Critical neural networks with short and long term plasticity

In recent years self organised critical neuronal models have provided insights regarding the origin of the experimentally observed avalanching behaviour of neuronal systems. It has been shown that dynamical synapses, as a form of short-term plasticity, can cause critical neuronal dynamics. Whereas long-term plasticity, such as hebbian or activity dependent plasticity, have a crucial role in shaping the network structure and endowing neural systems with learning abilities. In this work we provide a model which combines both plasticity mechanisms, acting on two different time-scales. The measured avalanche statistics are compatible with experimental results for both the avalanche size and duration distribution with biologically observed percentages of inhibitory neurons. The time-series of neuronal activity exhibits temporal bursts leading to 1/f decay in the power spectrum. The presence of long-term plasticity gives the system the ability to learn binary rules such as XOR, providing the foundation of future research on more complicated tasks such as pattern recognition.Comment: 8 pages, 7 figure

P12-11. Resistance to the CD4 mimetic mini protein M48-U1 induces changes in a highly conserved region on the HIV-1 gp120 envelope protein

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A covalent antagonist for the human adenosine A(2A) receptor

The structure of the human A(2A) adenosine receptor has been elucidated by X-ray crystallography with a high affinity non-xanthine antagonist, ZM241385, bound to it. This template molecule served as a starting point for the incorporation of reactive moieties that cause the ligand to covalently bind to the receptor. In particular, we incorporated a fluorosulfonyl moiety onto ZM241385, which yielded LUF7445 (4-((3-((7-amino-2-(furan-2-yl)-[1, 2, 4]triazolo[1,5-a][1, 3, 5]triazin-5-yl)amino)propyl)carbamoyl)benzene sulfonyl fluoride). In a radioligand binding assay, LUF7445 acted as a potent antagonist, with an apparent affinity for the hA(2A) receptor in the nanomolar range. Its apparent affinity increased with longer incubation time, suggesting an increasing level of covalent binding over time. An in silico A(2A)-structure-based docking model was used to study the binding mode of LUF7445. This led us to perform site-directed mutagenesis of the A(2A) receptor to probe and validate the target lysine amino acid K153 for covalent binding. Meanwhile, a functional assay combined with wash-out experiments was set up to investigate the efficacy of covalent binding of LUF7445. All these experiments led us to conclude LUF7445 is a valuable molecular tool for further investigating covalent interactions at this receptor. It may also serve as a prototype for a therapeutic approach in which a covalent antagonist may be needed to counteract prolonged and persistent presence of the endogenous ligand adenosine

Impact of a Community Pharmacist-Delivered Information Program on the Follow-up of Type-2 Diabetic Patients: A Cluster Randomized Controlled Study.

Low-quality communication between patients and care providers and limited patient knowledge of the disease and the therapy are important factors associated with poor glycemic control in patients with type 2 diabetes. We conducted a multicenter study to determine whether structured and tailored information delivered by pharmacists to type 2 diabetic patients could improve patient treatment adherence, hemoglobin A1c (HbA1c) levels and knowledge about diabetes. One hundred seventy-four pharmacies were randomized to deliver an educational program on diet, drug treatment, disease and complications during three 30-min interviews over a 6-month period, or to provide no intervention, to type 2 diabetic patients treated with oral antidiabetic agents. Medication adherence was assessed by measuring the medication possession ratio and diabetes control by collecting HbA1c values. Levels of patient treatment self-management and disease knowledge were assessed using self-questionnaires. Three hundred seventy-seven patients were analyzed. The medication possession ratio, already very high at baseline in the intervention (94.8%) and control (92.3%) groups, did not vary significantly after 6 months with no difference between the two groups. Significant decreases in HbA1c were observed in both groups at 6 months (p < 0.001) and 12 months (p < 0.01), with significantly greater changes from baseline in the intervention group than in the control group at 6 months (- 0.5% vs. - 0.2%, p = 0.0047) and 12 months (- 0.6% vs. - 0.2%, p = 0.0057). Patients in the intervention group showed greater improvement in their ability to self-manage treatment (+ 4.86 vs. + 1.58, p = 0.0014) and in the extent of their knowledge about diabetes (+ 0.6 vs. + 0.2, p < 0.01) at 6 months versus baseline compared with the control group. Tailored information provided by the pharmacist to patients with type 2 diabetes did not significantly improve the already high adherence rates, but was associated with a significant decrease in HbA1c and an improvement of patient knowledge about diabetes. ISRCTN33776525. MSD France

Statistical expression deconvolution from mixed tissue samples

Motivation: Global expression patterns within cells are used for purposes ranging from the identification of disease biomarkers to basic understanding of cellular processes. Unfortunately, tissue samples used in cancer studies are usually composed of multiple cell types and the non-cancerous portions can significantly affect expression profiles. This severely limits the conclusions that can be made about the specificity of gene expression in the cell-type of interest. However, statistical analysis can be used to identify differentially expressed genes that are related to the biological question being studied

Regulated Membrane Localization of Tiam1, Mediated by the NH2-terminal Pleckstrin Homology Domain, Is Required for Rac-dependent Membrane Ruffling and C-Jun NH2-terminal Kinase Activation

Rho-like GTPases, including Cdc42, Rac, and Rho, regulate signaling pathways that control actin cytoskeletal structures and transcriptional activation. The Tiam1 gene encodes an activator of Rac1, and similarly to constitutively activated (V12)Rac1, overexpression of Tiam1 in fibroblasts induces the formation of membrane ruffles. Tiam1 contains a Dbl homology (DH) domain and adjacent pleckstrin homology (PH) domain, hallmarks for activators of Rho-like GTPases. Unique for Tiam1 are an additional PH domain and a Discs-large homology region in the NH2-terminal part of the protein. Here we show that both in fibroblasts and COS cells, membrane localization of Tiam1 is required for the induction of membrane ruffling. A detailed mutational analysis, in combination with confocal laser scanning microscopy and immunoelectron microscopy, demonstrates that the NH2-terminal PH domain of Tiam1, but not the DH-adjacent PH domain, is essential for membrane association. This NH2-terminal PH domain of Tiam1 can be functionally replaced by the myristoylated membrane localization domain of c-Src, indicating that the primary function of this PH domain is to localize the protein at the membrane. After serum starvation, both membrane association of Tiam1 and ruffling can be induced by serum, suggesting that receptor stimulation induces membrane translocation of Tiam1. Similar to V12Rac1, Tiam1 stimulates the activity of the c-Jun NH2-terminal kinase (JNK). This Rac-dependent stimulation of JNK also requires membrane association of Tiam1. We conclude that the regulated membrane localization of Tiam1 through its NH2-terminal PH domain determines the activation of distinct Rac-mediated signaling pathways

The influence of feature selection methods on accuracy, stability and interpretability of molecular signatures

Motivation: Biomarker discovery from high-dimensional data is a crucial problem with enormous applications in biology and medicine. It is also extremely challenging from a statistical viewpoint, but surprisingly few studies have investigated the relative strengths and weaknesses of the plethora of existing feature selection methods. Methods: We compare 32 feature selection methods on 4 public gene expression datasets for breast cancer prognosis, in terms of predictive performance, stability and functional interpretability of the signatures they produce. Results: We observe that the feature selection method has a significant influence on the accuracy, stability and interpretability of signatures. Simple filter methods generally outperform more complex embedded or wrapper methods, and ensemble feature selection has generally no positive effect. Overall a simple Student's t-test seems to provide the best results. Availability: Code and data are publicly available at http://cbio.ensmp.fr/~ahaury/