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。     

经腹腹腔镜下右肾周筋膜解剖研究及其在腹腔镜右肾切除中应用价值

目的通过研究经腹途径腹腔镜下右肾肾周筋膜的分层结构,为腹腔镜筋膜入路右肾切除手术的可行性及安全性提供解剖学依据。方法在国内外学者对肾周筋膜研究的基础上结合CT肾周筋膜的呈现,对经腹途径腹腔镜下肾周筋膜分层结构进行研究,并以此为基础设计好手术的筋膜入路及分离途径并应用于指导经腹腹腔镜下右肾切除术,记录2015年1月至2019年6月来自阳江市中医医院和人民医院的45例患者的术中肾周筋膜观察结果及手术时间、出血及术中术后并发症等。结果经腹途径腹腔镜下肾周间隙周围存在一个潜在连续的由疏松纤维条索填充的无血管层面,这个无血管层面存在于相邻的两层肾周筋膜之间,45例患者均按术前设计的手术路径顺利完成手术,其中42例患者可以很好或较好的保持筋膜完整性的情况下完成分离,2例脓肾患者及1例无功能肾患者由于粘连明显未能保持分离面筋膜完整性,平均手术时间73 min,平均出血50 ml,术后引流管时间2.7 d,术中无肠管及下腔静脉损伤病例,术后无肠漏及严重的继发出血病例,无围手术期死亡病例。结论肾周筋膜的分层结构及肾周间隙周围存在的连续的潜在无血管层面为经腹途径腹腔镜筋膜入路右肾切除有效的解剖依据,经腹腹腔镜下筋膜入路右肾切除是安全可行的,可以让手术更加安全及出血更少。     

The Protective Effects of Up-Regulating Prostacyclin Biosynthesis on Neuron Survival in Hippocampus

Cellular arachidonic acid (AA), an unsaturated fatty acid found ubiquitously in plasma membranes, is metabolized to different prostanoids, such as prostacyclin (PGI₂) and prostaglandin E₂ (PGE₂), by the three-step reactions coupling the upstream cyclooxygenase (COX) isoforms (COX-1 and COX-2) with the corresponding individual downstream synthases. While the vascular actions of these prostanoids are well-characterized, their specific roles in the hippocampus, a major brain area for memory, are poorly understood. The major obstacle for its understanding in the brain was to mimic the biosynthesis of each prostanoid. To solve the problem, we utilized Single-Chain Hybrid Enzyme Complexes (SCHECs), which could successfully control cellular AA metabolites to the desired PGI₂ or PGE₂. Our in vitro studies suggested that neurons with higher PGI₂ content and lower PGE₂ content exhibited survival protection and resistance to Amyloid-β-induced neurotoxicity. Further extending to an in vivo model, the hybrid of PGI₂-producing transgenic mice and Alzheimer’s disease (AD) mice showed restored long-term memory. These findings suggested that the vascular prostanoids, PGI₂ and PGE₂, exerted significant regulatory influences on neuronal protection (by PGI₂), or damage (by PGE₂) in the hippocampus, and raised a concern that the wide uses of aspirin in cardiovascular diseases may exert negative impacts on neurodegenerative protection.

Our study intended to understand the crosstalk of prostanoids in the hippocampus, a major brain area impacted in AD, by using hybrid enzymes to redirect the synthesis of prostanoids to PGE₂ and PGI₂, respectively. Our data indicated that during inflammation, the vascular mediators, PGI₂ and PGE₂, exerted significant regulatory influences on neuronal protection (by PGI₂), or damage (by PGE₂) in the hippocampus. These findings also raised a concern that the widely uses of non-steroidal anti-inflammatory drugs in cardiovascular diseases may exert negative impacts on neurodegenerative protection.

     

Warthin’s tumour in oral and maxillofacial regions: an 18-year retrospective study of 1084 cases in an eastern-Chinese population

There is little information in the English-language literature regarding Warthin’s tumour (WT) in the eastern-Chinese population. A large retrospective study (1084 primary tumours over a period of 18 years) was carried out to investigate the clinicopathological features (patients’ gender, age and tumour location) of these tumours in this population. A total of 994 (91.7%) patients were male and 90 (8.3%) were female, with a male/female ratio of 11:1. The mean age was 56.48 years (range 20–89 years), with a peak incidence in the fifth to seventh decade (82.1%). The favorite primary site of the tumour was the parotid gland (n = 1055), followed by intra-/peri-parotid lymph nodes (n = 13), upper neck (n = 10), submandibular gland (n = 4) and upper lip (n = 1). Multifocal WTs arose in 9.5% (103 patients) of cases whereas bilateral multifocal WTs were found in 0.65% (seven patients). In 24 (2.2%) patients, WT were found to coexist with other different types of neoplasm synchronously. The most common subtype of metaplasia was the squamous metaplasia (166/250, 66.4%). The usual treatment measure is (bilateral) superficial parotidectomy and the patients should be followed long term, in view of possible metachronous WT, even after prolonged time intervals.