Photosynthetic Bacteria-Hitchhiking 2D iMXene-mRNA Vaccine to Enable Photo-Immunogene Cancer Therapy.

Therapeutic mRNA vaccines have become powerful therapeutic tools for severe diseases, including infectious diseases and malignant neoplasms. mRNA vaccines encoding tumor-associated antigens provide unprecedented hope for many immunotherapies that have hit the bottleneck. However, the application of mRNA vaccines is limited because of biological instability, innate immunogenicity, and ineffective delivery in vivo. This study aims to construct a novel mRNA vaccine delivery nanosystem to successfully co-deliver a tumor-associated antigen (TAA) encoded by the Wilms' tumor 1 (WT1) mRNA. In this system, named PSB@Nb1.33C/mRNA, photosynthetic bacteria (PSB) efficiently delivers the iMXene-WT1 mRNA to the core tumor region using photo-driven and hypoxia-driven properties. The excellent photothermal therapeutic (PTT) properties of PSB and 2D iMxene (Nb1.33C) trigger tumor immunogenic cell death, which boosts the release of the WT1 mRNA. The released WT1 mRNA is translated, presenting the TAA and amplifying immune effect in vivo. The designed therapeutic strategy demonstrates an excellent ability to inhibit distant tumors and counteract postsurgical lung metastasis. Thus, this study provides an innovative and effective paradigm for tumor immunotherapy, i.e., photo-immunogene cancer therapy, and establishes an efficient delivery platform for mRNA vaccines, thereby opening a new path for the wide application of mRNA vaccines.

Subtype prediction of intrahepatic cholangiocarcinoma using dynamic contrast-enhanced ultrasound.

OBJECTIVE: The study aimed to investigate the predictive value of dynamic contrast-enhanced ultrasound (DCE-US) in differentiating small-duct (SD) and large-duct (LD) types of intrahepatic cholangiocarcinoma (ICC). METHODS: This study retrospectively enrolled 110 patients with pathologically confirmed ICC lesions who were subject to preoperative contrast-enhanced ultrasound (CEUS) examinations between January 2022 and February 2023. Patients were further classified according to the subtype: SD-type and LD-type, and an optimal predictive model was established and validated using the above pilot cohort. The test cohort, consisting of 48 patients prospectively enrolled from March 2023 to September 2023, was evaluated. RESULTS: In the pilot cohort, compared with SD-type ICCs, more LD-type ICCs showed elevated carcinoembryonic antigen (p < 0.001), carbohydrate antigen 19-9 (p = 0.004), ill-defined margin (p = 0.018), intrahepatic bile duct dilation (p < 0.001). Among DCE-US quantitative parameters, the wash-out area under the curve (WoAUC), wash-in and wash-out area under the curve (WiWoAUC), and fall time (FT) at the margin of lesions were higher in the SD-type group (all p < 0.05). Meanwhile, the mean transit time (mTT) and wash-out rate (WoR) at the margin of the lesion were higher in the LD-type group (p = 0.041 and 0.007, respectively). Logistic regression analysis showed that intrahepatic bile duct dilation, mTT, and WoR were significant predictive factors for predicting ICC subtypes, and the AUC of the predictive model achieved 0.833 in the test cohort. CONCLUSIONS: Preoperative DCE-US has the potential to become a novel complementary method for predicting the pathological subtype of ICC. CRITICAL RELEVANCE STATEMENT: DCE-US has the potential to assess the subtypes of ICC lesions quantitatively and preoperatively, which allows for more accurate and objective differential diagnoses, and more appropriate treatments and follow-up or additional examination strategies for the two subtypes. KEY POINTS: Preoperative determination of intrahepatic cholangiocarcinoma (ICC) subtype aids in surgical decision-making. Quantitative parameters from dynamic contrast-enhanced US (DCE-US) allow for the prediction of the ICC subtype. DCE-US-based imaging has the potential to become a novel complementary method for predicting ICC subtypes.

A multi-parameter intrahepatic cholangiocarcinoma scoring system based on modified contrast-enhanced ultrasound LI-RADS M criteria for differentiating intrahepatic cholangiocarcinoma from hepatocellular carcinoma.

PURPOSE: To develop a multi-parameter intrahepatic cholangiocarcinoma (ICC) scoring system and compare its diagnostic performance with contrast-enhanced ultrasound (CEUS) liver imaging reporting and data system M (LR-M) criteria for differentiating ICC from hepatocellular carcinoma (HCC). METHODS: This retrospective study enrolled 62 high-risk patients with ICCs and 62 high-risk patients with matched HCCs between January 2022 and December 2022 from two institutions. The CEUS LR-M criteria was modified by adjusting the early wash-out onset (within 45 s) and the marked wash-out (within 3 min). Then, a multi-parameter ICC scoring system was established based on clinical features, B-mode ultrasound features, and modified LR-M criteria. RESULT: We found that elevated CA 19-9 (OR=12.647), lesion boundary (OR=11.601), peripheral rim-like arterial phase hyperenhancement (OR=23.654), early wash-out onset (OR=7.211), and marked wash-out (OR=19.605) were positive predictors of ICC, whereas elevated alpha-fetoprotein (OR=0.078) was a negative predictor. Based on these findings, an ICC scoring system was established. Compared with the modified LR-M and LR-M criteria, the ICC scoring system showed the highest area under the curve (0.911 vs. 0.831 and 0.750, both p<0.05) and specificity (0.935 vs. 0.774 and 0.565, both p<0.05). Moreover, the numbers of HCCs categorized as LR-M decreased from 27 (43.5%) to 14 (22.6%) and 4 (6.5%) using the modified LR-M criteria and ICC scoring system, respectively. CONCLUSION: The modified LR-M criteria-based multi-parameter ICC scoring system had the highest specificity for diagnosing ICC and reduced the number of HCC cases diagnosed as LR-M category.

Quantitative analysis of pre-treatment dynamic contrast-enhanced ultrasound for assessing the response of colorectal liver metastases to chemotherapy plus targeted therapy: a dual-institutional study.

OBJECTIVES: To investigate the clinical value of pre-treatment quantitative contrast-enhanced ultrasound (CEUS) in assessing the response of colorectal liver metastases (CRLM) to chemotherapy plus targeted therapy. METHODS: This study retrospectively enrolled 50 CRLM patients from the Zhongshan Hospital, Fudan University as the training cohort and 14 patients from Shanghai Tenth People's Hospital as the testing cohort. Patients underwent the CEUS examination before receiving chemotherapy (CAPOX, FOLFOX, FOLFIRI, or FOLFOXIRI) plus targeted therapy (Bevacizumab or Cetuximab). The therapy response was determined according to Response Evaluation Criteria in Solid Tumors version 1.1 based on pre-treatment CT and 3-month follow-up CT after therapy. Dynamic analysis was performed by VueBox® software. Time-intensity curves with quantitative perfusion parameters were obtained. In the training cohort, univariable and multivariable logistic regression analyses were used to develop the predictive model of therapy response. The predictive performance of the developed model was validated in the testing cohort. RESULTS: After the logistic regression analyses, the peak enhancement (PE) (odds ratio = 1.640; 95% confidence intervals [CI] 1.022-2.633) and time to peak (TTP) (odds ratio = 0.495; 95% CI 0.246-0.996) were determined as independent predictive factors. PE and TTP generated from VueBox® were not affected by ultrasound instruments and contrast agent dosage in therapy response evaluation (P > 0.05). The logistic regression model achieved satisfactory prediction performance (area under the curve: 0.923 in the training cohort and 0.854 in the testing cohort). CONCLUSION: CEUS with dynamic quantitative perfusion analysis, which presents high consistency, has potential practical value in predicting the response of CRLM to chemotherapy plus targeted therapy.

Response Evaluation Using Contrast-Enhanced Ultrasound for Unresectable Advanced Hepatocellular Carcinoma Treated With Tyrosine Kinase Inhibitors Plus Anti-PD-1 Antibody Therapy.

OBJECTIVE: The aim of the work described here was to evaluate the role of contrast-enhanced ultrasound (CEUS) in response evaluation for unresectable advanced hepatocellular carcinoma (HCC) treated with tyrosine kinase inhibitors (TKIs) plus anti-programmed cell death protein-1 (PD-1) antibody therapy. METHODS: A prospective cohort of consecutive patients with HCC who received combined TKI/anti-PD-1 antibody treatment for unresectable HCC between January 2022 and October 2022 was included in this study. The patients underwent unenhanced ultrasound (US) and CEUS examinations before treatment and at follow-up. Changes in the largest diameters of the target tumor on unenhanced US and the largest diameters of the enhancing target tumors on CEUS were evaluated. Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 with unenhanced US and magnetic resonance imaging/computed tomography (MRI/CT) and modified RECIST (mRECIST) with CEUS and CEMRI/CT were used to assess treatment response. RESULTS: A total of 24 HCC patients (23 men and 1 woman; mean age: 56.5 ± 8.5 y; Barcelona Clinic Liver Cancer stage C, 62.5%; 29 intrahepatic target tumors) were studied. Calculations of degree of necrosis in the target tumors revealed no significant differences between CEUS and CEMRI/CT (44.5 ± 36.2% vs. 45.3 ± 36.8%, p = 0.862). As for the differentiation of responders from non-responders, the agreement between RECIST version 1.1 of unenhanced US and mRECIST-CEUS was poor (κ coefficient = 0.233). Meanwhile, there was a high degree of concordance between mRECIST-CEUS and mRECIST-CEMRI/CT (κ coefficient = 0.812). CONCLUSION: CEUS proved to be superior to baseline US and is comparable to CEMRI/CT in defining treatment outcome for combined TKI/anti-PD-1 antibody therapy.

Risk stratification of gallbladder masses by machine learning-based ultrasound radiomics models: a prospective and multi-institutional study.

OBJECTIVE: This study aimed to evaluate the diagnostic performance of machine learning (ML)-based ultrasound (US) radiomics models for risk stratification of gallbladder (GB) masses. METHODS: We prospectively examined 640 pathologically confirmed GB masses obtained from 640 patients between August 2019 and October 2022 at four institutions. Radiomics features were extracted from grayscale US images and germane features were selected. Subsequently, 11 ML algorithms were separately used with the selected features to construct optimum US radiomics models for risk stratification of the GB masses. Furthermore, we compared the diagnostic performance of these models with the conventional US and contrast-enhanced US (CEUS) models. RESULTS: The optimal XGBoost-based US radiomics model for discriminating neoplastic from non-neoplastic GB lesions showed higher diagnostic performance in terms of areas under the curves (AUCs) than the conventional US model (0.822-0.853 vs. 0.642-0.706, p < 0.05) and potentially decreased unnecessary cholecystectomy rate in a speculative comparison with performing cholecystectomy for lesions sized over 10 mm (2.7-13.8% vs. 53.6-64.9%, p < 0.05) in the validation and test sets. The AUCs of the XGBoost-based US radiomics model for discriminating carcinomas from benign GB lesions were higher than the conventional US model (0.904-0.979 vs. 0.706-0.766, p < 0.05). The XGBoost-US radiomics model performed better than the CEUS model in discriminating GB carcinomas (AUC: 0.995 vs. 0.902, p = 0.011). CONCLUSIONS: The proposed ML-based US radiomics models possess the potential capacity for risk stratification of GB masses and may reduce the unnecessary cholecystectomy rate and use of CEUS. CLINICAL RELEVANCE STATEMENT: The machine learning-based ultrasound radiomics models have potential for risk stratification of gallbladder masses and may potentially reduce unnecessary cholecystectomies. KEY POINTS: • The XGBoost-based US radiomics models are useful for the risk stratification of GB masses. • The XGBoost-based US radiomics model is superior to the conventional US model for discriminating neoplastic from non-neoplastic GB lesions and may potentially decrease unnecessary cholecystectomy rate for lesions sized over 10 mm in comparison with the current consensus guideline. • The XGBoost-based US radiomics model could overmatch CEUS model in discriminating GB carcinomas from benign GB lesions.

Three-dimensional convolutional neural network model to identify clinically significant prostate cancer in transrectal ultrasound videos: a prospective, multi-institutional, diagnostic study.

Background: Identifying patients with clinically significant prostate cancer (csPCa) before biopsy helps reduce unnecessary biopsies and improve patient prognosis. The diagnostic performance of traditional transrectal ultrasound (TRUS) for csPCa is relatively limited. This study was aimed to develop a high-performance convolutional neural network (CNN) model (P-Net) based on a TRUS video of the entire prostate and investigate its efficacy in identifying csPCa. Methods: Between January 2021 and December 2022, this study prospectively evaluated 832 patients from four centres who underwent prostate biopsy and/or radical prostatectomy. All patients had a standardised TRUS video of the whole prostate. A two-dimensional CNN (2D P-Net) and three-dimensional CNN (3D P-Net) were constructed using the training cohort (559 patients) and tested on the internal validation cohort (140 patients) as well as on the external validation cohort (133 patients). The performance of 2D P-Net and 3D P-Net in predicting csPCa was assessed in terms of the area under the receiver operating characteristic curve (AUC), biopsy rate, and unnecessary biopsy rate, and compared with the TRUS 5-point Likert score system as well as multiparametric magnetic resonance imaging (mp-MRI) prostate imaging reporting and data system (PI-RADS) v2.1. Decision curve analyses (DCAs) were used to determine the net benefits associated with their use. The study is registered at https://www.chictr.org.cn with the unique identifier ChiCTR2200064545. Findings: The diagnostic performance of 3D P-Net (AUC: 0.85-0.89) was superior to TRUS 5-point Likert score system (AUC: 0.71-0.78, P = 0.003-0.040), and similar to mp-MRI PI-RADS v2.1 score system interpreted by experienced radiologists (AUC: 0.83-0.86, P = 0.460-0.732) and 2D P-Net (AUC: 0.79-0.86, P = 0.066-0.678) in the internal and external validation cohorts. The biopsy rate decreased from 40.3% (TRUS 5-point Likert score system) and 47.6% (mp-MRI PI-RADS v2.1 score system) to 35.5% (2D P-Net) and 34.0% (3D P-Net). The unnecessary biopsy rate decreased from 38.1% (TRUS 5-point Likert score system) and 35.2% (mp-MRI PI-RADS v2.1 score system) to 32.0% (2D P-Net) and 25.8% (3D P-Net). 3D P-Net yielded the highest net benefit according to the DCAs. Interpretation: 3D P-Net based on a prostate grayscale TRUS video achieved satisfactory performance in identifying csPCa and potentially reducing unnecessary biopsies. More studies to determine how AI models better integrate into routine practice and randomized controlled trials to show the values of these models in real clinical applications are warranted. Funding: The National Natural Science Foundation of China (Grants 82202174 and 82202153), the Science and Technology Commission of Shanghai Municipality (Grants 18441905500 and 19DZ2251100), Shanghai Municipal Health Commission (Grants 2019LJ21 and SHSLCZDZK03502), Shanghai Science and Technology Innovation Action Plan (21Y11911200), and Fundamental Research Funds for the Central Universities (ZD-11-202151), Scientific Research and Development Fund of Zhongshan Hospital of Fudan University (Grant 2022ZSQD07).

Design of a self-driven probiotic-CRISPR/Cas9 nanosystem for sono-immunometabolic cancer therapy.

Reprogramming the tumor immunosuppressive microenvironment is a promising strategy for improving tumor immunotherapy efficacy. The clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein 9 system can be used to knockdown tumor immunosuppression-related genes. Therefore, here, a self-driven multifunctional delivery vector is constructed to efficiently deliver the CRISPR-Cas9 nanosystem for indoleamine 2,3-dioxygenase-1 (IDO1) knockdown in order to amplify immunogenic cell death (ICD) and then reverse tumor immunosuppression. Lactobacillus rhamnosus GG (LGG) is a self-driven safety probiotic that can penetrate the hypoxia tumor center, allowing efficient delivery of the CRISPR/Cas9 system to the tumor region. While LGG efficiently colonizes the tumor area, it also stimulates the organism to activate the immune system. The CRISPR/Cas9 nanosystem can generate abundant reactive oxygen species (ROS) under the ultrasound irradiation, resulting in ICD, while the produced ROS can induce endosomal/lysosomal rupture and then releasing Cas9/sgRNA to knock down the IDO1 gene to lift immunosuppression. The system generates immune responses that effectively attack tumor cells in mice, contributing to the inhibition of tumor re-challenge in vivo. In addition, this strategy provides an immunological memory effect which offers protection against lung metastasis.

Decoding the molecular subtypes of breast cancer seen on multimodal ultrasound images using an assembled convolutional neural network model: A prospective and multicentre study.

BACKGROUND: Preoperative determination of breast cancer molecular subtypes facilitates individualized treatment plan-making and improves patient prognosis. We aimed to develop an assembled convolutional neural network (ACNN) model for the preoperative prediction of molecular subtypes using multimodal ultrasound (US) images. METHODS: This multicentre study prospectively evaluated a dataset of greyscale US, colour Doppler flow imaging (CDFI), and shear-wave elastography (SWE) images in 807 patients with 818 breast cancers from November 2016 to February 2021. The St. Gallen molecular subtypes of breast cancer were confirmed by postoperative immunohistochemical examination. The monomodal ACNN model based on greyscale US images, the dual-modal ACNN model based on greyscale US and CDFI images, and the multimodal ACNN model based on greyscale US and CDFI as well as SWE images were constructed in the training cohort. The performances of three ACNN models in predicting four- and five-classification molecular subtypes and identifying triple negative from non-triple negative subtypes were assessed and compared. The performance of the multimodal ACNN was also compared with preoperative core needle biopsy (CNB). FINDING: The performance of the multimodal ACNN model (macroaverage area under the curve [AUC]: 0.89-0.96) was superior to that of the dual-modal ACNN model (macroaverage AUC: 0.81-0.84) and the monomodal ACNN model (macroaverage AUC: 0.73-0.75) in predicting four-classification breast cancer molecular subtypes, which was also better than that of preoperative CNB (AUC: 0.89-0.99 vs. 0.67-0.82, p < 0.05). In addition, the multimodal ACNN model outperformed the other two ACNN models in predicting five-classification molecular subtypes (AUC: 0.87-0.94 vs. 0.78-0.81 vs. 0.71-0.78) and identifying triple negative from non-triple negative breast cancers (AUC: 0.934-0.970 vs. 0.688-0.830 vs. 0.536-0.650, p < 0.05). Moreover, the multimodal ACNN model obtained satisfactory prediction performance for both T1 and non-T1 lesions (AUC: 0.957-0.958 and 0.932-0.985). INTERPRETATION: The multimodal US-based ACNN model is a potential noninvasive decision-making method for the management of patients with breast cancer in clinical practice. FUNDING: This work was supported in part by the National Natural Science Foundation of China (Grants 81725008 and 81927801), Shanghai Municipal Health Commission (Grants 2019LJ21 and SHSLCZDZK03502), and the Science and Technology Commission of Shanghai Municipality (Grants 19441903200, 19DZ2251100, and 21Y11910800).

Does PSA level affect the choice of prostate puncture methods among MRI-ultrasound fusion targeted biopsy, transrectal ultrasound systematic biopsy or the combination of both?

OBJECTIVES: To explore whether prostate-specific antigen (PSA) affects the choice of prostate puncture methods by comparing MRI-ultrasound fusion targeted biopsy (MRI-TBx) with transrectal ultrasound systematic biopsy (TRUS-SBx) in the detection of prostate cancer (PCa), clinically significant prostate cancer (csPCa) and non-clinically significant prostate cancer (nsPCa) in different PSA groups (<10.0,10.0-20.0 and>20.0 ng ml-1). METHODS: A total of 190 patients with 215 lesions who underwent both MRI-TBx and TRUS-SBx were included in this retrospective study. PSA was measured pre-operatively and stratified to three levels. The detection rates of PCa, csPCa and nsPCa through different methods (MRI-TBx, TRUS-SBx, or MRI-TBx +TRUS SBx) were compared with stratification by PSA. RESULTS: Among the 190 patients, the histopathological results revealed PCa in 126 cases, including 119 csPCa. In PSA <10.0 ng ml-1 group, although the detection rates of PCa and csPCa by MRI-TBx were higher than those of TRUS-SBx, no significant differences were observed (p = 0.741; p = 0.400). In PSA 10.0-20.0 ng ml-1 group, difference between the detection rate of csPCa with TRUS-SBx and the combined method was statistically significant (p = 0.044). As for PSA >20.0 ng ml-1, MRI-TBx had a higher csPCa rate than TRUS-SBx with no statistical significance noted (p = 0.600). CONCLUSION: MRI-TBx combined with TRUS-SBx could be suitable as a standard detection approach for csPCa in patients with PSA 10.0-20.0 ng ml-1. As for PSA >20.0 and <10.0 ng ml-1, both MRI-TBx and TRUS-SBx might provide effective solutions for tumor detection. ADVANCES IN KNOWLEDGE: This study gives an account of choosing appropriate prostate puncture methods through PSA level.

A Comparative Analysis of Two Machine Learning-Based Diagnostic Patterns with Thyroid Imaging Reporting and Data System for Thyroid Nodules: Diagnostic Performance and Unnecessary Biopsy Rate.

Background: The risk stratification system of the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) for thyroid nodules is affected by low diagnostic specificity. Machine learning (ML) methods can optimize the diagnostic performance in medical image analysis. However, it is unknown which ML-based diagnostic pattern is more effective in improving diagnostic performance for thyroid nodules and reducing nodule biopsies. Therefore, we compared ML-assisted visual approaches and radiomics approaches with ACR TI-RADS in diagnostic performance and unnecessary fine-needle aspiration biopsy (FNAB) rate for thyroid nodules. Methods: This retrospective study evaluated a data set of ultrasound (US) and shear wave elastography (SWE) images in patients with biopsy-proven thyroid nodules (≥1 cm) from the Shanghai Tenth People's Hospital (743 nodules in 720 patients from September 2017 to January 2019) and an independent test data set from the Ma'anshan People's Hospital (106 nodules in 102 patients from February 2019 to April 2019). Six US features and five SWE parameters from the radiologists' interpretation were used for building the ML-assisted visual approaches. The radiomics features extracted from the US and SWE images were used with ML methods for developing the radiomics approaches. The diagnostic performance for differentiating thyroid nodules and the unnecessary FNAB rate of the ML-assisted visual approaches and the radiomics approaches were compared with ACR TI-RADS. Results: The ML-assisted US visual approach had the best diagnostic performance than the US radiomics approach and ACR TI-RADS (area under the curve [AUC]: 0.900 vs. 0.789 vs. 0.689 for the validation data set, 0.917 vs. 0.770 vs. 0.681 for the test data set). After adding SWE, the ML-assisted visual approach had a better diagnostic performance than US alone (AUC: 0.951 vs. 0.900 for the validation data set, 0.953 vs. 0.917 for the test data set). When applying the ML-assisted US+SWE visual approach, the unnecessary FNAB rate decreased from 30.0% to 4.5% in the validation data set and from 37.7% to 4.7% in the test data set in comparison to ACR TI-RADS. Conclusions: The ML-assisted dual modalities visual approach can assist radiologists to diagnose thyroid nodules more effectively and considerably reduce the unnecessary FNAB rate in the clinical management of thyroid nodules.

Ultrasound Molecular Imaging as a Potential Non-invasive Diagnosis to Detect the Margin of Hepatocarcinoma via CSF-1R Targeting.

Though radiofrequency ablation (RFA) is considered to be an effective treatment for hepatocellular carcinoma (HCC), but more than 30% of patients may suffer insufficient RFA (IRFA), which can promote more aggressive of the residual tumor. One possible method to counter this is to accurately identify the margin of the HCC. Colony-stimulating factor 1 receptor (CSF-1R) has been found to be restrictively expressed by tumor associated macrophages (TAMs) and monocytes which more prefer to locate at the boundary of HCC. Using biotinylation method, we developed a CSF-1R-conjugated nanobubble CSF-1R (NBCSF-1R) using a thin-film hydration method for margin detection of HCC. CSF-1R expression was higher in macrophages than in HCC cell lines. Furthermore, immunofluorescence showed that CSF-1R were largely located in the margin of xenograft tumor and IFRA models. In vitro, NBCSF-1R was stable and provided a clear ultrasound image even after being stored for 6 months. In co-culture, NBCSF-1R adhered to macrophages significantly better than HCC cells (p = 0.05). In in vivo contrast-enhanced ultrasound imaging, the washout half-time of the NBCSF-1R was significantly greater than that of NBCTRL and Sonovue® (p = 0.05). The signal intensity of the tumor periphery was higher than the tumor center or non-tumor region after NBCSF-1R injection. Taken together, NBCSF-1R may potentially be used as a non-invasive diagnostic modality in the margin detection of HCC, thereby improving the efficiency of RFA. This platform may also serve as a complement method to detect residual HCC after RFA; and may also be used for targeted delivery of therapeutic drugs or genes.

Acidic pH-Activated Gas-Generating Nanoparticles with Pullulan Decorating for Hepatoma-Targeted Ultrasound Imaging.

Contrast-enhanced ultrasound (US) is a widely used imaging modality for hepatocellular carcinoma diagnosis. Mostly, US imaging is confined to the intravascular process because of the limitation of the microbubble contrast agent currently utilized. Targeted contrast agents that incline to accumulate in tumor tissue or tumor cells and enhance the US signal may advance the sensitivity of ultrasonography and exploit the dimension of US imaging of tumor at the molecular level. In this study, we developed CaCO3/pul-PCB (CPP) hybrid nanoparticles with hepatoma-targeting pullulan decorating on the surface through a mineralization route using the pullulan- graft-poly(carboxybetaine methacrylate) (pul-PCB) copolymer as a modifier. This particle was stable in blood physiological pH and generated echogenic CO2 bubbles under tumoral acidic conditions, which enabled the US signal enhancement. Upon intravenous injection, CPP hybrid nanoparticles accumulated efficiently in tumor tissue and exhibited sixfold contrast enhancement in 35 min at the tumor site in the hepatoma-bearing mice model. By contrast, there was barely any signal change in normal liver tissue. Therefore, the presented CPP hybrid nanoparticle is a promising contrast agent for effective US imaging of hepatoma.

Assisting anti-PD-1 antibody treatment with a liposomal system capable of recruiting immune cells.

Despite the functions of anti-PD-1 antibodies as immune checkpoint regulators, less than 30% of patients exhibit durable therapeutic responses to anti-PD-1 antibodies. Studies have shown that insufficient infiltration of immune cells might limit the outcome of anti-PD-1 therapy. Therefore, we synthesized an immune cell-recruiting liposomal system (FN-nps) to improve this therapeutic strategy. The FN-nps could generate cell debris and expose heat shock protein 70, which could recruit immune cells to tumor sites to assist in anti-PD-1 treatment. In vivo experiments revealed that the FN-nps could assist in anti-PD-1 therapy by increasing the number of lymphocytes in the peripheral blood and tumor site by generating tumor antigens, and this effect was accompanied by an increase in cytokine expression. The number of CTLs increased and mRNA expression levels of cytokines were regulated when the FN-nps were combined with anti-PD-1 therapy. The revealed properties of the liposomal system make it highly promising for assisting in anti-PD-1 antibody immunotherapy in different cancers.

Effect of purslane (Portulaca oleracea L.) extract on anti-browning of fresh-cut potato slices during storage.

Enzymatic browning is a crucial reaction affecting the quality of fresh-cut fruit and vegetables. Purslane is an edible Chinese folk medicine with extensive distribution and containing a lot of polyphenols and alkaloids. However, little research on its' anti-browning effect on fresh-cut food was reported. In this study, the effectiveness of 0.05% (w/w) purslane aqueous extract treatment efficiently inhibited the activities of polyphenol oxidase (PPO), peroxidase (POD) and phenylalanine ammonia-lyase (PAL), the membrane integrity was effectively maintained, and malondialdehyde (MDA) content increases was retarded during whole storage period at 4 °C. Oddly, the higher purslane extract concentration, the lower endogenesis phenolic content. Additionally, thirty polyphenols and fifty-six alkaloids were found in purslane aqueous extract by LC-MS/MS. All results suggest that purslane aqueous extract is a promising nutritive anti-browning agent for fresh-cut potato.

Impact of body characteristics on ultrasound-measured inferior vena cava parameters in Chinese children

Ultrasound-measured inferior vena cava (IVC) and abdominal aorta (Ao)-associated parameters have been used to predict volume status for decades, yet research focusing on the impact of individual physical characteristics, including gender, height/weight, body surface area (BSA), and age, assessed simultaneously on those parameters in Chinese children is lacking. The aim of the present study was to explore the impact of individual characteristics on maximum IVC diameter (IVCmax), Ao, and IVCmax/Ao in healthy Chinese children. From September to December 2015, 200 healthy children from 1 to 13 years of age were enrolled. IVCmax and Ao diameters were measured by 2D ultrasound. We found that age (years), height (cm), weight (kg), waist circumference (cm), and BSA (m2) were positively correlated with IVCmax and Ao. Multivariate linear regression showed that age was the only independent variable for IVCmax (mm) in female children, height was the only independent variable for IVCmax in male children, and age was the only independent variable for Ao in both females and males. IVCmax/Ao was not significantly influenced by the subjects' characteristics. In conclusion, IVCmax and Ao were more susceptible to subjects' characteristics than IVCmax/Ao. IVCmax/Ao could be a reliable and practical parameter in Chinese children as it was independent of age, height, and weight.