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.

Despite significant advances in the field of critical care medicine over the past three decades, veno-arterial extracorporeal membrane oxygenation (V-A ECMO) remains the primary temporary mechanical circulatory support modality for patients with acute severe circulatory failure. With the accumulation of clinical experience and the increasing maturity of operational techniques in V-A ECMO, its technical management—particularly hemodynamic management—has become a key factor influencing patient outcomes. To further improve patient survival, the Chinese Critical Care Ultrasound Study Group, in collaboration with the Hemodynamic Therapy of Critical Care Collaborative Group and the Critical Care Medicine Branch of the China International Exchange and Promotive Association for Medical and Health Care, organized experts in critical care medicine to develop the Consensus on Hemodynamic Management in Adult Veno-Arterial Extracorporeal Membrane Oxygenation (2026 Edition). Based on years of clinical experience and the latest evidence-based medical evidence, this consensus formulates 15 systematic recommendations covering the entire process of V-A ECMO, including initiation, management during support, and weaning, aiming to promote standardized application of hemodynamic management in V-A ECMO.

Objectives: . Idiopathic sudden sensorineural hearing loss (ISSNHL) is a significant cause of hearing loss. Intratympanic steroid injection (ITSI) is commonly used as an initial or salvage treatment; however, the lack of a standardized treatment protocol has resulted in variability in clinical practice. In addition, no efficient prediction model currently exists to support personalized management. Therefore, this study aimed to develop tailored management strategies for ISSNHL using a machine-learning model. Methods: . This retrospective multicenter cohort study was conducted between January 2015 and December 2020, with data analysis performed between January 2021 and March 2024. Patients were selected based on the International Classification of Diseases, 10th Revision criteria for ISSNHL, along with relevant medication and procedure codes. Patients with pure-tone audiogram results not meeting ISSNHL criteria, better initial hearing in the affected ear, an identifiable etiology, no post-treatment audiogram, or delayed treatment (>6 weeks) were excluded. We included 770 patients diagnosed with ISSNHL who received ITSI. The primary outcome was the area under the receiver operating characteristic curve for prediction performance. Recovery status was determined using the last pure-tone audiogram. Modeling was conducted on the Quanta for Medical Care AI platform using five machine-learning algorithms and a nested cross-validation framework, in which feature selection and hyperparameter tuning were performed in the inner folds and model performance was evaluated in the outer folds. Results: . A random forest classifier outperformed the other models in predicting hearing outcomes, achieving an area under the receiver operating characteristic curve of 0.788. Time to ITSI was the most influential treatment-related factor, with ITSI administered within 10 days of hearing loss being associated with better outcomes. This model can be used to provide personalized prognostic estimates under different treatment protocols. Conclusion . The machine-learning-based prediction model facilitates personalized treatment strategies and timely treatment adjustments for ISSNHL, thereby optimizing the likelihood of complete recovery.

ObjectiveType I interferon (IFN-I) signaling is essential for antiviral innate immunity, yet its sustained or excessive activation contributes to the pathogenesis of several autoimmune diseases and interferonopathies, such as systemic lupus erythematosus and Aicardi-Goutières syndrome. Current strategies targeting this pathway, exemplified by JAK inhibitors, act mainly on downstream signal transduction and provide limited direct control over upstream IFN-I production, while also carrying the risk of broad immunosuppression. Phyllanthus emblica L. has long been used in traditional medicine for inflammatory disorders, but the bioactive constituent responsible for its regulation of IFN-I signaling and the underlying molecular mechanism have not been clearly defined. This study aimed to identify the active anti-inflammatory component of P. emblica and to characterize its mechanism of action on the IFN-I pathway in macrophages. MethodsActive components ofP. emblica and their candidate targets were screened by network pharmacology using the TCMSP and DrugBank databases (oral bioavailability≥30%, drug-likeness≥0.18) and intersected with inflammation-related genes retrieved from public databases. The predicted interaction between EGCG and IFN-I pathway proteins (TBK1, IRF3, STAT1) was evaluated by molecular docking, with BX795 and GSK8612 used as reference TBK1 inhibitors. Mechanistic experiments were performed in THP-1-derived macrophages and primary bone marrow-derived macrophages (BMDM). Upstream signaling was activated by transfection of the nucleic acid analogs poly(I∶C) and poly(dA∶dT) or by lipopolysaccharide (LPS) stimulation, whereas downstream signaling was activated by exogenous IFN-β. An siRNA-mediated TREX1 knockdown model was used to mimic endogenous nucleic acid-driven interferonopathy. Expression of IFN-β1 and interferon-stimulated genes (ISGs) was measured by RT-qPCR, protein phosphorylation by Western blot, and IFN-β secretion by ELISA. Cellular thermal shift assay (CETSA) and drug affinity responsive target stability (DARTS) were used to probe the interactionbetween EGCG and IRF3. ResultsNetwork pharmacology identified (-)-epigallocatechin-3-gallate (EGCG) as a candidate IFN-I-suppressive constituent of P. emblica, with predicted binding to TBK1, IRF3, and STAT1. Molecular docking yielded binding energies of -9.2, -7.2, and -8.2 kcal/mol for TBK1, IRF3, and STAT1, respectively, indicating an affinity for TBK1 comparable to that of the reference inhibitors BX795 (-5.7 kcal/mol) and GSK8612 (-6.4 kcal/mol). EGCG suppressed IFN-β1 and ISG mRNA expression under poly (I∶C), poly (dA∶dT), and LPS stimulation in both THP-1 macrophages and BMDM. At the protein level, EGCG reduced the phosphorylation of TBK1 and IRF3 without affecting the levels of the upstream sensors cGAS and RIG-I, and lowered IFN-β secretion in a concentration-dependent manner. CETSA and DARTS showed that EGCG did not enhance the thermal stability or protease resistance of IRF3, indicating that its effect on IRF3 is indirect. Following IFN-β stimulation, prolonged EGCG treatment reduced STAT1 phosphorylation in a time-dependent manner without an apparent change in IRF9, and partially attenuated ISG transcription; this effect was not monotonicly concentration-dependent, and CXCL10 showed the most consistent suppression. In TREX1-knockdown cells, the elevated mRNA levels of ISG15, ISG56, and CXCL10 were reduced by EGCG. ConclusionEGCG suppresses IFN-I responses by concurrently inhibiting TBK1-IRF3-dependent IFN‑β production and JAK-STAT1-mediated downstream transcription. These in vitro findings provide a mechanistic basis for the anti-inflammatory use of P. emblica in traditional medicine and identify EGCG as a candidate for further evaluation in interferon-driven autoimmune disease models.

Objective To evaluate the drug-loading performance,biocompatibility,bone tissue compati-bility,and therapeutic efficacy of vancomycin(VA)-loaded hydroxyapatite(HA)/β-tricalcium phosphate(β-TCP)scaffolds in treating infectious bone defects in mice.Methods HA/β-TCP scaffolds were fabricated by using 3D printing technology,and VA was loaded onto the scaffolds via freeze-drying to create the composite VA/HA/β-TCP scaffolds.The scaffolds were observed by using scanning electron microscopy(SEM),and their encapsulation efficiency,drug-loading capacity,and release kinetics were assessed.An in vitro co-culture system was established with mouse embryonic osteoblasts(MC3T3-E1)and the scaffolds,The cells were di-vided into the control group(HA/β-TCP scaffolds)and the VA/HA/β-TCP group.Cell viability was assessed by using the methyl thiazolyl tetrazolium(MTT)assay,and osteocalcin(OCN)expression levels were meas-ured by ELISA at 7,12,and 14 days of co-culture.Antibacterial activity was evaluated through adhesion ex-periments.A mouse cranial defect model was constructed and implanted with the scaffolds for 4 weeks.Hema-toxylin and eosin(HE)staining was performed to observe material degradation and bone formation in the sur-rounding tissues.Results The VA/HA/β TCP scaffolds exhibited uniform pore size distribution and excel-lent drug-loading performance,with an encapsulation efficiency of 70.32％and an actual drug-loading rate of 30.53％,effectively loading VA.The scaffolds sustained VA release over 36 hours.Compared to the control group,MC3T3-E1 cell viability on the VA/HA/β-TCP scaffolds was significantly inhibited at 7 and 12 days of co-culture(P＜0.01),but no significant difference in proliferation activity was observed between the two groups after 14 days(P＞0.05).No significant differences in OCN expression levels were found in MC3T3-E1 cells on the VA/HA/β-TCP scaffolds compared to the control group at any time point(P＞0.05).The VA/HA/β-TCP scaffolds demonstrated strong antibacterial properties,with significantly reduced numbers of Escherichia coli in the co-cultured bacterial solution and on the scaffold surface compared to the control group(P＜0.001).Compared with the control group,the VA/HA/β-TCP group demonstrated significantly reduced cranial hemorrhage and inflammatory infiltration,alongside a marked increase in new bone tissue.Conclusion The VA/HA/β-TCP scaffolds exhibit excellent drug-loading performance,controlled drug re-lease,biocompatibility,antibacterial activity,and bone tissue compatibility,offering a novel approach for trea-ting bone infections.

Objective To explore the regulatory effect of corilagin(COR)on Nod-like receptor family pyrin domain-containing protein 3(NLRP3)inflammasome activation and chondrocyte pyroptosis induced by lipopolysaccharide(LPS)combined with nigericin(NIG).Methods Primary chondrocytes isolated from C57BL/6J mice were cultured to passage 3 for experiments.Cells were divided into control group,LPS group,LPS+NIG group,and LPS+NIG+COR(low-,medium-,and high-dose)groups.The chondrocytes were pre-sensitized with LPS for 4 h.Then the cells were treated with COR at different concentrations(10,20,and 40 μmol/L)for 30 min,and finally NIG(10 μmol/L)was supplemented for 1 h.Control cells were cultured in DMEM/F-12 medium supplemented with 1%FBS.Cell counting kit 8(CCK-8)was used to detect the effect of COR at different concentrations(10,20,40 μmol/L)on chondrocyte viability.Propidium iodide(PI)and Hoechst 33342 staining and lactate dehydrogenase(LDH)release assay were used to analyze the effect of COR on chondrocyte death induced by LPS and NIG.Western blotting was used to detect the expression of the NLRP3 inflammasome activation marker cysteine aspartic acid specific protease 1(caspase 1)p20 in the cell supernatant and NLRP3,apoptosis-associated speck-like protein(ASC),caspase 1,interleukin-1β precursor(pro-IL-1β),and pyroptosis execution protein gasdermin D(GSDMD)in the cell lysate.Enzyme-linked immunosorbent assay was used to detect the level of IL-1β in cell culture supernatant.Reactive oxygen species(ROS)fluorescent probe 2',7'-dichlorodihydrofluorescein diacetate(H2DCFDA)staining was used to observe the effect of COR on ROS production,and Western blotting was used to detect the expression of intracellular glycolysis-related proteins hexokinase 2(HK2),glucose transporter 1(GLUT1),and lactate dehydrogenase A(LDHA).Results COR exhibited slight effect on chondrocyte viability at the concentration≤40 μmol/L.COR(10-40 μmol/L)reduced the proportion of PI-positive cells(all P＜0.05)and the release of LDH(all P＜0.01)stimulated by LPS and NIG,inhibited the expression of GSDMD N-terminus domain in chondrocytes,and reduced the release of caspase 1 p20 and IL-1β from chondrocytes(all P＜0.01).Furthermore,COR(40 μmol/L)reduced the production of ROS(compared with the control group,P＜0.01)and inhibited the expression of glycolysis-related proteins HK2,GLUT1,and LDHA(all P＜0.05).Conclusion COR can inhibit NIG-induced glycolysis/ROS/NLRP3 signaling,thereby preventing NLRP3 inflammasome activation and chondrocyte pyroptosis.

Objective To investigate the effects of long-term radiofrequency(RF)radiation at 2.65 GHz on behavior,inflammatory response,and intestinal microecology in mice in order to provide a basis for the safety assessment of long-term RF exposure.Methods One hundred and eight male C57BL/6N mice(17～21 g,6～8 weeks old)were randomly assigned to a control group(Con)and a RF exposure group.The mice of the RF exposure group were subjected to whole-body uniform exposure to 2.65 GHz RF radiation in an electromagnetic reverberation chamber for 3 h/day for 28 consecutive days.RF field distribution and changes in core body temperature were monitored using an electromagnetic radiation analyzer and a fiber-optic temperature probe,respectively.Cognitive function was assessed using the Y-maze and novel object recognition(NOR)test.Anxiety-like behaviors were evaluated through open field test(OFT)and elevated plus maze(EPM),while depressive-like behaviors were examined with sucrose preference test(SPT)and tail suspension test(TST).HE staining was used to observe the histopathological changes in mouse tissues.Radioimmunoassay(RIA)was employed to detect the expression of pro-inflammatory cytokines,TNF-α and IL-1 β,as well as anti-inflammatory cytokines,IL-4 and IL-10 in the serum,brain,jejunum,and spleen samples.Additionally,metagenomic sequencing was performed to assess alterations in the gut microbiota composition.Results Long-term RF radiation led to a maximal increase of 0.59℃in the core body temperature,but had no significant effects on cognitive function,anxiety-like behaviors,or depressive-like behaviors,or apparent damage of the hippocampal or jejunal tissues in the exposed mice.However,RF exposure significantly up-regulated the expression of the pro-inflammatory cytokine TNF-α in serum(P<0.05),and did not significantly alter the concentrations of other cytokines(IL-1β,IL-4,IL-10),caused significant decrease in α-diversity of the intestinal microbiota(P<0.01),with reduced relative abundances of Ligilactobacillus murinus and Acetatifactor muris(P<0.05),while elevated abundances of Lachnospiraceae bacterium(P<0.01).Conclusion Long-term exposure to 2.65 GHz RF radiation induces systemic inflammatory responses and disrupts gut microbiota homeostasis in mice.

The blue fluorescent carbon dots(TMCDs)and cyan fluorescent carbon dots(TMCDs-H2O)were synthesized fromm-phenylenediamine and tricarballylic acid through air-assisted melting polymerization and one-step hydrothermal method,respectively.Air purging could effectively inhibit the side reactions and reduce the derivative structures in the carbon dots product.The structure and morphology of these two materials were systematically characterized using liquid nuclear magnetic resonance spectroscopy(NMR),mass spectrometry(MS),and transmission electron microscopy.Compared to TMCDs-H2O((3.12±0.63)nm),TMCDs showed a smaller average particle size(approximately(1.85±0.02)nm).The NMR and MS analysis revealed that although the main structure of both types of carbon dots was similar,TMCDs exhibited a simpler structure with higher degree of polymerization.These results suggested that supramolecular interactions might introduce numerous small molecule derivatives into TMCDs-H2O particles,resulting in lower polymerization degree,multiple substructures,and larger particle size characteristics for this material.When employed as chemical sensors for metal ion detection,in the linear range of 1×10-5-5×10-4 mol/L,the detection limits of Fe3+by TMCDs and TMCDs-H2O were 3.3×10-6 mol/L and 3.8×10-6 mol/L,respectively.The experimental results demonstrated that the recoveries of CDs and inductively coupled plasma optical emission spectrometer(ICP-OES)were similarity,whereas TMCDs displayed a considerable relative standard deviation.This study demonstrated that endogenously derived structures in CDs could enhance the performance of metal ion sensing.

In this work,with tris(4-aminophenyl)amine(TAPA)and 1,3,5-tris(4-formylphenyl)benzene(TFPB)as monomers,an imine-type porous organic polymer,TAPA-TFPB,was synthesized using a simple method under the catalysis of acetic acid.The material TAPA-TFPB was used as solid-phase extraction adsorbent and combined with ultra-performance liquid chromatography/quadrupole time-of-flight-tandem mass spectrometry(UHPLC-QTOF-MS)to establish a detection method for four kinds of nitrofuran metabolites(NFMs)residues in meat samples.The parameters of the adsorbent dosage,the pH value and volume of sample,and the type and volume of washing and eluent solvents were optimized,respectively.Under the optimal extraction conditions,low detection limits(0.11-1.60 μg/kg)were achieved for four kinds of NFMs.At three different spiked levels,the intra-day and inter-day precisions(Relative standard deviations)were 2.8% -10.9% and 4.3% -16.2%,respectively,and the spiked recoveries were 72.0% -107.2%.The results showed that the method chould be used for efficient extraction and analysis of trace NFMs residues in meat samples,indicating that TAPA-TFPB was a kind of promising SPE adsorbent.