Analysis of drug resistance of Acinetobacter baumannii in burn wards and infection distribution during 5 years

目的  回顾性分析5年间医院烧伤病房鲍曼不动杆菌（AB）的耐药性变迁及感染分布，提供合理有效的临床应用抗菌素治疗方案，控制感染同时延缓AB耐药甚至多重AB耐药发展。方法： 收集烧伤整形美容科2010年1月一2014年12月间所有住院患者资料，筛选出162例AB感染患者，总结AB动态耐药性变迁及感染特点。结果： 烧伤病房AB的检出率逐年呈增高趋势；162例AB感染患者检出标本分别为:创面分泌物116株，痰液25株，血液16株，深静脉尖端导管5株。分别占：71.6%，15.4%，9.9%，3.1%。尿液及大便中未见AB检出，与其他AB研究者结果一致；烧伤ICU患者检出AB有76例，其中死亡12例，死亡率较高；AB对多粘菌素B仍保持较高的敏感性，敏感率为98.3%，曾保持较高敏感性的亚胺培南、米诺环素近些年来耐药率逐年增高，分别由2010年敏感率50%降为2014年31.4%，75%降为35.3%，对第三代头孢菌素及其他6种抗菌素耐药率几乎接近100%，泛耐药现象十分严重。结论：AB耐药性存在地区和医院差异，通过了解我院烧伤患者AB感染分布及耐药性特点，指导本院甚至本地区临床控制感染的同时有效减缓AB耐药的快速发展。Objective:To provide reasonable and effective clinical applications scheme of antibiotics treatment and control infection while delaying the development of Acinetobacter baumannii(AB) drug resistance or multidrug resistance by analyzing change of AB drug resistance and infection distribution retrospectively during 5 years. Methods: From Jan 2010 to Dec 2014,the whole clinical data of 162 patients with AB infections in department of burn and plastic surgery were analyzed,the drug resistance and the characteristics of the infections were summarized. Results:The detection rate of AB in burn ward is increasing year by year; The result of 162 AB infection detected specimens was following: there were 116 (71.6%) strains isolated from the wound secretions,25 (15.4%) strains from sputum,16 (9.9%) strains from blood,5 (3.1%) strains from deep intravenous catheter. Consistent with other AB researchers ,no AB strain was isolated from feces or urine; 76 patients was detected with AB in ICU, 12 cases died, and relatively high mortality ; AB still maintains a relatively high sensitivity(98.3%) with polymyxin B , The drug resistance rates with imipenem and minocycline were increasing in recent years , respective sensitivity from 50% fell to 28% , 75% to 35.3%, AB had nearly 100% resistance rate for the third generation cephalosporins and other 6 kinds of antibiotic, serious extensive drug resistant phenomenon. Conclusion: Understanding the distribution and drug resistance of AB with patients in our burn wards despite of regional and hospital differences,providing better guidance for clinical medication.

A Benchmark for Understanding and Generating Dialogue between Characters in Stories

Many classical fairy tales, fiction, and screenplays leverage dialogue to advance story plots and establish characters. We present the first study to explore whether machines can understand and generate dialogue in stories, which requires capturing traits of different characters and the relationships between them. To this end, we propose two new tasks including Masked Dialogue Generation and Dialogue Speaker Recognition, i.e., generating missing dialogue turns and predicting speakers for specified dialogue turns, respectively. We build a new dataset DialStory, which consists of 105k Chinese stories with a large amount of dialogue weaved into the plots to support the evaluation. We show the difficulty of the proposed tasks by testing existing models with automatic and manual evaluation on DialStory. Furthermore, we propose to learn explicit character representations to improve performance on these tasks. Extensive experiments and case studies show that our approach can generate more coherent and informative dialogue, and achieve higher speaker recognition accuracy than strong baselines

Cinnamic aldehyde treatment alleviates chronic unexpected stress-induced depressive-like behaviors via targeting cyclooxygenase-2 in mid-aged rats

Ethnopharmacological relevance: COX-2 has been considered as a potent molecular target for prevention and therapy of depression. However, a recent study showed that COX-2 inhibitor does not improve depressive symptoms in persons aged 70 and over. Therefore, whether treatments targeting COX-2 have a clinical efficacy in depression, especially elderly individuals, remains unclear. Cinnamic aldehyde is a major constituent of Cinnamomum cassia, which has exhibited excellent anti-inflammatory activities as a COX-2 inhibitor. To investigate the potential antidepressant effect of cinnamic aldehyde in mid-aged rats

Adaptive CGFs Based on Grammatical Evolution

Computer generated forces (CGFs) play blue or red units in military simulations for personnel training and weapon systems evaluation. Traditionally, CGFs are controlled through rule-based scripts, despite the doctrine-driven behavior of CGFs being rigid and predictable. Furthermore, CGFs are often tricked by trainees or fail to adapt to new situations (e.g., changes in battle field or update in weapon systems), and, in most cases, the subject matter experts (SMEs) review and redesign a large amount of CGF scripts for new scenarios or training tasks, which is both challenging and time-consuming. In an effort to overcome these limitations and move toward more true-to-life scenarios, a study using grammatical evolution (GE) to generate adaptive CGFs for air combat simulations has been conducted. Expert knowledge is encoded with modular behavior trees (BTs) for compatibility with the operators in genetic algorithm (GA). GE maps CGFs, represented with BTs to binary strings, and uses GA to evolve CGFs with performance feedback from the simulation. Beyond-visual-range air combat experiments between adaptive CGFs and nonadaptive baseline CGFs have been conducted to observe and study this evolutionary process. The experimental results show that the GE is an efficient framework to generate CGFs in BTs formalism and evolve CGFs via GA