ObjectiveTo observe the effects of Yiqi Huoxue Jiedu formula（YHJF） on immune cell exhaustion in the spleen of septic mice and to explore and validate its potential intervention targets. MethodsMice were randomly divided into the sham-operated， model， low-dose YHJF（4.1 g·kg^-1）， and high-dose YHJF（8.2 g·kg^-1） groups. Except for the sham-operated group， a cecal ligation and puncture（CLP） procedure was performed to establish a mouse sepsis model. The treatment groups received oral administration of the corresponding doses， while the sham-operated and model groups received an equal volume of physiological saline. After the intervention， the 7-day survival rate of each group was recorded， and spleen samples were collected 72 h post-intervention， and the spleen index was calculated. Terminal deoxynucleotidyl transferase deoxyuridine triphosphate（dUTP） nick end labeling（TUNEL） staining was used to detect apoptosis in spleen cells. Enzyme-linked immunosorbent assay（ELISA） was performed to measure the levels of interleukin（IL）-4 and IL-10 in the serum. Transcriptomics and metabolomics were used to screen for differentially expressed genes（DEGs） and differential metabolites in the spleen， followed by bioinformatics analysis to identify key targets. Real-time quantitative polymerase chain reaction（Real-time PCR）， flow cytometry， and multiplex immunofluorescence were used to verify the expressions of key genes and proteins. ResultsThe high-dose YHJF group significantly improved the 7-day survival rate of septic mice（P0.05）. Compared with the sham-operated group， the model group showed a significant increase in apoptosis of spleen cells and a decrease in the spleen index at 72 h post-modeling， with markedly elevated peripheral serum IL-4 and IL-10 levels（P0.01）. Compared with the model group， the high-dose YHJF group showed a reduction in apoptosis of spleen cells， an increase in the spleen index， and a significant decrease in peripheral serum IL-4 and IL-10 levels（P0.05）. Spleen transcriptomics identified 255 DEGs between groups， potentially serving as intervention targets for YHJF. Gene Ontology（GO） enrichment analysis revealed that DEGs were mainly involved in biological processes such as natural killer（NK） cell-mediated positive immune regulation， cell killing， cytokine production， positive regulation of innate immune cells， and interferon production. Kyoto Encyclopedia of Genes and Genomes（KEGG） pathway enrichment analysis showed that DEGs were mainly involved in cytokine-cytokine receptor interactions， viral protein interactions with cytokines and cytokine receptors， chemokine signaling pathway， and nuclear transcription factor-κB（NF-κB） signaling pathway. Protein-protein interaction（PPI） network analysis identified CD160， granzyme B（GZMB）， and chemokine ligand 4（CCL4） as key targets for YHJF in treating sepsis. Metabolomics identified 46 differential metabolites that were significantly reversed by YHJF intervention， and combined transcriptomics and metabolomics analysis identified 17 differential metabolites closely related to CD160. Pathway enrichment revealed that these metabolites were mainly involved in glycerophospholipid metabolism， arachidonic acid metabolism， glycosylphosphatidylinositol（GPI） anchor biosynthesis， linoleic acid metabolism， and α-linolenic acid metabolism pathways. Verification results showed that， compared with the sham-operated group， the model group exhibited significantly elevated CD160 mRNA expression level in the spleen， along with markedly decreased CCL4 and GZMB mRNA expression， and had a significant increase in CD160 expression on the surface of natural killer T（NKT） cells in the spleen（P0.01）. Compared with the model group， the high-dose YHJF group had a significant decrease in CD160 mRNA expression in the spleen， a significant increase in CCL4 and GZMB mRNA expressions. Further flow cytometry and immunofluorescence revealed that compared with the sham-operated group， CD160 expression on the surface of splenic NKT cells in the model group was significantly increased（P0.01）， while high-dose YHJF intervention significantly reduced CD160 expression（P0.01）. ConclusionYHJF may alleviate NKT cell exhaustion in sepsis by downregulating the expression of the negative co-stimulatory molecule CD160， and this regulatory effect is closely related to fatty acid metabolism pathways. This study provides new insights and targets for further exploration of strengthening vital Qi and detoxifying strategy to improve immune cell exhaustion in acute deficiency syndrome of sepsis.

ObjectiveTo observe the effects of Yiqi Huoxue Jiedu formula（YHJF） on immune cell exhaustion in the spleen of septic mice and to explore and validate its potential intervention targets. MethodsMice were randomly divided into the sham-operated， model， low-dose YHJF（4.1 g·kg^-1）， and high-dose YHJF（8.2 g·kg^-1） groups. Except for the sham-operated group， a cecal ligation and puncture（CLP） procedure was performed to establish a mouse sepsis model. The treatment groups received oral administration of the corresponding doses， while the sham-operated and model groups received an equal volume of physiological saline. After the intervention， the 7-day survival rate of each group was recorded， and spleen samples were collected 72 h post-intervention， and the spleen index was calculated. Terminal deoxynucleotidyl transferase deoxyuridine triphosphate（dUTP） nick end labeling（TUNEL） staining was used to detect apoptosis in spleen cells. Enzyme-linked immunosorbent assay（ELISA） was performed to measure the levels of interleukin（IL）-4 and IL-10 in the serum. Transcriptomics and metabolomics were used to screen for differentially expressed genes（DEGs） and differential metabolites in the spleen， followed by bioinformatics analysis to identify key targets. Real-time quantitative polymerase chain reaction（Real-time PCR）， flow cytometry， and multiplex immunofluorescence were used to verify the expressions of key genes and proteins. ResultsThe high-dose YHJF group significantly improved the 7-day survival rate of septic mice（P0.05）. Compared with the sham-operated group， the model group showed a significant increase in apoptosis of spleen cells and a decrease in the spleen index at 72 h post-modeling， with markedly elevated peripheral serum IL-4 and IL-10 levels（P0.01）. Compared with the model group， the high-dose YHJF group showed a reduction in apoptosis of spleen cells， an increase in the spleen index， and a significant decrease in peripheral serum IL-4 and IL-10 levels（P0.05）. Spleen transcriptomics identified 255 DEGs between groups， potentially serving as intervention targets for YHJF. Gene Ontology（GO） enrichment analysis revealed that DEGs were mainly involved in biological processes such as natural killer（NK） cell-mediated positive immune regulation， cell killing， cytokine production， positive regulation of innate immune cells， and interferon production. Kyoto Encyclopedia of Genes and Genomes（KEGG） pathway enrichment analysis showed that DEGs were mainly involved in cytokine-cytokine receptor interactions， viral protein interactions with cytokines and cytokine receptors， chemokine signaling pathway， and nuclear transcription factor-κB（NF-κB） signaling pathway. Protein-protein interaction（PPI） network analysis identified CD160， granzyme B（GZMB）， and chemokine ligand 4（CCL4） as key targets for YHJF in treating sepsis. Metabolomics identified 46 differential metabolites that were significantly reversed by YHJF intervention， and combined transcriptomics and metabolomics analysis identified 17 differential metabolites closely related to CD160. Pathway enrichment revealed that these metabolites were mainly involved in glycerophospholipid metabolism， arachidonic acid metabolism， glycosylphosphatidylinositol（GPI） anchor biosynthesis， linoleic acid metabolism， and α-linolenic acid metabolism pathways. Verification results showed that， compared with the sham-operated group， the model group exhibited significantly elevated CD160 mRNA expression level in the spleen， along with markedly decreased CCL4 and GZMB mRNA expression， and had a significant increase in CD160 expression on the surface of natural killer T（NKT） cells in the spleen（P0.01）. Compared with the model group， the high-dose YHJF group had a significant decrease in CD160 mRNA expression in the spleen， a significant increase in CCL4 and GZMB mRNA expressions. Further flow cytometry and immunofluorescence revealed that compared with the sham-operated group， CD160 expression on the surface of splenic NKT cells in the model group was significantly increased（P0.01）， while high-dose YHJF intervention significantly reduced CD160 expression（P0.01）. ConclusionYHJF may alleviate NKT cell exhaustion in sepsis by downregulating the expression of the negative co-stimulatory molecule CD160， and this regulatory effect is closely related to fatty acid metabolism pathways. This study provides new insights and targets for further exploration of strengthening vital Qi and detoxifying strategy to improve immune cell exhaustion in acute deficiency syndrome of sepsis.

Based on spleen deficiency-phlegm dampness as the core pathogenesis of obesity， and integrating recent advances in modern medicine regarding the key role of immune inflammation in obesity， this paper proposes a multidimensional pathogenic network of "obesity-spleen deficiency-phlegm dampness-immune imbalance". Various traditional Chinese medicine （TCM） herbs that strengthen the spleen， regulate qi， and resolve phlegm and dampness can treat obesity by improving spleen-stomach transport and transformation， promoting water-damp metabolism， and regulating immune homeostasis. This highlights immune inflammation as an important entry point to elucidate the TCM concepts of "spleen deficiency-phlegm dampness" and the therapeutic principle of "strengthening the spleen and eliminating dampness to treat obesity". By systematically analyzing the intrinsic connection between "spleen deficiency generating dampness， internal accumulation of phlegm dampness" and immune dysregulation in obesity， this paper aims to provide theoretical support for TCM treatment of obesity based on dampness.

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.

Allergen-specific immunotherapy（AIT） remains the only therapeutic approach with the potential to modify the natural course of allergic rhinitis（AR）. Nevertheless, considerable inter-individual variability exists in patients'responses to AIT. To facilitate more reliable assessment of treatment efficacy, the China Rhinopathy Research Cooperation Group（CRRCG） convened young and middle-aged nasal experts in China to formulate the present consensus. The recommended subjective outcome measures for AIT comprise symptom scores, medication scores, combined symptom and medication scores, quality-of-life assessments, evaluation of disease control, and assessment of comorbidities. Objective indicators may supplement these measures. Currently available objective approaches include skin prick testing, nasal provocation testing, and allergen exposure chambers. However, these methods remain constrained by practical limitations and are not yet appropriate for routine implementation in clinical efficacy evaluation. In addition, several biomarkers, including sIgE and the sIgE/tIgE ratio, sIgG4, serum IgE-blocking activity, IgA, cytokines and chemokines, as well as immune cell surface molecules and their functional activity, have been shown to have associations with AIT outcomes. While these biomarkers may complement subjective assessments, they are subject to significant limitations. Consequently, large-scale multicenter trials and real-world evidence are required to strengthen the evidence base. The present consensus underscores the necessity of integrating patients'subjective experiences with objective testing throughout the treatment process, thereby providing a more comprehensive and accurate framework for efficacy evaluation. Looking forward, future investigations should prioritize the incorporation of multi-omics data and artificial intelligence methodologies, which hold promise for overcoming current limitations in assessment strategies and for advancing both the standardization and personalization of AIT.
Humans ; Allergens/immunology* ; China ; Consensus ; Desensitization, Immunologic ; Immunoglobulin E ; Quality of Life ; Rhinitis, Allergic/therapy* ; Treatment Outcome ; East Asian People

Alzheimer's disease (AD) is the major form of dementia in the elderly and is closely related to the toxic effects of microglia sustained activation. In AD, sustained microglial activation triggers impaired synaptic pruning, neuroinflammation, neurotoxicity, and cognitive deficits. Accumulating evidence has demonstrated that aberrant expression of deubiquitinating enzymes is associated with regulating microglia function. Here, we use RNA sequencing to identify a deubiquitinase YOD1 as a regulator of microglial function and AD pathology. Further study showed that YOD1 knockout significantly improved the migration, phagocytosis, and inflammatory response of microglia, thereby improving the cognitive impairment of AD model mice. Through LC-MS/MS analysis combined with Co-IP, we found that Myosin heavy chain 9 (MYH9), a key regulator maintaining microglia homeostasis, is an interacting protein of YOD1. Mechanistically, YOD1 binds to MYH9 and maintains its stability by removing the K48 ubiquitin chain from MYH9, thereby mediating the microglia polarization signaling pathway to mediate microglia homeostasis. Taken together, our study reveals a specific role of microglial YOD1 in mediating microglia homeostasis and AD pathology, which provides a potential strategy for targeting microglia to treat AD.

Extracellular vesicles (EVs) are crucial for facilitating intercellular communication, promoting cell migration, and orchestrating the immune response. Recently, EVs can diagnose and treat tumors. EVs can be measured as biomarkers to provide information about the type of disease and therapeutic efficacy. Furthermore, EVs with lower immunogenicity and better biocompatibility are natural carriers of chemicals and gene drugs. Herein, we review the molecular composition, biogenesis, and separation methods of EVs. We also highlight the important role of EVs from different origins as biomarkers and drug delivery systems in tumor therapy. Finally, we provide deep insights into how EVs play a role in reversing the immunosuppressive microenvironment.

Traditional development of small protein scaffolds has relied on display technologies and mutation-based engineering, which limit sequence and functional diversity, thereby constraining their therapeutic and application potential. Protein design tools have significantly advanced the creation of novel protein sequences, structures, and functions. However, further improvements in design strategies are still needed to more efficiently optimize the functional performance of protein-based drugs and enhance their druggability. Here, we extended an evolution-based design protocol to create a novel minibinder, BindHer, against the human epidermal growth factor receptor 2 (HER2). It not only exhibits super stability and binding selectivity but also demonstrates remarkable properties in tissue specificity. Radiolabeling experiments with ^99mTc, ⁶⁸Ga, and ¹⁸F revealed that BindHer efficiently targets tumors in HER2-positive breast cancer mouse models, with minimal nonspecific liver absorption, outperforming scaffolds designed through traditional engineering. These findings highlight a new rational approach to automated protein design, offering significant potential for large-scale applications in therapeutic mini-protein development.