Spectroscopic, microscopic characterization of Cannabis sativa leaf extract mediated silver nanoparticles and their synergistic effect with antibiotics against human pathogen

Silver nanoparticles (SNPs) are successfully synthesized from aqueous silver nitrate (AgNO3) through a simple novel route using the leaf extract of Cannabis sativa. The results obtained from UV–visible spectroscopy, FTIR (Fourier transform-infrared) spectroscopy, XRD (X-ray diffraction), DLS (dynamic light scattering) SEM (scanning electron microscopy), EDS (energy dispersive spectroscopy), TEM (transmission electron microscopy), SAED (selected area electron diffraction) and AFM (atomic force microscopy) indicate towards the formation of stable, spherical and crystalline SNPs in the size range of 13–25 nm with absorbance peak at 392 nm. Further, various antibiotic alone and with SNPs have been tested against different pathogenic microorganisms and the results show that control of pathogenic microorganisms is more when antibiotics are mixed with SNPs. Keywords: Cannabis sativa, SNPs, TEM, AFM, Antibioti

Ab initio prediction of metabolic networks using Fourier transform mass spectrometry data

Fourier transform mass spectrometry has recently been introduced into the field of metabolomics as a technique that enables the mass separation of complex mixtures at very high resolution and with ultra high mass accuracy. Here we show that this enhanced mass accuracy can be exploited to predict large metabolic networks ab initio, based only on the observed metabolites without recourse to predictions based on the literature. The resulting networks are highly information-rich and clearly non-random. They can be used to infer the chemical identity of metabolites and to obtain a global picture of the structure of cellular metabolic networks. This represents the first reconstruction of metabolic networks based on unbiased metabolomic data and offers a breakthrough in the systems-wide analysis of cellular metabolism. KEY WORDS: Fourier transform mass spectrometry; metabolic networks; network reconstruction; computational methods. 1