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See detailAutomatic localization of interest points in zebrafish images with tree-based methods
Stern, Olivier ULg; Marée, Raphaël ULg; Aceto, Jessica ULg et al

in Proceedings of the 6th IAPR International Conference on Pattern Recognition in Bioinformatics (2011)

In many biological studies, scientists assess effects of experimental conditions by visual inspection of microscopy images. They are able to observe whether a protein is expressed or not, if cells are ... [more ▼]

In many biological studies, scientists assess effects of experimental conditions by visual inspection of microscopy images. They are able to observe whether a protein is expressed or not, if cells are going through normal cell cycles, how organisms evolve in different experimental conditions, etc. But, with the large number of images acquired in high-throughput experiments, this manual inspection becomes lengthy, tedious and error-prone. In this paper, we propose to automatically detect specific interest points in microscopy images using machine learning methods with the aim of performing automatic morphometric measurements in the context of Zebrafish studies. We systematically evaluate variants of ensembles of classification and regression trees on four datasets corresponding to different imaging modalities and experimental conditions. Our results show that all variants are effective, with a slight advantage for multiple output methods, which are more robust to parameter choices. [less ▲]

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See detailDiscovery and biochemical characterisation of four novel biomarkers for osteoarthritis.
DE SENY, Dominique ULg; Sharif, Mohammed; Fillet, Marianne ULg et al

in Annals of the Rheumatic Diseases (2011), 70(6), 1144-52

OBJECTIVE: Knee osteoarthritis (OA) is a heterogeneous, complex joint pathology of unknown aetiology. Biomarkers have been widely used to investigate OA but currently available biomarkers lack specificity ... [more ▼]

OBJECTIVE: Knee osteoarthritis (OA) is a heterogeneous, complex joint pathology of unknown aetiology. Biomarkers have been widely used to investigate OA but currently available biomarkers lack specificity and sensitivity. Therefore, novel biomarkers are needed to better understand the pathophysiological processes of OA initiation and progression. METHODS: Surface enhanced laser desorption/ionisation-time of flight-mass spectrometry proteomic technique was used to analyse protein expression levels in 284 serum samples from patients with knee OA classified according to Kellgren and Lawrence (K&L) score (0-4). OA serum samples were also compared to serum samples provided by healthy individuals (negative control subjects; NC; n=36) and rheumatoid arthritis (RA) patients (n=25). Proteins that gave similar signal in all K&L groups of OA patients were ignored, whereas proteins with increased or decreased levels of expression were selected for further studies. RESULTS: Two proteins were found to be expressed at higher levels in sera of OA patients at all four K&L scores compared to NC and RA, and were identified as V65 vitronectin fragment and C3fpeptide. Of the two remaining proteins, one showed increased expression (unknown protein at m/z of 3762) and the other (identified as connective tissue-activating peptide III protein) was decreased in K&L scores >2 subsets compared to NC, RA and K&L scores 0 or 1 subsets. CONCLUSION: The authors detected four unexpected biomarkers (V65 vitronectin fragment, C3f peptide, CTAP-III and m/z 3762 protein) that could be relevant in the pathophysiological process of OA as having significant correlation with parameters reflecting local inflammation and bone remodelling, as well as decrease in cartilage turnover. [less ▲]

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See detailRadar Classification based on Extra-Trees
Pisane, Jonathan ULg; Marée, Raphaël ULg; Wehenkel, Louis ULg et al

(2010, May 24)

In this paper, we describe a new automatic target recognition algorithm for classifying SAR images based on the PiXiT im- age classifier. It uses randomized sub-windows extraction and extremely randomized ... [more ▼]

In this paper, we describe a new automatic target recognition algorithm for classifying SAR images based on the PiXiT im- age classifier. It uses randomized sub-windows extraction and extremely randomized trees (extra-trees). This approach re- quires very little pre-processing of the images, thereby lim- iting the computational load. It was successfully tested on an extended version of the public standard MSTAR database, that includes targets of interest, false targets, and background clutter. A misclassification rate of about three percent has been achieved. [less ▲]

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See detailZebrafish as model in toxicology/pharmacology.
Voncken, Audrey ULg; Piot, Amandine ULg; Stern, Olivier ULg et al

Poster (2010, March 17)

Detailed reference viewed: 94 (35 ULg)
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See detailIncremental Indexing and Distributed Image Search using Shared Randomized Vocabularies
Marée, Raphaël ULg; Denis, Philippe; Wehenkel, Louis ULg et al

in ACM Proceedings MIR 2010 (2010, March)

We present a cooperative framework for content-based image retrieval for the realistic setting where images are distributed across multiple cooperating servers. The proposed method is in line with bag-of ... [more ▼]

We present a cooperative framework for content-based image retrieval for the realistic setting where images are distributed across multiple cooperating servers. The proposed method is in line with bag-of-features approaches but uses fully data-independent, randomized structures, shared by the cooperating servers, to map image features to common visual words. A coherent, global image similarity measure (which is a kernel) is computed in a distributed fashion over visual words, by only requiring a small amount of data transfers between nodes. Our experiments on various image types show that this framework is a very promising step towards large-scale, distributed content-based image retrieval. [less ▲]

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See detailBiomedical Imaging Modality Classification Using Bags of Visual and Textual Terms with Extremely Randomized Trees: Report of ImageCLEF 2010 Experiments
Marée, Raphaël ULg; Stern, Olivier ULg; Geurts, Pierre ULg

in CLEF Notebook Papers/LABs/Workshops (2010)

In this paper we describe our experiments related to the ImageCLEF 2010 medical modality classification task using extremely randomized trees. Our best run combines bags of textual and visual features. It ... [more ▼]

In this paper we describe our experiments related to the ImageCLEF 2010 medical modality classification task using extremely randomized trees. Our best run combines bags of textual and visual features. It yields 90% recognition rate and ranks 6th among 45 runs (ranging from 94% downto 12%). [less ▲]

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See detailRobust Automatic Target Recognition Using Extra-trees
Pisane, Jonathan ULg; Marée, Raphaël ULg; Wehenkel, Louis ULg et al

in Pisane, Jonathan (Ed.) Robust Automatic Target Recognition Using Extra-trees (2010)

In this paper, we describe a new automatic target recognition algorithm for classifying SAR images based on the PiXiT image classifier. It uses randomized sub-windows extraction and extremely randomized ... [more ▼]

In this paper, we describe a new automatic target recognition algorithm for classifying SAR images based on the PiXiT image classifier. It uses randomized sub-windows extraction and extremely randomized trees (extra-trees). This approach requires very little pre-processing of the images, thereby limiting the computational load. It was successfully tested on an extended version of the public standard MSTAR database, that includes targets of interest, false targets, and background clutter. A misclassification rate of about three percent has been achieved. [less ▲]

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See detailOligodendrocyte development and myelinogenesis are not impaired by high concentrations of phenylalanine or its metabolites.
Schoemans, Renaud; Aigrot, Marie-Stephane; Wu, Chaohong et al

in Journal of Inherited Metabolic Disease (2010), 33(2), 113-20

Phenylketonuria (PKU) is a metabolic genetic disease characterized by deficient phenylalanine hydroxylase (PAH) enzymatic activity. Brain hypomyelination has been reported in untreated patients, but its ... [more ▼]

Phenylketonuria (PKU) is a metabolic genetic disease characterized by deficient phenylalanine hydroxylase (PAH) enzymatic activity. Brain hypomyelination has been reported in untreated patients, but its mechanism remains unclear. We therefore investigated the influence of phenylalanine (Phe), phenylpyruvate (PP), and phenylacetate (PA) on oligodendrocytes. We first showed in a mouse model of PKU that the number of oligodendrocytes is not different in corpus callosum sections from adult mutants or from control brains. Then, using enriched oligodendroglial cultures, we detected no cytotoxic effect of high concentrations of Phe, PP, or PA. Finally, we analyzed the impact of Phe, PP, and PA on the myelination process in myelinating cocultures using both an in vitro index of myelination, based on activation of the myelin basic protein (MBP) promoter, and the direct quantification of myelin sheaths by both optical measurement and a bioinformatics method. None of these parameters was affected by the increased levels of Phe or its derivatives. Taken together, our data demonstrate that high levels of Phe, such as in PKU, are unlikely to directly induce brain hypomyelination, suggesting involvement of alternative mechanisms in this myelination defect. [less ▲]

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See detailFast Multi-Class Image Annotation with Random Subwindows and Multiple Output Randomized Trees
Dumont, Marie; Marée, Raphaël ULg; Wehenkel, Louis ULg et al

in Proc. International Conference on Computer Vision Theory and Applications (VISAPP) (2009, February)

This paper addresses image annotation, i.e. labelling pixels of an image with a class among a finite set of predefined classes. We propose a new method which extracts a sample of subwindows from a set of ... [more ▼]

This paper addresses image annotation, i.e. labelling pixels of an image with a class among a finite set of predefined classes. We propose a new method which extracts a sample of subwindows from a set of annotated images in order to train a subwindow annotation model by using the extremely randomized trees ensemble method appropriately extended to handle high-dimensional output spaces. The annotation of a pixel of an unseen image is done by aggregating the annotations of its subwindows containing this pixel. The proposed method is compared to a more basic approach predicting the class of a pixel from a single window centered on that pixel and to other state-of-the-art image annotation methods. In terms of accuracy, the proposed method significantly outperforms the basic method and shows good performances with respect to the state-of-the-art, while being more generic, conceptually simpler, and of higher computational efficiency than these latter. [less ▲]

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See detailContent-based Image Retrieval by Indexing Random Subwindows with Randomized Trees
Marée, Raphaël ULg; Geurts, Pierre ULg; Wehenkel, Louis ULg

in IPSJ Transactions on Computer Vision and Applications (2009), 1

We propose a new method for content-based image retrieval which exploits the similarity measure and indexing structure of totally randomized tree ensembles induced from a set of subwindows randomly ... [more ▼]

We propose a new method for content-based image retrieval which exploits the similarity measure and indexing structure of totally randomized tree ensembles induced from a set of subwindows randomly extracted from a sample of images. We also present the possibility of updating the model as new images come in, and the capability of comparing new images using a model previously constructed from a different set of images. The approach is quantitatively evaluated on various types of images and achieves high recognition rates despite its conceptual simplicity and computational efficiency. [less ▲]

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See detailAn Extra-trees-based Automatic Target Recognition Algorithm
Pisane, Jonathan ULg; Marée, Raphaël ULg; Ries, Philippe ULg et al

in To appear in Proc. International Radar Conference (2009)

Detailed reference viewed: 130 (33 ULg)
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See detailA Machine Learning Approach for Material Detection in Hyperspectral Images
Marée, Raphaël ULg; Stevens, Benjamin ULg; Geurts, Pierre ULg et al

in Proc. 6th IEEE Workshop on Object Tracking and Classification Beyond and in the Visible Spectrum (OTCBVS-CVPR09) (2009)

In this paper we propose a machine learning approach for the detection of gaseous traces in thermal infra red hyperspectral images. It exploits both spectral and spatial information by extracting subcubes ... [more ▼]

In this paper we propose a machine learning approach for the detection of gaseous traces in thermal infra red hyperspectral images. It exploits both spectral and spatial information by extracting subcubes and by using extremely randomized trees with multiple outputs as a classifier. Promising results are shown on a dataset of more than 60 hypercubes. [less ▲]

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See detailBiomarker discovery in asthma-related inflammation and remodeling.
Quesada Calvo, Florence ULg; Fillet, Marianne ULg; De Seny, Dominique ULg et al

in Proteomics (2009), 9(8), 2163-2170

Asthma is a complex inflammatory disease of airways. A network of reciprocal interactions between inflammatory cells, peptidic mediators, extracellular matrix components, and proteases is thought to be ... [more ▼]

Asthma is a complex inflammatory disease of airways. A network of reciprocal interactions between inflammatory cells, peptidic mediators, extracellular matrix components, and proteases is thought to be involved in the installation and maintenance of asthma-related airway inflammation and remodeling. To date, new proteic mediators displaying significant activity in the pathophysiology of asthma are still to be unveiled. The main objective of this study was to uncover potential target proteins by using surface-enhanced laser desorption/ionization-time of flight-mass spectrometry (SELDI-TOF-MS) on lung samples from mouse models of allergen-induced airway inflammation and remodeling. In this model, we pointed out several protein or peptide peaks that were preferentially expressed in diseased mice as compared to controls. We report the identification of different five proteins: found inflammatory zone 1 or RELM (FIZZ-1), calcyclin (S100A6), clara cell secretory protein 10 (CC10), Ubiquitin, and Histone H4. [less ▲]

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See detailProtéomique par SELDI-TOF-MS des maladies inflammatoires articulaires: identification des protéines S100 comme protéines d'intérêt
De Seny, Dominique ULg; Ribbens, Clio ULg; Cobraiville, Gaël ULg et al

in Revue Médicale de Liège (2009), 64(Spec No), 29-35

Clinical proteomics is a technical approach studying the entire proteome expressed by cells, tissues or organs. It describes the dynamics of cell regulation by detecting molecular events related to ... [more ▼]

Clinical proteomics is a technical approach studying the entire proteome expressed by cells, tissues or organs. It describes the dynamics of cell regulation by detecting molecular events related to diseases development. Proteomic techniques focus mainly on identification of new biomarkers or new therapeutic targets. It is a multidisciplinary approach using medical, biological, bioanalytical and bioinformatics knowledges. A strong collaboration between these fields allowed SELDI-TOF-MS proteomics studies to be performed at the CHU and the University of Liege, in GIGA-Research facilities. The aim of these studies was driven along three main axes of research related to the identification of biomarkers specific to a studied pathology, to a common biological pathway and, finally, to a treatment response. [less ▲]

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See detailP2X1 Ion Channels Promote Neutrophil Chemotaxis through Rho Kinase Activation
Lecut, Christelle ULg; Frederix, Kim ULg; Johnson, Daniel M et al

in Journal of Immunology (2009)

This study shows that activation of P2X1 ion channels by ATP promotes neutrophil chemotaxis, a process involving Rho kinase-dependent actomyosin-mediated contraction at the cell rear. These ion channels ... [more ▼]

This study shows that activation of P2X1 ion channels by ATP promotes neutrophil chemotaxis, a process involving Rho kinase-dependent actomyosin-mediated contraction at the cell rear. These ion channels may therefore play a significant role in host defense and inflammation. [less ▲]

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See detailMonomeric calgranulins measured by SELDI-TOF mass spectrometry and calprotectin measured by ELISA as biomarkers in arthritis
De Seny, Dominique ULg; Fillet, Marianne ULg; Ribbens, Clio ULg et al

in Clinical Chemistry (2008), 54

BACKGROUND: SELDI-TOF mass spectrometry (MS) is a high-throughput proteomic approach with potential for identifying novel forms of serum biomarkers of arthritis. METHODS: We used SELDI-TOF MS to analyze ... [more ▼]

BACKGROUND: SELDI-TOF mass spectrometry (MS) is a high-throughput proteomic approach with potential for identifying novel forms of serum biomarkers of arthritis. METHODS: We used SELDI-TOF MS to analyze serum samples from patients with various forms of inflammatory arthritis. Several protein profiles were collected on different Bio-Rad Laboratories ProteinChip arrays (CM10 and IMAC-Cu(2+)) and were evaluated statistically to select potential biomarkers. RESULTS: SELDI-TOF MS analyses identified several calgranulin proteins [S100A8 (calgranulin A), S100A9 (calgranulin B), S100A9*, and S100A12 (calgranulin C)], serum amyloid A (SAA), SAA des-Arg (SAA-R), and SAA des-Arg/des-Ser (SAA-RS) as biomarkers and confirmed the results with other techniques, such as western blotting, immunoprecipitation, and nano-LC-MS/MS. The S100 proteins were all able to significantly differentiate samples from patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA), and ankylosing spondylitis (AS) from those of patients with inflammatory bowel diseases used as an inflammatory control (IC) group, whereas the SAA, SAA-R, and SAA-RS proteins were not, with the exception of AS. The 4 S100 proteins were coproduced in all of the pathologies and were significantly correlated with the plasma calprotectin concentration; however, these S100 proteins were correlated with the SAA peak intensities only in the RA and IC patient groups. In RA, these S100 proteins (except for S100A12) were significantly correlated with the serum concentrations of C-reactive protein, matrix metalloproteinase 3, and anti-cyclic citrullinated peptide and with the Disease Activity Score (DAS(28)). CONCLUSIONS: The SELDI-TOF MS technology is a powerful approach for analyzing the status of monomeric, truncated, or posttranslationally modified forms of arthritis biomarkers, such as the S100A8, S100A9, S100A12, and SAA proteins. The fact that the SELDI-TOF MS data were correlated with results obtained with the classic calprotectin ELISA test supports the reliability of this new proteomic technique. [less ▲]

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See detailA novel formulation of inhaled doxycycline reduces allergen-induced inflammation, hyperresponsiveness and remodeling by matrix metalloproteinases and cytokines modulation in a mouse model of asthma
Guéders, Maud ULg; Bertholet, P.; Perin, Fabienne ULg et al

in Biochemical Pharmacology (2008), 75(2), 514-26

Background In this study, we assess the effectiveness of inhaled doxycycline, a tetracycline antibiotic displaying matrix metalloproteinases (MMP) inhibitory effects to prevent allergen-induced ... [more ▼]

Background In this study, we assess the effectiveness of inhaled doxycycline, a tetracycline antibiotic displaying matrix metalloproteinases (MMP) inhibitory effects to prevent allergen-induced inflammation, hyperresponsiveness and remodeling. MMPs play key roles in the complex cascade of events leading to asthmatic phenotype. Methods Doxycycline was administered by aerosols by the mean of a novel formulation as a complex with hydroxypropyl-gamma-cyclodextrin (HP-gamma-CD) used as an excipient. BALB/c mice (n = 16–24 in each group) were sensitized and exposed to aerosolized ovalbumin (OVA) from day 21 to 27 (short-term exposure protocol) or 5 days/odd weeks from day 22 to 96 (long-term exposure protocol). Results In the short-term exposure model, inhaled doxycycline decreased allergen-induced eosinophilic inflammation in bronchoalveolar lavage (BAL) and in peribronchial areas, as well as airway hyperresponsiveness. In lung tissue, exposure to doxycycline via inhaled route induced a fourfold increase in IL-10 levels, a twofold decrease in IL-5, IL-13 levels and diminished MMP-related proteolysis and the proportion of activated MMP-9 as compared to placebo. In the long-term exposure model, inhaled doxycycline significantly decreased the extent of glandular hyperplasia, airway wall thickening, smooth muscle hyperplasia and subepithelial collagen deposition which are well recognized features of airway remodeling. Conclusion Doxycycline administered by aerosols decreases the allergen-induced airway inflammation and hyperresponsiveness and inhibits the development of bronchial remodeling in a mouse model of asthma by modulation of cytokines production and MMP activity. [less ▲]

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See detailCompositional protein analysis of HDL by SELDI-TOF MS during experimental endotoxemia
Levels, Johannes HM; Marée, Raphaël ULg; Geurts, Pierre ULg et al

Poster (2008)

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See detailProteomics for prediction and characterization of response to infliximab in Crohn's disease: a pilot study.
Meuwis, Marie-Alice ULg; Fillet, Marianne ULg; Lutteri, Laurence ULg et al

in Clinical Biochemistry (2008), 41(12), 960-7

OBJECTIVES: Infliximab is the first anti-TNFalpha accepted by the Food and Drug Administration for use in inflammatory bowel disease treatment. Few clinical, biological and genetic factors tend to predict ... [more ▼]

OBJECTIVES: Infliximab is the first anti-TNFalpha accepted by the Food and Drug Administration for use in inflammatory bowel disease treatment. Few clinical, biological and genetic factors tend to predict response in Crohn's disease (CD) patient subcategories, none widely predicting response to infliximab. DESIGN AND METHODS: Twenty CD patients showing clinical response or non response to infliximab were used for serum proteomic profiling on Surface Enhanced Lazer Desorption Ionisation-Time of Flight-Mass Spectrometry (SELDI-TOF-MS), each before and after treatment. Univariate and multivariate data analysis were performed for prediction and characterization of response to infliximab. RESULTS: We obtained a model of classification predicting response to treatment and selected relevant potential biomarkers, among which platelet aggregation factor 4 (PF4). We quantified PF4, sCD40L and IL-6 by ELISA for correlation studies. CONCLUSIONS: This first proteomic pilot study on response to infliximab in CD suggests association between platelet metabolism and response to infliximab and requires validation studies on a larger cohort of patients. [less ▲]

Detailed reference viewed: 156 (26 ULg)