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.

Background: High-mobility group box protein 1 (HMGB1) is a chromatin-binding protein involved in arthritis, ischemia, sepsis, atherosclerosis, neurodegenerative disorders, meningitis, and cancer. HMGB1 exhibits dual roles in cancer, acting as either a tumor suppressor or oncoprotein depending on context. Objective: This research aimed to elucidate HMGB1’s functional significance in cutaneous squamous cell carcinoma (cSCC). Methods: We overexpressed HMGB1 in cSCC cell lines using recombinant adenovirus and examined its effects on cell proliferation, colony formation, and cell migration. Results: Immunohistochemical analysis revealed elevated HMGB1 expression levels in cSCC tissue relative to normal epidermis. To assess the influence of HMGB1, we employed recombinant adenoviruses expressing HMGB1 to transduce SCC cell lines (SCC12 and SCC13). Enhanced HMGB1 expression significantly promoted cellular proliferation and colony formation capacity.Notably, HMGB1 overexpression elevated the levels of proliferation regulators, including P63, SOX2, CDK4 and CDK6. Furthermore, HMGB1 overexpression substantially enhanced tumor invasiveness, accompanied by upregulation of epithelial-mesenchymal transition (EMT) biomarkers. Mechanistically, overexpression of HMGB1 enhanced transforming growth factor-β signaling by increasing phosphorylation of SMAD2/3, the key mediators of EMT. Conclusion These data imply that HMGB1 acts as a tumor-promoting factor in cSCC.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

Objective To investigate the alterations of cerebral blood flow(CBF)in type 2 diabetic mellitus(T2DM) patients without cognitive impairment by using arterial spin labeling(ASL)technique.Methods A total of 23 T2DM patients without cognitive impairment and 23 healthy controls(HC)matched by age,sex,and education attainment were recruited.Their clinical data were collected,and neuropsychological tests and cerebral magnetic resonance imaging were performed.Then,the outcomes of clinical features,neuropsychological tests,and global and regional CBF were compared between the two groups.The significant regional zCBF(z-transformed relative CBF)values were extracted and correlated with clinical data and neuropsychological scores in T2DM patients,controlling age,sex,and education.Results No significant difference was found in whole brain CBF between the two groups(P=0.155),while significantly higher CBF was identified in the left superior temporal gyrus and left insula in the T2DM group(Gaussian random field correction,initial threshold P < 0.001,cluster level P < 0.05).No correlation was observed between the significant regional zCBF values and the clinical data or the neuropsychological scores in T2DM patients(all P>0.05).Conclusion Alterations in cerebral hemodynamics may precede cognitive function changes in T2DM,suggesting that the ASL technique is promising for early monitoring of cerebral hemodynamic changes associated with cognitive impairment in patients with T2DM.
Humans ; Diabetes Mellitus, Type 2/physiopathology* ; Cerebrovascular Circulation ; Middle Aged ; Male ; Female ; Magnetic Resonance Imaging ; Case-Control Studies ; Cognitive Dysfunction ; Neuropsychological Tests ; Aged

Objective To investigate the correlation of monocyte count(MONO)to high density lipopro-tein-cholesterol(HDL-C)ratio(MHR)and systemic immune-inflammation index(SII)with diabetic retinop-athy(DR).Methods Patients with type 2 diabetes mellitus(T2DM)admitted to the hospital from June 2020 to May 2023 were selected as the research objects.According to the presence or absence of DR,the patients were divided into non-retinopathy group(NDR group)and DR Group.The differences in basic information,blood routine,and biochemical indexes between the two groups were analyzed,and the MHR and SII were cal-culated.Multivariate Logistic regression was used to analyze the risk factors for DR.Spearman correlation a-nalysis was used to analyze the correlation between risk factors and DR.The receiver operating characteristic(ROC)curve was used to evaluate the value of MHR and SII in predicting DR in T2DM patients.Results A total of 291 T2DM patients were enrolled,including 135 patients in the NDR group and 156 patients in the DR group.Compared with the NDR group,duration of diabetes was significantly prolonged(P<0.05),glycosy-lated hemoglobin(HbA1c),creatinine,fasting plasma glucose(FPG),total cholesterol(TC),platelet count(PLT),MHR and SII were increased(P<0.05),and high density lipoprotein-cholesterol(HDL-C)was de-creased(P<0.05)in the DR Group.Spearman correlation analysis showed that DR was positively correlated with duration of diabetes,FPG,HbA1c,PLT,MHR and SII(P<0.05),and negatively correlated with HDL-C(P<0.05).Multivariate Logistic regression analysis showed that gender(OR=0.151,95%CI 0.052-0.432,P<0.001),history of heavy drinking(OR=7.199,95%CI 2.845-18.216,P<0.001),duration of di-abetes(OR=1.570,95%CI 1.354-1.821,P<0.001),HbA1c(OR=1.218,95%CI 1.013-1.464,P=0.036),MHR(OR=1.054,95%CI 1.028-1.080,P<0.001)and SII(OR=1.002,95%CI 1.001-1.003,P=0.002)were independent influencing factors for DR patients.ROC curve analysis showed that the area un-der the curve(AUC)of MHR and SII in predicting the development of T2DM to DR was 0.696 and 0.567,re-spectively.The AUC of MHR and SII combined in predicting DR was 0.702.Conclusion MHR and SII are closely related to the incidence of DR,and both have certain predictive value for DR,and the predictive value of the combined of MHR and SII is higher.

OBJECTIVE: To investigate the anti-tumor effects of cinobufacini (CINO) on hepatocellular carcinoma (HCC) induced by des-gamma-carboxy-prothrombin (DCP) and to uncover the underlying mechanisms. METHODS: The inhibitory effect of CINO on HCC cell proliferation was evaluated using the cell counting kit-8 method, and the apoptosis rate was quantified using flow cytometry. Immunofluorescence and Western blot analyses were used to investigate the differential expression of proteins associated with cell growth, apoptosis, migration, and invasion pathways after CINO treatment. The therapeutic potential of CINO for HCC was confirmed, and the possibility of combining cinobufacini with c-Met inhibitor for the treatment of primary HCC was further validated by in vivo experiments. RESULTS: Under the induction of DCP, CINO inhibited the activity of HCC cells, induced apoptosis, and inhibited migration and invasion. Upon the induction of DCP, CINO regulated c-Met activation and the activation of the phosphatidylinositol-3 kinase/protein kinase B (PI3K/AKT) and mitogen-activated protein kinase kinase/extracellular signal-regulated kinase (MEK/ERK) pathways. In a mouse model of HCC, CINO exhibited significant antitumor effects by inhibiting the phosphorylation of c-Met and the downstream PI3K/AKT and MEK/ERK pathways in tumor tissues. CONCLUSIONS CINO inhibited HCC cell growth, promoted apoptosis, and suppressed HCC cell invasion and migration by targeting c-Met and PI3K/AKT and MEK/ERK signaling pathways under DCP induction.
Carcinoma, Hepatocellular/drug therapy* ; Proto-Oncogene Proteins c-met/metabolism* ; Liver Neoplasms/drug therapy* ; Signal Transduction/drug effects* ; Animals ; Humans ; Cell Movement/drug effects* ; Apoptosis/drug effects* ; Cell Proliferation/drug effects* ; Amphibian Venoms/therapeutic use* ; Cell Line, Tumor ; Neoplasm Metastasis ; Cell Survival/drug effects* ; Proto-Oncogene Proteins c-akt/metabolism* ; Phosphatidylinositol 3-Kinases/metabolism* ; Neoplasm Invasiveness ; Mice, Inbred BALB C ; Mice, Nude ; Mice ; Male ; Bufanolides/therapeutic use* ; Protein Precursors ; Prothrombin ; Biomarkers

OBJECTIVE: To investigate the therapeutic potential of pseudolaric acid B (PAB) on non-alcoholic fatty liver disease (NAFLD) and its underlying molecular mechanism in vitro and in vivo. METHODS: Eight-week-old male C57BL/6J mice (n=32) were fed either a normal chow diet (NCD) or a high-fat diet (HFD) for 8 weeks. The HFD mice were divided into 3 groups according to a simple random method, including HFD, PAB low-dose [10 mg/(kg·d), PAB-L], and PAB high-dose [20 mg/(kg·d), PAB-H] groups. After 8 weeks of treatment, glucose metabolism and insulin resistance were assessed by oral glucose tolerance test (OGTT) and insulin tolerance test (ITT). Biochemical assays were used to measure the serum and cellular levels of total cholesterol (TC), triglycerides (TG), aspartate aminotransferase (AST), alanine aminotransferase (ALT), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C). White adipose tissue (WAT), brown adipose tissue (BAT) and liver tissue were subjected to hematoxylin and eosin (H&E) staining or Oil Red O staining to observe the alterations in adipose tissue and liver injury. PharmMapper and DisGeNet were used to predict the NAFLD-related PAB targets. Peroxisome proliferator-activated receptor alpha (PPARα) pathway involvement was suggested by Kyoto Encyclopedia of Genes and Genomes (KEGG) and search tool Retrieval of Interacting Genes (STRING) analyses. Luciferase reporter assay, cellular thermal shift assay (CETSA), and drug affinity responsive target stability assay (DARTS) were conducted to confirm direct binding of PAB with PPARα. Molecular dynamics simulations were applied to further validate target engagement. RT-qPCR and Western blot were performed to assess the downstream genes and proteins expression, and validated by PPARα inhibitor MK886. RESULTS: PAB significantly reduced serum TC, TG, LDL-C, AST, and ALT levels, and increased HDL-C level in HFD mice (P<0.01). Target prediction analysis indicated a significant correlation between PAB and PPARα pathway. PAB direct target binding with PPARα was confirmed through luciferase reporter assay, CETSA, and DARTS (P<0.05 or P<0.01). The target engagement between PAB and PPARα protein was further confirmed by molecular dynamics simulations and the top 3 amino acid residues, LEU321, MET355, and PHE273 showed the most significant changes in mutational energy. Subsequently, PAB upregulated the genes expressions involved in lipid metabolism and mitochondrial biogenesis downstream of PPARα (P<0.05 or P<0.01). Significantly, the PPARα inhibitor MK886 effectively reversed the lipid-lowering and PPARα activation properties of PAB (P<0.05 or P<0.01). CONCLUSION PAB mitigates lipid accumulation, ameliorates liver damage, and improves mitochondrial biogenesis by binding with PPARα, thus presenting a potential candidate for pharmaceutical development in the treatment of NAFLD.
Animals ; PPAR alpha/metabolism* ; Non-alcoholic Fatty Liver Disease/pathology* ; Male ; Mice, Inbred C57BL ; Lipid Metabolism/drug effects* ; Diterpenes/therapeutic use* ; Organelle Biogenesis ; Diet, High-Fat ; Humans ; Mice ; Liver/metabolism* ; Insulin Resistance ; Mitochondria/metabolism* ; Molecular Docking Simulation

Mesenchymal stem cells (MSCs) have been widely used in the treatment of various autoimmune and inflammation-related diseases due to their potent immunomodulatory properties. Several studies have demonstrated that MSC-mediated immunomodulation is complex and bidirectional, with the in vivo microenvironment influencing the direction of this modulation. Indoleamine-2,3-dioxygenase (IDO), an immunosuppressive factor, has been identified as a key "switch" in the immunomodulatory role of MSCs. In this review, we explore how IDO functions as a critical regulator of MSC immunoregulatory plasticity. We delve into the mechanisms by which changes in IDO expression affect the function of various immune cells, summarize relevant research and clinical advances regarding the role of IDO expression in MSC-based therapies for various diseases, and discuss potential therapeutic strategies that target IDO to enhance the stability of MSC therapeutic effects. This provides a theoretical foundation for optimizing MSCs as safer and more effective clinical therapeutic agents.