Screening and identification of dietary oils and unsaturated fatty acids in inhibiting inflammatory prostaglandin E

ABSTRACT: BACKGROUND: The molecular mechanisms of dietary oils (such as fish oil) and unsaturated fatty acids, which are widely used by the public for anti-inflammation and vascular protection, have not been settled yet. In this study, prostaglandin E2 (PGE2)-mediated calcium signaling was used to screen dietary oils and eight unsaturated fatty acids for identification of their anti-inflammatory mechanisms. Isolated fat/stromal cells expressing endogenous PGE2 receptors and an HEK293 cell line specifically expressing the recombinant human PGE2 receptor subtype-1 (EP1) were cultured and used in live cell calcium signaling assays. The different dietary oils and unsaturated fatty acids were used to affect cell signaling under the specific stimulation of a pathological amount of inflammatory PGE2. RESULTS: It was identified that fish oil best inhibited the PGE2 signaling in the primary cultured stromal cells. Second, docosahexaenoic acid (DHA), found in abundance in fish oil, was identified as a key factor of inhibition of PGE2 signaling. Eicosapentaenoic acid (EPA), another major fatty acid found in fish oil and tested in this study was found to have small effect on EP1 signaling. The study suggested one of the four PGE2 subtype receptors, EP1 as the key target for the fish oil and DHA target. These findings were further confirmed by using the recombinant EP1 expressed in HEK293 cells as a target. CONCLUSION: This study demonstrated the new mechanism behind the positive effects of dietary fish oils in inhibiting inflammation originates from the rich concentration of DHA, which can directly inhibit the inflammatory EP1-mediated PGE2 receptor signaling, and that the inflammatory response stimulated by PGE2 in the fat stromal cells, which directly related to metabolic diseases, could be down regulated by fish oil and DHA. These findings also provided direct evidence to support the use of dietary oils and unsaturated fatty acids for protection against heart disease, pain, and cancer resulted from inflammatory PGE2.     

Non-Mass Breast Lesions on Ultrasound: Feature Exploration and Multimode Ultrasonic Diagnosis

The aim of this study was to analyze the features of non-mass breast lesions (NMLs) on B-mode ultrasound (US), color Doppler US, strain elastography (SE) and contrast-enhanced ultrasound (CEUS) and to develop a multimode ultrasonic method for NML differentiation. Seventy-one NMLs were included in this retrospective study. Binary logistic regression was used to identify the independent risk factors. Pathology results were used as the standard criterion. Microcalcification on US, high stiffness on SE and hyper-enhanced intensity on CEUS were identified as features correlated with malignancy. A multimode method to evaluate NMLs based on the logistic regression was developed. The sensitivity and specificity for US, US?+?Doppler, US?+?SE, US?+?CEUS and the multimode method were 100% and 29%, 92.5% and 41.9%, 97.5% and 58.1%, 90.0% and 58.1% and 95.0% and 77.4%, respectively. The accuracy of these methods was 69.0%, 70.4%, 80.2%, 76.1% and 87.3%, respectively. The multimode ultrasonic method is simple and exhibited high diagnostic performance, which might be helpful for predicting the potential malignancy of NMLs.     

Discovery of structure-based small molecular inhibitor of αB-crystallin against basal-like/triple-negative breast cancer development in vitro and in vivo

αB-crystallin (CRYAB) is present at a high frequency in poor prognosis basal-like breast tumours, which are largely absent of oestrogen, progesterone receptors and HER2 known as triple-negative breast cancer (TNBC). CRYAB functions as a molecular chaperone to bind to and correct intracellular misfolded/unfolded proteins such as vascular endothelial growth factor (VEGF), preventing non-specific protein aggregations under the influence of the tumour microenvironment stress and/or anti-cancer treatments including bevacizumab therapy. Directly targeting CRYAB can sensitize tumour cells to chemotherapeutic agents and decrease tumour aggressiveness. However, growing evidence shows that CRYAB is a critical adaptive response element after ischemic heart disease and stroke, implying that directly targeting CRYAB might cause serious unwanted side effects. Here, we used structure-based molecular docking of CRYAB and identified a potent small molecular inhibitor, NCI-41356, which can strongly block the interaction between CRYAB and VEGF₁₆₅ without affecting CRYAB levels. The disruption of the interaction between CRYAB and VEGF₁₆₅ elicits in vitro anti-tumour cell proliferation and invasive effects through the down-regulation of VEGF signalling in the breast cancer cells. The observed in vitro anti-tumour angiogenesis of endothelial cells might be attributed to the down-regulation of paracrine VEGF signalling in the breast cancer cells after treatment with NCI-41356. Intraperitoneal injection of NCI-41356 greatly inhibits the tumour growth and vasculature development in in vivo human breast cancer xenograft models. Our findings provide ‘proof-of-concept’ for the development of highly specific structure-based alternative targeted therapy for the prevention and/or treatment of TNBC.     

Deep learning applied to two-dimensional color Doppler flow imaging ultrasound images significantly improves diagnostic performance in the classification of breast masses: a multicenter study

BackgroundThe current deep learning diagnosis of breast masses is mainly reflected by the diagnosis of benign and malignant lesions. In China, breast masses are divided into four categories according to the treatment method: inflammatory masses, adenosis, benign tumors, and malignant tumors. These categorizations are important for guiding clinical treatment. In this study, we aimed to develop a convolutional neural network (CNN) for classification of these four breast mass types using ultrasound (US) images.MethodsTaking breast biopsy or pathological examinations as the reference standard, CNNs were used to establish models for the four-way classification of 3623 breast cancer patients from 13 centers. The patients were randomly divided into training and test groups (n = 1810 vs. n = 1813). Separate models were created for two-dimensional (2D) images only, 2D and color Doppler flow imaging (2D-CDFI), and 2D-CDFI and pulsed wave Doppler (2D-CDFI-PW) images. The performance of these three models was compared using sensitivity, specificity, area under receiver operating characteristic curve (AUC), positive (PPV) and negative predictive values (NPV), positive (LR+) and negative likelihood ratios (LR−), and the performance of the 2D model was further compared between masses of different sizes with above statistical indicators, between images from different hospitals with AUC, and with the performance of 37 radiologists.ResultsThe accuracies of the 2D, 2D-CDFI, and 2D-CDFI-PW models on the test set were 87.9%, 89.2%, and 88.7%, respectively. The AUCs for classification of benign tumors, malignant tumors, inflammatory masses, and adenosis were 0.90, 0.91, 0.90, and 0.89, respectively (95% confidence intervals [CIs], 0.87–0.91, 0.89–0.92, 0.87–0.91, and 0.86–0.90). The 2D-CDFI model showed better accuracy (89.2%) on the test set than the 2D (87.9%) and 2D-CDFI-PW (88.7%) models. The 2D model showed accuracy of 81.7% on breast masses ≤1 cm and 82.3% on breast masses >1 cm; there was a significant difference between the two groups (P < 0.001). The accuracy of the CNN classifications for the test set (89.2%) was significantly higher than that of all the radiologists (30%).ConclusionsThe CNN may have high accuracy for classification of US images of breast masses and perform significantly better than human radiologists.Trial registrationChictr.org, ChiCTR1900021375; http://www.chictr.org.cn/showproj.aspx?proj=33139.     

双镜联合胆总管探查切开取石术治疗胆石症引起的急性胆源性胰腺炎68例疗效观察

[目的]探讨腹腔镜联合胆道镜胆总管探查切开取石术（laparoscopic common bile duct exploration,LCBDE）治疗胆石症引起的急性胆源性胰腺炎（acute biliary pancreatitis,ABP）的临床效果。[方法]选择我院行LCBDE的68例胆石症引起的ABP患者为实验组,同期行开腹胆总管切开取石T管引流术（open choledocholithotomy T-tube drainage,OCTD）的87例胆石症引起的ABP患者为对照组。比较两组手术时间、术后恢复情况、取石结果及并发症情况。[结果]实验组68例均成功完成LCBDE,无中转开腹;取净胆管内结石61例,T管拔除为术后4周;残余结石7例于术后6周经T管窦道胆道镜再次取残余结石。对照组87例行OCTD成功79例,失败8例6周后经胆道镜取尽石;OCTD术中取净结石者71例,T管拔除为术后6周,未取尽者于术后6周经T管窦道胆道镜再次取尽残余结石。两组在术后恢复、并发症发生方面,实验组优于对照组（P〈0.05,P〈0.01）。[结论]LCBDE一期治疗胆石症引起的ABP安全可行,创伤小,恢复快,疗效好。     

广义模糊DEA模型在区域医疗资源优化配置中的应用

目的  通过建立公立医院合作决策模型，实现在任选决策单元中选择最佳合作伙伴，提升医疗资源利用效率，推动区域内医疗资源最佳配置。方法  在传统数据包络分析（data envelopment analysis，DEA）模型的基础上，构建对模糊指标和任选决策单元具有更好适用性的广义模糊DEA合作决策模型，通过输入职工总数、病床数、年门急诊量、出院人数、总收入、医院等级评价等指标信息，计算出某一区域内不同医院的合作效率区间，从而实现在任选决策单元中科学选择最佳合作伙伴。结果  以河南省某地区10所医院为例进行分析验证可知，广义模糊DEA模型对该区域内公立医院之间的合作决策具有很好的效果，可有效为区域内任一医院选择最佳合作伙伴。结论  与传统DEA方法相比，广义模糊DEA方法更具灵活性，能较好地评价复杂模型，可以对任选决策单元中的个体实现最优合作决策选择，为实现区域医疗资源优化配置提供决策支撑。