Controlled Synthesis of Preferential Facet-Exposed Fe-MOFs for Ultrasensitive Detection of Peroxides.

Exposing different facets on metal-organic frameworks (MOFs) is highly desirable to enhance the performance for various applications, however, exploiting a concise and effective approach to achieve facet-controlled synthesis of MOFs remains challenging. Here, by modulating the ratio of metal precursors to ligands, the facet-engineered iron-based MOFs (Fe-MOFs) exhibits enhanced catalytic activity for Fenton reaction are explored, and the mechanism of facet-dependent performance is revealed in detail. Fully exposed (101) and (100) facets on spindle-shaped Fe-MOFs enable rapid oxidation of colorless o-phenylenediamine (OPD) to colored products, thereby establishing a dual-mode platform for the detection of hydrogen peroxide (H2O2) and triacetone triperoxide (TATP). Thus, a detection limit as low as 2.06 nm is achieved, and robust selectivity against a wide range of common substances (>16 types) is obtained, which is further improved by incorporating a deep learning architecture with an SE-VGG16 network model, enabling precise differentiation of oxidizing agents from captured images. The present strategy is expected will shine light on both the rational synthesis of nanomaterials with modulated morphologies and the exploitation of high-performance trace chemical sensors.

Development and validation of a multi-modal ultrasomics model to predict response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer.

OBJECTIVES: To assess the performance of multi-modal ultrasomics model to predict efficacy to neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC) and compare with the clinical model. MATERIALS AND METHODS: This study retrospectively included 106 patients with LARC who underwent total mesorectal excision after nCRT between April 2018 and April 2023 at our hospital, randomly divided into a training set of 74 and a validation set of 32 in a 7: 3 ratios. Ultrasomics features were extracted from the tumors' region of interest of B-mode ultrasound (BUS) and contrast-enhanced ultrasound (CEUS) images based on PyRadiomics. Mann-Whitney U test, spearman, and least absolute shrinkage and selection operator algorithms were utilized to reduce features dimension. Five models were built with ultrasomics and clinical analysis using multilayer perceptron neural network classifier based on python. Including BUS, CEUS, Combined_1, Combined_2 and Clinical models. The diagnostic performance of models was assessed with the area under the curve (AUC) of the receiver operating characteristic. The DeLong testing algorithm was utilized to compare the models' overall performance. RESULTS: The AUC (95% confidence interval [CI]) of the five models in the validation cohort were as follows: BUS 0.675 (95%CI: 0.481-0.868), CEUS 0.821 (95%CI: 0.660-0.983), Combined_1 0.829 (95%CI: 0.673-0.985), Combined_2 0.893 (95%CI: 0.780-1.000), and Clinical 0.690 (95%CI: 0.509-0.872). The Combined_2 model was the best in the overall prediction performance, showed significantly better compared to the Clinical model after DeLong testing (P < 0.01). Both univariate and multivariate logistic regression analyses showed that age (P < 0.01) and clinical stage (P < 0.01) could be an independent predictor of efficacy after nCRT in patients with LARC. CONCLUSION: The ultrasomics model had better diagnostic performance to predict efficacy to nCRT in patients with LARC than the Clinical model.

Endoscopic Rectal Ultrasound-Based Radiomics Analysis for the Prediction of Synchronous Liver Metastasis in Patients With Primary Rectal Cancer.

OBJECTIVES: To develop and validate an ultrasound-based radiomics model to predict synchronous liver metastases (SLM) in rectal cancer (RC) patients preoperatively. METHODS: Two hundred and thirty-nine RC patients were included in this study and randomly divided into training and validation cohorts. A total of 5936 radiomics features were calculated on the basis of ultrasound images to build a radiomic model and obtain a radiomics score (Rad-score) using logistic regression. Meanwhile, clinical characteristics were collected to construct a clinical model. The radiomics-clinical model was developed and validated by integrating the radiomics features with the selected clinical characteristics. The performances of three models were evaluated and compared through their discrimination, calibration, and clinical usefulness. RESULTS: The radiomics model was developed based on 13 radiomic features. The radiomics-clinical model, which incorporated Rad-score, CEA, and CA199, exhibited favorable discrimination and calibration with areas under the receiver operating characteristic curve (AUC) of 0.920 (95% CI: 0.874-0.965) in the training cohorts and 0.855 (95% CI: 0.759-0.951) in the validation cohorts. And the AUC of the radiomics-clinical model was 0.849 (95% CI: 0.771-0.927) for the training cohorts and 0.780 (95% CI: 0.655-0.905) for the validation cohorts, the clinical model was 0.811 (95% CI: 0.718-0.905) for the training cohorts and 0.805 (95% CI: 0.645-0.965) for the validation cohorts. Moreover, decision curve analysis (DCA) further confirmed the clinical utility of the radiomics-clinical model. CONCLUSIONS: The radiomics-clinical model performed satisfactory predictive performance, which can help improve clinical diagnosis performance and outcome prediction for SLM in RC patients.

Microwave ablation versus laparoscopic resection as first-line therapy for solitary 3-5-cm HCC.

BACKGROUND AND AIMS: The study objective was to compare the effectiveness of microwave ablation (MWA) and laparoscopic liver resection (LLR) on solitary 3-5-cm HCC over time. APPROACH AND RESULTS: From 2008 to 2019, 1289 patients from 12 hospitals were enrolled in this retrospective study. Diagnosis of all lesions were based on histopathology. Propensity score matching was used to balance all baseline variables between the two groups in 2008-2019 (n = 335 in each group) and 2014-2019 (n = 257 in each group) cohorts, respectively. For cohort 2008-2019, during a median follow-up of 35.8 months, there were no differences in overall survival (OS) between MWA and LLR (HR: 0.88, 95% CI 0.65-1.19, p = 0.420), and MWA was inferior to LLR regarding disease-free survival (DFS) (HR 1.36, 95% CI 1.05-1.75, p = 0.017). For cohort 2014-2019, there was comparable OS (HR 0.85, 95% CI 0.56-1.30, p = 0.460) and approached statistical significance for DFS (HR 1.33, 95% CI 0.98-1.82, p = 0.071) between MWA and LLR. Subgroup analyses showed comparable OS in 3.1-4.0-cm HCCs (HR 0.88, 95% CI 0.53-1.47, p = 0.630) and 4.1-5.0-cm HCCs (HR 0.77, 95% CI 0.37-1.60, p = 0.483) between two modalities. For both cohorts, MWA shared comparable major complications (both p > 0.05), shorter hospitalization, and lower cost to LLR (all p < 0.001). CONCLUSIONS: MWA might be a first-line alternative to LLR for solitary 3-5-cm HCC in selected patients with technical advances, especially for patients unsuitable for LLR.

Differences between CEUS LI-RADS and CECT LI-RADS in the diagnosis of focal liver lesions in patients at risk for HCC.

OBJECTIVES: To compare the inter-modality consistency and diagnostic performances of the contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) and contrast-enhanced computed tomography (CECT) LI-RADS in patients at risk for hepatocellular carcinoma (HCC), so as to help clinicians to select a more appropriate modality to follow the focal liver lesions (FLLs). METHODS: This retrospective study included untreated 277 FLLs from 247 patients who underwent both CEUS and CECT within 1 month. The ultrasound contrast medium used was SonoVue. FLL categories were independently assigned by two ultrasound physicians and two radiologists using CEUS LI-RADS v2017 and CECT LI-RADS v2018, respectively. The diagnostic performances of CEUS and CECT LI-RADS were evaluated using sensitivity, specificity, positive predictive value (PPV), and negative predictive value. Cohen's Kappa was employed to evaluate the concordance of the LI-RADS category. RESULTS: The inter-modality consistency for CEUS and CECT LI-RADS was 0.31 (p < 0.001). HCC was more frequently observed in CECT LR-3 and LR-4 hepatic lesions than in CEUS (7.3% vs. 19.5%, p < 0.001). The specificity and PPV of CEUS and CECT LR-5 for the diagnosis of HCC were 89.5%, 95.0%, and 82.5%, 94.4%, respectively. The sensitivity of CEUS LR-5 + LR-M for the diagnosis of hepatic malignancies was higher than that of CECT (93.7% vs. 82.7%, p < 0.001). The specificity and PPV of CEUS LR-M for the diagnosis of non-HCC malignancies were lower than those of CECT (59.7% vs. 95.5%, p < 0.001; 23.4% vs. 70.3%, p < 0.001). CONCLUSIONS: The inter-modality consistency between the CEUS and CECT LI-RADS categories is fair. CEUS LI-RADS was more sensitive than CECT LI-RADS in terms of identifying hepatic malignancies, but weaker in terms of separating HCC from non-HCC malignancies.

Can Modifications of LR-M Criteria Improve the Diagnostic Performance of Contrast-Enhanced Ultrasound LI-RADS for Small Hepatic Lesions up to 3 cm?

OBJECTIVE: To assess the diagnostic performance of the contrast-enhanced ultrasound liver imaging reporting and data system (CEUS LI-RADS) version 2017 for small hepatic lesions of ≤3 cm before and after changing the LR-M criteria. METHODS: We retrospectively analyzed the CEUS examination of 179 patients who were at high risk of hepatocellular carcinoma (HCC) with focal hepatic lesions ≤3 cm (194 lesions in total) and evaluated the diagnostic capability of the American College of Radiology and modified CEUS LI-RADS algorithms. RESULTS: Revision of the early washout time to 45 seconds increased the sensitivity of LR-5 in predicting HCC (P = .004), with no significant decrease in specificity (P = .118). It also made better the specificity of LR-M in predicting non-HCC malignancies (P = .001), with no significant decrease in sensitivity (P = .094). However, using within 3 minutes as the criterion for marked washout time improved the LR-5 sensitivity (P < .001) but decreased its specificity (P = .009) in predicting HCC, whereas the specificity of LR-M in predicting non-HCC malignancies increased (P < .001), but the sensitivity decreased (P = .027). CONCLUSIONS: CEUS LI-RADS (v2017) is a valid method for predicting HCC risk in high-risk patients. The diagnostic performance of LR-5 and LR-M could boost when the early washout time is revised to 45 seconds.

An endorectal ultrasound-based radiomics signature for preoperative prediction of lymphovascular invasion of rectal cancer.

OBJECTIVE: To investigate whether radiomics based on ultrasound images can predict lymphovascular invasion (LVI) of rectal cancer (RC) before surgery. METHODS: A total of 203 patients with RC were enrolled retrospectively, and they were divided into a training set (143 patients) and a validation set (60 patients). We extracted the radiomic features from the largest gray ultrasound image of the RC lesion. The intraclass correlation coefficient (ICC) was applied to test the repeatability of the radiomic features. The least absolute shrinkage and selection operator (LASSO) was used to reduce the data dimension and select significant features. Logistic regression (LR) analysis was applied to establish the radiomics model. The receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to evaluate the comprehensive performance of the model. RESULTS: Among the 203 patients, 33 (16.7%) were LVI positive and 170 (83.7%) were LVI negative. A total of 5350 (90.1%) radiomic features with ICC values of ≥ 0.75 were reported, which were subsequently subjected to hypothesis testing and LASSO regression dimension reduction analysis. Finally, 15 selected features were used to construct the radiomics model. The area under the curve (AUC) of the training set was 0.849, and the AUC of the validation set was 0.781. The calibration curve indicated that the radiomics model had good calibration, and DCA demonstrated that the model had clinical benefits. CONCLUSION: The proposed endorectal ultrasound-based radiomics model has the potential to predict LVI preoperatively in RC.

Image Semantic Segmentation of Underwater Garbage with Modified U-Net Architecture Model.

Autonomous underwater garbage grasping and collection pose a great challenge to underwater robots. To assist underwater robots in locating and recognizing underwater garbage objects efficiently, a modified U-Net-based architecture consisting of a deeper contracting path and an expansive path is proposed to accomplish end-to-end image semantic segmentation. In addition, a dataset for underwater garbage semantic segmentation is established. The proposed architecture is further verified in the underwater garbage dataset and the effects of different hyperparameters, loss functions, and optimizers on the performance of refining the predicted segmented mask are examined. It is confirmed that the focal loss function will lead to a boost in solving the target-background unbalance problem. Eventually, the obtained results offer a solid foundation for fast and precise underwater target recognition and operations.

A Hierarchical Stabilization Control Method for a Three-Axis Gimbal Based on Sea-Sky-Line Detection.

Obtaining a stable video sequence for cameras on surface vehicles is always a challenging problem due to the severe disturbances in heavy sea environments. Aiming at this problem, this paper proposes a novel hierarchical stabilization method based on real-time sea-sky-line detection. More specifically, a hierarchical image stabilization control method that combines mechanical image stabilization with electronic image stabilization is adopted. With respect to the mechanical image stabilization method, a gimbal with three degrees of freedom (DOFs) and with a robust controller is utilized for the primary motion compensation. In addition, the electronic image stabilization method based on sea-sky-line detection in video sequences accomplishes motion estimation and compensation. The Canny algorithm and Hough transform are utilized to detect the sea-sky line. Noticeably, an image-clipping strategy based on prior information is implemented to ensure real-time performance, which can effectively improve the processing speed and reduce the equipment performance requirements. The experimental results indicate that the proposed method for mechanical and electronic stabilization can reduce the vibration by 74.2% and 42.1%, respectively.

Ultrasound Image-Based Radiomics: An Innovative Method to Identify Primary Tumorous Sources of Liver Metastases.

OBJECTIVES: To develop radiomic models of B-mode ultrasound (US) signatures for determining the origin of primary tumors in metastatic liver disease. METHODS: A total of 254 patients with a diagnosis of metastatic liver disease were included in this retrospective study. The patients were divided into 3 groups depending on the origin of the primary tumor: group 1 (digestive tract versus non-digestive tract tumors), group 2 (breast cancer versus non-breast cancer), and group 3 (lung cancer versus other malignancies). The patients in each group were allocated to a training or testing set (a ratio of 8:2). The region of interest of liver metastasis was determined through manual differentiation of the tumors, and radiomic signatures were acquired from B-mode US images. Optimal features were selected to develop 3 radiomic models using multiple-dimensionality reduction and classifier screening. The area under the curve (AUC) of the receiver operating characteristic curve was applied to assess each model's performance. RESULTS: A total of 5936 features were extracted, and 40, 6, and 14 optimal features were sequentially identified for the development of radiomic models for groups 1, 2, and 3, respectively, with training set AUC values of 0.938, 0.974, and 0.768 and testing set AUC values of 0.767, 0.768, and 0.750. The differences in age, sex, and number of liver metastatic lesions varied greatly between the 4 primary tumors (P < .050). CONCLUSIONS: B-mode US radiomic models could be effective supplemental means to identify the origin of hepatic metastatic lesions (ie, unknown primary sites).

An Individualized Immune Prognostic Index is a Superior Predictor of Survival of Hepatocellular Carcinoma.

BACKGROUND The tumor microenvironment is largely orchestrated by the immune cells. Considerable evidence has shown their excellent clinicopathological application value in assessment of clinical outcomes and immunotherapy efficacy. Hence, a moderate, individualized prognostic signature based on immune cells that can estimate prognosis and reflect the immune microenvironment in hepatocellular carcinoma (HCC) patients is greatly needed. MATERIAL AND METHODS Here, we systematically analyzed the expression differences and survival prediction value of tumor infiltrating immune cells by analyzing 638 HCC patients from 3 public cohorts, including 2 microarray datasets and 1 RNA sequencing dataset. CIBERSORT software, a computational algorithm, was used to calculate the relative levels of immune cells. Three immune microenvironment subtypes were defined via ConsensuClusterPlus package. Univariate and multivariate survival analyses were used to develop an individualized immune prognostic index based on immune cell pairs. RESULTS Notably, HCC patients with higher immune signatures score, utterly appreciable, suffered inferior prognosis (hazard ratio=2.742; 95% confidence interval: 1.887-3.983; P.

Using ultrasound features and radiomics analysis to predict lymph node metastasis in patients with thyroid cancer.

BACKGROUND: Lymph node metastasis (LNM) is an important factor for thyroid cancer patients' treatment and prognosis. The aim of this study was to explore the clinical value of ultrasound features and radiomics analysis in predicting LNM in thyroid cancer patients before surgery. METHODS: The characteristics of ultrasound images of 150 thyroid nodules were retrospectively analysed. All nodules were confirmed as thyroid cancer. Among the assessed patients, only one hundred and twenty-six patients underwent lymph node dissection. All patients underwent an ultrasound examination before surgery. In the radiomic analysis, the area of interest was identified from selected ultrasound images by using ITK-SNAP software. The radiomic features were extracted by using Ultrosomics software. Then, the data were classified into a training set and a validation set. Hypothetical tests and bagging were used to build the model. The diagnostic performance of different ultrasound features was assessed, a radiomic analysis was conducted, and a receiver operating characteristic (ROC) curve analysis was performed to explore the diagnostic accuracy. RESULTS: Regarding the prediction of LNM, the ROC curves showed that the area under the curve (AUC) values of an irregular shape and microcalcification were 0.591 (P = 0.059) and 0.629 (P = 0.007), respectively. In the radiomics analysis, in the training set, the AUC value of LNM was 0.759, with a sensitivity of 0.90 and a specificity of 0.860. In the verification set, the AUC was 0.803, with a sensitivity of 0.727 and a specificity of 0.800. CONCLUSIONS: Microcalcification and an irregular shape are predictors of LNM in thyroid carcinoma patients. In addition, radiomics analysis has promising value in screening meaningful ultrasound features in thyroid cancer patients with LNM. Therefore, the prediction of LNM based on ultrasound features and radiomic features is useful for making appropriate decisions regarding surgery and interventions before thyroid carcinoma surgery.

Lower Serum Levels of miR-29c-3p and miR-19b-3p as Biomarkers for Alzheimer's Disease.

MicroRNAs (miRNAs) are short noncoding RNA that participate in posttranscriptional gene regulation. However, little is understood about the roles of miRNAs in Alzheimer's disease (AD). In this study, we used next-generation sequencing on RNA extracted from the serum samples of 20 AD patients and 20 controls, yielding a total of 72 miRNAs with significantly changed expression levels. Among these candidates, we selected 9 miRNAs with most significant alteration in disease, and validated their expression levels using RT-qPCR analysis on serum samples from 45 AD patients and 40 control subjects. Thus, the serum levels of miR-146a-5p, 106b-3p, 195-5p, 20b-5p, and 497-5p were significantly higher, while those of miR-125b-3p, 29c-3p, 93-5p and 19b-3p were significantly lower in AD patients, compared with control subjects. Two miRNAs, miR-29c-3p and miR-19b-3p, were selected because both RNA deep-sequencing and q-PCR methods indicated lower serum levels of these miRNAs in AD patients. Computational analysis predicted that 3'-untranslated region of signal transduction and activator of transcription 3 (STAT3) mRNA is targeted both by miR-29c-3p and miR-19b-3p. Using SH-SY5Y human neuroblastoma cells, we showed that transfection with miR-29c-3p or miR-19b-3p inhibitor significantly increased STAT3 phosphorylation. Furthermore, Water maze test, which assesses the learning and memory deficits in rodents, showed that escape latency was significantly shorter in AD rats with overexpression of miR-29c-3p or miR-19b-3p than in control AD rats. These results suggest that miR-29c-3p or miR-19b-3p may contribute to the cognitive function. In conclusion, the serum levels of miR-29c-3p and miR-19b-3p are helpful biomarkers for AD.

Identification of microRNA-93 as a functional dysregulated miRNA in triple-negative breast cancer.

MicroRNAs (miRNAs) are widely recognized as key players in cancer progression and drug resistance, but less is known about the role of miRNAs in triple-negative (estrogen receptor, progesterone receptor, and HER-2/neu) breast cancer (TNBC). The aim of the present study was to examine the expression profile of miRNAs and to explore their possible roles in TNBC. Differentially expressed miRNAs were identified by miRNA microarray and verified by quantitative real-time polymerase chain reaction. The expression of miR-93 was assessed by in situ hybridization in 119 cases of breast cancer. Cell proliferation potential was examined by MTT assay. Cell migration and invasion abilities were evaluated by a wound healing assay and transwell invasion or migration assay. Seven upregulated and ten downregulated miRNAs in TNBC were identified. The miR-93 expression level in TNBC tissues was significantly higher than that in non-triple-negative breast cancer tissues. The potentials of proliferation, invasion, and metastasis in breast cancer MCF-7 cells were promoted by ectopic transfection of miR-93. Our study found several distinct differentially expressed miRNAs in TNBC, as compared to non-triple-negative breast cancer. Among them, miR-93 may be considered as a biomarker associated with the biological and clinical characteristics of human TNBC.

Margin quality analysis for wedge resection of lung cancer and construction of a predictive model.

Background: Insufficient pulmonary wedge resection margin is associated with malignant positive margins and high local recurrence risk for lung cancer. This study aimed to identify the risk factors of insufficient or guideline discordant resection margin distance and establish a predictive model to preoperatively estimate the risk of discordant margin for individual patient. Methods: Guideline discordant resection margin was defined as ratio of resection margin distance to tumor size less than one. Patients who had pulmonary malignancies and underwent wedge resection between April 2014 and February 2023 were enrolled and stratified by quality of resection margin. Multivariable logistic regression analysis was employed to identify risk factors of guideline discordant margin and a predictive model was developed. Data from March 2023 to January 2024 were collected for internal validation. Results: A total of 530 patients were included. The incidence of guideline discordant wedge resection margin was 37.2%. Longer tumor's max distance to pleura and larger tumor size were variables associated with increased risk and included in the final model. Preoperative localization and right-side surgery were protective variables in the predictive model. A nomogram was built based on the predictive model. The model showed satisfying predictive performance with a concordance index of 0.720 for the predictive model, and 0.761 for internal validation. The goodness-if-fit tests were non-significant for both model development and internal validation data set. Conclusions: The preoperative predictive model and nomogram show good predictive performance to estimate the risk of guideline discordant wedge resection margin. Individualized surgical plans or preoperative nodule localization can be made for high-risk patients.

Sulfidation-Induced Surface Local Electronic and Atomic Structures in a Silver Catalyst Enables Silicon Photocathode for Selective and Efficient Photoelectrochemical CO2 Reduction.

Converting CO2 to value-added chemicals through a photoelectrochemical (PEC) system is a creative approach toward renewable energy utilization and storage. However, the rational design of appropriate catalysts while being effectively integrated with semiconductor photoelectrodes remains a considerable challenge for achieving single-carbon products with high efficiency. Herein, we demonstrate a novel sulfidation-induced strategy for in situ grown sulfide-derived Ag nanowires on a Si photocathode (denoted as SD-Ag/Si) based on the standard crystalline Si solar cells. Such an exquisite design of the SD-Ag/Si photocathode not only provides a large electrochemically active surface area but also endows abundant active sites of Ag2S/Ag interfaces and high-index Ag facets for PEC CO production. The optimized SD-Ag/Si photocathode displays an ideal CO Faradic efficiency of 95.2% and an onset potential of +0.26 V versus the reversible hydrogen electrode, ascribed to the sulfidation-induced synergistic effect of the surface atomic arrangement and electronic structure in Ag catalysts that promote charge transfer, facilitate CO2 adsorption and activation, and suppress hydrogen evolution reaction. This sulfidation-induced strategy represents a scalable approach for designing high-performance catalysts for electrochemical and PEC devices with efficient CO2 utilization.

Risks for preeclampsia and small for gestational age: predictive values of placental growth factor, soluble fms-like tyrosine kinase-1, and inhibin A in singleton and multiple-gestation pregnancies.

OBJECTIVE: To determine the accuracy of placental growth factor (PlGF), soluble fms-like tyrosine kinase-1 (sFlt-1), and inhibin A in singleton and multiple-gestation pregnancies for predicting preeclampsia (PE) and small for gestational age (SGA). STUDY DESIGN: A prospective cohort nested in a randomized controlled trial of antioxidant supplementation for the prevention of PE. Plasma biomarkers were evaluated at 12 to 18 (visit 1) and 24 to 26 (visit 2) weeks' gestation and expressed as adjusted multiples of the median. RESULTS: Multiple-gestation pregnancy (74/772) had a significant impact on all biomarkers' levels. PlGF was the best predictor of PE and SGA. At a 10% false-positive rate, PlGF at visit 1 had 21% sensitivity for predicting PE in singleton versus 60% in multiple-gestation pregnancies. PlGF at visit 1 had a 31% sensitivity in singleton and 27% in multiple-gestation pregnancies for SGA prediction. CONCLUSION: PlGF level was a good predictor of subsequent PE as early as 12 to 18 weeks in multiple-gestation pregnancies but was not clinically useful enough to be used as a single marker.

Performance of current versus modified CEUS LI-RADS in the diagnosis of non-hepatocellular carcinoma malignancies.

PURPOSE: The high proportion of HCC in CEUS LR-M decreases the sensitivity of LR-5 for the diagnosis of HCC. However, when modifying LR-M criteria to further improve the sensitivity of LR-5, it is also important not to compromise the diagnostic performance (especially sensitivity) of LR-M for non-hepatocellular carcinoma malignancies (non-HCCMs). The purpose of this study was to evaluate the diagnostic performance of CEUS LI-RADS (2017 version) for non-HCCMs and to explore the impact of modified CEUS LI-RADS on the diagnostic performance of LR-M. METHODS: In this retrospective study, patients with pathologically confirmed non-HCCMs were evaluated. Two radiologists independently interpreted the major CEUS features and categorized the liver lesions. New LR-M criteria were applied: early washout (< 45 s) or marked washout (< 5 min). The sensitivity values of the current and modified CEUS LR-M were assessed and then compared using a paired χ2 test. Cohen's κ was used to compare the inter-reader agreement of the LI-RADS categories. RESULTS: A total of 131 non-HCCMs were ultimately selected, including 71 intrahepatic cholangiocarcinomas, 26 combined hepatocellular cholangiocarcinomas, 29 metastases, and 5 other non-HCCMs. The numbers of LR-M, LR-5, LR-4, and LR-3 in liver lesions were 111, 18, 1, and 1, respectively. The inter-reader agreement of the LI-RADS categories for non-HCCMs was 0.59. The sensitivity of the current CEUS LR-M in diagnosing non-HCCMs was 84.7%. By adjusting the early washout time to < 45 s, the sensitivity of LR-M was 80.9%. By adjusting the marked washout time within 5 min, the sensitivity of LR-M was 72.5%. CONCLUSION: CEUS LR-M has high sensitivity in diagnosing non-HCCMs. For LR-M nodules with nonrim arterial phase hyperenhancement and early washout, advancing the time of early washout to < 45 s has a minimal impact on the sensitivity of LR-M in diagnosing non-HCCMs compared to the condition of increasing the marked washout within 5 min.

Lysosomal membrane permeabilization is involved in curcumin-induced apoptosis of A549 lung carcinoma cells.

We previously reported that curcumin inhibited lung cancer A549 cells growth and promoted cell apoptosis in vitro. In this study, we further examined the apoptosis-related parameters, including lysosomal damage and cathepsin activation, in A549 cells exposed to curcumin. We found that curcumin caused lysosomal membrane permeabilization (LMP) and cytosolic relocation of cathepsin B (cath B) and cathepsin D (cath D). However, only Z-FA-fmk (a cath B inhibitor) but not pepstatin A (a cath D inhibitor) inhibited curcumin-induced cell apoptosis, mitochondrial membrane potential loss, and cytochrome c release. The antioxidant N-acetylcysteine and glutathione attenuated LMP, suggesting that lysosomal destabilization was dependent on the elevation of reactive oxygen species and which precedes mitochondrial dysfunction. These findings indicated a novel pathway for curcumin regulation of ROS-lysosomal-mitochondrial pathway and provided the key mechanism of regulation of LMP in cell apoptosis, which may be exploited for cancer treatment.

[Expression of ezrin in human non-small cell lung cancer and its relationship with metastasis and prognosis].

OBJECTIVE: To explore the expression of ezrin protein in human non-small cell lung cancer (NSCLC) tissues and lung cancer cell lines, and the association between the expression of ezrin protein and the expression of E-cadherin and CD44V6 proteins. METHODS: The expression of ezrin protein and mRNA in lung cancer cell lines was detected by RT-PCR and Western blotting. Ezrin, E-cadherin and CD44V6 were detected by immunohistochemical SP staining in tumor tissues from 150 lung cancer cases and in adjacent normal lung tissues from 30 patients. Furthermore, the expression of ezrin in 30 freshly-taken NSCLC tissues was also detected by Western blot. RESULTS: The expression of ezrin protein and mRNA was up-regulated in highly metastatic human lung cancer. The positive rate of ezrin, E-cadherin and CD44V6 expression in the lung cancer was 61.3%, 54.0% and 58.7%, respectively. The up-regulation of ezrin expression was significantly correlated with lymph node metastasis, but not correlated with age, sex, tumor size, histological type, clinical TNM system and pathological grade. Western blot analysis showed that the level of ezrin in the NSCLC tissues was significantly higher than that in the normal tissues (t = 5.013, P < 0.01). Survival analysis showed that the 5-year survival rate of patients with negative ezrin expression was 29.3%, significantly higher than that of patients with positive ezrin expression (15.2%, χ(2) = 4.128, P = 0.042). Multivariate Cox regression analysis showed that ezrin expression (RR = 3.012, P = 0.047) and lymph node metastasis (RR = 4.827, P = 0.035) were significantly independent prognostic factors for patients with lung cancer. Furthermore, a negative correlation was observed between the expressions of ezrin and E-cadherin in lung cancer, and a positive correlation between the expressions of ezrin and CD44V6 in lung cancer. CONCLUSIONS: Ezrin, E-cadherin and CD44V6 play an important role in the regulation of growth and meastasis of lung cancer. Combined detection of ezrin, E-cadherin and CD44V6 expression is helpful in evaluating the metastasis and prognosis of non-small cell lung cancer.