秋水仙碱与他汀类潜在药物相互作用处方风险分析

目的 分析秋水仙碱与他汀类潜在药物相互作用(potential drug-drug interactions,pDDIs)处方,进行风险评估并制定预防措施。方法 检索知网、维普、万方、PubMed和Elsevier数据库关于秋水仙碱与他汀类相互作用致不良反应的个案和研究报道,进行文献分析;通过医院合理用药软件抽取2020年1月—2022年10月秋水仙碱联合他汀类药物的所有门诊处方,鉴别出潜在药物相互作用并进行严重性分级。结果 检索到该药物相互作用致不良反应个案报道22例,病例对照研究1篇,观察性队列研究2篇;不良反应以老年人居多,男性多于女性;发生时间集中在联合用药21 d内,3例患者死亡;高剂量、高龄、男性和肝/肾功能不全可能增加该pDDIs发生风险;遵义医科大学附属医院共收集到秋水仙碱联合他汀类药物处方72张,其中阿托伐他汀65张,瑞舒伐他汀6张,辛伐他汀1张,危险程度分级均为严重;1例患者联合使用秋水仙碱和阿托伐他汀4个月后出现肌病,1个月后好转;临床药师制定了7项预防措施。结论 遵义医科大学附属医院秋水仙碱与他汀类处方存在pDDIs,需积极实施预防措施并加强监测,尤其是联合用药...     

Novel food drug interaction mechanism involving acyclovir,chitosan and endogenous mucus

Drug absorption from drug products may be affected by pharmaceutical excipients and/or food additives through different mechanisms. Chitosan is a recognized nutraceutical, with potential as an excipient due to its permeability enhancer properties. While chitosan properties have been evaluated in in vitro and pre-clinical models, studies in humans are scarce. Unexpectedly, a controlled clinical trial showed chitosan actually reduced acyclovir bioavailability. The effect seems to be related to an interaction with gastrointestinal mucus that prevents further absorption, although more in depth research is needed to unravel the mechanism. In this paper, we propose a mechanism underlying this excipient effect. The mucus – chitosan interaction was characterized and its effect on acyclovir diffusion, permeation and bioaccessibility was investigated. Further, pharmacokinetic modeling was used to assess the clinical relevance of our findings. Results suggest that in situ coacervation between endogenous mucus and chitosan rapidly entrap 20–30% of acyclovir dissolved dose in the intestinal lumen. This local reduction of acyclovir concentration together with its short absorption window in the small intestine would explain the reduction in acyclovir C_max and AUC. This study highlights the importance of considering mucus in any biorelevant absorption model attempting to anticipate the effect of chitosan on drug absorption.     

Donor-recipient age interaction and the impact on clinical results after heart transplantation

To evaluate the impact of donor-recipient age matching on clinical outcomes after heart transplantation, a total of 509 patients (January 1990-December 2018, mean follow-up 111 ± 80 months) were stratified into 4 groups (young-R/young-D, young-R/old-D, old-R/young-D, old-R/old-D) according to the recipient (young-R < 60, old-R ≥ 60 years) and the donor (young-D < 50, old-D ≥ 50 years) age. No difference was found among 30-day mortality (P = .11) and postoperative complications between groups. Both unadjusted and adjusted survival was significantly higher for group young-R/young-D than that of other groups, in which survival was similar [adjusted HR for mortality of 2.0(1.2-3.4), 2.1(1.4-3.8) and 2.5(1.6-4.1) for groups old-R/young-D, young-R/old-D, old-R/old-D, respectively]. Compared to other groups, the incidence of grade ≥ 2 CAV was significantly lower in old-R/young-D group [adjusted HR 0.4(0.2-0.7)]. Among young recipients, the rate of acute grade ≥ 2 rejection episodes was higher in those receiving an old donor graft (P = .04). Old recipient groups were more affected by neoplasms and severe renal failure than young recipient groups (P < .01). Employment of hearts from donors ≥50 years of age adversely affects survival in recipients <60 years of age but does not influence outcomes in older recipients. Also, donor and recipient ages seem to have opposite effects on incidence of rejections and CAV of high grade.     

Position-aware deep multi-task learning for drug–drug interaction extraction

ObjectiveA drug–drug interaction (DDI) is a situation in which a drug affects the activity of another drug synergistically or antagonistically when being administered together. The information of DDIs is crucial for healthcare professionals to prevent adverse drug events. Although some known DDIs can be found in purposely-built databases such as DrugBank, most information is still buried in scientific publications. Therefore, automatically extracting DDIs from biomedical texts is sorely needed.Methods and materialIn this paper, we propose a novel position-aware deep multi-task learning approach for extracting DDIs from biomedical texts. In particular, sentences are represented as a sequence of word embeddings and position embeddings. An attention-based bidirectional long short-term memory (BiLSTM) network is used to encode each sentence. The relative position information of words with the target drugs in text is combined with the hidden states of BiLSTM to generate the position-aware attention weights. Moreover, the tasks of predicting whether or not two drugs interact with each other and further distinguishing the types of interactions are learned jointly in multi-task learning framework.ResultsThe proposed approach has been evaluated on the DDIExtraction challenge 2013 corpus and the results show that with the position-aware attention only, our proposed approach outperforms the state-of-the-art method by 0.99% for binary DDI classification, and with both position-aware attention and multi-task learning, our approach achieves a micro F-score of 72.99% on interaction type identification, outperforming the state-of-the-art approach by 1.51%, which demonstrates the effectiveness of the proposed approach.     

直接脑控多机器人协作任务研究

脑控是一种新的控制方法。传统脑控机器人主要是控制单个机器人完成特定任务,而脑控多机器人协作(MRC)任务是一个有待研究的新课题。本文介绍了参加世界机器人大赛"脑—机接口(BCI)脑控机器人比赛"获得"创新创意奖"的一个试验研究,试验设置了2个脑开关,采用基于稳态视觉诱发电位(SSVEP)的BCI(SSVEP-BCI)控制人形机器人和机械臂完成协作任务。通过10名受试者的控制试验结果表明,通过适当设置脑开关,采用性能优良的SSVEP-BCI能够实现MRC任务的有效完成。本研究可望为未来实用化的脑控MRC任务系统的研究提供启发。     

Biochemical characterization of the Helicobacter pylori Cag Type 4 Secretion System protein CagN and its interaction partner CagM

Highly virulent Helicobacter pylori strains contain the cag pathogenicity island (cagPAI). It codes for about 30 proteins forming a type IV secretion system (T4SS) which translocates the pro-inflammatory protein CagA into epithelial host cells. While CagA and various other Cag proteins have been extensively studied, several cagPAI proteins are poorly characterized or of unknown function. CagN (HP0538) is of unknown function but highly conserved in the cagPAI suggesting an important role. cagM (HP0537) is the first gene of the cagMN operon and its product is part of the CagT4SS core complex. Both proteins do not have detectable homologs in other type IV secretion systems. We have characterized the biochemical and structural properties of CagN and CagM and their interaction. We demonstrate by circular dichroism, Multi-Angle Light Scattering (MALS) and small angle X-ray scattering (SAXS) that CagN is a folded, predominantly monomeric protein with an elongated shape in solution. CagM is folded and forms predominantly dimers that are also elongated in solution. We found by various in vivo and in vitro methods that CagN and CagM directly interact with each other. CagM self-interacts stably with a low nanomolar K_D and can form stable multimers. Finally, in vivo experiments show that deletion of CagM reduces the amounts of CagN and other outer CagPAI proteins in H. pylori cells.     

Formation of the Legionella-containing vacuole: phosphoinositide conversion,GTPase modulation and ER dynamics

The environmental bacterium Legionella pneumophila replicates in free-living amoeba as well as in alveolar macrophages upon inhalation of bacteria-laden aerosols. Resistance of the opportunistic pathogen to macrophages is a prerequisite to cause a severe pneumonia called Legionnaires’ disease. L. pneumophila grows intracellularly in a unique, ER-associated compartment, the Legionella-containing vacuole (LCV). The bacterial Icm/Dot type IV secretion system represents an essential virulence factor, which translocates approximately 300 “effector proteins” into protozoan or mammalian host cells. Some of these effectors contribute to the formation of the LCV by targeting conserved host factors implicated in membrane dynamics, such as phosphoinositide lipids and small GTPases. Here we review recent findings on the role of phosphoinositides, small and large GTPases as well as ER dynamics for pathogen vacuole formation and intracellular replication of L. pneumophila.