Objective To address the inter-observer annotation variability in echocardiographic image segmentation caused by image boundary ambiguity and differences in experts’ clinical backgrounds. Methods A framework was proposed that leveraged a conditional diffusion model, guided by cardiac ultrasound images, to learn the probability distribution of multi-expert annotations. A probabilistic consensus strategy was further introduced to dynamically fuse these annotations. This approach was designed to simultaneously aggregate clinical consensus among experts and preserve the diversity of the annotation distribution, thereby jointly modeling both the stable morphological features of the target anatomy and the reasonable variations inherent in expert annotations. Given the scarcity of authentic multi-expert annotations in public datasets like CAMUS, a synthetic multi-expert annotation system was developed using morphological operations. This system was designed to simulate three typical clinical annotation style (conservative, optimal, and aggressive), to provide a reliable data foundation for validating the proposed method. Results The proposed model significantly outperformed state-of-the-art methods in both left ventricular endocardium (LVEndo) and left ventricular epicardium (LVEpi) segmentation tasks. For LVEndo, the generalized energy distance () at the end-diastolic (ED) phase reached 0.073 1, representing a 43.9% reduction compared to the D-Persona model. For LVEpi, the decreased by 42.0% and 39.0% at the ED and end-systolic phases, respectively, relative to D-Persona. Furthermore, the structural fidelity improved by 2.7-3.5 percentage points for LVEndo and 1.4-2.2 percentage points for LVEpi compared to single-expert models, indicating a superior ability to capture diverse expert preferences. Conclusion By jointly modeling population-level consensus and annotation diversity, this work enables a unified characterization of anatomical structures and their associated annotation uncertainty in cardiac ultrasound images, offering a novel approach toward robust and interpretable segmentation in clinical settings.

Background/Aims: Dysregulated cholesterol metabolism is a hallmark of hepatocellular carcinoma (HCC) that drives tumor initiation and progression. However, clinical targeting of cholesterol metabolism has yielded limited benefits due to stringent feedback in tumor cells. Identifying a central mediator capable of restoring cholesterol homeostasis within the cell’s intrinsically fine-tuned regulatory framework is urgently needed. Methods: We integrated a proteomic dataset from patients with cholesterol-dysregulated HCC into a global cholesterol metabolic regulatory network to identify potential therapeutic targets for disrupted cholesterol homeostasis. The prognostic significance of the candidate targets was further validated in an independent cohort through immunohistochemistry. Functional and mechanistic studies were conducted in vitro using HCC cell lines and in vivo using mouse models. The pharmacological efficacy of the candidate agent was evaluated in both subcutaneous and orthotopic HCC mouse models. Results: ER lipid raft-associated 1 (ERLIN1), a pivotal regulator of cholesterol metabolism reprogramming, was identified as an independent favorable prognostic indicator in HCC. ERLIN1 constrains HCC progression both in vitro and in vivo by stabilizing the INSIG1–SCAP–SREBP2 axis and maintaining the metabolic balance of intracellular cholesterol. Under hypoxia, impaired factor-inhibiting hypoxia-1-dependent hydroxylation of ASB11 at asparagine residues 90 and 92 enhances ASB11-mediated ERLIN1 degradation. Pharmacological targeting of this axis using zoledronic acid (ZoA) attenuated HCC progression by weakening the ASB11–ERLIN1 interaction and restoring cholesterol homeostasis. Conclusions ERLIN1 represents a druggable metabolic vulnerability in cholesterol-dysregulated HCC. Targeting the ASB11–ERLIN1 axis with the clinically approved ZoA reestablishes cholesterol homeostasis and offers a promising therapeutic strategy to overcome the current limitations of cholesterol-targeted HCC therapies.

Prolonged standing work can lead to various lower limb health issues. Footwear, as a convenient and noninvasive intervention, plays a key role in foot protection. The purpose of this review was to evaluate the impact of footwear characteristics on foot comfort among workers engaged in prolonged standing occupations. A systematic search of PubMed, Web of Science, Scopus, and the Cochrane Library was conducted until March 2025 for experimental and observational studies; the review is registered in International Prospective Register of Systematic Reviews (CRD420251003253).Given the diversity of study designs, participant characteristics, and outcome measures, results were synthesized narratively, organizing findings by footwear design factors. The synthesis indicated that soft soles reduce foot impact and fatigue but offer limited support, whereas hard soles enhance stability but may cause localized pressure and discomfort. Sole hardness should balance cushioning and support based on activity: hard soles for standing and soft soles for walking. Insole hardness must be carefully considered as semirigid arch supports can cause discomfort. Most insoles improve pressure distribution by adjusting arch loading, and some enhance intrinsic foot muscles by promoting toe engagement, reducing leg swelling. Custom orthotic insoles outperform standard ones in comfort and balance. Future research should promote interdisciplinary collaboration with footwear designers to explore key design parameters and establish a scientific framework for protective footwear.

Objective:To construct a "local-systemic" dual-track prediction model integrating the resistance index (RI) score of bilateral sacroiliac joints and the systemic immune-inflammation index (SII), and to evaluate its predictive efficacy for the active stage of ankylosing spondylitis (AS).Methods:A total of 205 patients with ankylosing spondylitis (AS) from the Second Hospital of Lanzhou University between April 2022 and April 2025 were retrospectively enrolled and categorized into an active group ( n=113) and a remission group ( n=92). Hematological parameters and ultrasound data were collected. The resistance index (RI) of the synovial area in bilateral sacroiliac joints was measured by Doppler ultrasound and scored as follows: RI < 0.5: 3 points; RI 0.5~0.55: 2 points; RI > 0.55: 1 point; undetectable blood flow: 0 points. A total bilateral RI score (range 0 to 6) was calculated. The systemic immune-inflammation index (SII) was derived as (neutrophils× platelets)/lymphocytes. Normality was tested for all continuous variables; normally distributed data were compared using the t-test, while non-normally distributed data were analyzed with the Mann-Whitney U test. Categorical variables were compared using the χ2 test or analysis of variance.Variable selection was performed using Lasso regression, and a multivariate logistic regression model was developed to assess predictive performance. Results:The proportion of patients with a bilateral RI total score≥5 was significantly higher in the active group compared to the remission group (50 of 113, 44.3% vs 2 of 92, 2.2%, χ2=55.63, P<0.001). Multivariate logistic regression analysis, after adjustment for confounding variables, identified the SII [ OR(95% CI)=1.01(1.00, 1.01), P<0.001], bilateral RI total score [ OR(95% CI)=1.67(1.29, 2.26), P<0.001], erythrocyte sedimentation rate [ OR(95% CI)=1.19(1.11, 1.30), P<0.001], and mean corpuscular hemoglobin concentration [ OR(95% CI)=1.09(1.03, 1.17), P<0.001] as independent risk factors for active AS. Conversely, lymphocyte count [ OR(95% CI)=0.42(0.18, 0.92), P=0.030] and globulin [ OR(95% CI)=0.89(0.80, 0.99), P=0.040] were significantly associated with protective effects. The bilateral RI total score demonstrated the strongest predictive effect, with each 1-point increase associated with a 67% elevation in the risk of active disease. ROC curve analysis indicated that the area under the curve (AUC) for predicting whether AS is in the active disease phase was 0.94 for the combined model (SII+bilateral RI total score), compared with 0.93 for the SII-alone model and 0.92 for the bilateral RI total score-alone model, demonstrating superior predictive performance of the combined model (SII+bilateral RI total score). An online prediction tool has been developed based on the combined model. Conclusion:The dual-track prediction model, which integrates local joint hemodynamic characteristics and systemic immune-inflammatory status, facilitates a multidimensional assessment of the risk of active AS and provides an objective basis for early identification.

BACKGROUND:Macrophage polarization plays a key role in chronic inflammatory joint diseases such as rheumatoid arthritis.Cerium dioxide(CeO2)nanoparticles have a wide range of biomedical applications such as modulating the local inflammatory microenvironment of tissues.OBJECTIVE:To investigate the role of CeO2 nanoparticles on macrophage polarization and inflammatory factor expression,as well as inflammatory modulation in a co-culture system of macrophages and fibroblasts.METHODS:(1)CeO2 nanoparticles were dispersed and observed morphologically by transmission electron microscopy.(2)Human leukemia monocytes(THP-1)were induced to differentiate and establish the M1 macrophage pro-inflammatory cell model of rheumatoid arthritis.The cells were divided into M0 group(undifferentiated macrophages),M1 group(successful macrophage modeling),CeO2 nanoparticle treatment group(M1 group with CeO2 nanoparticle treatment),and dexamethasone control group(M1 group with dexamethasone treatment)and incubated for 48 hours.The effects of CeO2 nanoparticles on the expression of inflammatory factors(endogenous nitric oxide synthase,CD86,CD80)in M1 macrophages and M1 macrophage phenotype(CD80,CD206)were detected by RT-qPCR,western blot assay,and flow cytometry.(3)A co-culture system of macrophages and fibroblasts was established,and CeO2 nanoparticles acted on the upper macrophages.The regulation of CeO2 nanoparticles on the expression of inflammatory factors(interleukin-6,tumor necrosis factor-α,cyclooxygenase-2,and endogenous nitric oxide synthase)of fibroblasts in the co-culture system was observed at the mRNA and protein levels.RESULTS AND CONCLUSION:(1)Transmission electron microscopy showed that the diameter of CeO2 nanoparticles was(19.5±2.0)nm.(2)Compared with the M0 group,the mRNA of endogenous nitric oxide synthase and CD86,and the protein expression of endogenous nitric oxide synthase and CD80 in the M1 group were upregulated.Compared with the M1 group,the mRNA expression of endogenous nitric oxide synthase and CD86,and the protein expression of endogenous nitric oxide synthase and CD80 in the CeO2 nanoparticle treatment group were downregulated.Flow cytometry showed that 20 nm CeO2 nanoparticles downregulated the number of M1 macrophages.(3)Compared with the M1 group,20 nm CeO2 nanoparticles downregulated the mRNA and protein expression of inflammatory factors(tumor necrosis factor α,interleukin 6,cyclooxygenase 2,and endogenous nitric oxide synthase)in the co-culture system HFL1 cells.(4)The results showed that 20 nm CeO2 nanoparticles can alleviate inflammation in the co-culture system by inhibiting the expression of pro-inflammatory factors in M1 macrophages,providing a new idea for the treatment of inflammatory diseases such as rheumatoid arthritis.

Objective:To explore the clinical characteristics, diagnosis and treatment strategies, and prognosis of pulmonary embolism (PE) complicating childhood rheumatic diseases.Methods:A retrospective case series study was performed on the demographic data, laboratory indicators, imaging features, treatment regimens, and follow-up data of 8 children with rheumatic diseases complicated by PE who were admitted to the Department of Rheumatology and Immunology, Capital Center for Children′s Health, Capital Medical University from January 2014 to October 2023.Results:Among the 8 children, there were 4 boys and 4 girls, with an age of 12.0 (7.5, 13.0) years. Among the primary diseases, there were 3 cases of systemic lupus erythematosus, 2 cases of Beh?et′s disease, 2 cases of Takayasu arteritis, and 1 case of antiphospholipid syndrome. All children developed PE during the active phase of the primary disease. PE was detected at the onset of the primary disease in 3 cases, and the median time from the diagnosis of the primary disease to the development of PE was 10.0 (6.0, 25.0) months in the remaining 5 cases. Fever was present in all 8 children, 4 cases were accompanied by chest tightness, dyspnea, etc., and 2 cases only presented with fever. Laboratory examinations revealed the following results: erythrocyte sedimentation rate was 42.0 (17.0, 78.0) mm/1 h, high-sensitivity C-reactive protein was 12.7 (2.6, 78.7) mg/L, white blood cell count was 9.6 (7.2, 18.7)×10 9/L; D-dimer was 2.3 (0.9, 6.2) mg/L; and hemoglobin was (109±16) g/L.Imaging examinations revealed that 5 cases had involvement of the bilateral lower pulmonary arteries, 5 cases had peripheral embolism, and 3 cases had central PE. Complications included 3 cases of deep vein thrombosis, 2 cases of intracranial venous sinus thrombosis, and 1 case of mild pulmonary hypertension.In terms of treatment, 7 cases received anticoagulation with heparin followed by warfarin. Immunomodulation was mainly based on glucocorticoids combined with immunosuppressants, and 4 cases were combined with biological agents. The follow-up time of 4.17 (1.75, 7.17) years, the time for complete absorption of PE was 10.5 (6.0, 18.0) months; all 8 children had no target events, with no recurrence or chronic thromboembolic pulmonary hypertension, and the pulmonary artery remodeling was good. Conclusions:PE complicating childhood rheumatic diseases is closely related to the activity of the primary disease. The clinical manifestations are insidious, with fever as the main symptom. Imaging examination is the key to diagnosis.Early adoption of heparin followed by warfarin anticoagulation and glucocorticoids combined with immunosuppressants and (or) biological agents to control the primary disease can achieve a favorable prognosis.

Objective:To construct a "local-systemic" dual-track prediction model integrating the resistance index (RI) score of bilateral sacroiliac joints and the systemic immune-inflammation index (SII), and to evaluate its predictive efficacy for the active stage of ankylosing spondylitis (AS).Methods:A total of 205 patients with ankylosing spondylitis (AS) from the Second Hospital of Lanzhou University between April 2022 and April 2025 were retrospectively enrolled and categorized into an active group ( n=113) and a remission group ( n=92). Hematological parameters and ultrasound data were collected. The resistance index (RI) of the synovial area in bilateral sacroiliac joints was measured by Doppler ultrasound and scored as follows: RI < 0.5: 3 points; RI 0.5~0.55: 2 points; RI > 0.55: 1 point; undetectable blood flow: 0 points. A total bilateral RI score (range 0 to 6) was calculated. The systemic immune-inflammation index (SII) was derived as (neutrophils× platelets)/lymphocytes. Normality was tested for all continuous variables; normally distributed data were compared using the t-test, while non-normally distributed data were analyzed with the Mann-Whitney U test. Categorical variables were compared using the χ2 test or analysis of variance.Variable selection was performed using Lasso regression, and a multivariate logistic regression model was developed to assess predictive performance. Results:The proportion of patients with a bilateral RI total score≥5 was significantly higher in the active group compared to the remission group (50 of 113, 44.3% vs 2 of 92, 2.2%, χ2=55.63, P<0.001). Multivariate logistic regression analysis, after adjustment for confounding variables, identified the SII [ OR(95% CI)=1.01(1.00, 1.01), P<0.001], bilateral RI total score [ OR(95% CI)=1.67(1.29, 2.26), P<0.001], erythrocyte sedimentation rate [ OR(95% CI)=1.19(1.11, 1.30), P<0.001], and mean corpuscular hemoglobin concentration [ OR(95% CI)=1.09(1.03, 1.17), P<0.001] as independent risk factors for active AS. Conversely, lymphocyte count [ OR(95% CI)=0.42(0.18, 0.92), P=0.030] and globulin [ OR(95% CI)=0.89(0.80, 0.99), P=0.040] were significantly associated with protective effects. The bilateral RI total score demonstrated the strongest predictive effect, with each 1-point increase associated with a 67% elevation in the risk of active disease. ROC curve analysis indicated that the area under the curve (AUC) for predicting whether AS is in the active disease phase was 0.94 for the combined model (SII+bilateral RI total score), compared with 0.93 for the SII-alone model and 0.92 for the bilateral RI total score-alone model, demonstrating superior predictive performance of the combined model (SII+bilateral RI total score). An online prediction tool has been developed based on the combined model. Conclusion:The dual-track prediction model, which integrates local joint hemodynamic characteristics and systemic immune-inflammatory status, facilitates a multidimensional assessment of the risk of active AS and provides an objective basis for early identification.

ObjectiveTo analyze the characteristics of 150 patients with spinal cord injury complicated with spasticity. MethodsA cross-sectional survey was conducted on 150 patients with spinal cord injury accompanied by spasticity from September, 2019 to December, 2024. Their age, gender, cause of injury, injury site, severity of injury, spasticity severity and other indicators were recorded. The relationships between different characteristics were analyzed, and a correlation analysis of disease duration, spasticity grade, injury level, injury severity and age were conducted. ResultsThere was no significant difference in age distribution between patients with tetraplegia and paraplegia (Z = 0.806, P = 0.420). The proportions of trauma (χ² = 3.982, P = 0.046) and tetraplegia (χ² = 10.559, P = 0.010) were higher in males than in females. Trauma was the main cause of injury in both tetraplegia and paraplegia patients; the proportion of tetraplegia was higher than paraplegia in trauma patients, while paraplegia was higher than tetraplegia in non-trauma patients (χ² = 11.885, P < 0.001). Patients with tetraplegia was dominated by incomplete injury, whereas patients with paraplegia was dominated by complete injury (χ² = 10.885, P = 0.012). Grade A injury was predominant in trauma patients (P = 0.003). Spasticity grade showed a very weak positive correlation with disease duration (r = 0.175, P = 0.032) and age (r = 0.168, P = 0.040). Injury severity showed a very weak positive correlation with age (r = 0.183, P = 0.025). ConclusionCharacteristics of patients with spinal cord injury complicated with spasticity is different with gender, cause of injury, injury level, injury severity.

ObjectiveDonkey hide is the sole legally designated raw material for the preparation of the traditional Chinese medicine Ejiao. The quality stability of donkey hide during preservation directly determines the efficacy and safety of Ejiao. This study focuses on the dynamic succession of microbial communities during the preservation of donkey hides from different origins, aiming to clarify the correlation between microbial biodiversity difference and the degradation profiles of hide collagen and critical biochemical components, thereby providing a theoretical foundation for developing targeted preservation strategies based on microbial regulation. MethodsDonkey hides originating from four different regions were subjected to an accelerated microbial aging assay to simulate the spoilage process. The microbial community succession was analyzed using high-throughput sequencing. Microstructure changes and pore structure characteristics were assessed by scanning electron microscopy and mercury intrusion porosimetry, respectively. Additionally, the content of major components, including lipids, proteins, and sugars were determined by biochemical methods. ResultsAfter 96 h of aging, the collagen fiber structure in Africa donkey hides (ADH) exhibited significant degradation and collapse, followed by Xinjiang donkey hides (XDH). Instead, the microstructure of Dong’e black donkey hides (DDH) and Peru donkey hides (PDH) remained relatively intact. The porosities of DDH, XDH, PDH, and ADH increased from 27.9%, 15.7%, 30.3%, and 46.2% to 36.5%, 52.6%, 42.8%, and 57.7%, respectively, during the aging process, which suggested that the originally compact fiber structure was disrupted by microbial aging. Fourier transform infrared spectrometer analysis revealed the amide bands in XDH exhibited relatively weak intensity, and no collagen amide I band was observed in ADH. Meanwhile, the lipid and protein contents decreased in all four types of donkey hides, indicating that these components served as the primary nutrient sources for the growth of microorganism. Notably, the most severe collagen degradation was observed in XDH and ADH. A substantial increase was detected in the total soluble sugar in PDH aging solution and hydroxyproline in the ADH aging solution, respectively. These results indicated that donkey hides exhibit distinct patterns of structural degradation and nutrient utilization. Furthermore, the viable cells number of donkey hides increased sharply after 48 h of aging. Metagenomic analysis revealed that the relative abundance of Euryarchaeota in ADH, PDH and XDH declining from initial 93.19%, 97.73% and 30.08% to 0.79%, 1.43% and 0.02% after 96 h, respectively. Conversely, a significantly increase was observed in the abundance of Bacillota, with a marked increase in ADH, peaking at 92.75%. Additionally, the abundance of Pseudomonadota in PDH increased from 0.10% to 87.84%, suggesting that Bacillota and Pseudomonadota may be key factors exacerbating donkey hide spoilage. Unlike the other three types of donkey hides, the dominant bacterial phylum in DDH shifted from Pseudomonadota to Bacteroidota, characterized by a substantial abundance increase of Bacteroidota from 0.13% to 44.22%. ConclusionRegional variation in origin significantly influence the microbial aging of donkey hides, leading to distinct patterns of structural deterioration and differential nutrient utilization. Therefore, implementing origin-specific preservation strategies, through the precisely controlling environmental factors to suppress harmful phyla such as Bacillota and Pseudomonadota, is crucial for enhancing the storage quality of donkey hides.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.