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Antibiotic resistance continues to pose significant health challenges. Considering severe limitations in the discovery and supply of new antibiotics, there is an unmet need to design alternative and more effective strategies for addressing this global issue. Use of polymeric nanoparticles with cationic shell surfaces offers a highly promising approach to coupling their inherent bactericidal action with sustained delivery of small lipophilic microbicides. We have utilized this platform for assembling multi-tasking soft core-shell nanoparticles from star polymers with the desired asymmetric arm composition. These stable nanoparticles with low critical micelle concentration imparted intrinsic antimicrobial potency due to high positive charge density in the corona, as well as the loading of active biocidal agents (such as curcumin and terbinafine) for potential dual and coadjuvant inhibition. This strategic combination allows for both immediate (direct contact) and extended (drug delivery) antibacterial activities for better therapeutic efficacy. Micellar nanoparticles with and without therapeutic cargo were highly efficient against both Escherichia coli ( E. coli ) and Bacillus subtilis ( B. subtilis ), representative Gram-negative and Gram-positive bacteria, respectively. Interestingly, we observed bacteria- and concentration-dependent effects, in which higher concentrations of charged nanoparticles were more effective against E. coli , whereas B. subtilis was inhibited only at lower concentrations. This work highlights a valuable platform to achieve combination therapy through nanoparticles with charged coronas and delivery of potent therapeutics to overcome antimicrobial resistance.

A multi-component hydrogel was developed using bacterial cellulose, alginate, and gelatin with the aid of glycerol as trihydric alcohol which participates in re-distribution of hydrogen bonds in the test system. FTIR, XRD, SEM, and TGA as instrumental techniques were used to structurally characterize the physical/chemical properties of the formed composite hydrogel. By using an exponential equation, swelling behavior of the hydrogel was evaluated. By incorporating a model drug (methylene blue-MB) in the formed hydrogel, experiments were directed to study release characteristics of the MB where the medium solution for the release was prepared at four different pHs. The maximum cumulative drug release at pH 2.8, 6, 7.4, and 9 were 42.8, 63, 80, and 84.5%, respectively. Data fitting process was carried out using five kinetic models (Korsmeyer-Peppas, Higuchi, Hopfenberg, zero-order, and first-order equations) and the preferred kinetic model at each pH was estimated by applying TOPSIS algorithmic technique. The adsorption capacity of the hydrogel in relation to MB was determined while thermodynamic properties of this relationship were quantified ([Formula: see text] and [Formula: see text]). The results of the present study were in favor of the potential usage of the developed composite hydrogel in drug delivery systems., (© 2023. The Author(s).)

Bacterial cellulose (BC) was produced via the static fermentation process using G. xylinus. Cellulose and diethylaminoethyl cellulose (DEAEC) were converted to carboxymethyl cellulose (CMC) and carboxymethylated diethylaminoethyl cellulose (CMDEAEC) while to prepare the composites, two different methods were used: by either direct addition of the materials to the fermentation medium or addition of the materials after the fermentation process. Structural characteristics of composites were determined using instrumental techniques. Potential application of BC, BC/CMC, and BC/CMDEAEC in drug delivery system was examined using methylene blue (MB) as a model drug where the loading capacity and swelling ratio for the samples were as follows: BC/CMC > BC/CMDEAEC > BC. The result of the in-vitro study was in favor of the release behavior of BC/CMDEAEC composite. The MB loading data were fitted using Langmuir and Freundlich equations and kinetic behavior of the release was described by Higuchi and Korsmeyer-Peppas models., (Copyright © 2021 Elsevier Ltd. All rights reserved.)