Biomedical subjects

Dominique de Seny

Publications and source records attributed to Dominique de Seny.

3 recordsLinked to original sources

PubMed2005

Proteomic mass spectra classification using decision tree based ensemble methods.

MOTIVATION: Modern mass spectrometry allows the determination of proteomic fingerprints of body fluids like serum, saliva or urine. These measurements can be used in many medical applications in order to diagnose the current state or predict the evolution of a disease. Recent developments in machine learning allow one to exploit such datasets, characterized by small numbers of very high-dimensional samples. RESULTS: We propose a systematic approach based on decision tree ensemble methods, which is used to automatically determine proteomic biomarkers and predictive models. The approach is validated on two datasets of surface-enhanced laser desorption/ionization time of flight measurements, for the diagnosis of rheumatoid arthritis and inflammatory bowel diseases. The results suggest that the methodology can handle a broad class of similar problems.

Algorithms↗

PubMed2005

Discovery of new rheumatoid arthritis biomarkers using the surface-enhanced laser desorption/ionization time-of-flight mass spectrometry ProteinChip approach.

OBJECTIVE: To identify serum protein biomarkers specific for rheumatoid arthritis (RA), using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technology. METHODS: A total of 103 serum samples from patients and healthy controls were analyzed. Thirty-four of the patients had a diagnosis of RA, based on the American College of Rheumatology criteria. The inflammation control group comprised 20 patients with psoriatic arthritis (PsA), 9 with asthma, and 10 with Crohn's disease. The noninflammation control group comprised 14 patients with knee osteoarthritis and 16 healthy control subjects. Serum protein profiles were obtained by SELDI-TOF-MS and compared in order to identify new biomarkers specific for RA. Data were analyzed by a machine learning algorithm called decision tree boosting, according to different preprocessing steps. RESULTS: The most discriminative mass/charge (m/z) values serving as potential biomarkers for RA were identified on arrays for both patients with RA versus controls and patients with RA versus patients with PsA. From among several candidates, the following peaks were highlighted: m/z values of 2,924 (RA versus controls on H4 arrays), 10,832 and 11,632 (RA versus controls on CM10 arrays), 4,824 (RA versus PsA on H4 arrays), and 4,666 (RA versus PsA on CM10 arrays). Positive results of proteomic analysis were associated with positive results of the anti-cyclic citrullinated peptide test. Our observations suggested that the 10,832 peak could represent myeloid-related protein 8. CONCLUSION: SELDI-TOF-MS technology allows rapid analysis of many serum samples, and use of decision tree boosting analysis as the main statistical method allowed us to propose a pattern of protein peaks specific for RA.

Adult↗

PubMed2002

Mutational analysis of the two zinc-binding sites of the Bacillus cereus 569/H/9 metallo-beta-lactamase.

The metallo-beta-lactamase BcII from Bacillus cereus 569/H/9 possesses a binuclear zinc centre. The mono-zinc form of the enzyme displays an appreciably high activity, although full efficiency is observed for the di-zinc enzyme. In an attempt to assign the involvement of the different zinc ligands in the catalytic properties of BcII, individual substitutions of selected amino acids were generated. With the exception of His(116)-->Ser (H116S), C221A and C221S, the mono- and di-zinc forms of all the other mutants were poorly active. The activity of H116S decreases by a factor of 10 when compared with the wild type. The catalytic efficiency of C221A and C221S was zinc-dependent. The mono-zinc forms of these mutants exhibited a low activity, whereas the catalytic efficiency of their respective di-zinc forms was comparable with that of the wild type. Surprisingly, the zinc contents of the mutants and the wild-type BcII were similar. These data suggest that the affinity of the beta-lactamase for the metal was not affected by the substitution of the ligand. The pH-dependence of the H196S catalytic efficiency indicates that the zinc ions participate in the hydrolysis of the beta-lactam ring by acting as a Lewis acid. The zinc ions activate the catalytic water molecule, but also polarize the carbonyl bond of the beta-lactam ring and stabilize the development of a negative charge on the carbonyl oxygen of the tetrahedral reaction intermediate. Our studies also demonstrate that Asn(233) is not directly involved in the interaction with the substrates.

Bacillus cereus↗