Forensic examination of ink by high-performance thin layer chromatography - The United States Secret Service Digital Ink Library

Forensic examinations of ink have been performed since the beginning of the 20th century. Since the 1960s, the International Ink Library, maintained by the United States Secret Service, has supported those analyses. Until 2009, the search and identification of inks were essentially performed manually. This paper describes the results of a project designed to improve ink samples' analytical and search processes. The project focused on the development of improved standardization procedures to ensure the best possible reproducibility between analyses run on different HPTLC plates. The successful implementation of this new calibration method enabled the development of mathematical algorithms and of a software package to complement the existing ink library.

Positional scanning-synthetic peptide library-based analysis of self- and pathogen-derived peptide cross-reactivity with tumor-reactive Melan-A-specific CTL.

Synthetic combinatorial peptide libraries in positional scanning format (PS-SCL) have recently emerged as a useful tool for the analysis of T cell recognition. This includes identification of potentially cross-reactive sequences of self or pathogen origin that could be relevant for the understanding of TCR repertoire selection and maintenance, as well as of the cross-reactive potential of Ag-specific immune responses. In this study, we have analyzed the recognition of sequences retrieved by using a biometric analysis of the data generated by screening a PS-SCL with a tumor-reactive CTL clone specific for an immunodominant peptide from the melanocyte differentiation and tumor-associated Ag Melan-A. We found that 39% of the retrieved peptides were recognized by the CTL clone used for PS-SCL screening. The proportion of peptides recognized was higher among those with both high predicted affinity for the HLA-A2 molecule and high predicted stimulatory score. Interestingly, up to 94% of the retrieved peptides were cross-recognized by other Melan-A-specific CTL. Cross-recognition was at least partially focused, as some peptides were cross-recognized by the majority of CTL. Importantly, stimulation of PBMC from melanoma patients with the most frequently recognized peptides elicited the expansion of heterogeneous CD8(+) T cell populations, one fraction of which cross-recognized Melan-A. Together, these results underline the high predictive value of PS-SCL for the identification of sequences cross-recognized by Ag-specific T cells.

ROBETH: un logiciel pour les procédés statistiques robustes [ROBETH: a library for robust statistical procedures].

In the past 20 years the theory of robust estimation has become an important topic of mathematical statistics. We discuss here some basic concepts of this theory with the help of simple examples. Furthermore we describe a subroutine library for the application of robust statistical procedures, which was developed with the support of the Swiss National Science Foundation.

Automated scoring of AFLPs using RawGeno v 2.0, a free R CRAN library.

Amplified Fragment Length Polymorphisms (AFLPs) are a cheap and efficient protocol for generating large sets of genetic markers. This technique has become increasingly used during the last decade in various fields of biology, including population genomics, phylogeography, and genome mapping. Here, we present RawGeno, an R library dedicated to the automated scoring of AFLPs (i.e., the coding of electropherogram signals into ready-to-use datasets). Our program includes a complete suite of tools for binning, editing, visualizing, and exporting results obtained from AFLP experiments. RawGeno can either be used with command lines and program analysis routines or through a user-friendly graphical user interface. We describe the whole RawGeno pipeline along with recommendations for (a) setting the analysis of electropherograms in combination with PeakScanner, a program freely distributed by Applied Biosystems; (b) performing quality checks; (c) defining bins and proceeding to scoring; (d) filtering nonoptimal bins; and (e) exporting results in different formats.

Combinatorial peptide library-based identification of peptide ligands for tumor-reactive cytolytic T lymphocytes of unknown specificity.

A novel approach for the identification of tumor antigen-derived sequences recognized by CD8(+) cytolytic T lymphocytes (CTL) consists in using synthetic combinatorial peptide libraries. Here we have screened a library composed of 3.1 x 10(11) nonapeptides arranged in a positional scanning format, in a cytotoxicity assay, to search the antigen recognized by melanoma-reactive CTL of unknown specificity. The results of this analysis enabled the identification of several optimal peptide ligands, as most of the individual nonapeptides deduced from the primary screening were efficiently recognized by the CTL. The results of the library screening were also analyzed with a mathematical approach based on a model of independent and additive contribution of individual amino acids to antigen recognition. This biometrical data analysis enabled the retrieval, in public databases, of the native antigenic peptide SSX-2(41-49), whose sequence is highly homologous to the ones deduced from the library screening, among the ones with the highest stimulatory score. These results underline the high predictive value of positional scanning synthetic combinatorial peptide library analysis and encourage its use for the identification of CTL ligands.