The search for sensitive and rapid analytical techniques for the determination of natural antioxidants is an area in constant growth due, among other aspects, to the complexity of plant matrices. In this study, silver nanoparticles prepared with the aqueous extract of Mimosa albida leaves were used to assess their polyphenolic content and antioxidant capacity. Silver nanoparticles were characterized by different techniques. As a result, nanoparticles of 6.5 ± 3.1 nm were obtained. The total phenolic content in the extract was 1320.4 ± 17.6 mg of gallic acid equivalents GAE· 100 g⁻¹ and in the nanoparticles 257.3 ± 5.1 mg GAE· 100 g⁻¹. From the phenolic profile analyzed by ultra high-performance liquid chromatography (UPLC) with a diode-array detector (DAD), the presence of apigenin and luteolin in the plant extract is postulated. The antioxidant capacity measured by oxygen radical absorbance capacity ORAC-fluorescein assay was 86917 ± 6287 and 7563 ± 967 µmol ET g⁻¹ in the extract and nanoparticles respectively. Electrochemical analysis by cyclic voltammetry (CV) confirmed the effective reduction capacity of the Mimosa albida leaves extract to reduce Ag ions to AgNPs and differential pulse voltammetry (DPV) suggested the presence of two main reducing agents in the extract. From this study, it was concluded that the aqueous extract of Mimosa albida contains reducing agents capable of synthesizing silver nanoparticles, which can be used in the phytochemical industry.

Silver nanoparticles are recognized for their numerous physical, biological, and pharmaceutical applications. In the present study, the interaction of silver clusters with monosaccharide molecules is examined to identify which molecule works better as a reducing agent in the application of a green synthesis approach. Geometry optimization of clusters containing one, three, and five silver atoms is performed along with the optimization of α-d-glucose, α-d-ribose, d-erythrose, and glyceraldehyde using density functional theory. Optimized geometries allow identifying the interaction formed in the silver cluster and monosaccharide complexes. An electron localization function analysis is performed to further analyze the interaction found and explain the reduction process in the formation of silver nanoparticles. The overall results indicate that glyceraldehyde presents the best characteristics to serve as the most efficient reducing agent.

In this review, a timeline starting at the willow bark and ending in the latest discoveries of analgesic and anti-inflammatory drugs will be discussed. Furthermore, the chemical features of the different small organic molecules that have been used in pain management will be studied. Then, the mechanism of different types of pain will be assessed, including neuropathic pain, inflammatory pain, and the relationship found between oxidative stress and pain. This will include obtaining insights into the cyclooxygenase action mechanism of nonsteroidal anti-inflammatory drugs (NSAID) such as ibuprofen and etoricoxib and the structural difference between the two cyclooxygenase isoforms leading to a selective inhibition, the action mechanism of pregabalin and its use in chronic neuropathic pain, new theories and studies on the analgesic action mechanism of paracetamol and how changes in its structure can lead to better characteristics of this drug, and cannabinoid action mechanism in managing pain through a cannabinoid receptor mechanism. Finally, an overview of the different approaches science is taking to develop more efficient molecules for pain treatment will be presented.

Silver nanoparticles are recognized for numerous physical, biological, and pharmaceutical applications. Their main uses in the medical field comprise diagnostic and therapeutic applications. In this project, the interaction between silver nanoparticles and the lipid layer of the skin was studied in order to know how nanoparticles behave when they are in contact with the skin. Energies of the silver nanoparticles were calculated through the optimization of silver clusters using density functional theory implemented in the Gaussian program 09W. Biological molecules such as glucose, stearic acid, palmitic acid, and quercetin present in coated nanoparticles and in the skin were also optimized. The silver clusters containing 6 atoms were proven to be the most stable complexes. Moreover, a study of molecular orbital describing HOMO interactions of the clusters was performed showing that the electronic density was around the silver cluster. Molecular dynamics simulation was performed using Abalone program. Silver nanoparticles seemed to have very good clearance properties in our molecular dynamics simulation because over a certain period of time, the silver cluster got far away from the biological molecules.