP group(P=0.022);NES subgroup was slightly higher than NEA(P=0.048),and there was no statistical significance between MIA and MEA subgroups(P=0.067).Spearman correlation analysis showed a positive correlation between sali-vary ANG-2 level and inflammation activity in OLP patients(r=0.314,P=0.003).The expression of ANG-2 in non-erosive OLP mu-cosal tissues slightly increased than normal oral mucosal tissue(P＞0.05),but there was no significant difference.The expression of ANG-2 in erosive OLP mucosal tissues significantly increased than normal oral mucosal tissue(P＜0.001)and non-erosive OLP group(P＜0.001).Conclusion There is a certain correlation between sali-vary ANG-2 level and inflammatory activity of OLP,indicating that salivary ANG-2 level is probable to be one of the inflammatory activity indicators to monitor the state-variation of OLP as a clinical non-inva-sive method.

Objective To analyze the risk factors associated with the occurrence of rectal neuroendocrine tumors (RNETs) and construct a risk prediction model. Methods Clinical data of patients who underwent electronic colonoscopy were collected. The clinical information on patients with and without RNETs were compared, and potential risk factors for RNETs were identified. Binary logistic regression was performed to analyze the relevant risk factors and construct a risk prediction model. Results Among 164 patients, 66 were diagnosed with RNETs, and 98 who did not have such a condition were randomly selected. Univariate logistic regression analysis revealed that age, fatty liver, anxiety and depression, total cholesterol, triglyceride levels, and carcinoembryonic antigen (CEA) were significant factors influencing the occurrence of RNETs (P<0.05). Multivariate logistic regression analysis identified age (P=0.015), anxiety and depression (P=0.031), cholesterol level (P=0.009), fatty liver (P=0.001), and CEA (P<0.001) as independent risk factors for RNETs. The participants were randomly divided into training and test sets at a 7:3 ratio. The training set was used to construct a nomogram-based risk prediction model, and the testing set was used for internal validation. The area under the curve values for the training and testing sets were 0.843 and 0.772, respectively (P>0.05). These findings indicate a good discriminative performance. The calibration curves for the training and testing sets were in good agreement with the 45° standard line, which suggests that the predicted probabilities were consistent with the actual outcomes. Decision curve analysis showed that the model provided a high net benefit within a threshold range of 0.2 to 0.7 for clinical decision making. Conclusion Young age, fatty liver, high CEA levels, high cholesterol levels, and anxiety and depression are independent risk factors for RNETs. The nomogram model constructed based on these risk factors exhibits a strong capability to predict the occurrence of RNETs, and clinical intervention can be considered based on the predicted probability values.