Direct analysis of volatile organic compounds in foods by headspace extraction atmospheric pressure chemical ionisation mass spectrometry

Rationale The rapid screening of volatile organic compounds (VOCs) by direct analysis has potential applications in the areas of food and flavour science. Currently the technique of choice for VOC analysis is gas chromatography-mass spectrometry (GC/MS). However, the long chromatographic run times and elaborate sample preparation associated with this technique has led a movement towards direct analysis techniques, such as selected ion flow tube mass spectrometry (SIFT-MS), proton transfer reaction mass spectrometry (PTR-MS) and electronic noses. The work presented here describes the design and construction of a Venturi jet-pump based modification for a compact mass spectrometer which enables the direct introduction of volatiles for qualitative and quantitative analysis. Methods Volatile organic compounds were extracted from the headspace of heated vials into the atmospheric pressure chemical ionization source of a quadrupole mass spectrometer using a Venturi pump. Samples were analysed directly with no prior sample preparation. Principal component analysis was used to differentiate between different classes of samples. Results The interface is shown to able to routinely detect problem analytes such as fatty acids and biogenic amines without the requirement of a derivatisation step, and is shown to be able to discriminate between four different varieties of cheese with good intra and inter-day reproducibility using an unsupervised principal component analysis model. Quantitative analysis is demonstrated using indole standards with limits of detection and quantification of 0.395 µg/ml and 1.316 µg/ml respectively, and then applied to measure indole in aged pork samples. Conclusions The methodology described has shown to be able to routinely detect highly reactive analytes such as volatile fatty acids and diamines without the need for a derivatisation step or lengthy chromatographic separations. The capability of the system is demonstrated by discriminating between different varieties of cheese and monitoring the spoilage of meats

Additional file 1: Supplementary material. of A 3D in vitro model of the human breast duct: a method to unravel myoepithelial-luminal interactions in the progression of breast cancer

Figure S1. Promoter efficacy in primary cultures of myoepithelial and luminal cells. a Representative images of GFP expression in myoepithelial and luminal cells 48 h following infection with neuraminidase-treated lentiviral particles driving GFP expression under either human/mouse CMV, human/mouse EF1α, CAG, PGK and UBC promoters. Scale bar = 20 μm. b Mean fluorescence intensity (MFI) values of myoepithelial and luminal cells 48 h post-infection with lentiviral particles as in (a). Images and values are representative of cells derived from two donors. Figure S2. Spheroids formed in Matrigel cultures express markers of both luminal and myoepithelial cells. Expression of cytokeratin (CK) 8 and P-cadherin in spheroids formed in Matrigel from co-culture of isolated myoepithelial and luminal cells over 21 days. Images are representative of cells derived from at least three donors. Scale bar = 20 μm. Figure S3. Objective and systematic calculation of cell and spheroid volumes. Representative workflow of spheroid analysis. Raw DAPI z-sections (a) are converted into greyscale images and a greyscale distribution profile (b). Greyscale images are then converted to binary images using a calculated threshold to indicate cell presence (c). The pixels that indicate cells are then translated into a geometrically accurate point cloud using the known image resolutions (d). Further post-processing using density-based spatial clustering of applications with noise (DBSCAN) is performed to identify the main body of cells (e). The point cloud representing the main spheroid is then extracted (f). The alpha-shape algorithm is applied using thresholds set as a function of the image resolutions to form triangulated bodies that represent the cells and body (g). The volumes of these bodies are then calculated alongside the resultant cell/body ratio. (PDF 1342 kb

Additional file 1: Table S1. of Loss of MMP-8 in ductal carcinoma in situ (DCIS)-associated myoepithelial cells contributes to tumour promotion through altered adhesive and proteolytic function

Summary of breast tissue examined for MMP8. (DOC 27 kb

Additional file 5: Figure S3. of Loss of MMP-8 in ductal carcinoma in situ (DCIS)-associated myoepithelial cells contributes to tumour promotion through altered adhesive and proteolytic function

(i) Densitometry quantifying pSMAD2 versus tSMAD2 normalised to the loading control. MECs transfected with MMP-8 WT show a marked reduction of pSMAD2 compared to Empty Vector and MMP-8 EA at 5 minutes. (ii) Densitometry quantifying pSMAD2 versus tSMAD2 normalised to the loading control. MECs transfected with siRNA to MMP-8 demonstrated a markedly stronger pSMAD2 signal compared to control siRNA (siLUC). (TIF 336 kb

Space Telescope and Optical Reverberation Mapping Project. VII. Understanding the UV anomaly in NGC 5548 with X-Ray Spectroscopy

During the Space Telescope and Optical Reverberation Mapping Project (STORM) observations of NGC 5548, the continuum and emission-line variability became decorrelated during the second half of the 6-month long observing campaign. Here we present Swift and Chandra X-ray spectra of NGC 5548 obtained as a part of the campaign. The Swift spectra show that excess flux (relative to a power-law continuum) in the soft X-ray band appears before the start of the anomalous emission-line behavior, peaks during the period of the anomaly, and then declines. This is a model-independent result suggesting that the soft excess is related to the anomaly. We divide the Swift data into on- and off-anomaly spectra to characterize the soft excess via spectral fitting. The cause of the spectral differences is likely due to a change in the intrinsic spectrum rather than being due to variable obscuration or partial covering. The Chandra spectra have lower signal-to-noise ratios, but are consistent with Swift data. Our preferred model of the soft excess is emission from an optically thick, warm Comptonizing corona, the effective optical depth of which increases during the anomaly. This model simultaneously explains all the three observations: the UV emission line flux decrease, the soft-excess increase, and the emission line anomaly