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.     

Sustainability evaluation framework for building cooling systems: a comparative study of snow storage and conventional chiller systems

In Canada, the residential building sector consumes 17 % of the total energy and 15 % of the total greenhouse gas emissions. In particular, the energy demand for cooling in the residential sector is increasing due to the large occupancy floor area and high usage of air conditioning. Minimizing energy use and greenhouse gas emissions is one of the highest priority goals set for national energy management strategies in developed countries including Canada. In this study, a framework based on the life cycle assessment approach is developed to assess the environmental impacts of different building cooling systems, namely conventional snow storage system, watertight snow storage system, high-density snow storage system, and the conventional chiller cooling system. Moreover, all these systems have varying energy requirements and associated environmental impacts during different phases (extraction and construction, utilization, and end of life) of the life cycle of a building. A low-rise residential building in Kelowna (BC, Canada) has been selected for the pragmatic application of the proposed framework. The annual cooling energy demand for the building is estimated for different phases. Subsequently, the life cycle impact assessment has been carried out using SimaPro 8.1 software and TRACI 2.1 method. For sustainability evaluation of different cooling systems over their life cycle, multi-criteria decision analysis has been employed using the ‘Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE II).’ The results showed that the snow storage systems tend to reduce greenhouse gas emissions and associated environmental impacts more than the conventional system.     

Proteome of human endometrium: Identification of differentially expressed proteins in proliferative and secretory phase endometrium

Purpose: To exploit the potential of proteomics to identify and study additional yet‐unidentified important proteins present in human endometrium. Experimental design: The proteome of human endometrium would be established using 2‐DE and MALDI and the data analyzed to identify differential protein expression in the proliferative and secretory phase of the menstrual cycle using PDQuest software and MALDI. Results: In the present work, 2‐DE of human endometrium protein led to the resolution of over 200 spots. Subsequent MALDI analysis of 215 spots allowed the identification of 194 proteins. A total of 57 out of the 215 spots were found to be differentially expressed, out of which 49 could be identified using MALDI. These differentially expressed proteins included structural proteins, molecular chaperones, signaling proteins, metabolic proteins, proteins related to immunity, RNA biogenesis, protein biosynthesis and others. The differential expressions of seven representative proteins in secretory and proliferative phase endometrium tissue were confirmed by immunoblot analysis. Conclusion and clinical relevance: This study establishes the 2‐D proteome of human endometrium represented by 194 identified protein spots. The present data provides an important clue towards determining the function of these proteins with respect to endometrium related diseases.     

Robust object tracking with background-weighted local kernels

Object tracking is critical to visual surveillance, activity analysis and event/gesture recognition. The major issues to be addressed in visual tracking are illumination changes, occlusion, appearance and scale variations. In this paper, we propose a weighted fragment based approach that tackles partial occlusion. The weights are derived from the difference between the fragment and background colors. Further, a fast and yet stable model updation method is described. We also demonstrate how edge information can be merged into the mean shift framework without having to use a joint histogram. This is used for tracking objects of varying sizes. Ideas presented here are computationally simple enough to be executed in real-time and can be directly extended to a multiple object tracking system.     

Facial expression recognition using radial encoding of local Gabor features and classifier synthesis

Primarily motivated by some characteristics of the human visual cortex (HVC), we propose a new facial expression recognition scheme, involving a statistical synthesis of hierarchical classifiers. In this scheme, the input images of the database are first subjected to local, multi-scale Gabor-filter operations, and then the resulting Gabor decompositions are encoded using radial grids, imitating the topographical map-structure of the HVC. The codes are fed to local classifiers to produce global features, representing facial expressions. Experimental results show that such a hybrid combination of the HVC structure with a hierarchical classifier significantly improves expression recognition accuracy when applied to wide-ranging databases in comparison with the results in the literature. Furthermore, the proposed system is not only robust to corrupted data and missing information, but can also be generalized to cross-database expression recognition.     

Role of sample size in the nucleation kinetics of phase transformations in steel alloys

Certain commercial steel alloys exhibit a two-step phase transformation process during solidification when substantial undercooling of the liquid allows access to the metastable phase. This two-step transformation leads to a desirable microstructure under certain conditions. Electrostatic Levitation (ESL) and Electromagnetic Levitation (EML) are two methods of containerless processing used to study how nucleation and growth kinetics influence the transformation delay between phases. Because the two facilities show substantially different delay results, the test environment differences have been analyzed to determine the root cause of this deviation. In particular, the difference in sample size between ESL and EML is examined and modeling shows that this difference is not the controlling factor in determining transformation delay behavior.     

Ferroelectric Materials for Microwave Tunable Applications

A review of the properties of ferroelectric materials that are relevant to microwave tunable devices is presented: we discuss the theory of dielectric response of tunable bulk materials and thin films; the experimental results from the literature and from own work are reviewed; the correspondence between the theoretical results and the measured properties of tunable materials is critically analyzed; nominally pure, real (defected), and composite bulk materials and thin films are addressed. In addition, techniques for characterization of tunable ferroelectrics and applications of these materials are briefly presented.