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Ovarian cancer (OC) is a common malignant reproductive tumor among women that adversely affects their health. It has been proven that Sauchinone (Sau) derived from Saururus chinensis (Lour.) Baill may aid tumorigenesis in diversiform cancers. Despite this, the regulatory impact of Sau on OC progression remains unclear. In this study, firstly, Sau (10 or 20 µM) had been confirmed to possess no cytotoxicity, so Sau (10 or 20 µM) was utilized for the next experiments. Sau was shown to prevent cell growth in OC. Furthermore, Sau inhibited cell migration and invasion in OC. Our findings demonstrated that Sau attenuated the epithelial-mesenchymal transition (EMT) process by elevating E-cadherin and declining N-cadherin and alpha-smooth muscle actin (a-SMA) expressions. Lastly, Sau blocked the wingless/integrated (Wnt)/ß-catenin pathway. In summary, Sau inhibited cell growth, EMT, and blocked the Wnt/ß-catenin pathway in OC progression. Sau may offer novel perspectives on OC treatment in this study. [ABSTRACT FROM AUTHOR]

Vanadium-based compounds are explored as promising electrode materials in lithium/sodium-ion batteries exhibiting superior energy storage properties. However, similar attempts are rarely reported for potassium-ion batteries (PIBs), in which the fundamental reaction mechanisms remain inexplicit. Herein, porous CaV4O9 nanobelts (NBs) are selected as a PIB anode to systematically investigate potassium storage mechanisms through in situ transmission electron microscopy. In situ measurements track overall electrochemical potassiation reactions of CaV4O9 and identify a polyphase state of V4O7, CaO, and K2O phases after potassiation. Unexpectedly, the potassiated products can be partially converted back to the original CaV4O9 phase with residual VO2 and CaO phases, which is different from the irreversible phase transformations in lithium/sodium storages of CaV4O9. Impressively, the cavities in NBs alternately disappear and appear with (de)potassiation, avoiding the drastic volume change and structural degradation of anodes. The reversible potassium storage and stable cycling are evaluated by electrochemical measurements and in situ X-ray diffraction analysis. This work provides a paradigm by revisiting the existing anode materials in lithium/sodium-ion batteries to seek out viable anodes for next-generation PIBs. [ABSTRACT FROM AUTHOR]

Introduction: Preoperative evaluation of the mitotic index (MI) of gastrointestinal stromal tumors (GISTs) represents the basis of individualized treatment of patients. However, the accuracy of conventional preoperative imaging methods is limited. The aim of this study was to develop a predictive model based on multiparametric MRI for preoperative MI prediction. Methods: A total of 112 patients who were pathologically diagnosed with GIST were enrolled in this study. The dataset was subdivided into the development (n = 81) and test (n = 31) sets based on the time of diagnosis. With the use of T2- weighted imaging (T2WI) and apparent diffusion coefficient (ADC) map, a convolutional neural network (CNN)-based classifier was developed for MI prediction, which used a hybrid approach based on 2D tumor images and radiomics features from 3D tumor shape. The trained model was tested on an internal test set. Then, the hybrid model was comprehensively tested and compared with the conventional ResNet, shape radiomics classifier, and age plus diameter classifier. Results: The hybrid model showed good MI prediction ability at the image level; the area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC), and accuracy in the test set were 0.947 (95% confidence interval [CI]: 0.927-0.968), 0.964 (95% CI: 0.930- 0.978), and 90.8 (95% CI: 88.0-93.0), respectively. With the average probabilities from multiple samples per patient, good performance was also achieved at the patient level, with AUROC, AUPRC, and accuracy of 0.930 (95% CI: 0.828-1.000), 0.941 (95% CI: 0.792-1.000), and 93.6% (95% CI: 79.3-98.2) in the test set, respectively. Discussion: The deep learning-based hybridmodel demonstrated the potential to be a good tool for the operative and non-invasive prediction of MI in GIST patients. [ABSTRACT FROM AUTHOR]

Background: Rapid serial visual presentation (RSVP) has become a popular target detection method by decoding electroencephalography (EEG) signals, owing to its sensitivity and effectiveness. Most current research on EEG-based RSVP tasks focused on feature extraction algorithms developed to deal with the non-stationarity and low signal-to-noise ratio (SNR) of EEG signals. However, these algorithms cannot handle the problem of no eventrelated potentials (ERP) component or miniature ERP components caused by the attention lapses of human vision in abnormal conditions. The fusion of human-computer vision can obtain complementary information, making it a promising way to become an efficient and general way to detect objects, especially in attention lapses. Methods: Dynamic probability integration (DPI) was proposed in this study to fuse human vision and computer vision. A novel basic probability assignment (BPA) method was included, which can fully consider the classification capabilities of different heterogeneous information sources for targets and non-targets and constructs the detection performance model for the weight generation based on classification capabilities. Furthermore, a spatial-temporal hybrid common spatial pattern-principal component analysis (STHCP) algorithm was designed to decode EEG signals in the RSVP task. It is a simple and effective method of distinguishing target and non-target using spatial-temporal features. Results: A nighttime vehicle detection based on the RSVP task was performed to evaluate the performance of DPI and STHCP, which is one of the conditions of attention lapses because of its decrease in visual information. The average AUC of DPI was 0.912 ± 0.041 and increased by 11.5, 5.2, 3.4, and 1.7% compared with human vision, computer vision, naive Bayesian fusion, and dynamic belief fusion (DBF), respectively. A higher average balanced accuracy of 0.845 ± 0.052 was also achieved using DPI, representing that DPI has the balanced detection capacity of target and non-target. Moreover, STHCP obtained the highest AUC of 0.818 ± 0.06 compared with the other two baseline methods and increased by 15.4 and 23.4%. Conclusion: Experimental results indicated that the average AUC and balanced accuracy of the proposed fusion method were higher than individual detection methods used for fusion, as well as two excellent fusion methods. It is a promising way to improve detection performance in RSVP tasks, even in abnormal conditions. [ABSTRACT FROM AUTHOR]

Background: Diabetic cardiomyopathy (DCM), a fatal cardiovascular complication of diabetes mellitus, often leads to progressive heart failure, however its pathogenesis remains unclear. Corin, a cardiac serine protease, is responsible for converting pro-atrial natriuretic peptide (pro-ANP) to biologically active atrial natriuretic peptide (ANP). It has been well established that corin deficiency is associated with the progression of hypertension, cardiac hypertrophy and heart failure. However, because the involvement of corin-mediated pro-ANP processing in DCM has not been clarified, this study aims to investigate the role of corin in the pathogenesis of DCM. Methods: Diabetes mellitus was induced by a single intraperitoneal injection of streptozotocin (STZ 65 mg/kg) to Sprague-Dawley rats (180-220 g). DCM was confirmed by monitoring continuously transthoracic echocardiography every 4 weeks and hemodynamic measurements at 20 weeks. Myocardial disorder and fibrosis were detected by HE staining and Masson's trichrome staining. The mRNA and protein levels of corin and ANP in rat hearts and cardiomyocytes were determined by quantitative real-time PCR, western blotting and immunohistochemical staining, respectively. H9c2 cardiomyoblasts proliferation was detected by MTT colorimetric assay and viable cell counting with trypan blue. The effect of Corin-siRNA H9c2 cardiomyoblasts on EA.hy926 cells migration was measured by the wound healing scratch assay. Results: The corin and ANP expression in mRNA and protein levels was decreased in DCM rat hearts. Corin and ANP levels of neonatal rat cardiomyocytes and H9c2 cardiomyoblasts treated with high glucose were significantly lower than that of normal glucose treated. Precisely, corin and ANP levels decreased in DCM rats at 12, 16, 20 and 33 weeks; neonatal cardiomyocytes and H9c2 cardiomyoblasts treated with high glucose at 36, 48 and 60 h demonstrated significant reduction in corin and ANP levels. Corin-siRNA H9c2 cardiomyoblasts showed decreased proliferation. Culture supernatants of Corin-siRNA H9c2 cardiomyoblasts prevented endothelial cell line EA.hy926 migration in the wound healing scratch assay. Furthermore, iso-lectin expression in arteriole and capillary endothelium was down-regulated in DCM rats. Conclusions: Our results indicate that corin plays an important role in cardioprotection by activating pro-atrial natriuretic peptide pathway in DCM. Corin deficiency leads to endothelial dysfunction and vascular remodeling. [ABSTRACT FROM AUTHOR]