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.

Objective: To explore the effectiveness of different intervention modalities on nonsuicidal selfinjury (NSSI) in adolescents, so as to provide an evidencebased basis for the intervention strategy of NSSI in adolescents. Methods: Randomized controlled trials on interventions for adolescent NSSI were retrieved from databases, such as CNKI, Wanfang, VIP, CBM, Web of Science, PubMed, Embase, and Cochrane Library, spanning from the inception of these databases to March 5, 2025. Network Metaanalysis was performed by using Stata 17.0 and Review Manager 5.3 software, and the standardized mean difference (SMD) and 95%CI were used as the effect indicators to compare the differences in the effectiveness of the interventions and rank the effect. Results: A total of 26 articles with 2 034 adolescents with NSSI were included in the study, including 10 intervention modalities:dialectical behavior therapy, emotional regulation intervention, mentalizationbased therapy, family therapy, cutting down programme, cognitive behavioral therapy, narrative therapy, stepped care approach, positive psychological intervention, and acceptance and commitment therapy. The results showed that compared with the treatment as usual, positive psychological intervention [SMD(95%CI)=-2.12(-3.51 to -0.74)], stepped care intervention [SMD(95%CI)=-2.07(-3.43 to -0.71)], and dialectical behavior therapy [SMD(95%CI)=-1.70(-2.60 to -0.80)], cognitive behavioral therapy [SMD(95%CI)=-1.54(-2.61 to -0.48)], and acceptance and commitment therapy[SMD(95%CI)=-1.50(-2.68 to -0.32)] were statistically significant differences in reducing adolescents NSSI behaviors(P<0.05). Positive psychological intervention, stepped care intervention, and dialectical behavior therapy were more effective than the mentalizationbased therapy and the cutting down programme (SMD=-2.08, -2.03, -1.66, -2.06, -2.01, -1.64,P<0.05); the area under the cumulative ranking probability graph revealed that positive psychological intervention may have the best effect in improving NSSI among adolescents (82.5). Conclusions Positive psychological interventions show the best results in improving adolescent NSSI among multiple intervention modalities. It is recommended to give priority to positive psychological interventions in clinical interventions.

Objective: To utilize machine learning(ML) algorithms to develop accurate and effective prediction models for TAC dose/weight-adjusted trough concentration(C0/D). Methods: Data were collected on 264 TAC blood concentration monitoring data from 72 patients undergoing kidney transplantation. The effects of population statistical data, clinical features, combined medication, and ultrasound feature parameters on TAC C0/D were analyzed. Features with a significance level less than 0.05 in the univariate analysis of TAC C0/D were selected for inclusion in the random forest(RF) algorithm to identify significant features. These features were interpreted using partial dependency plots. Five ML algorithms, including RF, support vector regression(SVR), extreme gradient boosting(XGBoost), decision trees(DT) and artificial neural networks(ANN), were employed to establish the TAC C0/D prediction model. Hyper-parameter tuning was performed on the RF model that performed the best. Results : Ten characteristic variables with importance scores>5 were retained and included in the ML model: transglutaminase, red blood cell count, blood urea nitrogen, weight, serum creatinine, renal segmental arterial resistance index, renal aortic resistance index, hematocrit, renal pelvic Young′s modulus value, and time after transplantation. The partial dependence plots showed that all 10 important variables screened were positively correlated with TAC C0/D. The tuned RF model outperformed the other models with aR2of 0.81, aRMSEof 43.93, and aMAEof 29.97. Conclusion The ML models demonstrate good performance in predicting TAC C0/D and provide innovative interpretations using partial dependence plot. The optimized RF model shows optimal performance and offers a novel tool for individualized medication adjustment for TAC in renal transplant patients.

The electrocatalytic nitrate reduction reaction(NO3RR)presents a sustainable pathway for large-scale ammonia production,yet it faces significant challenges due to proton supply limitations caused by the high energy barrier for water dissociation,which slows ammonia(NH3)generation.Herein,a palladium(Pd)-modified copper-cobalt(CuCo)hollow fiber penetration electrode that enabled H2 injection through its hollow structures,thereby enhancing proton availability for NO3RR was developed.The active Pd component efficiently dissociated H2,facilitating active hydrogen(*H)spillover and speeding up the cascade NO3RR process on Cu and Co sites.As a result,a half-cell energy efficiency of 39.53%and an NH3 Faradaic efficiency(FE)of 97.11%±1.17%at-0.1 V(vs RHE)were achieved,comparable to state-of-the-art systems.Importantly,the H2-assisted approach prevented the oxidation of active Cu and Co phases,demonstrating exceptional stability with less than 5.6%decay in current density(267 mA/cm2)and retention of NH3 FE at 94.8%after over 70 h of electrolysis.These findings offered valuable insights into proton supply pathways and design of NO3RR electrodes.

Objective:To prepare decellularized extracellular matrix (dECM)-gelatin methacryloyl (GelMA) composite hydrogels and to study their effects on hepatocyte proliferation.Methods:Hepatic dECM was prepared by elution, and GelMA hydrogel and 10%, 30% and 50% dECM-GelMA composite hydrogels were prepared by pepsin solubilization. The morphology of normal liver and dECM liver was observed by eyes and scanning electron microscopy using hematoxylin-eosin, Sirius red and periodate-Schiff staining, respectively. The internal structure of the dECM-GelMA composite hydrogels was observed by scanning electron microscopy, and the pore diameter was measured. Liver HL-7702 cells were co-cultured with GelMA hydrogel and 10%, 30% and 50% dECM-GelMA composite hydrogels, and the cell proliferation viability was determined by cell counting kit-8. The expression of proliferating cell nuclear antigen (PCNA), Wnt family protein 5a (Wnt5a), β-catenin, extracellular-regulated protein kinase 1/2 (ERK1/2) and phosphorylated ERK1/2 (p-ERK1/2) were detected by Western blotting. Comparisons were made using independent sample t-test or one-factor analysis of variance. Results:After decellularization, the hepatocyte morphology showed rounded depressions, and the extracellular matrix structure was intact. The GelMA hydrogel and 10%, 30% and 50% dECM-GelMA composite hydrogels showed inernally porous structures. The pore diameter increased from (3.06±1.35) μm in the GelMA hydrogel to (16.01±4.02) μm in the 50% dECM-GelMA composite hydrogel. On the 3rd, 5th and 7th day, the relative cell proliferation was higher in the 50% dECM-GelMA composite hydrogel group than that in the GelMA hydrogel group (1.89±0.04 vs 1.53±0.01, 9.36±0.04 vs 3.89±0.09, 7.15±0.27 vs 4.89±0.15, all P<0.05). The relative expression levels of PCNA, Wnt5a, β-catenin, and p-ERK1/2/ERK1/2 proteins in the 50% dECM-GelMA composite hydrogel group were higher than those in the GelMA hydrogel group (2.14±0.04 vs 1.00±0.03, 2.36±0.09 vs 1.00±0.08, 1.45±0.03 vs 1.00±0.04, 1.43±0.04 vs 1.00±0.01, all P<0.05). Conclusions:A dECM-GelMA composite hydrogel can be prepared, which may promote hepatocyte proliferation by upregulating the phosphorylation of ERK1/2 and activating Wnt/β-catenin signaling pathway.

Objective:To compare the clinical efficacy of navigation system and orthopedic robot-assisted nail placement in the treatment of lower cervical fracture and dislocation.Methods:A retrospective cohort study was conducted to analyze the clinical data of 49 patients with fracture and dislocation of the lower cervical spine who were admitted to Honghui Hospital, Xi′an Jiaotong University School of Medicine from May 2021 to October 2022, including 38 males and 11 females, aged 29-61 years [(39.3±7.3)years]. Injury segments involved C 3 in 12 patients, C 4 in 11, C 5 in 8, C 6 in 9 and C 7 in 9. Twenty-one patients were treated with S8 navigation system (navigation group, 84 screws), and 28 with TINAVI orthopedic robot (robot group, 112 screws). The two groups were compared in terms of the total surgical duration, single screw placement time, total screw placement time, distance between the screw and the anterior cortex, incision length, intraoperative radiation dose, intraoperative blood loss and length of hospital stay. The height of intervertebral space, Cobb angle, sliding distance between vertebral bodies and American Spinal Injury Association (ASIA) grade were assessed before surgery and at 3 days after surgery. Visual analogue scale (VAS), Japanese Orthopedic Association (JOA) score and neck dysfunction index (NDI) before surgery, at 3 days, 3 months after surgery and at the last follow-up were compared. The accuracy of screw placement, intraoperative invasion rate of adjacent facet joints and rate of postoperative complications (infection, screw loosening, etc.) were evaluated. Results:All the patients were followed up for 12-16 months [(13.6±1.9)months]. In the navigation group, the total surgical duration, distance from the screw to the anterior cortex and the intraoperative radiation dose were (236.2±30.6)minutes, (2.0±0.2)mm and (374.3±90.3)mGy respectively, which were significantly shorter or less than those in the robot group [(278.4±20.7)minutes, (10.6±2.9)mm and (448.4±77.9)mGy] ( P<0.01). The single screw placement time, total screw placement time, incision length and intraoperative blood loss were (3.5±0.4)minutes, (23.9±0.5)minutes, (9.1±2.4)cm and (422.2±30.4)ml respectively, which were significantly longer or more than those in the robot group [(2.6±0.2)minutes, (17.9±0.7)minutes, (6.6±2.6)cm and (360.3±56.3)ml] ( P<0.01). There was no significant difference in the length of hospital stay between the two groups ( P>0.05). No significant differences were observed in the height of the intervertebral space, Cobb angle, sliding distance between the vertebral bodies and ASIA grade between the two groups ( P>0.05). At 3 days after surgery, the height of intervertebral space, Cobb angle, sliding distance between vertebral bodies and ASIA grade in both groups were significantly improved when compared with those before surgery ( P<0.05 or 0.01). There were no significant differences in VAS, JOA scores or NDI between the two groups before surgery, at 3 days, 3 months after surgery and at the last follow-up ( P>0.05). The VAS, JOA scores and NDI in both groups were gradually improved at 3 days, 3 months and at the last follow-up after surgery when compared with those before surgery ( P<0.05). There was no significant difference in the accuracy of screw placement of levels 0 and 0+1 between the two groups ( P>0.05). No significant difference in the intraoperative invasion rate of adjacent facet joints between the two groups was found ( P>0.05). There were no serious complications such as infection or screw loosening after surgery in both groups. Conclusions:For lower cervical fracture and dislocation, although there are more advantages in total surgical duration, screw holding force and radiation control regarding the navigation system, and more outstanding performance in screw placement efficiency, incision length and intraoperative blood loss regarding the orthopedic robot, both of them can effectively rebuild the cervical structure, improve neurological function, relieve postoperative pain, improve screw placement accuracy and reduce facet joint injury and serious complications. Selection of the best auxiliary screw placement system should comprehensively consider patients′ conditions and the experience of the surgical team.

Acute symptomatic osteoporotic thoracolumbar compression fracture (ASOTLF) can lead to chronic low back pain, kyphosis deformity, pulmonary dysfunction, loss of mobility, and even life-threatening complications. Vertebral augmentation is currently the mainstream treatment method for this condition. In 2019, the Editorial Board of Chinese Journal of Trauma and the Spinal Trauma Group of Orthopedic Surgeons Branch of Chinese Medical Doctor Association collaboratively led the development of Clinical guideline for vertebral augmentation for acute symptomatic osteoporotic thoracolumbar compression fractures. Six years later, with advances in clinical diagnosis and treatment techniques as well as accumulating evidence in related fields, the 2019 guideline requires updating. To this end, the Spinal Trauma Group of Orthopedic Surgeons Branch of Chinese Medical Doctor Association, the Spinal Health Professional Committee of China Human Health Science and Technology Promotion Association, and the Minimally Invasive Orthopedics Professional Committee of Shaanxi Medical Doctor Association have organized experts in the field to develop the Clinical guideline for vertebral augmentation of acute symptomatic osteoporotic thoracolumbar compression fractures ( version 2025) , based on the latest evidence-based medical researches. This guideline incorporates 3 recommendations retained from the 2019 version with updated strength of evidence, along with 12 new recommendations. It provides recommendations from six aspects of diagnosis, pain management, treatment option selection, prevention of postoperative complications, anti-osteoporosis therapy, and postoperative rehabilitation, aiming to provide a reference for standard treatment of vertebral augmentation for ASOTLF in hospitals at all levels.

[This corrects the article DOI: 10.11909/j.issn.1671-5411.2017.08.005.].

OBJECTIVE: To explore and verify the effect and potential mechanism of Brucea javanica Seed Oil Emulsion Injection (YDZI) and Shengmai Injection (SMI) on peripheral microcirculation dysfunction in treatment of gastric cancer (GC). METHODS: The potential mechanisms of YDZI and SMI were explored through network pharmacology and verified by cellular and clinical experiments. Human microvascular endothelial cells (HMECs) were cultured for quantitative real-time polymerase chain reaction, Western blot analysis, and human umbilical vein endothelial cells (HUVECs) were cultured for tube formation assay. Twenty healthy volunteers and 97 patients with GC were enrolled. Patients were divided into surgical resection, surgical resection with chemotherapy, and surgical resection with chemotherapy combining YDZI and SMI groups. Forearm skin blood perfusion was measured and recorded by laser speckle contrast imaging coupled with post-occlusive reactive hyperemia. Cutaneous vascular conductance and microvascular reactivity parameters were calculated and compared across the groups. RESULTS: After network pharmacology analysis, 4 ingredients, 82 active compounds, and 92 related genes in YDZI and SMI were screened out. β-Sitosterol, an active ingredient and intersection compound of YDZI and SMI, upregulated the expression of vascular endothelial growth factor A (VEGFA) and prostaglandin-endoperoxide synthase 2 (PTGS2, P<0.01), downregulated the expression of caspase 9 (CASP9) and estrogen receptor 1 (ESR1, P<0.01) in HMECs under oxaliplatin stimulation, and promoted tube formation through VEGFA. Chemotherapy significantly impaired the microvascular reactivity in GC patients, whereas YDZI and SMI ameliorated this injury (P<0.05 or P<0.01). CONCLUSIONS YDZI and SMI ameliorated peripheral microvascular reactivity in GC patients. β-Sitosterol may improve peripheral microcirculation by regulating VEGFA, PTGS2, ESR1, and CASP9.
Humans ; Microcirculation/drug effects* ; Drugs, Chinese Herbal/administration & dosage* ; Stomach Neoplasms/physiopathology* ; Emulsions ; Male ; Plant Oils/administration & dosage* ; Brucea/chemistry* ; Middle Aged ; Female ; Drug Combinations ; Human Umbilical Vein Endothelial Cells/metabolism* ; Seeds/chemistry* ; Injections ; Vascular Endothelial Growth Factor A/metabolism* ; Aged ; Network Pharmacology