Corrigendum to 'Predicting post-resection recurrence by integrating imaging-based surrogates of distinct vascular patterns of hepatocellular carcinoma' (JHEP Reports 5 [2023] 100806).

[This corrects the article DOI: 10.1016/j.jhepr.2023.100806.].

Signal enhancement ratio of multi-phase contrast-enhanced MRI: an imaging biomarker for survival in pancreatic adenocarcinoma.

OBJECTIVES: To evaluate signal enhancement ratio (SER) for tissue characterization and prognosis stratification in pancreatic adenocarcinoma (PDAC), with quantitative histopathological analysis (QHA) as the reference standard. METHODS: This retrospective study included 277 PDAC patients who underwent multi-phase contrast-enhanced (CE) MRI and whole-slide imaging (WSI) from three centers (2015-2021). SER is defined as (SIlt - SIpre)/(SIea - SIpre), where SIpre, SIea, and SIlt represent the signal intensity of the tumor in pre-contrast, early-, and late post-contrast images, respectively. Deep-learning algorithms were implemented to quantify the stroma, epithelium, and lumen of PDAC on WSIs. Correlation, regression, and Bland-Altman analyses were utilized to investigate the associations between SER and QHA. The prognostic significance of SER on overall survival (OS) was evaluated using Cox regression analysis and Kaplan-Meier curves. RESULTS: The internal dataset comprised 159 patients, which was further divided into training, validation, and internal test datasets (n = 60, 41, and 58, respectively). Sixty-five and 53 patients were included in two external test datasets. Excluding lumen, SER demonstrated significant correlations with stroma (r = 0.29-0.74, all p < 0.001) and epithelium (r = -0.23 to -0.71, all p < 0.001) across a wide post-injection time window (range, 25-300 s). Bland-Altman analysis revealed a small bias between SER and QHA for quantifying stroma/epithelium in individual training, validation (all within ± 2%), and three test datasets (all within ± 4%). Moreover, SER-predicted low stromal proportion was independently associated with worse OS (HR = 1.84 (1.17-2.91), p = 0.009) in training and validation datasets, which remained significant across three combined test datasets (HR = 1.73 (1.25-2.41), p = 0.001). CONCLUSION: SER of multi-phase CE-MRI allows for tissue characterization and prognosis stratification in PDAC. CLINICAL RELEVANCE STATEMENT: The signal enhancement ratio of multi-phase CE-MRI can serve as a novel imaging biomarker for characterizing tissue composition and holds the potential for improving patient stratification and therapy in PDAC. KEY POINTS: Imaging biomarkers are needed to better characterize tumor tissue in pancreatic adenocarcinoma. Signal enhancement ratio (SER)-predicted stromal/epithelial proportion showed good agreement with histopathology measurements across three distinct centers. Signal enhancement ratio (SER)-predicted stromal proportion was demonstrated to be an independent prognostic factor for OS in PDAC.

CT energy spectral parameters of creeping fat in Crohn's disease and correlation with inflammatory activity.

OBJECTIVES: Creeping fat is a kind of unique abnormal mesenteric tissue at the sites of diseased bowel of Crohn's disease. By using dual-energy CT enterography, this study aimed to evaluate the feasibility of spectral parameters in the quantitative analysis of mesenteric adipose tissue or creeping fat. METHODS: In this study, patients with known or suspected Crohn's disease who underwent dual-energy CT enterography from March 1, 2019, to March 31, 2021, were enrolled. Among them, 40 patients with surgery and pathology-proven creeping fat were selected as the creeping fat Crohn's disease group, and 40 normal patients were selected as the control group. The quantitative spectral parameters including the slope of the Hounsfield unit curve, normalised fat-water concentration, normalised fat-iodine concentration, and normalised fat volume fraction at the enteric phases were obtained. Mann-Whitney U test, Kruskal-Wallis H test, and receiver operating characteristic curve analysis were applied to compare quantitative parameters among various groups. RESULTS: A significant difference was observed in the slope of the Hounsfield unit curve, normalised fat-water concentration, normalised fat-iodine concentration, and normalised fat volume fraction between mesenteric adipose tissue and creeping fat with Crohn's disease at the enteric phase (all p < 0.001). The slope of the Hounsfield unit curve of creeping fat at the enteric phase had a better capability to distinguish inactive and active Crohn's disease (AUC = 0.93, p < 0.001). CONCLUSION: Dual-energy CT enterography with quantitative spectral parameters is a potentially novel noninvasive tool for evaluating creeping fat in Crohn's disease. CRITICAL RELEVANCE STATEMENT: Energy spectral parameters of creeping fat in Crohn's disease are significantly different from normal mesenteric adipose tissues and are correlated with inflammatory activity. KEY POINTS: • Dual-energy CT enterography allows quantitatively assessing creeping fat with spectral parameters. • The creeping fat has distinct spectral parameters to normal mesenteric adipose. • The spectral parameters accurately differentiate active and inactive Crohn's disease.

Development of a radiomics-based model to predict occult liver metastases of pancreatic ductal adenocarcinoma: a multicenter study.

BACKGROUND: Undetectable occult liver metastases block the long-term survival of pancreatic ductal adenocarcinoma (PDAC). This study aimed to develop a radiomics-based model to predict occult liver metastases and assess its prognostic capacity for survival. MATERIALS AND METHODS: Patients who underwent surgical resection and were pathologically proven with PDAC were recruited retrospectively from five tertiary hospitals between January 2015 and December 2020. Radiomics features were extracted from tumors, and the radiomics-based model was developed in the training cohort using LASSO-logistic regression. The model's performance was assessed in the internal and external validation cohorts using the area under the receiver operating curve (AUC). Subsequently, the association of the model's risk stratification with progression-free survival (PFS) and overall survival (OS) was then statistically examined using Cox regression analysis and the log-rank test. RESULTS: A total of 438 patients [mean (SD) age, 62.0 (10.0) years; 255 (58.2%) male] were divided into the training cohort ( n =235), internal validation cohort ( n =100), and external validation cohort ( n =103). The radiomics-based model yielded an AUC of 0.73 (95% CI: 0.66-0.80), 0.72 (95% CI: 0.62-0.80), and 0.71 (95% CI: 0.61-0.80) in the training, internal validation, and external validation cohorts, respectively, which were higher than the preoperative clinical model. The model's risk stratification was an independent predictor of PFS (all P <0.05) and OS (all P <0.05). Furthermore, patients in the high-risk group stratified by the model consistently had a significantly shorter PFS and OS at each TNM stage (all P <0.05). CONCLUSION: The proposed radiomics-based model provided a promising tool to predict occult liver metastases and had a great significance in prognosis.

Establishment of machine learning-based tool for early detection of pulmonary embolism.

BACKGROUND AND OBJECTIVES: Pulmonary embolism (PE) is a complex disease with high mortality and morbidity rate, leading to increasing society burden. However, current diagnosis is solely based on symptoms and laboratory data despite its complex pathology, which easily leads to misdiagnosis and missed diagnosis by inexperienced doctors. Especially, CT pulmonary angiography, the gold standard method, is not widely available. In this study, we aim to establish a rapid and accurate screening model for pulmonary embolism using machine learning technology. Importantly, data required for disease prediction are easily accessed, including routine laboratory data and medical record information of patients. METHODS: We extracted features from patients' routine laboratory results and medical records, including blood routine, biochemical group, blood coagulation routine and other test results, as well as symptoms and medical history information. Samples with a feature loss rate greater than 0.8 were deleted from the original database. Data from 4723 cases were retained, 231 of which were positive for pulmonary embolism. 50 features were retained through the positive and negative statistical hypothesis testing which was used to build the predictive model. In order to avoid identification as majority-class samples caused by the imbalance of sample proportion, we used the method of Synthetic Minority Oversampling Technique (SMOTE) to increase the amount of information on minority samples. Five typical machine learning algorithms were used to model the screening of pulmonary embolism, including Support Vector Machines, Logistic Regression, Random Forest, XGBoost, and Back Propagation Neural Networks. To evaluate model performance, sensitivity, specificity and AUC curve were analyzed as the main evaluation indicators. Furthermore, a baseline model was established using the characteristics of the pulmonary embolism guidelines as a comparison model. RESULTS: We found that XGBoost showed better performance compared to other models, with the highest sensitivity and specificity (0.99 and 0.99, respectively). Moreover, it showed significant improvement in performance compared to the baseline model (sensitivity and specificity were 0.76 and 0.76 respectively). More important, our model showed low missed diagnosis rate (0.46) and high AUC value (0.992). Finally, the calculation time of our model is only about 0.05 s to obtain the possibility of pulmonary embolism. CONCLUSIONS: In this study, five machine learning classification models were established to assess the likelihood of patients suffering from pulmonary embolism, and the XGBoost model most significantly improved the precision, sensitivity, and AUC for pulmonary embolism screening. Collectively, we have established an AI-based model to accurately predict pulmonary embolism at early stage.

Computed tomographic manifestations of celiac ganglia between hypertensive and non-hypertensive population.

The celiac ganglion (CG) is associated with the sympathetic nervous system (SNS) and plays an important role in the pathogenesis of hypertension. The characteristics of the CG in patients with hypertension remain unknown. The aim of our study was to explore the differences in celiac ganglia (CGs) characteristics between hypertensive and non-hypertensive populations using computed tomography (CT). CGs manifestations on multidetector row CT in 1003 patients with and without hypertension were retrospectively analyzed. The morphological characteristics and CT values of the left CGs were recorded. The CT values of the ipsilateral adrenal gland (AG) and crus of the diaphragm (CD) were also measured. The left CG was located between the left AG and CD, and most CGs were long strips. The frequency of visualization of the left CGs was higher in the hypertension group than in the non-hypertension group (p < .05). There were no significant differences in the maximum diameter, size, and shape ratio of the left CGs between the two groups (p > .05). Except for the left CG in the arterial phase, the CT values of the left CG and AG in the non-hypertensive group were higher than those in the hypertension group (p < .05). The venous phase enhancement of the left CG in the non-hypertension group was significantly higher than that in the hypertension group (p < .05). Our findings reveal that CGs have characteristic manifestations in the hypertensive population. As important targets of the SNS, CGs have the potential to regulate blood pressure.

Predicting post-resection recurrence by integrating imaging-based surrogates of distinct vascular patterns of hepatocellular carcinoma.

Background & Aims: Distinct vascular patterns, including microvascular invasion (MVI) and vessels encapsulating tumour clusters (VETC), are associated with poor outcomes of hepatocellular carcinoma (HCC). Imaging surrogates of these vascular patterns potentially help to predict post-resection recurrence. Herein, a prognostic model integrating imaging-based surrogates of these distinct vascular patterns was developed to predict postoperative recurrence-free survival (RFS) in patients with HCC. Methods: Clinico-radiological data of 1,285 patients with HCC from China undergoing surgical resection were retrospectively enrolled from seven medical centres between 2014 and 2020. A prognostic model using clinical data and imaging-based surrogates of MVI and VETC patterns was developed (n = 297) and externally validated (n = 373) to predict RFS. The surrogates (i.e. MVI and VETC scores) were individually built from preoperative computed tomography using two independent cohorts (n = 360 and 255). Whether the model's stratification was associated with postoperative recurrence following anatomic resection was also evaluated. Results: The MVI and VETC scores demonstrated effective performance in their respective training and validation cohorts (AUC: 0.851-0.883 for MVI and 0.834-0.844 for VETC). The prognostic model incorporating serum alpha-foetoprotein, tumour multiplicity, MVI score, and VETC score achieved a C-index of 0.748-0.764 for the developing and external validation cohorts and generated three prognostically distinct strata. For patients at model-predicted medium risk, anatomic resection was associated with improved RFS (p <0.05). By contrast, anatomic resection had no impact on RFS in patients at model-predicted low or high risk (both p >0.05). Conclusions: The proposed model integrating imaging-based surrogates of distinct vascular patterns enabled accurate prediction for RFS. It can potentially be used to identify HCC surgical candidates who may benefit from anatomic resection. Impact and implications: MVI and VETC are distinct vascular patterns of HCC associated with aggressive biological behaviour and poor outcomes. Our multicentre study provided a model incorporating imaging-based surrogates of these patterns for preoperatively predicting RFS. The proposed model, which uses imaging detection to estimate the risk of MVI and VETC, offers an opportunity to help shed light on the association between tumour aggressiveness and prognosis and to support the selection of the appropriate type of surgical resection.

A Phase 1/2 Multicenter Randomized Trial of Local Ablation plus Toripalimab versus Toripalimab Alone for Previously Treated Unresectable Hepatocellular Carcinoma.

PURPOSE: To assess the safety and efficacy of local ablation plus PD-1 inhibitor toripalimab in previously treated unresectable hepatocellular carcinoma (HCC). PATIENTS AND METHODS: In the multicenter, two-stage, and randomized phase 1/2 trial, patients were randomly assigned to receive toripalimab alone (240 mg, every 3 weeks), subtotal local ablation followed by toripalimab starting on post-ablation day 3 (Schedule D3), or on post-ablation day 14 (Schedule D14). The first endpoint of stage 1 was to determine which combination schedule could continue and progression-free survival (PFS) as the primary endpoint for stage 1/2. RESULTS: A total of 146 patients were recruited. During stage 1, Schedule D3 achieved numerically higher objective response rate (ORR) than Schedule D14 for non-ablation lesions (37.5% vs. 31.3%), and was chosen for stage 2 evaluation. For the entire cohort of both stages, patients with Schedule D3 had a significantly higher ORR than with toripalimab alone (33.8% vs. 16.9%; P = 0.027). Moreover, patients with Schedule D3 had improved median PFS (7.1 vs. 3.8 months; P < 0.001) and median overall survival (18.4 vs. 13.2 months; P = 0.005), as compared with toripalimab alone. In addition, six (9%) patients with toripalimab, eight (12%) with Schedule D3, and 4 (25%) with Schedule D14 developed grade 3 or 4 adverse events, and one patient (2%) with Schedule D3 manifested grade 5 treatment-related pneumonitis. CONCLUSIONS: In patients with previously treated unresectable HCC, subtotal ablation plus toripalimab improved the clinical efficacy as compared with toripalimab alone, with an acceptable safety profile.

Predicting Microvascular Invasion in Hepatocellular Carcinoma Using CT-based Radiomics Model.

Background Prediction of microvascular invasion (MVI) may help determine treatment strategies for hepatocellular carcinoma (HCC). Purpose To develop a radiomics approach for predicting MVI status based on preoperative multiphase CT images and to identify MVI-associated differentially expressed genes. Materials and Methods Patients with pathologically proven HCC from May 2012 to September 2020 were retrospectively included from four medical centers. Radiomics features were extracted from tumors and peritumor regions on preoperative registration or subtraction CT images. In the training set, these features were used to build five radiomics models via logistic regression after feature reduction. The models were tested using internal and external test sets against a pathologic reference standard to calculate area under the receiver operating characteristic curve (AUC). The optimal AUC radiomics model and clinical-radiologic characteristics were combined to build the hybrid model. The log-rank test was used in the outcome cohort (Kunming center) to analyze early recurrence-free survival and overall survival based on high versus low model-derived score. RNA sequencing data from The Cancer Image Archive were used for gene expression analysis. Results A total of 773 patients (median age, 59 years; IQR, 49-64 years; 633 men) were divided into the training set (n = 334), internal test set (n = 142), external test set (n = 141), outcome cohort (n = 121), and RNA sequencing analysis set (n = 35). The AUCs from the radiomics and hybrid models, respectively, were 0.76 and 0.86 for the internal test set and 0.72 and 0.84 for the external test set. Early recurrence-free survival (P < .01) and overall survival (P < .007) can be categorized using the hybrid model. Differentially expressed genes in patients with findings positive for MVI were involved in glucose metabolism. Conclusion The hybrid model showed the best performance in prediction of MVI. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Summers in this issue.

A Rare Case of Extrauterine Endometrial Stromal Sarcoma Arising from Deep Pelvic Endometriosis: Role of Multidisciplinary Team Meeting.

INTRODUCTION: Extrauterine endometrial stromal sarcoma (EESS) arising from Deep pelvic endometriosis (DPE) has a poor life quality and is difficult to diagnose pre-operatively. However, the patient's quality of life can be improved when it is diagnosed precisely and managed successfully. CASE REPORT: A 35-year-old woman presented to our hospital with a 3-month history of hematochezia and anal pain. Initially, she was misdiagnosed as a rectal stromal tumor and then precisely diagnosed as having EESS from DPE following several multidisciplinary team (MDT) meetings. The lesion was shrunk by gonadotrophin-releasing hormone agonist (GnRH-α) treatment and then resected with minimal trauma. CONCLUSION: MDT is crucial in the treatment of the patient. It can promote individualized treatment and improve patient's quality of life.

Radiosensitizer EXO-miR-197-3p Inhibits Nasopharyngeal Carcinoma Progression and Radioresistance by Regulating the AKT/mTOR Axis and HSPA5-mediated Autophagy.

The biological functions of exosomes and microRNAs (miRs) in nasopharyngeal carcinoma (NPC) remain largely unexplored. Here, miR-197-3p was screened and identified, and whose level was reduced in serum and exosomes of patients with NPC. MiR-197-3p might be a good diagnostic and prognostic indicator. Our data showed that miR-197-3p expression was closely related to radioresistance, apoptosis, proliferation, migration, and survival of NPC. Inhibition of miR-197-3p expression in vitro could promote the proliferation and migration of NPC cells, while promotion of miR-197-3p expression in vivo could significantly inhibit the growth and enhance the radiosensitivity of NPC cells. From the perspective of mechanism, miR-197-3p could inhibit AKT/mTOR phosphorylation activation, inhibit an activated pathway of AKT/mTOR, target Heat Shock 70-kDa Protein 5(HSPA5) related to endoplasmic reticulum homeostasis, inhibit HSPA5-mediated autophagy, and reverse the radioresistance of NPC. Interestingly, exosomal miR-197-3p (EXO-miR-197-3p) reduced the proliferation and migration potential of NPC cells in vitro, and tumor growth and radioresistance of NPC cells in vivo. EXO-miR-197-3p inhibited NPC progression and radioresistance by regulating AKT/mTOR phosphorylation activation and HSPA5-mediated autophagy. In conclusion, our results highlight the potential of EXO-miR-197-3p as an effective radiosensitizer and therapeutic agent for refractory NPC.

Preoperative Microvascular Invasion Prediction to Assist in Surgical Plan for Single Hepatocellular Carcinoma: Better Together with Radiomics.

BACKGROUND: Prediction models with or without radiomic analysis for microvascular invasion (MVI) in hepatocellular carcinoma (HCC) have been reported, but the potential for model-predicted MVI in surgical planning is unclear. Therefore, we aimed to explore the effect of predicted MVI on early recurrence after anatomic resection (AR) and non-anatomic resection (NAR) to assist surgical strategies. METHODS: Patients with a single HCC of 2-5 cm receiving curative resection were enrolled from 2 centers. Their data were used to develop (n = 230) and test (n = 219) two prediction models for MVI using clinical factors and preoperative computed tomography images. The two prediction models, clinico-radiologic model and clinico-radiologic-radiomic (CRR) model (clinico-radiologic variables + radiomic signature), were compared using the Delong test. Early recurrence based on model-predicted high-risk MVI was evaluated between AR (n = 118) and NAR (n = 85) via propensity score matching using patient data from another 2 centers for external validation. RESULTS: The CRR model showed higher area under the curve values (0.835-0.864 across development, test, and external validation) but no statistically significant improvement over the clinico-radiologic model (0.796-0.828). After propensity score matching, difference in 2-year recurrence between AR and NAR was found in the CRR model predicted high-risk MVI group (P = 0.005) but not in the clinico-radiologic model predicted high-risk MVI group (P = 0.31). CONCLUSIONS: The prediction model incorporating radiomics provided an accurate preoperative estimation of MVI, showing the potential for choosing the more appropriate surgical procedure between AR and NAR.

MiR-138-1-3p alters the stemness and radiosensitivity of tumor cells by targeting CRIPTO and the JAK2/STAT3 pathway in nasopharyngeal carcinoma.

BACKGROUND: Tumor resistance to radiotherapy is one of the main obstacles to the clinical treatment of nasopharyngeal carcinoma (NPC). Improving the radiosensitivity of tumor cells has an important clinical significance in treatment of clinical NPC. This study aimed to identify that miR-138-1-3p as a novel therapeutic target in radioresistant NPC cells and found its targets, CRIPTO and the JAK2/STAT3 pathway. METHODS: Radioresistant C666-IR and HK-1R cells were derived from the NPC cell lines C666-1 and HK-1. The different microRNAs (miRNAs) and their targeting genes were analyzed between C666-1 and C666-IR cells using microarray bioinformatics. Western blot, qRT-PCR, gene transfection, Luciferase reporter assay, and confocal laser scanning microscopy were applied for the analysis of the different genes. RESULTS: MiR-138-1-3p was found to target CRIPTO, which involved in the epithelial-mesenchymal transition (EMT) and JAK2/STAT3 signaling pathways. The luciferase reporter assay confirmed that miR-138-1-3p targeted CRIPTO and downregulated the expression of CRIPTO. Furthermore, miR-138-1-3p affected the stability of the CRIPTO-GRP78 complex on the cell membrane and also reversed the radioresistant characteristics of NPC stem cells, which affected EMT and the JAK2/STAT3 signaling pathway. CONCLUSIONS: The miR-138-1-3p is a small molecule that can modulate radiosensitivity in the radioresistant C666-IR and HK-1R NPC cell lines by inhibiting EMT and targeting CRIPTO to reduce the activation of the JAK2/STAT3 pathway.

Comparing the clinical utility of single-shot echo-planar imaging and readout-segmented echo-planar imaging in diffusion-weighted imaging of the liver at 3 tesla.

PURPOSE: To compare the clinical utility of single-shot echo-planar imaging (SS-EPI) using different breathing schemes and readout-segmented EPI (RS-EPI) in the repeatability of apparent diffusion coefficient (ADC) measurements, signal-to-noise ratio (SNR) and image quality. METHODS: In this institutional review board-approved prospective study, hepatic DWIs (b = 50, 300, 600 s/mm2) were performed in 22 volunteers on 3.0 T MRI using SS-EPI with free-breathing diffusion-weighted imaging (FB-DWI), breath-hold (BH-DWI), respiratory-triggered (RT-DWI) and navigator-triggered (NT-DWI), and readout-segmented EPI (RS-DWI). ADC and surrogate SNR (sSNR) were measured in nine anatomic locations in the right lobe, and image quality was assessed on all FB-DWI, BH-DWI, RT-DWI, NT-DWI, and RS-DWI sequences. The sequence with the optimal clinical utility was decided by systematically comparing the ADC repeatability, sSNR and image quality of the above DWIs. RESULTS: In all the five sequences, NT-DWI had the most reliable intra-observer agreement (intraclass correlation coefficient (ICC): 0.900-0.922; all P > 0.05), and a better interobserver agreement (ICC: 0.853-0.960; all p > 0.05) than RS-DWI (ICC:0.881-0.916; some P < 0.05). NT-DWI had the best ADC repeatability in the nine locations (mean ADC absolute differences: 38.47-56.38 × 10-6 mm2/s, limits of agreement (LOA): 17.33-22.52 × 10-6 mm2/s). Also, NT-DWI had the highest sSNR (Reader 1: 50.58 ±â€¯20.11 (Superior), 74.06 ±â€¯28.37 (Central), 80.99 ±â€¯38.11(Inferior)); Reader 2: 48.07 ±â€¯23.92 (Superior), 68.23 ±â€¯32.91 (Central), 76.78 ±â€¯33.07 (Inferior)) in three representative sections except for RS-DWI. Furthermore, NT-DWI had a better image quality than RS-DWI (P < 0.05) and was superior to FB-DWI and BH-DWI in sharpness of the liver (at b = 300 s/mm2) (P < 0.05) CONCLUSION: RS-DWI has the best SNR. However, NT-DWI can provide sufficient SNR, excellent image quality, and the best ADC repeatability on 3.0 T MRI. It is thus the recommended sequence for the clinical application of hepatic DWI.

Improved Dielectric Properties of Thermoplastic Polyurethane Elastomer Filled with Core-Shell Structured PDA@TiC Particles.

Insulating interlayer between nanoparticles and polymer matrix is crucial for suppressing the dielectric loss of polymer composites. In this study, titanium carbide (TiC) particles were surface modified by polydopamine (PDA), and the obtained PDA@TiC powders were used to reinforce thermoplastic polyurethane (TPU). The results indicate that the PDA@TiC were homogenously dispersed in the matrix compared with the pristine TiC, and that the PDA@TiC/TPU composites show improved dielectric and mechanical properties, i.e., much lower dissipation factors and obviously enhanced dielectric breakdown strength, as well as higher tensile strength and elongation at break as compared to the raw TiC/TPU. The nanoscale PDA interlayer contributes to the dielectric and mechanical enhancements because it not only serves as an insulating shell that prevents TiC particles from direct contacting and suppresses the loss and leakage current to very low levels, but also enhances the interfacial interactions thereby leading to improved mechanical strength and toughness. The prepared flexible PDA@TiC/TPU with high permittivity but low loss will find potential applications in electronic and electrical applications.

Comparing Chinese children and adults with RT-PCR positive COVID-19: A systematic review.

BACKGROUND: The various clinical manifestations of COVID-19 with RT-PCR positive patients have been reported. However, the differences in the clinical presentation between children and adults were unclear. Thus, we aimed to investigate the differences in the clinical manifestations and imaging characteristics between Chinese children and adults with COVID-19 by systematically analyzing the data derived from some latest literatures. METHODS: An extensive search of COVID-19 papers was conducted in PubMed and Chinese medical journal network, and relevant articles were selected based on some standard requirements. The included papers were analyzed for differences in clinical manifestation between children and adults with COVID-19 after the quality evaluation with the QUADAS-2 tool. The differences in the clinical features and CT findings were analyzed using a Pearson χ2 test or Fisher's exact test. Patients who underwent CT examination were divided into the initial examination (0-4days) and follow-up examination groups (5-14 days). RESULTS: A total of 345patients (70 children and 275 adults) with RT- PCR (+) were included in our study (5 papers for children and 5 papers for adult groups). Significant differences between children and adults were found in exposure history (p < 0.001, χ2 = 166.890), fever (p = 0.016, χ2 = 5.757), white cell count (p < 0.001, χ2 = 14.043), and CT features in the initial (p < 0.001, χ2 = 60.653) and follow-up stages (p < 0.001, χ2 = 52.924); and the involved lung in the follow-up stage (p ＜ 0.001, χ2 = 16.776). CONCLUSIONS: Some differences have been presented between children and adults with RT-PCR positive COVID-19, which are helpful in the management and protection of children with COVID-19.

A Hereditable Mutation of MSH2 Gene Associated with Lynch Syndrome in a Five Generation Chinese Family.

PURPOSE: In order to clarify which variants of the MMR gene could provide current "healthy" members in affected families a more accurate risk assessment or predictive testing. PATIENTS AND METHODS: One family, which meets the criteria according to both Amsterdam I/II and Bethesda guidelines, is reported in this study. The proband and some relatives of the patient have been investigated for whole genome sequencing, microsatellite instability, immunohistochemical MMR protein staining and verified by Sanger sequencing. RESULTS: A heterozygous insertion of uncertain significance (c.420dup, p.Met141Tyrfs) in MSH2 gene was found in proband (III-16) and part of His relatives. The variant was associated with a lack of expression of MSH2 protein (MMR deficient) and high microsatellite instability analysis (MSI) status in tumor tissues of LS patients. In addition, we found that the variant could affect the expression of MSH2 and the response to chemotherapy drugs in vitro. CONCLUSION: We identified an insertion mutation (rs1114167810, c.420dup, p.Met141Tyrfs) in MSH2 in LS using whole genome-wide sequencing (WGS). We further confirmed that this mutation plays an important role in LS patients of this pedigree based on in vivo and vitro study.

MRI-Based Radiomics Predicts Tumor Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer.

Background: Conventional methods for predicting treatment response to neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC) are limited. Methods: This study retrospectively recruited 134 LARC patients who underwent standard nCRT followed by total mesorectal excision surgery in our institution. Based on pre-operative axial T2-weighted images, machine learning radiomics was performed. A receiver operating characteristic (ROC) curve was performed to test the efficiencies of the predictive model. Results: Among the 134 patients, 32 (23.9%) achieved pathological complete response (pCR), 69 (51.5%) achieved a good response, and 91 (67.9%) achieved down-staging. For prediction of pCR, good-response, and down-staging, the predictive model demonstrated high classification efficiencies, with an AUC value of 0.91 (95% CI: 0.83-0.98), 0.90 (95% CI: 0.83-0.97), and 0.93 (95% CI: 0.87-0.98), respectively. Conclusion: Our machine learning radiomics model showed promise for predicting response to nCRT in patients with LARC. Our predictive model based on the commonly used T2-weighted images on pelvic Magnetic Resonance Imaging (MRI) scans has the potential to be adapted in clinical practice. Novelty and Impact Statements: Methods for predicting the response of the locally advanced rectal cancer (LARC, T3-4, or N+) to neoadjuvant chemoradiotherapy (nCRT) is lacking. In the present study, we developed a new machine learning radiomics method based on T2-weighted images. As a non-invasive tool, this method facilitates prediction performance effectively. It achieves a satisfactory overall diagnostic accuracy for predicting of pCR, good response, and down-staging show an AUC of 0.908, 0.902, and 0.930 in LARC patients, respectively.

A novel role of kynureninase in the growth control of breast cancer cells and its relationships with breast cancer.

Breast cancer is the most common malignancy among women worldwide. Kynureninase (KYNU) located in 2q22.2, which was associated with tryptophan utilization and metabolic diseases including cardiac, renal and limb defects syndrome 2. However, the role of KYNU in breast cancer (BC) development remains unclear. The expression of KYNU was examined by immunohistochemistry (IHC) in 137 primary BC tissues, and the correlation of KYNU expression with clinical pathological characteristics and the biomarkers (ER, PR, HER2, E-cad and Ki-67) was analysed. The role of KYNU in cancer cell proliferation, tumour growth and development was evaluated by MTT assay, soft agar colony formation assay and xenograft mouse models. Among 137 primary BC tissues, 46.7% (64/137) had high KYNU expression (IHC scores >4) while 53.3% (73/137) had low KYNU expression (IHC scores ≤4). The expression of KYNU was positively correlated with the expressions of ER (P = .002), PR (P = .007) and E-cad (P = .03), while negatively associated with tumour grade (P = .008), tumour stage (P < .001) and the expressions of HER2 (P = .04) and Ki-67 (P = .019). Overexpression of KYNU significantly inhibited cell proliferation in cell culture, colony formation in soft agar and xenograft BC development in NOD/SCID mice. Kynureninase suppresses BC cell proliferation, tumour growth and development. Kynureninase may function as a tumour suppressor in BC.

[Correlation of CT imaging features and CT texture analysis parameters with pathologic risk stratification in gastric stromal tumors].

OBJECTIVE: To analyze the correlation of the CT imaging features and CT texture analysis (CTTA) parameters with risk stratifications of the gastric stromal tumors (GSTs).
 Methods: CT (plain scans with portal phase contrast enhanced scans) images from 98 GSTs patients before surgery were collected. CT features of the tumors were retrospectively analyzed and pathological risk stratifications were determined. Feature parameters of CTTA at plain and portal phase were obtained by using a MaZda software. The correlations of CT imaging features and CTTA parameters with the risk stratifications were analyzed.
 Results: CT imaging features including tumor size, growth pattern, shape, margin, the relationship between mass and adjacent organs, enhancement pattern, necrosis or cystic change, and the abnormal tumor vessels were associated with the risk stratifications (P<0.05). For CTTA, entropy was associated with the risk stratifications (P<0.05).
 Conclusion: Certain CT imaging features and CTTA parameters are associated with risk classifications in GSTs.