How relevant are S=O and P=O Double Bonds for the Description of the Acid Molecules H2SO3, H2SO4, and H3PO4, respectively?

The acid molecules H₂SO₃, H₂SO₄, and H₃PO₄ are usually drawn using "Lewis structures" which exhibit the octet extension by 3d-orbitals on sulfur and phosphorus, respectively. Thus, S=O and P=O double bonds are assumed to be formed. The natural d-orbital occupancies on S and P, however, were calculated to be as low as 0.1 e, and therefore, an octet extension can hardly be expected. After the natural bond orbitals (NBO) search procedure was forced to attempt to form different Lewis structures of bonds and lone pairs, we defined the optimal Lewis structure, if a dominant structure exists at all, by the maximum electronic charge in Lewis orbitals. Indeed, sulfur obeys the octet rule in the optimal zwitterionic Lewis structures and does not form S=O double bonds. No dominant resonance structure could be found for H₃PO₄ where polarized PO ?-bond and zwitterionic PO bond structures exhibit similar weights.     

STDP Installs in Winner-Take-All Circuits an Online Approximation to Hidden Markov Model Learning

In order to cross a street without being run over, we need to be able to extract very fast hidden causes of dynamically changing multi-modal sensory stimuli, and to predict their future evolution. We show here that a generic cortical microcircuit motif, pyramidal cells with lateral excitation and inhibition, provides the basis for this difficult but all-important information processing capability. This capability emerges in the presence of noise automatically through effects of STDP on connections between pyramidal cells in Winner-Take-All circuits with lateral excitation. In fact, one can show that these motifs endow cortical microcircuits with functional properties of a hidden Markov model, a generic model for solving such tasks through probabilistic inference. Whereas in engineering applications this model is adapted to specific tasks through offline learning, we show here that a major portion of the functionality of hidden Markov models arises already from online applications of STDP, without any supervision or rewards. We demonstrate the emergent computing capabilities of the model through several computer simulations. The full power of hidden Markov model learning can be attained through reward-gated STDP. This is due to the fact that these mechanisms enable a rejection sampling approximation to theoretically optimal learning. We investigate the possible performance gain that can be achieved with this more accurate learning method for an artificial grammar task.     

The Extracellular δ-Domain is Essential for the Formation of CD81 Tetraspanin Webs

CD81 is a ubiquitously expressed member of the tetraspanin family. It forms large molecular platforms, so-called tetraspanin webs that play physiological roles in a variety of cellular functions and are involved in viral and parasite infections. We have investigated which part of the CD81 molecule is required for the formation of domains in the cell membranes of T-cells and hepatocytes. Surprisingly, we find that large CD81 platforms assemble via the short extracellular δ-domain, independent from a strong primary partner binding and from weak interactions mediated by palmitoylation. The δ-domain is also essential for the platforms to function during viral entry. We propose that, instead of stable binary interactions, CD81 interactions via the small δ-domain, possibly involving a dimerization step, play the key role in organizing CD81 into large tetraspanin webs and controlling its function.     

Symbolic Extensions Applied to Multiscale Structure of Genomes

A genome of a living organism consists of a long string of symbols over a finite alphabet carrying critical information for the organism. This includes its ability to control post natal growth, homeostasis, adaptation to changes in the surrounding environment, or to biochemically respond at the cellular level to various specific regulatory signals. In this sense, a genome represents a symbolic encoding of a highly organized system of information whose functioning may be revealed as a natural multilayer structure in terms of complexity and prominence. In this paper we use the mathematical theory of symbolic extensions as a framework to shed light onto how this multilayer organization is reflected in the symbolic coding of the genome. The distribution of data in an element of a standard symbolic extension of a dynamical system has a specific form: the symbolic sequence is divided into several subsequences (which we call layers) encoding the dynamics on various “scales”. We propose that a similar structure resides within the genomes, building our analogy on some of the most recent findings in the field of regulation of genomic DNA functioning.     

We'll Meet Again: Revealing Distributional and Temporal Patterns of Social Contact

What are the dynamics and regularities underlying social contact, and how can contact with the people in one''s social network be predicted? In order to characterize distributional and temporal patterns underlying contact probability, we asked 40 participants to keep a diary of their social contacts for 100 consecutive days. Using a memory framework previously used to study environmental regularities, we predicted that the probability of future contact would follow in systematic ways from the frequency, recency, and spacing of previous contact. The distribution of contact probability across the members of a person''s social network was highly skewed, following an exponential function. As predicted, it emerged that future contact scaled linearly with frequency of past contact, proportionally to a power function with recency of past contact, and differentially according to the spacing of past contact. These relations emerged across different contact media and irrespective of whether the participant initiated or received contact. We discuss how the identification of these regularities might inspire more realistic analyses of behavior in social networks (e.g., attitude formation, cooperation).     

Crystal structure of cathepsin A,a novel target for the treatment of cardiovascular diseases

The lysosomal serine carboxypeptidase cathepsin A is involved in the breakdown of peptide hormones like endothelin and bradykinin. Recent pharmacological studies with cathepsin A inhibitors in rodents showed a remarkable reduction in cardiac hypertrophy and atrial fibrillation, making cathepsin A a promising target for the treatment of heart failure. Here we describe the crystal structures of activated cathepsin A without inhibitor and with two compounds that mimic the tetrahedral intermediate and the reaction product, respectively. The structure of activated cathepsin A turned out to be very similar to the structure of the inactive precursor. The only difference was the removal of a 40 residue activation domain, partially due to proteolytic removal of the activation peptide, and partially by an order–disorder transition of the peptides flanking the removed activation peptide. The termini of the catalytic core are held together by the Cys253–Cys303 disulfide bond, just before and after the activation domain. One of the compounds we soaked in our crystals reacted covalently with the catalytic Ser150 and formed a tetrahedral intermediate. The other compound got cleaved by the enzyme and a fragment, resembling one of the natural reaction products, was found in the active site. These studies establish cathepsin A as a classical serine proteinase with a well-defined oxyanion hole. The carboxylate group of the cleavage product is bound by a hydrogen-bonding network involving one aspartate and two glutamate side chains. This network can only form if at least half of the carboxylate groups involved are protonated, which explains the acidic pH optimum of the enzyme.     

Combination of Enzastaurin and Pemetrexed Inhibits Cell Growth and Induces Apoptosis of Chemoresistant Ovarian Cancer Cells Regulating Extracellular Signal-Regulated Kinase 1/2 Phosphorylation

New strategies in the therapy for malignant diseases depend on a targeted influence on signal transduction pathways that regulate proliferation, cell growth, differentiation, and apoptosis by the activation of serine/threonine kinases. Enzastaurin ({"type":"entrez-nucleotide","attrs":{"text":"LY317615","term_id":"1257423630","term_text":"LY317615"}}LY317615.HCl), a selective inhibitor of protein kinase Cβ (PKCβ), is one of these new drugs and causes inhibition of proliferation and induction of apoptosis. Pemetrexed, a multitarget inhibitor of folate pathways, is broadly active in a wide variety of solid tumors. Therefore, the effect of enzastaurin and the combination treatment with pemetrexed was analyzed when applied to the drug-sensitive ovarian cancer cell line HEY and various subclones with drug resistance against cisplatin, etoposide, docetaxel, and paclitaxel, as well as pemetrexed, and gemcitabine. In these novel chemoresistant subclones, the expression of the enzastaurin targets PKCβII and glycogen synthase kinase 3β (GSK3β) was analyzed. Exposition to enzastaurin showed various inhibitory effects on phosphorylated forms of GSK3β and the mitogen-activated protein kinase extracellular signal-regulated kinase 1/2. Cell proliferation experiments identified the cell line-specific half-maximal inhibitory concentration values of enzastaurin and a synergistic inhibitory effect by cotreatment with the antifolate pemetrexed. Induction of apoptosis by enzastaurin treatment was investigated by Cell Death Detection ELISA and immunoblot analyses. Simultaneous treatment with pemetrexed resulted in an enhanced inhibition of proliferation and induction of apoptosis even in partial enzastaurin-resistant cells. Therefore, the combinational effect of enzastaurin and pemetrexed can have promise in clinical application to overcome the fast-growing development of resistance to chemotherapy in ovarian cancer.     

Electroconvulsive Therapy Induces Neurogenesis in Frontal Rat Brain Areas

Electroconvulsive therapy (ECT) is an effective therapy for several psychiatric disorders, including severe major depression, mania and certain forms of schizophrenia. It had been proposed that ECT acts by modulating local plasticity via the stimulation of neurogenesis. In fact, among antidepressant therapies, ECT is the most robust enhancer of neurogenesis in the hippocampus of rodents and non-human primates. The existence of ECT-triggered neurogenesis in other brain areas, particularly in those adjacent to the other main locus of neurogenesis, the subventricular zone (SVZ), had so far remained unknown. Here we show that ECT also strongly enhances neurogenesis in frontal brain areas, especially in the rostro-medial striatum, generating specific, small-size calretinin-positive interneurons. We provide here the first evidence that ECT stimulates neurogenesis in areas outside the hippocampus. Our data may open research possibilities that focus on the plastic changes induced by ECT in frontal limbic circuitry.