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The feasibility of the use of piezoelectric drop-on-demand inkjet printing to prepare test materials for trace explosive analysis is demonstrated. RDX (1,3,5-trinitro-1,3,5 triazcyclohexane) was formulated into inkjet printable solutions and jetted onto substrates suitable for calibration of the ion mobility spectrometry (IMS) instruments currently deployed worldwide for contraband screening. Gravimetric analysis, gas chromatography/mass spectrometry (GC/MS), and ultraviolet-visible (UV-vis) absorption spectroscopy were used to verify inkjet printer solution concentrations and the quantity of explosive dispensed onto test materials. Reproducibility of the inkjet printing process for mass deposition of the explosive RDX (1,3,5-trinitro-1,3,5 triazcyclohexane) was determined to be better than 2% for a single day of printing and better than 3% day-to-day. 10.1021/ac101439r

In order to utilize complementary imaging techniques to supply higher resolution data for fusion with secondary ion mass spectrometry (SIMS) chemical images, there are a number of aspects that, if not given proper consideration, could produce results which are easy to misinterpret. One of the most critical aspects is that the two input images must be of the same exact analysis area. With the desire to explore new higher resolution data sources that exists outside of the mass spectrometer, this requirement becomes even more important. To ensure that two input images are of the same region, an implementation of the insight segmentation and registration toolkit (ITK) was developed to act as a preprocessing step before performing image fusion. This implementation of ITK allows for several degrees of movement between two input images to be accounted for, including translation, rotation, and scale transforms. First, the implementation was confirmed to accurately register two multimodal images by supplying a known transform. Once validated, two model systems, a copper mesh grid and a group of RAW 264.7 cells, were used to demonstrate the use of the ITK implementation to register a SIMS image with a microscopy image for the purpose of performing image fusion. [ABSTRACT FROM AUTHOR]

To achieve successful drug delivery via nanoparticles the interactions between the nanoparticle and the chemistry of the surrounding biological environment is of central importance. A thorough understanding of these interactions is necessary in order to better elucidate information regarding drug pathways and mechanisms of action in treatment protocols. As such, it is important to identify the location of the nanoparticle, the state of its functionalization, as well as any changes in the cellular environment. The use of cluster secondary ion mass spectrometry (SIMS) using C60+ primary ions makes simultaneous acquisition of this information possible. Here, SIMS has been successfully used to chemically image gold nanoparticles (AuNPs) within a model, single cell system involving macrophage-like RAW 264.7 cells. The macrophage-like properties of this cell line make it extremely well-suited for cell-uptake studies. Both AuNPs and two pharmaceutical compounds, amiodarone and elacridar, were successfully imaged within a cellular system using cluster SIMS. To verify that SIMS can also be used to detect functionalization and nanoparticles simultaneously, fluorophore-functionalized AuNPs were studied as a model system. The fluorescent characteristics of these functionalized nanoparticles enabled the visual confirmation of the presence and location of the particles within the cell. [ABSTRACT FROM AUTHOR]

Gas cluster ion beam-secondary ion mass spectrometry (GCIB-SIMS) has shown the full potential of mapping intact lipids in biological systems with better than 10 μm lateral resolution. This study investigated further the capability of GCIB-SIMS in imaging high-mass signals from intact cardiolipin (CL) and gangliosides in normal brain and the effect of a controlled cortical impact model (CCI) of traumatic brain injury (TBI) on their distribution. A combination of enzymatic and chemical treatments was employed to suppress the signals from the most abundant phospholipids (phosphatidylcholine (PC) and phosphatidylethanolamine (PE)) and enhance the signals from the low-abundance CLs and gangliosides to allow their GCIB-SIMS detection at 8 and 16 μm spatial resolution. Brain CLs have not been observed previously using other contemporary imaging mass spectrometry techniques at better than 50 μm spatial resolution. High-resolution images of naive and injured brain tissue facilitated the comparison of CL species across three multicell layers in the CA1, CA3, and DG regions of the hippocampus. GCIB-SIMS also reliably mapped losses of oxidizable polyunsaturated CL species (but not the oxidation-resistant saturated and monounsaturated gangliosides) to regions including the CA1 and CA3 of the hippocampus after CCI. This work extends the detection range for SIMS measurements of intact lipids to above m/z 2000, bridging the mass range gap compared with MALDI. Further advances in high-resolution SIMS of CLs, with the potential for single cell or supra-cellular imaging, will be essential for the understanding of CL's functional and structural organization in normal and injured brain.

To achieve successful drug delivery via nanoparticles the interactions between the nanoparticle and the chemistry of the surrounding biological environment is of central importance. A thorough understanding of these interactions is necessary in order to better elucidate information regarding drug pathways and mechanisms of action in treatment protocols. As such, it is important to identify the location of the nanoparticle, the state of its functionalization, as well as any changes in the cellular environment. The use of cluster secondary ion mass spectrometry (SIMS) using C60 (+) primary ions makes simultaneous acquisition of this information possible. Here, SIMS has been successfully used to chemically image gold nanoparticles (AuNPs) within a model, single cell system involving macrophage-like RAW 264.7 cells. The macrophage-like properties of this cell line make it extremely well-suited for cell-uptake studies. Both AuNPs and two pharmaceutical compounds, amiodarone and elacridar, were successfully imaged within a cellular system using cluster SIMS. To verify that SIMS can also be used to detect functionalization and nanoparticles simultaneously, fluorophore-functionalized AuNPs were studied as a model system. The fluorescent characteristics of these functionalized nanoparticles enabled the visual confirmation of the presence and location of the particles within the cell.

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is an emerging technique for the characterization of biological systems. With the development of novel ion sources such as cluster ion beams, ionization efficiency has been increased, allowing for greater amounts of information to be obtained from the sample of interest. This enables the plotting of the distribution of chemical compounds against position with submicrometer resolution, yielding a chemical map of the material. In addition, by combining imaging with molecular depth profiling, a complete 3-dimensional rendering of the object is possible. The study of single biological cells presents significant challenges due to the fundamental complexity associated with any biological material. Sample preparation is of critical importance in controlling this complexity, owing to the fragile nature of biological cells and to the need to characterize them in their native state, free of chemical or physical changes. Here, we describe the four most widely used sample preparation methods for cellular imaging using ToF-SIMS, and provide guidance for data collection and analysis procedures.

A major limitation of SIMS studies of cells is the limited number of molecules available for detection. This study examines the possibility of utilizing a molecular tag which is easily identifiable using SIMS and does not interfere with the mass spectra of commonly identified cellular components, to aid in the visualization of specific cellular organelles. Here, a fluorescent, nuclear stain (Hoechst 33342) was used to allow for verification of the staining protocols prior to SIMS analysis. The stain was successfully chemically imaged within the nuclear region of a glutaraldehyde fixed bovine aortic endothelial cell. The ability to chemically map a larger variety of organelles and cellular components will allow for further possible study of a greater number of biological pathways and processes, as well as make cell-drug studies more feasible using SIMS.

Background: Bladder exstrophy (BE) and cloacal exstrophy (CE) are rare birth defects that have been reported to occur in 1:30,000-50,000 and 1:200,000-400,000 live births. Disagreement exists as to whether they comprise two distinct disorders or are part of a spectrum. We examined epidemiologic trends and risk factors for BE and CE in a large population-based dataset., Methods: Potential cases were identified in the New York State (NYS) Congenital Malformations Registry. When nonspecific codes for CE were reported, narrative descriptions were reviewed for classification. Birth certificate data were analyzed with descriptive statistics and Poisson regression was used to calculate crude (PR) and adjusted prevalence ratios (aPR) and 95% confidence intervals (CI)., Results: In NYS from 1983 through 1999, 95 BE cases and 29 CE cases were identified for a live-birth prevalence of 2.1 and 0.6 per 100,000 live births. BE showed a statistically significant downward linear trend by year. Factors associated with BE included summer conception (vs. winter, aPR 2.46, CI 1.19-5.10), white, non-Hispanic maternal race/ethnicity (vs. black non-Hispanic, aPR 3.20, CI 1.20-8.52), and male sex (female vs. male, aPR 0.53, CI 0.33-0.87). Factors associated with CE included preterm low birth weight birth (aPR 14.55, CI 5.28-40.07), multiple birth (aPR 6.68, CI 1.19-23.27), non-New York City residence (aPR 3.27, CI 1.04-10.22), and female sex (aPR 2.57, CI 1.00-6.64). Infant mortality was greater in the CE group., Conclusions: The epidemiology suggests different risk factor patterns for BE and CE. Classification of BE and CE is difficult due to the nonspecific coding.