nab-Paclitaxel-based induction chemotherapy followed by cisplatin and radiation therapy for human papillomavirus-unrelated head and neck squamous-cell carcinoma

Ovarian cancer is one of the most lethal gynecological cancers; owning to its late detection and chemoresistance, understanding the pathogenesis of this malignant tumor is much critical. Previous studies have reported that ubiquitin-specific peptidase 39 (USP39) is generally overexpressed in a variety of cancers, including hepatocellular carcinoma, gastric cancer and so forth. Furthermore, USP39 is proved to be associated with the proliferation of malignant tumors. However, the function and mechanism of USP39 in ovarian cancer have not been elucidated. In the present study, we observed that USP39 was frequently overexpressed in human ovarian cancer and was highly correlated with TNM stage. Suppression of USP39 markedly inhibited the growth and migration of ovarian cancer cell lines HO-8910 and SKOV3 and induced cell cycle G2/M arrest. Moreover, knockdown of USP39 inhibited ovarian tumor growth in a xenograft model. In addition, our findings indicated that cell cycle arrest induced by USP39 knockdown might be involved in p53/p21 signaling pathway. Furthermore, we found that the depletion of USP39 inhibited the migration of ovarian cancer cells via blocking epithelial–mesenchymal transition. Taken together, these results suggest that USP39 may play vital roles in the genesis and progression and may serve as a potential biomarker for diagnosis and therapeutic target of ovarian cancer.

     

基于二氧化硅纳米粒子的抗肿瘤药物递送系统研究进展CSCD

近年来癌症治疗受到广泛关注,二氧化硅纳米颗粒因其独特的理化性质在肿瘤诊疗领域展现巨大潜力。基于二氧化硅纳米粒子的药物输送系统可被动或主动靶向肿瘤组织,并通过刺激响应的方式实现药物在肿瘤部位的可控释放,有效提高抗肿瘤药物在肿瘤部位的浓度,提高治疗效率。同时,二氧化硅纳米粒子通过负载造影剂可实现生物成像功能,用于肿瘤组织定位及药物追踪,实现更高效的抗肿瘤治疗。本文介绍了二氧化硅纳米粒子的制备方式,并对二氧化硅纳米粒子在药物靶向递送系统及生物成像领域中的研究进展进行综述。     

“一带一路”倡议背景下中医药文化传播传承的建议与策略

"一带一路"中医药发展工作办公室强调了九个方面的重点工作,其中包括推进中医药文化传播。更好地传播和传承中医药文化势在必行。坚持古为今用、洋为中用,不断推陈出新,提倡多模式传播传承中医药文化,彰显中医药文化的活力和魅力,更好地发展中医药,从而提高国家软实力。     

替考拉宁在中国成人患者中的群体药动学研究

目的建立中国成年患者的替考拉宁(teicoplanin,TEC)群体药动学(population pharmacokinetics,PPK)模型,考察TEC药动学参数的影响因素。方法前瞻性收集139例革兰阳性球菌感染患者静脉注射TEC后的222份常规监测血药浓度和相关信息,采用一级消除的一室模型进行数据拟合,并应用非线性混合效应模型(nonlinear mixed effect model,NONMEM)程序建立PPK模型。采用Bootstrap、正态预测分布误差法(normalized predictive distribution error,NPDE)进行最终模型评价。利用蒙特卡洛模拟法对给药方案进行优化。结果确定了肌酐清除率(creatinine clearance,CLcr)、白蛋白(albumin,ALB)为影响TEC清除率的主要因素。最终模型为:CL(L·h^-1)=1.24×(CLcr/77)0.564×31/ALB;V(L)=69.2。验证表明,模型稳定、有效,且有较好的预测效能。对于不同ALB和CLcr的多数患者起始负荷剂量400 mg/q12h,iv,3次,维持剂量400~800 mg·d^-1的给药方案可达有效治疗谷浓度。严重感染者需调整负荷剂量至800 mg/q12h,iv,3次,维持剂量400~800 mg·d^-1的给药方案来确保血药浓度达到15 mg·L^-1以上。结论本实验报道了CLcr、ALB对TEC清除率有显著影响,所建模型对TEC在中国成人患者中实现个体化给药具有重要应用价值。     

“一带一路”倡议布局下培养高等中医药专业人才的对策

培养中医药创新人才是实现中医药传承和国际化的重要条件。但目前中医药专业人才短缺,尤其紧缺精通中医药翻译和国际贸易服务的人才。因此,在"一带一路"倡议指导下,高等中医药院校应积极合理地开设课程,选择教材,建立科学合理的教学模式,完善考试制度,从而更好地培养中医药人才。     

Vitamin A deficiency exacerbates autism-like behaviors and abnormalities of the enteric nervous system in a valproic acid-induced rat model of autism

The manifestations of autism spectrum disorder (ASD) are highly heterogeneous. As many individuals with ASD have gastrointestinal (GI) comorbidities, ASD with GI problems is considered to be a subtype of ASD. Vitamin A (VA) plays an important role in the development of both the central and peripheral nervous system. However, the relationship between VA deficiency (VAD) and ASD with GI comorbidities is still unclear. We established rat models with different VA levels based on the valproic acid-induced autism model. Compared to autism model rats with VA normal (VAN), autism model rats with gestational VAD showed more severe autism-like behavior, increased GI transit time, and impairment of the enteric nervous system (ENS). Besides, the expression levels of retinoic acid receptor α (RARα) and Ret in autism model rats with VAD were decreased compared with those in rats with VAN. Supplementation with VA was found to effectively ameliorate autism-like behaviors and impairments of GI motility and the ENS in autism model rats with VAD. Chromatin immunoprecipitation results suggested that RARa can bind to the promoter region of the Ret gene and regulate the Ret signaling pathway. We speculate that VAD in autism might lead to impairments of both the brain and ENS. VAD might be a factor that causes individuals to be more susceptible to ASD-related risk factors and aggravates a subtype of ASD with GI comorbidities.     

类风湿关节炎合并骨折患者的围手术期处理

类风湿关节炎好发于中老年人，其病情复杂、合并症多，一旦发生骨折则围手术期处理难度大且风险较高。本文就类风湿关节炎患者骨折围手术期评估、围手术期用药管理及骨折的预防进行综述，以期减少此类患者围手术期风险，保障医疗安全。     

A novel incremental simulation of facial changes following orthognathic surgery using FEM with realistic lip sliding effect

Accurate prediction of facial soft-tissue changes following orthognathic surgery is crucial for surgical outcome improvement. We developed a novel incremental simulation approach using finite element method (FEM) with a realistic lip sliding effect to improve the prediction accuracy in the lip region.First, a lip-detailed mesh is generated based on accurately digitized lip surface points. Second, an improved facial soft-tissue change simulation method is developed by applying a lip sliding effect along with the mucosa sliding effect. Finally, the orthognathic surgery initiated soft-tissue change is simulated incrementally to facilitate a natural transition of the facial change and improve the effectiveness of the sliding effects.Our method was quantitatively validated using 35 retrospective clinical data sets by comparing it to the traditional FEM simulation method and the FEM simulation method with mucosa sliding effect only. The surface deviation error of our method showed significant improvement in the upper and lower lips over the other two prior methods. In addition, the evaluation results using our lip-shape analysis, which reflects clinician's qualitative evaluation, also proved significant improvement of the lip prediction accuracy of our method for the lower lip and both upper and lower lips as a whole compared to the other two methods.In conclusion, the prediction accuracy in the clinically critical region, i.e., the lips, significantly improved after applying incremental simulation with realistic lip sliding effect compared with the FEM simulation methods without the lip sliding effect.     

A deep joint sparse non-negative matrix factorization framework for identifying the common and subject-specific functional units of tongue motion during speech

Intelligible speech is produced by creating varying internal local muscle groupings—i.e., functional units—that are generated in a systematic and coordinated manner. There are two major challenges in characterizing and analyzing functional units. First, due to the complex and convoluted nature of tongue structure and function, it is of great importance to develop a method that can accurately decode complex muscle coordination patterns during speech. Second, it is challenging to keep identified functional units across subjects comparable due to their substantial variability. In this work, to address these challenges, we develop a new deep learning framework to identify common and subject-specific functional units of tongue motion during speech. Our framework hinges on joint deep graph-regularized sparse non-negative matrix factorization (NMF) using motion quantities derived from displacements by tagged Magnetic Resonance Imaging. More specifically, we transform NMF with sparse and graph regularizations into modular architectures akin to deep neural networks by means of unfolding the Iterative Shrinkage-Thresholding Algorithm to learn interpretable building blocks and associated weighting map. We then apply spectral clustering to common and subject-specific weighting maps from which we jointly determine the common and subject-specific functional units. Experiments carried out with simulated datasets show that the proposed method achieved on par or better clustering performance over the comparison methods.Experiments carried out with in vivo tongue motion data show that the proposed method can determine the common and subject-specific functional units with increased interpretability and decreased size variability.