Survey on batch-to-batch variation in spray paints: a collaborative study.

This study represents the most extensive analysis of batch-to-batch variations in spray paint samples to date. The survey was performed as a collaborative project of the ENFSI (European Network of Forensic Science Institutes) Paint and Glass Working Group (EPG) and involved 11 laboratories. Several studies have already shown that paint samples of similar color but from different manufacturers can usually be differentiated using an appropriate analytical sequence. The discrimination of paints from the same manufacturer and color (batch-to-batch variations) is of great interest and these data are seldom found in the literature. This survey concerns the analysis of batches from different color groups (white, papaya (special shade of orange), red and black) with a wide range of analytical techniques and leads to the following conclusions. Colored batch samples are more likely to be differentiated since their pigment composition is more complex (pigment mixtures, added pigments) and therefore subject to variations. These variations may occur during the paint production but may also occur when checking the paint shade in quality control processes. For these samples, techniques aimed at color/pigment(s) characterization (optical microscopy, microspectrophotometry (MSP), Raman spectroscopy) provide better discrimination than techniques aimed at the organic (binder) or inorganic composition (fourier transform infrared spectroscopy (FTIR) or elemental analysis (SEM - scanning electron microscopy and XRF - X-ray fluorescence)). White samples contain mainly titanium dioxide as a pigment and the main differentiation is based on the binder composition (CH stretches) detected either by FTIR or Raman. The inorganic composition (elemental analysis) also provides some discrimination. Black samples contain mainly carbon black as a pigment and are problematic with most of the spectroscopic techniques. In this case, pyrolysis-GC/MS represents the best technique to detect differences. Globally, Py-GC/MS may show a high potential of discrimination on all samples but the results are highly dependent on the specific instrumental conditions used. Finally, the discrimination of samples when data was interpreted visually as compared to statistically using principal component analysis (PCA) yielded very similar results. PCA increases sensitivity and could perform better on specific samples, but one first has to ensure that all non-informative variation (baseline deviation) is eliminated by applying correct pre-treatments. Statistical treatments can be used on a large data set and, when combined with an expert's opinion, will provide more objective criteria for decision making.

Characteristics of fibers formed by cytochrome c and induced by anionic phospholipids.

Recent publications described the formation of millimeter-length fibers by diverse lipid-binding proteins (e.g., histone H1, cytochrome c, indolicidin, and endostatin) when they are mixed with 80:20 phosphatidylcholine/phosphatidylserine vesicles. Further, these fibers displayed amyloid characteristics when stained with Congo Red. In the study presented here, we found by FTIR the amide I absorption band to reveal significant variation in fibers formed by cytochrome c, with some consisting of cytochrome c in a nativelike conformation and some exhibiting strong amyloid (beta-sheet) characteristics. Protein structure also varied from amyloid to nearly native within single fibers. Fibers were frequently blue or bluish and sometimes iridescent, likely due to interference of light in the fibers. The amyloid-type amide I band was observed for blue fibers only. AFM shows that fibers consist of smaller 3-4 nm diameter fibers with 10 nm lateral spacing.