No abstract

Eukaryotic cells respond to many hormones and neurotransmitters with increased activity of the enzyme phospholipase C and a subsequent rise in the concentration of intracellular free calcium ([Ca2+]i). The increase in [Ca2+]i occurs as a result of the release of Ca2+ from intracellular stores and an influx of Ca2+ through the plasma membrane; this influx of Ca2+ may or may not be store-dependent. Drosophila transient receptor potential (TRP) proteins and some mammalian homologues (TRPC proteins) are thought to mediate capacitative Ca2+ entry. Here we describe the molecular mechanism of store-depletion-independent activation of a subfamily of mammalian TRPC channels. We find that hTRPC6 is a non-selective cation channel that is activated by diacylglycerol in a membrane-delimited fashion, independently of protein kinases C activated by diacylglycerol. Although hTRPC3, the closest structural relative of hTRPC6, is activated in the same way, TRPCs 1, 4 and 5 and the vanilloid receptor subtype 1 are unresponsive to the lipid mediator. Thus, hTRPC3 and hTRPC6 represent the first members of a new functional family of second-messenger-operated cation channels, which are activated by diacylglycerol.

We review machine learning methods employing positive definite kernels. These methods formulate learning and estimation problems in a reproducing kernel Hilbert space (RKHS) of functions defined on the data domain, expanded in terms of a kernel. Working in linear spaces of function has the benefit of facilitating the construction and analysis of learning algorithms while at the same time allowing large classes of functions. The latter include nonlinear functions as well as functions defined on nonvectorial data. We cover a wide range of methods, ranging from binary classifiers to sophisticated methods for estimation with structured data.Comment: Published in at http://dx.doi.org/10.1214/009053607000000677 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input representations. This paper addresses the complementary issue of problems involving complex outputs such as multiple dependent output variables and structured output spaces. We propose to generalize multiclass Support Vector Machine learning in a formulation that involves features extracted jointly from inputs and outputs. The resulting optimization problem is solved efficiently by a cutting plane algorithm that exploits the sparseness and structural decomposition of the problem. We demonstrate the versatility and effectiveness of our method on problems ranging from supervised grammar learning and named-entity recognition, to taxonomic text classification and sequence alignment.

Collaborative filtering aims at learning predictive models of user preferences, interests or behavior from community data, that is, a database of available user preferences. In this article, we describe a new family of model-based algorithms designed for this task. These algorithms rely on a statistical modelling technique that introduces latent class variables in a mixture model setting to discover user communities and prototypical interest profiles. We investigate several variations to deal with discrete and continuous response variables as well as with different objective functions. The main advantages of this technique over standard memory-based methods are higher accuracy, constant time prediction, and an explicit and compact model representation. The latter can also be used to mine for user communitites. The experimental evaluation shows that substantial improvements in accucracy over existing methods and published results can be obtained.

Probabilistic Latent Semantic Indexing is a novel approach to automated document indexing which is based on a statistical latent class model for factor analysis of count data. Fitted from a training corpus of text documents by a generalization of the Expectation Maximization algorithm, the utilized model is able to deal with domain{specific synonymy as well as with polysemous words. In contrast to standard Latent Semantic Indexing (LSI) by Singular Value Decomposition, the probabilistic variant has a solid statistical foundation and defines a proper generative data model. Retrieval experiments on a number of test collections indicate substantial performance gains over direct term matching methods as well as over LSI. In particular, the combination of models with different dimensionalities has proven to be advantageous.

Transient receptor potential melastatin-3 (TRPM3) is a broadly expressed Ca(2+)-permeable nonselective cation channel. Previous work has demonstrated robust activation of TRPM3 by the neuroactive steroid pregnenolone sulfate (PS), but its in vivo gating mechanisms and functions remained poorly understood. Here, we provide evidence that TRPM3 functions as a chemo- and thermosensor in the somatosensory system. TRPM3 is molecularly and functionally expressed in a large subset of small-diameter sensory neurons from dorsal root and trigeminal ganglia, and mediates the aversive and nocifensive behavioral responses to PS. Moreover, we demonstrate that TRPM3 is steeply activated by heating and underlies heat sensitivity in a subset of sensory neurons. TRPM3-deficient mice exhibited clear deficits in their avoidance responses to noxious heat and in the development of inflammatory heat hyperalgesia. These experiments reveal an unanticipated role for TRPM3 as a thermosensitive nociceptor channel implicated in the detection of noxious heat.

Hormones, neurotransmitters, and growth factors give rise to calcium entry via receptor-activated cation channels that are activated downstream of phospholipase C activity. Members of the transient receptor potential channel (TRPC) family have been characterized as molecular substrates mediating receptoractivated cation influx. TRPC channels are assumed to be composed of multiple TRPC proteins. However, the cellular principles governing the assembly of TRPC proteins into homo-or heteromeric ion channels still remain elusive. By pursuing four independent experimental approaches-i.e., subcellular cotrafficking of TRPC subunits, differential functional suppression by dominant-negative subunits, fluorescence resonance energy transfer between labeled TRPC subunits, and coimmunoprecipitation-we investigate the combinatorial rules of TRPC assembly. Our data show that (i) TRPC2 does not interact with any known TRPC protein and (ii) TRPC1 has the ability to form channel complexes together with TRPC4 and TRPC5. (iii) All other TRPCs exclusively assemble into homo-or heterotetramers within the confines of TRPC subfamilies-e.g., TRPC4͞5 or TRPC3͞6͞7. The principles of TRPC channel formation offer the conceptual framework to assess the physiological role of distinct TRPC proteins in living cells.A fter binding to their cognate receptors on the cell membrane, many hormones, neurotransmitters, and growth factors induce increases in the intracellular free calcium concentration ([Ca 2ϩ ] i ) subsequent to phospholipase C (PLC) stimulation. In addition to inositol-1,4,5-trisphosphate (InsP 3 )-mediated calcium release from intracellular stores, plasma membrane ion channels are activated in a PLC-dependent manner in most cells either by second messenger-mediated pathways or by store depletion (1). Mammalian homologues of the Drosophila melanogaster transient receptor potential (TRP) visual transduction channels (2), the TRP channel (TRPC) proteins, have been identified (3-8) and characterized as subunits of receptoractivated cation channels (9-12). Although it has been established that TRPC proteins are subject to a gating mechanism that operates through PLC, the exact activation mechanism for distinct TRPC family members is still a controversial issue. Proposed models favoring store-dependent or InsP 3 receptormediated channel gating (5, 6, 13, 14) were challenged (8,(15)(16)(17)(18), and alternative hypotheses like the direct second messengermediated activation of TRPC3, TRPC6, and TRPC7 by diacylglycerol have been put forward (8,16).TRPC channels and TRP-related protein families (11, 12) belong to the superfamily of hexahelical cation channels. Therefore, several assumptions on the structure and function of TRPC channels were made based on analogous reasoning. (i) TRPC proteins are thought to span the plasma membrane 6 times with a pore loop inserted between transmembrane segments 5 and 6.(ii) Functional channel complexes are believed to be composed of tetrameric TRPC proteins. (iii) Because the canonical TRPC family compr...