Determination of cefotaxime, cefoperazone, ceftazidime and cefadroxil using surface plasmon resonance band of silver nanoparticles

The aim of this work is to evaluate simple, sensitive, effective and validated procedures for the determination of cefotaxime, cefoperazone, ceftazidime and cefadroxil. In this study, the methods based on the ability of the cited drugs to reduce Ag+ ions to silver nanoparticles (Ag-NPs) in the presence of Polyvinyl Pyrrolidone (PVP) as a stabilizing agent producing very intense surface plasmon resonance peak of Ag-NPs (λmax. = 410-430 nm). The plasmon absorbance of the Ag-NPs allows the quantitative spectrophotometric determination of the cited drugs. The calibration curves are linear with concentration ranges of 0.4-3.2, 1-8, 0.5-4.0 and 1.5-9.0 µg/mL for cefotaxime, cefoperazone, ceftazidime and cefadroxil, respectively. Apparent molar absorptivity, detection and quantitative limits are calculated. Applications of the proposed methods to representative pharmaceutical formulations are successfully presented. The extracellular synthesis of nanoparticles is fast, and the method doesn't require various elaborate treatments and tedious extraction procedures.

Titanium dioxide nanoparticles: some aspects of toxicity/focus on the development.

Nanosized titanium dioxide (TiO2) particles belong to the most widely manufactured nanoparticles (NPs) on a global scale because of their photocatalytic properties and the related surface effects. TiO2 NPs are in the top five NPs used in consumer products. Ultrafine TiO2 is widely used in the number of applications, including white pigment in paint, ceramics, food additive, food packaging material, sunscreens, cosmetic creams, and, component of surgical implants. Data evidencing rapid distribution, slow or ineffective elimination, and potential long-time tissue accumulation are especially important for the human risk assessment of ultrafine TiO2 and represent new challenges to more responsibly investigate potential adverse effects by the action of TiO2 NPs considering their ubiquitous exposure in various doses. Transport of ultrafine TiO2 particles in systemic circulation and further transition through barriers, especially the placental and blood-brain ones, are well documented. Therefore, from the developmental point of view, there is a raising concern in the exposure to TiO2 NPs during critical windows, in the pregnancy or the lactation period, and the fact that human mothers, women and men in fertile age and last but not least children may be exposed to high cumulative doses. In this review, toxicokinetics and particularly toxicity of TiO2 NPs in relation to the developing processes, oriented mainly on the development of the central nervous system, are discussed Keywords: nanoparticles, nanotoxicity, nanomaterials, titanium dioxide, reproductive toxicity, developmental toxicity, blood brain barrier, placental barrier.

Environmental life cycle assessment of nanosilver-enabled bandages.

Over 400 tons of silver nanoparticles (AgNPs) are produced annually, 30% of which are used in medical applications due to their antibacterial properties. The widespread use of AgNPs has implications over the entire life cycle of medical products, from production to disposal, including but not limited to environmental releases of nanomaterials themselves. Here a cradle-to-grave life cycle assessment from nanoparticle synthesis to end-of-life incineration was performed for a commercially available nanosilver-enabled medical bandage. Emissions were linked to multiple categories of environmental impacts, making primary use of the TRACI 2.1 impact assessment method, with specific consideration of nanosilver releases relative to all other (non-nanosilver) emissions. Modeling results suggest that (1) environmental impacts of AgNP synthesis are dominated by upstream electricity production, with the exception of life cycle ecotoxicity where the largest contributor is mining wastes, (2) AgNPs are the largest contributor to impacts of the bandage for all impact categories considered despite low AgNP loading, and (3) impacts of bandage production are several times those bandage incineration, including nanosilver releases to the environment. These results can be used to prioritize research and policy measures in order to improve the overall ecotoxicity burdens of nanoenabled products under a life cycle framework.

High-throughput screening for developability during early-stage antibody discovery using self-interaction nanoparticle spectroscopy.

The discovery of monoclonal antibodies (mAbs) that bind to a particular molecular target is now regarded a routine exercise. However, the successful development of mAbs that (1) express well, (2) elicit a desirable biological effect upon binding, and (3) remain soluble and display low viscosity at high concentrations is often far more challenging. Therefore, high throughput screening assays that assess self-association and aggregation early in the selection process are likely to yield mAbs with superior biophysical properties. Here, we report an improved version of affinity-capture self-interaction nanoparticle spectroscopy (AC-SINS) that is capable of screening large panels of antibodies for their propensity to self-associate. AC-SINS is based on concentrating mAbs from dilute solutions around gold nanoparticles pre-coated with polyclonal capture (e.g., anti-Fc) antibodies. Interactions between immobilized mAbs lead to reduced inter-particle distances and increased plasmon wavelengths (wavelengths of maximum absorbance), which can be readily measured by optical means. This method is attractive because it is compatible with dilute and unpurified mAb solutions that are typical during early antibody discovery. In addition, we have improved multiple aspects of this assay for increased throughput and reproducibility. A data set comprising over 400 mAbs suggests that our modified assay yields self-interaction measurements that are well-correlated with other lower throughput assays such as cross-interaction chromatography. We expect that the simplicity and throughput of our improved AC-SINS method will lead to improved selection of mAbs with excellent biophysical properties during early antibody discovery.

Selective detection of endotoxin using an impedance aptasensor with electrochemically deposited gold nanoparticles.

Using a single-stranded DNA (ssDNA) aptamer exhibiting high binding affinity (Kd = 12 nM) to endotoxin as a probe, an impedance sensor where aptamer-conjugated gold nanoparticles (AuNPs) were electrochemically deposited on a gold electrode was fabricated and its performance in regard to endotoxin detection assessed. AuNPs have been employed widely as biosensors because of their unique physical and chemical properties. In order to maximize the performance of the impedance aptasensor on endotoxin detection, some critical factors affecting aptamer conjugation to AuNPs and target recognition ability (i.e. concentrations of aptamer coupled with AuNPs, pH, ion strength and cation effect at the time of aptamer-endotoxin interaction) were optimized. Electrochemical impendence spectroscopy, cyclic voltametry, atomic force microscope, scanning electron microscope and quartz crystal microbalance were employed to characterize all the modification/detection procedures during the sensor fabrication. The developed aptasensor showed a broad linear dynamic detection range (0.01-10.24 ng/ml) with a very low detection limit for endotoxin (0.005 ng/ml), despite the presence of several biomolecules (e.g. plasmid DNA, RNA, serum albumin, Glc and sucrose) known to interfere with other endotoxin assays. The demonstrated aptasensor required a detection time of only 10 min, providing a simple and fast analytical method to specifically detect endotoxin from complex biological liqors.

The use of Bayesian networks for nanoparticle risk forecasting: model formulation and baseline evaluation.

We describe the use of Bayesian networks as a tool for nanomaterial risk forecasting and develop a baseline probabilistic model that incorporates nanoparticle specific characteristics and environmental parameters, along with elements of exposure potential, hazard, and risk related to nanomaterials. The baseline model, FINE (Forecasting the Impacts of Nanomaterials in the Environment), was developed using expert elicitation techniques. The Bayesian nature of FINE allows for updating as new data become available, a critical feature for forecasting risk in the context of nanomaterials. The specific case of silver nanoparticles (AgNPs) in aquatic environments is presented here (FINE(AgNP)). The results of this study show that Bayesian networks provide a robust method for formally incorporating expert judgments into a probabilistic measure of exposure and risk to nanoparticles, particularly when other knowledge bases may be lacking. The model is easily adapted and updated as additional experimental data and other information on nanoparticle behavior in the environment become available. The baseline model suggests that, within the bounds of uncertainty as currently quantified, nanosilver may pose the greatest potential risk as these particles accumulate in aquatic sediments.

Estimating production data for five engineered nanomaterials as a basis for exposure assessment.

The magnitude of engineered nanomaterials (ENMs) being produced and potentially released to the environment is a crucial and thus far unknown input to exposure assessment. This work estimates upper and lower bound annual United States production quantities for 5 classes of ENMs. A variety of sources were culled to identify companies producing source ENM products and determine production volumes. Using refining assumptions to attribute production levels from companies with more reliable estimates to companies with little to no data, ranges of U.S. production quantities were projected for each of the 5 ENMs. The quality of data is also analyzed; the percentage of companies for which data were available (via Web sites, patents, or direct communication) or unavailable (and thus extrapolated from other companies' data) is presented.

New opportunities: the use of nanotechnologies to manipulate and track stem cells.

Nanotechnologies are emerging platforms that could be useful in measuring, understanding, and manipulating stem cells. Examples include magnetic nanoparticles and quantum dots for stem cell labeling and in vivo tracking; nanoparticles, carbon nanotubes, and polyplexes for the intracellular delivery of genes/oligonucleotides and protein/peptides; and engineered nanometer-scale scaffolds for stem cell differentiation and transplantation. This review examines the use of nanotechnologies for stem cell tracking, differentiation, and transplantation. We further discuss their utility and the potential concerns regarding their cytotoxicity.