Objective To investigate the predictive value of the combined tumor burden score (TBS) and platelet-albumin-bilirubin (PALBI) score model for postoperative tumor recurrence in liver transplant recipients with hepatocellular carcinoma (HCC). Methods The general information of 158 recipients diagnosed with HCC and underwent liver transplantation at the 900th Hospital of the Joint Logistics Support Force of the Chinese People's Liberation Army from 2008 to 2021 was collected. Lasso regression analysis combined with multivariate Cox regression analysis were used to identify independent risk factors for postoperative tumor recurrence after liver transplantation with HCC. A nomogram prediction model was constructed based on variables selected by Lasso regression analysis, and the predictive performance of the model was verified by calibration curve and clinical decision curve. The optimal cut-off values for postoperative tumor recurrence in liver transplant recipients with HCC were determined by receiver operating characteristic (ROC) curve, and Kaplan-Meier analysis was used to compare survival differences among different groups. Results Among the 158 liver transplant recipients with HCC, 82 experienced tumor recurrence, with a recurrence rate of 51.9% and a median tumor-free survival time of 10 (4, 25) months. Results of Lasso regression analysis and multivariate Cox regression analysis showed that alpha-fetoprotein (AFP) ≥400 ng/mL, TBS and PALBI score were all independent risk factors for postoperative tumor recurrence in liver transplant recipients with HCC (all P<0.05). The combined high TBS-high PALBI score showed the highest predictive value (hazard ratio 6.909, 95% confidence interval 3.067-15.563, P<0.001). A nomogram prediction model was constructed based on six variables selected by Lasso regression analysis. Calibration curve showed good consistency between the model's predicted results and the ideal curve. Decision curve analysis indicated that the nomogram prediction model provided the highest clinical benefit for predicting 1-year tumor-free survival after liver transplantation with HCC. Time-dependent ROC curves at 1, 3 and 5 years after surgery showed that TBS-PALBI model had good predictive performance, with no significant difference in area under the curve (AUC) compared with TBS-PALBI-AFP model. The optimal cut-off values for predicting postoperative tumor recurrence were determined by ROC curve, with a PALBI score cut-off of −2.334 and a TBS cut-off of 5.305. Recipients were divided into a low TBS-low PALBI score group (n=47) and a low/high TBS-low/high PALBI score group (at least one score was high) (n=111). Kaplan-Meier survival analysis showed that the low TBS-low PALBI score group had a higher tumor-free survival rate than the low/high TBS-low/high PALBI score group, with a significant difference (P<0.05). Conclusions TBS-PALBI model provides a novel, simple and effective tool for assessing the prognosis of liver transplant recipients with HCC. The nomogram model constructed based on this has significant advantages in predictive performance and may serve as a reference for guiding individualized treatment plans and improving clinical outcomes.

OBJECTIVE To compare the efficacy of ceftazidime and avibactam （CZA） monotherapy and combination therapy in the treatment of carbapenem-resistant Gram-negative bacteria （CRGNB） infections， and analyze the influencing factors. METHODS The data of patients with CRGNB infection who received CZA treatment from January 2020 to March 2025 were collected retrospectively. The patients were divided into the CZA monotherapy group （52 cases） and the CZA combination therapy group （85 cases） according to treatment regimen. The therapeutic effects of the two groups were compared， and the drug susceptibility results of isolated strains were recorded. The multivariate Logistic regression model was used to analyze the factors influencing clinical efficacy of CRGNB patients. RESULTS The bacterial clearance rate of patients was significantly higher in the CZA combination therapy group than in the CZA monotherapy group （P＝0.012）. However， when comparing the 30-day mortality rate and the clinical response rate between the two groups， no statistically significant differences were observed （P＞0.05）. Among the isolates， carbapenem-resistant Klebsiella pneumoniae had the highest sensitivity to tigecycline （87.3%） and carbapenem-resistant Pseudomonas aeruginosa showed 90.9% sensitivity to amikacin. Five isolates were resistant to CZA. The multivariate Logistic regression showed， lung infection， receiving continuous renal replacement therapy （CRRT）， and inadequate treatment courses were significantly correlated with clinical treatment failure （P＜0.05）. CONCLUSIONS For CRGNB infection， the clinical efficacy of CZA combination therapy is similar to that of monotherapy， but the combination therapy has a higher bacterial clearance rate. Lung infections， receiving CRRT and inadequate treatment courses （No. are independent risk factors for clinical treatment failure.

Objective To compare the long-term survival of elderly patients with esophageal squamous cell carcinoma (ESCC) treated with surgical versus non-surgical treatment. Methods A retrospective analysis was conducted on the clinical data of elderly patients aged ≥70 years with ESCC who underwent esophagectomy or radiotherapy/chemotherapy at Sichuan Cancer Hospital from January 2009 to September 2017. Patients were divided into a surgical group (S group) and a non-surgical group (NS group) according to the treatment method. The propensity score matching method was used to match the two groups of patients at a ratio of 1∶1, and the survival of the two groups before and after matching was analyzed. Results A total of 726 elderly patients with ESCC were included, including 552 males and 174 females, with 651 patients aged ≥70-80 years and 75 patients aged ≥80-90 years. There were 515 patients in the S group and 211 patients in the NS group. The median follow-up time was 60.8 months, and the median overall survival of the S group was 41.9 months [95%CI (35.2, 48.5)], while that of the NS group was only 24.0 months [95%CI (19.8, 28.3)]. The 1-, 3-, and 5-year overall survival rates of the S group were 84%, 54%, and 40%, respectively, while those of the NS group were 72%, 40%, and 30%, respectively [HR=0.689, 95%CI (0.559, 0.849), P<0.001]. After matching, 138 patients were included in each group, and there was no statistical difference in the overall survival between the two groups [HR=0.871, 95%CI (0.649, 1.167), P=0.352]. Conclusion Compared with conservative treatment, there is no significant difference in the long-term survival of elderly patients aged ≥70 years who undergo esophagectomy for ESCC. Neoadjuvant therapy combined with surgery is still an important choice to potentially improve the survival of elderly patients with ESCC.

Objective: To explore the association between the Internet usage characteristics and suicidal ideation among vocational high school students, so as to provide a theoretical basis for precise intervention of suicide among vocational high school students. Methods: A total of 1 781 students were recruited from three vocational high schools in Wuhan and Xianning in March 2023 by using the cluster random sampling method. The Columbia-Suicide Severity Rating Scale and Revised Chen Internet Addiction Scale were used to measure suicidal ideation and Internet addiction, respectively. LASSO regression model was used to select influential factors related to suicidal ideation, and the gradient boosting decision tree algorithm XGBoost was used to develop prediction models and evaluate predictive performance. By calculating the SHAP values, the contribution of each influential factor was quantified. Results: The prevalence of suicidal ideation among vocational high school students was 42.22% and prevalence of Internet addiction was 26.39%. LASSO regression results indicated that age, gender, experience of being left behind, parental relationship, holding a class cadre position, using the Internet for learning, Internet use during dawn, morning and late night, Internet addiction, and depressive symptoms were all the influential factors of suicidal ideation among vocational high school students ( β= -0.05 , 0.29, 0.09, 0.27, 0.10, -0.01, 0.09, 0.05, 0.24, 0.28, 0.78, all P <0.05). The AUC of the prediction model was 0.75. The results based on SHAP values indicated that all influential factors identified through multivariate analysis contributed positively to the model predictions ( SHAP >0). Among these, depressive symptoms and parental relationship had the greatest impact on suicidal ideation ( SHAP =0.77, 0.26), and the joint effect of features with higher contribution could improve the prediction probability. Conclusions Depressive symptoms, parental relationships, Internet addiction, and time of Internet use are most important risk factors of suicidal behaviors for vocational high school students. Thus, effective interventions should be conducted to reduce their suicidal ideation.

RNA modifications constitute a crucial class of post-transcriptional chemical alterations that profoundly influence RNA stability and translational efficiency, thereby shaping cellular protein expression profiles. These diverse chemical marks are ubiquitously involved in key biological processes, including cell proliferation, differentiation, apoptosis, and metastatic potential, and they exert precise regulatory control over these functions. A major advance in the field is the recognition that RNA modifications do not act in isolation. Instead, they participate in complex, dynamic interactions—through synergistic enhancement, antagonism, competitive binding, and functional crosstalk—forming what is now termed the “RNA modification interactome” or “RNA modification interaction network.” The formation and functional operation of this interactome rely on a multilayered regulatory framework orchestrated by RNA-modifying enzymes—commonly referred to as “writers,” “erasers,” and “readers.” These enzymes exhibit hierarchical organization within signaling cascades, often functioning in upstream-downstream sequences and converging at critical regulatory nodes. Their integration is further mediated through shared regulatory elements or the assembly into multi-enzyme complexes. This intricate enzymatic network directly governs and shapes the interdependent relationships among various RNA modifications. This review systematically elucidates the molecular mechanisms underlying both direct and indirect interactions between RNA modifications. Building upon this foundation, we introduce novel quantitative assessment frameworks and predictive disease models designed to leverage these interaction patterns. Importantly, studies across multiple disease contexts have identified core downstream signaling axes driven by specific constellations of interacting RNA modifications. These findings not only deepen our understanding of how RNA modification crosstalk contributes to disease initiation and progression, but also highlight its translational potential. This potential is exemplified by the discovery of diagnostic biomarkers based on interaction signatures and the development of therapeutic strategies targeting pathogenic modification networks. Together, these insights provide a conceptual framework for understanding the dynamic and multidimensional regulatory roles of RNA modifications in cellular systems. In conclusion, the emerging concept of RNA modification crosstalk reveals the extraordinary complexity of post-transcriptional regulation and opens new research avenues. It offers critical insights into the central question of how RNA-modifying enzymes achieve substrate specificity—determining which nucleotides within specific RNA transcripts are selectively modified during defined developmental or pathological stages. Decoding these specificity determinants, shaped in large part by the modification interactome, is essential for fully understanding the biological and pathological significance of the epitranscriptome.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

ObjectiveTo elucidate the potential mechanism of modified Sinisan （MSNS） in alleviating anxiety-like behaviors induced by chronic restraint stress （CRS） in mice at the metabolic level based on serum untargeted metabolomics and identify key metabolites and metabolic pathways regulated by MSNS. MethodsSeventy-two male C57BL/6 mice were randomly assigned into six groups： control， model， high-dose （2.4 g·kg^-1） MSNS， medium-dose （1.2 g·kg^-1） MSNS， low-dose （0.6 g·kg^-1） MSNS， and positive control （fluoxetine， 2.6 mg·kg^-1）. Except the control group， the other groups were subjected to CRS for the modeling of anxiety. Mice were administrated with corresponding agents by gavage 2 h before daily restraint for 14 days. Anxiety-like behaviors were evaluated by the open field test （OFT）， elevated plus maze （EPM） test， and light/dark box （LDB） test. Serum levels of corticotropin-releasing hormone （CRH）， adrenocorticotrophic hormone （ACTH）， and corticosterone （CORT） were measured via ELISA to assess stress levels. Ultra-performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS） was employed to detect 9 metabolites in the brain tissue and serum metabolites. Orthogonal partial least squares-discriminant analysis （OPLS-DA） was adopted to identify differential metabolites （VIP>1.0， P<0.05）. MetaboAnalyst 5.0 was used for metabolic pathway enrichment analysis of the differential metabolites. ResultsCompared with the control group， the model group showed reductions in the central activity time and central distance in the OFT （P<0.05）， the proportions of open-arm residence time and open-arm residence times in the EPM test （P<0.01）， and the proportions of open box activity time and open box activity distance in the LDB test （P<0.05）， which were increased in the medium- and high-dose MSNS groups compared with the model group （P<0.05）. Compared with the control group， the model group showed elevated levels of CRH， ACTH， and CORT in the serum （P<0.01）， and the elevations were diminished in the medium- and high-dose MSNS groups （P<0.05）. UPLC-MS results indicated that compared with the control group， the model group presented declined DA， GABA， 5-HIAA， 5-HT， and 5-HT/Trp levels （P<0.05， P<0.01） and raised Glu， NE， Kyn， and Kyn/Trp levels （P<0.05）. Compared with the model group， high-dose MSNS increased the GABA， 5-HIAA， and 5-HT/Trp levels （P<0.05） and lowered the Glu and Kyn/Trp levels （P<0.05）. Untargeted metabolomics identified that 16 CRS-induced metabolic disturbances were reversed by MSNS. KEGG pathway analysis indicated that MSNS primarily modulated eight core pathways including alanine/aspartate/glutamate metabolism， butyrate metabolism， arginine-proline metabolism， TCA cycle， unsaturated fatty acid biosynthesis， and tryptophan metabolism. The mechanisms involved multidimensional biological processes， including neurotransmitter homeostasis regulation， TCA cycle energy metabolism optimization， and inflammatory response suppression. ConclusionMSNS alleviates CRS-induced anxiety-like behaviors in mice by mitigating hypothalamic-pituitary-adrenal axis hyperactivity， improving hippocampal neurotransmitter and tryptophan metabolic pathways， and regulating alanine/aspartate/glutamate metabolism， butyrate metabolism， arginine-proline metabolism， and TCA cycle.

ObjectiveTo elucidate the potential mechanism of modified Sinisan （MSNS） in alleviating anxiety-like behaviors induced by chronic restraint stress （CRS） in mice at the metabolic level based on serum untargeted metabolomics and identify key metabolites and metabolic pathways regulated by MSNS. MethodsSeventy-two male C57BL/6 mice were randomly assigned into six groups： control， model， high-dose （2.4 g·kg^-1） MSNS， medium-dose （1.2 g·kg^-1） MSNS， low-dose （0.6 g·kg^-1） MSNS， and positive control （fluoxetine， 2.6 mg·kg^-1）. Except the control group， the other groups were subjected to CRS for the modeling of anxiety. Mice were administrated with corresponding agents by gavage 2 h before daily restraint for 14 days. Anxiety-like behaviors were evaluated by the open field test （OFT）， elevated plus maze （EPM） test， and light/dark box （LDB） test. Serum levels of corticotropin-releasing hormone （CRH）， adrenocorticotrophic hormone （ACTH）， and corticosterone （CORT） were measured via ELISA to assess stress levels. Ultra-performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS） was employed to detect 9 metabolites in the brain tissue and serum metabolites. Orthogonal partial least squares-discriminant analysis （OPLS-DA） was adopted to identify differential metabolites （VIP>1.0， P<0.05）. MetaboAnalyst 5.0 was used for metabolic pathway enrichment analysis of the differential metabolites. ResultsCompared with the control group， the model group showed reductions in the central activity time and central distance in the OFT （P<0.05）， the proportions of open-arm residence time and open-arm residence times in the EPM test （P<0.01）， and the proportions of open box activity time and open box activity distance in the LDB test （P<0.05）， which were increased in the medium- and high-dose MSNS groups compared with the model group （P<0.05）. Compared with the control group， the model group showed elevated levels of CRH， ACTH， and CORT in the serum （P<0.01）， and the elevations were diminished in the medium- and high-dose MSNS groups （P<0.05）. UPLC-MS results indicated that compared with the control group， the model group presented declined DA， GABA， 5-HIAA， 5-HT， and 5-HT/Trp levels （P<0.05， P<0.01） and raised Glu， NE， Kyn， and Kyn/Trp levels （P<0.05）. Compared with the model group， high-dose MSNS increased the GABA， 5-HIAA， and 5-HT/Trp levels （P<0.05） and lowered the Glu and Kyn/Trp levels （P<0.05）. Untargeted metabolomics identified that 16 CRS-induced metabolic disturbances were reversed by MSNS. KEGG pathway analysis indicated that MSNS primarily modulated eight core pathways including alanine/aspartate/glutamate metabolism， butyrate metabolism， arginine-proline metabolism， TCA cycle， unsaturated fatty acid biosynthesis， and tryptophan metabolism. The mechanisms involved multidimensional biological processes， including neurotransmitter homeostasis regulation， TCA cycle energy metabolism optimization， and inflammatory response suppression. ConclusionMSNS alleviates CRS-induced anxiety-like behaviors in mice by mitigating hypothalamic-pituitary-adrenal axis hyperactivity， improving hippocampal neurotransmitter and tryptophan metabolic pathways， and regulating alanine/aspartate/glutamate metabolism， butyrate metabolism， arginine-proline metabolism， and TCA cycle.

ObjectiveTo explore the mechanism by which Xiaoyaosan regulates HPT axis dysfunction in the rat model with the syndrome of liver depression and spleen deficiency by observing its effect on the glycoprotein hormone α-subunit （CGA）/glutathione peroxidase 2 （GPX2）/thyroid-stimulating hormone β-subunit （TSHβ） pathway for thyroid hormone synthesis. MethodsSeventy-two male SD rats were randomized into six groups： normal， model， high-dose （16.7 g·kg^-1）， medium-dose （8.35 g·kg^-1）， and low-dose （4.175 g·kg^-1） Xiaoyaosan， and fluoxetine （0.001 8 g·kg^-1） groups， with 12 rats in each group. The rat model of liver depression and spleen deficiency was induced by chronic restraint stress for 21 days. The intervention groups were treated with Xiaoyaosan decoctions or fluoxetine suspension， respectively. After modeling， hematoxylin-eosin staining was employed to observe morphological changes in the thyroid and pituitary tissue of the rats. Serum levels of triiodothyronine （T3）， tetraiodothyronine （T4）， and thyroid-stimulating hormone （TSH） were measured by enzyme-linked immunosorbent assay （ELISA）. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） and Western blot were employed to determine the mRNA and protein levels， respectively， of TSH receptor （TSHR） in the thyroid tissue， thyrotropin-releasing hormone receptor （TRHR） and TSHβ in the pituitary tissue， and thyrotropin-releasing hormone （TRH）， CGA， GPX2， and TSHβ in the hypothalamic tissue. ResultsCompared with the normal group， the model group showed significant atrophy and irregularity of thyroid follicles， a marked reduction in colloid secretion， extensive vacuolar degeneration of adenocytes in the anterior pituitary， lowered serum levels of T3， T4， and TSH （P<0.01）， and down-regulated mRNA and protein levels of TSHR in the thyroid tissue， TRHR and TSHβ in the pituitary tissue， and TRH， CGA， GPX2， and TSHβ in the hypothalamic tissue （P<0.01）. Compared with the model group， high- and medium-dose Xiaoyaosan and fluoxetine alleviated the pathological changes in the thyroid and pituitary tissue， outperforming the low-dose Xiaoyaosan group. Moreover， they elevated the serum levels of T3， T4， and TSH （P<0.05， P<0.01）. The serum TSH level was also elevated in the low-dose Xiaoyaosan group （P<0.05）. The mRNA and protein levels of TSHR in the thyroid， TRHR and TSHβ in the pituitary， and TRH， CGA， GPX2， and TSHβ in the hypothalamus were up-regulated in the high- and medium-dose Xiaoyaosan groups （P<0.05， P<0.01）. Additionally， the mRNA and protein levels of TSHβ in the hypothalamus were up-regulated in the low-dose Xiaoyaosan group （P<0.01）. In the fluoxetine group， the mRNA and protein levels of TSHR in the thyroid， TRHR in the pituitary， and TRH， CGA， and GPX2 in the hypothalamus were up-regulated （P<0.05， P<0.01）. ConclusionThe downregulation of CGA/GPX2/TSHβ pathway may be one of the biological mechanisms underlying HPT axis dysfunction in the rat model with the syndrome of liver depression and spleen deficiency. Xiaoyaosan may regulate the HPT axis dysfunction by up-regulating the CGA/GPX2/TSHβ pathway.

AIM:To analyze the influencing factors of visual outcome after vitrectomy for polypoidal choroidal vasculopathy(PCV)combined with vitreous hemorrhage and establish a predictive model.METHODS: A retrospective analysis was conducted on the clinical data of 129 cases(129 eyes)of patients who underwent vitrectomy for PCV combined with vitreous hemorrhage from June 2021 to January 2024 in our hospital. They were divided into elevated group(71 eyes)and non-elevated group(58 eyes)according to visual outcome at early posoperative stage(within 24 mo). Another 30 cases(30 eyes)of PCV with vitreous hemorrhage undergoing vitrectomy were selected as external validation data. The predictive value of the model for the postoperative visual outcomes of both internal and external populations was evaluated.RESULTS: The non-elevated group had a higher proportion of patients aged ≥60 years, diabetes, continuous abnormalities of the ellipsoid zone(EZ)during surgery, bleeding involving the macular fovea, and postoperative retinal scar formation than the elevated group were independent factors affecting postoperative visual acuity(all P<0.05). The AUC of the predictive model for predicting the postoperative visual outcomes of internal and external populations was 0.824(95%CI: 0.750-0.898)and 0.809(95%CI: 0.723-0.865), respectively.CONCLUSION:Patients aged ≥60 years, diabetes, intraoperative continuous abnormalities of EZ, bleeding involving the macular fovea, and postoperative retinal scar formation are influencing factors for visual outcome after vitrectomy in patients with PCV combined with vitreous hemorrhage. A predictive model based on those factors has been established, which has a certain predictive value for postoperative visual outcome.