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At least 1,423 records · Page 79Linked to original sources
PubMed1997

Compaction as a method to characterise fibrin network structure: kinetic studies and relationship to crosslinking.

While it has been shown that compaction is inversely correlated to the Young's modulus of elasticity of the network and to the final strength at break, the relationship between collapsibility of the network subjected to a standardised centrifugal force and the degree of crosslinking (i.e., compaction) has not been properly addressed. Three sets of networks developed from plasma and pure fibrinogen solution, with varying degree of crosslinking induced by the addition of different amounts of calcium, were subjected to centrifugation at 8000g. In networks developed from plasma, compaction correlated with the degree of crosslinking. Whilst totally crosslinked clots were most resistant to collapse, partially crosslinked clots were far less resistant to collapse. In purified fibrinogen, however, the effect crosslinking was all or nothing. Both totally crosslinked and partially crosslinked clots were equally resistant to collapse. Calcium induced crosslinking provides fibrin with the required strengthening of the fibrin network. However, there are also fibre to fibre interactions as can be observed in networks developed in the presence of drugs like gliclazide. Compaction is a simple technique which can be used in any clinical laboratory to characterise the degree of crosslinking and also the tensile properties of the network.

Cross-Linking Reagents↗
PubMed2000

Social networks, ideation, and contraceptive behavior in Bangladesh: a longitudinal analysis.

Longitudinal survey data from a panel of married women in Bangladesh is used to estimate the impact of a social network approach to family planning field worker communication and to test a theoretical model of behavior change that explains why women adopt modern contraceptives. Government field workers were trained to organize group discussions with women in the homes of opinion leaders located at central points in each village's social network. A set of intervening variables, referred to collectively as 'ideation', are derived from diffusion of innovation and social network theory to explain how the social network approach affects contraceptive behavior. The rate of increase in modern contraceptive use was found to be five times greater among women in the social network approach than among women who were visited by field workers at home. The impact of the social network approach on modern contraceptive use was almost double that of conventional field worker visits after controlling for the effects of prior contraceptive use and intention, prior home visits, and selected socio-demographic characteristics. Both approaches had the same degree of impact on ideation. The results confirm the influence of ideation on fertility change and suggest that family planning programs would benefit from training field workers to use a social network approach.

Adolescent↗
PubMed1997

Social network characteristics and injecting HIV-risk behaviors among street injection drug users.

As an alternative approach to individually-focused understanding of HIV risk behavior, this study explored the relationship between social network characteristics and HIV-risk injecting behaviors. Subjects were 499 inner-city injection drug users (IDUs) recruited from the streets of Baltimore, Maryland. Analysis of structural and functional network data indicates that a substantial proportion of drug sharing network members also provided social support, often because of family and sexual partner relationships. IDUs with larger drug networks which also provided social support were more likely to share needles, while IDUs with larger drug networks which did not provide social support were more likely to inject in commercial settings. The findings suggest that social support from drug network members has differential effects on injecting HIV-risk behaviors among IDUs. HIV prevention efforts should be expanded to reach drug-sharing networks and should take into account their social support relationships.

Adult↗
PubMed2000

Regeneration and maintenance of bile canalicular networks in collagen-sandwiched hepatocytes.

The morphological and cytoskeletal reorganization of collagen-sandwiched rat hepatocytes during the de novo formation of complete canalicular networks was examined by phase, fluorescence and electron microscopy. During the initial stages of membrane repolarization, there was a marked accumulation of both microfilaments and microtubules at the sites of canalicular generation. Microtubule-disrupting agents (colchicine, nocodazole) inhibited the localization of actin filaments at cell margins and the initiation and branching of canalicular networks. After removal of microtubule-disrupting agents, microfilaments relocalized to the canalicular borders and microtubules nucleated along the margins of the bile canaliculi at sites distinct from the peri-canalicular actin networks. Microfilament-perturbing agents (cytochalasin D, phalloidin) did not affect the de novo initiation of bile canaliculi and only slightly impaired the development of canalicular lumina into networks. In established cultures with complete canalicular networks, subsequent treatment with microtubule-disrupting agents did not acutely affect the integrity of preformed canalicular networks. In contrast, treatment with microfilament-perturbing agents caused a marked dilation of most canaliculi. These results illustrate the differential role of the cytoskeleton in the regeneration and maintenance of bile canalicular networks by collagen-sandwiched hepatocytes. Moreover, this study shows the utility of this system as an in vitro model for examining the regulation of cell and membrane polarity.

Actin Cytoskeleton↗
PubMed1996

Object Generation with Neural Networks (When Spurious Memories are Useful).

Object generation constitutes a new class of problems which can be solved using neural networks. It is reverse to classification and makes a good use of the stable network modes generally considered as undesired (spurious memories). Single-class networks are considered as basic elements instead of multiclass ones, and attractors of the former are treated as potential objects of the corresponding class. Development of multiple attractors reflects the network generalization abilities and converts the single-class network into the active generator of templates. Object generating networks can also be used as moduli of recognition systems which are free from some disadvantages inherent in multi-class discriminant networks. Copyright 1996 Elsevier Science Ltd.

Journal Article↗
PubMed1998

Hybrid interior point training of modular neural networks.

Modular neural networks use a single gating neuron to select the outputs of a collection of agent neurons. Expectation-maximization (EM) algorithms provide one way of training modular neural networks to approximate non-linear functionals. This paper introduces a hybrid interior-point (HIP) algorithm for training modular networks. The HIP algorithm combines an interior-point linear programming (LP) algorithm with a Newton-Raphson iteration in such a way that the computational efficiency of the interior point LP methods is preserved. The algorithm is formally proven to converge asymptotically to locally optimal networks with a total computational cost that scales in a polynomial manner with problem size. Simulation experiments show that the HIP algorithm produces networks whose average approximation error is better than that of EM-trained networks. These results also demonstrate that the computational cost of the HIP algorithm scales at a slower rate than the EM-procedure and that, for small-size networks, the total computational costs of both methods are comparable.

Journal Article↗
PubMed1996

Skeletal muscle determination and differentiation: story of a core regulatory network and its context.

Regulation of skeletal muscle determination and differentiation in vertebrates centers on a core regulatory network which is composed of two families of transcription factors, the MyoD group basic helix-loop-helix (bHLH) muscle regulatory factors (MRFs) and the myocyte enhancer factor 2 (MEF2) group of MADS-box regulators. Members of this network interact with each other genetically and physically, and together they cooperate to positively regulate transcription of downstream muscle-specific differentiation genes. During development, the myogenic network can be activated or repressed in response to patterning signals, some of which have recently been identified. Once activated, the powerful myogenic activity of the core network can be modulated and held in check by a remarkably large group of negative regulators that operate on network components by diverse mechanisms. Recent discoveries highlight extensive parallels between myogenesis and peripheral neurogenesis in the structures of their respective regulatory networks and in the interaction of their bHLH networks with other regulatory circuits. Comparisons with Drosophila indicate that these ensembles of interacting molecular circuits have been highly conserved during evolution.

Animals↗
PubMed2001

Functional brain networks in Parkinson's disease.

With the advent of new methods of network analysis, we have utilized metabolic data acquired through positron emission tomography (PET) to identify disease-related patterns of functional pathology in the movement disorders. In Parkinson's disease (PD), we have used [(18)F]-fluorodeoxyglucose (FDG)/PET to identify a disease-related regional metabolic covariance pattern characterized by lentiform and thalamic hypermetabolism associated with regional metabolic decrements in the lateral premotor cortex, the supplementary motor area, the dorsolateral prefrontal cortex, and the parieto-occipital association regions. The expression of this network is modulated in a predictable fashion by levodopa therapy and by stereotaxic interventions for PD.We have extended this network analytical approach from studies of glucose metabolism in the resting state to dynamic studies of brain activation during motor performance. These PET studies utilized [(15)O]-water (H(2) (15)O) to measure cerebral blood flow activation responses during the execution of simple and complex motor tasks. In addition to the modulation of abnormal resting metabolic networks, effective PD therapy can enhance brain activation responses during motor execution, with specific regional associations with improvements in timing and spatial accuracy.This approach is also useful in identifying specific brain networks mediating the learning of sequential information. We have found that the normal relationship between brain networks and learning performance are altered in the earliest stages of PD with a functional shift from striatal to cortical processing. Brain activation PET studies during therapeutic interventions for PD demonstrate how normal brain-behavior relationships can be restored with successful therapy. Thus, functional brain imaging with network analysis can provide insights into the mechanistic basis of basal ganglia disorders and their treatment.

Antiparkinson Agents↗
PubMed2006

The effect of social networks on the relation between Alzheimer's disease pathology and level of cognitive function in old people: a longitudinal cohort study.

BACKGROUND: Few data are available about how social networks reduce the risk of cognitive impairment in old age. We aimed to measure this effect using data from a large, longitudinal, epidemiological clinicopathological study. METHODS: 89 elderly people without known dementia participating in the Rush Memory and Aging Project underwent annual clinical evaluation. Brain autopsy was done at the time of death. Social network data were obtained by structured interview. Cognitive function tests were Z scored and averaged to yield a global and specific measure of cognitive function. Alzheimer's disease pathology was quantified as a global measure based on modified Bielschowsky silver stain. Amyloid load and the density of paired helical filament tau tangles were also quantified with antibody-specific immunostains. We used linear regression to examine the relation of disease pathology scores and social networks to level of cognitive function. FINDINGS: Cognitive function was inversely related to all measures of disease pathology, indicating lower function at more severe levels of pathology. Social network size modified the association between pathology and cognitive function (parameter estimate 0.097, SE 0.039, p=0.016, R(2)=0.295). Even at more severe levels of global disease pathology, cognitive function remained higher for participants with larger network sizes. A similar modifying association was observed with tangles (parameter estimate 0.011, SE 0.003, p=0.001, R(2)=0.454). These modifying effects were most pronounced for semantic memory and working memory. Amyloid load did not modify the relation between pathology and network size. The results were unchanged after controlling for cognitive, physical, and social activities, depressive symptoms, or number of chronic diseases. INTERPRETATION: These findings suggest that social networks modify the relation of some measures of Alzheimer's disease pathology to level of cognitive function.

Aged↗
PubMed2006

Assessment of the electrochemical behavior of two-dimensional networks of single-walled carbon nanotubes.

Scanning electrochemical microscopy (SECM) has been employed in the feedback mode to assess the electrochemical behavior of two-dimensional networks of single-walled carbon nanotubes (SWNTs). It is shown that, even though the network comprises both metallic and semiconducting SWNTs, at high density (well above the percolation threshold for metallic SWNTs) and with approximately millimolar concentrations of redox species the network behaves as a thin metallic film, irrespective of the formal potential of the redox couple. This result is particularly striking since the fractional surface coverage of SWNTs is only approximately 1% and SECM delivers high mass transport rates to the network. Finite element simulations demonstrate that under these conditions diffusional overlap between neighboring SWNTs is significant so that planar diffusion prevails in the gap between the SECM tip and the underlying SWNT substrate. The SECM feedback response diminishes at higher concentrations of the redox species. However, wet gate measurements show that at the solution potentials of interest the conductivity is sufficiently high that lateral conductivity is not expected to be limiting. This suggests that reaction kinetics may be a limiting factor, especially since the low surface coverage of the SWNT network results in large fluxes to the SWNTs, which are characterized by a low density of electronic states. For electroanalytical purposes, significantly, two-dimensional SWNT networks can be considered as metallic films for typical millimolar concentrations employed in amperometry and voltammetry. Moreover, SWNT networks can be inexpensively and easily formed over large scales, opening up the possibility of further electroanalytical applications.

Journal Article↗
PubMed2000

Artificial neural networks for the automated detection of trichloroethylene by passive Fourier transform infrared spectrometry

Artificial neural networks are applied to the automated classification of trichloroethylene (TCE) signatures from passive Fourier transform infrared remote sensing interferogram data. Through the use of three data collection methods, a combination of laboratory and field data is acquired that allows the methodology to be evaluated under a variety of infrared background conditions and in the presence of potentially interfering compounds such as sulfur hexafluoride, methyl ethyl ketone, acetone, carbon tetrachloride, and ammonia. To maximize the computational efficiency of the network optimization, experimental design techniques are employed to develop a training protocol for the network that takes into account the relationships among five variables that are related either to the network architecture or to the training process. This protocol is implemented for the case of a back-propagation neural network (BNN) and is used to develop an optimized network for the detection of TCE. The classification performance of the network is assessed by comparing both TCE detection capabilities and false detection rates to similar classification results obtained with the technique of piecewise linear discriminant analysis (PLDA). When applied to prediction data withheld from the optimization of both the BNN and PLDA algorithms, the BNN method is observed to outperform PLDA overall, with TCE detection rates in excess of 99% and false detection rates less than 0.5%.

Journal Article↗
PubMed2005

Size and shape selectivity of host networks built based on tunable secondary building units.

By modulating the secondary building units derived from the primary building units, N-acylsalicylhydrazides (H3 xshz), we have been able to construct isostructural but tunable host networks, [Mn6(xshz)6(dmf)2(bpea)2], with different cavity sizes and shapes where the secondary building units, [Mn6(xshz)6], were linked through exo-bidentate bridging ligand, 1,2-bis(pyridyl)ethane (bpea) to form 3-D networks. With a short length linear N-acyl side chain at the primary building unit, the host networks have a 3-D network with three-dimensional cavities. With an appropriate length linear N-acyl side chain at the primary building unit, the host network keeps the isostructural 3-D network but with two types of one-dimensional channels of reduced cavity volume. The tuned host networks showed not only size selectivity for the guest molecules but also shape selectivity. While the three-dimensional channeled host showed selectivity depending on the length of the podal guests, the one-dimensional channeled host showed selectivity depending on both the length and/or the podality of the guest molecules.

Journal Article↗
PubMed1999

Magic Electron Counts for Networks of Condensed Octahedral Niobium Clusters in Oxoniobates.

Chemical bonding in networks of octahedral oxoniobate clusters condensed through vertex-sharing is analyzed at the extended Hückel level of theory. Crystal or molecular orbitals of the condensed cluster networks are derived from the Nb-Nb bonding molecular orbitals of the monomeric Nb(6)O(18) cluster. Extended networks are treated by considering crystal orbitals at special points of the corresponding Brillouin zones. We find that cluster electron counts corresponding to optimal bonding in these networks decrease from 14 for the Nb(6)O(18) cluster to 12 per Nb octahedron for a dimer, 11 for a linear chain of clusters, 10-10(1)/(2) for a square network of clusters, and 7(3)/(4)-8(1)/(2) for cubic NbO in which all cluster vertices are shared. These results are in good agreement with both the counts derived from the experimentally observed structures and a previously devised counting scheme. The loss of Nb-Nb bonding at the shared cluster vertices and the Nb-O-Nb pi antibonding involving Nb atoms of neighboring octahedra are the reasons for the reduction of the magic cluster electron counts in the considered networks. It is proposed that similar counting schemes can be developed for other condensed cluster networks.

Journal Article↗
PubMed2006

Real-time observation of fiber network formation in molecular organogel: supersaturation-dependent microstructure and its related rheological property.

Low-molecular mass organic gelators self-organizing into three-dimensional fiber networks within organic solvents have attracted much attention in recent years. However, to date, how the microstructure of fiber network is formed in a gelation process and the key factors that govern the topological structure of a gel network remain to be determined. In this work, we address these issues by investigating the in situ formation of the gel networks in the N-lauroyl-l-glutamic acid di-n-butylamide (GP-1)/propylene glycol (PG) system. By using optical microscopy, the time evolution of the gel network microstructure was investigated under various supersaturation conditions. It is found that supersaturation is one of the key factors that govern the topological structure of a gel network. In particular, the creation of the junctions turns out to be supersaturation-dependent. The rheological experiments further revealed the correlation between topological structure and mechanical properties. It suggests that the rheological properties can be effectively modified by tuning the microstructure topology of the gel network. Our results reported here provide new physical insight into the formation kinetics of a molecular gel. Furthermore, this work could be important in constructing and engineering a supramolecular structure for the purpose of applications.

Gels↗
PubMed2006

Comparative study of morphometric properties characterizing the complexity of silicate pore networks probed by adsorption of nitrogen and methanol.

In this work, we compare the surface and morphometric properties of the pore networks in four silicas (code names Fr1428, Fr474, Fr1386, and MM1164) with different random porosities using the adsorption isotherms of two different probe adsorbents, nitrogen and methanol. The parent material Fr1428 was a pure silica 25 microm sample. The Fr474 sample was the same one with bonded electroneutral diol groups on its outer surface. Fr1386 was the parent material with bonded electroneutral diol groups on its outer surface and sulfonic groups on its inner surface, and the MM1164 sample was the original sample with external electroneutral diol groups and internal n-octadecyl groups. The properties examined were the specific surface area S(p) and the specific pore volume V(p), the pore connectivity c, the pore anisotropy b, the tortuosity tau, and the lacunarity lambda of the pore network as well as the percentage microporosity. These properties provide a complete characterization of complexity of the porous network. The surface areas of the solids were estimated via the traditional BET plots (S(BET)) and the I-point method (S(I)). The two sets of values S(BET) and S(I) were practically identical and they decrease as the size of the functional group increases. The values of percentage microporosity were also determined by the same I-point method using the variation of the C parameter of the BET equation. The total pore volume V(p) was found to be higher in the case of methanol adsorption, compared to nitrogen, which might be related to increase condensation. The networks of the pores were simulated using a dual site bond model (DSBM) and Monte Carlo (MC) techniques for achieving their proper arrangement into the solids. From the resulting simulating networks, the pore connectivity distributions (PCD) and their mean values c(mean) were estimated and favorably compared to the values of connectivity c(Seaton) determined according to the method of Seaton. Both values decrease with the size of the functional groups and are weakly affected by the adsorbent employed. From the simulation pore network, the mean values of tortuosity tau(mean) were also estimated and found to be lower when N2 was used as adsorbate compared to MeOH. The values of lacunarity lambda, estimated according to the method by Allain and Cloitre using the moving box technique in the DSBM/MC simulation matrix of the pore network, indicate that the distribution of the poreless mass into the matrix increases with the size of the functional group. Finally, the internal relationships observed between the pore anisotropy b and the percentage microporosity as well as between the tortuosity tau and the pore connectivity c are discussed.

Journal Article↗
PubMed2006

Direct reconstitution of plasma membrane lipids and proteins in nanotube-vesicle networks.

We demonstrate here that nanotube-vesicle networks can be constructed directly from plasma membranes of cultured cells. We used a combination of dithiothreitol (DTT) and formaldehyde to produce micron-sized plasma membrane vesicles that were subsequently shaped into networks using micromanipulation methods previously used on purely synthetic systems. Only a single cell is required to derive material sufficient to build a small network. This protocol covers the advantages of reconstitution in vesicles, such as full control over the solution environment, while keeping the proteins in their original surroundings with the proper orientation. Furthermore, control of membrane protein and lipid content in the networks is achievable by employing different cell types, for example, by overexpression of a desired protein or the use of specialized cell-types as sources for rare proteins and lipids. In general, the method provides simple accessibility for functional studies of plasma membrane constituents. Specifically, it provides a direct means to functionalize nanotube-vesicle networks with desired proteins and lipids for studies of transport activity both across membranes (protein-mediated) and across nanotubes (diffusion), and substrate conversion down to the single-molecule limit. Nanotube-vesicle networks can adopt different geometries and topologies and undergo shape changes at will, providing a flexible system for changing the physical and chemical environment around, for example, a membrane protein. Furthermore, the method offers unique possibilities for extracting membrane and protein material for nanotechnological sensor and analytical devices based on lipid membrane networks.

Animals↗
PubMed2002

Bayesian probabilistic network modeling of remifentanil and propofol interaction on wakeup time after closed-loop controlled anesthesia.

OBJECTIVE: Until now, the knowledge of combining anesthetics to obtain an adequate level of anesthesia and to economize wakeup time has been empirical and difficult to represent in quantitative models. Since there is no reason to expect that the effect of non-opioid and opioid anesthetics can be modeled in a simple linear manner, the use of a new computational approach with Bayesian belief network software is demonstrated. METHODS: A data set from a pharmacodynamic study was used where remifentanil was randomly given in three fixed target concentrations (2, 4, and 8 ng/ml) to 62 subjects. Target concentrations of propofol were controlled according to the closed-loop system feedback of the auditory evoked potential index to render modeling unbiased by the level of anesthesia. Time to open eyes was measured to represent wakeup time after surgery. The NETICA version 1.37 software was used on a personal computer for network building, validation, and prediction. RESULTS: After the learning phase, the network was used to generate a series of random cases whose probability distribution matches that of the compiled network. The sampling algorithms used are precise, so that the frequencies of the simulated cases will exactly approach the probabilities of the network and that of the data learned. The graphical display of the predicted wakeup time shows less variability but a more complex interaction pattern than with the unadjusted original data. CONCLUSIONS: Model building and evaluation with Bayesian networks does not depend on underlying linear relationships. Bayesian relationships represent true features of the represented data sample. Data may be sparse, uncertain, stochastic, or imprecise. Multiple platform software that is easy to use is increasingly available. Bayesian networks promise to be versatile tools for building valid, nonlinear, predictive instruments to further gain insight into the complex interaction of anesthetics.

Anesthesia Recovery Period↗
PubMed1991

"On-off" thermocontrol of solute transport. I. Temperature dependence of swelling of N-isopropylacrylamide networks modified with hydrophobic components in water.

The swelling in water, as a function of temperature, of two series of N-isopropylacrylamide (NIPAAm) polymer networks was studied. In the first series, n-butylmethacrylate (BMA) was copolymerized with NIPAAm, and in the second, polytetramethylene ether glycol (PTMEG) was incorporated into NIPAAm network as a chemically independent interpenetrating network. With increasing BMA content in the poly(NIPAAm-co-BMA) network, the gel collapse point was lowered and the gels deswelled in a more gradual manner with increasing temperature. In the interpenetrating polymer networks (IPN) system, the gel collapse point was not significantly changed by the amount of incorporated PTMEG. In DSC thermograms of swollen samples, the shape and onset temperature of the endothermic peak corresponded to the gel deswelling behavior and gel collapse point. The temperature dependence of equilibrium swelling in water was shown to be a function of the gel composition in both network series. The synthesized networks formed a dense surface layer as the temperature increased past the gel collapse point. This dense layer retarded water efflux and thereby resulted in water pockets at the membrane surface.

Acrylamides↗