National Institute of Standards and Technology

About: National Institute of Standards and Technology is a government organization based out in Gaithersburg, Maryland, United States. It is known for research contribution in the topics: Laser & Scattering. The organization has 26667 authors who have published 60661 publications receiving 2215547 citations. The organization is also known as: National Bureau of Standards & NIST.

Relation between the redox state of iron-based nanoparticles and their cytotoxicity toward Escherichia coli.

Abstract: Iron-based nanoparticles have been proposed for an increasing number of biomedical or environmental applications although in vitro toxicity has been observed. The aim of this study was to understand the relationship between the redox state of iron-based nanoparticles and their cytotoxicity toward a Gram-negative bacterium, Escherichia coli. While chemically stable nanoparticles (γFe2O3) have no apparent cytotoxicity, nanoparticles containing ferrous and, particularly, zerovalent iron are cytotoxic. The cytotoxic effects appear to be associated principally with an oxidative stress as demonstrated using a mutant strain of E. coli completely devoid of superoxide dismutase activity. This stress can result from the generation of reactive oxygen species with the interplay of oxygen with reduced iron species (FeII and/or Fe0) or from the disturbance of the electronic and/or ionic transport chains due to the strong affinity of the nanoparticles for the cell membrane.

Development and validation of a spectral library searching method for peptide identification from MS/MS.

Abstract: A notable inefficiency of shotgun proteomics experiments is the repeated rediscovery of the same identifiable peptides by sequence database searching methods, which often are time-consuming and error-prone. A more precise and efficient method, in which previously observed and identified peptide MS/MS spectra are catalogued and condensed into searchable spectral libraries to allow new identifications by spectral matching, is seen as a promising alternative. To that end, an open-source, functionally complete, high-throughput and readily extensible MS/MS spectral searching tool, SpectraST, was developed. A high-quality spectral library was constructed by combining the high-confidence identifications of millions of spectra taken from various data repositories and searched using four sequence search engines. The resulting library consists of over 30,000 spectra for Saccharomyces cerevisiae. Using this library, SpectraST vastly outperforms the sequence search engine SEQUEST in terms of speed and the ability to discriminate good and bad hits. A unique advantage of SpectraST is its full integration into the popular Trans Proteomic Pipeline suite of software, which facilitates user adoption and provides important functionalities such as peptide and protein probability assignment, quantification, and data visualization. This method of spectral library searching is especially suited for targeted proteomics applications, offering superior performance to traditional sequence searching.

IARPA Janus Benchmark - C: Face Dataset and Protocol

Abstract: Although considerable work has been done in recent years to drive the state of the art in facial recognition towards operation on fully unconstrained imagery, research has always been restricted by a lack of datasets in the public domain In addition, traditional biometrics experiments such as single image verification and closed set recognition do not adequately evaluate the ways in which unconstrained face recognition systems are used in practice The IARPA Janus Benchmark–C (IJB-C) face dataset advances the goal of robust unconstrained face recognition, improving upon the previous public domain IJB-B dataset, by increasing dataset size and variability, and by introducing end-to-end protocols that more closely model operational face recognition use cases IJB-C adds 1,661 new subjects to the 1,870 subjects released in IJB-B, with increased emphasis on occlusion and diversity of subject occupation and geographic origin with the goal of improving representation of the global population Annotations on IJB-C imagery have been expanded to allow for further covariate analysis, including a spatial occlusion grid to standardize analysis of occlusion Due to these enhancements, the IJB-C dataset is significantly more challenging than other datasets in the public domain and will advance the state of the art in unconstrained face recognition