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At least 325 records · Page 18Linked to original sources

PubMed2006

Large-scale neural ensemble recording in the brains of freely behaving mice.

With the availability of sophisticated genetic techniques, the mouse is a valuable mammalian model to study the molecular and cellular basis of cognitive behaviors. However, the small size of mice makes it difficult for a systematic investigation of activity patterns of neural networks in vivo. Here we report the development and construction of a high-density ensemble recording array with up to 128-recording channels that can be formatted as single electrodes, stereotrodes, or tetrodes. This high-density recording array is capable of recording from hundreds of individual neurons simultaneously in the hippocampus of the freely behaving mice. This large-scale in vivo ensemble recording techniques, once coupled with mouse genetics, should be valuable to the study of complex relationship between the genes, neural network, and cognitive behaviors.

Action Potentials↗

PubMed2005

A perspective on how the Vitamin D sterol/Vitamin D receptor (VDR) conformational ensemble model can potentially be used to understand the structure-function results of A-ring modified Vitamin D sterols.

The steroid hormone 1alpha,25(OH)(2)-Vitamin D(3) (1,25D) activates both genomic and non-genomic intracellular signaling cascades. It is also well recognized that co-incubation of 1,25D with its C-1 epimer, 1beta,25D (HL), suppresses the efficiency of the non-genomic signal activated by 1,25D alone and that its C-3 epimer, 3alpha-1,25D (HJ) is nearly as potent as 1,25D in suppressing PTH secretion, believed to be propagated by 1,25D's genomic signaling. Both these sterols lack the hypercalcemic effect induced by pharmacological doses of 1,25D and have reduced VDR affinity compared to 1,25D, as measured in a steroid competition assay. Recent functional studies suggest that the VDR is required for both non-genomic and genomic signaling. Along these lines we have recently proposed a Vitamin D sterol/VDR conformational ensemble model that posits the VDR contains two distinct, yet overlapping ligand binding sites, and that the potential differential stabilities of 1,25D and HL in these two pockets can be used to explain their different non-genomic signaling properties. The overlapping region is predominantly occupied by the sterol's A-ring when it is bound to either the genomic ligand binding pocket (G-pocket), defined by X-ray crystallography, or the alternative ligand binding pocket (A-pocket), discovered using in silico techniques (directed docking). Therefore, to gain further insight into the potential application of this model we docked the other A-ring diastereomer [(1beta,3alpha)=HH] of 1,25D and its 1- and 3-deoxy forms (25D and CF, respectively) to the A- and G-pockets to assess their potential stabilities in the pockets, relative to 1,25D. The models were then used to provide putative mechanistic arguments for their known structure-function experimental results. This model may provide new insights into how Vitamin D sterols that uncouple the unwanted hypercalcemic effect from attractive growth inhibitory/differentiation properties can do so by differentially stabilizing different subpopulations of VDR conformational ensemble members.

Animals↗

PubMed2004

Spin-mediated consciousness theory: possible roles of neural membrane nuclear spin ensembles and paramagnetic oxygen.

A novel theory of consciousness is proposed in this paper. We postulate that consciousness is intrinsically connected to quantum spin since the latter is the origin of quantum effects in both Bohm and Hestenes quantum formulism and a fundamental quantum process associated with the structure of space-time. That is, spin is the "mind-pixel". The unity of mind is achieved by entanglement of the mind-pixels. Applying these ideas to the particular structures and dynamics of the brain, we theorize that human brain works as follows: through action potential modulated nuclear spin interactions and paramagnetic O2/NO driven activations, the nuclear spins inside neural membranes and proteins form various entangled quantum states some of which survive decoherence through quantum Zeno effects or in decoherence-free subspaces and then collapse contextually via irreversible and non-computable means producing consciousness and, in turn, the collective spin dynamics associated with said collapses have effects through spin chemistry on classical neural activities thus influencing the neural networks of the brain. Our proposal calls for extension of associative encoding of neural memories to the dynamical structures of neural membranes and proteins. Thus, according our theory, the nuclear spin ensembles are the "mind-screen" with nuclear spins as its pixels, the neural membranes and proteins are the mind-screen and memory matrices, and the biologically available paramagnetic species such as O2 and NO are pixel-activating agents. Together, they form the neural substrates of consciousness. We also present supporting evidence and make important predictions. We stress that our theory is experimentally verifiable with present technologies. Further, experimental realizations of intra-/inter-molecular nuclear spin coherence and entanglement, macroscopic entanglement of spin ensembles and NMR quantum computation, all in room temperatures, strongly suggest the possibility of a spin-mediated mind.

Action Potentials↗

PubMed2007

Is there a tipping point in neuronal ensembles during learning?

Learning is important for humans and can be disrupted by disease. However, the essence of how learning may be represented within a neuronal network is still elusive. Spike trains generated by neurons have been demonstrated to carry information which is relevant for learning. The present study uses well-established mutual information (MI) analysis techniques to better understand learning within neuronal ensembles. Spike trains in tetrode recordings from the dorso-lateral striatum were used for computing MI as rats learnt a T-maze procedural task. We demonstrate that in in-vivo recordings the growth of MI is reflected in the behavioral response as learning proceeds. These changes in MI are seen to correspond to three phases, a low MI value, namely early learning, a rapid increase in MI value, task-acquisition and stabilization of MI, over-training. Over multiple training sessions, small changes in MI within the neuronal network suddenly produce a big change in ensemble MI during the task acquisition phase. This phase represents the "tipping point" in the neuronal network where the MI growth builds habits during motor learning in the striatum.

Action Potentials↗

PubMed2006

Rapid alterations in corticostriatal ensemble coordination during acute dopamine-dependent motor dysfunction.

Dopaminergic dysregulation can cause motor dysfunction, but the mechanisms underlying dopamine-related motor disorders remain under debate. We used an inducible and reversible pharmacogenetic approach in dopamine transporter knockout mice to investigate the simultaneous activity of neuronal ensembles in the dorsolateral striatum and primary motor cortex during hyperdopaminergia ( approximately 500% of controls) with hyperkinesia, and after rapid and profound dopamine depletion (<0.2%) with akinesia in the same animal. Surprisingly, although most cortical and striatal neurons ( approximately 70%) changed firing rate during the transition between dopamine-related hyperkinesia and akinesia, the overall cortical firing rate remained unchanged. Conversely, neuronal oscillations and ensemble activity coordination within and between cortex and striatum did change rapidly between these periods. During hyperkinesia, corticostriatal activity became largely asynchronous, while during dopamine-depletion the synchronicity increased. Thus, dopamine-related disorders like Parkinson's disease may not stem from changes in the overall levels of cortical activity, but from dysfunctional activity coordination in corticostriatal circuits.

Action Potentials↗

PubMed2006

Top-down control of motor cortex ensembles by dorsomedial prefrontal cortex.

Dorsomedial prefrontal cortex is critical for the temporal control of behavior. Dorsomedial prefrontal cortex might alter neuronal activity in areas such as motor cortex to inhibit temporally inappropriate responses. We tested this hypothesis by recording from neuronal ensembles in rodent dorsomedial prefrontal cortex during a delayed-response task. One-third of dorsomedial prefrontal neurons were significantly modulated during the delay period. The activity of many of these neurons was predictive of premature responding. We then reversibly inactivated dorsomedial prefrontal cortex while recording ensemble activity in motor cortex. Inactivation of dorsomedial prefrontal cortex reduced delay-related firing, but not response-related firing, in motor cortex. Finally, we made simultaneous recordings in dorsomedial prefrontal cortex and motor cortex and found strong delay-related temporal correlations between neurons in the two cortical areas. These data suggest that functional interactions between dorsomedial prefrontal cortex and motor cortex might serve as a top-down control signal that inhibits inappropriate responding.

Animals↗

PubMed2004

Complementarity of structure ensembles in protein-protein binding.

Protein-protein association is often accompanied by changes in receptor and ligand structure. This interplay between protein flexibility and protein-protein recognition is currently the largest obstacle both to our understanding of and to the reliable prediction of protein complexes. We performed two sets of molecular dynamics simulations for the unbound receptor and ligand structures of 17 protein complexes and applied shape-driven rigid body docking to all combinations of representative snapshots. The crossdocking of structure ensembles increased the likelihood of finding near-native solutions. The free ensembles appeared to contain multiple complementary conformations. These were in general not related to the bound structure. We suggest that protein-protein binding follows a three-step mechanism of diffusion, free conformer selection, and refolding. This model combines previously conflicting ideas and is in better agreement with the current data on interaction forces, time scales, and kinetics.

Models, Molecular↗

PubMed2004

Genome information resources - developments at Ensembl.

Genome information resources such as Ensembl manage and present DNA sequence and annotation arising from genome projects. Recent developments in the Ensembl system include access to inter-species comparisons at both the genomic and protein sequence levels and improvements to the display of polymorphism data. Users can now display their own data in the context of other annotation. In addition, a fast and flexible data retrieval system, EnsMart, has been developed.

Animals↗

PubMed1987

Determination of cell membrane permeability in concentrated cell ensembles.

The method of volume averaging is used to analyze the process of diffusion in concentrated cell ensembles in which significant resistance to mass transfer is caused by the cellular membrane. A general closure scheme is given that allows for direct theoretical prediction of effective diffusivities for any cellular geometry. Numerical results are presented for the classical parallelepiped arrangement used to model cellular systems, and these results are used in conjunction with experimental studies of concentrated cell ensembles to determine membrane permeabilities for solute diffusion in several cellular systems. Membrane permeabilities are compared with predictions from other models of diffusion in cellular systems.

Animals↗

PubMed2002

Differential salt-induced stabilization of structure in the initial folding intermediate ensemble of barstar.

The effects of two salts, KCl and MgCl(2), on the stability and folding kinetics of barstar have been studied at pH 8. Equilibrium urea unfolding curves were used to show that the free energy of unfolding, deltaG(UN), of barstar increased from a value of 4.7 kcalmol(-1) in the absence of salt to a value of 6.9 kcalmol(-1) in the presence of 1M KCl or 1M MgCl(2). For both salts, deltaG(UN) increases linearly with an increase in concentration of salt from 0M to 1M, suggesting that stabilization of the native state occurs primarily through a Hofmeister effect. Refolding kinetics were studied in detail in the presence of 1M KCl as well as in the presence of 1M MgCl(2), and it is shown that the basic folding mechanism is not altered upon addition of salt. The major effects on the refolding kinetics can be attributed to the stabilization of the initial burst phase ensemble, I(E), by salt. Stabilization of structure in I(E) by KCl causes the fluorescence properties of I(E) to change, so that there is an initial burst phase change in fluorescence at 320 nm, during refolding. The structure in I(E) is stabilized by MgCl(2), but no burst phase change in fluorescence at 320 nm is observed during refolding. The fluorescence emission spectra of I(E) show that when refolding is initiated in 1M KCl, the three tryptophan residues in I(E) are less solvent exposed than when folding is initiated in 1M MgCl(2). Stabilization of I(E) leads to an acceleration in the rate of the fast observable phase of folding by both salts, suggesting that structure of the transition state resembles that of I(E). The stabilization of I(E) by salts can be accounted for largely by the same mechanism that accounts for the stabilization of the native state of the protein, namely through the Hofmeister effect. The salts do not affect the rates of the slower phases of folding, indicating that the late intermediate ensemble, I(L), is not stabilized by salts. Stabilization of the native state results in deceleration of the fast unfolding rate, which has virtually no dependence on the concentration of KCl or MgCl(2) at high concentrations. The observation that the salt-induced stabilization of structure in I(E) is accompanied by an acceleration in the fast folding rate, suggests that I(E) is likely to be a productive on-pathway intermediate.

Bacterial Proteins↗

PubMed1998

Demography and the canonical ensemble.

The Gibbs canonical ensemble of statistical mechanics is used to describe the probability distribution of the age classes of mothers of new-borns in an age-structured population. The Malthusian parameter emerges as a Lagrange multiplier corresponding to a generation time constraint, while a new perturbation parameter appears as the Lagrange multiplier corresponding to a maternity constraint. Classical Lotka stability reduces to the unperturbed case of the more general canonical ensemble model. The model is used in a case study of the female (peninsular) Malaysian population of 1970. The Malthusian parameter and perturbation are calculated easily by linear regression. Use of the model identifies an anomaly in the population due to the effects of World War II.

Adolescent↗

PubMed2003

Modeling and analysis of dispersed-drug release into a finite medium from sphere ensembles with a boundary layer.

Mathematical models were developed and analytical solutions were derived for describing kinetics of dispersed-drug release into a finite external medium from multi-particulate systems, such as ensembles of matrix spheres and microcapsules with a diffusion boundary layer. The solutions can be used to compute profiles of the moving boundary of a dispersed drug and the amount of drug released for multiparticulate ensembles with various ratios of initial drug loading (C(0)) to drug solubility (C(s)) in a finite to infinite medium. They are also applicable to a single sphere without a boundary layer in a perfect sink. The determinants of release kinetics, such as the liquid volume, the initial drug loading, the boundary layer thickness, and the number of spheres in a population, were analyzed using the derived solutions. The effect of coating thickness and material on the release profiles of microcapsules was studied as well. Criteria were established for finding the conditions when drug release would stall due to saturation of the medium, which can be used to determine suitable liquid volume and time for refreshing the medium.

Capsules↗

PubMed2002

Gene expression data analysis of human lymphoma using support vector machines and output coding ensembles.

The large amount of data generated by DNA microarrays was originally analysed using unsupervised methods, such as clustering or self-organizing maps. Recently supervised methods such as decision trees, dot-product support vector machines (SVM) and multi-layer perceptrons (MLP) have been applied in order to classify normal and tumoural tissues. We propose methods based on non-linear SVM with polynomial and Gaussian kernels, and output coding (OC) ensembles of learning machines to separate normal from malignant tissues, to classify different types of lymphoma and to analyse the role of sets of coordinately expressed genes in carcinogenic processes of lymphoid tissues. Using gene expression data from "Lymphochip", a specialised DNA microarray developed at Stanford University School of Medicine, we show that SVM can correctly separate normal from tumoural tissues, and OC ensembles can be successfully used to classify different types of lymphoma. Moreover, we identify a group of coordinately expressed genes related to the separation of two distinct subgroups inside diffuse large B-cell lymphoma (DLBCL), validating a previous Alizadeh's hypothesis about the existence of two distinct diseases inside DLBCL.

Artificial Intelligence↗

PubMed2003

Orientation restraints in molecular dynamics simulations using time and ensemble averaging.

In this article we present methodology for simulating protein dynamics while imposing restraints derived from NMR measurements on partially ordered molecules. Such measurements may include residual dipolar couplings and chemical-shift anisotropies. We define a restraint potential for use in molecular dynamics and energy minimization. The presented potential is consistent with the simultaneously optimized molecular order tensor. Restraining can be performed with time and ensemble averaging. We performed a large number of molecular dynamics simulations of the histidine containing phosphocarrier protein with restraints on backbone N-H vector orientations derived from residual dipolar couplings. From these simulations it is evident that the use of time- or ensemble-averaged restraints is essential to leave the fluctuations of the restrained vectors unaffected. Without averaging the fluctuations of the restrained vectors are reduced significantly. This also has the effect of decreasing the apparent molecular order-parameter tensor.

Algorithms↗

PubMed2005

Fabrication of 3D gold nanoelectrode ensembles by chemical etching.

A simple chemical etching procedure based on the solubility of polycarbonate membranes in solvent mixtures is reported for fabricating 3D gold nanoelectrode ensembles. A solvent ratio of 50:50 dichloromethane/ethanol was found to be optimum for selective controlled etching of the surface layers of the polycarbonate membranes to expose up to 200-nm lengths of gold nanowires. The absence of double layer charging current in cyclic voltammograms of the resulting 3D nanoelectrode ensemble verified that the seal between the gold nanowires and the polycarbonate membrane was not compromised as a result of the chemical etching.

Gold↗

PubMed2006

Revealing the nature of the native state ensemble through cold denaturation.

Recent advances in NMR methodology have enabled the structural analysis of proteins at temperatures far below the freezing point of water, thus opening a window to the cold denaturation process. Although the phenomenon of cold denaturation has been known since the mid-1970s, the freezing point of water has prevented detailed and structurally resolved studies without application of additional significant perturbations of the protein ensemble. As a result, the cold-denatured state and the process of cold denaturation have gone largely unstudied. Here, the structural and thermodynamic basis of cold denaturation is explored with emphasis placed on the insights that are uniquely ascertained from low-temperature studies. It is shown that the noncooperative cold-induced unfolding of protein results in the population of partially folded states that cannot be accessed by other techniques. The structurally resolved view of the cold denaturation process therefore can provide direct access to the cooperative substructures within the protein molecule and provide an unprecedented structurally resolved picture of the states that comprise the native state ensemble.

Animals↗

PubMed1999

The native state conformational ensemble of the SH3 domain from alpha-spectrin.

The folding/unfolding equilibrium of the alpha-spectrin SH3 domain has been measured by NMR-detected hydrogen/deuterium exchange and by differential scanning calorimetry. Protection factors against exchange have been obtained under native conditions for more than half of the residues in the domain. Most protected residues are located at the beta-strands, the short 3(10) helix, and part of the long RT loop, whereas the loops connecting secondary structure elements show no measurable protection. Apparent stability constants per residue and their corresponding Gibbs energies have been calculated from the exchange experiments. The most stable region of the SH3 domain is defined by the central portions of the beta-strands. The peptide binding region, on the other hand, is composed of a highly stable region (residues 53-57) and a highly unstable region, the loop between residues 34-41 (n-Src loop). All residues in the domain have apparent Gibbs energies lower than the global unfolding Gibbs energy measured by differential scanning calorimetry, indicating that under our experimental conditions the amide exchange of all residues in the SH3 domain occurs primarily via local unfolding reactions. A structure-based thermodynamic analysis has allowed us to predict correctly the thermodynamics of the global unfolding of the domain and to define the ensemble of conformational states that quantitatively accounts for the observed pattern of hydrogen exchange protection. These results demonstrate that under native conditions the SH3 domain needs to be considered as an ensemble of conformations and that the hydrogen exchange data obtained under those conditions cannot be interpreted by a two-state equilibrium. The observation that specific regions of a protein are able to undergo independent local folding/unfolding reactions indicates that under native conditions the scale of cooperative interactions is regional rather than global.

Calorimetry, Differential Scanning↗

PubMedDate not supplied

Predicting the genotoxicity of secondary and aromatic amines using data subsetting to generate a model ensemble.

Binary quantitative structure-activity relationship (QSAR) models are developed to classify a data set of 334 aromatic and secondary amine compounds as genotoxic or nongenotoxic based on information calculated solely from chemical structure. Genotoxic endpoints for each compound were determined using the SOS Chromotest in both the presence and absence of an S9 rat liver homogenate. Compounds were considered genotoxic if assay results indicated a positive genotoxicity hit for either the S9 inactivated or S9 activated assay. Each compound in the data set was encoded through the calculation of numerical descriptors that describe various aspects of chemical structure (e.g. topological, geometric, electronic, polar surface area). Furthermore, five additional descriptors that focused on the secondary and aromatic nitrogen atoms in each molecule were calculated specifically for this study. Descriptor subsets were examined using a genetic algorithm search engine interfaced with a k-Nearest Neighbor fitness evaluator to find the most information-rich subsets, which ultimately served as the final predictive models. Models were chosen for their ability to minimize the total number of misclassifications, with special attention given to those models that possessed fewer occurrences of positive toxicity hits being misclassified as nontoxic (false negatives). In addition, a subsetting procedure was used to form an ensemble of models using different combinations of compounds in the training and prediction sets. This was done to ensure that consistent results could be obtained regardless of training set composition. The procedure also allowed for each compound to be externally validated three times by different training set data with the resultant predictions being used in a "majority rules" voting scheme to produce a consensus prediction for each member of the data set. The individual models produced an average training set classification rate of 71.6% and an average prediction set classification rate of 67.7%. However, the model ensemble was able to correctly classify the genotoxicity of 72.2% of all prediction set compounds.

Algorithms↗