The activation of the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway represents a promising strategy for eliciting host immune responses to eradicate tumors. However, the clinical application of STING agonists is severely hindered by the tumor immunosuppressive microenvironment (TIME) and non-specific delivery. Herein, a biomimetic phototheranostic nanotrident (mPDXZ@M) is meticulously designed through hierarchical engineering of mesoporous polydopamine (mPDA). Upon near-infrared laser irradiation, mPDA-mediated photothermal therapy (PTT) evokes robust cell apoptosis and immunogenic cell death, thereby ameliorating the TIME and triggering ATP secretion for Zn2+ and 5,6-dimethylxanthenone-4-acetic acid (DMXAA) release. The Zn2+ then inhibits glycolysis, lowering heat shock protein 70 and sensitizing tumors to PTT. Ultimately, DMXAA activates the cGAS-STING pathway to promote dendritic cell maturation and cytotoxic T cell infiltration, collectively driving potent tumor regression. Overall, this tailor-engineered phototheranostic nanotrident exemplifies a transformative strategy for self-amplified photo-immunometabolic therapy, enabling effective immune priming and pronounced tumor suppression.

Background: Emerging evidence suggests that platelet activation and aggregation are common factors in both metabolic syndrome (MetS) and severe COVID-19, emphasizing the need to investigate their biological connection. Objectives: We hypothesized that enhanced platelet aggregation mediates the association between MetS and severe COVID-19. This study aimed to determine whether platelet aggregation serves as a mechanistic link between MetS and COVID-19 severity and to develop an image-based biomarker capable of predicting severe disease. Methods: We conducted massive image-based profiling of circulating platelets in a retrospective cohort of 327 COVID-19 patients (63.9% male; median age, 59.0 years) with metabolic records. Morphologic features of platelets, including shape, density and radial distribution, and texture, were extracted. A machine learning model was developed to construct the COVID-19 Platelet Aggregate Formation Index (CoPAFI), which could quantitatively reflect platelet aggregation and predict severe COVID-19. Mediation analysis was then performed to quantify the extent to which platelet aggregation mediated the association between components of MetS and severe COVID-19. Results: The CoPAFI predicted severe COVID-19 with an area under the curve of 0.82 and an odds ratio of 3.76 (95% CI, 2.63-5.38). The CoPAFI was strongly associated with a hypercoagulable state and served as a reliable indicator for assessing the risk of severe COVID-19. In patients with components of MetS, platelet aggregation, as measured by the CoPAFI, accounted for approximately 25% of the increased severity of COVID-19. Conclusion: Enhanced platelet aggregation partially mediates the impact of components of MetS on COVID-19 severity, accounting for approximately 25% of the association, emphasizing the need for integrated metabolic and coagulation management in COVID-19 treatment.

BACKGROUND:Metabolic dysfunction-associated steatotic liver disease (MASLD) is a risk factor for cardiovascular disease (CVD). However, the risk of liver-related events (LREs) after CVD is often overlooked. We investigated the association between incident CVD and subsequent long-term LRE risk among individuals with MASLD. METHODS:We used UK Biobank data to examine whether incident CVD (coronary heart disease [CHD], myocardial infarction [MI], heart failure [HF], or atrial fibrillation [AF]) was associated with subsequent long-term LREs (cirrhosis, decompensation, hepatocellular carcinoma, or liver-related death) in MASLD. Semi-Markov multi-state and time-dependent Cox regression models estimated transition rates and adjusted hazard ratios (aHRs). Imaging and proteomic data explored biological mechanisms. RESULTS:Among 142,454 individuals with MASLD, 22,630 (15.9%) developed incident CVD, and 2635 (1.8%) developed subsequent LREs over a median of 15.1 years. The transition rate from CVD to LREs was higher than the direct progression from MASLD to LREs (3.56 vs. 1.08 per 1000 person-years). Time-dependent Cox regression showed that incident CVD was associated with a higher risk of subsequent LREs (aHR 1.93, 95%CI 1.73-2.14). The risk varied by CVD subtypes, with HF highest, followed by AF, CHD, and MI (all P < 0.001). Exploratory integrated multi-omics analyses revealed associations between cardiac dysfunction and hepatic parameters, and identified a shared proteomic signature enriched in immune and fibrotic pathways. CONCLUSIONS:Individuals with MASLD who experience a CVD event have a higher subsequent risk of long-term LREs. These findings underscore the value of targeted liver monitoring for high-risk individuals after CVD and integrated heart-liver co-management.

[This corrects the article DOI: 10.7150/thno.54217.].

Atherosclerosis is the main pathological basis of cardiovascular disease and urgently requires more effective and targeted therapies. Here, we present a cholesterol-modulated macrophage membrane–mimetic nanoplatform for rapamycin delivery, in which β-cyclodextrin is employed to selectively deplete cholesterol from donor cell membranes. Cholesterol depletion significantly improves nanoparticle uptake by inflammatory macrophages, potentially through enhanced membrane fluidity and preserved key receptor–ligand interactions. In vitro, the cholesterol-depleted nanomedicines promote foam cell cholesterol efflux and suppress pro-inflammatory cytokine secretion, with therapeutic efficacy increasing as membrane cholesterol content decreases. In vivo, the resulting “slimming” membrane–coated nanoparticles exhibit enhanced immune evasion, prolonged systemic circulation, and improved plaque targeting, while maintaining excellent biosafety. In atherosclerotic mice, treatment with these nanoparticles reduces plaque area and lipid accumulation while increasing collagen content in a membrane cholesterol–dependent manner, indicating therapeutic effects and enhanced plaque stability. Notably, these benefits are achieved without altering systemic lipid levels, suggesting a primarily lesion-localized mechanism of action. Collectively, this study demonstrates that the “slimming” membrane–mimetic nanoplatform offers a promising approach for precise, inflammation-targeted therapy of atherosclerosis and may be extended to other chronic inflammatory vascular disorders.

Radiotherapy (RT) is a clinical mainstay of cancer treatment that triggers tumor-specific immune responses. However, the effectiveness is usually hampered due to the hypoxic tumor microenvironment (TME) and the ambivalent impact of RT on the immune landscape of tumors. Herein, we develop an injectable hydrogel encapsulating interleukin-12 (IL-12)/anti-CTLA-4 (aCTLA-4) co-engineered red blood cells (RBC), which is in situ self-assembled within the TME to increase oxygen supply and instigate sequential aCTLA-4/IL-12 release, thus achieving Ba/O2 self-compensated radiosensitization and activating multistage immune responses. Once in the acidic TME, the in situ injected BaO2 undergoes hydrolysis to generate H2O2 and Ba2+, followed by the rapid reaction of Ba2+ with sodium alginate to afford a biocompatible hydrogel. Meanwhile, catalase presented on RBC converts H2O2 into O2, thereby alleviating hypoxia-induced radioresistance and inducing O2-mediated pore formation on RBC membrane for rapid release of aCTLA-4 to relieve tumor immunosuppression. Subsequently, IL-12 anchored on RBC is dilatorily released and interacts with T/NK cells within the TME to induce IFN-γ-dependent antitumor immunity. Taken together, the in situ self-assembled cell reservoir hydrogel offers a futuristic avenue to realize multistage radioimmunotherapy for effective tumor regression by programmable immunoregulation with significant clinical value.

Prostate cancer (PCa) is a malignancy with high heterogeneity arising from tumor microenvironment and histological subtypes. Identifying conserved progression drivers within such heterogeneity is essential for improving clinical outcomes. Using imaging mass cytometry, this study analyzes 38 proteins across paracancerous tissue and four histological subtypes: low-grade prostate acinar adenocarcinoma (LgPAC), high-grade PAC (HgPAC), intraductal carcinoma (IDC), and ductal adenocarcinoma (DAC). Results reveal that eIF1A is overexpressed in high-risk subtypes including HgPAC, IDC, and DAC and correlates with poor prognosis. In luminal cells, EIF1A knockdown and the translation inhibitor homoharringtonine (HHT) both suppress HIF-1α translation and tumor growth, while promoting infiltration of anticancer immune cells including PD-1- T cells and CD163- macrophages. Clinically, neoadjuvant HHT combined with androgen deprivation therapy reduces hypoxia and enhances immune cell infiltration, as shown by single-cell RNA sequencing. Collectively, this work defines conserved molecular features across PCa subtypes, providing promising insights for clinical management. This study was registered at Clinicaltrials.gov (NCT06834321).

PURPOSE:This study aims to establish a retrospective, single-centre, feasibility-oriented benchmark for medical imaging quality control(QC) and to evaluate the potential of multiple large language models for chest X-ray radiograph(CXR) technical QC and CT report consistency assessment, based on a relatively small, radiologist-annotated dataset derived from routine clinical practice. METHODS:This retrospective, single-centre study included 161 CXRs and 219 structured CT reports from routine clinical practice. Twelve labels were used for CXR QC, including eleven radiologist-defined error categories and one error-free label, while nine labels were used for CT report evaluation, including eight inconsistency categories and one error-free label. All cases were annotated using a radiologist consensus reference standard. Multiple large language models(LLMs) and multimodal large language models(MLLMs) were evaluated using Micro-F1 and Macro-F1 for CXR QC and expert-based Micro-F1 for CT report QC. RESULTS:For CXR QC, Gemini 2.0 Flash showed the strongest performance, achieving robust category-level generalization, while GPT-4o and Qwen2.5-VL-72B-Instruct demonstrated more balanced but weaker performance. In CT report QC, DeepSeek-R1 achieved the highest recall (62.23%) and the best overall performance. Across models, protocol-report mismatches and metric inconsistencies were the most common error types. CONCLUSION:This study presents an initial, feasibility-oriented multimodal benchmark for medical imaging quality control, showing that LLM's performance is highly task- and modality-dependent. Given the limited sample size, single-centre design, and Chinese-language scope, the findings support future multicentral validation and workflow-integrated evaluation, rather than immediate clinical deployment.

BACKGROUND AND AIMS:Nonperipheral washout is a major imaging feature of hepatocellular carcinoma (HCC) with prognostic value, but whether its temporal differentiation can refine prognostic stratification remains understudied. This study aimed to investigate the prognostic implications of nonperipheral washout timing in HCC. METHODS:This multicentre, retrospective cohort study included patients who underwent curative resection for single BCLC stage 0/A HCC and preoperative extracellular contrast agent-enhanced MRI at seven tertiary centres (March 2011 to April 2023). Three masked radiologists independently evaluated nonperipheral washout patterns, which were classified as early (present in the portal venous phase), late (present only in the delayed phase), or absent. Early recurrence-free survival (eRFS; ≤ 2 years) and 5-year RFS were assessed using Kaplan-Meier and Cox regression analyses. RESULTS:A total of 611 patients (median age, 55 years; 520 men) were included. Early, late, and no washout were observed in 367 (60.1%), 95 (15.5%), and 149 (24.4%) patients, respectively. Inter- and intra-reader agreements were substantial to excellent (κ range, 0.67-0.94). Early washout was associated with microvascular invasion (p = 0.01) and Edmondson-Steiner G3/4 (p = 0.002). The eRFS rates were 67.3%, 82.1%, and 85.2% for the early, late, and no-washout groups (p < 0.001); the 5-year RFS rates were 53.4%, 62.1%, and 71.8% (p = 0.002). In multivariable Cox analysis adjusting for factors, early washout independently predicted eRFS (HR, 1.86; p < 0.001) and 5-year RFS (HR, 1.46; p = 0.006). CONCLUSIONS:In patients undergoing curative resection for single BCLC 0/A HCC, temporal differentiation of nonperipheral washout refines prognostic stratification, with early washout identifying patients at higher risk of recurrence.

This study aimed to explore the prognostic value of body composition (BC) parameters derived from CT imaging and their derived phenotypes following resection of hepatocellular carcinoma (HCC). Retrospective collection of HCC patients who underwent liver resection at 5 medical centers. TotalSegmentator was employed to segment adipose and muscle tissues on CT images. Manual corrections were performed at the L3 level to extract tissue area and CT density parameters. Cox proportional hazards models were used to identify potential prognostic parameters for 2-year recurrence-free survival (RFS) and construct BC phenotypes. Further exploration was conducted on the prognostic value of the BC phenotypes. A total of 497 patients were included (mean age, 59.3 ± 11.0 years; 396 men; cirrhosis prevalence, 53.50

Abstract Background To evaluate the association between styloid process (SP) morphology derived from CTA and extracranial internal carotid artery dissection (ICAD). Materials and methods This retrospective case-control study included 85 patients with unilateral extracranial ICAD and 85 frequency-matched controls who underwent head and neck CTA. Two neuroradiologists independently measured SP length, the distance from the SP tip to the internal carotid artery (SPT–ICA distance), and SP orientation (medial and anterior inclination angles). Group comparisons were performed between the dissection side in the ICAD group and the corresponding matched side in controls. Multivariable logistic regression was used to identify independent morphologic factors associated with ICAD, and ROC analysis was performed to evaluate the diagnostic performance of each individual parameter and of the combined model. Results Compared with controls, ICAD showed a longer SP, a shorter SPT–ICA distance, and a smaller anterior inclination angle (all p < 0.001). Multivariable logistic regression identified SP length, SPT–ICA distance, and anterior inclination angle as independent factors associated with ICAD. ROC analysis showed that the combined model achieved the best performance (AUC = 0.836), compared with SP length (AUC = 0.752), SPT–ICA distance (AUC = 0.742), and anterior inclination angle (AUC = 0.717). Conclusion The combined model based on SP length, SPT–ICA distance, and anterior inclination angle showed the best performance, suggesting that these CTA-derived SP morphologic features may help identify an anatomic pattern associated with extracranial ICAD.

To evaluate the diagnostic performance of the Node Reporting and Data System (Node-RADS) and its enhanced versions for central (CLNM) and lateral lymph node metastases (LLNM) in papillary thyroid cancer (PTC). This retrospective study enrolled 227 patients with histologically confirmed PTC who underwent preoperative thyroid-dedicated contrast-enhanced CT. The original Node-RADS scores were assigned to lymph nodes in cervical levels II–VI, and the results were compared with histopathology. A Hyper‑Enhancement Node‑RADS (HE‑Node‑RADS) model by assigning a hyper‑enhancement feature was further developed. Multivariate logistic regression was used to identify independent predictors of CLNM and construct a Nomogram‑Augmented Node‑RADS (NA‑Node‑RADS). The diagnostic performance of different thresholds of Node-RADS and the modified models was assessed and compared. Node-RADS demonstrated moderate to good diagnostic performance for both CLNM (threshold > 1, AUC = 0.741) and LLNM (threshold > 2, AUC = 0.801). Interobserver agreements were excellent (κ = 0.838 for CLNM and κ = 0.827 for LLNM). At threshold > 2, HE-Node-RADS (AUC = 0.883) was significantly superior to Node-RADS for LLNM (p = 0.004). NA-Node-RADS (predicted probability > 47.1

BACKGROUND:The metabolic score of visceral fat (METS-VF) is linked to chronic obstructive pulmonary disease (COPD) incidence, while its association with mortality and adverse outcomes in patients with COPD remains unclear. MATERIALS AND METHODS:We analysed 7246 participants with COPD from the UK Biobank and 869 from US National Health and Nutrition Examination Survey (US NHANES) (1999-2018). METS-VF was categorised into quartiles. In UK Biobank, outcomes included all-cause, cardiovascular disease (CVD), COPD-specific mortality, pulmonary heart disease (PHD), pulmonary embolism (PE) and heart failure (HF); in NHANES, only all-cause and CVD mortality were evaluated. UK Biobank analyses used Cox models, restricted cubic splines, Kaplan-Meier curves, time-dependent receiver operating characteristic (ROC) curves and mediation analysis (C reactive protein (CRP), white blood cell count (WBC), platelet count (PLT)). NHANES served as an external validation cohort using survey-weighted Cox models, subgroup and sensitivity analyses and time-dependent ROC for the two mortality outcomes. RESULTS:In UK Biobank, restricted cubic splines identified non-linear associations of METS-VF with all-cause and CVD mortality, with a common inflection point at 7.03, and linear associations with secondary outcomes. Compared with the lowest quartile, the highest METS-VF quartile showed significantly higher risks of all-cause mortality (HR 1.467), CVD mortality (HR 3.000), COPD-specific mortality (HR 1.952), PHD (HR 3.505), PE (HR 2.301) and HF (HR 2.567). Similar positive associations were observed in NHANES, where the highest METS-VF quartile remained significantly associated with all-cause mortality (HR 3.337) and CVD mortality (HR 3.011). Time-dependent ROC analyses demonstrated modest but stable discrimination across follow-up in both cohorts. Mediation analyses showed that CRP and WBC partially mediated the associations of METS-VF with mortality and cardiopulmonary outcomes, whereas PLT did not exhibit significant mediation effects. CONCLUSIONS:Elevated METS-VF is consistently associated with increased long-term risks of mortality and cardiopulmonary complications in COPD across independent discovery and validation cohorts. METS-VF may serve as a practical prognostic biomarker for risk stratification in the clinical management of COPD.

Hepatocellular carcinoma (HCC) is a malignant tumor that is common worldwide. It is characterized by high incidence and mortality rates. Interventional therapy is a minimally invasive treatment for HCC that offers diverse methods that cover different stages. Because of the significant heterogeneity of tumors, even at the same stage, the effectiveness of interventional therapy can vary greatly, which makes it difficult for clinicians to determine the optimal treatment plan before treatment. Increasing evidence suggests that tumor-related imaging characteristics are correlated with biological functions and can be used to predict different subtypes of HCC and reflect their heterogeneity. In recent years, artificial intelligence (AI) has received widespread attention and been applied widely. AI can automatically extract features from medical images, objectively quantifying low-dimensional to high-dimensional information about tumors, which helps to directly or indirectly predict prognostic stratification and treatment response to interventional therapy. Furthermore, when AI integrates high-dimensional quantifiable information from imaging data with multimodal clinical and molecular data, its accuracy and interpretability improve significantly. Although image-derived AI models have achieved good performance and have broad prospects for application in the prognosis and treatment of HCC, their clinical implementation has limitations, including data and imaging standardization, model interpretability, and the need for multicenter validation. This review summarizes the latest advancements in medical image-driven AI in the prognostic stratification and efficacy prediction of interventional therapy for HCC, and outlines the main challenges that need to be addressed and good prospects for application.

BACKGROUND:Steatotic liver disease (SLD) is closely associated with cardiometabolic factors, but whether the cardiovascular-kidney-metabolic (CKM) stage stratifies risk for major adverse cardiovascular events (MACEs) and liver-related events (LREs) across SLD subtypes remains unclear. METHODS:In the UK Biobank study, participants with SLD were classified into subtypes of metabolic dysfunction-associated steatotic liver disease (MASLD), metabolic dysfunction and alcohol-associated liver disease (MetALD), and alcohol-related liver disease (ALD). The primary outcomes were incident MACEs and LREs, assessed overall and by subtype. Associations were evaluated using Cox models, Kaplan-Meier curves, and population-attributable risks (PARs). FINDINGS:Over 14.7 years of follow-up, 17,973 MACEs (14.0%) and 2,742 LREs (2.0%) occurred among 142,564 individuals with SLD. Higher CKM stage was associated with graded increases in both outcomes (CKM stages 2-4 vs. 0-1: adjusted HRs 1.51 [95% CI 1.43-1.59] to 3.62 [3.31-3.97] for MACEs and 1.28 [1.11-1.48] to 2.32 [1.95-2.75] for LREs), with similar trends across subtypes. Obesity and hypertension were the leading contributors to both outcomes (PARs of up to 19.0% and 22.8% for LREs), whereas diabetes contributed more prominently to LREs than to MACEs (17.5% vs. 7.9%). CONCLUSIONS:A higher CKM stage is associated with an increased long-term risk of MACEs and LREs across the SLD spectrum. Obesity and hypertension are the primary contributors to both outcomes, and diabetes additionally contributes to LREs. FUNDING:Supported by the National Science and Technology Major Project, the National Key R&D Program of China, and the National Natural Science Foundation of China.

BACKGROUND & AIMS:Conventional CT (CCT) is widely used to assess hepatocellular carcinoma (HCC) after transarterial chemoembolization (TACE), but its diagnostic performance is often limited by lipiodol-induced beam-hardening artifacts and poor contrast resolution. Dual-energy CT (DECT) with low-keV monochromatic imaging may improve detection of viable residual tumors, yet its clinical value remains to be fully established. This study compared diagnostic performance, image quality, spatial accuracy, and interobserver agreement of DECT versus CCT for identifying viable HCC post-TACE using MRI as the reference standard. MATERIALS AND METHODS:This retrospective, single-center study included 48 patients with 76 HCC lesions who underwent both DECT and MRI within 3 months after conventional TACE. Conventional CT (CCT) and 40-keV monoenergetic (MonoE40) images were reconstructed from DECT data. Diagnoses were independently assessed by radiologists blinded to MRI results. Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), Dice similarity coefficient (DSC) for spatial agreement, and Fleiss' kappa for interobserver agreement were analyzed. RESULTS:Fifty-five lesions were viable per MRI. MonoE40 images showed significantly superior diagnostic performance compared to CCT (P < 0.05), especially for lesions with viable components < 2 cm (detection rates: 74.1 %-85.2 % vs. 25.9 %-48.1 %). MonoE40 also yielded higher diagnostic confidence, lesion conspicuity, and arterialphase CNR (P < 0.001). Dice coefficients for tumor delineation improved from 0.31 to 0.54 on CCT to 0.76-0.95 on MonoE40 (P < 0.05). Interobserver agreement at whole-lesion level was higher with MonoE40 (κ = 0.55) versus CCT (κ = 0.29), with the greatest improvement among less-experienced readers (κ from 0.35 to 0.59). CONCLUSION:DECT with 40-keV monochromatic reconstruction significantly improves detection of viable residual HCC after TACE, enhances tumor boundary delineation, and increases consistency among radiologists compared with CCT, especially benefiting less-experienced readers. These results support incorporating DECT into standard post-TACE imaging protocols.

BACKGROUND & AIMS:Predicting retreatment response of viable tumours after transarterial chemoembolization (TACE) is critical for personalised treatment and prognosis assessment in hepatocellular carcinoma (HCC). We aimed to develop an MRI-based prediction model for viable tumour response. METHODS:This retrospective multicentre study included patients with HCC who presented with viable tumours 1 month after initial TACE between February 2015 and October 2022. In addition, data from a prospective clinical trial were reanalyzed as an external validation cohort. All patients underwent contrast-enhanced MRI at baseline (for initial HCC assessment), at 1 month (for evaluation of viable tumour characteristics) and at 6 months (for assessment of treatment response). The training set (n = 167) and test set (n = 59) were used to build lesion- and patient-level models predicting retreatment response at 6 months via logistic regression. Risk groups were stratified by the Youden index and analysed across retreatment subgroups. RESULTS:The Viable tumour Imaging Traits for Assessing Likelihood of response (VITAL) model incorporated four features: diffusion restriction (p = 0.050; 1 point), peritumoral hyperenhancement (p = 0.002; 1 point), heterogeneity (p < 0.001; 2 points) and mural nodule (p = 0.004; 2 points if absent). The model achieved AUCs of 0.821 (95% CI: 0.760-0.882) and 0.733 (95% CI: 0.602-0.865) in training and test cohorts. The patient-level VITAL-P Score was calculated as: 1 × (largest viable tumour size + viable tumour number) + 3 × VITAL Score. High-risk patients (VITAL-p ≥ 16) had significantly shorter overall survival (OS) in the overall cohort (p = 0.021) and shorter progression-free survival (PFS)and OS compared with low-risk patients in the locoregional therapy subgroup (p = 0.021 and 0.002, respectively). CONCLUSIONS:The prediction model based on imaging features of post-TACE viable HCCs demonstrates strong predictive power for tumour retreatment response at 6 months and correlates well with prognosis.

Loss of major histocompatibility complex (MHC)-I is a hallmark of prostate cancer (PCa) immune evasion and immunotherapy failure. Here, we identify ZNF263 as a transcriptional repressor that silences MHC-I by recruiting nucleosome-remodeling and deacetylase (NuRD) to the STAT1 promoter, reducing STAT1 and MHC-I expression. Hypoxia enhances this repression through two ZNF263 modifications: phosphorylation-driven phase separation that strengthens NuRD interaction and O-GlcNAcylation at S662 that aids STAT1 promoter binding. O-GlcNAcylation also promotes interaction with protein kinase, DNA‑activated catalytic subunit (PRKDC), amplifying phosphorylation. Interferon‑gamma (IFN‑γ)‑induced MHC-I induction is augmented upon ZNF263 loss. In silico docking identified Viroptic as a Krüppel‑associated box (KRAB) pocket binder disrupting ZNF263-NuRD, derepressing STAT1, and potentiating IFN-γ antitumor immunity in vivo. High ZNF263 correlates with low MHC-I, scarce CD8+ T cells, and poor survival, providing rationale for targeting ZNF263 in PCa immunotherapy.

Abstract Intranasal delivery offers a direct route to the brain, circumventing the blood-brain barrier (BBB) and minimizing systemic toxicity. However, its efficiency is mainly limited by the nasal mucosal barrier (NMB). Here, low-intensity pulsed ultrasound (LIPUS) without depending on the microbubbles (MBs) to amplify energy, is directly used to reversibly open the NMB by disrupting tight junction proteins. A bionic nanovesicle (iRGD-anti-programmed cell death ligand 1 (aPD-L1) & carvedilol (β-blocker) @ macrophage-derived extracellular vesicles, iMPC) is designed to co-deliver carvedilol for β-receptor blockade to reduce T-cell exhaustion, and aPD-L1 to enhance T-cell anti-tumor activity in orthotopic glioblastoma (GBM) mice during the two-hour window for NMB opening. Consequently, compared to free aPD-L1, up to a 33.38-fold increase of aPD-L1 in the GBM region is obtained with LIPUS-mediated intranasal delivery of iMPC. Reactivating T cells significantly enhances immunotherapy, leading to a 40% tumor reduction, extended survival, and long-term immune memory in orthotopic GBM mice. Overall, the LIPUS-mediated NMB opening strategy notably enhances nose-to-brain drug delivery efficiency, offering a promising platform for treating brain diseases.

ABSTRACT The recurrence and metastasis of breast cancer are driven by immunosuppressive myeloid cells in tumors and lymph nodes. The inherent heterogeneity of myeloid cells poses a significant challenge for real‐time imaging and precise treatment. In this study, we developed microenvironment‐responsive second near‐infrared (NIR‐II) biomimetic nanoparticles (PA NPs) to spatiotemporally modulate macrophage‐mediated immunotherapies. These NIR‐II activatable “off–on” PA NPs accumulate in tumors and lymph nodes, enabling controlled immune activation. By incorporating colony‐stimulating factor 1 receptor inhibitors, PA NPs repolarized M2‐like macrophages toward the pro‐inflammatory M1‐like phenotype. The subsequent production of nitric oxide (NO) specifically illuminated the NIR‐II fluorescence of PA NPs, thereby providing dynamic visualization of macrophage migration and polarization in vivo. Moreover, PA NPs functionalized with anti‐CD47 antibodies selectively bound to tumor cells, blocked the CD47‐SIRPα “don't eat me” signal, and actively reprogrammed macrophages to enhance phagocytic clearance of tumor cells. In multiple breast cancer models, these nanoparticles effectively remodeled immunosuppressive niches and induced durable anti‐tumor immunity, which was further validated using patient‐derived tumor and lymph node fragments. Collectively, this strategy integrates NIR‑II–guided diagnosis and macrophage reprogramming therapy to remodel the immunosuppressive microenvironment across primary and metastatic niches, offering a potent immunotherapeutic approach against breast cancer.