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A quantitative model for designing keyboard layout.

This study analyzed the quantitative relationship between keytapping times and ergonomic principles in typewriting skills. Keytapping times and key-operating characteristics of a female subject typing on the Qwerty and Dvorak keyboards for six weeks each were collected and analyzed. The results showed that characteristics of the typed material and the movements of hands and fingers were significantly related to keytapping times. The most significant factors affecting keytapping times were association frequency between letters, consecutive use of the same hand or finger, and the finger used. A regression equation for relating keytapping times to ergonomic principles was fitted to the data. Finally, a protocol for design of computerized keyboard layout based on the regression equation was proposed.

Adult↗

Use of quantitative modelling in methylene chloride risk assessment.

The benefits of basing quantitative risk assessment on measures of 'internal dose', i.e. target organ exposures as estimated, for instance, by pharmacokinetic models, have been extensively discussed. Recasting risk assessment methods at the level of internal dose raises novel issues, however, some of which are explored by examining the 1987 revision by the US Environmental Protection Agency (EPA) of its cancer risk assessment for inhaled methylene chloride, which was based on the 1987 pharmacokinetic model results of Andersen and coworkers. The internal dose measure was the daily amount of methylene chloride metabolized by a glutathione-S-transferase pathway per 1 of target organ (liver and lung). Owing to high-dose saturation of a competing detoxification reaction, this metabolic activation is less-than-proportionally active at low exposure levels. For a given inhalation exposure, humans have relatively less metabolic activation than do mice, but this is shown to be a foreseeable consequence of their relatively lower breathing rate, a cross-species difference already accounted for in standard EPA methodology. Indeed, many species differences in the rates and tempos of physiological processes evince regular 'scaling' relationships across differently sized mammals. EPA's practice of scaling carcinogen doses by body surface area for cross-species extrapolation, often viewed as a correction for metabolic activation, is shown to be more reasonably regarded as an accommodation for the more general species variation in the pace of physiological processes underlying both pharmacokinetics and the carcinogenic response to internal doses. Under this view, the issue of cross-species dose scaling is not obviated by the use of pharmacokinetics.

Administration, Inhalation↗

A quantitative model of work-related fatigue: empirical evaluations.

Systematic and quantitative management of work-related fatigue within workplaces has been a challenging task due to a lack of useful tools. A previous paper provided background and development of a work-related fatigue modelling approach. The current paper outlines model evaluations using sleep deprivation experiments and recommendations of work scheduling. Previous studies have reported cumulative effects of sleep restriction (4-5 h per night) on a number of measures. Model predictions were correlated against psychomotor vigilance task lapses (r = 0.92) and reaction time responses (slowest 10%, r = 0.91) as well as sleep latency (r = -0.97). Further correlations were performed on four measures from a 64 h continuous sleep deprivation study; that is objective vigilance (r = -0.75) as well as subjective performance (r = -0.75), sleepiness (r = 0.82) and tiredness (r = 0.79). Evaluation against current scheduling recommendations illustrated consistency with the literature with the exception that forward rotation did not provide benefits over backward rotation. The results indicate that model predictions correlate well across a range of objective and subjective measures. This relationship also appears to hold for cumulative and continuous sleep deprivation protocols. Future studies will also focus on field-based evaluation.

Ergonomics↗

Striatal contributions to category learning: quantitative modeling of simple linear and complex nonlinear rule learning in patients with Parkinson's disease.

The contribution of the striatum to category learning was examined by having patients with Parkinson's disease (PD) and matched controls solve categorization problems in which the optimal rule was linear or nonlinear using the perceptual categorization task. Traditional accuracy-based analyses, as well as quantitative model-based analyses were performed. Unlike accuracy-based analyses, the model-based analyses allow one to quantify and separate the effects of categorization rule learning from variability in the trial-by-trial application of the participant's rule. When the categorization rule was linear, PD patients showed no accuracy, categorization rule learning, or rule application variability deficits. Categorization accuracy for the PD patients was associated with their performance on a test believed to be sensitive to frontal lobe functioning. In contrast, when the categorization rule was nonlinear, the PD patients showed accuracy, categorization rule learning, and rule application variability deficits. Furthermore, categorization accuracy was not associated with performance on the test of frontal lobe functioning. Implications for neuropsychological theories of categorization learning are discussed.

Aged↗

A quantitative model of the relationship between phenotypic variance and heterozygosity at marker loci under partial selfing.

Negative relationships between allozyme heterozygosity and morphological variance have often been observed and interpreted as evidence for increased developmental stability in heterozygotes. However, inbreeding can also generate such relationships by decreasing heterozygosity at neutral loci and redistributing genetic variance at the same time. I here provide a quantitative genetic model of this process by analogy with heterozygosity-fitness relationships. Inbreeding generates negative heterozygosity-variance relationships irrespective of the genetic architecture of the trait. This holds for fitness traits as well as neutral traits, the effect being stronger for fitness traits under directional dominance or overdominance. The order of magnitude of heterozygosity-variance regressions is compatible with empirical data even with very low inbreeding. Although developmental stability effects cannot be excluded, inbreeding is a parsimonious explanation that should be seriously considered to explain correlations between heterozygosity and both mean and variance of phenotypes in natural populations.

Animals↗

Towards a quantitative model of immunogenicity: counting pathways in sequence space.

One of the fundamental aims of structural biology is the identification of high-affinity ligands for arbitrary receptors. The maturation of the antibody repertoire elegantly and robustly solves this problem through an evolutionary mechanism comprising repeated cycles of mutation and preferential replication. To understand better the limitations and biases of this process, we developed an interpretation of antibody maturation within the framework of sequence space and fitness landscapes. Several well-described phenomena can be directly derived from this framework, and new predictions can be made. Ultimately, this reconceptualization of the clonal selection process suggests a quantitative, testable model of immunogenicity.

Antibodies↗

Flagellar biosynthesis in silico: building quantitative models of regulatory networks.

In this issue of Cell, describe the construction of an in silico model for the regulatory network responsible for the control of flagellar biosynthesis in E. coli based on quantitative gene expression data. They show how the model can be used as a quantitative blueprint to design genetic modifications with predictable influence on the dynamics of the system. The work by provides a general approach for building detailed models of transcriptional regulatory networks.

Computer Simulation↗

A quantitative model of odor deactivation based on the redox shift of the pheromone-binding protein im moth antennae.

Recent in vitro experiments with homogenates of isolated olfactory hairs of Antheraea polyphemus suggest that the pheromone-binding protein (PBP) is involved not only in pheromone solubilization and transport but also in pheromone deactivation. PBP occurs in a reduced form with one or two disulfide bridges (PBP(red)) and in the oxidized form with three bridges (PBP(ox)). From kinetic experiments it was concluded that the pheromone is first bound to PBP(red). This complex activates the receptor molecules and then turns into the oxidized form which--according to our working hypothesis--is unable to activate further receptor molecules. Apparently, the pheromone bound to the PBP (both forms) is protected from enzymatic degradation into nonexcitatory metabolites. A quantitative kinetic model of pheromone deactivation was developed (in collaboration with J. Thorson, Oxford) in which the receptor molecules are considered to act as enzymes catalyzing the redox shift of the binding protein.

Animals↗

Microdialysis of dopamine interpreted with quantitative model incorporating probe implantation trauma.

Although microdialysis is widely used to sample endogenous and exogenous substances in vivo, interpretation of the results obtained by this technique remains controversial. The goal of the present study was to examine recent criticism of microdialysis in the specific case of dopamine (DA) measurements in the brain extracellular microenvironment. The apparent steady-state basal extracellular concentration and extraction fraction of DA were determined in anesthetized rat striatum by the concentration difference (no-net-flux) microdialysis technique. A rate constant for extracellular clearance of DA calculated from the extraction fraction was smaller than the previously determined estimate by fast-scan cyclic voltammetry for cellular uptake of DA. Because the relatively small size of the voltammetric microsensor produces little tissue damage, the discrepancy between the uptake rate constants may be a consequence of trauma from microdialysis probe implantation. The trauma layer has previously been identified by histology and proposed to distort measurements of extracellular DA levels by the no-net-flux method. To address this issue, an existing quantitative mathematical model for microdialysis was modified to incorporate a traumatized tissue layer interposed between the probe and surrounding normal tissue. The tissue layers are hypothesized to differ in their rates of neurotransmitter release and uptake. A post-implantation traumatized layer with reduced uptake and no release can reconcile the discrepancy between DA uptake measured by microdialysis and voltammetry. The model predicts that this trauma layer would cause the DA extraction fraction obtained from microdialysis in vivo calibration techniques, such as no-net-flux, to differ from the DA relative recovery and lead to an underestimation of the DA extracellular concentration in the surrounding normal tissue.

Animals↗

Inferring quantitative models of regulatory networks from expression data.

MOTIVATION: Genetic networks regulate key processes in living cells. Various methods have been suggested to reconstruct network architecture from gene expression data. However, most approaches are based on qualitative models that provide only rough approximations of the underlying events, and lack the quantitative aspects that are critical for understanding the proper function of biomolecular systems. RESULTS: We present fine-grained dynamical models of gene transcription and develop methods for reconstructing them from gene expression data within the framework of a generative probabilistic model. Unlike previous works, we employ quantitative transcription rates, and simultaneously estimate both the kinetic parameters that govern these rates, and the activity levels of unobserved regulators that control them. We apply our approach to expression datasets from yeast and show that we can learn the unknown regulator activity profiles, as well as the binding affinity parameters. We also introduce a novel structure learning algorithm, and demonstrate its power to accurately reconstruct the regulatory network from those datasets.

Binding Sites↗

Stoichiometric flux balance models quantitatively predict growth and metabolic by-product secretion in wild-type Escherichia coli W3110.

Flux balance models of metabolism use stoichiometry of metabolic pathways, metabolic demands of growth, and optimality principles to predict metabolic flux distribution and cellular growth under specified environmental conditions. These models have provided a mechanistic interpretation of systemic metabolic physiology, and they are also useful as a quantitative tool for metabolic pathway design. Quantitative predictions of cell growth and metabolic by-product secretion that are experimentally testable can be obtained from these models. In the present report, we used independent measurements to determine the model parameters for the wild-type Escherichia coli strain W3110. We experimentally determined the maximum oxygen utilization rate (15 mmol of O2 per g [dry weight] per h), the maximum aerobic glucose utilization rate (10.5 mmol of Glc per g [dry weight] per h), the maximum anaerobic glucose utilization rate (18.5 mmol of Glc per g [dry weight] per h), the non-growth-associated maintenance requirements (7.6 mmol of ATP per g [dry weight] per h), and the growth-associated maintenance requirements (13 mmol of ATP per g of biomass). The flux balance model specified by these parameters was found to quantitatively predict glucose and oxygen uptake rates as well as acetate secretion rates observed in chemostat experiments. We have formulated a predictive algorithm in order to apply the flux balance model to describe unsteady-state growth and by-product secretion in aerobic batch, fed-batch, and anaerobic batch cultures. In aerobic experiments we observed acetate secretion, accumulation in the culture medium, and reutilization from the culture medium. In fed-batch cultures acetate is cometabolized with glucose during the later part of the culture period.(ABSTRACT TRUNCATED AT 250 WORDS)

Acetates↗

A quantitative model for allosteric control of purine reduction by murine ribonucleotide reductase.

The reduction of purine nucleoside diphosphates by murine ribonucleotide reductase requires catalytic (R1) and free radical-containing (R2) enzyme subunits and deoxynucleoside triphosphate allosteric effectors. A quantitative 16 species model is presented, in which all pertinent equilibrium constants are evaluated, that accounts for the effects of the purine substrates ADP and GDP, the deoxynucleoside triphosphate allosteric effectors dGTP and dTTP, and the dimeric murine R2 subunit on both the quaternary structure of murine R1 subunit and the dependence of holoenzyme (R1(2)R2(2)) activity on substrate and effector concentrations. R1, monomeric in the absence of ligands, dimerizes in the presence of substrate, effectors, or R2(2) because each of these ligands binds R1(2) with higher affinity than R1 monomer. This leads to apparent positive heterotropic cooperativity between substrate and allosteric effector binding that is not observed when binding to the dimeric protein itself is evaluated. Allosteric activation results from an increase in k(cat) for substrate reduction upon binding of the correct effector, rather than from heterotropic cooperativity between effector and substrate. Neither the allosteric site nor the active site displays nucleotide base specificity: dissociation constants for dGTP and dTTP are nearly equivalent and K(m) and k(cat) values for both ADP and GDP are similar. R2(2) binding to R1(2) shows negative heterotropic cooperativity vis-à-vis effectors but positive heterotropic cooperativity vis-à-vis substrates. Binding of allosteric effectors to the holoenzyme shows homotropic cooperativity, suggestive of a conformational change induced by activator binding. This is consistent with kinetic results indicating full dimer activation upon binding a single equivalent of effector per R1(2)R2(2).

Allosteric Regulation↗

A quantitative model of work-related fatigue: background and definition.

Fatigue has been identified as a major risk factor for shiftworkers. However, few organizations or governments currently manage work-related fatigue in any systematic or quantitative manner. This paper outlines an approach to managing fatigue that could improve shiftwork management. Using shift start and finish times as an input, the outlined model quantifies work-related fatigue on the basis of its known determinants; that is shift timing and duration, work history and the biological limits on sleep length at specific times of day. Evaluations suggest that work-related fatigue scores correlate very highly with sleep-onset latency, neurobehavioural impairment and subjective sleepiness. The model is useful in that it allows comparisons to be made between rosters independent of shift length and timing or the total number of work hours. Furthermore, unlike many models of sleepiness and fatigue, individual's sleep times are not required as hours of work are used as the input. It is believed the model provides the potential quantitatively to link the effects of shiftwork to specific organizational health and safety outcomes. This simple approach may be especially critical at a time when many organizations view longer and more flexible hours from their employees as an immediate productivity gain.

Fatigue↗

Phase-field formulation for quantitative modeling of alloy solidification.

A phase-field formulation is introduced to simulate quantitatively microstructural pattern formation in alloys. The thin-interface limit of this formulation yields a much less stringent restriction on the choice of interface thickness than previous formulations and permits one to eliminate nonequilibrium effects at the interface. Dendrite growth simulations with vanishing solid diffusivity show that both the interface evolution and the solute profile in the solid are accurately modeled by this approach.

Journal Article↗

[Early matrix and cellular modifications in a hypertension model induced in rats (Goldblatt model). Quantitative and morphometric study].

In the two-kidney one-clip hypertensive Goldblatt model of nephrosclerosis, the aim of this study was to detect, during the first twenty-eight days of high blood pressure, interstitial and periarterial (interlobular arterial and arteriolar) kidney changes. Morphometric analysis for type I collagen, in situ hybridization for type I and IV collagen mRNAs and immunohistochemistry for inflammatory cells were used to quantify and localize the following lesions: 1) A very early increase of collagen I proteins and mRNAs soon as the first 3 days and an important influx of inflammatory cells (macrophages and T-helper lymphocytes) were observed concomitantly. Then, these phenomenons decrease until the end of the experiment. 2) The interstitium reacts in the same way but with a lower intensity and with a time shifting. The main interstitial changes were seen after the second week of hypertension. 3) A same periarterial collagen I increase was measured during the first 3 days of hypertension in both clipped kidney and unclipped kidney. This hypertension-independent manifestation in the clipped kidney does not increase in later times of hypertension as it does in the unclipped kidney. A possible explanation is given by the angiotensin II concentration higher in the clipped kidney than in the unclipped kidney, and by direct angiotensin II effects as growth factor. 4) Periarterial fibrosis and macrophages or T-helper lymphocytes infiltration were co-localized. The intensity of both phenomenons is well correlated. These facts suggest that inflammatory cell infiltration and interstitial fibrosis are strongly and early linked.

Animals↗

Testing quantitative models of binocular disparity selectivity in primary visual cortex.

Disparity-selective neurons in striate cortex (V1) probably implement the initial processing that supports binocular vision. Recently, much progress has been made in understanding the computations that these neurons perform on retinal inputs. The binocular energy model has been highly successful in providing a simple theory of these computations. A key feature of the energy model is that it is linear until after inputs from the two eyes are combined. Recently, however, a modified version of the energy model, incorporating threshold nonlinearities before binocular combination, has been proposed to account for the weaker disparity tuning observed with anticorrelated stimuli. In this study, we present new data needed for a critical assessment of these two models. We compare two key predictions of the models with responses of disparity-selective neurons recorded from V1 of awake fixating monkeys. We find that the original energy model, and a family of generalizations retaining linear binocular combination, are quantitatively inconsistent with the response of V1 neurons. In contrast, the modified version incorporating threshold nonlinearities can explain both sets of observations. We conclude that the energy model can be reconciled with experimental observations by adding a threshold before binocular combination. This gives us the clearest picture yet of the computation being carried out by disparity-selective V1 neurons.

Action Potentials↗

Photochemically-induced lesion of the rat retina: a quantitative model for the evaluation of ischemia-induced retinal damage.

The effects of ischemia-induced retinal damage were quantitatively evaluated in rats with the aim of obtaining a suitable model to study the pathogenesis of the loss of retinal neurons after ischemic episodes. Anaesthetized rats were injected with 80 mg/kg i.v. of the fluorescein rose bengal dye and one eye was exposed to cold light for different periods (from 5 to 30 min). The animals were sacrificed at different times (1 and 4 hr; 2 and 7 days) after the lesion and the photochemically-induced damage was evaluated. The damaged retinae appeared thicker, numerous neurons of the inner nuclear layers showed swelling of the perinuclear cytoplasm and the retinal vessels were enlarged. The activity of choline acetyltransferase (ChAT) and glutamic acid decarboxylase (GAD), two marker enzymes of the GABAergic and cholinergic neurons, significantly decreased, indicating a degeneration of GABAergic and cholinergic amacrine cells.

Animals↗

A quantitative model of the Escherichia coli 16 S RNA in the 30 S ribosomal subunit.

We use a computer-based protocol for automated structure refinement of large RNAs and ribonucleoproteins to propose a three-dimensional model for the Escherichia coli 16 S RNA in the 30 S ribosomal subunit along with the first quantitative estimates of the uncertainties in the model. Our models are based on the 16 S RNA secondary structure, the small angle neutron scatter map of 30 S proteins, tertiary RNA-RNA and RNA-protein contacts as suggested by cross-linking, chemical footprinting and other experimental studies, and electron microscopy data for the shape of the 30 S subunit and placement of 16 S RNA fragments, along with known motifs in RNA structure. In addition, some data on the interaction of the tRNAs/mRNA with the 16 S RNA were used to localize the active site. Since there are not enough structural data to derive a unique three-dimensional folding of the 16 S RNA, several different conformations can be generated to satisfy the experimental data. A set of seven models was refined to survey the range of acceptable conformations. These models were analyzed to deduce probable positions and orientations of the different helical segments that comprise the 16 S RNA in the Escherichia coli small subunit, and one consensus model from this set is presented here. An estimate of the reliability of our predicted structure is made using the variations between the models, and about 75% of 16 S RNA helical segments are localized to 15 A or less in their position in the small subunit. Our models show a distinct separation of the three major domains of the 16 S RNA. The 5' major domain and the central domain are clustered in the body of the 30 S subunit, whereas the 3' major domain is localized in the head of the subunit. Our modeling results are compared with models of the 16 S RNA proposed by other researchers, and are seen to be similar to the manually built models by Stern et al. and Brimacombe et al. with a few significant differences. The position of nucleotides implicated by footprinting and crosslinking data in tRNA and mRNA binding, and in subunit association are examined, and many of these sites are seen to lie along the 30 S subunit neck, cleft and the platform.

Base Sequence↗