An exploratory analysis of multiple mutation spectra

A hybrid PCA-CART-MARS-based prognostic approach of the remaining useful life for aircraft engines

Prognostics is an engineering discipline that predicts the future health of a system. In this research work, a data-driven approach for prognostics is proposed. Indeed, the present paper describes a data-driven hybrid model for the successful prediction of the remaining useful life of aircraft engines. The approach combines the multivariate adaptive regression splines (MARS) technique with the principal component analysis (PCA), dendrograms and classification and regression trees (CARTs). Elements extracted from sensor signals are used to train this hybrid model, representing different levels of health for aircraft engines. In this way, this hybrid algorithm is used to predict the trends of these elements. Based on this fitting, one can determine the future health state of a system and estimate its remaining useful life (RUL) with accuracy. To evaluate the proposed approach, a test was carried out using aircraft engine signals collected from physical sensors (temperature, pressure, speed, fuel flow, etc.). Simulation results show that the PCA-CART-MARS-based approach can forecast faults long before they occur and can predict the RUL. The proposed hybrid model presents as its main advantage the fact that it does not require information about the previous operation states of the input variables of the engine. The performance of this model was compared with those obtained by other benchmark models (multivariate linear regression and artificial neural networks) also applied in recent years for the modeling of remaining useful life. Therefore, the PCA-CART-MARS-based approach is very promising in the field of prognostics of the RUL for aircraft engines.

Genomics and ethics: the case of cloned and/or transgenic animals

The point of the present study is to illustrate and, if possible, promote the existing link between genomics and ethics, taking the example of cloned and transgenic animals. These ‘new animals’ raise theoretical and practical problems that concern applied ethics. We will explore more particularly an original strategy showing that it is possible, starting from philosophical questioning about the nature of identity, to use a genomic approach, based on amplification fragment length polymorphism (AFLP) and methylation-sensitive amplification polymorphism (MSAP) detection, to provide useful tools to define more rigorously what cloned animals are, by testing their genetic and epigenetic identity. We expect from the future results of this combined approach to stimulate the creativity of the philosophical and ethical reflection about the impact of biotechnology on animals, and to increase scientific involvement in such issues.

Structural and functional analysis of mutations at the human hypoxanthine phosphoribosyl transferase (HPRT1) locus

Hypoxanthine phosphoribosyl transferase (HPRT, also known as HGPRT) is an often-used genetic marker in eukaryotic cells. The gene is conserved from bacteria to human, with retained catalytic activity, although substrate specificity may have changed, and the enzyme is essential in malaria-causing protozoans. Inherited mutations in the human HPRT1 gene result in three different phenotypes: Lesch-Nyhan syndrome (LNS or LND), LND variants, and HPRT-related hyperuricemia (HRH). In cultured cells, loss of HPRT activity gives rise to 6-thioguanine (6-TG) resistance. In general, cells from LND patients are also 6-TG resistant, whereas cells from HRH patients are not, with some interesting exceptions. Using modeling methods, we have studied the correlation between the mutable and nonmutated amino acid residues on one hand, and sequence conservation and predicted phenotypic effects on the other hand. Our results demonstrate that most of the mutations are explainable by the predicted effect on protein structure and function. They are also consistent with sequence conservation. Moreover, the mutational profiles of TG-resistant cells and LND overlap to a great extent, while most of the mutations in HRH are unique to that condition. We have also noticed a strong correlation between mutations in the tetramer interfaces and observed phenotypes, suggesting a functional role for a tetramer transition during catalysis.

Theoretical analysis of mutation hotspots and their DNA sequence context specificity

Mutation frequencies vary significantly along nucleotide sequences such that mutations often concentrate at certain positions called hotspots. Mutation hotspots in DNA reflect intrinsic properties of the mutation process, such as sequence specificity, that manifests itself at the level of interaction between mutagens, DNA, and the action of the repair and replication machineries. The hotspots might also reflect structural and functional features of the respective DNA sequences. When mutations in a gene are identified using a particular experimental system, resulting hotspots could reflect the properties of the gene product and the mutant selection scheme. Analysis of the nucleotide sequence context of hotspots can provide information on the molecular mechanisms of mutagenesis. However, the determinants of mutation frequency and specificity are complex, and there are many analytical methods for their study. Here we review computational approaches for analyzing mutation spectra (distribution of mutations along the target genes) that include many mutable (detectable) positions. The following methods are reviewed: derivation of a consensus sequence, application of regression approaches to correlate nucleotide sequence features with mutation frequency, mutation hotspot prediction, analysis of oligonucleotide composition of regions containing mutations, pairwise comparison of mutation spectra, analysis of multiple spectra, and analysis of "context-free" characteristics. The advantages and pitfalls of these methods are discussed and illustrated by examples from the literature. The most reliable analyses were obtained when several methods were combined and information from theoretical analysis and experimental observations was considered simultaneously. Simple, robust approaches should be used with small samples of mutations, whereas combinations of simple and complex approaches may be required for large samples. We discuss several well-documented studies where analysis of mutation spectra has substantially contributed to the current understanding of molecular mechanisms of mutagenesis. The nucleotide sequence context of mutational hotspots is a fingerprint of interactions between DNA and DNA repair, replication, and modification enzymes, and the analysis of hotspot context provides evidence of such interactions.