Vitexin suppresses the proliferation, angiogenesis and stemness of endometrial cancer through the PI3K/AKT pathway.

CONTEXT: Endometrial cancer is a common gynecologic malignancy. Vitexin is an active flavonoid compound with an antitumor function. OBJECTIVE: This study elucidated the role of vitexin in endometrial cancer development and clarified the potential mechanism. MATERIALS AND METHODS: The toxicity of vitexin (0-80 µM) treatment for 24 h on HEC-1B and Ishikawa cells was tested utilizing the CCK-8 assay. Endometrial cancer cells were divided into vitexin 0, 5, 10, and 20 µM groups. Cell proliferation, angiogenesis and stemness in vitro after treatment with vitexin (0, 5, 10, 20 µM) for 24 h were evaluated using the EdU staining assay, tube formation assay and sphere formation assay, respectively. Twelve BALB/c mice were grouped into control and vitexin (80 mg/kg) groups to monitor tumour growth for 30 days. RESULTS: Vitexin suppressed cell viability of HEC-1B (IC50 = 9.89 µM) and Ishikawa (IC50 = 12.35 µM) cells. The proliferation (55.3% and 80% for HEC-1B; 44.7% and 75% for Ishikawa), angiogenesis (54.3% and 78.4% for HEC-1B; 47.1% and 68.2% for Ishikawa) and stemness capacity (57.2% and 87.3% for HEC-1B; 53.4% and 78.4% for Ishikawa) of endometrial cancer cells were inhibited by 10 and 20 µM vitexin. Furthermore, the inhibitory effects of vitexin on endometrial cancer were reversed by PI3K/AKT agonist 740Y-P (20 µM). Moreover, the xenograft tumour experiment lasting for 30 days proved that vitexin (80 mg/kg) blocked tumour growth of endometrial cancer in vivo. DISCUSSION AND CONCLUSIONS: Vitexin has therapeutic potential on endometrial cancer, which supports further clinical trials.

Aptamer-functionalised metal-organic frameworks as an 'on-off-on' fluorescent sensor for bisphenol S detection.

Bisphenol S (BPS) is an industrial chemical that is widely used to manufacture daily items, such as plastic water bottles, milk bottles, water cups, and paper products. BPS is a biologically toxic environmental endocrine disruptor. Long-term exposure to BPS can disrupt the reproductive system, endanger health, and increase the risk of cancer. The metal-organic framework UiO-66 is characterised with high thermal and chemical stability, a simple synthetic route, and low preparation cost. In this study, we modified UiO-66 with nucleic acid aptamers to prepare an 'on-off-on' fluorescent sensor for the simple and rapid detection of BPS. The FAM-labelled aptamer was selected as the fluorescent probe (i.e. 'on'). In the presence of UiO-66, the FAM-labelled aptamer adsorbed onto the surface of the UiO-66 material, and the fluorescence of FAM was quenched by photoinduced electron transfer (i.e. 'off'). When BPS was introduced into the system, the configuration of the FAM-labelled aptamer changed after binding to BPS, and the adsorption of FAM on UiO-66 weakened, resulting in fluorescence recovery (i.e. 'on'). Based on this principle, the reaction system was optimised, and the BPS content was analysed according to the change in the fluorescence signal. The signals changed linearly in the BPS concentration range of 2.0 × 10-4-4.0 × 10-2 mmol L-1, and the system had a detection limit of 1.84 × 10-4 mmol L-1. The sensor was successfully used to detect the BPS content in commercial plastic bottled water.

Sensitive fluorescent biosensor based on a europium-based metal-organic framework for protein kinase activity analysis.

Protein kinases play crucial regulatory roles in the physiological activities in the human body. Understanding protein kinase activity and its inhibition is essential for the management of human diseases. Considering the limitations of the existing protein kinase-related analysis methods, the aim of the present study was to develop a fluorescent biosensor based on Eu(BTC) (H2O)6 (BTC = 1,3,5-Benzenetricarboxylic acid) for evaluating protein kinase activity and the relevant inhibitors. A fluorophore-labelled substrate polypeptide was phosphorylated under the catalysis of protein kinase. This phosphorylated peptide can be coordinated explicitly with the europium site of Eu(BTC) (H2O)6 to detect the protein kinase. The developed biosensor performed well, with a detection limit of 0.00003 U µL-1, and it showed good selectivity and universality. Protein kinase activity could also be detected in MCF-7 cells using this method. Furthermore, in terms of inhibitor screening using the Eu(BTC) (H2O)6-based sensor, both H-89 and ellagic acid were found to inhibit protein kinase activity with IC50 values of 1.09 and 19.88 nmol L-1, respectively. Overall, this biosensor has broad application prospects in monitoring and controlling protein kinase activity.

Correlations of Computed Tomography Measurement of Distal Pulmonary Vascular Pruning with Airflow Limitation and Emphysema in COPD Patients.

Background: Pulmonary vascular alteration is an important feature of chronic obstructive pulmonary disease (COPD), which is characterized by distal pulmonary vascular pruning in angiography. We aimed to further investigate the clinical relevance of pulmonary vasculature in COPD patients using non-contrast computed tomography (CT). Methods: Seventy-one control subjects and 216 COPD patients completed the questionnaires, spirometry, and computed tomography (CT) scans within 1 month and were included in the study. Small pulmonary vessels represented by percentage of cross-sectional area of pulmonary vessels smaller than 5 mm2 or 5-10 mm2 to the total lung fields (%CSA<5 or %CSA5-10, respectively) were measured using ImageJ software. Spearman correlation was used to investigate the relationship between %CSA<5 and airflow limitation. A receiver operating characteristic (ROC) curve was built to evaluate the value of %CSA<5 in discriminating COPD patients from healthy control subjects. Segmented regression was used to analyze the relationship between %CSA<5 and %LAA-950 (percentage of low-attenuation areas less than -950 HU). Results: We found a significant correlation between %CSA<5 and forced expiratory volume in one second (FEV1) percentage of predicted value (%pred) (r = 0.564, P < 0.001). The area under the ROC curve for the value of %CSA<5 in distinguishing COPD was 0.816, with a cut-off value of 0.537 (Youden index J, 0.501; sensitivity, 78.24%; specificity, 71.83%). Since the relationship between %CSA<5 and %LAA-950 was not constant, performance of segmented regression was better than ordinary linear regression (adjusted R2, 0.474 vs 0.332, P < 0.001 and P < 0.001, respectively). As %CSA<5 decreased, %LAA-950 slightly increased until an inflection point (%CSA<5 = 0.524) was reached, after which the %LAA-950 increased apparently with a decrease in %CSA<5. Conclusion: %CSA<5 was significantly correlated with both airflow limitation and emphysema, and we identified an inflection point for the relationship between %CSA<5 and %LAA-950.

Pattern classification for breast lesion on FFDM by integration of radiomics and deep features.

The radiomics model can be used in breast cancer detection via calculating quantitative image features. However, these features are explicitly designed, or handcrafted in advance, and this would limit their ability to characterize the lesion properly. This paper aims to build an integrated-features-based classification framework which cooperate the radiomics features and the deep features to classify benign and malignant breast lesions on full-filed digital mammography (FFDM). We propose a classification framework consists of three steps: (1) handcrafted features (HCFs) extraction and selection, (2) deep features (DFs) extraction and (3) the integrated features-based classification. Specifically, HCFs comprise the gray-level gap-length matrix (GLGLM) texture features and shape features, and DFs contain the pooled features and high-level fully-connected features. Then, a multi-classifier method is applied to construct our classification framework using integrated features for breast lesion classification. A total of 106 retrospective FFDM data (51 are malignant and 55 are benign) in both craniocaudal (CC) view and mediolateral oblique (MLO) view were included in this study. The areas under a receiver operating characteristic curve (AUC) value, accuracy, sensitivity, specificity and Youden's index, are used to examine the performance of our proposed method in differentiating benign and malignant breast lesion. Proposed framework trained on the concatenation of fully-connected features and HCFs can significantly improve classification performance (AUC of 94.6 %, accuracy of 96.4 %, sensitivity of 93.6 %, specificity of 98.9 % and Yonden's index of 92.5 %) compared with other features sets. Experimental results demonstrate that performance of proposed framework is improved, indicating the potential of concatenation of the fully-connected features and HCFs set in breast cancer patients.

Enhanced biosynthetic gene expressions and production of ganoderic acids in static liquid culture of Ganoderma lucidum under phenobarbital induction.

Static liquid culture of Ganoderma lucidum, a traditional Chinese medicinal mushroom, is a proven technology for producing ganoderic acids, which are secondary metabolites that possess antitumor properties. In this work, the addition of phenobarbital, a P450 inducer, was used to enhance the production of total and individual ganoderic acids in a two-stage cultivation involving a period of initial shake flask culture followed by static liquid culture of G. lucidum. The dosage and time of phenobarbital induction were critical for the enhanced production of ganoderic acids. The addition of 100 muM (final concentration) phenobarbital on day 5 after the shake flask culture was converted to the static liquid culture was found to be optimal, resulting in a maximal amount of total ganoderic acids of 41.4 +/- 0.6 mg/g cell dry weight and increases in the levels of ganoderic acid-Mk, -T, -S, and -Me in the treated cells by 47%, 28%, 36%, and 64%, respectively. Meanwhile, the accumulation of lanosterol, a key intermediate, was found to decrease and transcriptions of three key genes encoding 3-hydroxy-3-methylglutaryl coenzyme A reductase, squalene synthase, and lanosterol synthase in the triterpene biosynthetic pathway were up-regulated under phenobarbital induction. This work demonstrated a useful strategy for the enhanced production of ganoderic acids by G. lucidum.

[Establishment of a deep feature-based classification model for distinguishing benign and malignant breast tumors on full-filed digital mammography].

OBJECTIVE: To develop a deep features-based model to classify benign and malignant breast lesions on full- filed digital mammography. METHODS: The data of full-filed digital mammography in both craniocaudal view and mediolateral oblique view from 106 patients with breast neoplasms were analyzed. Twenty-three handcrafted features (HCF) were extracted from the images of the breast tumors and a suitable feature set of HCF was selected using t-test. The deep features (DF) were extracted from the 3 pre-trained deep learning models, namely AlexNet, VGG16 and GoogLeNet. With abundant breast tumor information from the craniocaudal view and mediolateral oblique view, we combined the two extracted features (DF and HCF) as the two-view features. A multi-classifier model was finally constructed based on the combined HCF and DF sets. The classification ability of different deep learning networks was evaluated. RESULTS: Quantitative evaluation results showed that the proposed HCF+DF model outperformed HCF model, and AlexNet produced the best performances among the 3 deep learning models. CONCLUSIONS: The proposed model that combines DF and HCF sets of breast tumors can effectively distinguish benign and malignant breast lesions on full-filed digital mammography.

A computer-aided diagnosis scheme of breast lesion classification using GLGLM and shape features: Combined-view and multi-classifiers.

PURPOSE: To address high false-positive results of FFDM issue, we make the first effort to develop a computer-aided diagnosis (CAD) scheme to analyze and distinguish breast lesions. METHOD: The breast lesion regions were first segmented and depicted on FFDM images from 106 patients. In this work, 11 gray-level gap-length matrix texture features and 12 shape features were extracted form craniocaudal view and mediolateral oblique view, and then Student's t-test, Fisher-score and Relief-F were introduced to select features. We also investigated the effect of three factors, i.e., discretisation, selection methods and classifier methods, of the classification performance via analysis of variance. Finally, a classification model was constructed. Spearman's correlation coefficient analysis was conducted to assess the internal relevance of features. RESULTS: The proposed scheme using Student's t-test achieved an area under the receiver operating characteristic curve (AUC) value of 0.923 at 512 bins. The AUC values are 0.884, 0.867, 0.874 and 0.901 for the low gray-level gaps emphasis (LGGE), solidity, extent, and the combined set, respectively. Solidity and extent depicts the correlation coefficient of 0.86 (P < 0.05). CONCLUSIONS: We present a new CAD scheme based on the contribution of the significant factors. The experimental results demonstrate that the presented scheme can be used to successfully distinguish breast carcinoma lesions and benign fibroadenoma lesions in our FFDM dataset and the MIAS dataset, which may provide a CAD method to assist radiologists in diagnosing and interpreting screening mammograms. Moreover, we found that LGGE, solidity and extent features show great potential for breast lesion classification.