Bacteria-Responsive Self-Assembly of Antimicrobial Peptide Nanonets for Trap-and-Kill of Antibiotic-Resistant Strains

Bacterial trapping using nanonets is a ubiquitous immune defense mechanism against infectious microbes. These nanonets can entrap microbial cells, effectively arresting their dissemination and rendering them more vulnerable to locally secreted microbicides. Inspired by this evolutionarily conserved anti-infective strategy, a series of 15 to 16 residue-long synthetic β-hairpin peptides is herein constructed with the ability to self-assemble into nanonets in response to the presence of bacteria, enabling spatiotemporal control over microbial killing. Using amyloid-specific K114 assay and confocal microscopy, the membrane components lipoteichoic acid and lipopolysaccharide are shown to play a major role in determining the amyloid-nucleating capacity as triggered by Gram-positive and Gram-negative bacteria respectively. These nanonets displayed both trapping and killing functionalities, hence offering a direct improvement from the trap-only biomimetics in literature. By substituting a single turn residue of the non-amyloidogenic BTT1 peptide, the nanonet-forming BTT1-3A analog is produced with comparable antimicrobial potency. With the same sequence manipulation approach, BTT2-4A analog modified from BTT2 peptide showed improved antimicrobial potency against colistin-resistant clinical isolates. The peptide nanonets also demonstrated robust stability against proteolytic degradation, and promising in vivo efficacy and biosafety profile. Overall, these bacteria-responsive peptide nanonets are promising clinical anti-infective alternatives for circumventing antibiotic resistance.     

Evolutionary state-based novel multi-objective periodic bacterial foraging optimization algorithm for data clustering

Clustering divides objects into groups based on similarity. However, traditional clustering approaches are plagued by their difficulty in dealing with data with complex structure and high dimensionality, as well as their inability in solving multi-objective data clustering problems. To address these issues, an evolutionary state-based novel multi-objective periodic bacterial foraging optimization algorithm (ES-NMPBFO) is proposed in this article. The algorithm is designed to alleviate the high-computing complexity of the standard bacterial foraging optimization (BFO) algorithm by introducing periodic BFO. Moreover, two learning strategies, global best individual (gbest) and personal historical best individual (pbest), are used in the chemotaxis operation to enhance the convergence speed and guide the bacteria to the optimum position. Two elimination-dispersal operations are also proposed to prevent falling into local optima and improve the diversity of solutions. The proposed algorithm is compared with five other algorithms on six validity indexes in two data clustering cases comprising nine general benchmark datasets and four credit risk assessment datasets. The experimental results suggest that the proposed algorithm significantly outperforms the competing approaches. To further examine the effectiveness of the proposed strategies, two variants of ES-NMPBFO were designed, and all three forms of ES-NMPBFO were tested. The experimental results show that all of the proposed strategies are conducive to the improvement of solution quality, diversity and convergence.     

我国细菌耐药问题的现状和防控策略

细菌耐药危机日趋严峻,已经成为全球范围内的重大公共安全问题,严重危害人类、动物的健康和生态环境。本文总结了我国各领域细菌耐药问题的现状,分析了加剧细菌耐药性的直接原因,揭示了细菌耐药问题对国民健康、食品安全、生态环境、经济发展等可能造成的危害,整理了我国目前开展的防控行动以及取得的主要成果,最后针对我国细菌耐药防控在耐药监测、抗生素监管、危害风险评估、人才队伍建设等方面的不足,提出了多领域合作、多部门联防联控的细菌耐药防控策略。     

粘合体系对天然橡胶复合材料性能的影响

本文以木质纤维素/蒙脱土、炭黑为增强材料,制备了天然橡胶复合材料,探讨了以间苯二酚(R-80)、六甲氧基甲基三聚氰胺(HMMM)和新癸酸钴为主要成分的粘合体系对天然橡胶复合材料性能的影响。结果表明:间-甲-钴粘合体系大幅提高了天然橡胶复合材料的焦烧时间(T_(10))和正硫化时间(T_(90)),降低了其硫化速度(V_(C1));力学测试显示,粘合体系对复合材料的拉伸强度、撕裂强度和断裂伸长率的影响相当大;提高了复合材料的邵氏A硬度、密度和耐磨性。     

射频输入功率对DLC∶F∶Si薄膜结构和附着特性的调制机理

以SiC陶瓷靶为靶材,Ar和CHF_3为源气体,采用反应磁控溅射法在双面抛光的316L不锈钢基片上制备出了系列Si和F共掺杂的DLC∶F∶Si薄膜。研究了射频输入功率对薄膜的附着力、硬度和表面接触角的影响。结果表明,选取适当的输入功率(180W左右)可以制备出附着力达11N的DLC∶F∶Si薄膜。通过拉曼和红外光谱分析以及样品粗糙度分析,作者提出了输入功率对DLC∶F∶Si薄膜结构和特性调制的机理,即输入功率直接影响SiC靶的溅射产额、空间Ar~+的能量以及CHF_3的分解程度,继而影响空间Si、C、-CF、-CF_2,特别是F~*等基团的能量和浓度,调制薄膜中F含量以及Si-C键含量和C网络的关联度。Si-C、C=C键的增加有助于薄膜附着力的明显改善,F含量的减少则会导致薄膜的疏水性能有所下降。     

基于表面理论的温拌SBS改性沥青-集料体系的粘附性

采用躺滴法检测了掺加1.5%、3%的Sasobit和0.5%、1%的Evotherm 3G制备得到的温拌SBS改性沥青与蒸馏水、甘油和甲酰胺3种液体的接触角;基于表面自由能理论,对比了温拌SBS改性沥青在无水条件下的表面自由能和粘聚功以及在有水条件下的剥落功;同时,考察了温拌SBS改性沥青和石灰岩质集料的粘附功和配伍率。结果表明:采用躺滴法可以准确检测温拌SBS改性沥青与常用检测液体的接触角;以粘聚功、粘附功、剥落功、配伍率作为评价指标可用于表征温拌SBS改性沥青-集料体系的粘附性;温拌SBS改性沥青的表面自由能及其分量、粘聚功、配伍率随着Sasobit掺量的增大而减小,但随着Evotherm温拌剂掺量的增加而增大;水的参与降低了温拌剂对SBS改性沥青-集料体系粘附性影响的差异;Evotherm温拌剂有助于改善温拌SBS改性沥青的水敏感性,Sasobit温拌剂增加了温拌SBS改性沥青的水敏感性。     

Q345B钢氧化铁皮的高温粘附性研究

热轧板带加热过程中高温氧化将直接影响氧化铁皮的结构、元素分布以及粘附性,进而间接影响后续除鳞效果以及粗轧和精轧后得到的成品钢板表面质量。本文利用Gleeble热模拟试验机模拟Q345B连铸坯粗轧前在1 150和1 250℃加热阶段的氧化情况,并结合拉伸试验研究了两个温度下氧化铁皮的表面形貌、次生氧化铁皮的裂纹以及氧化铁皮与基体界面处截面形貌和各合金的元素分布。研究表明：高温短时氧化生成的一次氧化铁皮粘附性小,仅微小变形即可完全剥离脱落;次生氧化铁皮粘附性大,但强度低,塑性差,易产生裂纹。此外,次生氧化铁皮与基体界面处反应生成的Fe₂SiO₄会改变氧化铁皮FeO内层的相间分布,对氧化皮起到钉扎作用,导致氧化皮的粘附性强,这增大了后续除鳞的难度。为改善钢板的表面质量,生产实践中建议在粗轧除鳞前控制钢板氧化铁皮界面温度高于Fe₂SiO₄凝固温度,以降低氧化铁皮与钢板基体附着力。     

细菌菌落优化算法

根据细菌菌落生长演化的基本规律,提出一种新的细菌菌落优化算法.首先,依据细菌生长繁殖规律,制定符合算法需要的个体进化机制.其次根据细菌在培养液中的觅食行为,建立算法中个体泳动、翻滚、停留等运动方式.最后,借鉴菌落中细菌信息交互方式,建立个体信息共享机制.另外,该算法提供了一种新的结束方式,即在没有任何迭代次数或精度条件的前提下,算法会随着菌落的消失而自然结束,并且可以保持一定的精度.通过与两类PSO算法比较的仿真实验验证了细菌菌落优化算法的效果,通过仿真实验验证了细菌菌落优化算法自然结束过程.