Neurosteroids: Deficient cognitive performance in aged rats depends on low pregnenolone sulfate levels in the hippocampus

Pregnenolone sulfate (PREG S) is synthesized in the nervous system and is a major neurosteroid in the rat brain. Its concentrations were measured in the hippocampus and other brain areas of single adult and aged (22–24 month-old) male Sprague–Dawley rats. Significantly lower levels were found in aged rats, although the values were widely scattered and reached, in about half the animals, the same range as those of young ones. The spatial memory performances of aged rats were investigated in two different spatial memory tasks, the Morris water maze and Y-maze. Performances in both tests were significantly correlated and, accompanied by appropriate controls, likely evaluated genuine memory function. Importantly, individual hippocampal PREG S and distance to reach the platform in the water maze were linked by a significant correlation, i.e., those rats with lower memory deficit had the highest PREG S levels, whereas no relationship was found with the PREG S content in other brain areas (amygdala, prefrontal cortex, parietal cortex, striatum). Moreover, the memory deficit of cognitively impaired aged rats was transiently corrected after either intraperitoneal or bilateral intrahippocampal injection of PREG S. PREG S is both a γ-aminobutyric acid antagonist and a positive allosteric modulator at the N-methyl-d-aspartate receptor, and may reinforce neurotransmitter system(s) that decline with age. Indeed, intracerebroventricular injection of PREG S was shown to stimulate acetylcholine release in the adult rat hippocampus. In conclusion, it is proposed that the hippocampal content of PREG S plays a physiological role in preserving and/or enhancing cognitive abilities in old animals, possibly via an interaction with central cholinergic systems. Thus, neurosteroids should be further studied in the context of prevention and/or treatment of age-related memory disorders.

Memory landscapes of single-enzyme molecules

Immobilized single horseradish peroxidase enzymes were observed by confocal fluorescence spectroscopy during catalysis of the oxidation reaction of the nonfluorescent dihydrorhodamine 6G substrate into the highly fluorescent product rhodamine 6G. By extracting only the non-Markovian behavior of the spectroscopic two-state process of enzyme-product complex formation and release, memory landscapes were generated for single-enzyme molecules. The memory landscapes can be used to discriminate between different origins of stretched exponential kinetics that are found in the first-order correlation analysis. Memory landscapes of single-enzyme data shows oscillations that are expected in a single-enzyme system that possesses a set of transient states. Alternative origins of the oscillations may not, however, be ruled out. The data and analysis indicate that substrate interaction with the enzyme selects a set of conformational substates for which the enzyme is active.

A novel approach for the identification of protein–protein interaction with integral membrane proteins

Protein–protein interaction plays a major role in all biological processes. The currently available genetic methods such as the two-hybrid system and the protein recruitment system are relatively limited in their ability to identify interactions with integral membrane proteins. Here we describe the development of a reverse Ras recruitment system (reverse RRS), in which the bait used encodes a membrane protein. The bait is expressed in its natural environment, the membrane, whereas the protein partner (the prey) is fused to a cytoplasmic Ras mutant. Protein–protein interaction between the proteins encoded by the prey and the bait results in Ras membrane translocation and activation of a viability pathway in yeast. We devised the expression of the bait and prey proteins under the control of dual distinct inducible promoters, thus enabling a rapid selection of transformants in which growth is attributed solely to specific protein–protein interaction. The reverse RRS approach greatly extends the usefulness of the protein recruitment systems and the use of integral membrane proteins as baits. The system serves as an attractive approach to explore novel protein–protein interactions with high specificity and selectivity, where other methods fail.

Memory from the dynamics of intrinsic membrane currents

Almost all theoretical and experimental studies of the mechanisms underlying learning and memory focus on synaptic efficacy and make the implicit assumption that changes in synaptic efficacy are both necessary and sufficient to account for learning and memory. However, network dynamics depends on the complex interaction between intrinsic membrane properties and synaptic strengths and time courses. Furthermore, neuronal activity itself modifies not only synaptic efficacy but also the intrinsic membrane properties of neurons. This paper presents examples demonstrating that neurons with complex temporal dynamics can provide short-term “memory” mechanisms that rely solely on intrinsic neuronal properties. Additionally, we discuss the potential role that activity may play in long-term modification of intrinsic neuronal properties. While not replacing synaptic plasticity as a powerful learning mechanism, these examples suggest that memory in networks results from an ongoing interplay between changes in synaptic efficacy and intrinsic membrane properties.

Muscarinic acetylcholine receptor expression in memory circuits: Implications for treatment of Alzheimer disease

Cholinergic transmission at muscarinic acetylcholine receptors (mAChR) has been implicated in higher brain functions such as learning and memory, and loss of synapses may contribute to the symptoms of Alzheimer disease. A heterogeneous family of five genetically distinct mAChR subtypes differentially modulate a variety of intracellular signaling systems as well as the processing of key molecules involved in the pathology of the disease. Although many muscarinic effects have been identified in memory circuits, including a diversity of pre- and post-synaptic actions in hippocampus, the identities of the molecular subtypes responsible for any given function remain elusive. All five mAChR genes are expressed in hippocampus, and subtype-specific antibodies have enabled identification, quantification, and localization of the encoded proteins. The m1, m2, and m4 mAChR proteins are most abundant in forebrain regions and they have distinct cellular and subcellular localizations suggestive of various pre- and postsynaptic functions in cholinergic circuits. The subtypes are also differentially altered in postmortem brain samples from Alzheimer disease cases. Further understanding of the molecular pharmacology of failing synapses in Alzheimer disease, together with the development of new subtype-selective drugs, may provide more specific and effective treatments for the disease.

Cross-talk between the insulin and angiotensin signaling systems.

Angiotensin II (AII), acting via its G-protein linked receptor, is an important regulator of cardiac, vascular, and renal function. Following injection of AII into rats, we find that there is also a rapid tyrosine phosphorylation of the major insulin receptor substrates 1 and 2 (IRS-1 and IRS-2) in the heart. This phenomenon appears to involve JAK2 tyrosine kinase, which associates with the AT1 receptor and IRS-1/IRS-2 after AII stimulation. AII-induced phosphorylation leads to binding of phosphatidylinositol 3-kinase (PI 3-kinase) to IRS-1 and IRS-2; however, in contrast to other ligands, AII injection results in an acute inhibition of both basal and insulin-stimulated PI 3-kinase activity. The latter occurs without any reduction in insulin receptor or IRS phosphorylation or in the interaction of the p85 and p110 subunits of PI 3-kinase with each other or with IRS-1/IRS-2. These effects of AII are inhibited by AT1 receptor antagonists. Thus, there is direct cross-talk between insulin and AII signaling pathways at the level of both tyrosine phosphorylation and PI 3-kinase activation. These interactions may play an important role in the association of insulin resistance, hypertension, and cardiovascular disease.

Phosphorylation of synaptic vesicle proteins: modulation of the alpha SNAP interaction with the core complex.

We analyzed whether synaptic membrane trafficking proteins are substrates for casein kinase II, calcium/calmodulin-dependent protein kinase II, and cAMP-dependent protein kinase (PKA), three kinases implicated in the modulation of synaptic transmission. Each kinase phosphorylates a specific set of the vesicle proteins syntaxin 1A, N-ethylmaleimide-sensitive factor (NSF), vesicle-associated membrane protein (VAMP), synaptosome-associated 25-kDa protein (SNAP-25), n-sec1, alpha soluble NSF attachment protein (alpha SNAP), and synaptotagmin. VAMP is phosphorylated by calcium/calmodulin-dependent protein kinase II on serine 61. alpha SNAP is phosphorylated by PKA; however, the beta SNAP isoform is phosphorylated only 20% as efficiently. alpha SNAP phosphorylated by PKA binds to the core docking and fusion complex 10 times weaker than the dephosphorylated form. These studies provide a first glimpse at regulatory events that may be important in modulating neurotransmitter release during learning and memory.

Reverse two-hybrid and one-hybrid systems to detect dissociation of protein-protein and DNA-protein interactions.

Macromolecular interactions define many biological phenomena. Although genetic methods are available to identify novel protein-protein and DNA-protein interactions, no genetic system has thus far been described to identify molecules or mutations that dissociate known interactions. Herein, we describe genetic systems that detect such events in the yeast Saccharomyces cerevisiae. We have engineered yeast strains in which the interaction of two proteins expressed in the context of the two-hybrid system or the interaction between a DNA-binding protein and its binding site in the context of the one-hybrid system is deleterious to growth. Under these conditions, dissociation of the interaction provides a selective growth advantage, thereby facilitating detection. These methods referred to as the "reverse two-hybrid system" and "reverse one-hybrid system" facilitate the study of the structure-function relationships and regulation of protein-protein and DNA-protein interactions. They should also facilitate the selection of dissociator molecules that could be used as therapeutic agents.

Genetic characterization of a mammalian protein-protein interaction domain by using a yeast reverse two-hybrid system.

Many biological processes rely upon protein-protein interactions. Hence, detailed analysis of these interactions is critical for their understanding. Due to the complexities involved, genetic approaches are often needed. In yeast and phage, genetic characterizations of protein complexes are possible. However, in multicellular organisms, such characterizations are limited by the lack of powerful selection systems. Herein we describe genetic selections that allow single amino acid changes that disrupt protein-protein interactions to be selected from large libraries of randomly generated mutant alleles. The strategy, based on a yeast reverse two-hybrid system, involves a first-step negative selection for mutations that affect interaction, followed by a second-step positive selection for a subset of these mutations that maintain expression of full-length protein (two-step selection). We have selected such mutations in the transcription factor E2F1 that affect its ability to heterodimerize with DP1. The mutations obtained identified a putative helix in the marked box, a region conserved among E2F family members, as an important determinant for interaction. This two-step selection procedure can be used to characterize any interaction domain that can be tested in the two-hybrid system.

The role of DT-diaphorase in the maintenance of the reduced antioxidant form of coenzyme Q in membrane systems.

The experiments reported here were designed to test the hypothesis that the two-electron quinone reductase DT-diaphorase [NAD(P)H:(quinone-acceptor) oxidoreductase, EC 1.6.99.2] functions to maintain membrane-bound coenzyme Q (CoQ) in its reduced antioxidant state, thereby providing protection from free radical damage. DT-diaphorase was isolated and purified from rat liver cytosol, and its ability to reduce several CoQ homologs incorporated into large unilamellar vesicles was demonstrated. Addition of NADH and DT-diaphorase to either large unilamellar or multilamellar vesicles containing homologs of CoQ, including CoQ9 and CoQ10, resulted in the essentially complete reduction of the CoQ. The ability of DT-diaphorase to maintain the reduced state of CoQ and protect membrane components from free radical damage as lipid peroxidation was tested by incorporating either reduced CoQ9 or CoQ10 and the lipophylic azoinitiator 2,2'-azobis(2,4-dimethylvaleronitrile) into multilamellar vesicles in the presence of NADH and DT-diaphorase. The presence of DT-diaphorase prevented the oxidation of reduced CoQ and inhibited lipid peroxidation. The interaction between DT-diaphorase and CoQ was also demonstrated in an isolated rat liver hepatocyte system. Incubation with adriamycin resulted in mitochondrial membrane damage as measured by membrane potential and the release of hydrogen peroxide. Incorporation of CoQ10 provided protection from adriamycin-induced mitochondrial membrane damage. The incorporation of dicoumarol, a potent inhibitor of DT-diaphorase, interfered with the protection provided by CoQ. The results of these experiments provide support for the hypothesis that DT-diaphorase functions as an antioxidant in both artificial membrane and natural membrane systems by acting as a two-electron CoQ reductase that forms and maintains the antioxidant form of CoQ. The suggestion is offered that DT-diaphorase was selected during evolution to perform this role and that its conversion of xenobiotics and other synthetic molecules is secondary and coincidental.

Adrenocortical suppression blocks the memory-enhancing effects of amphetamine and epinephrine.

This study examined glucocorticoid-adrenergic interactions in modulating acquisition and memory storage for inhibitory avoidance training. Systemically (s.c.) administered amphetamine (1 mg/kg), but not epinephrine (0.1 mg/kg) or the peripherally acting amphetamine derivative 4-OH amphetamine (2 mg/kg), given to rats shortly before training facilitated acquisition performance in a continuous multiple-trial inhibitory avoidance (CMIA) task. Adrenocortical suppression with the 11beta-hydroxylase inhibitor metyrapone (50 mg/kg; s.c.), given to rats 90 min before training, did not block the effect of amphetamine and did not affect acquisition performance of otherwise untreated animals. Retention of CMIA and one-trial inhibitory avoidance was enhanced by either pre- or posttraining injections of amphetamine as well as 4-OH amphetamine and epinephrine. The finding that injections of amphetamine and epinephrine have comparable effects on memory is consistent with the view that amphetamine may modulate memory storage, at least in part, by inducing the release of epinephrine from the adrenal medulla. Metyrapone pretreatment blocked the memory-enhancing effects of amphetamine, 4-OH amphetamine, and epinephrine but did not affect retention performance of otherwise untreated animals. Posttraining injections of different doses of epinephrine (ranging from 0.0001 to 1.0 mg/kg) produced a dose-dependent memory enhancement for inhibitory avoidance training and metyrapone blocked the memory-enhancing effects of all these doses. These findings provide further evidence that the sympathoadrenal and adrenocortical systems are intimately coupled during processes of memory storage.

On the development of advanced techniques for mixed-elastohydrodynamic lubrification modelling of journal and sliding bearing systems.

The present thesis is focused on the development of a thorough mathematical modelling and computational solution framework aimed at the numerical simulation of journal and sliding bearing systems operating under a wide range of lubrication regimes (mixed, elastohydrodynamic and full film lubrication regimes) and working conditions (static, quasi-static and transient conditions). The fluid flow effects have been considered in terms of the Isothermal Generalized Equation of the Mechanics of the Viscous Thin Films (Reynolds equation), along with the massconserving p-Ø Elrod-Adams cavitation model that accordingly ensures the so-called JFO complementary boundary conditions for fluid film rupture. The variation of the lubricant rheological properties due to the viscous-pressure (Barus and Roelands equations), viscous-shear-thinning (Eyring and Carreau-Yasuda equations) and density-pressure (Dowson-Higginson equation) relationships have also been taken into account in the overall modelling. Generic models have been derived for the aforementioned bearing components in order to enable their applications in general multibody dynamic systems (MDS), and by including the effects of angular misalignments, superficial geometric defects (form/waviness deviations, EHL deformations, etc.) and axial motion. The bearing exibility (conformal EHL) has been incorporated by means of FEM model reduction (or condensation) techniques. The macroscopic in fluence of the mixedlubrication phenomena have been included into the modelling by the stochastic Patir and Cheng average ow model and the Greenwood-Williamson/Greenwood-Tripp formulations for rough contacts. Furthermore, a deterministic mixed-lubrication model with inter-asperity cavitation has also been proposed for full-scale simulations in the microscopic (roughness) level. According to the extensive mathematical modelling background established, three significant contributions have been accomplished. Firstly, a general numerical solution for the Reynolds lubrication equation with the mass-conserving p - Ø cavitation model has been developed based on the hybridtype Element-Based Finite Volume Method (EbFVM). This new solution scheme allows solving lubrication problems with complex geometries to be discretized by unstructured grids. The numerical method was validated in agreement with several example cases from the literature, and further used in numerical experiments to explore its exibility in coping with irregular meshes for reducing the number of nodes required in the solution of textured sliding bearings. Secondly, novel robust partitioned techniques, namely: Fixed Point Gauss-Seidel Method (PGMF), Point Gauss-Seidel Method with Aitken Acceleration (PGMA) and Interface Quasi-Newton Method with Inverse Jacobian from Least-Squares approximation (IQN-ILS), commonly adopted for solving uid-structure interaction problems have been introduced in the context of tribological simulations, particularly for the coupled calculation of dynamic conformal EHL contacts. The performance of such partitioned methods was evaluated according to simulations of dynamically loaded connecting-rod big-end bearings of both heavy-duty and high-speed engines. Finally, the proposed deterministic mixed-lubrication modelling was applied to investigate the in fluence of the cylinder liner wear after a 100h dynamometer engine test on the hydrodynamic pressure generation and friction of Twin-Land Oil Control Rings.

Human-computer interaction for optical music recognition tasks

The need to digitise music scores has led to the development of Optical Music Recognition (OMR) tools. Unfortunately, the performance of these systems is still far from providing acceptable results. This situation forces the user to be involved in the process due to the need of correcting the mistakes made during recognition. However, this correction is performed over the output of the system, so these interventions are not exploited to improve the performance of the recognition. This work sets the scenario in which human and machine interact to accurately complete the OMR task with the least possible effort for the user.

Grouping genetic operators for the delineation of functional areas based on spatial interaction

The delineation of functional economic areas, or market areas, is a problem of high practical relevance, since the delineation of functional sets such as economic areas in the US, Travel-to-Work Areas in the United Kingdom, and their counterparts in other OECD countries are the basis of many statistical operations and policy making decisions at local level. This is a combinatorial optimisation problem defined as the partition of a given set of indivisible spatial units (covering a territory) into regions characterised by being (a) self-contained and (b) cohesive, in terms of spatial interaction data (flows, relationships). Usually, each region must reach a minimum size and self-containment level, and must be continuous. Although these optimisation problems have been typically solved through greedy methods, a recent strand of the literature in this field has been concerned with the use of evolutionary algorithms with ad hoc operators. Although these algorithms have proved to be successful in improving the results of some of the more widely applied official procedures, they are so time consuming that cannot be applied directly to solve real-world problems. In this paper we propose a new set of group-based mutation operators, featuring general operations over disjoint groups, tailored to ensure that all the constraints are respected during the operation to improve efficiency. A comparative analysis of our results with those from previous approaches shows that the proposed algorithm systematically improves them in terms of both quality and processing time, something of crucial relevance since it allows dealing with most large, real-world problems in reasonable time.

A Survey on FPGA-Based Sensor Systems: Towards Intelligent and Reconfigurable Low-Power Sensors for Computer Vision, Control and Signal Processing

The current trend in the evolution of sensor systems seeks ways to provide more accuracy and resolution, while at the same time decreasing the size and power consumption. The use of Field Programmable Gate Arrays (FPGAs) provides specific reprogrammable hardware technology that can be properly exploited to obtain a reconfigurable sensor system. This adaptation capability enables the implementation of complex applications using the partial reconfigurability at a very low-power consumption. For highly demanding tasks FPGAs have been favored due to the high efficiency provided by their architectural flexibility (parallelism, on-chip memory, etc.), reconfigurability and superb performance in the development of algorithms. FPGAs have improved the performance of sensor systems and have triggered a clear increase in their use in new fields of application. A new generation of smarter, reconfigurable and lower power consumption sensors is being developed in Spain based on FPGAs. In this paper, a review of these developments is presented, describing as well the FPGA technologies employed by the different research groups and providing an overview of future research within this field.