Purpose: To address the therapeutic challenges associated with triple-negative breast cancer (TNBC), we developed a folic acidpolyethylene glycol-modified ZIF8-based nanotheranostic platform (FA-PEG@ZIF8@CIP) designed to integrate synergistic sonodynamic therapy, chemotherapy, and immune activation for enhanced antitumor treatment. Methods: FA-PEG@ZIF8@CIP was constructed as a folic acid-polyethylene glycol-functionalized ZIF8 nanoplatform for the delivery of ciprofloxacin. In this system, ciprofloxacin acted as both a sonosensitizer and a chemotherapeutic agent, while the ZIF8 carrier provided pH-responsive release behavior in the acidic tumor microenvironment. The platform was further evaluated for its physicochemical properties, cellular uptake, antitumor efficacy, immune activation, and ultrasound imaging performance through a series of in vitro and in vivo experiments. Results: FA-PEG@ZIF8@CIP exhibited favorable tumor-targeting capability and potent antitumor activity. Under ultrasound irradiation, the platform markedly enhanced reactive oxygen species (ROS) generation, leading to effective tumor cell killing. In addition, it induced immunogenic cell death (ICD), as evidenced by enhanced calreticulin exposure, HMGB1 translocation, and extracellular ATP release. These effects further promoted dendritic cell maturation and increased cytotoxic T-lymphocyte infiltration within tumor tissues, indicating activation of antitumor immune responses. The proportions of CD8+ T cells in tumor tissues and spleen increased to 18.7% and 14.6%, respectively, corresponding to approximately 3.0-fold and 2.9-fold increases over the PBS group. The antitumor efficacy of FA-PEG@ZIF8@CIP+US was 4.21-fold higher than that of PBS. Moreover, the platform demonstrated effective ultrasound imaging capability, supporting its application for imaging-guided therapy. Collectively, these findings suggest that FA-PEG@ZIF8@CIP exerts therapeutic effects through the coordinated actions of sonodynamic therapy, chemotherapy, and immune modulation. Conclusion: This multifunctional nanosystem enables the integration of diagnosis and therapy and represents a promising strategy for TNBC treatment. By combining targeted delivery, pH-responsive drug release, ultrasound imaging, and synergistic therapeutic effects within a single platform, FA-PEG@ZIF8@CIP may offer a valuable approach for improving theranostic outcomes in TNBC.

Background Hepatic portal venous gas (HPVG) is a critical imaging finding, often indicative of an acute abdominal catastrophe of gastrointestinal origin. The condition progresses rapidly and is associated with an extremely high mortality rate. Conventional conservative management or surgical intervention carries significant risk, particularly for perioperative patients.Case Summary A 64-year-old female patient was admitted to our hospital on August 1, 2023, with a chief complaint of abdominal pain, distension, and cessation of defecation and flatus for one day. The diagnosis was small bowel obstruction, for which an endoscopic nasojejunal feeding tube placement was performed. On August 30, a follow-up abdominal CT scan revealed intrahepatic biliary duct dilation and HPVG. Due to clinical deterioration, the patient was transferred to the ICU. Following a multidisciplinary consultation, an ultrasound-guided portal vein puncture and catheterization was performed first. This intervention successfully alleviated the signs of HPVG, thereby reducing the risk for the subsequent laparotomy. The patient was ultimately successfully treated.Conclusions In this case, the hepatic portal vein was directly punctured under ultrasound guidance, and a PICC catheter was inserted into the portal vein. A mixture of blood and gas was successfully aspirated post-puncture. An immediate post-procedural scan revealed a significant reduction of gas within the intrahepatic portal veins, alleviating HPVG and mitigating the risk for the subsequent laparotomy. This demonstrates that this method can effectively provide direct relief from HPVG and offers a novel therapeutic approach for the management of similar cases.

Impaired dendritic cell (DC) recruitment, maturation, and antigen presentation within the immunosuppressive tumor microenvironment (TME) critically limit the efficacy of cancer immunotherapies. Strategies attempt to restore DC function using systemically administered granulocyte-macrophage colony-stimulating factor (GM-CSF) are constrained by poor tumor accumulation and dose-limiting toxicity. Herein, we developed a biosynthetic, ultrasound-triggered in situ cancer vaccine based on a hybrid nanoplatform (OMVsGM-Lip@Ce6) that integrates GM-CSF-expressing bacterial outer membrane vesicles (OMVsGM) with pH/ultrasound-responsive liposomes encapsulating the sonosensitizer chlorin e6 (Ce6). In the acidic TME, the hybrid vesicles destabilize, enabling localized release of biosynthetically loaded GM-CSF. Subsequent local ultrasound irradiation activates Ce6 to generate reactive oxygen species (ROS), inducing immunogenic cell death (ICD) and thereby promoting the in situ release of tumor-associated antigens (TAAs) and damage-associated molecular patterns (DAMPs). These endogenous danger signals, together with pathogen-associated molecular patterns (PAMPs) intrinsically carried by OMVs, synergize with locally delivered GM-CSF to enhance DC recruitment, expansion, and maturation, ultimately facilitating efficient antigen presentation and priming of tumor-specific T-cell responses. This biosynthetic OMVs-based platform thus realizes spatially controlled GM-CSF delivery and self-adjuvanted in situ cancer vaccination, effectively remodeling the immunosuppressive TME and eliciting robust systemic antitumor immunity to overcome resistance to immunotherapy.

Despite breakthroughs in cancer immunotherapy, its efficacy remains limited by the immunosuppressive tumordraining lymph node (TDLN) microenvironment. A key challenge is simultaneously achieving both efficient tumor antigen release and precise TDLN remodeling. This study employs synthetic biology and genetic engineering to construct an engineered bacteria-vesicle system (EcG@DNPs-PMAN) capable of in situ production at the tumor site and active targeting of TDLNs. The system employs tumor-homing Escherichia coli MG1655 (E. coli MG1655) as the chassis, incorporating a low-intensity focused ultrasound (LIFU)-activated thermosensitive lambda pL/ pR promoter for on-demand expression of granulocyte-macrophage colony-stimulating factor (GM-CSF) packaged into outer membrane vesicles (OMVs). Concurrently, mannosamine (ManN)-modified DSPE-PEOz-COOH and doxorubicin (DOX) are assembled into a pH-responsive lipid film (DNPs-PMAN) coated onto the bacterial surface. This design enables EcG@DNPs-PMAN to preferentially colonize tumor hypoxic regions, inducing immunogenic cell death (ICD) and promoting the release of tumor antigens and damage-associated molecular patterns (DAMPs). Upon LIFU stimulation, the engineered bacteria locally produce and secrete GM-CSF-loaded, mannose (Man)-decorated OMVGM-PMAN vesicles. These vesicles retain pathogen-associated molecular patterns (PAMPs) and are decorated with Man groups, enabling efficient drainage to TDLNs and preferential capture by DCs. Within TDLNs, OMVGM-PMAN promote DC maturation and antigen cross-presentation, thereby reversing the immunosuppressive TDLN microenvironment and activating tumor-specific cytotoxic T cells for synergistic antitumor immunity. This work proposes a synthetic biology-driven strategy termed "in situ tumor-engineered bacteria - lymph node-targeted OMVs," providing a novel approach and expandable platform to overcome immunotherapy resistance by enabling concurrent local antigen release and TDLN remodeling.

Diabetic wound infection remains a devastating threat to human health, largely due to bacterial colonization and increased antibiotic resistance during conventional treatments, and alternative therapeutic strategies are thus urgent to improve diabetic wound healing. Herein, we developed a multifaceted nanoplatform (CuO@SiO2@NO@Au, CSNA NPs) consisting of a cupric oxide (CuO) core, a mesoporous silicon nanoshell loaded with nitric oxide (NO), and in situ grown ultrasmall Au nanoparticles (NPs) for improved diabetic wound treatment. The results showed that the prepared CSNA NPs exhibited remarkable dual-enzyme mimic activity of glucose oxidase (GOx) and peroxidase (POD), effectively oxidizing glucose to generate gluconic acid, thereby reducing the glucose levels and reversing the acidic wound microenvironment. In addition, the fabricated nanoplatform generated abundant H2O2, which was converted into highly toxic hydroxyl radical (·OH), leading to efficient bacterial eradication that was subsequently. Under near-infrared (NIR) light irradiation, the CSNA nanozyme also triggered the release of NO gas and aided in the removal of bacterial biofilms, collectively improving the wound microenvironment. By integrating chemodynamic therapy (CDT), photothermal therapy, and NO gas therapy, this self-activatable NIR- augmented nanozyme provides a promising antimicrobial strategy for diabetic wound treatment.

Immune checkpoint blockade resistance, driven by alternative immune checkpoint upregulation and inefficient T cell-mediated immune stimulation, remains a major challenge in cancer immunotherapy. Here, we present a nanoengineered T cell membrane-coated nanodecoy (NTND) that effectively disrupts the interaction between FGL1-LAG-3, thereby alleviating immunosuppressive signaling and restoring T cell-mediated antitumor immunity. The NTNDs integrate a T cell membrane with high LAG-3 expression and pH-sensitive liposomes sonosensitizer encapsulating the sonosensitizer hematoporphyrin monomethyl ether (HMME). Within the tumor microenvironment (TME), the NTNDs gradually disintegrated and released the immune checkpoint molecules LAG-3 from T cell membrane, which can competitively bind to FGL1 on tumor cells, thereby relieving the immune suppressive effects. Additionally, the generation of abundant reactive oxygen species (ROS) under ultrasound irradiation induces immunogenic cell death (ICD), thereby promoting dendritic cell maturation and cytotoxic T cell infiltration to amplify anti-PD-1 efficacy. Our findings demonstrate that NTNDs can effectively restore the ability of T cells to eliminate anti-PD-1-resistant tumors, suggesting a promising strategy for overcoming immunoresistance in cancer treatment.

The ultrasound microbubbles modified with the nanomaterial GO not only allow real-time monitoring of liver blood flow for disease diagnosis but also serve as drug delivery carriers, offering the dual benefits of diagnostic imaging and targeted therapy. This presents a highly promising strategy for the integrated diagnosis and treatment of hepatocellular carcinoma (HCC) patients. In this study, L-theanine (TH), a natural polyphenol with antioxidant, and antitumor, was used as a "green" reducing agent for graphene oxide (GO) to prepare nanoscale reduced graphene oxide (rGO-TH), which was then blended with SonoVue microbubbles to prepare composite microbubbles (SV@rGO-TH MBs) for the integrated diagnosis and treatment of HCC. The SV@rGO-TH MBs remain stable at higher Mechanical Index (MI), thereby enhancing contrast-enhanced ultrasound(CEUS) imaging effects and improving the accuracy of disease diagnosis. SV@rGO-TH MBs show significant antitumor activity, inhibiting HepG2 cancer cell growth in vivo and in vitro. Furthermore, combined with ultrasound irradiation, nanoscale rGO-TH more easily penetrates the vascular walls and accumulates in tumor tissues, enhancing the antitumor effect. Our research demonstrates that SV@rGO-TH MBs are a safe and effective ultrasound contrast agent (UCA) for the integrated diagnosis and treatment of HCC, providing insights for the early diagnosis and precise treatment of tumors.

Immunotherapy has shown significant potential in treating various cancers, but its efficacy in solid tumors like triple-negative breast cancer (TNBC) is often limited by the dense extracellular matrix (ECM), which impedes T cell infiltration and immune activation. In TNBC, the overactivation of focal adhesion kinase (FAK) drives ECM fibrosis and strengthens an immunosuppressive tumor microenvironment. To address these challenges, we developed an ultrasound-driven nano-sapper that can selectively target tumor tissues to efficiently deliver FAKtargeting siRNA (siFAK) and the sonosensitizer Chlorin e6 (Ce6) by utilizing a hybrid membrane system composed of tumor cell membranes and thylakoid (TK) membranes. Upon ultrasound stimulation, the nanosapper leverages the intrinsic peroxidase-like activity of TK membranes to boost reactive oxygen species (ROS) generation and downregulate FAK expression, thereby facilitating tumor cell destruction, triggering neoantigen release and modulating ECM stiffness. This process initiates an in situ vaccine-like effect, enhances T cell infiltration and antitumor immune responses, and significantly inhibits tumor growth, metastasis, and recurrence. These findings highlight a promising strategy to improve cancer immunotherapy outcomes and overcome immunotherapy resistance.

Objectives To explore the utility of machine learning-based ultrasound radiomics for predicting TP53 gene mutation in hepatocellular carcinoma (HCC).Methods 154 HCC patients with 182 lesions from 2019 to 2024 were reviewed retrospectively. All lesions were randomly split into the training set (n = 129) and the test set (n = 53), and ultrasound radiomics features were extracted and selected. Extreme gradient boosting tree (XGBoost), decision tree (DT), random forest (RF), support vector machine (SVM), and logistic regression (LR) were used to construct the ultrasound radiomics models, the clinical models, and the combined models. The predictive performance of various models was evaluated by the area under the curve (AUC), accuracy, calibration curve, and decision curve analysis (DCA).Results Among the 182 lesions, 102 were confirmed as mutant TP53 and 80 were confirmed as wild-type TP53. The ultrasound radiomics model obtained an AUC of 0.778 and an accuracy of 0.774 in the test set. The clinical model achieved an AUC of 0.761 and an accuracy of 0.710 in the test set. Notably, integrating clinical features with ultrasound radiomics further enhanced predictive performance. The XGBoost-based combined model exhibited the highest predictive performance among all models, achieving an AUC of 0.846 and an accuracy of 0.823 in the test set. The decision curve analysis and calibration curve revealed that the XGBoost-based combined model provided the highest clinical benefit and exhibited strong predictive consistency.Conclusion Machine learning-based ultrasound radiomics signatures accurately predict TP53 gene mutations in HCC. The XGBoost-based combined model, which combined ultrasound radiomics features with clinical features, showed the best performance and represented a promising noninvasive approach for screening TP53-mutated HCC.

Metabolic competition and accumulation of metabolic byproducts in the tumor microenvironment (TME) severely impair the antitumor functions of T cells, leading to suboptimal outcomes in cancer immunotherapy. To address these challenges, we developed an ultrasound-visualized methionine partitioning nano-modulator utilizing erythrocyte membrane-hybridized liposomes loaded with the glycolysis inhibitor lonidamine (LND) and small interfering RNA (siRNA) against methionine transporter solute carrier family 43, member 2 (SLC43A2). By downregulating SLC43A2 expression to reduce methionine uptake by tumor cells and suppressing tumor glycolysis to alleviate the acidic TME, the nano-modulator enhances methionine availability for T cells and improves T cell activity. Moreover, the oxygen-enriched perfluorohexane (PFH-O2) loaded in the core of the nano-modulator alleviates tumor hypoxic, further reducing the glycolysis rate of tumor cells. Furthermore, ultrasound-triggered liquid-gas phase transitions enable real-time ultrasound contrast imaging for precise tumor visualization, while leveraging the ultrasonic cavitation effect to enhance drug penetration and release at the tumor site. In summary, this ultrasound-visualized methionine partitioning nano-modulator effectively reshapes tumor metabolism and immunosuppressive TME under ultrasound guidance, thereby significantly improving the efficacy of tumor immunotherapy. These findings demonstrate a promising strategy for enhancing immunotherapy outcomes through metabolic modulation and microenvironment regulation.

Conventional antitumor therapies induce immunogenic cell death (ICD), releasing large amounts of ATP that are rapidly converted into immunosuppressive adenosine within the tumor microenvironment (TME). This accumulation of adenosine promotes tumor immune evasion by inhibiting effector immune cells and upregulating inhibitory immune checkpoints. To overcome this challenge, we designed ultrasound (US)-activated nanovesicle system ADA/Ce6@tLipo which is composed of T cell membranes displaying multiple immune checkpoint molecules and a liposome encapsulating chlorin e6 (Ce6) and adenosine deaminase (ADA). Upon US exposure, these nanovesicles generate reactive oxygen species (ROS) to induce ICD and initiate an antitumor immune response. Concurrently, ADA converts adenosine, produced from ATP breakdown following ICD, into inosine, reversing adenosine-mediated immunosuppression and enhancing T cell activation. Furthermore, the immune checkpoint molecules displayed on the nanovesicles block immune checkpoint ligands on tumor cells, boosting T cell activity and preventing exhaustion. ADA/Ce6@tLipo reprograms the TME by modulating adenosine metabolism and inhibiting multiple immune checkpoints, thereby amplifying T cell-mediated antitumor immunity. This approach offers a promising strategy to enhance the efficacy of cancer immunotherapy.

Purpose:Macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) is a special pathological subtype of HCC, which is related to invasiveness and poor prognosis. We aimed to construct an ultrasomics model for preoperative noninvasive prediction of MTM-HCC. Patients and Methods:Patients with pathologically confirmed HCC who underwent liver surgery between January 2021 and December 2023 were retrospectively enrolled. 211 eligible patients (169 males and 42 females) were divided 7:3 into the training set (n=147) and test set (n=64) by random stratified sampling. Ultrasomics models were constructed based on the ultrasound image features of the training set using five different ML algorithms, including random forest (RF), eXtreme gradient boosting (XGBoost), support vector machine (SVM), decision tree (DT), and logistic regression (LR). Additionally, a model based on clinical features and a combined model based on clinical and ultrasomics features were constructed to predict MTM-HCC. The performance of the models in the preoperative prediction of MTM-HCC was evaluated on the test set using area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy. Results:The ultrasomics models and the combined models of the five algorithms were effective in predicting MTM-HCC, and the combined models have improved AUC after adding clinical features compared with the ultrasomics model in the test set. The model constructed based on the RF algorithm in the test set has a high accuracy rate and specificity, and the overall performance of the models is better than that of the other four algorithm models, the AUC, accuracy, specificity, and sensitivity of its combined model and ultrasomics model are significantly higher than the clinical model. Conclusion:ML-based ultrasomics model is an effective tool for predicting MTM-HCC before surgery. Integrating clinical and ultrasound image features enhances predictive performance, offering a novel approach for non-invasive preoperative diagnosis of MTM-HCC.

BackgroundThis study seeks to investigate the potential synergistic effects of combining ultrasound-guided percutaneous radiofrequency ablation with anti-PD-1 therapy on prostate cancer, utilizing animal models.MethodsA mouse model of prostate cancer was established by subcutaneous injection of 1 × 106 Myc-Cap cells on the right side of FVB mice. When the volume of the tumors reached about 400mm3, the mice were randomly divided into four groups and received corresponding intervention treatments. Among them, Group 1 was the blank control group, Group 2 was the simple anti-PD-1 treatment group, Group 3 was the simple radiofrequency ablation group, and Group 4 is the group that received percutaneous radiofrequency ablation combined with anti-PD-1 therapy under ultrasound guidance. The growth of the tumors was observed in mice after treatment in each group, tumor tissues were collected, and the immune status of the mice was analyzed through flow cytometry, immunohistochemistry, immunofluorescence, and other methods.ResultsCompared with other treatment groups, ultrasound-guided percutaneous radiofrequency ablation combined with anti-PD-1 therapy significantly reduced the weight and volume of the tumors, demonstrating more effective tumor suppression. At the same time, combination therapy can promote the aggregation of T-cells within the tumor and increase the proportion of cytotoxic T-cells, increase the proportion of M1 macrophages and iNOS expression, and decrease the proportion of M2 macrophages and Arg expression in the local area of the tumors.ConclusionLocal ablation can improve the therapeutic effect of PD-1 monoclonal antibody. Our preliminary results suggest that ultrasound-guided percutaneous radiofrequency ablation, in combination with anti-PD-1 treatment, produces synergistic effects. These effects may be driven by changes in immune cell populations within the tumor’s immunosuppressive microenvironment.

ObjectiveTo investigate the ability of ultrasomics to noninvasively predict epidermal growth factor receptor (EGFR) expression status in patients with hepatocellular carcinoma (HCC).Methods198 HCC patients were comprised in the study (n = 138 in the training dataset and n = 60 in the test dataset). EGFR expression was detected by immunohistochemistry. Ultrasomics features from gray-scale ultrasound images were extracted. Intra-class correlation coefficient (ICC) screening, variance filtering, mutual information method, and extreme gradient boosting (XGboost) embedding method were applied for selecting the best features. Random forest (RF), XGBoost, support vector machine (SVM), decision tree (DT), and logistic regression (LR) 5 machine learning algorithms were used to construct clinical models, ultrasomics models, and clinical-ultrasomics combined models, respectively. Area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, decision curve analysis (DCA), and calibration curve were used to assess the predictive performance of the model.ResultsIn 198 patients, high EGFR expression was observed in 100 patients and low EGFR expression was observed in 98 patients. The RF machine learning ultrasomics model was found to perform well, with the AUC of the training and test dataset being 0.929 (95%CI, 0.874–0.966) and 0.807 (95%CI, 0.684–0.897) respectively, the sensitivity being 0.843 and 0.767 respectively, the specificity being 0.857 and 0.800 respectively, and the accuracy being 0.850 and 0.783, respectively. The predictive performance of the combined model established by integrating ultrasomics features and clinical baseline characteristics was improved, with the AUC, sensitivity, specificity, and accuracy of the RF machine learning combined model for the training and test dataset reaching 0.937 (95%CI, 0.884–0.971), 0.822 (95%CI, 0.702–0.909); 0.857, 0.833; 0.857, 0.800; 0.857, 0.817, respectively.ConclusionTo predict the status of EGFR expression in HCC patients, the ultrasomics model and combined model created by five machine learning algorithms can be utilized as efficient and noninvasive techniques, and the ultrasomics model and combined model established by RF classifier have the best predictive performance.

This work characterized the structural features and investigated the immunomodulatory activity of an alkaline-precipitated polysaccharide fraction produced by Chaetomium globosum CGMCC 6882 (CGP-AP) in RAW 264.7 macrophages. The CGP-AP yield was 0.93 ± 0.08 g/L, which contained 98.33% ± 2.04% (w/w) carbohydrate and 1.52% ± 0.26% (w/w) protein. Structural analysis showed that CGP-AP comprised glucose (99.51%) and arabinose (0.49%), its weight (Mw) and number (Mn) average molecular weights were 0.948 and 0.55 kDa, and its polydispersity (Mw/Mn) was 1.724. In vitro immunomodulatory results show that CGP-AP stimulated nitric oxide production and tumor necrosis factor-α, interleukin (IL)-1β, IL-6, and IL-8 secretion via upregulation of the expression levels of related genes in RAW 264.7 macrophages. Meanwhile, CGP-AP upregulated the expression levels of proinflammatory genes (inducible nitric oxide synthase and cyclooxygenase-2 COX-2). Furthermore, CGP-AP improved the antioxidant status of RAW 264.7 cells by increasing antioxidase (superoxide dismutase, catalase, and glutathione peroxidase) levels and enhancing the mRNA expression of nuclear factor erythroid-2 related factor 2. The above results indicate that CGP-AP may be used as a potential immunomodulator in the pharmaceutical industry.

BACKGROUND AND OBJECTIVE:The measurement of portal venous pressure (PVP) has been extensively studied, primarily through indirect methods. However, the potential of ultrasound-guided percutaneous transhepatic PVP measurement as a direct method has been largely unexplored. This study aimed to investigate the accuracy, safety, and feasibility of this approach. METHODS:In vitro, the experiment aimed to select a needle that could accurately transmit pressure, had a small inner diameter and was suitable for liver puncture, and performed on 20 healthy New Zealand white rabbits. An ultrasound-guided percutaneous transhepatic portal vein puncture was undertaken to measure PVP. Additionally, free hepatic venous pressure (FHVP) and wedged hepatic venous pressure (WHVP) were measured under digital subtraction angiography (DSA). The correlation between the two methods was assessed. Enroll study participants from October 18, 2023 to November 11, 2023 with written informed consent. Five patients were measured the PVP under ultrasound guidance before surgery to determine the feasibility of this measurement method. RESULTS:There was no significant difference in the results obtained using 9 different types of needles (P > 0.05). This demonstrated a great repeatability (P < 0.05). The 22G chiba needle with small inner diameter, allowing for accurate pressure transmission and suitable for liver puncture, was utilized for percutaneous transhepatic PVP measurement. There were positive correlations between PVP and HVPG (r = 0.881), PVP and WHVP (r = 0.709), HVPG and WHVP (r = 0.729), IVCP and FHVP (r = 0.572). The PVP was accurately and safely measured in 5 patients with segmental hepatectomy. No complications could be identified during postoperative ultrasound. CONCLUSION:Percutaneous transhepatic portal venous puncture under ultrasound guidance is accurate, safe and feasible to measure portal venous pressure. CLINICAL TRIAL REGISTRATION NUMBER:This study has been registered in the Chinese Clinical Trial Registry with registration number ChiCTR2300076751.

ObjectiveThe objective of this study is to build and verify the performance of machine learning-based ultrasomics in predicting the objective response to combination therapy involving a tyrosine kinase inhibitor (TKI) and anti-PD-1 antibody for individuals with unresectable hepatocellular carcinoma (HCC). Radiomic features can reflect the internal heterogeneity of the tumor and changes in its microenvironment. These features are closely related to pathological changes observed in histology, such as cellular necrosis and fibrosis, providing crucial non-invasive biomarkers to predict patient treatment response and prognosis.MethodsClinical, pathological, and pre-treatment ultrasound image data of 134 patients with recurrent unresectable or advanced HCC who treated with a combination of TKI and anti-PD-1 antibody therapy at Henan Provincial People’s Hospital and the First Affiliated Hospital of Zhengzhou University between December 2019 and November 2023 were collected and retrospectively analyzed. Using stratified random sampling, patients from the two hospitals were assigned to training cohort (n = 93) and validation cohort (n = 41) at a 7:3 ratio. After preprocessing the ultrasound images, regions of interest (ROIs) were delineated. Ultrasomic features were extracted from the images for dimensionality reduction and feature selection. By utilizing the extreme gradient boosting (XGBoost) algorithm, three models were developed: a clinical model, an ultrasomic model, and a combined model. By analyzing the area under the receiver operating characteristic (ROC) curve (AUC), specificity, sensitivity, and accuracy, the predicted performance of the models was evaluated. In addition, we identified the optimal cutoff for the radiomic score using the Youden index and applied it to stratify patients. The Kaplan-Meier (KM) survival curves were used to examine differences in progression-free survival (PFS) between the two groups.ResultsTwenty ultrasomic features were selected for the construction of the ultrasomic model. The AUC of the ultrasomic model for the training cohort and validation cohort were 0.999 (95%CI: 0.997-1.000) and 0.828 (95%CI: 0.690-0.966), which compared significant favorably to those of the clinical model [AUC = 0.876 (95%CI: 0.815-0.936) for the training cohort, 0.766 (95%CI: 0.597-0.935) for the validation cohort]. Compared to the ultrasomic model, the combined model demonstrated comparable performance within the training cohort (AUC = 0.977, 95%CI: 0.957-0.998) but higher performance in the validation cohort (AUC = 0.881, 95%CI: 0.758-1.000). However, there was no statistically significant difference (p > 0.05). Furthermore, ultrasomic features were associated with PFS, which was significantly different between patients with radiomic scores (Rad-score) greater than 0.057 and those with Rad-score less than 0.057 in both the training (HR = 0.488, 95% CI: 0.299-0.796, p = 0.003) and validation cohorts (HR = 0.451, 95% CI: 0.229-0.887, p = 0.02).ConclusionThe ultrasomic features demonstrates excellent performance in accurately predicting the objective response to TKI in combination with anti-PD-1 antibody immunotherapy among patients with unresectable or advanced HCC.

Myocardial infarction (MI) leads to substantial cellular necrosis as a consequence of reduced blood flow and oxygen deprivation. Stimulating cardiomyocyte proliferation and angiogenesis can promote functional recovery after cardiac events. In this study, we explored a novel therapeutic strategy for MI by synthesizing a biomimetic nanovesicle (NV). This biomimetic NVs are composed of exosomes sourced from umbilical cord mesenchymal stem cells, which have been loaded with placental growth factors (PLGF) and surface-engineered with a cardiac-targeting peptide (CHP) through covalent bonding, termed Exo-P-C NVs. With the help of the myocardial targeting effect of homing peptides, NVs can be enriched in the MI site, thus improve cardiac regeneration, reduce fibrosis, stimulate cardiomyocyte proliferation, and promote angiogenesis, ultimately resulted in improved cardiac functional recovery. It was demonstrated that Exo-P-C NVs have the potential to offer novel therapeutic strategies for the improvement of cardiac function and management of myocardial infarction.

To evaluate the feasibility and safety of percutaneous puncture guided by a 5th generation mobile communication technology (5G)-based telerobotic ultrasound system in phantom and animal experiments. In the phantom experiment, 10 simulated lesions were punctured, once at each of two angles for each lesion, under the guidance of a telerobotic ultrasound system and ultrasound-guided freehand puncture. Student’s t test was used to compare the two methods in terms of puncture accuracy, total operation duration, and puncture duration. In the animal experiment, under the guidance of the telerobotic ultrasound system, an 18G puncture needle was used to puncture 3 target steel beads in the liver, right kidney, and right gluteal muscle, respectively. The animal experiment had no freehand ultrasound-guided control group. After puncture, a CT scan was performed to verify the position of the puncture needle in relation to the target, and the complications and puncture duration, etc., were recorded. In the phantom experiment, the mean accuracies of puncture under telerobotic ultrasound guidance and conventional ultrasound guidance were 1.8 ± 0.3 mm and 1.6 ± 0.3 mm (P = 0.09), respectively; therefore, there was no significant difference in the accuracy of the two guide methods. In the animal experiment, the first-attempt puncture success (the needle tip close to the target) rate was 93