The ionic gelation process for the synthesis of chitosan nanoparticles was carried out in microdroplet reactions. The synthesis could be stopped instantaneously at different time points by fast dilution of the reaction mixture with DI water. Using this simple technique, the effect of temperature and reactant concentrations on the size and distribution of the nanoparticles formed, as a function of time, could be investigated by DLS and SEM. Results obtained indicated very early (1–5 s) nucleation of the particles followed by growth. The concentration of reactants, reaction temperature as well as time, were found to (severally and collectively) determine the size of nanoparticles and their distribution. Nanoparticles obtained at 4 °C were smaller (60–80 nm) with narrower size distribution. Simulation experiments using Comsol software showed that at 4 °C ‘droplet synthesis’ of nanoparticles gets miniaturised to ‘droplet-core synthesis’, which is being reported for the first time.
Chitosan nanoparticles are promising drug delivery vehicles. However, the conventional method of unregulated mixing during ionic gelation limits their application because of heterogeneity in size and physicochemical properties. Therefore, a detailed theoretical analysis of conventional and active microreactor models was simulated. This led to design and fabrication of a polydimethylsiloxane microreactor with magnetic micro needles for the synthesis of monodisperse chitosan nanoparticles. Chitosan nanoparticles synthesized conventionally, using 0.5 mg/mL chitosan, were 250 ± 27 nm with +29.8 ± 8 mV charge. Using similar parameters, the microreactor yielded small size particles (154 ± 20 nm) at optimized flow rate of 400 μL/min. Further optimization at 0.4 mg/mL chitosan concentration yielded particles (130 ± 9 nm) with higher charge (+39.8 ± 5 mV). The well-controlled microreactor-based mixing generated highly monodisperse particles with tunable properties including antifungal drug entrapment (80%), release rate, and effective activity (MIC, 1 μg/mL) against Candida.
The recent need for remote health wellness monitoring has led to the extensive use of wearable sensors. Owing to their increased use, these sensors are required to exhibit both functionality and safety to the user. A major component in the fabrication of these sensors and their associated circuitry is the use of metallic/organic conductive inks. However, very less is known about the interfacial and molecular interactions of these inks with biological matter as they can result in an inflammatory reaction to the user. Significant efforts are thus needed to explore and improve the bio-acceptability of such conductive ink-based wearable sensors. The present study investigates the biocompatibility of encapsulated and non-encapsulated wearable electrochemical sensors used for sensing uric acid as a biomarker for wound healing fabricated using screen-printing technique. Ionic release of metallic ions was investigated first to understand the susceptibility of the conductive inks towards ionic leaching when in contact with a fluid. Time-lapse investigation using ICPS (inductive couple plasma spectroscopy) shows a high concentration (607.31 ppb) of leached silver (Ag+) ions from the non-encapsulated sensors. The cell viability data suggests a 2.5-fold improvement in the sensor biocompatibility for an encapsulated sensor. While the carbon ink shows negligible effect on cell viability, the silver ink elicits significant decrease (< 50%) in cell viability at concentrations higher than 2 mg ml-1. The toxicity pathway of these sensors was further determined to be through the generation of reactive oxygen species resulting in over 20% apoptotic cell death. Our results show that the lower biocompatibility of the non-encapsulated sensor attributes to the higher leaching of Ag+ ions from the printed inks which elicits several different inflammatory pathways. This work highlights the importance biocompatibility evaluation of the material used in sensor fabrication to develop safe and sustainable sensors for long-term applications.
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