Objective: To explore the impact of adverse childhood experiences (ACEs) on health risk behaviors (HRBs) among college students and the mediating role of psychological symptoms, so as to provide a basis for developing intervention strategies. Methods: From March to April 2023, a convenience cluster sample of 1 801 students from 12 universities in Nanning, Liuzhou, Guilin, Wuzhou of Guangxi completed an online survey. A self designed questionnaire, Adverse Childhood Experiences-International Questionnaire (ACE-IQ) and Symptom Checklist-90 (SCL-90) were used for evaluation tools. Binary Logistic regression, structural equation modeling (SEM) and Bootstrap methods were used to analyze the associations and mediating effects. Results: Overall, 71.2% of college students experienced at least one type of ACE, with emotional neglect (40.3%) and emotional abuse ( 25.2 %) having the highest detection rates. The top three HRBs were unhealthy diet (77.8%), physical inactivity (54.1%), and smoking/alcohol use (18.5%). Logistic regression showed that poor family functioning, abuse, and extra familial violence were each associated with an increased risk of smoking/alcohol use ( OR =1.14, 1.11, 1.18) and deliberate self harm ( OR =1.26, 1.19,1.30) (all P <0.05). Experience of abuse increased the risk of high risk sexual behavior and family dysfunction increaded the risk of physical inactivity, respectively ( OR = 1.07 , 1.04, both P <0.05). Mediation analysis revealed that anxiety ( β =0.20) and depression ( β = 0.09 ) partially mediated the pathway from poor family functioning to deliberate self harm; paranoia ( β =0.02) partially mediated the pathway from abuse to high risk sexual behavior; and obsessive-compulsive symptoms ( β =0.26) and depression ( β =0.10) partially mediated the pathway from extra familial violence to deliberate self harm (all P <0.05). Conclusion Psychological symptoms play a mediating role in the association between ACEs and HRBs, and mental health interventions may reduce the risk of HRBs among college students.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

Methods: Fifty patients who underwent UBE-TLIF and 50 patients who underwent W-TLIF, each with >2 years of follow-up, were retrospectively analyzed. Outcomes included operative parameters, time to postoperative mobilization, paravertebral muscle atrophy and fat infiltration rates, clinical scores (Visual Analog Scale [VAS], Oswestry Disability Index [ODI], Japanese Orthopaedic Association [JOA]), modified Macnab criteria, fusion rates, and complications. Results: Compared with W-TLIF, the UBE-TLIF group had significantly less intraoperative blood loss, shorter operative times, and lower postoperative drainage volumes (p <0.05). The UBE-TLIF group showed faster postoperative recovery and shorter hospital stays. At 6 months, 1 year, and 2 years, W-TLIF patients had higher multifidus and erector spinae atrophy, and greater paravertebral muscle fat infiltration (p <0.05). The UBE-TLIF group also had lower VAS and ODI scores at 1 year and 2 years (p <0.05) and fewer surgical complications (6% vs. 10%). Fusion rates (94% vs. 92%) and modified Macnab outcomes (88% vs. 86%) were comparable (p >0.05). Conclusions UBE-TLIF is associated with reduced intraoperative trauma, quicker recovery, and fewer complications. In the long-term, it better preserves paravertebral muscle integrity and provides superior pain and functional outcomes.

ObjectiveTo investigate the safety and efficacy of transparent cap-assisted peroral cholangiopancreatoscopy-guided electrohydraulic lithotripsy （EHL）. MethodsA retrospective analysis was performed for the clinical data of 60 patients with large common bile duct stones who were admitted to Department of Gastroenterology， Jilin People’s Hospital， from May 1， 2023 to January 31， 2026， and according to the treatment method， the patients were divided into transparent cap-assisted peroral cholangiopancreatoscopy-guided electrohydraulic lithotripsy group and peroral cholangiopancreatoscopy-guided electrohydraulic lithotripsy group， with 30 patients in each group. The two groups were compared in terms of the rate of successful single-session stone fragmentation and removal， procedural time， duration of electrohydraulic lithotripsy， clinical success rate， and complications. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. ResultsCompared with the peroral cholangiopancreatoscopy-guided electrohydraulic lithotripsy group， the transparent cap-assisted peroral cholangiopancreatoscopy-guided electrohydraulic lithotripsy group had a significantly higher technical success rate （83.33% vs 60.00%， χ²=4.022， P=0.045） and significantly shorter procedural time ［46.00 （42.25 — 49.00） min vs 54.50 （42.00 — 65.00） min， Z=2.012， P=0.044］ and duration of electrohydraulic lithotripsy ［8.00 （6.25 — 11.75） min vs 13.50 （9.25 — 17.75） min， Z=2.749， P=0.006］. Both groups achieved a clinical success rate of 100%， with no significant difference in the incidence rate of complications （P>0.05）. ConclusionTransparent cap-assisted peroral cholangiopancreatoscopy-guided electrohydraulic lithotripsy has a high rate of successful single-session stone fragmentation and removal and a short procedural time， with good safety and efficacy， and therefore， it holds promise for clinical application.

Pancreatic cancer （PC）， a highly malignant tumor of the digestive system， is characterized by extremely high incidence and mortality rates， imposing a severe burden on the healthcare system. Despite significant advancements in comprehensive therapeutic strategies for PC， clinical benefits for patients remain limited due to the high heterogeneity and unique microenvironment of the tumor. Therefore， further elucidating the molecular mechanisms underlying PC progression and developing novel， effective therapeutic strategies have become an urgent necessity in the current research. Programmed cell death （PCD） is a genetically orchestrated process of autonomous cell demise that is crucial for maintaining cellular homeostasis. Recent studies have demonstrated that tumor cells can remodel the tumor microenvironment by modulating various PCD pathways—including apoptosis， autophagy， pyroptosis， and ferroptosis—thereby driving tumor proliferation， invasion， and drug resistance. Traditional Chinese medicine （TCM） possesses unique advantages in anti-tumor therapy， characterized by multi-component， multi-target， and multi-pathway regulation. Accumulating evidence suggests that TCM formulas and their natural active compounds can effectively delay the malignant progression of PC by modulating PCD in tumor cells. This article systematically summarizes the molecular mechanisms of PCD in PC progression and reviews the mechanisms by which TCM formulas and natural active compounds intervene in PC through PCD modulation. This review aims to provide theoretical support and future research directions for the prevention and treatment of PC with TCM.

Background Acute hypoxia exposure can impair synaptic transmission in hippocampal neurons and disrupt neural network function. However, the specific molecular mechanisms underlying hypoxia-induced synaptic vesicle dysfunction remain not fully elucidated. Objective To investigate the molecular mechanisms underlying acute hypoxia-induced synaptic vesicle dysfunction in human hippocampal neuronal cells (HPPNCs) with a particular focus on the regulatory role of long non-coding RNA (lncRNA) FTX in the miR-137-3p/soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) complex axis. Methods An acute hypoxia injury model was established in HPPNCs. Cell counting kit-8 (CCK-8) assay was used to determine the optimal seeding density and hypoxic exposure duration. Proteomic analysis was utilized to identify differentially expressed proteins (DEPs) between normoxic and hypoxic conditions, followed by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses to identify affected biological pathways. Bioinformatics prediction (e.g, RPISeq prediction of RNA-protein interactions) was integrated with quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting to evaluate changes in DEPs and the lncRNA FTX/miR-137-3p axis. Small interfering RNA (siRNA) silencing and interaction potential prediction were further employed to confirm the regulatory role of lncRNA FTX. Results CCK-8 assay determined that the optimal seeding density for HPPNCs was 3.5×10³ cells·well⁻¹ and that 48 h of acute hypoxia exposure significantly reduced cell viability. Proteomic analysis revealed that DEPs were primarily enriched in the synaptic vesicle cycle pathway. Synaptosomal-associated protein 25 (SNAP25), a core component of the SNARE complex, was significantly downregulated at both mRNA and protein levels (P < 0.01). Mechanistic studies found that lncRNA FTX expression was significantly decreased in hypoxic cells, whereas miR-137-3p expression was significantly elevated. Furthermore, siRNA silencing of lncRNA FTX significantly reduced SNAP25 expression. RPISeq prediction suggested a potential interaction between lncRNA FTX and the SNAP25 protein (random forest, RF=0.75; support vector machine, SVM=0.56). Conclusion Acute hypoxia exposure may impair synaptic vesicle function in hippocampal neuronal cells by downregulating lncRNA FTX, increasing miR-137-3p expression, and suppressing SNAP25 expression, thereby disrupting the SNARE complex. These findings suggest that the lncRNA FTX/miR-137-3p/SNAP25 axis may play an important role in acute hypoxia-induced synaptic dysfunction.

Diabetic nephropathy belongs to diabetic microvascular aseptic inflammation， which is the main cause of end-stage renal disease and can cause damage to the structure of glomeruli and tubulointerstitium. Pyroptosis is a potent pro-inflammatory model of programmed cell death mediated by gasdermin （GSDM） protein family， which is characterized by nuclear shrinkage， chromatin DNA fragmentation， plasma membrane rupture， cell swelling and deformation. Related studies have found that pyroptosis is closely related to the occurrence and development of diabetic nephropathy. Inhibition of pyroptosis to a certain extent can reduce diabetic renal injury， so the pathway of pyroptosis involved in the pathogenesis of diabetic nephropathy is the current research focus. The characteristics of multi-components， multi-targets and multi-pathways of traditional Chinese medicine have significant advantages in the treatment of diabetic nephropathy. Some components of traditional Chinese medicine， single traditional Chinese medicine and compound prescription of traditional Chinese medicine can improve diabetic renal injury by inhibiting pyroptosis pathway and related targets. Based on the molecular mechanism of pyroptosis， this paper clarifies the mechanism of pyroptosis in diabetic nephropathy by expounding the relationship between pyroptosis and its pathway targets and diabetic nephropathy. This paper summarizes the research status of traditional Chinese medicine in the treatment of diabetic nephropathy by interfering with related pyroptosis pathways in recent years， so as to provide perspectives and ideas for the prevention， early diagnosis， drug development and molecular treatment of diabetic nephropathy in the future.

[Objective] To explore the strategy of blood management in patients with massive transfusion in the frigid plateau region. [Methods] The treatment process of a patient with liver rupture in the frigid plateau region was analyzed, and the blood management strategy of the frigid plateau region was discussed in combination with the difficulties of blood transfusion and literature review. [Results] The preoperative complete blood count (CBC) test results of the patient were as follows: RBC 3.14×10¹²/L, Hb 10⁶ g/L, HCT 30.40%, PLT 115.00×10⁹/L; coagulation function: PT 18.9 s, FiB 1.31 g/L, DD > 6 μg/mL, FDP 25.86 μg/mL; ultrasound examination and imaging manifestations suggested liver contusion and laceration / intraparenchymal hematoma, splenic contusion and laceration, and massive blood accumulation in the abdominal cavity; it was estimated that the patient's blood loss was ≥ 2 000 mL, and massive blood transfusion was required during the operation; red blood cell components were timely transfused during the operation, and the blood component transfusion was guided according to the patient's CBC and coagulation function test results, providing strong support and guarantee for the successful treatment of the patient. The patient recovered well after the operation, and the CBC test results were as follows: RBC 4.32×10¹²/L, Hb 144 g/L, HCT 39.50%, PLT 329.00×10⁹/L; coagulation function: APTT 29.3 s, PT 12.1 s, FiB 2.728 g/L, DD>6 μg/mL, FDP 25.86 μg/mL. The patient was discharged after 20 days, and regular follow-up reexamination showed no abnormal results. [Conclusion] Individualized blood management strategy should comprehensively consider the patient’s clinical symptoms, the degree of hemoglobin decline, dynamic coagulation test results and existing treatment conditions. Efficient and reasonable patient blood management strategies can effectively improve the clinical outcomes of massive transfusion patients in the frigid plateau region.