Data-driven clustering : new methods and applications

Abstract : This work is concerned with the development and application of novel unsupervised learning methods, having in mind two target applications: the analysis of forensic case data and the classification of remote sensing images. First, a method based on a symbolic optimization of the inter-sample distance measure is proposed to improve the flexibility of spectral clustering algorithms, and applied to the problem of forensic case data. This distance is optimized using a loss function related to the preservation of neighborhood structure between the input space and the space of principal components, and solutions are found using genetic programming. Results are compared to a variety of state-of--the-art clustering algorithms. Subsequently, a new large-scale clustering method based on a joint optimization of feature extraction and classification is proposed and applied to various databases, including two hyperspectral remote sensing images. The algorithm makes uses of a functional model (e.g., a neural network) for clustering which is trained by stochastic gradient descent. Results indicate that such a technique can easily scale to huge databases, can avoid the so-called out-of-sample problem, and can compete with or even outperform existing clustering algorithms on both artificial data and real remote sensing images. This is verified on small databases as well as very large problems. Résumé : Ce travail de recherche porte sur le développement et l'application de méthodes d'apprentissage dites non supervisées. Les applications visées par ces méthodes sont l'analyse de données forensiques et la classification d'images hyperspectrales en télédétection. Dans un premier temps, une méthodologie de classification non supervisée fondée sur l'optimisation symbolique d'une mesure de distance inter-échantillons est proposée. Cette mesure est obtenue en optimisant une fonction de coût reliée à la préservation de la structure de voisinage d'un point entre l'espace des variables initiales et l'espace des composantes principales. Cette méthode est appliquée à l'analyse de données forensiques et comparée à un éventail de méthodes déjà existantes. En second lieu, une méthode fondée sur une optimisation conjointe des tâches de sélection de variables et de classification est implémentée dans un réseau de neurones et appliquée à diverses bases de données, dont deux images hyperspectrales. Le réseau de neurones est entraîné à l'aide d'un algorithme de gradient stochastique, ce qui rend cette technique applicable à des images de très haute résolution. Les résultats de l'application de cette dernière montrent que l'utilisation d'une telle technique permet de classifier de très grandes bases de données sans difficulté et donne des résultats avantageusement comparables aux méthodes existantes.

Characterization of surface functional groups present on laboratory-generated and ambient aerosol particles by means of heterogeneous titration reactions

A Knudsen flow reactor has been used to quantify surface functional groups on aerosols collected in the field. This technique is based on a heterogeneous titration reaction between a probe gas and a specific functional group on the particle surface. In the first part of this work, the reactivity of different probe gases on laboratory-generated aerosols (limonene SOA, Pb(NO3)2, Cd(NO3)2) and diesel reference soot (SRM 2975) has been studied. Five probe gases have been selected for the quantitative determination of important functional groups: N(CH3)3 (for the titration of acidic sites), NH2OH (for carbonyl functions), CF3COOH and HCl (for basic sites of different strength), and O3 (for oxidizable groups). The second part describes a field campaign that has been undertaken in several bus depots in Switzerland, where ambient fine and ultrafine particles were collected on suitable filters and quantitatively investigated using the Knudsen flow reactor. Results point to important differences in the surface reactivity of ambient particles, depending on the sampling site and season. The particle surface appears to be multi-functional, with the simultaneous presence of antagonistic functional groups which do not undergo internal chemical reactions, such as acid-base neutralization. Results also indicate that the surface of ambient particles was characterized by a high density of carbonyl functions (reactivity towards NH2OH probe in the range 0.26-6 formal molecular monolayers) and a low density of acidic sites (reactivity towards N(CH3)3 probe in the range 0.01-0.20 formal molecular monolayer). Kinetic parameters point to fast redox reactions (uptake coefficient ?0>10-3 for O3 probe) and slow acid-base reactions (?0<10-4 for N(CH3)3 probe) on the particle surface. [Authors]

Astrocytic αVβ3 integrin inhibits neurite outgrowth and promotes retraction of neuronal processes by clustering Thy-1.

Thy-1 is a membrane glycoprotein suggested to stabilize or inhibit growth of neuronal processes. However, its precise function has remained obscure, because its endogenous ligand is unknown. We previously showed that Thy-1 binds directly to α(V)β(3) integrin in trans eliciting responses in astrocytes. Nonetheless, whether α(V)β(3) integrin might also serve as a Thy-1-ligand triggering a neuronal response has not been explored. Thus, utilizing primary neurons and a neuron-derived cell line CAD, Thy-1-mediated effects of α(V)β(3) integrin on growth and retraction of neuronal processes were tested. In astrocyte-neuron co-cultures, endogenous α(V)β(3) integrin restricted neurite outgrowth. Likewise, α(V)β(3)-Fc was sufficient to suppress neurite extension in Thy-1(+), but not in Thy-1(-) CAD cells. In differentiating primary neurons exposed to α(V)β(3)-Fc, fewer and shorter dendrites were detected. This effect was abolished by cleavage of Thy-1 from the neuronal surface using phosphoinositide-specific phospholipase C (PI-PLC). Moreover, α(V)β(3)-Fc also induced retraction of already extended Thy-1(+)-axon-like neurites in differentiated CAD cells as well as of axonal terminals in differentiated primary neurons. Axonal retraction occurred when redistribution and clustering of Thy-1 molecules in the plasma membrane was induced by α(V)β(3) integrin. Binding of α(V)β(3)-Fc was detected in Thy-1 clusters during axon retraction of primary neurons. Moreover, α(V)β(3)-Fc-induced Thy-1 clustering correlated in time and space with redistribution and inactivation of Src kinase. Thus, our data indicates that α(V)β(3) integrin is a ligand for Thy-1 that upon binding not only restricts the growth of neurites, but also induces retraction of already existing processes by inducing Thy-1 clustering. We propose that these events participate in bi-directional astrocyte-neuron communication relevant to axonal repair after neuronal damage.

Logistic services as competitive means : segmenting the retail market for softwood lumber

Abstract

Phenotyping of 60 cultured human gliomas and 34 other neuroectodermal tumors by means of monoclonal antibodies against glioma, melanoma and HLA-DR antigens.

The reactivity spectrum of three monoclonal antibodies (Mabs) to human malignant glioma, five Mabs to melanomas and one Mab anti-HLA-DR was investigated by an indirect antibody binding radioimmunoassay on a panel of cells derived from 60 glioma lines, including 47 malignant astrocytomas, 11 low-grade astrocytomas and two malignant ependymomas as well on cells from 12 melanoma, three neuroblastoma, three medulloblastoma, two schwannoma, two retinoblastoma, two choroïd plexus papilloma, ten meningioma and 12 unrelated tumor lines. The anti-glioma Mabs BF7 and GE2 reacted preferentially with gliomas, while the anti-glioma Mab CG12 reacted with gliomas, melanomas, neuroblastomas and medulloblastomas. The five anti-melanoma Mabs reacted with gliomas, neuroblastomas and medulloblastomas. The anti-HLA-DR Mab D1-12 reacted with gliomas, melanomas and some meningiomas. On the basis of the data presented, we describe three different antigenic systems; the first one is glioma-associated, the second one is related to differentiation antigens expressed on cells derived from the neuroectoderm and the third is represented by HLA-DR antigens which are expressed not only on B-lymphoblastoid cells but also on melanomas and gliomas.

Large-scale clustering through functional embedding

We present a new framework for large-scale data clustering. The main idea is to modify functional dimensionality reduction techniques to directly optimize over discrete labels using stochastic gradient descent. Compared to methods like spectral clustering our approach solves a single optimization problem, rather than an ad-hoc two-stage optimization approach, does not require a matrix inversion, can easily encode prior knowledge in the set of implementable functions, and does not have an ?out-of-sample? problem. Experimental results on both artificial and real-world datasets show the usefulness of our approach.

Investigation of high-resolution functional magnetic resonance imaging by means of surface and array radiofrequency coils at 7 T.

In this investigation, high-resolution, 1x1x1-mm(3) functional magnetic resonance imaging (fMRI) at 7 T is performed using a multichannel array head coil and a surface coil approach. Scan geometry was optimized for each coil separately to exploit the strengths of both coils. Acquisitions with the surface coil focused on partial brain coverage, while whole-brain coverage fMRI experiments were performed with the array head coil. BOLD sensitivity in the occipital lobe was found to be higher with the surface coil than with the head array, suggesting that restriction of signal detection to the area of interest may be beneficial for localized activation studies. Performing independent component analysis (ICA) decomposition of the fMRI data, we consistently detected BOLD signal changes and resting state networks. In the surface coil data, a small negative BOLD response could be detected in these resting state network areas. Also in the data acquired with the surface coil, two distinct components of the positive BOLD signal were consistently observed. These two components were tentatively assigned to tissue and venous signal changes.

Testing a large-scale forestry scenario model by means of successive inventories on a forest property

Abstract

Full activation of the T cell receptor requires both clustering and conformational changes at CD3.

T cell receptor (TCR-CD3) triggering involves both receptor clustering and conformational changes at the cytoplasmic tails of the CD3 subunits. The mechanism by which TCRalphabeta ligand binding confers conformational changes to CD3 is unknown. By using well-defined ligands, we showed that induction of the conformational change requires both multivalent engagement and the mobility restriction of the TCR-CD3 imposed by the plasma membrane. The conformational change is elicited by cooperative rearrangements of two TCR-CD3 complexes and does not require accompanying changes in the structure of the TCRalphabeta ectodomains. This conformational change at CD3 reverts upon ligand dissociation and is required for T cell activation. Thus, our permissive geometry model provides a molecular mechanism that rationalizes how the information of ligand binding to TCRalphabeta is transmitted to the CD3 subunits and to the intracellular signaling machinery.

Multicentric carpotarsal osteolysis is caused by mutations clustering in the amino-terminal transcriptional activation domain of MAFB.

Multicentric carpotarsal osteolysis (MCTO) is a rare skeletal dysplasia characterized by aggressive osteolysis, particularly affecting the carpal and tarsal bones, and is frequently associated with progressive renal failure. Using exome capture and next-generation sequencing in five unrelated simplex cases of MCTO, we identified previously unreported missense mutations clustering within a 51 base pair region of the single exon of MAFB, validated by Sanger sequencing. A further six unrelated simplex cases with MCTO were also heterozygous for previously unreported mutations within this same region, as were affected members of two families with autosomal-dominant MCTO. MAFB encodes a transcription factor that negatively regulates RANKL-induced osteoclastogenesis and is essential for normal renal development. Identification of this gene paves the way for development of novel therapeutic approaches for this crippling disease and provides insight into normal bone and kidney development.