The need of natural antimicrobials is paramount to avoid harmful synthetic chemicals. The study aimed to determine the antifungal activity of natural compound chitosan and its nanoparticles forms against Candida albicans, Fusarium solani and Aspergillus niger. Chitosan nanoparticles were prepared from low (LMW), high molecular weight (HMW) chitosan and its derivative, trimethyl chitosan (TMC). Particle size was increased when chitosan/TMC concentration was increased from 1 to 3 mg/mL. Their zeta potential ranged from +22 to +55 mV. Chitosan nanoparticles prepared from different concentrations of LMW and HMW were also found to serve a better inhibitory activity against C. albicans (MICLMW = 0.25–0.86 mg/mL and MICHMW = 0.6–1.0 mg/mL) and F. solani (MICLMW = 0.86–1.2 mg/mL and MICHMW = 0.5–1.2 mg/mL) compared to the solution form (MIC = 3 mg/mL for both MWs and species). This inhibitory effect was also influenced by particle size and zeta potential of chitosan nanoparticles. Besides, Aspergillus niger was found to be resistant to chitosan nanoparticles except for nanoparticles prepared from higher concentrations of HMW. Antifungal activity of nanoparticles prepared from TMC was negligible. The parent compound therefore could be formulated and applied as a natural antifungal agent into nanoparticles form to enhance its antifungal activity.

Recently, the attention of researchers has been drawn toward the synthesis of chitosan derivatives and their nanoparticles with enhanced antimicrobial activities. In this study, chitosan derivatives with different azides and alkyne groups were synthesized using click chemistry, and these were further transformed into nanoparticles by using the ionotropic gelation method. A series of chitosan derivatives was successfully synthesized by regioselective modification of chitosan via an azide-alkyne click reaction. The amino moieties of chitosan were protected during derivatization by pthaloylation and subsequently unblocked at the end to restore their functionality. Nanoparticles of synthesized derivatives were fabricated by ionic gelation to form complexes of polyanionic penta-sodium tripolyphosphate (TPP) and cationic chitosan derivatives. Particle size analysis showed that nanoparticle size ranged from 181.03 ± 12.73 nm to 236.50 ± 14.32 nm and had narrow polydispersity index and positive surface charge. The derivatives and corresponding nanoparticles were evaluated in vitro for antibacterial and antifungal activities against three gram-positive and gram-negative bacteria and three fungal strains, respectively. The minimum inhibitory concentration (MIC) of all derivatives ranged from 31.3 to 250 µg/mL for bacteria and 188 to1500 µg/mL for fungi and was lower than that of native chitosan. The nanoparticles with MIC ranging from 1.56 to 25 µg/mLfor bacteria and 94 to 750 µg/mL for fungi exhibited higher activity than the chitosan derivatives. Chitosan O-(1-methylbenzene) triazolyl carbamate and chitosan O-(1-methyl phenyl sulfide) triazolyl carbamate were the most active against the tested bacterial and fungal strains. The hemolytic assay on erythrocytes and cell viability test on two different cell lines (Chinese hamster lung fibroblast cells V79 and Human hepatic cell line WRL68) demonstrated the safety; suggesting that these derivatives could be used in future medical applications. Chitosan derivatives with triazole functionality, synthesized by Huisgen 1,3-dipolar cycloaddition, and their nanoparticles showed significant enhancement in antibacterial and antifungal activities in comparison to those associated with native, non-altered chitosan.

No abstract

No abstract

This study contributes to the technology management literature on the effects of IT on operations processes by examining the use of systems based on Artificial Intelligence (AI) in professional services. The paper builds on key concepts on AI, information systems, professional work, and professional services operations management. A model is developed to explain how AI‐based systems combine with humans to do work, both automating and augmenting the work of the professional, leading to process improvement and extension of the service offering. The study uses case‐based research in two law firms and two accountancy firms using AI‐based systems. It shows that AI‐based systems are used selectively, mainly on high‐volume, back‐office tasks, across the sequence of stages in the professional service process—diagnosis, inference, and treatment. Automation using AI relieves professionals from repetitive tasks, while AI achieves augmentation by buffering professionals from low‐value activity, making their expertise scalable and providing new analytical insights. System use can improve performance in delivering core professional services and enable service extension into additional, high‐value advisory work. The model and research approach have potential implications for other emerging areas of technology management in OM.