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.

Mice ; Animals ; Tandem Mass Spectrometry ; Alpha-Amanitin ; Chromatography, Liquid ; Metabolomics ; Chromatography, High Pressure Liquid/methods*

OBJECTIVE: To explore the genetic basis for two patients from a family with BCL11A-related intellectual disability (BCL11A-ID). METHODS: Clinical data of the proband and her family members was analyzed. Chromosomal karyotyping analysis, trio-whole exome sequencing (trio-WES) and copy number variation sequencing (CNV-seq) were carried out. For the suspected genetic variants, Sanger sequencing was used to verify, and pathogenicity assessment was conducted. RESULTS: The proband and her mother both had intellectual and language impairment, and their fetal hemoglobin (HbF) was significantly elevated. A heterozygous c.1327_c.1328delTC (p.Ser443Hisfs*128) variant was found in exon 4 of the BCL11A gene by WES, which has resulted in truncated expression of the encoded protein, and Sanger sequencing has verified that the variant was inherited from the mother. The variant was not found in related databases. The variant was predicted as pathogenic according to the guidelines from the American College of Medical Genetics and Genomics (ACMG) (PVS1+PM2+PP1). No karyotypic abnormality was found in the proband, her parents and brother, and no pathogenic CNVs was found in the proband and her parents. CONCLUSION The c.1327_c.1328delTC (p.Ser443Hisfs*128) variant may underlay the BCL11A-ID in the proband and her mother. This de novo variant has expanded the mutational spectrum of the BCL11A gene.
Humans ; Male ; Female ; Intellectual Disability/genetics* ; DNA Copy Number Variations ; Pedigree ; Mutation ; Transcription Factors/genetics* ; Mothers ; Repressor Proteins/genetics*

OBJECTIVE: To investigate the expression level and prognostic value of miR-21, miR-18a, miR-146a, and Let-7b derived from serum exosomes in patients with multiple myeloma (MM). METHODS: Serum exosomes were extracted from 57 MM patients and 20 healthy persons using ExoQuick exosome precipitation solution kit, and the relative expression level of miR-21, miR-18a, miR-146a, and Let-7b derived from serum exosomes was measured by RT-qPCR. Correlations of the expression levels of all miRNAs mentioned above with routine laboratory parameters were analyzed by Spearman correlation analysis. The relationship between the expression level of miR-21, miR-18a, miR-146a, and Let-7b derived from serum exosomes and overall survival of patients with MM was analyzed using the Kaplan-Meier survival curve. RESULTS: The expression levels of miR-21, miR-18a, and Let-7b derived from serum exosomes in patients with MM were significantly lower than those in the normal control group (P<0.001), while the expression level of miR-146a between the two groups was not significantly different (P>0.05). The expression level of miR-21 was strongly negatively correlated with serum β₂-microglobulin concentration (r=-0.830), and weakly negatively correlated with serum creatinine, corrected serum calcium, and cystatin C (r=-0.488, -0.282, -0.627). The expression levels of Let-7b and miR-18a were also weakly negatively correlated with the corrected serum calcium, β₂-microglobulin, and cystatin C concentration (r=-0.305, -0.362, -0.461; -0.317, -0.542, -0.434). However, there was no significant correlation between the expression level of miR-146a and routine laboratory parameters in MM patients. The overall survival rate of MM patients with low expression level of miR-21, miR-18a, and Let-7b significantly decreased compared with high expression level group (P<0.05), however, the expression level of miR-146a was not related to the overall survival rate. CONCLUSION Aberrant low expression levels of miR-21, miR-18a, and Let-7b derived from serum exosomes exist in patients with MM, which are associated with a worse overall survival rate.
Calcium/metabolism* ; Creatinine/metabolism* ; Cystatin C/metabolism* ; Exosomes/metabolism* ; Humans ; MicroRNAs/metabolism* ; Multiple Myeloma/metabolism*

Objective:To investigate the detecting method and clinical characteristics of anti-nodal/paranodal antibodies in chronic inflammatory demyelinating polyradiculopathy.Methods:Serum samples were collected from 212 patients with chronic inflammatory demyelinating polyradiculopathy who were admitted to Huashan Hospital of Fudan University or from other clinical centers from January 2018 to July 2021. Autoantibodies (anti-NF155, anti-NF186, anti-CNTN1) and IgG subtypes were detected with cell-based assay. According to the test results, patients were divided into anti-NF155 positive group, anti-NF186 positive group and anti-CNTN1 positive group, clinical characteristics of patients in each group, including limb weakness, superficial sensation and proprioception, tremor, cerebrospinal fluid protein level, brachial plexus magnetic resonance (MRI) were retrospectively analyzed and compared.Results:A total of 23 patients (10.8%,23/212) were positive for anti-NF155 antibody, 12 (5.7%,12/212) for anti-NF186 antibody, and 4 (1.9%,4/212) for anti-CNTN1 antibody. IgG 4 was the predominant subtype in anti-NF155 and anti-CNTN1 groups. In the anti-NF186 group, all cases were IgG positive and antibody subtypes could be detected in 4 cases (4/12). In anti-NF155 group, 23 patients (100%,23/23) had limb weakness and deep sensory disturbance, 19 patients (82.6%,19/23) had superficial sensory disturbance, 22 patients (95.7%,22/23) were symmetrically involved, 18 patients (78.3%,18/23) showed tremor, 19 patients (19/19) showed abnormal in brachial plexus MRI. In anti-NF186 group, 12 patients had limb weakness (12/12), 9 patients (9/12) and 6 patients (6/12) had superficial sensory disturbance and deep sensory disturbance respectively, 8 patients (8/12) were asymmetrically involved, and only 1 patient (1/12) showed tremor, 1 (1/7) showed abnormal brachial plexus MRI. In anti-CNTN1 group, 4 cases showed symmetrical limb weakness and sensory disturbance, 3 patients had tremor, and four patients showed brachial plexus MRI abnormality. There were statistically significant differences in onset age, proprioception, tremor and MRI abnormalities of brachial plexus among the 3 groups ( P<0.01). Conclusions:The clinical characteristics of CIDP patients with anti-NF155, anti-NF186 and anti-CNTN1 antibodies are different. Screening anti-nodal/paranodal antibodies is of great significance for accurate diagnosis and treatment of patients with peripheral neuropathy.

Localized peripheral neuropathy amyloidosis is a rare disease that mainly occurred in elder people who present with focal neurological symptoms. AL is the main type of amyloid protein. Biopsy is the golden standard for diagnosis. Mass spectrometry and immunohistochemical analysis help to confirm the type of amyloid protein. This paper retrospectively analyzes the clinical and imaging data, auxiliary examinations, histological, and immunohistochemical markers. The patient, a 34-year-old woman, presented with a right neck mass and weakness of the right arm. Brachial plexus magnetic resonance imaging (MRI) showed a tumor-like lesion in the nerve root at C5 and C6 and in upper trunk. Electrophysiological studies revealed damage in the upper trunk of the brachial plexus. Positive staining with Congo red was found in brachial plexus biopsy. Mass spectrometry showed that the type of amyloid protein was AHL(G-λ). The patient underwent nerve graft for treatment. Meanwhile, literature review revealed that the average onset age of localized spinal nerve amyloidosis was 62.4 years old.The radial nerve was the most susceptible, followed by the lumbosacral plexus. Fifty percent of the type of amyloid protein is AL.Until now, no consolidated treatment is available. Here, we summarize the clinical characteristics of localized peripheral neuropathy amyloidosis in order to raise the awareness of the disease.

TANK-binding kinase 1 (TBK1), a core kinase of antiviral pathways, activates the production of interferons (IFNs). It has been reported that deacetylation activates TBK1; however, the precise mechanism still remains to be uncovered. We show here that during the early stage of viral infection, the acetylation of TBK1 was increased, and the acetylation of TBK1 at Lys241 enhanced the recruitment of IRF3 to TBK1. HDAC3 directly deacetylated TBK1 at Lys241 and Lys692, which resulted in the activation of TBK1. Deacetylation at Lys241 and Lys692 was critical for the kinase activity and dimerization of TBK1 respectively. Using knockout cell lines and transgenic mice, we confirmed that a HDAC3 null mutant exhibited enhanced susceptibility to viral challenge via impaired production of type I IFNs. Furthermore, activated TBK1 phosphorylated HDAC3, which promoted the deacetylation activity of HDAC3 and formed a feedback loop. In this study, we illustrated the roles the acetylated and deacetylated forms of TBK1 play in antiviral innate responses and clarified the post-translational modulations involved in the interaction between TBK1 and HDAC3.

Objective: To evaluate the associations of sarcopenia, handgrip strength and calf circumference with cognitive impairment among Chinese older adults. Methods: Totally 2,525 older adults were recruited from the Healthy Aging and Biomarkers Cohort Study. Cognitive impairment was assessed by the Chinese Mini-Mental State Examination. Handgrip strength was calculated from the means of the right and left hand values. Calf circumference was measured at the site of maximum circumference of the non-dominant leg. The formula developed by Ishii was used to define sarcopenia. Multiple logistic regression was performed to evaluate the associations of sarcopenia, handgrip strength, and calf circumference with cognitive impairment. Results: The prevalence of cognitive impairment was 34.36%. The adjusted odds ratio ( Conclusion Sarcopenia, identified by low handgrip strength and low calf circumference, was positively associated with cognitive impairment.
Aged ; Aged, 80 and over ; China/epidemiology* ; Cognitive Dysfunction/etiology* ; Female ; Hand Strength ; Humans ; Leg/anatomy & histology* ; Logistic Models ; Male ; Sarcopenia/pathology*