Actividad insecticida de extractos de bocconia frutescens l. sobre hypothenemus hampei f.

Se evaluó la actividad de Bocconia frutescens L. como insecticida sobre Hypothenemus hampei F. Extractos de hojas, semillas, y corteza se estudiaron en concentraciones de 2000 ppm, 1000 ppm y 500 ppm, encontrando que la corteza posee la mayor actividad insecticida. Posteriormente, se evaluó la actividad de un extracto rico en alcaloides, hallando una acción insecticida Aprox. 15 por ciento. Además se identificó la presencia de alcaloides utilizando los métodos de Caín, y A. Sanabria. Se diseñó un método para evaluar la actividad insecticida de plantas que se presumen ricas en alcaloides sobre Hypothenemus hampei F

Actividad insecticida de extractos de bocconia frutescens l. sobre hypothenemus hampei f.

Se evaluó la actividad de Bocconia frutescens L. como insecticida sobre Hypothenemus hampei F. Extractos de hojas, semillas, y corteza se estudiaron en concentraciones de 2000 ppm, 1000 ppm y 500 ppm, encontrando que la corteza posee la mayor actividad insecticida. Posteriormente, se evaluó la actividad de un extracto rico en alcaloides, hallando una acción insecticida Aprox. 15 por ciento. Además se identificó la presencia de alcaloides utilizando los métodos de Caín, y A. Sanabria. Se diseñó un método para evaluar la actividad insecticida de plantas que se presumen ricas en alcaloides sobre Hypothenemus hampei F

Kinase/phosphatase overexpression reveals pathways regulating hippocampal neuron morphology

Kinases and phosphatases that regulate neurite number versus branching versus extension are weakly correlated.The kinase family that most strongly enhances neurite growth is a family of non-protein kinases; sugar kinases related to NADK.Pathway analysis revealed that genes in several cancer pathways were highly active in enhancing neurite growth

Sensitivity, Noise and Detection of Enzyme Inhibition in Progress Curves

Starting with the development of an enzymatic assay, where an enzyme in solution hydrolysed a solid-phase bound peptide, a model for the kinetics of enzyme action was introduced. This model allowed the estimation of kinetic parameters and enzyme activity for a system that has the peculiarity of not being saturable with the substrate, but with the enzyme. In a derivation of the model, it was found that the sensitivity of the signal to variations in the enzyme concentration had a transient increase along the reaction progress with a maximum at high substrate conversion levels. The same behaviour was derived for the sensitivity in classical homogeneous enzymatic assays and experimental evidence of this was obtained. The impact of the transient increase of the sensitivity on the error structure, and on the ability of homogeneous end-point enzymatic assays to detect competitive inhibition, came into focus. First, a non-monotonous shape in the standard deviation of progress curve data was found and it was attributed to the random dispersion in the enzyme concentration operating through the transient increase in the sensitivity. Second, a model for the detection limit of the quantity Ki/[I] (the IDL-factor) as a function of the substrate conversion level was developed for homogeneous end-point enzymatic assays. It was found that the substrate conversion level where the IDL-factor reached an optimum was beyond the initial velocity range. Moreover, at this optimal point not only the ability to detect inhibitors but also the robustness of the assays was maximized. These results may prove to be relevant in drug discovery for optimising end point homogeneous enzymatic assays that are used to find inhibitors against a target enzyme in compound libraries, which are usually big (>10000) and crowded with irrelevant compounds

Sensitivity, Noise and Detection of Enzyme Inhibition in Progress Curves

Starting with the development of an enzymatic assay, where an enzyme in solution hydrolysed a solid-phase bound peptide, a model for the kinetics of enzyme action was introduced. This model allowed the estimation of kinetic parameters and enzyme activity for a system that has the peculiarity of not being saturable with the substrate, but with the enzyme. In a derivation of the model, it was found that the sensitivity of the signal to variations in the enzyme concentration had a transient increase along the reaction progress with a maximum at high substrate conversion levels. The same behaviour was derived for the sensitivity in classical homogeneous enzymatic assays and experimental evidence of this was obtained. The impact of the transient increase of the sensitivity on the error structure, and on the ability of homogeneous end-point enzymatic assays to detect competitive inhibition, came into focus. First, a non-monotonous shape in the standard deviation of progress curve data was found and it was attributed to the random dispersion in the enzyme concentration operating through the transient increase in the sensitivity. Second, a model for the detection limit of the quantity Ki/[I] (the IDL-factor) as a function of the substrate conversion level was developed for homogeneous end-point enzymatic assays. It was found that the substrate conversion level where the IDL-factor reached an optimum was beyond the initial velocity range. Moreover, at this optimal point not only the ability to detect inhibitors but also the robustness of the assays was maximized. These results may prove to be relevant in drug discovery for optimising end point homogeneous enzymatic assays that are used to find inhibitors against a target enzyme in compound libraries, which are usually big (>10000) and crowded with irrelevant compounds

Sensitivity, Noise and Detection of Enzyme Inhibition in Progress Curves

Starting with the development of an enzymatic assay, where an enzyme in solution hydrolysed a solid-phase bound peptide, a model for the kinetics of enzyme action was introduced. This model allowed the estimation of kinetic parameters and enzyme activity for a system that has the peculiarity of not being saturable with the substrate, but with the enzyme. In a derivation of the model, it was found that the sensitivity of the signal to variations in the enzyme concentration had a transient increase along the reaction progress with a maximum at high substrate conversion levels. The same behaviour was derived for the sensitivity in classical homogeneous enzymatic assays and experimental evidence of this was obtained. The impact of the transient increase of the sensitivity on the error structure, and on the ability of homogeneous end-point enzymatic assays to detect competitive inhibition, came into focus. First, a non-monotonous shape in the standard deviation of progress curve data was found and it was attributed to the random dispersion in the enzyme concentration operating through the transient increase in the sensitivity. Second, a model for the detection limit of the quantity Ki/[I] (the IDL-factor) as a function of the substrate conversion level was developed for homogeneous end-point enzymatic assays. It was found that the substrate conversion level where the IDL-factor reached an optimum was beyond the initial velocity range. Moreover, at this optimal point not only the ability to detect inhibitors but also the robustness of the assays was maximized. These results may prove to be relevant in drug discovery for optimising end point homogeneous enzymatic assays that are used to find inhibitors against a target enzyme in compound libraries, which are usually big (>10000) and crowded with irrelevant compounds

Segregation and Crosstalk of D1 Receptor-Mediated Activation of ERK in Striatal Medium Spiny Neurons upon Acute Administration of Psychostimulants

<div><p>The convergence of corticostriatal glutamate and dopamine from the midbrain in the striatal medium spiny neurons (MSN) triggers synaptic plasticity that underlies reinforcement learning and pathological conditions such as psychostimulant addiction. The increase in striatal dopamine produced by the acute administration of psychostimulants has been found to activate not only effectors of the AC5/cAMP/PKA signaling cascade such as GluR1, but also effectors of the NMDAR/Ca²⁺/RAS cascade such as ERK. The dopamine-triggered effects on both these cascades are mediated by D1R coupled to Golf but while the phosphorylation of GluR1 is affected by reductions in the available amount of Golf but not of D1R, the activation of ERK follows the opposite pattern. This segregation is puzzling considering that D1R-induced Golf activation monotonically increases with DA and that there is crosstalk from the AC5/cAMP/PKA cascade to the NMDAR/Ca²⁺/RAS cascade via a STEP (a tyrosine phosphatase). In this work, we developed a signaling model which accounts for this segregation based on the assumption that a common pool of D1R and Golf is distributed in two D1R/Golf signaling compartments. This model integrates a relatively large amount of experimental data for neurons in vivo and in vitro. We used it to explore the crosstalk topologies under which the sensitivities of the AC5/cAMP/PKA signaling cascade to reductions in D1R or Golf are transferred or not to the activation of ERK. We found that the sequestration of STEP by its substrate ERK together with the insensitivity of STEP activity on targets upstream of ERK (i.e. Fyn and NR2B) to PKA phosphorylation are able to explain the experimentally observed segregation. This model provides a quantitative framework for simulation based experiments to study signaling required for long term potentiation in MSNs.</p></div

The effect of mutants on APA-induced ERK activation and GluR1 phosphorylation @845.

<p>A) Subnetwork representing the edges used to generate different crosstalking schemes. A sequence of edge numeric identifiers defines a crosstalking scheme. B) Grey-scale legend, binary encoding, edge-encoding and goodness of fit (r²) for the different crosstalking schemes. The resulting levels of active ERK and <a href="mailto:GluR1@845" target="_blank">GluR1@845</a> at 15′ after psychostimulant injection do depend on the crosstalking scheme. The scheme 010 is the one closest (r² = 0.8, * label) to the experimental values (dashed red line) for D1R (D) and Golf (E) haploinsufficiency and also for DARPP32 knock out (F). The other crosstalking schemes failed in one or more phenotypes as judged by the low r² (B). With the 010 crosstalking scheme, the model closely matches all the phenotypes (C). The colored dots correspond to the mutant's phenotypes, while the empty circles represent the non-APA phenotypes.</p

Quantitative phenotypes used to constrain and challenge the model.

<p>STEPact, non-phosphorylated STEP over total STEP; D32p34, DARPP32 phosphorylated in threonine 34; D32p75, DARPP32 phosphorylated in threonine 75; PFC, prefrontal cortex; APA, acute psychostimulant administration; WT, wild type; IB, immunoblot; ERKpp, active ERK; GluR1p, AMPAR subunit GluR1 phosphorylated in the PKA site; t. series, time series; Monoexp, monoexponential. The names of the phenotypic variables are built from the name and marker columns except for parameterized time series or dose responses where it is used the parameter name instead of the marker.</p