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.

Loss of protein homeostasis is a hallmark of cellular senescence, and ribosome pausing plays a crucial role in the collapse of proteostasis. However, our understanding of ribosome pausing in senescent cells remains limited. In this study, we utilized ribosome profiling and G-quadruplex RNA immunoprecipitation sequencing techniques to explore the impact of RNA G-quadruplex (rG4) on the translation efficiency in senescent cells. Our results revealed a reduction in the translation efficiency of rG4-rich genes in senescent cells and demonstrated that rG4 structures within coding sequence can impede translation both in vivo and in vitro. Moreover, we observed a significant increase in the abundance of rG4 structures in senescent cells, and the stabilization of the rG4 structures further exacerbated cellular senescence. Mechanistically, the RNA helicase DHX9 functions as a key regulator of rG4 abundance, and its reduced expression in senescent cells contributing to increased ribosome pausing. Additionally, we also observed an increased abundance of rG4, an imbalance in protein homeostasis, and reduced DHX9 expression in aged mice. In summary, our findings reveal a novel biological role for rG4 and DHX9 in the regulation of translation and proteostasis, which may have implications for delaying cellular senescence and the aging process.
G-Quadruplexes ; Cellular Senescence ; Ribosomes/genetics* ; Humans ; Animals ; Mice ; DEAD-box RNA Helicases/genetics* ; Protein Biosynthesis ; RNA/chemistry* ; Neoplasm Proteins

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

Objective To evaluate the predictive ability and clinical application value of artificial intelligence (AI) systems in the benign and malignant differentiation and pathological type of pulmonary nodules, and to summarize clinical application experience. Methods A retrospective analysis was conducted on the clinical data of patients with pulmonary nodules admitted to the Department of Thoracic Surgery, Second Hospital of Lanzhou University, from February 2016 to February 2025. Firstly, pulmonary nodules were divided into benign and non-benign groups, and the discriminative abilities of AI systems and clinicians were compared. Subsequently, lung nodules reported as precursor glandular lesions (PGL), microinvasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) in postoperative pathological results were analyzed, comparing the efficacy of AI systems and clinicians in predicting the pathological type of pulmonary nodules. Results In the analysis of benign/non-benign pulmonary nodules, clinical data from a total of 638 patients with pulmonary nodules were included, of which there were 257 males (10 patients and 1 patient of double and triple primary lesions, respectively) and 381 females (18 patients and 1 patient of double and triple primary lesions, respectively), with a median age of 55.0 (47.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis of the two groups of variables showed that, except for nodule location, the differences in the remaining variables were statistically significant (P<0.05). Multivariate logistic regression analysis showed that age, nodule type (subsolid pulmonary nodule), average density, spicule sign, and vascular convergence sign were independent influencing factors for non-benign pulmonary nodules, among which age, nodule type (subsolid pulmonary nodule), spicule sign, and vascular convergence sign were positively correlated with non-benign pulmonary nodules, while average density was negatively correlated with the occurrence of non-benign pulmonary nodules. The area under the receiver operating characteristic curve (AUC) of the malignancy risk value given by the AI system in predicting non-benign pulmonary nodules was 0.811, slightly lower than the 0.898 predicted by clinicians. In the PGL/MIA/IAC analysis, clinical data from a total of 411 patients with pulmonary nodules were included, of which there were 149 males (8 patients of double primary lesions) and 262 females (17 patients of double primary lesions), with a median age of 56.0 (50.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis results showed that, except for gender, nodule location, and vascular convergence sign, the differences in the remaining variables among the three groups of PGL, MIA, and IAC patients were statistically significant (P<0.05). Multinomial multivariate logistic regression analysis showed that the differences between the parameters in the PGL group and the MIA group were not statistically significant (P>0.05), and the maximum diameter and average density of the nodules were statistically different between the PGL and IAC groups (P<0.05), and were positively correlated with the occurrence of IAC as independent risk factors. The average AUC value, accuracy, recall rate, and F1 score of the AI system in predicting lung nodule pathological type were 0.807, 74.3%, 73.2%, and 68.5%, respectively, all better than the clinical physicians’ prediction of lung nodule pathological type indicators (0.782, 70.9%, 66.2%, and 63.7% respectively). The AUC value of the AI system in predicting IAC was 0.853, and the sensitivity, specificity, and optimal cutoff value were 0.643, 0.943, and 50.0%, respectively. Conclusion This AI system has demonstrated high clinical value in predicting the benign and malignant nature and pathological type of lung nodules, especially in predicting lung nodule pathological type, its ability has surpassed that of clinical physicians. With the optimization of algorithms and the adequate integration of multimodal data, it can better assist clinical physicians in formulating individualized diagnostic and treatment plans for patients with lung nodules.

Based on the traditional Chinese medicine(TCM) theory of "kidney-brain interaction", a two-sample Mendelian randomization(MR) analysis was conducted to investigate the causal effects of chronic kidney disease(CKD) on Alzheimer's disease(AD) and analyze the potential mechanisms of kidney-tonifying and essence-replenishing TCM to improve AD. From the perspective that CKD is closely related to the core pathogenesis of AD, namely "kidney deficiency, essence loss, and marrow reduction", genome-wide association study(GWAS) data was used, with the inverse variance weighting(IVW) method as the main approach to reveal the causal association between CKD and AD. Sensitivity analysis was conducted to evaluate the robustness of the results. To further investigate the causal effects of CKD on AD, two different AD datasets were used as outcomes, and the urinary albumin-to-creatinine ratio(UACR) data was used as the exposure for a supplementary analysis. On this basis, the modern scientific mechanism of the kidney-tonifying and essence-replenishing method for improving AD was further explored. The IVW analysis show that CKD(ieu-b-2: OR=1.084, 95%CI[1.011, 1.163], P=0.024; ieu-b-5067: OR=1.001, 95%CI[1.000, 1.001], P=0.002) and UACR(ieu-b-2: OR=1.247, 95%CI[1.021, 1.522], P=0.031; ieu-b-5067: OR=1.001, 95%CI[1.000, 1.003], P=0.015) both have significant causal effects on AD in different datasets, with CKD increasing the risk of AD. The sensitivity analysis further confirmed the reliability of the results. Genetic studies have shown that CKD has a significant causal effect on AD, suggesting that controlling CKD is an important intervention measure for preventing and treating AD. Therefore, further research on CKD's role in AD is crucial in clinical practice. The research enriches the theoretical implication of "kidney-brain interaction", deepens the understanding of AD' etiology, and provides further insights and directions for the prevention and treatment of AD with TCM, specifically from a kidney-based perspective.
Humans ; Alzheimer Disease/genetics* ; Renal Insufficiency, Chronic/genetics* ; Kidney/metabolism* ; Brain/physiopathology* ; Genome-Wide Association Study ; Medicine, Chinese Traditional ; Mendelian Randomization Analysis

BACKGROUND: Lung cancer is one of the most common malignant tumors worldwide and a major cause of cancer-related deaths. Early-stage lung cancer is often manifested as pulmonary nodules, and accurate assessment of the malignancy risk is crucial for prolonging survival and avoiding overtreatment. This study aims to construct a model based on image feature parameters automatically extracted by artificial intelligence (AI) to evaluate its effectiveness in predicting the malignancy of part-solid nodule (PSN). METHODS: This retrospective study analyzed 229 PSN from 222 patients who underwent pulmonary nodule resection at Lanzhou University Second Hospital between October 2020 and February 2025. According to pathological results, 45 cases of benign lesions and precursor glandular lesion were categorized into the non-malignant group, and 184 cases of pulmonary malignancies were categorized into the malignant group. All patients underwent preoperative chest computed tomography (CT), and AI software was used to extract imaging feature parameters. Univariate analysis was used to screen significant variables; variance inflation factor (VIF) was calculated to exclude highly collinear variables, and LASSO regression was further applied to identify key features. Multivariate Logistic regression was used to determine independent risk factors. Based on the selected variables, five models were constructed: Logistic regression, random forest, XGBoost, LightGBM, and support vector machine (SVM). Receiver operating characteristic (ROC) curves were used to assess the performance of the models. RESULTS: The independent risk factors for the malignancy of PSN include roughness (ngtdm), dependence variance (gldm), and short run low gray-level emphasis (glrlm). Logistic regression achieved area under the curves ( AUCs) of 0.86 and 0.89 in the training and testing sets, respectively, showing good performance. XGBoost had AUCs of 0.78 and 0.77, respectively, demonstrating relatively balanced performance, but with lower accuracy. SVM showed an AUC of 0.93 in the training set, which decreased to 0.80 in the testing set, indicating overfitting. LightGBM performed excellently in the training set with an AUC of 0.94, but its performance declined in the testing set, with an AUC of 0.88. In contrast, random forest demonstrated stable performance in both the training and testing sets, with AUCs of 0.89 and 0.91, respectively, exhibiting high stability and excellent generalizability. CONCLUSIONS The random forest model constructed based on independent risk factors demonstrated the best performance in predicting the malignancy of PSN and could provide effective auxiliary predictions for clinicians, supporting individualized treatment decisions.
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Humans ; Male ; Female ; Lung Neoplasms/pathology* ; Middle Aged ; Retrospective Studies ; Artificial Intelligence ; Aged ; Tomography, X-Ray Computed ; Adult ; Solitary Pulmonary Nodule/diagnostic imaging* ; ROC Curve

Objective To explore the effects and potential mechanism of electroacupuncture at acute phase on cognitive dysfunction at later stage in rats with middle cerebral artery occlusion(MCAO).Methods Totally 39 SD rats were randomly divided into sham-operation group,model group and electroacupuncture group,with 13 rats in each group.MCAO model was established by Zea Longa thread embolism method in model group and electroacupuncture group.The sham-operation group only separated blood vessels.Electroacupuncture group was treated with electroacupuncture at"Baihui"and"Shenting"acupoints at 5 min and 6 h after model establishment respectively,for 30 min.The body mass,modified neuropathy severity scale(mNSS),and percentage of stiff immobility time of rats were monitored weekly,Nissl staining was used to observe the morphology of hippocampal tissue on the 28 d,immunofluorescence staining was used to detect the expression of Ki67,dual cortin(DCX)and neuronal differentiation factor 1(NeuroD1)in dentate gyrus of the hippocampus,the expression of synaptic vesicle protein 2A(SV2A)protein in dentate gyrus of hippocampus was detected by Western blot.Results Compared with the sham-operation group,on the first day after operation,the body mass of the model group rats decreased,then gradually increased,and on the 28th day,the body mass was still lower than that of the sham-operation group(P<0.05);on the first day after operation,the mNSS score significantly increased,gradually decreased thereafter,and remained higher than the sham-operation group until the 28th day(P<0.01);the percentage of stiff immobility time significantly decreased on the first day after operation,gradually stabilized,and remained lower than the sham-operation group on the 28th day(P<0.05);the hippocampal tissue structure was significantly damaged,and the density of Ki67+DCX+NeuroD1 positive cells in the dentate gyrus of hippocampus was significantly increased(P<0.05),the expression of SV2A protein in the dentate gyrus of hippocampal was significantly decreased(P<0.05).Compared with the model group,the body mass of rats in the electroacupuncture group showed an increasing trend(P<0.05),the mNSS score decreased(P<0.01),and the percentage of stiff immobility time increased(P<0.05);the ischemic injury area was significantly reduced,the structure was clearer,and the disordered and irregularly cells arrangement were reduced,the density of Ki67+DCX+NeuroD1 positive cells in the dentate gyrus of hippocampus significantly increased(P<0.05),and the expression of SV2A protein in the dentate gyrus of hippocampal significantly increased(P<0.05).Conclusion Electroacupuncture at acute phase at"Baihui"and"Shenting"can promote the recovery of cognitive dysfunction in MCAO rats in the later stage,and its mechanism may be related to enhancing the proliferation and differentiation of neural precursor cells in the dentate gyrus of hippocampus,promoting neurogenesis.

Cervical spinal cord injury without fracture-dislocation (CSCIWFD) is referred to as a special type of cervical spinal cord injury characterized by traumatic spinal cord dysfunction and no significant bony structural abnormalities on imagines. Duo to the high risk of missed diagnosis during the initial consultation, CSCIWFD may lead to progressive neurological deterioration or even complete paralysis, severely impacting patients′ prognosis. Currently, there are no established consensuses over the diagnosis and treatment of CSCIWFD, such as the lack of evidence-based standards for indications of non-surgical treatment and risk of secondary neurological injury, as well as debates over the optimal timing for surgical intervention and indications for different surgical approaches. To address these issues, the Spine Trauma Group of the Orthopedic Branch of the Chinese Medical Doctor Association organized experts in the relevant fields to formulate Diagnosis and treatment guideline for acute cervical spinal cord injury without fracture- dislocation in adults ( version 2025) . Based on evidence-based medicine and the principles of scientific rigor and clinical applicability, the guidelines proposed 11 recommendations covering terminology, diagnosis, evaluation treatment, and rehabilitation, etc., aiming to standardize the management of CSCIWFD.