137 research outputs found

    Synthesis of well-defined catechol polymers for surface functionalization of magnetic nanoparticles

    Get PDF
    In order to obtain dual-modal fluorescent magnetic nanoparticles, well-defined fluorescent functional polymers with terminal catechol groups were synthesized by single electron transfer living radical polymerization (SET-LRP) under aqueous conditions for “grafting to” modification of iron oxide nanoparticles. Acrylamide, N-isopropylacrylamide, poly(ethylene glycol) methyl ether acrylate, 2-hydroxyethyl acrylate, glycomonomer and rhodamine B piperazine acrylamide were homo-polymerized or block-copolymerized directly from an unprotected dopamine-functionalized initiator in an ice-water bath. The Cu-LRP tolerated the presence of catechol groups leading to polymers with narrow molecular weight distributions (Mw/Mn < 1.2) and high or full conversion obtained in a few minutes. Subsequent immobilization of dopamine-terminal copolymers on an iron oxide surface were successful as demonstrated by Fourier transform infrared spectroscopy (FTIR), dynamic light scattering (DLS), transition electron microscopy (TEM) and thermogravimetric analysis (TGA), generating stable polymer-coated fluorescent magnetic nanoparticles. The nanoparticles coated with hydrophilic polymers showed no significant cytotoxicity when compared with unmodified particles and the cellular-uptake of fluorescent nanoparticles by A549 cells was very efficient, which also indicated the potential application of these advanced nano materials for bio-imaging

    Polymeric drug delivery systems for biological antimicrobial agents

    Get PDF
    The objective of this work was to develop suitable delivery systems for biological agents that have antimicrobial activities using biocompatible polymers, aiming to reduce their toxicity when administered. Two biological agents, colistin as an antibacterial agent and nystatin (Nys) as an antifungal agent, are the focus of this thesis as they are potent treatments for current pathogen infections, especially to the multidrug-resistant (MDR) bacteria/fungi, but have potential toxicity to human. Polymeric drug delivery systems, including prodrug, hydrogel and micelle formulations, have been developed and discussed for their potential as topical and systemic regimes. The majority of the work was focused on the effect of the covalently attachment of synthetic polymers onto the biological agents upon their antimicrobial activities and the toxicity. The conjugation between colistin and polymers was achieved successfully through either irreversible or releasable linkages. Although irreversible polymer modifications on colistin showed no antimicrobial activity (chapter 2), an acceptable antibacterial activity was observed from the polymer-colistin conjugates with a releasable linkage through either ‘grafting-to’ (chapter 3) or ‘grafting-from’ (chapter 4) approaches. On the other hand, even though the pure polymer-Nys conjugate with a releasable imine linkage cannot be obtained due to the nature of the labile imine bond, the crude conjugate showed an excellent antifungal activity and a reduced toxicity compared to the native Nys (chapter 6). Other polymeric delivery systems were also discussed in this thesis. The incorporation of colistin within a developed hydrogel delivery system as an antibacterial patch for burn infections was investigated through in vitro and in vivo studies, showing a similar antibacterial activity as the native colistin solution against MDR Gram-negative bacteria with no systemic toxicity (chapter 5). Finally, an amphiphilic polymer containing boronic acid groups on the side chains was synthesised and used to target the hydroxyl groups on Nys, expecting to build up an environmental responsive micelle through dynamic boronate ester bond (chapter 7). Although more work is still needed, this system showed a potential to improve Nys solubility

    A hydrogel based localized release of colistin for antimicrobial treatment of burn wound infection

    Get PDF
    There is an urgent unmet medical need for new treatments for wound and burn infections caused by multidrug-resistant (MDR) Gram-negative ‘superbugs’, especially the problematic Pseudomonas aeruginosa. In this work we report the incorporation of colistin, a potent lipopeptide into a self-healable hydrogel (via dynamic imine bond formation) following the chemical reaction between the amine groups present in glycol chitosan and an aldehyde modified poly (ethylene glycol) (PEG). The storage module (G’) of the colistin-loaded hydrogel ranged from 1.3 kPa to 5.3 kPa by varying the amount of the cross-linker and colistin loading providing different options for topical wound healing. The majority of the colistin is released from the hydrogel within 24 h and remains active as demonstrated by both antibacterial in vitro disk diffusion and time-kill assays. Moreover and pleasingly, the colistin-loaded hydrogel performed almost equally well as native colistin against both the colistin-sensitive and also colistin-resistant P. aeruginosa strain in the in vivo animal 'burn' infection model despite exhibiting a slower killing profile in vitro. Based on this antibiotic performance along with the biodegradability of the product, we believe the colistin-loaded hydrogel to be a potential localized wound-healing formulation to treat burn wounds against microbial infection

    Machine-learning Classifier to Detect Atrial Fibrillation based on Facial Action Units

    No full text
    Facial action units (AUs) are numerical representations of indicative facial features drawn by facial landmark localization. Tiny muscular movements on the face can be reflected through facial AUs. In this project, using AUs to diagnose atrial fibrillation (AFib) in real-time is investigated for the first time, and AUs are shown to have a connection with AFib occurrence. Unlike ECG/PPG/VPG, the machine-learning-enabled AFib detector proposed in this project can realize real-time contactless monitoring of AFib continuously in home settings while maintaining the accuracy of AFib detection. ECG data and tablet image snapshots are synchronized to form the dataset that will be used. AUs extracted from the images serve as predictors, and the ECG data corresponds to a binary AFib label at a time instant. Due to limited data, the original dataset is balanced and augmented. AUs are engineered based on a feature selection method. AFib data are partitioned into a training/validation set and a test set, and modern machine-learning classifiers are used to fit the data. Upon five-fold cross-validation, random forest (RF) stands out and is further fine-tuned, achieving the best performance curve and the highest area under the curve (AUC). After RF has been fine-tuned, an F2-score of 0.811, recall of 0.782, and accuracy of 0.969 can be attained. For new subjects that have not been trained before in the test set, RF is also proved to be superior to a random classifier. As more training data are available, the RF classifier to detect AFib is promising for future real-life applications

    Dynamic Hydrogels against Infections: From Design to Applications

    No full text
    Human defense against infection remains a global topic. In addition to developing novel anti-infection drugs, therapeutic drug delivery strategies are also crucial to achieving a higher efficacy and lower toxicity of these drugs for treatment. The application of hydrogels has been proven to be an effective localized drug delivery approach to treating infections without generating significant systemic adverse effects. The recent emerging dynamic hydrogels further show power as injectable formulations, giving new tools for clinical treatments. In this review, we delve into the potential applications of dynamic hydrogels in antibacterial and antiviral treatments and elaborate on their molecular designs and practical implementations. By outlining the chemical designs underlying these hydrogels, we discuss how the choice of dynamic chemical bonds affects their stimulus responsiveness, self-healing capabilities, and mechanical properties. Afterwards, we focus on how to endow dynamic hydrogels with anti-infection properties. By comparing different drug-loading methods, we highlight the advantages of dynamic chemical bonds in achieving sustained and controlled drug release. Moreover, we also include the design principles and uses of hydrogels that possess inherent anti-infective properties. Furthermore, we explore the design principles and applications of hydrogels with inherent anti-infective properties. Finally, we briefly summarize the current challenges faced by dynamic hydrogels and present a forward-looking vision for their future development. Through this review, we expect to draw more attention to these therapeutic strategies among scientists working with chemistry, materials, as well as pharmaceutics

    Numerical Analysis for Wetting Behaviors of an Oil Jet Lubricated Spur Gear

    No full text
    As it is widely employed in the aeronautical transmission system, a better understanding of the oil jet lubrication behavior is vital to determine the total system energy consumption. Firstly, this study presents related theoretical models such as the sum of oil jet resistance torque, impingement depth, and wetted area of the oil film for calibrating the physical characteristics of the impact of the oil jet on the gear flank. Then, in terms of the flow phenomenology of the liquid column for the oil jet impact on an isolated spur gear, a detailed transient and spatial flow field analysis becomes available, benefiting from an overset mesh method integrating with a volume-of-fluid (VOF) method. Furthermore, not only the oil jet resistance torque, but also the impingement depth as well as the spatial and temporal evolution of wetted surface by the oil film on the gear tooth given by numerical investigations were compared well with the theoretical calculations

    Using a specific wavelength for broadcast/multicast transmission in hybrid WDM/TDM PON

    No full text

    Prediction and diagnosis of mine hoist fault based on wavelet neural network

    No full text
    corecore