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Unlike chemical synthesis, biological synthesis of nanoparticles is gaining tremendous interest, and plant extracts are preferred over other biological sources due to their ample availability and wide array of reducing metabolites. In this project, we investigated the reducing potential of aqueous extract of Artemisia absinthium L. for synthesizing silver nanoparticles (AgNPs). Optimal synthesis of AgNPs with desirable physical and biological properties was investigated using ultra violet-visible spectroscopy (UV-vis), dynamic light scattering (DLS), transmission electron microscopy (TEM) and energy-dispersive X-ray analysis (EDX). To determine their appropriate concentrations for AgNP synthesis, two-fold dilutions of silver nitrate (20 to 0.62 mM) and aqueous plant extract (100 to 0.79 mg ml(-1)) were reacted. The results showed that silver nitrate (2mM) and plant extract (10 mg ml(-1)) mixed in different ratios significantly affected size, stability and yield of AgNPs. Extract to AgNO3 ratio of 6:4v/v resulted in the highest conversion efficiency of AgNO3 to AgNPs, with the particles in average size range of less than 100 nm. Furthermore, the direct imaging of synthesized AgNPs by TEM revealed polydispersed particles in the size range of 5 to 20 nm. Similarly, nanoparticles with the characteristic peak of silver were observed with EDX. This study presents a comprehensive investigation of the differential behavior of plant extract and AgNO3 to synthesize biologically stable AgNPs.

Application of nanoparticles for controlling plant pathogens is a rapidly emerging area in plant disease management, and nanoparticles synthesis methods that are economical and ecofriendly are extensively investigated. In this project, we investigated the potential of silver nanoparticles (AgNPs) synthesized with aqueous extract of Artemisia absinthium against several Phytophthora spp., which cause many economically important crop diseases. In in vitro dose-response tests conducted in microtiter plates, 10 µg ml⁻¹ of AgNPs inhibited mycelial growth of P. parasitica, P. infestans, P. palmivora, P. cinnamomi, P. tropicalis, P. capsici, and P. katsurae. Detailed in vitro dose-response analyses conducted with P. parasitica and P. capsici revealed that AgNPs synthesized with A. absinthium extract were highly potent (IC50: 2.1 to 8.3 µg ml⁻¹) and efficacious (100%) in inhibiting mycelial growth, zoospore germination, germ tube elongation, and zoospore production. Interestingly, AgNP treatment accelerated encystment of zoospores. Consistent with in vitro results, in planta experiments conducted in a greenhouse revealed that AgNP treatments prevented Phytophthora infection and improved plant survival. Moreover, AgNP in in planta experiments did not produce any adverse effects on plant growth. These investigations provide a simple and economical method for controlling Phytophthora with AgNP without affecting normal plant physiology.

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(2019) Sustainable production of biomass and industrially important secondary metabolites in cell cultures of selfheal (Prunellavulgaris L.) elicited by silver and gold nanoparticles,

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Telemedicine is a booming healthcare practice that has facilitated the exchange of medical data and expertise between healthcare entities. However, the widespread use of telemedicine applications requires a secured scheme to guarantee confidentiality and verify authenticity and integrity of exchanged medical data. In this paper, we describe a region-based, crypto-watermarking algorithm capable of providing confidentiality, authenticity, and integrity for medical images of different modalities. The proposed algorithm provides authenticity by embedding robust watermarks in images' region of non-interest using SVD in the DWT domain. Integrity is provided in two levels: strict integrity implemented by a cryptographic hash watermark, and content-based integrity implemented by a symmetric encryption-based tamper localization scheme. Confidentiality is achieved as a byproduct of hiding patient's data in the image. Performance of the algorithm was evaluated with respect to imperceptibility, robustness, capacity, and tamper localization, using different medical images. The results showed the effectiveness of the algorithm in providing security for telemedicine applications.