Neutrophil extracellular traps mediate cardiomyocyte ferroptosis via the Hippo-Yap pathway to exacerbate doxorubicin-induced cardiotoxicity.

Doxorubicin-induced cardiotoxicity (DIC), which is a cardiovascular complication, has become the foremost determinant of decreased quality of life and mortality among survivors of malignant tumors, in addition to recurrence and metastasis. The limited ability to accurately predict the occurrence and severity of doxorubicin-induced injury has greatly hindered the prevention of DIC, but reducing the dose to mitigate side effects may compromise the effective treatment of primary malignancies. This has posed a longstanding clinical challenge for oncologists and cardiologists. Ferroptosis in cardiomyocytes has been shown to be a pivotal mechanism underlying cardiac dysfunction in DIC. Ferroptosis is influenced by multiple factors. The innate immune response, as exemplified by neutrophil extracellular traps (NETs), may play a significant role in the regulation of ferroptosis. Therefore, the objective of this study was to investigate the involvement of NETs in doxorubicin-induced cardiomyocyte ferroptosis and elucidate their regulatory role. This study confirmed the presence of NETs in DIC in vivo. Furthermore, we demonstrated that depleting neutrophils effectively reduced the occurrence of doxorubicin-induced ferroptosis and myocardial injury in DIC. Additionally, our findings showed the pivotal role of high mobility group box 1 (HMGB1) as a critical molecule implicated in DIC and emphasized its involvement in the modulation of ferroptosis subsequent to NETs inhibition. Mechanistically, we obtained preliminary evidence suggesting that doxorubicin-induced NETs could modulate yes-associated protein (YAP) activity by releasing HMGB1, which subsequently bound to toll like receptor 4 (TLR4) on the cardiomyocyte membrane, thereby influencing cardiomyocyte ferroptosis in vitro. Our findings suggest that doxorubicin-induced NETs modulate cardiomyocyte ferroptosis via the HMGB1/TLR4/YAP axis, thereby contributing to myocardial injury. This study offers a novel approach for preventing and alleviating DIC by targeting alterations in the immune microenvironment.

Protective effect of low-intensity pulsed ultrasound on immune checkpoint inhibitor-related myocarditis via fine-tuning CD4+ T-cell differentiation.

PURPOSE: Immune checkpoint inhibitors (ICIs) have transformed traditional cancer treatments. Specifically, ICI-related myocarditis is an immune-related adverse event (irAE) with high mortality. ICIs activate CD4+ T-lymphocyte reprogramming, causing an imbalance between Th17 and Treg cell differentiation, ultimately leading to myocardial inflammatory damage. Low-intensity pulsed ultrasound (LIPUS) can limit inflammatory responses, with positive therapeutic effects across various cardiovascular inflammatory diseases; however, its role in the pathogenesis of ICI-related myocarditis and CD4+ T-cell dysfunction remains unclear. Accordingly, this study investigated whether LIPUS can alleviate ICI-related myocarditis inflammatory damage and, if so, aimed to elucidate the beneficial effects of LIPUS and its underlying molecular mechanisms. METHODS: An in vivo model of ICI-related myocarditis was obtained by intraperitonially injecting male A/J mice with an InVivoPlus anti-mouse PD-1 inhibitor. LIPUS treatment was performed via an ultrasound-guided application to the heart via the chest wall. The echocardiographic parameters were observed and cardiac function was assessed using an in vivo imaging system. The expression of core components of the HIPPO pathway was analyzed via western blotting. RESULTS: LIPUS treatment reduced cardiac immune responses and inflammatory cardiac injury. Further, LIPUS treatment alleviated the inflammatory response in mice with ICI-related myocarditis. Mechanistically, in the HIPPO pathway, the activation of Mst1-TAZ axis improved autoimmune inflammation by altering the interaction between the transcription factors FOXP3 and RORγt and regulating the differentiation of Treg and Th17 cells. CONCLUSION: LIPUS therapy was shown to reduce ICI-related myocarditis inflammatory damage and improve cardiac function, representing an exciting finding for irAEs treatment.

Evaluation of standard breast ultrasonography by adding two-dimensional and three-dimensional shear wave elastography: a prospective, multicenter trial.

OBJECTIVE: To reduce the number of biopsies performed on benign breast lesions categorized as BI-RADS 4-5, we investigated the diagnostic performance of combined two-dimensional and three-dimensional shear wave elastography (2D + 3D SWE) with standard breast ultrasonography (US) for the BI-RADS assessment of breast lesions. METHODS: A total of 897 breast lesions, categorized as BI-RADS 3-5, were subjected to standard breast US and supplemented by 2D SWE only and 2D + 3D SWE analysis. Based on the malignancy rate of less than 2% for BI-RADS 3, lesions assessed by standard breast US were reclassified with SWE assessment. RESULTS: After standard breast US evaluation, 268 (46.1%) participants underwent benign biopsies in BI-RADS 4-5 lesions. By using separated cutoffs for upstaging BI-RADS 3 at 120 kPa and downstaging BI-RADS 4a at 90 kPa in 2D + 3D SWE reclassification, 123 (21.2%) participants underwent benign biopsy, resulting in a 54.1% reduction (123 versus 268). CONCLUSION: Combining 2D + 3D SWE with standard breast US for reclassification of BI-RADS lesions may achieve a reduction in benign biopsies in BI-RADS 4-5 lesions without sacrificing sensitivity unacceptably. CLINICAL RELEVANCE STATEMENT: Combining 2D + 3D SWE with US effectively reduces benign biopsies in breast lesions with categories 4-5, potentially improving diagnostic accuracy of BI-RADS assessment for patients with breast lesions. TRIAL REGISTRATION: ChiCTR1900026556 KEY POINTS: • Reduce benign biopsy is necessary in breast lesions with BI-RADS 4-5 category. • A reduction of 54.1% on benign biopsies in BI-RADS 4-5 lesions was achieved using 2D + 3D SWE reclassification. • Adding 2D + 3D SWE to standard breast US improved the diagnostic performance of BI-RADS assessment on breast lesions: specificity increased from 54 to 79%, and PPV increased from 54 to 71%, with slight loss in sensitivity (97.2% versus 98.7%) and NPV (98.1% versus 98.7%).

Construction and validation of a nomogram prediction model for axillary lymph node metastasis of cT1 invasive breast cancer.

OBJECTIVE: Based on the ultrasonic characteristics of the breast mass and axillary lymph nodes as well as the clinicopathological information, a model was developed for predicting axillary lymph node metastasis in cT1 breast cancer, and relevant features associated with axillary lymph node metastasis were identified. METHODS: Our retrospective study included 808 patients with cT1 invasive breast cancer treated at the Second Affiliated Hospital and the Cancer Hospital Affiliated with Harbin Medical University from February 2012 to August 2021 (250 cases in the positive axillary lymph node group and 558 cases in the negative axillary lymph node group). We allocated 564 cases to the training set and 244 cases to the verification set. R software was used to compare clinicopathological data and ultrasonic features between the two groups. Based on the results of multivariate logistic regression analysis, a nomogram prediction model was developed and verified for axillary lymph node metastasis of cT1 breast cancer. RESULTS: Univariate and multivariate logistic regression analysis indicated that palpable lymph nodes (P = 0.003), tumor location (P = 0.010), marginal contour (P < 0.001), microcalcification (P = 0.010), surrounding tissue invasion (P = 0.046), ultrasonic detection of lymph nodes (P = 0.001), cortical thickness (P < 0.001) and E-cadherin (P < 0.001) are independently associated with axillary lymph node metastasis. Using these features, a nomogram was developed for axillary lymph node metastasis. The training set had an area under the curve of 0.869, while the validation set had an area under the curve of 0.820. Based on the calibration curve, the model predicted axillary lymph node metastases were in good agreement with reality (P > 0.05). Nomogram's net benefit was good based on decision curve analysis. CONCLUSION: The nomogram developed in this study has a high negative predictive value for axillary lymph node metastasis in invasive cT1 breast c ancer. Patients with no axillary lymph node metastases can be accurately screened using this nomogram, potentially allowing this group of patients to avoid invasive surgery.

Quality assessment of transperineal ultrasound in Chinese tertiary medical centers: a multicenter study.

Background: Transperineal ultrasound (TPUS) is a vital examination method for diagnosing pelvic floor diseases. However, the quality of TPUS largely relies on the operator's experience, and there is a lack of studies on the evaluation of TPUS quality. Therefore, the objective of this study was to assess the quality of TPUS examinations in Chinese tertiary medical centers. Methods: This multicenter study conducted in 44 Chinese tertiary medical centers recruited postpartum women between September 2020 and September 2021. All participants underwent a standardized inquiry and TPUS examination. The participating centers were required to submit 5 parts of ultrasound data to the National Ultrasound Quality Control Center: 2-dimensional images at rest, 2-dimensional images at strain; 4-dimensional images of the levator ani hiatus; 4-dimensional images of the levator ani muscle; and 4-dimensional images of the anal sphincter. Quality assessment was performed by 2 experts with more than 5 years of experience in TPUS, and the reasons for nonqualification were stated. Results: In this study, 31 hospitals that were distributed across 20 provinces in China were included, submitting 2,251 cases in total. The overall qualified rate ranged from 12.00% to 86.92%. In each part, the qualified rate of 2-dimensional images at rest, 2-dimensional images at straining, levator ani hiatus, levator ani muscle, and anal sphincter was 94.27% (2,122/2,251), 78.54% (1,768/2,251), 85.52% (1,925/2,251), 93.03% (2,094/2,251), and 88.09% (1,983/2,251), respectively. Most of the nonqualified images belonged to 2-dimensional images at strain, and the errors in image acquisition (221/483, 45.76%) and measurement (262/483, 54.24%) were the main reasons for nonqualification. For levator ani hiatus images, error in image acquisition (275/326, 84.36%) was the main reason for nonqualification. Reconstruction error was the most common reason for nonqualification for levator ani muscle (133/157, 84.71%) and anal sphincter images (133/268, 49.63%). Conclusions: This multicenter study assessed the quality of TPUS in tertiary medical centers in China and identified the common reasons for nonqualification in each part. These findings can aid in forming the basis for quality control management and training for TPUS.

Deep learning-based classification of breast lesions using dynamic ultrasound video.

PURPOSE: We intended to develop a deep-learning-based classification model based on breast ultrasound dynamic video, then evaluate its diagnostic performance in comparison with the classic model based on ultrasound static image and that of different radiologists. METHOD: We collected 1000 breast lesions from 888 patients from May 2020 to December 2021. Each lesion contained two static images and two dynamic videos. We divided these lesions randomly into training, validation, and test sets by the ratio of 7:2:1. Two deep learning (DL) models, namely DL-video and DL-image, were developed based on 3D Resnet-50 and 2D Resnet-50 using 2000 dynamic videos and 2000 static images, respectively. Lesions in the test set were evaluated to compare the diagnostic performance of two models and six radiologists with different seniority. RESULTS: The area under the curve of the DL-video model was significantly higher than those of the DL-image model (0.969 vs. 0.925, P = 0.0172) and six radiologists (0.969 vs. 0.779-0.912, P < 0.05). All radiologists performed better when evaluating the dynamic videos compared to the static images. Furthermore, radiologists performed better with increased seniority both in reading images and videos. CONCLUSIONS: The DL-video model can discern more detailed spatial and temporal information for accurate classification of breast lesions than the conventional DL-image model and radiologists, and its clinical application can further improve the diagnosis of breast cancer.

Development and validation of a transformer-based CAD model for improving the consistency of BI-RADS category 3-5 nodule classification among radiologists: a multiple center study.

Background: Significant differences exist in the classification outcomes for radiologists using ultrasonography-based Breast Imaging Reporting and Data Systems for diagnosing category 3-5 (BI-RADS 3-5) breast nodules, due to a lack of clear and distinguishing image features. Consequently, this retrospective study investigated the improvement of BI-RADS 3-5 classification consistency using a transformer-based computer-aided diagnosis (CAD) model. Methods: Independently, 5 radiologists performed BI-RADS annotations on 21,332 breast ultrasonographic images collected from 3,978 female patients from 20 clinical centers in China. All images were divided into training, validation, testing, and sampling sets. The trained transformer-based CAD model was then used to classify test images, for which sensitivity (SEN), specificity (SPE), accuracy (ACC), area under the curve (AUC), and calibration curve were evaluated. Variations in these metrics among the 5 radiologists were analyzed by referencing BI-RADS classification results for the sampling test set provided by CAD to determine whether classification consistency (the k value), SEN, SPE, and ACC could be improved. Results: After the training set (11,238 images) and validation set (2,996 images) were learned by the CAD model, the classification ACC of the CAD model applied to the test set (7,098 images) was 94.89% in category 3, 96.90% in category 4A, 95.49% in category 4B, 92.28% in category 4C, and 95.45% in category 5 nodules. Based on pathological results, the AUC of the CAD model was 0.924 and the predicted probability of CAD was a little higher than the actual probability in the calibration curve. After referencing BI-RADS classification results, the adjustments were made to 1,583 nodules, of which 905 were classified to a lower category and 678 to a higher category in the sampling test set. As a result, the ACC (72.41-82.65%), SEN (32.73-56.98%), and SPE (82.46-89.26%) of the classification by each radiologist were significantly improved on average, with the consistency (k values) in almost all of them increasing to >0.6. Conclusions: The radiologist's classification consistency was markedly improved with almost all the k values increasing by a value greater than 0.6, and the diagnostic efficiency was also improved by approximately 24% (32.73% to 56.98%) and 7% (82.46% to 89.26%) for SEN and SPE, respectively, of the total classification on average. The transformer-based CAD model can help to improve the radiologist's diagnostic efficacy and consistency with others in the classification of BI-RADS 3-5 nodules.

Correlation of androgen receptor with ultrasound, clinicopathological features and clinical outcomes in breast cancer.

BACKGROUND: This study aimed to explore whether there is an association between androgen receptor (AR) expression and ultrasound, clinicopathological features and prognosis of breast cancer. METHODS: A total of 141 breast cancer patients were included in this retrospective study. AR expression was analyzed by immunohistochemistry. The images of B-mode, color Doppler and strain elastography from 104 patients were collected continuously, and the corresponding ultrasound characteristics were obtained. The differences in ultrasound and clinicopathological features in different AR status were analyzed. Progression-free survival (PFS) of patients was obtained through up to 90 months of follow-up; then, the effect of AR on PFS was analyzed. Subsequently, a nomogram was constructed to predict the AR status. The predictive accuracy was calculated using C-index. RESULTS: The positive expression of AR (AR +) was associated with lower histological grade (p = 0.034) and lower Ki-67 level (p = 0.029). Triple-negative breast cancer (TNBC) had the lowest probability of AR + (p < 0.001). The AR + group mostly showed unsmooth margin (p < 0.001), posterior acoustic shadowing (p = 0.002) and higher elasticity score (p = 0.022) on ultrasound. The echo pattern of most tumors with AR + was heterogeneous (p = 0.024) in Luminal A subtype. AR + could be a sign of a better prognosis in overall breast cancer (p < 0.001), as well as in human epidermal growth factor receptor 2 (HER2) overexpression and Luminal B subtypes (p = 0.001 and 0.025). The nomogram showed relatively reliable performance with a C-index of 0.799. CONCLUSION: Our research demonstrated that AR expression was closely related to ultrasound, clinicopathological features and prognosis of breast cancer.

Nomogram based on the O-RADS for predicting the malignancy risk of adnexal masses with complex ultrasound morphology.

OBJECTIVE: The accurate preoperative differentiation of benign and malignant adnexal masses, especially those with complex ultrasound morphology, remains a great challenge for junior sonographers. The purpose of this study was to develop and validate a nomogram based on the Ovarian-Adnexal Reporting and Data System (O-RADS) for predicting the malignancy risk of adnexal masses with complex ultrasound morphology. METHODS: A total of 243 patients with data on adnexal masses with complex ultrasound morphology from January 2019 to December 2020 were selected to establish the training cohort, while 106 patients with data from January 2021 to December 2021 served as the validation cohort. Univariate and multivariate analyses were used to determine independent risk factors for malignant tumors in the training cohort. Subsequently, a predictive nomogram model was developed and validated in the validation cohort. The calibration, discrimination, and clinical net benefit of the nomogram model were assessed separately by calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). Finally, we compared this model to the O-RADS. RESULTS: The O-RADS category, an elevated CA125 level, acoustic shadowing and a papillary projection with color Doppler flow were the independent predictors and were incorporated into the nomogram model. The area under the ROC curve (AUC) of the nomogram model was 0.958 (95% CI, 0.932-0.984) in the training cohort. The specificity and sensitivity were 0.939 and 0.893, respectively. This nomogram also showed good discrimination in the validation cohort (AUC = 0.940, 95% CI, 0.899-0.981), with a sensitivity of 0.915 and specificity of 0.797. In addition, the nomogram model showed good calibration efficiency in both the training and validation cohorts. DCA indicated that the nomogram was clinically useful. Furthermore, the nomogram model had higher AUC and net benefit than the O-RADS. CONCLUSION: The nomogram based on the O-RADS showed a good predictive ability for the malignancy risk of adnexal masses with complex ultrasound morphology and could provide help for junior sonographers.

Ultrasound and microbubble-mediated delivery of miR-424-5p has a therapeutic effect in preeclampsia.

OBJECTIVE: To determine the influence of ultrasound/microbubble-mediated miR-424-5p delivery on trophoblast cells and the underlying mechanism. METHODS: Blood pressure and 24-h proteinuria of patients with preeclampsia (PE) were measured as well as the levels of miR-424-5p and amine oxidase copper containing 1 (AOC1) in placental tissues. HTR-8/Svneo and TEV-1 cells were subjected to cell transfection or ultrasonic microbubble transfection for determination of the expression of miR-424-5p, AOC1, ß-catenin and c-Myc as well as cell proliferation, apoptosis, migration and invasiveness. The concentrations of placental growth factor (PLGF), human chorionic gonadotropin (ß-hCG) and tumor necrosis factor-α (TNF-α) were measured in HTR-8/Svneo and TEV-1 cells. RNA immunoprecipitation (RIP) and dual luciferase reporter assay detected the binding of miR-424-5p to AOC1. A PE mouse model was induced by subcutaneous injection of L-NAME, where the influence of ultrasound/microbubble-mediated miR-424-5p delivery was evaluated. RESULTS: miR-424-5p was downregulated while AOC1 was upregulated in the placental tissues from PE patients. Overexpression of miR-424-5p activated Wnt/ß-catenin signaling pathway and promoted the proliferation of HTR-8/Svneo and TEV-1 cells as well as enhanced the migratory and invasive behaviors. AOC1 overexpression partly eliminated the effects of miR-424-5p on HTR-8/Svneo and TEV-1 cells. Ultrasound and microbubble mediated gene delivery enhanced the transfection efficiency of miR-424-5p and further promoted the effects of miR-424-5p in trophoblast cells. Ultrasound/microbubble-mediated miR-424-5p delivery alleviated experimental PE in mice. CONCLUSION: Ultrasound and microbubble-mediated miR-424-5p delivery targets AOC1 and activates Wnt/ß-catenin signaling pathway, thus promoting the aggressive phenotype of trophoblast cells, which indicating that miR-424-5p/AOC1 axis might be involved with PE pathogenesis.

Radiogenomic analysis of prediction HER2 status in breast cancer by linking ultrasound radiomic feature module with biological functions.

BACKGROUND: Human epidermal growth factor receptor 2 (HER2) overexpressed associated with poor prognosis in breast cancer and HER2 has been defined as a therapeutic target for breast cancer treatment. We aimed to explore the molecular biological information in ultrasound radiomic features (URFs) of HER2-positive breast cancer using radiogenomic analysis. Moreover, a radiomics model was developed to predict the status of HER2 in breast cancer. METHODS: This retrospective study included 489 patients who were diagnosed with breast cancer. URFs were extracted from a radiomics analysis set using PyRadiomics. The correlations between differential URFs and HER2-related genes were calculated using Pearson correlation analysis. Functional enrichment of the identified URFs-correlated HER2 positive-specific genes was performed. Lastly, the radiomics model was developed based on the URF-module mined from auxiliary differential URFs to assess the HER2 status of breast cancer. RESULTS: Eight differential URFs (p < 0.05) were identified among the 86 URFs extracted by Pyradiomics. 25 genes that were found to be the most closely associated with URFs. Then, the relevant biological functions of each differential URF were obtained through functional enrichment analysis. Among them, Zone Entropy is related to immune cell activity, which regulate the generation of calcification in breast cancer. The radiomics model based on the Logistic classifier and URF-module showed good discriminative ability (AUC = 0.80, 95% CI). CONCLUSION: We searched for the URFs of HER2-positive breast cancer, and explored the underlying genes and biological functions of these URFs. Furthermore, the radiomics model based on the Logistic classifier and URF-module relatively accurately predicted the HER2 status in breast cancer.

Epididymis cell atlas in a patient with a sex development disorder and a novel NR5A1 gene mutation.

This study aims to characterize the cell atlas of the epididymis derived from a 46,XY disorders of sex development (DSD) patient with a novel heterozygous mutation of the nuclear receptor subfamily 5 group A member 1 (NR5A1) gene. Next-generation sequencing found a heterozygous c.124C>G mutation in NR5A1 that resulted in a p.Q42E missense mutation in the conserved DNA-binding domain of NR5A1. The patient demonstrated feminization of external genitalia and Tanner stage 1 breast development. The surgical procedure revealed a morphologically normal epididymis and vas deferens but a dysplastic testis. Microfluidic-based single-cell RNA sequencing (scRNA-seq) analysis found that the fibroblast cells were significantly increased (approximately 46.5%), whereas the number of main epididymal epithelial cells (approximately 9.2%), such as principal cells and basal cells, was dramatically decreased. Bioinformatics analysis of cell-cell communications and gene regulatory networks at the single-cell level inferred that epididymal epithelial cell loss and fibroblast occupation are associated with the epithelial-to-mesenchymal transition (EMT) process. The present study provides a cell atlas of the epididymis of a patient with 46,XY DSD and serves as an important resource for understanding the pathophysiology of DSD.

Nicotine exacerbates endothelial dysfunction and drives atherosclerosis via extracellular vesicle-miRNA.

AIMS: Nicotine, a major component of tobacco, is an important factor contributing to atherosclerosis. However, the molecular mechanisms underlying the link between nicotine and atherosclerosis are unclear. As extracellular vesicles (EVs) are involved in intercellular communication in atherosclerosis, we investigated whether their influence on arterial pathophysiology under nicotine stimulation. METHODS AND RESULTS: EVs from the serum of smokers (smoker-EVs) were significantly increased and exacerbated endothelial inflammation, as well as apoptosis according to functional studies. Meanwhile, inhibition of EVs blunted the nicotine-induced atherosclerosis progression, and injection of nicotine-induced EVs promoted atherosclerosis progression in ApoE-/- mice. Furthermore, quantitative reverse transcription-polymerase chain reaction analysis revealed a remarkable increase in miR-155 levels in smoker-EVs, which was correlated with carotid plaque formation in patients measured by ultrasound imaging. Moreover, CD14 levels were significantly increased in EVs from smokers (representing EVs derived from monocytes), indicating that monocytes are an important source of smoker-EVs. DNA methylation and the transcription factor HIF1α may contribute to increased miR-155 levels in monocytes, as assessed with bisulfite conversion sequencing and chromatin immunoprecipitation. Mechanistically, EVs encapsulated miR-155 induced endothelial cell dysfunction by directedly targeting BCL2, MCL1, TIMP3, BCL6, and activating NF-κB pathway, as verified in a series of molecular and biological experiments. Injecting EVs from nicotine-stimulated monocytes promoted plaque formation and triggered vascular endothelial injury in ApoE-/- mice, whereas inhibition of miR-155 weakened this effect. CONCLUSION: Our findings revealed an EV-dependent mechanism of nicotine-aggravated atherosclerosis. Accordingly, we propose an EV-based intervention strategy for atherosclerosis management.

Ultrasound-based deep learning in the establishment of a breast lesion risk stratification system: a multicenter study.

OBJECTIVES: To establish a breast lesion risk stratification system using ultrasound images to predict breast malignancy and assess Breast Imaging Reporting and Data System (BI-RADS) categories simultaneously. METHODS: This multicenter study prospectively collected a dataset of ultrasound images for 5012 patients at thirty-two hospitals from December 2018 to December 2020. A deep learning (DL) model was developed to conduct binary categorization (benign and malignant) and BI-RADS categories (2, 3, 4a, 4b, 4c, and 5) simultaneously. The training set of 4212 patients and the internal test set of 416 patients were from thirty hospitals. The remaining two hospitals with 384 patients were used as an external test set. Three experienced radiologists performed a reader study on 324 patients randomly selected from the test sets. We compared the performance of the DL model with that of three radiologists and the consensus of the three radiologists. RESULTS: In the external test set, the DL model achieved areas under the receiver operating characteristic curve (AUCs) of 0.980 and 0.945 for the binary categorization and six-way categorizations, respectively. In the reader study set, the DL BI-RADS categories achieved a similar AUC (0.901 vs. 0.933, p = 0.0632), sensitivity (90.98% vs. 95.90%, p = 0.1094), and accuracy (83.33% vs. 79.01%, p = 0.0541), but higher specificity (78.71% vs. 68.81%, p = 0.0012) than those of the consensus of the three radiologists. CONCLUSIONS: The DL model performed well in distinguishing benign from malignant breast lesions and yielded outcomes similar to experienced radiologists. This indicates the potential applicability of the DL model in clinical diagnosis. KEY POINTS: • The DL model can achieve binary categorization for benign and malignant breast lesions and six-way BI-RADS categorizations for categories 2, 3, 4a, 4b, 4c, and 5, simultaneously. • The DL model showed acceptable agreement with radiologists for the classification of breast lesions. • The DL model performed well in distinguishing benign from malignant breast lesions and had promise in helping reduce unnecessary biopsies of BI-RADS 4a lesions.

Deep learning for the diagnosis of suspicious thyroid nodules based on multimodal ultrasound images.

Objectives: This study aimed to differentially diagnose thyroid nodules (TNs) of Thyroid Imaging Reporting and Data System (TI-RADS) 3-5 categories using a deep learning (DL) model based on multimodal ultrasound (US) images and explore its auxiliary role for radiologists with varying degrees of experience. Methods: Preoperative multimodal US images of 1,138 TNs of TI-RADS 3-5 categories were randomly divided into a training set (n = 728), a validation set (n = 182), and a test set (n = 228) in a 4:1:1.25 ratio. Grayscale US (GSU), color Doppler flow imaging (CDFI), strain elastography (SE), and region of interest mask (Mask) images were acquired in both transverse and longitudinal sections, all of which were confirmed by pathology. In this study, fivefold cross-validation was used to evaluate the performance of the proposed DL model. The diagnostic performance of the mature DL model and radiologists in the test set was compared, and whether DL could assist radiologists in improving diagnostic performance was verified. Specificity, sensitivity, accuracy, positive predictive value, negative predictive value, and area under the receiver operating characteristics curves (AUC) were obtained. Results: The AUCs of DL in the differentiation of TNs were 0.858 based on (GSU + SE), 0.909 based on (GSU + CDFI), 0.906 based on (GSU + CDFI + SE), and 0.881 based (GSU + Mask), which were superior to that of 0.825-based single GSU (p = 0.014, p< 0.001, p< 0.001, and p = 0.002, respectively). The highest AUC of 0.928 was achieved by DL based on (G + C + E + M)US, the highest specificity of 89.5% was achieved by (G + C + E)US, and the highest accuracy of 86.2% and sensitivity of 86.9% were achieved by DL based on (G + C + M)US. With DL assistance, the AUC of junior radiologists increased from 0.720 to 0.796 (p< 0.001), which was slightly higher than that of senior radiologists without DL assistance (0.796 vs. 0.794, p > 0.05). Senior radiologists with DL assistance exhibited higher accuracy and comparable AUC than that of DL based on GSU (83.4% vs. 78.9%, p = 0.041; 0.822 vs. 0.825, p = 0.512). However, the AUC of DL based on multimodal US images was significantly higher than that based on visual diagnosis by radiologists (p< 0.05). Conclusion: The DL models based on multimodal US images showed exceptional performance in the differential diagnosis of suspicious TNs, effectively increased the diagnostic efficacy of TN evaluations by junior radiologists, and provided an objective assessment for the clinical and surgical management phases that follow.

Melatonin alleviates arginine vasopressin-induced cardiomyocyte apoptosis via increasing Mst1-Nrf2 pathway activity to reduce oxidative stress.

Heart failure patients have elevated arginine vasopressin (AVP) levels, which are involved in inducing peripheral vasoconstriction and cardiac hypertrophy. This hypertrophy, along with cardiomyocyte apoptosis, results from oxidative stress. Therefore, the antioxidant drug, melatonin (Mel), is commonly used to treat cardiac hypertrophy and apoptosis; however, whether it could alleviate AVP-induced myocardialinjury remains to be addressed. In this study, high AVP doses were found to induce H9c2 cardiomyoblast apoptosis, demonstrated by increased terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL)-positive cells, pro-apoptotic B-cell lymphoma-2 (Bcl-2)-associated X protein (Bax) up-regulation, and anti-apoptotic Bcl-2 downregulation. This AVP-induced apoptotic increase, along with lowered cell viability, was also associated with higher reactive oxygen species (ROS) levels and lowered mitochondrial membrane potentials (MMP), which were all reversed upon Mel administration. Further investigations found that apoptosis, ROS, and MMP outcomes under high AVP were associated with Mst1-nuclear factor erythroid 2-related factor 2 (Nrf2) pathway suppression, yielding mitochondrial dysfunction, and Mel reversed them via promoting Mst1 phosphorylation, which then activated Nrf2 to increase anti-oxidative enzyme production. These findings were supported by siRNA gene suppression, where knocking down either Nrf2 or Mst1 abrogated the anti-apoptotic effects of Mel in cardiomyoblasts. Therefore, Mel could reduce cardiomyoblast apoptosis under high AVP levels, via Mst1-Nrf2 pathway re-activation, to enhance anti-oxidative responses.

LncRNA PVT1 is a novel mediator promoting the angiogenesis response associated with collateral artery formation.

AIMS: Angiogenesis plays a key role in coronary collateral circulation (CCC), the compensatory formation of new blood vessels during chronic total coronary occlusion. This study aimed to determine whether plasmacytoma variant translocation 1 (PVT1), a long non-coding (lnc) RNA involved in tumor angiogenesis, plays a role in regulating angiogenesis during chronic coronary ischemia. MAIN METHODS: Patients with coronary artery disease, and ≥ 90% stenosis, were examined and divided into "Good" and "Poor" CCC groups based on Rentrop Cohen classification. RNA samples were obtained from all patients, as well as from oxygen and glucose-deprived (OGD) HUVECs. PVT1, miR-15b-5p and AKT3 levels were measured with RT-qPCR or Western blot, while HUVEC migration and angiogenesis were detected by, respectively, wound-healing and tube formation assays. Luciferase reporter assay confirmed direct PVT1-miR-15b-5p binding. KEY FINDINGS: Increased PVT1 was found in "Good CCC" patient plasma, along with being highly expressed among OGD HUVECs; PVT1 knockdown reduced HUVEC migration, tube formation, and pro-angiogenic factor expression. Conversely, OGD HUVECs had downregulated miR-15b-5p, and miR-15b-5p overexpression significantly depressed their angiogenic capabilities. These PVT1 knockdown- or miR-15b-5p overexpression-associated reductions in angiogenic effects were reversed by AKT3 overexpression. In vivo, neovascularization and functioning in both ischemic mice hind-limbs and infarcted myocardium injected with ADV-sh-PVT1 were reduced, which were ameliorated by concurrent antagomiR-15b-5p injections. SIGNIFICANCE: Circulating PVT1 may serve as a useful biomarker to distinguish between good versus poor CCC, as it is involved in orchestrating angiogenesis via the miR-15b-5p-AKT3 axis; it thus has potential as a target for treating ischemic disease.

Deep learning based on ultrasound images assists breast lesion diagnosis in China: a multicenter diagnostic study.

BACKGROUND: Studies on deep learning (DL)-based models in breast ultrasound (US) remain at the early stage due to a lack of large datasets for training and independent test sets for verification. We aimed to develop a DL model for differentiating benign from malignant breast lesions on US using a large multicenter dataset and explore the model's ability to assist the radiologists. METHODS: A total of 14,043 US images from 5012 women were prospectively collected from 32 hospitals. To develop the DL model, the patients from 30 hospitals were randomly divided into a training cohort (n = 4149) and an internal test cohort (n = 466). The remaining 2 hospitals (n = 397) were used as the external test cohorts (ETC). We compared the model with the prospective Breast Imaging Reporting and Data System assessment and five radiologists. We also explored the model's ability to assist the radiologists using two different methods. RESULTS: The model demonstrated excellent diagnostic performance with the ETC, with a high area under the receiver operating characteristic curve (AUC, 0.913), sensitivity (88.84%), specificity (83.77%), and accuracy (86.40%). In the comparison set, the AUC was similar to that of the expert (p = 0.5629) and one experienced radiologist (p = 0.2112) and significantly higher than that of three inexperienced radiologists (p < 0.01). After model assistance, the accuracies and specificities of the radiologists were substantially improved without loss in sensitivities. CONCLUSIONS: The DL model yielded satisfactory predictions in distinguishing benign from malignant breast lesions. The model showed the potential value in improving the diagnosis of breast lesions by radiologists.

Single Nucleotide Polymorphisms of EXOC1, BCL2, CCAT2, and CARD8 Genes and Susceptibility to Cervical Cancer in the Northern Chinese Han Population.

Cervical cancer (CC) is one of the main malignant tumors that threaten the health and lives of women around the world, and its morbidity and mortality rate ranks fourth. At present, most studies on the genetic background of CC focus on genetic polymorphisms. Single nucleotide polymorphisms (SNPs) are considered clinically as potential diagnostic and therapeutic biomarkers for a variety of tumors. Therefore, we aimed to explore the association between SNPs in different genes (EXOC1 gene, BCL2 gene, CCAT2 gene and CARD8 gene) and susceptibility to CC. This study is a case-control study based on women in northern Chinese, which included 492 women with CC and 510 healthy women. This study used multiplex PCR combined with next-generation sequencing to genotype the selected SNPs (rs13117307(C/T) in EXOC1 gene, rs2279115(C/A) in BCL2 gene, rs6983267(G/T) in CCAT2 gene and rs7248320(G/A) in CARD8 gene). The results of the study showed that there was no significant association between the four SNPs and the susceptibility to CC. However, in further stratified analysis, we found that rs13117307 and rs2279115 were significantly related to squamous cell carcinoma antigen (SCC-Ag) levels in women with CC, and rs6983267 was significantly related to the menopausal status of women with CC. Specifically, alleles T of rs13117307 and genoytpe AA of rs2279115 when SCC-Ag is greater than 1.5 ng/ml increase the risk of CC. The genotype TG/TG+TT of rs6983267 increases the risk of CC in premenopausal women. In conclusion, although we did not directly find a significant correlation between four SNPs, rs13117307 in EXOC1 gene,rs2279115 in BCL2 gene, rs6983267 in CCAT2 gene and rs7248320 in CARD8 gene, and CC susceptibility, we found that SNPs rs13117307, rs2279115, rs6983267 were associated with the clinical characteristics of several patients' CC patients. Therefore, this study provides us with new ideas for understanding CC and the diagnosis and treatment of CC in the future.

Nomograms predicting recurrence in patients with triple negative breast cancer based on ultrasound and clinicopathological features.

OBJECTIVES: The clinicopathological and ultrasound features associated with recurrence in patients with triple negative breast cancer (TNBC) were used to develop a nomogram to predict the prognosis of TNBC. METHODS: Clinicopathological data of 300 patients with TNBC treated between July 2012 and September 2014 were retrospectively reviewed. The endpoint was progression-free survival (PFS). Prognostic factors were screened by multivariate COX regression to develop nomograms. The C-index and calibration curves were used to evaluate the predictive accuracy and discriminatory ability of nomograms. RESULTS: Of 300 patients with TNBC followed-up for 5 years, 80 (26.7%) had PFS events. Five informative prognostic factors (large size, vertical orientation, posterior acoustic enhancement, lymph node involvement, and high pathological stage) were screened and used to construct a nomogram for PFS. The C-index of the PFS nomogram was 0.88 (p < 0.01, 95% confidence interval, 0.85-0.90), indicating good predictive accuracy. CONCLUSIONS: We developed and validated a nomogram for predicting PFS in TNBC. Vertical orientation and posterior acoustic enhancement in ultrasound images of TNBC were associated with worse outcomes. ADVANCES IN KNOWLEDGE: Patients with TNBC have a very poor prognosis and patients have a high risk of recurrence, and our study developed a nomogram based on ultrasound and clinicopathological features for TNBC patients to improve the accuracy of individualized prediction of recurrence and provide help for clinical treatment.