Jian Chen

Ultrasound can alter the state of lipid membranes through mechanical, thermal, and sonochemical effects. Moving beyond the view of membranes as passive carriers, this review examines membranes as both targets of ultrasound-induced stimuli and tunable functional interfaces in cancer nanomedicine. We compare the acoustic response characteristics of natural cell membranes, artificial lipid membranes, and hybrid membranes from the perspective of membrane engineering, discussing how membrane deformation, phase transition, and oxidation contribute to hypoxia alleviation, localized drug release, combination therapy, and immune modulation, while the evidence directly linking membrane changes to therapeutic outcomes remains limited. We propose that a key to clinical translation is to establish a quantifiable and reproducible relationship between membrane composition, in situ acoustic exposure, membrane response, and therapeutic output. Redefining membranes as tunable acoustic-responsive interfaces could provide a more controllable design framework for ultrasound-enhanced cancer nanotherapy.

The rapid hemostasis of deep and irregular wounds is of great clinical significance. In this study, an injectable hemostatic hydrogel based on bioorthogonal conjugation was developed. This gel uses thrombin (TMB) as the hemostatic active substance and 4ARM-PEG-N₃ as the crosslinking agent, which undergo orthogonal conjugation via the classic azide–alkyne click reaction to form an injectable hydrogel (TMB-PEG). The resulting hydrogel exhibited a transparent, injectable gel state. TEM images revealed that the hydrogel comprised sheet-like structures and interwoven fibers with a diameter of approximately 100 nanometers. In a puncture bleeding wound model, hemostasis with the TMB-PEG hydrogel required only 25 s, with a blood loss of 1.9 ± 1.3 mg, both approximately one-sixth of that of the control group. Moreover, the hemostatic performance of the TMB-PEG hydrogel was far superior to that of three other commonly used hemostatic materials. Furthermore, cephalosporin antibiotics were conjugated to the hemostatic gel via orthogonal reactions, endowing it with significant broad-spectrum antibacterial activity, achieving over 99% antibacterial efficacy against both Gram-negative and Gram-positive bacteria.

Early and accurate tumor detection remains a major challenge in oncology. Here, we develop a tumor-targeted dual-modality imaging probe, SonoVue-DBCO-Cy5 (SDC), by embedding DBCO-modified Cy5 fluorophores into the lipid shell of clinically approved SonoVue® microbubbles. In tumor cells metabolically labeled with Ac4ManNAz, azide-bearing glycans allow specific SDC recognition through copper-free strain-promoted azide–alkyne cycloaddition (SPAAC). The combined effects of SPAAC targeting and ultrasound-induced microbubble cavitation greatly enhance both fluorescence labeling and contrast-enhanced ultrasound (CEUS) signals by increasing vascular permeability and promoting probe accumulation in tumor tissues. As a result, SDC achieves 2.6-fold higher tumor retention and enables tumor visualization about 36 hours earlier than conventional CEUS alone. Together, these features make SDC a clinically translatable, bioorthogonal dual-modality imaging platform that integrates molecular targeting and cavitation synergy for real-time, non-radioactive early tumor diagnosis and image-guided therapy.

Background Type 2 diabetes mellitus (T2DM) is associated with a spectrum of liver disorders, ranging from nonalcoholic fatty liver disease to fibrosis and hepatocellular carcinoma. Early detection of hepatic changes is critical for risk stratification and management. Sound Touch Viscosity Imaging (STVi) allows noninvasive quantification of both tissue elasticity and viscosity, potentially providing complementary information beyond conventional stiffness measurements. This study aimed to evaluate the diagnostic value of liver viscosity as a biomarker in patients with T2DM. Methods 99 patients with T2DM and 73 healthy controls underwent liver assessment using STVi. Measurements of hepatic elasticity and viscosity were obtained under standardized protocols. Laboratory and demographic data were collected. Statistical analyses included Mann–Whitney U tests, Student’s t-tests, receiver operating characteristic (ROC) curve analysis, and multivariate logistic regression to assess the diagnostic performance of elasticity, viscosity, and their combination. Correlation between viscosity and elasticity was evaluated using Spearman analysis. Results T2DM patients showed significantly elevated liver viscosity (1.54 ± 0.36 Pa·s) and elasticity (7.37 ± 2.07 kPa) compared to controls (P < 0.001). Viscosity and elasticity were positively correlated (r = 0.683, P < 0.001). ROC analysis revealed superior diagnostic performance for viscosity (AUC = 0.836) over elasticity (AUC = 0.774), with the combined model yielding an AUC of 0.89. Multivariate analysis identified viscosity, ALT, and age as independent predictors of T2DM. Conclusions Liver viscosity serves as a sensitive biomarker for early liver alterations in T2DM, outperforming stiffness alone. Ultrasound-based viscosity imaging holds promise for non-invasive screening and risk stratification of liver injury in diabetic populations.

Background: The accurate monitoring of chronic kidney disease (CKD) progression is clinically challenging, as conventional shear wave elastography (SWE) only evaluates tissue stiffness by focusing solely on quantifying tissue elasticity, and this parameter is influenced by hemodynamic fluctuations. Sound touch viscosity imaging (STVi) addresses these limitations by simultaneously quantifying both elasticity and viscosity, providing a comprehensive biomechanical profile that better reflects the complex pathophysiology of CKD. This dual-parameter approach enables more reliable disease staging and progression monitoring. This study aimed to investigate whether STVi-derived viscosity parameters outperformed conventional elasticity measurements in CKD diagnosis and staging, establish clinically applicable cut-off values for viscosity to stratify CKD severity, and explore the pathophysiological correlation between viscoelastic properties and renal fibrosis. Methods: In total, 127 CKD patients [staged G1–G5 under the Kidney Disease: Improving Global Outcomes (KDIGO) criteria] and 84 healthy controls (HCs) were prospectively enrolled in this study. Ultrasound viscoelastic imaging was performed using Mindray Resona A20 systems with standardized protocols. Renal viscosity [pascal-seconds (Pa·s)] and elasticity (kPa) were measured simultaneously through Voigt model-based shear wave dispersion analysis. Histopathological correlation was established via image-guided biopsies. Results: The viscosity parameters showed superior diagnostic performance compared to the elasticity measurements. At the optimal cut-off value of 1.66 Pa·s, the area under the curve (AUC) for the right kidney was 0.95 [95% confidence interval (CI): 0.92–0.99] (sensitivity 94.4%, specificity 96.2%). The viscosity values showed a strong correlation with pathological grading (Spearman’s r=0.82, P0.90) and the significantly higher diagnostic accuracy for detecting inflammatory changes (AUC 0.95 vs. 0.73 for elasticity, PConclusions: STVi imaging provides a novel, non-invasive biomarker for assessing renal fibrosis in CKD that outperforms conventional SWE. The established cut-off values and characteristic progression patterns offer clinically actionable thresholds for early detection and staging. Future multicenter studies should be conducted to validate these findings across diverse populations and etiologies.

Background: chronic kidney disease (CKD) remains a global health challenge with limitations in current diagnostic methods, including the invasiveness of biopsies and variability of estimated glomerular filtration rate (eGFR). This study aimed to develop a noninvasive diagnostic model integrating ultrasound viscoelasticity parameters to address these gaps.Methods: A prospective cohort of 228 participants underwent standardized renal ultrasound with viscoelastic imaging (Mindray Resona A20) to assess viscoelastic parameters and structural metrics. Key predictors were selected through LASSO regression, and a logistic regression diagnostic model was constructed. Model performance was comprehensively evaluated by analyzing discriminative ability (AUC, sensitivity/specificity), calibration (Brier score, calibration curves), and clinical utility (nomogram development, risk stratification and stage-specific decision curve analysis). Multiclass analysis was implemented to evaluate stage-specific performance (Class 1: normal; Class 2: G1-3; Class 3: G4-5) using one-vs-rest ROC methodology. All statistical analyses incorporated 1000 bootstrap iterations for robust variance estimation.Results: The diagnostic model demonstrated superior accuracy with an AUC of 0.932 (95% CI 0.908-0.956) in validation sets. Pathological analysis revealed that viscosity values were significantly elevated in CKD patients compared to controls (1.99 vs. 1.64 Pa·s, P < 0.001), while elasticity and shear wave velocity showed increases of 12.7%-13.2% and 5.3% respectively (P < 0.001). For clinical implementation, the model incorporated a visual nomogram that converted scores ranging from 0 to 160 points into CKD probability estimates between 0.1 and 0.9, with an optimal cutoff value of 0.383 providing balanced sensitivity of 88.4% and specificity of 87.8%. Decision curve analysis confirmed clinical utility across probability thresholds of 20%-80%, with peak net benefit at 40% threshold probability. Multiclass analysis revealed stage-dependent performance: Class 3 showed the highest discrimination (AUC = 0.918), followed by Class 1 (AUC = 0.884) and Class 2 (AUC = 0.774), with significant inter-stage differences (DeLong’s test P < 0.001).Conclusion: This study establishes a novel “function-structure” integrated diagnostic paradigm for CKD, combining the accuracy of ultrasound parameters with unique structural insights. The model’s noninvasive nature and stability under physiological variability make it particularly valuable for early detection and longitudinal monitoring.