Sonogenetic holds great potential for modulating cellular functions and behaviors. However, developing hypersensitive ultrasound (US)-responsive receptors remains a substantial challenge. Here, we combine AlphaFold3 prediction with molecular dynamics simulations to identify a hypersensitive Gpr114 protein variant (T-Gpr114) that responds to short-pulse US stimulation for activation. We further design sonogenetic macrophages (MΦ) by fusing T-Gpr114 to a synthetic genetic circuit, this circuit initiates expression of the transcription factor ID3 upon short-pulse US treatment. In vivo assays using female tumor-bearing mice demonstrate that sonogenetic-MΦ suppress tumor growth with no obvious systemic toxicity, and exhibit enhanced anti-tumor efficacy relative to cells with constitutive ID3 expression. Single-cell RNA sequencing reveals that sonogentic-MΦ potentiate the recruitment recruitment of CD8+ T cells compared with constitutive ID3-overexpressing macrophages. In this work, this T-Gpr114-based US-hypersensitive gene circuit extends the scope of remote control over the activation of diverse cell types, thereby facilitating the programming of therapeutic cells.

The major target for SARS-CoV-2, angiotensin-converting enzyme 2 (ACE2), is widely expressed in the cardiovascular system, leading to vascular endothelial cell damage and inflammation. The aim of present study is to investigate impacts of Omicron on arterial structure and stiffness using longitudinal data with matched controls. In this longitudinal study, we collected clinical characteristics and laboratory values from participants recovered after COVID-19 infections during the Omicron wave (n = 45) and matched uninfected controls (n = 85) around the time of 2022 change in control measures. Corresponding baseline data in 2021 were included for repeated analyses. Carotid arterial properties, including intima-media thickness (IMT), diameter, stiffness and wave reflections were integratively assessed by ultrasound based on the raw radio frequency signal. Clinical characteristics and carotid properties were matched between COVID-19 and control groups at baseline. Carotid IMT was thicker in recovered participants than controls (567 ± 97 vs. 532 ± 88 μm, P = 0.037) at the follow-up of 2022, while no significant differences were found for the diameter, arterial stiffness and wave reflections in the two groups. Repeated ANOVA further revealed that COVID-19 infection was associated with higher increase of carotid IMT and concomitant concentric remodeling in comparison with controls (Ptime × COVID−19 < 0.01). Carotid structure is changed in recovered study participants of COVID-19 during the Omicron wave, featured by increased IMT and concentric remodeling. On the other hand, arterial stiffness and wave reflections seemed unimpacted by the Omicron variant. Whether the Omicron related carotid structure change is permanent or temporary needs further investigation by long-term follow-up.

Homozygous familial hypercholesterolemia (HoFH) presents a persistent and difficult-to-treat condition. This recalcitrance stems largely from loss-of-function mutations within the low-density lipoprotein receptor (LDLR) gene, which severely undermine the efficacy of standard therapeutic regimens. Here, we report a bioinspired "targeting and blockade" strategy for the efficient delivery of functional Ldlr mRNA to hepatocytes. This approach is realized through a rationally designed platform, Szd + AP@ExoE-Ldlr, which integrates APOA1-functionalized exosomes for hepatocyte-targeted delivery with a preemptive macrophage blockade using the clinical ultrasound contrast agent Sonazoid (Szd). The APOA1 modification confers specific recognition by the scavenger receptor class B type 1 on hepatocytes, while the pre-saturation of Kupffer cells with Szd significantly mitigates nonspecific clearance by the mononuclear phagocyte system (MPS). In a HoFH murine model, this synergistic strategy markedly enhanced the accumulation of exosomes in hepatocytes and achieved robust restoration of hepatic LDLR expression. Consequently, it elicited a profound correction of the atherogenic lipid profile and substantially attenuated the progression of atherosclerosis. A comprehensive biosafety evaluation confirmed the excellent biocompatibility of this platform. Our work provides a promising and broadly applicable solution for the treatment of liver-related genetic disorders by simultaneously overcoming the critical barriers of targeted delivery and MPS evasion.

Wearable ultrasound technology has recently emerged as a promising tool in medicine that combines advances in materials science, electronic engineering, and medical imaging to provide innovative solutions for clinical diagnosis and therapy. By miniaturizing ultrasound devices and incorporating flexibility and intelligence, this technology has enabled close skin contact and continuous real-time monitoring of physiological parameters. Compared with conventional ultrasound systems, wearable devices not only enhance patient comfort but also overcome the limitations of traditional ultrasound devices, paving the way for multisystem and multiscenario medical applications. Furthermore, wearable ultrasound devices offer unique advantages in specialized settings, such as intensive care monitoring, drug delivery surveillance, and rehabilitation outcome assessment, establishing them as a key enabler of precision medicine. However, despite their significant potential, wearable ultrasound devices face challenges related to technological maturity, data processing capabilities, and clinical standardization, which require further investigation and refinement.

[This corrects the article DOI: 10.3389/fmed.2026.1850790.].

Cancer immunotherapy has achieved remarkable progress, but its clinical efficacy is still limited by tumor heterogeneity and the immunosuppressive tumor microenvironment (TME). Ultrasound, as a non-invasive and highly controllable physical modality, can regulate anti-tumor immune responses by inducing immunogenic cell death, promoting antigen release, and enhancing immune cell infiltration into tumors. Moreover, recent advances in ultrasound-responsive materials, including living and synthetic systems, have provided novel strategies by enabling targeted, spatiotemporal regulation of the TME. These biocompatible materials enhance immune cell penetration, reduce systemic toxicity, and amplify anti-tumor immunity through precise modulation of immune signaling pathways. In this review, we summarize the mechanisms by which ultrasound reshapes anti-tumor immune responses, discuss the rational design of ultrasound-responsive materials to optimize immunotherapeutic efficacy, highlight their translational potential in cancer treatment, and propose the conceptual framework of sonoimmunology.

Diabetic cardiomyopathy (DCM) involves progressive cardiac dysfunction driven by vascular endothelial injury and cellular senescence. However, precisely targeting pre-senescent cells remains a major therapeutic challenge. Herein, through single-cell RNA sequencing of diabetic mouse hearts, we identified VCAM1 -positive (VCAM1+) cells as a distinct pre-senescent endothelial population. Both scRNA-seq and subsequent immunofluorescence analyses confirmed the concurrent upregulation of cGAS-STING signaling within this VCAM1 + population, nominating it as a critical therapeutic target for early intervention. To specifically deliver a STING antagonist to these cells, we developed a biomimetic delivery platform based on engineered HEK293T cell-derived nanovesicles. Through lipidomic analysis, we reprogrammed the vesicle membrane composition to mimic that of endothelial cells, thereby creating nanovesicles with enhanced membrane fusogenic properties (F-NVs). After loading with H151, a potent STING pathway inhibitor that acts by inhibiting STING phosphorylation, the resulting F-NVs-tVCAM1@H151 efficiently targeted VCAM1 + pre-senescent cells, potently inhibited their transition into a senescent state, and significantly reduced the overall senescent burden in the diabetic heart. Consequently, this targeted strategy alleviated cardiac microvascular injury and markedly improved cardiac function in diabetic mice. This work identifies VCAM1 as a novel pre-senescent marker and demonstrates membrane lipid engineering as an effective approach for targeted nanovesicle delivery, offering a precise targeted therapeutic paradigm for DCM.

INTRODUCTION:Clonal hematopoiesis of indeterminate potential (CHIP), driven by somatic mutations (e.g., TET2), is an independent risk factor for atherosclerosis (AS). CHIP-mutant macrophages promote plaque inflammation, but targeted therapies are lacking. Crucially, whether these clones acquire immunogenic neoantigens-enabling immune clearance-remains unexplored. OBJECTIVE:To investigate if Tet2-mutant cells in CHIP-associated AS develop immunogenic neoantigens and evaluate a neoantigen-targeting vaccine strategy. METHODS:Tet2 was edited in hematopoietic cells via CRISPR/Cas9 and transplanted into Ldlr-/- mice fed a high-fat diet to model CHIP-accelerated AS. DNA and RNA sequencing of Tet2-mutant macrophages identified nonsynonymous mutations. Neoantigen immunogenicity was predicted in NetMHCpan. A therapeutic vaccine (GelVax) encapsulating mutant cell lysates (neoantigen source), GM-CSF (DC recruitment), and R848 (TLR agonist) within a biocompatible hydrogel was developed. Efficacy was assessed in the AS model. RESULTS:Tet2 deficiency exacerbated atherosclerosis (+72% plaque area) and systemic inflammation.  DNA and RNA sequencing results identified 2 mutations showing high MHC-I binding affinity, suggesting neoantigenicity. GelVax vaccination reduced aortic plaque burden by 45%, selectively cleared Tet2-mutant macrophages in plaques, attenuated systemic cytokines (TNF-α, IL-1β) and improved plaque stability (↓ necrotic core, ↑ collagen). The protection was primarily CD8+ T-cell dependent. CONCLUSION:Tet2-mutant cells in CHIP-associated AS acquire immunogenic neoantigens. Leveraging these antigens via a hydrogel vaccine induces clone-specific CD8+ T cell responses, clears pathogenic macrophages, and ameliorates atherosclerosis. This validates mutant neoantigens as actionable targets for CHIP-driven cardiovascular disease.

ObjectiveThis study aimed to systematically investigate the association between obstructive sleep apnea syndrome (OSAS) and metabolic syndrome (MetS), with a particular focus on severity–stratified analysis, in order to clarify the differential risks of MetS and its components (hypertension, hyperglycemia, etc. ) among patients with different levels of OSAS severity.MethodsA comprehensive literature search was conducted in Web of Science, PubMed, Cochrane, and Embase databases from their inception to June 1, 2025, using keywords related to “sleep apnea syndrome” and “MetS”. After rigorous quality evaluation and data extraction of the included studies, a stratified meta-analysis by OSAS severity was performed using Stata 17.0 software.Subgroup analysis and meta-regression were further applied to explore heterogeneity sources, enhancing the reliability of results.ResultsA total of 10 studies involving 10,205 participants were included. The meta-analysis revealed that the risk of developing MetS in patients with moderate-to-severe OSAS was 2.18 times higher than in those with mild OSAS (OR = 2.18, 95%CI:1.30–3.68, P < 0.001). The risk of hypertension in patients with moderate-to-severe OSAS was 2.19 times higher than that in patients with mild OSAS (OR = 2.19, 95%CI:1.57–3.06, P < 0.05). The risk of hyperglycemia in patients with moderate-to-severe OSAS was 1.50 times higher than that in patients with mild OSAS(OR = 1.50, 95%CI:1.01–2.18). Subgroup analysis results showed that heterogeneity existed between studies published before 2016 (I2 = 54.6%, P = 0.051) and those published in or after 2016 (I2 = 65.2%, P = 0.035). Meta-regression analysis indicated that the heterogeneity in the results of studies on the association between OSAS and the risk of MetS was primarily due to the year of publication of the literature (2016).ConclusionThis study found that patients with moderate to severe OSAS have a 2.18 times higher risk of developing MetS than those with mild OSAS. Their risk of hypertension and hyperglycemia also goes up significantly. For patients with moderate to severe OSAS, it makes sense to prioritize MetS screening and start early intervention to lower their risk of developing MetS.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/.

OBJECTIVE:To investigate the diagnostic superiority of super-resolution ultrasound (SRUS) imaging over conventional contrast-enhanced ultrasound (CEUS) in differentiating breast masses, and to evaluate its clinical potential as a non-invasive tool for predicting histological grade, molecular subtypes and immune microenvironment characteristics. METHODS:A prospective cohort of 84 patients (25 benign, 59 malignant) underwent pre-biopsy assessments of CEUS and SRUS parameters. CEUS evaluated qualitative features (shape after enhancement, feeding vessel) and quantitative indices (area under the curve [AUC], peak intensity). SRUS quantified microvascular architecture via Vessel Ratio (area of vascular lumen), Complexity Level (vascular branching complexity), MeanDen (Mean Density, average microbubble signal density) and MeanVel (Mean Velocity, microbubble flow speed). Receiver operating characteristic curve analysis compared diagnostic accuracies, while correlations with histological grade (I-III), molecular subtypes (Luminal A, Luminal B, human epidermal growth factor receptor 2-enriched and triple-negative breast cancer) and CD3+ T-cell infiltration were evaluated. RESULTS:Malignant tumors showed distinct SRUS profiles: higher Vessel Ratio (29.8% vs. 13.6%, p < 0.001), MeanDen (12.46 ± 6.11 vs. 7.47 ± 2.60, p = 0.011) and MeanVel (14.19 ± 4.62 vs. 9.71 ± 2.96, p = 0.038) compared to benign lesions. SRUS alone achieved an AUC of 0.902 for malignancy discrimination, outperforming CEUS (AUC = 0.866), with combined CEUS + SRUS improving AUC to 0.939 (p < 0.05 for all comparisons). MeanDen inversely correlated with histological grade (Grade III < I/II, p < 0.05), while Complexity Level and MeanDen distinguished molecular subtypes. CD3+ infiltration was positively associated with higher Complexity Level (p < 0.05). CONCLUSION:SRUS provides multi-dimensional characterization of breast masses and performs better than CEUS. Its parameters enable non-invasive prediction of tumor malignancy, molecular phenotypes and immune infiltration, positioning SRUS as a promising tool for pre-operative risk stratification, personalized treatment guidance and therapeutic monitoring in clinical oncology.

Safe and efficient drug delivery is as important as drug development. Biological barriers, such as cell membranes, present significant challenges in drug delivery, especially for newly developed protein-, nucleic acid-, and cell-based drugs. Ultrasound-mediated drug delivery systems offer a promising strategy to overcome these challenges. Ultrasound, a mechanical wave with energy, produces thermal effects, cavitation, acoustic radiation, and other biophysical effects. Used alone or in combination with microbubbles or sonosensitizers, it breaks biological barriers, enhances targeted drug delivery, reduces adverse reactions, controls drug release, switches on/off drug functions, and ultimately improves therapeutic efficiency. Various ultrasound-mediated drug delivery methods, including transdermal drug delivery, nebulization, targeted microbubble destruction, and sonodynamic therapy, are being actively explored for the treatment of various diseases. This review article introduces the principles, advantages, and applications of ultrasound-mediated drug delivery methods for improved therapeutic outcomes and discusses future prospects in this field.

Rationale: Engineered bacteria have recently emerged as a novel and promising strategy for cancer immunotherapy. Nonetheless, precise spatiotemporal regulation of therapeutic gene expression within these bacteria is essential to optimize therapeutic efficacy while minimizing adverse effects. This study aims to develop a system for precise, ultrasound-driven regulation of gene expression in bacteria to enable targeted tumor therapy. Methods: A modular system (Stabilized Open RNA thermometer, SORT) was designed, comprising a modified RNA thermometer with QKI response elements (QRE), therapeutic coding sequences, and the RNA binding motif of QKI. As a proof-of-concept, the bacteria VNP20009 was engineered with plasmids expressing mutated IL-2 or soluble PD-1 (sPD-1) within the SORT cassette. Syngeneic tumor mouse models (4T1 breast cancer and A20 lymphoma) were used to assess bacterial accumulation, therapeutic protein expression, anti-tumor immunity, and toxicity. Results: Upon a single session of ultrasound irradiation, IL-2 or sPD-1 expression was efficiently and durably induced in the engineered VNP20009. In mouse tumor models, SORT-equipped VNP20009 accumulated in the tumor region and diminished from organs including the liver and lung. Ultrasound irradiation enabled the therapeutic protein (IL-2 or sPD-1) to be spatiotemporally switched-on within the tumor region. This localized expression resulted in robust activation of anti-tumor immunity alongside tolerable toxic effects. Conclusions: The modular SORT platform provides a refined approach for bacteria-based therapy, enabling spatiotemporal control of therapeutic gene expression. This system enhances anti-tumor efficacy while reducing off-target toxicity, representing a promising strategy for cancer immunotherapy.

This study aimed to develop and validate a novel strain elastography (SE) radiomics nomogram for diagnosing breast cancer (BC) by analyzing intratumoral and peritumoral regions. A cohort of 322 patients, comprising 217 from hospital #1 (06/2021–05/2023) and 105 from hospital #2 (06/2022–05/2023) with breast lesions, was enrolled. Radiomic features were extracted from intratumoral and peritumoral (0–1 mm, 1–2 mm, 2–3 mm) regions on strain elastography images. Significant features were selected using Mann–Whitney U test, Spearman's correlation coefficient, and LASSO logistic regression. A radiomic model was constructed utilizing these features, followed by the development of a radiomic nomogram integrating optimal features. The intratumoral radiomic model exhibited an area under the receiver operating characteristic curve (AUC) of 0.774 (95

Background: Abnormal alterations in cerebral blood flow (CBF) have been implicated in cognitive decline and neurodegeneration. Maintaining adequate CBF in astronauts during long-duration microgravity is therefore crucial for the success of manned spaceflight. However, the quantitative assessment of CBF during space missions remains challenging. Methods: Thirty-six participants underwent a 90-d −6° head-down tilt bed rest (HDTBR) protocol, a well-established ground-based analog of microgravity. Multimodal imaging data, including internal carotid artery Doppler ultrasound and brain magnetic resonance imaging, were collected during HDTBR. Multiple machine learning (ML) algorithms were developed to investigate carotid–CBF mapping relationship and establish CBF change prediction models. Results: After 90-d HDTBR, significant regional CBF decreases were observed, primarily in the right Heschl’s gyrus, right middle cingulate gyrus, and right superior frontal gyrus. The optimal ML model CatBoost showed robust predictive performance for CBF in these regions (right Heschl’s gyrus: AUC = 0.88, accuracy = 0.84; right middle cingulate gyrus: AUC = 0.92, accuracy = 0.83; right superior frontal gyrus: AUC = 0.82, accuracy = 0.72). To enhance accessibility and practical utility, the prediction model was implemented as an interactive web application for in-orbit deployment. Conclusion: This study demonstrates the feasibility of constructing ML-driven CBF prediction models under microgravity based on multimodal imaging. The developed prediction models show promise as early warning tools for brain health of astronauts in spaceflight.

BACKGROUND:The conventional 3-grade scheme recommended by American Society of Echocardiography (ASE) for secondary tricuspid regurgitation (STR) is limited by the frequent disagreement between multiparametric and single-parameter classifications and heterogeneous prognosis within the moderate group. We tested the hypothesis that the expert-recommended 4-grade scheme has better inherent agreement compared to the ASE scheme and further improved it as a revised 4-grade scheme using the corrected proximal isovelocity surface area (PISA) method to calculate effective regurgitant orifice area (EROA) and regurgitant volume (RegVol), along with the integration of other quantitative parameters. METHODS:A total of 178 patients with STR were included. The moderate grade according to the 3-grade ASE-recommended scheme was split into mild-moderate and moderate-severe grades following recent expert suggestions. The agreement between the multiparametric and single-parameter grading in TR severity was analyzed using the weighted kappa test. The structure and function of tricuspid valve and right heart, including the conventional parameters, strains, and the right ventricular‒pulmonary artery (RV-PA) coupling, were compared across grade severities. The partition values of quantitative regurgitation parameters were further determined by receiver operating characteristic curve analyses to develop the revised 4-grade scheme with involvement of corrected PISA method. RESULTS:The expert-recommended 4-grade scheme demonstrated better multiparametric and single-parameter agreement of RegVol (к = 0.901) in TR grading compared to the ASE-recommended 3-grade scheme (к = 0.506). Both RV strain and RV-PA coupling were significantly lower in patients with moderate-severe STR compared to those with mild-moderate STR (P < .05). The new cutoff values of EROA (0.34 cm2; area under the curve = 0.945) and RegVol (35 mL; area under the curve = 0.958), obtained using the corrected PISA method, demonstrated excellent accuracy in distinguishing mild-moderate from moderate-severe STR. CONCLUSIONS:The revised 4-grade scheme for STR severity exhibited better inherent agreement than the ASE-recommended scheme as well as matching with the right heart functional variations.

Congenital heart disease (CHD) has been one of the most serious problems in newborns. For fetal heart health care, 3D modeling and printing technology has been adopted in diagnosis of CHD during antenatal care. However, the development of 3D printing techniques and their applications in clinic have been hindered by the manually processing of ultrasound (US) volume data in clinical practice. To overcome this problem, we present an interactive semi-automatic method based on deep learning that uses manually processing results from expert sonographers for training. The accuracy, interpretability, and variability of the performances were evaluated on the validation set demonstrated that, compared with a physician with three years’ experience, Faster-RCNN-based Threshold (FRT) had achieved better performance on outflow tracts view (OTV) and three-vessel view (TVV). No significant difference was found among the clinical evaluation values, in proportion, measured from the model rebuilt by FRT and that from US volume data. Furthermore, reconstruction time of fetal heart blood pool model was reduced from approximately 5 hours to 5 minutes. Our results showed that deep learning has the ability to process US data accurately, representing an important step towards the reconstruction of the fetal heart digital model, which may make huge progress in clinical diagnosis and treatment of CHD during pregnancy.

Background:The arterial stiffening is attributed to the intrinsic structural stiffening and/or load-dependent stiffening by increased blood pressure (BP). The respective lifetime alterations and major determinants of the two components with normal aging are not clear. Methods:A total of 3053 healthy adults (1922 women) aged 18-79 years were enrolled. The carotid intima-media thickness, diameter, and local BPs were automatically determined by the radio frequency ultrasound system. The Peterson and Young elastic moduli were then calculated to represent total arterial stiffness. Structural stiffness was recalculated at a reference BP of 120/80 mmHg with established models. Load-dependent stiffness was the difference between total and structural stiffness. Results:Both structural and load-dependent stiffness increased with aging, with much larger changes in the structural components. The age-related increasing rates were higher in women for the structural stiffness than men (P < 0.05), but similar for the load-dependent stiffness. The clinical characteristics and arterial stiffness were widely correlated, but most correlations were quite weak (r < 0.3) other than BPs. Multiple regression analyses adjusted for sex, age and other clinical correlates showed that structural stiffness increased with pulse pressure (PP) and load-dependent stiffness increased with mean arterial pressure (MAP), respectively. Conclusion:The age-related arterial stiffening is mainly caused by the intrinsic structural stiffening, which demonstrated significant age-sex interaction. BPs were the major clinical determinants of arterial stiffness, with PP and MAP associated with different arterial stiffness components. The differentiation of the structural and load-dependent arterial stiffness should be highlighted for the optimal vascular health management.

Congenital heart disease (CHD) has been one of the most serious problems in newborns. Forfetal heart health care, 3D modeling and printing technology have been adopted in the diagnosis of CHD during antenatal care. However, the development of 3D printing techniques and their clinical applications have been hindered by the manual processing of ultrasound (US) volume data in clinical practice. To overcome this problem, we present an interactive semi-automatic method based on deep learning that uses manual processing results from expert sonographers for training. The accuracy, interpretability, and variability of the performances were evaluated on the validation set. The results demonstrated that compared with a physician with less than 3 years of experience, a better Faster-region-based convolutional neural network-based threshold was achieved using our proposed fetal heart reconstruction technique (FRT), with enhanced performance based on the outflow tract view and three-vessel view. No significant difference was found among the clinical parameters, in proportion, measured from the model rebuilt using FRT and US volume data. Furthermore, the reconstruction time of the fetal heart blood pool model was reduced from approximately 5 h to 5 min. Our results indicate that deep learning has the ability to process US data accurately, representing an important step towards the reconstruction of the fetal heart digital model, which is critical for advancing clinical diagnosis and treatment of CHD during pregnancy.