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.

ObjectiveTo explore the effect and mechanism of Jianpi Xiaoai prescription （JPXA） in ameliorating the 5-fluorouracil （5-FU） resistance of colon cancer. MethodsA HCT116/5-FU resistant cell line was established. Different concentrations （10%， 15%， 20%） of JPXA-containing serum and drug-free serum were used for intervention， and 10% fetal bovine serum （10% FBS）， fibroblast growth factor receptor （FGFR） inhibitor （AZD4547）， and recombinant fibroblast growth factor 2 （FGF2） were set as the control groups. Sensitive HCT116 cells were used in the FGF2 group， while HCT116/5-FU cells were used in other groups. Drug resistance， the level of FGF2 in the cell culture medium， the mRNA level of FGF2 in cells， and the protein levels of FGF2/FGFR and phosphatidylinositol 3-kinase/protein kinase B （PI3K/Akt） were determined. The drug-resistant cells were transplanted into the axilla of nude mice to establish a tumor model. The modeled mice were allocated into model， JPXA （15 g·kg^-1）， 5-FU （0.02 g·kg^-1）， JPXA+5-FU （15 g·kg^-1+0.02 g·kg^-1）， AZD4547 （0.012 5 g·kg^-1）， and AZD4547+5-FU （0.012 5 g·kg^-1+0.02 g·kg^-1） groups. The tumor growth and the protein levels of FGF/FGFR and PI3K/Akt in each group were observed. ResultsThe survival rate of HCT116/5-FU cells decreased in all the JPXA groups with different concentrations. The cell survival rate was decreased most obviously in the 20% JPXA group. The level of FGF2 in the cell culture medium and the mRNA level of FGF2 in cells of each JXPA group decreased， and the decrease was the most significant in the 20% group （P<0.01）. HCT116/5-FU cells showed up-regulated protein levels of FGF2 and phosphorylated fibroblast growth factor receptor 1 （p-FGFR1）， but down-regulated protein level of FGFR1 （P<0.01）. JPXA down-regulated the expression of FGF2 and p-FGFR1 and up-regulated the expression of FGFR1 （P<0.05）. In addition， JPXA down-regulated the expression levels of phosphorylated protein kinase B （p-Akt） and phosphorylated mammalian target of rapamycin （p-mTOR）， while up-regulating the expression levels of Akt and Bcl-2-asociated death promoter （Bad） （P<0.05）. Animal experiments showed that the JPXA combined with 5-FU significantly inhibited the growth of drug-resistant tumors， reduced the protein levels of FGF2， p-FGFR1， phosphorylated phosphatidylinositol-3-kinase （p-PI3K）， p-Akt， and p-mTOR， and increased the expression of Bad. It indicated that JPXA can inhibit the FGF2/FGFR1 signaling in colon cancer and regulate PI3K/Akt and downstream signaling pathways. ConclusionJPXA can ameliorate the chemotherapy resistance of colon cancer through down-regulating FGF2 expression and inhibiting the activation of the PI3K/Akt signaling pathway.

BACKGROUND:Studies have shown that lipid metabolism and related diseases can affect the development of osteoporosis.OBJECTIVE:Using bibliometric visualization analysis software to analyze and summarize the frontier content and research hotspots in the field of lipid metabolism affecting osteoporosis.METHODS:Using the Web of Science core collection database as the retrieval platform,relevant literature regarding the effect of lipid metabolism on osteoporosis from 2004 to 2024 was retrieved.VOSviewer and CiteSpace were used for bibliometric and visual analyses.RESULTS AND CONCLUSION:A total of 1 277 articles were included,and the number of articles on the effect of lipid metabolism on osteoporosis at home and abroad was increasing year by year.The number of articles published in China was 417,ranking first,and the United States was 243,ranking second.Shanghai Jiao Tong University ranked first with 30 articles.Professor Rosen Clifford J from Tufts University School of Medicine and Professor Recker Robert R from Clayton University were the most cited authors.The number of documents published in BONE in the Netherlands ranked first,and the JOURNAL OF CLINICAL ENDOCRINOLOGY & METABOLISM in England was the most cited journal.Bone mineral density,bone metabolism,menopause,and obesity were the core keywords,and they were also research hotspots in this field.The above results show that in the past 20 years,research in the field of lipid metabolism affecting osteoporosis has focused on the role of abnormal lipid metabolism in bone mineral density and bone metabolism,thereby regulating osteoporosis and post-menopause osteoporosis.Clarifying the pathway of this mechanism and"bone-lipid balance"is the future research idea and direction.

OBJECTIVE To systematically evaluate the correlation between dynamic changes in inflammatory markers during treatment with epidermal growth factor receptor-tyrosine kinase inhibitors （EGFR-TKIs） in non-small cell lung cancer （NSCLC） patients and therapeutic efficacy， with the aim of providing evidence-based support for clinical prognosis assessment and treatment strategy adjustment. METHODS Databases including PubMed， Embase， Cochrane Library， CNKI， Wanfang Data， and CBM were searched from the inception to July 20， 2025. Following literature screening， data extraction and quality assessment， descriptive analysis was conducted on the outcomes of included studies. RESULTS A total of eight studies were included to analyze the correlation of 6 inflammatory markers before and after treatment with EGFR-TKIs with therapeutic efficacy. The risk of bias assessment identified six high-quality studies and two moderate-quality studies. Among these studies， seven studies demonstrated that lower levels of neutrophil-to-lymphocyte ratio （NLR）， derived neutrophil-to-lymphocyte ratio （dNLR）， platelet-to-lymphocyte ratio （PLR）， and monocyte-to-lymphocyte ratio （MLR）， higher lymphocyte-to-monocyte ratio （LMR） before treatment， as well as decreased NLR and MLR and increased LMR after treatment were associated with longer median progression-free survival. Five studies indicated that lower levels of NLR， dNLR， PLR， and interleukin-6 （IL-6）， higher LMR before treatment as well as decreased NLR and dNLR and increased LMR were associated with longer median overall survival. Three studies indicated that lower levels of IL-6 were associated with a higher objective response rate， while the association of these markers after treatment remained controversial； another study showed that an early decline in NLR， MLR， and PLR after treatment may be associated with objective response benefit. CONCLUSIONS Lower inflammatory levels during EGFR-TKIs therapy correlate with better therapeutic efficacy in NSCLC patients.

AIM:To investigate the therapeutic effects of bone marrow mesenchymal stem cell-derived exosomes(BMSC-Exos)on diabetic retinopathy(DR)in rats, with a focus on their ability to modulate oxidative stress and inflammatory responses through the TLR4/NF-κB signaling pathway.METHODS:Streptozotocin(STZ)-induced diabetic Sprague-Dawley(SD)rats were randomly divided into four groups: Group 1 [normal+phosphate-buffered saline(PBS)], Group 2(normal+Exos), Group 3(DR+PBS), and Group 4(DR+Exos). At the 8th week after modeling, BMSC-Exos or PBS were injected intravitreally. Retinal tissues were collected at the 16th week for histological analysis [hematoxylin and eosin(HE)staining], apoptosis detection(TUNEL). Oxidative stress markers [8-OHdG, superoxide dismutase(SOD), and glutathione(GSH)] were assessed, and inflammatory cytokines [enzyme-linked immunosorbent assay(ELISA)for interleukin(IL)-6 and tumor necrosis factor-alpha(TNF-α)], and molecular profiling [quantitative polymerase chain reaction(qPCR)for TLR4, NF-κB, and VEGF] were measured.RESULTS:The BMSC-Exos treatment significantly suppressed the activation of the TLR4/NF-κB pathway in DR rats(P<0.01), which was accompanied by reduced retinal vascular leakage(Evans blue assay, P<0.001), decreased apoptosis(TUNEL, P<0.05), and attenuated oxidative stress(elevated SOD and GSH, reduced 8-OHdG, P<0.05). The levels of inflammatory cytokines(IL-6 and TNF-α)were markedly decreased(P<0.01).CONCLUSION:BMSC-Exos alleviate DR by suppressing the TLR4/NF-κB axis, thus reducing oxidative damage, inflammation, and microvascular dysfunction. This research offers a novel therapeutic approach for early-stage DR.

Objective To investigate the post-discharge exercise behavior and factors influencing moderate to vigorous intensity physical activity (MVPA) in patients undergoing lung surgery. Methods A total of 2874 patients from the large prospective, observational perioperative lung symptom study cohort (CN-PRO-Lung 3) in the Department of Thoracic Surgery at Sichuan Cancer Hospital between April 7, 2021, and January 31, 2024, were selected as the survey subjects. A survey was conducted using the Investigation of Exercise Behavior after Lung Surgery questionnaire and the International Physical Activity Questionnaire-Short Form (IPAQ-SF) among patients who underwent lung surgery. Binary logistic regression was used to analyze the factors influencing patients’ engagement in MVPA. Results A total of 702 patients were surveyed, including 252 males and 450 females, with an average age of (52.4±10.2) years. Patients with lung cancer accounted for 85.9%. Only 36.0% of the patients had regular exercise habits, while 42.3% did not engage in any physical activity. The three main barriers for postoperative exercise were physical discomfort (pain, coughing, shortness of breath, etc, 54.7%), lack of professional guidance (41.7%), and concerns about the surgical wound (28.9%). The proportions of patients engaging in vigorous, moderate, and low-intensity physical activity were 5.7%, 28.2%, and 66.1%, respectively. Multivariate analysis showed that patients with a personal annual income ≥50000 yuan (OR=1.52, 95%CI 1.01-2.29, P=0.044), high school education or above (OR=1.92, 95%CI 1.33-2.76, P<0.001), and lobectomy (OR=1.44, 95%CI 1.02-2.03, P=0.037) engaged in more MVPA. Conclusion Patients undergoing lung surgery have inadequate physical activity after discharge, particularly lacking in MVPA. Patients with higher income, higher educational levels, and lobectomy are more frequently engaged in MVPA. Measures such as symptom control, providing exercise guidance, and enhancing education on wound care may potentially improve the inadequate physical activity in lung surgery patients after discharge.

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.