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.

Background/Aims: Lenvatinib resistance remains a critical barrier in advanced hepatocellular carcinoma (HCC) therapy. However, the underlying mechanisms and strategies for reversing resistance remain incompletely understood. Methods: Integrated transcriptomics of lenvatinib-resistant patient tumors and an acquired-resistance murine model identified a novel macrophage subpopulation. Functional validation employed CRISPR-SAM screening, conditioned medium (CM) assays, subcutaneous/orthotopic xenografts, patient-derived organoids (PDOs), and patient-derived xenografts (PDXs). Mechanistic studies included ChIP-qPCR, co-immunoprecipitation, and pharmacologic targeting. Clinical relevance was assessed in a retrospective cohort. Results: Resistant HCC exhibited significant enrichment of a COLEC12high TAM subset , which correlated with poor survival and treatment response. These TAMs secreted neuregulin-1 (NRG1) , activating HER2/HER3-AKT signaling in tumor cells to drive cancer stemness and lenvatinib resistance. Mechanistically, in TAMs COLEC12 sequestered STAT1 in the cytoplasm, preventing its phosphorylation, and thereby derepressing STAT3-mediated NRG1 transcription. Depletion of NRG1 reversed the stemness phenotypes and resensitized tumors to lenvatinib both in vitro and in vivo. Clinically, high NRG1 expression predicted an inferior lenvatinib response and shorter survival. Crucially, the bispecific anti-HER2/HER3 antibody zenocutuzumab restored lenvatinib efficacy in PDOs, PDXs, and murine models. Conclusions Our work establishes the COLEC12high TAM/NRG1 axis as a master regulator of therapeutic resistance and identifies NRG1 as a predictive biomarker, providing a clinically actionable strategy to overcome lenvatinib resistance in HCC.

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.

Objective: To investigate the trend in disease burden of interstitial lung disease (ILD) in China from 1990 to 2021, so as to provide a reference for formulating prevention and control strategies for chronic respiratory diseases. Methods: Based on the Global Burden of Disease 2021 database, data on the number of incident cases, incidence, standardized incidence, number of deaths, mortality, standardized mortality, number of disability-adjusted life years (DALY), DALY rate, and standardized DALY rate of ILD in China were collected. The incidence, mortality, and DALY rate were used to analyze the disease burden of ILD. The estimated annual percentage change (EAPC) was employed to assess the trend in standardized incidence, standardized mortality, and standardized DALY rate of ILD from 1990 to 2021. Rate decomposition analysis was applied to identify the main contributing factors affecting the trend in disease burden. Results: In 2021, China reported 48 514 cases, 7 674 deaths, and 222 288 person-years of DALY due to ILD, representing increases of 155.43%, 159.70%, and 97.34%, respectively, compared with 1990. From 1990 to 2021, the standardized incidence and standardized mortality of ILD in China showed upward trends (EAPC=1.106% and 0.239%, both P<0.05), while the standardized DALY rate showed a downward trend (EAPC=-0.230%, P<0.05). From 1990 to 2021, the standardized incidence and standardized mortality among males showed upward trends (EAPC=1.199% and 0.520%, both P<0.05), while the trend in the standardized DALY rate was not statistically significant (P>0.05). Among females, the standardized incidence of ILD showed an upward trend (EAPC=0.966%, P<0.05), while the standardized mortality and standardized DALY rate showed downward trends (EAPC=-0.306% and -0.760%, both P<0.05). In 2021, the incidence, mortality, and DALY rate of ILD in China increased with age, peaking in the group aged ≥95 years at 14.84/105, 13.90/105, and 124.71/105, respectively. Across all age groups aged ≥55 years, the incidence, mortality, and DALY rate of ILD were consistently higher in males than in females. The increase in the number of incident cases, deaths, and DALY due to ILD in China from 1990 to 2021 was primarily influenced by population aging, with contribution rates of 42.65%, 68.25%, and 69.79%, respectively. Conclusions From 1990 to 2021, the incidence and mortality risk of ILD in China showed upward trends, while the disability risk demonstrated a downward trend. Males bore a heavier disease burden of ILD, and aging was identified as the primary factor contributing to the increased burden of ILD in China.

Guided by the concept of quality by design(QbD), this study optimizes the calcination and quenching process of calcined Magnetitum and establishes the XRD characteristic spectra of calcined Magnetitum, providing a scientific basis for the formulation of quality standards. Based on the processing methods and quality requirements of Magnetitum in the Chinese Pharmacopoeia, the critical process parameters(CPPs) identified were calcination temperature, calcination time, particle size, laying thickness, and the number of vinegar quenching cycles. The critical quality attributes(CQAs) included Fe mass fraction, Fe~(2+) dissolution, and surface color. The weight coefficients were determined by combining Analytic Hierarchy Process(AHP) and the criteria importance though intercrieria correlation(CRITIC) method, and the calcination process was optimized using orthogonal experimentation. Surface color was selected as a CQA, and based on the principle of color value, the surface color of calcined Magnetitum was objectively quantified. The vinegar quenching process was then optimized to determine the best processing conditions. X-ray diffraction(XRD) was used to establish the characteristic spectra of calcined Magnetitum, and methods such as similarity evaluation, cluster analysis, and orthogonal partial least squares-discriminant analysis(OPLS-DA) were used to evaluate the quality of the spectra. The optimized calcined Magnetitum preparation process was found to be calcination at 750 ℃ for 1 h, with a laying thickness of 4 cm, a particle size of 0.4-0.8 cm, and one vinegar quenching cycle(Magnetitum-vinegar ratio 10∶3), which was stable and feasible. The XRD characteristic spectra analysis method, featuring 9 common peaks as fingerprint information, was established. The average correlation coefficient ranged from 0.839 5-0.988 1, and the average angle cosine ranged from 0.914 4 to 0.995 6, indicating good similarity. Cluster analysis results showed that Magnetitum and calcined Magnetitum could be grouped together, with similar compositions. OPLS-DA discriminant analysis identified three key characteristic peaks, with Fe_2O_3 being the distinguishing component between the two. The final optimized processing method is stable and feasible, and the XRD characteristic spectra of calcined Magnetitum was initially established, providing a reference for subsequent quality control and the formulation of quality standards for calcined Magnetitum.
X-Ray Diffraction/methods* ; Drugs, Chinese Herbal/chemistry* ; Quality Control ; Particle Size

The AP2/ERF transcription factor family is a class of transcription factors widely present in plants, playing a crucial role in regulating flowering, flower development, flower opening, and flower senescence. Based on transcriptome data from flower, leaf, and stem samples of two Lonicera macranthoides varieties, 117 L. macranthoides AP2/ERF family members were identified, including 14 AP2 subfamily members, 61 ERF subfamily members, 40 DREB subfamily members, and 2 RAV subfamily members. Bioinformatics and differential gene expression analyses were performed using NCBI, ExPASy, SOMPA, and other platforms, and the expression patterns of L. macranthoides AP2/ERF transcription factors were validated via qRT-PCR. The results indicated that the 117 LmAP2/ERF members exhibited both similarities and variations in protein physicochemical properties, AP2 domains, family evolution, and protein functions. Differential gene expression analysis revealed that AP2/ERF transcription factors were primarily differentially expressed in the flowers of the two L. macranthoides varieties, with the differentially expressed genes mainly belonging to the ERF and DREB subfamilies. Further analysis identified three AP2 subfamily genes and two ERF subfamily genes as potential regulators of flower development, two ERF subfamily genes involved in flower opening, and two ERF subfamily genes along with one DREB subfamily gene involved in flower senescence. Based on family evolution and expression analyses, it is speculated that AP2/ERF transcription factors can regulate flower development, opening, and senescence in L. macranthoides, with ERF subfamily genes potentially serving as key regulators of flowering duration. These findings provide a theoretical foundation for further research into the specific functions of the AP2/ERF transcription factor family in L. macranthoides and offer important theoretical insights into the molecular mechanisms underlying floral phenotypic differences among its varieties.
Plant Proteins/chemistry* ; Gene Expression Regulation, Plant ; Transcription Factors/chemistry* ; Lonicera/classification* ; Flowers/metabolism* ; Phylogeny ; Gene Expression Profiling ; Multigene Family

The anti-inflammatory phytochemical investigation of the leaves of Illicium dunnianum (I. dunnianum) resulted in the isolation of five pairs of new lignans (1-5), and 7 known analogs (6-12). The separation of enantiomer mixtures 1-5 to 1a/1b-5a/5b was achieved using a chiral column with acetonitrile-water mixtures as eluents. The planar structures of 1-2 were previously undescribed, and the chiral separation and absolute configurations of 3-5 were reported for the first time. Their structures were determined through comprehensive spectroscopic data analysis [nuclear magnetic resonance (NMR), high-resolution electrospray ionization mass (HR-ESI-MS), infrared (IR), and ultraviolet (UV)] and quantum chemistry calculations (ECD). The new isolates were evaluated by measuring their inhibitory effect on NO in lipopolysaccharide (LPS)-stimulated BV-2 cells. Compounds 1a, 3a, 3b, and 5a demonstrated partial inhibition of NO production in a concentration-dependent manner. Western blot and real-time polymerase chain reaction (PCR) assays revealed that 1a down-regulated the messenger ribonucleic acid (mRNA) levels of tumor necrosis factor α (TNF-α), interleukin-6 (IL-6), COX-2, and iNOS and the protein expressions of COX-2 and iNOS. This research provides guidance and evidence for the further development and utilization of I. dunnianum.
Lignans/isolation & purification* ; Plant Leaves/chemistry* ; Anti-Inflammatory Agents/isolation & purification* ; Mice ; Animals ; Molecular Structure ; Plant Extracts/pharmacology* ; Illicium/chemistry* ; Cyclooxygenase 2/immunology* ; Interleukin-6/immunology* ; Nitric Oxide/metabolism* ; Cell Line ; Tumor Necrosis Factor-alpha/immunology* ; Nitric Oxide Synthase Type II/immunology* ; Lipopolysaccharides

ObjectiveTo investigate the application of the novel inflammatory factor adsorption column CA280 combined with low-dose plasma exchange （LPE） in patients with acute-on-chronic liver failure （ACLF）. MethodsA prospective cohort study was designed， and a total of 93 ACLF patients who were admitted to The Ninth Hospital of Nanchang from June 2023 to January 2025 were enrolled and randomly divided into DPMAS+LPE group with 50 patients and CA280+LPE group with 43 patients. In addition to comprehensive medical treatment， the patients in the DPMAS+LPE group received DPMAS and LPE treatment， and those in the CA280+LPE group received CA280 and LPE treatment. The two groups were observed in terms of routine blood test results， liver function parameters， renal function markers， electrolytes， coagulation function parameters， cytokines， adverse events， and 28-day prognosis before surgery （baseline）， during surgery （DPMAS or CA280）， and after surgery （after sequential LPE treatment）. The paired t-test was used for comparison of normally distributed continuous data before and after treatment within each group， and the independent-samples t test was used for comparison between groups； the Wilcoxon signed-rank test was used for comparison of non-normally distributed continuous data before and after treatment within each group， and the Mann-Whitney U test was used for comparison between groups. The chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups， and the Spearman test was used for correlation analysis. ResultsAfter CA280 treatment， the ACLF patients had significant reductions in the levels of cytokines （IL-6， IL-8， IL-10， TNF-α， and IFN-γ）， liver function parameters （ALT， AST， ALP， TBil， DBil， Alb， and glutathione reductase）， and the renal function marker urea nitrogen （all P<0.05）， and in terms of coagulation function parameters， there were significant increases in prothrombin time， activated partial thromboplastin time （APTT）， thrombin time， and international normalized ratio （INR） and significant reductions in prothrombin activity （PTA） and fibrinogen （FIB） （all P<0.05）. Compared with the DPMAS+LPE group， the CA280+LPE group showed better improvements in the serum cytokines IL-8 （Z=-2.63， P=0.009）， IL-10 （Z=-3.94， P<0.001）， and TNF-α （Z=-1.53， P=0.023）， and the two artificial liver support systems had a similar effect in improving liver function （ALT， AST， GGT， GR， TBil， and DBil） （all P >0.05）， but the CA280+LPE group showed a significantly greater reduction in Alb （Z=-2.08， P=0.037）. CA280+LPE was more effective in reducing uric acid （Z=-2.97， P=0.003）. Compared with DPMAS+LPE， CA280+LPE treatment resulted in a significant reduction in INR （Z=-4.01， P<0.001）， a significant increase in APTT （Z=-2.53， P=0.011）， and significant greater increases in PTA （Z=-6.28， P<0.001） and FIB （Z=-3.93， P<0.001）. There were no significant differences in the incidence rates of adverse reactions and the rate of improvement at discharge between the two groups （all P>0.05）. The Spearman correlation analysis showed that IL-6 was significantly correlated with WBC （r=0.22， P=0.042）， TBil （r=0.29， P=0.005）， and FIB （r=-0.33， P=0.003）； IL-8 was positively correlated with APTT （r=0.37， P<0.001） and INR （r=0.25， P=0.013）； TNF-α was significantly correlated with WBC （r=0.40， P<0.001） and TBil （r=0.34， P<0.001）. ConclusionCompared with DPMAS， CA280 combined with LPE can effectively clear proinflammatory cytokines and improve liver function in ACLF patients， but it has a certain impact on Alb and coagulation function. This regimen provides a new option for the individualized treatment of ACLF and can improve the short-term prognosis of patients， but further studies are needed to verify its long-term efficacy.

Objective To investigate the critical role of hypoxia in impairing spermatogenesis via M1 macrophage polarization and subsequent induction of lysosome-dependent cell death(LDCD)in Leydig cells.Methods Ten eight-week-old male SD rats(weight 220～250 g)were randomly divided into normoxia(n=5)and hypoxia groups(n=5).Hypoxic models were established by housing rats in hypoxic chambers simulating 5 000 m altitude for 4 weeks.TM3 mouse Leydig cells underwent 1%O2 exposure for 2 d.A transwell co-culture system integrated RAW 264.7 macrophages and TM3 cells.Testicular histopathology was evaluated via HE staining(spermatogenic cells/tubular area).Testosterone levels were quantified by ELISA(BCA-quantified).Immunofluorescence assessed Leydig cells(CYP11A1+),M1 macrophages(CD68+/CD86+in tissue;iNOS+in cells),and lysosomal integrity(LysoTracker/CTSB staining).Single-cell RNA-seq data(PRJNA926018)with GSEA identified programmed cell death pathways.Results Hypoxia significantly reduced spermatogenic cell density(P<0.01),testosterone levels(P<0.01),and Leydig cell counts(P<0.01).scRNA-seq revealed decreased proportions of elongated spermatids,Leydig cells,and sertoli cells(P<0.01),but increased spermatocytes/spermatogonia(P<0.01),with significant LDCD enrichment in Leydig cells(P=0.002 7).Hypoxia induced testicular M1 macrophage infiltration(CD68+/CD86+)and elevated iNOS+in RAW 264.7 cells(P<0.01).Transwell co-culture showed hypoxia-treated macrophages,but not hypoxia alone,disrupted lysosomal membrane stability in TM3 cells.Conclusion Hypoxia impairs spermatogenesis by driving M1 macrophage polarization,triggering LDCD in Leydig cells,and reducing testosterone synthesis.