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Results for “nonlinear analyses”

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PubMed2005

Assessment of exposure to wheat flour and the shape of its relationship with specific sensitization.

OBJECTIVES: Dust and wheat-allergen exposure were assessed among bakers, flour millers, and bakery-ingredient producers, and the risk for sensitization was studied. METHODS: About 520 inhalable dust and wheat-allergen measurements were made among 270 Dutch workers. Data on sensitization to wheat and common allergens (atopy) were also available. Exposure was estimated according to the sector of industry, job title, and tasks. The shape of the relationship between sensitization and exposure was studied using a two-stage modeling approach: semi-parametric generalized additive modeling and, consequently, a simple description of the relationship using a parametric logistic model. To reduce the effect of exposure measurement errors (attenuation), a combination of the actual measured exposure and variance-weighted estimates of exposure was used. Results The effect of exposure to both inhalable dust and wheat allergens on sensitization was described best by a linear relationship in three industries and a quadratic relationship in one industry. The relation for the whole study population was best described as quadratic, and the probability of sensitization increased with exposure up to -2.7 mg/m3 for inhalable dust and approximately 25.7 microg EQ/m3 for wheat allergens. The risk decreased at higher exposures (P = 0.0121 and P = 0.0731 for dust and wheat, respectively). Atopy and sector of industry modified the sensitization risk significantly in all the analyses. Using a variant-weighted estimator to calculate exposures corrected for the bias and resulted in almost the same point risk estimators. Conclusions Exposure-response relationships for allergens may be nonlinear and differ between industries. A threshold is not indicated on which to base occupational exposure standards; alternatively, other approaches, such as benchmarking, seem warranted.

Allergens↗

PubMed1980

Estimation and comparison of parameters in stochastic growth models for barn owls.

Alternative methods for parameter estimation and the incorporation of stochasticity into growth models are investigated and compared to the commonly used sampling error model in which error terms are simply added-on to the integrated form of the growth equation. A process error model, in which the process of growth is assumed to have stochastic variation or error incorporated within it, was found to be more appropriate for use with nonlinear estimation procedures based on a minimization of sigma ei2. The process error model tended to minimize and/or eliminate the autocorrelation of residuals, which were characteristic of the sampling error model. These analyses further suggest that while the commonly used sampling error growth model may indeed provide unbiased parameter estimates, the estimated variances of such estimates are likely to be unwarrantedly low, thus raising questions as to the validity of any statistical comparisons based on such analyses. The procedure is illustrated with growth data from captive-reared sibling nestling barn owls, using the Richards' growth curve. These analyses suggest that both growth rate and growth form are subject to a higher degree of genetic control than is asymptotic weight which showed a greater tendency to vary according to the hatching order of the nestlings.

Age Factors↗

PubMedDate not supplied

MZ twinning: chance or determinism? An essay in nonlinear dynamics (chaos).

Classically, researchers considered monozygotic twinning (MZT) a random phenomenon. This paper tests the hypothesis with the aid of nonlinear dynamics techniques. The latter can tell true randomness from chance-like variation. Chaos, the endpoint of the threshold state of a nonlinear deterministic system, can mimic constrained randomness. From a practical standpoint, recognizing chaos in a time series data set means that the paradigmatic multifactorial model of causation is essentially ruled out. Specifically, time series of MZ, DZ, and single maternities were analysed. First, spectral analysis was used to uncover periodicities embedded in the series. Second, a singular value decomposition was undertaken to reduce noise from the series. Third, phase space attractors were drawn up that describe the 'asymptotic' trajectory of the system at any time. Results suggested that DZ, MZ, and single maternities shared a similar 32-year periodicity. Owing to two interwoven similar periodicities, the single-maternity cycle kinetics proved to be faster than that of DZ's. The MZ series was the only one to display secondary interacting harmonics, thus eliciting a rather unusual trajectory in the bidimensional phase space. The MZ time points were not spread in a haphazard fashion; on the contrary, a fine structure was present that did not reduce to a limit cycle such as the one characterizing the DZ- or the single-maternity trajectory. It was concluded that a complex nonlinear dynamic underlies MZ twinning. Therefore, calling for extrinsic causes to account for what appears to be random variation overtime would be pointless. MZ twinning should rather be traced to a limited number of intrinsic and deterministic interacting system components. The most likely candidates are presented and discussed.

Bias↗

PubMed1999

A weak pulsed magnetic field affects adenine nucleotide oscillations, and related parameters in aggregating Dictyostelium discoideum amoebae.

A model eukaryotic cell system was used to explore the effect of a weak pulsed magnetic field (PMF) on time-varying physiological parameters. Dictyostelium discoideum cells (V12 strain) were exposed to a pulsed magnetic field (PMF) of flux density 0.4 mT, generated via air-cored coils in trains of 2 ms pulses gated at 20 ms. This signal is similar to those used to treat non-uniting fractures. Samples were taken over periods of 20 min from harvested suspensions of amoebae during early aggregation phase, extracted and derivatised for HPLC fluorescent assay of adenine nucleotides. Analysis of variance showed a significant athermal damping effect (P < 0.002, n = 22) of the PMF on natural adenine nucleotide oscillations and some consistent changes in phase relationships. The technique of nonlinear dielectric spectroscopy (NLDS) revealed a distinctive effect of PMF, caffeine and EGTA in modulating the cellular harmonic response to an applied weak signal. Light scattering studies also showed altered frequency response of cells to PMF, EGTA and caffeine. PMF caused a significant reduction of caffeine induced cell contraction (P < 0.0006, n = 19 by paired t-test) as shown by Malvern particle size analyser, suggesting that intracellular calcium may be involved in mediating the effect of the PMF.

Adenine Nucleotides↗

PubMed2006

Dynamic modeling and torque estimation of FES-assisted arm-free standing for paraplegics.

This paper presents an application of recent findings in the field of redundant robotic systems' control, toward investigating the feasibility of functional electrical stimulation (FES) assisted arm-free standing for paraplegics. Twelve degrees-of-freedom (DOF) forward and inverse dynamic models of quiet standing have been developed. These models were used to investigate the minimum number of DOF that would need to be actuated in order to generate stable quiet standing in paraplegics despite internal and external disturbances. The results presented herein suggest that the proposed nonlinear dynamic model could achieve guaranteed asymptotic stability with only six active DOF, assuming that the remaining six DOF are passive, i.e., there is no active or passive torques applied to those DOF. The stability analyses were performed using a proportional and derivative (PD) controller coupled with gravity compensation. The results of this analysis suggest that if only six particular DOF are actively controlled in a paraplegic subject, this individual should be able to achieve stable quiet standing despite disturbances. This result has both clinical and system-design implications for the development of a device that will facilitate FES-assisted arm-free quiet standing. The clinical implication is, if a paraplegic patient can exert voluntary control over specified six DOF in the lower limbs, that patient, after intensive physiotherapy, will have the potential to perform quiet standing unassisted. The system-design implication is that FES-assisted arm-free standing for paraplegics is theoretically plausible if one would actively control only six out of 12 DOF in the lower limbs. The proposed solution does not require the locking of joints in the lower limbs (commonly applied in the field) or voluntary control of the upper body to compensate for the internal and external disturbances. Another important finding of this study is the existence of six different combinations of six active DOF able to facilitate stable quiet standing. This dynamic redundancy of the biological bipedal stance allows the selection of an ideal subset of six DOF in designing a neuroprosthesis for standing. This further implies that a considerably less complex FES system than previously anticipated needs to be developed for FES-assisted standing.

Algorithms↗

PubMed2025

S-GMAS: Genome-Wide Mediation Analysis With Brain Subcortical Shape Mediators.

Mediation analysis is widely utilized in neuroscience to investigate the role of brain image phenotypes in the neurological pathways from genetic exposures to clinical outcomes. However, it is still difficult to conduct mediation analyses with whole genome-wide exposures and brain subcortical shape mediators due to several challenges including (i) large-scale genetic exposures, that is, millions of single-nucleotide polymorphisms (SNPs); (ii) nonlinear Hilbert space for shape mediators; and (iii) statistical inference on the direct and indirect effects. To tackle these challenges, this paper proposes a genome-wide mediation analysis framework with brain subcortical shape mediators. First, to address the issue caused by the high dimensionality in genetic exposures, a fast genome-wide association analysis is conducted to discover potential genetic variants with significant genetic effects on the clinical outcome. Second, the square-root velocity function representations are extracted from the brain subcortical shapes, which fall in an unconstrained linear Hilbert subspace. Third, to identify the underlying causal pathways from the detected SNPs to the clinical outcome implicitly through the shape mediators, we utilize a shape mediation analysis framework consisting of a shape-on-scalar model and a scalar-on-shape model. Furthermore, the bootstrap resampling approach is adopted to investigate both global and spatial significant mediation effects. Finally, our framework is applied to the corpus callosum shape data from the Alzheimer's Disease Neuroimaging Initiative.

Humans↗

PubMed1998

The indirect verification of minimal two-generator model of homeostatic drinking by complexity examination.

In the course of previous examinations, it has been suggested that minimally two lick pattern generators have to take part in the formation of temporal patterns of homeostatic drinking. The drinking pattern of five rats was investigated, subsequently analysed and compared to simulated data. As the interaction of the two generators changes by the progress of satiation, the dynamics of drinking have to change too. In this experiment we demonstrated this nonlinear dynamical change by the examination of algorithmic complexity which reflects the nature of motivational changes and that the proportion of the change of complexity is in harmony with our model of homeostatic drinking.

Animals↗

PubMed2000

Arterial baroreflex influence on heart rate variability: a mathematical model-based analysis.

The influence of the arterial baroreflex on the heart rate variability is analysed by using a mathematical model of heart rate baroreceptor control. The basic mechanisms of the model, sufficient to elicit heart rate variability include: systemic circulation, a non-pulsatile cardiac pump and nonlinear negative feedback simulating arterial baroreflex closed-loop control of the heart rate (-3 bpm/mmHg as maximum reflex sensitivity). The latter reproduces, through two distinct delayed branches (0.8 and 2.8 s), the short-term autonomic control effected respectively by sympathetic and parasympathetic divisions on the sinus node. By means of this model, two distinct self-sustained oscillatory components with incommensurate frequencies (0.1 and 0.26 Hz) are reproduced. Frequencies of these two oscillatory components closely agree with the main heart rate rhythms in humans (0.09 +/- 0.01 Hz and 0.26 +/- 0.01 Hz). When sympathetic-mediated regulation prevails over parasympathetic activity, simulated heart rate oscillation is characterised by a low frequency (approximately 0.1 Hz). On the other hand, a high-frequency oscillatory component (approximately 0.26 Hz) appears when enhanced vagal activation or partial inhibition of the sympathetic control is simulated. When both autonomic divisions are operative, both low- and high-frequency components are present and the heart rate oscillates quasi-periodically. This variability in heart rate at different frequencies is reproduced without including outside perturbations and is due to the nonlinear delayed structure of the closed-loop control. Bifurcation theory of nonlinear system is used to explain the high sensitivity of the heart rate oscillatory pattern to model parameter changes.

Baroreflex↗

PubMed2005

Directed molecular evolution by machine learning and the influence of nonlinear interactions.

Alternative search strategies for the directed evolution of proteins are presented and compared with each other. In particular, two different machine learning strategies based on partial least-squares regression are developed: the first contains only linear terms that represent a given residue's independent contribution to fitness, the second contains additional nonlinear terms to account for potential epistatic coupling between residues. The nonlinear modeling strategy is further divided into two types, one that contains all possible nonlinear terms and another that makes use of a genetic algorithm to select a subset of important interaction terms. The performance of each modeling type as a function of training set size is analysed. Simulated molecular evolution on a synthetic protein landscape shows the use of machine learning techniques to guide library design can be a powerful addition to library generation methods such as DNA shuffling.

Algorithms↗

PubMed2001

Development of inferential measurements using neural networks.

In many industrial processes, the most desirable variables to control are measured infrequently off-line in a quality control laboratory. In these situations, use of advanced control or optimization techniques requires use of inferred measurements generated from correlations. For well-understood processes, the structure of the correlation as well as the choice of inputs may be known a priori. However, many industrial processes are too complex and the appropriate form of the correlation and choice of input measurements are not obvious. Here, process knowledge, operating experience, and statistical methods play an important role in development of correlations. This paper describes a systematic approach to the development of nonlinear correlations for inferential measurements using neural networks. A three-step procedure is proposed. The first step consists of data collection and preprocessing. Next, the process variables are subjected to simple statistical analyses to identify a subset of measurements to be used in the inferential scheme. The third step involves generation of the inferential scheme. We demonstrate the methodology by inferring the ASTM 95% endpoint of a petroleum product using data from a domestic US refinery.

Algorithms↗

PubMed2001

A treadmill ergometer for three-dimensional ground reaction forces measurement during walking.

This report describes new treadmill ergometer designed to measure the vertical and horizontal ground reaction forces produced by the left and right legs during walking. It was validated by static and dynamic tests. Non-linearity was from 0.2% (left vertical force) to 1.4% (right antero-posterior force). The resonance frequency was from 219 (right vertical direction) to 58 Hz (left medio-lateral direction). A calibration "leg", an air jack in series with a strain gauge, was developed and used to produce force signals comparable to those obtained during human locomotion. The mean differences between the force measured by the calibration leg and treadmill ergometer at 5 km h(-1) were 3.7 N (0.7%) for the left side and 6.5 N (1.2%) for the right. Measurements obtained during human walking showed that the treadmill ergometer has considerable potential for analysing human gait.

Calibration↗

PubMed1995

Glycosylated hemoglobin and the risk of microalbuminuria in patients with insulin-dependent diabetes mellitus.

BACKGROUND: The risk of microalbuminuria in patients with insulin-dependent diabetes mellitus (IDDM) is thought to depend on the degree of hyperglycemia, but the relation between the degree of hyperglycemia and urinary albumin excretion has not been defined. METHODS: We measured urinary albumin excretion in three random urine samples obtained at least one month apart from 1613 patients with IDDM. Microalbuminuria or overt albuminuria was considered to be present if the ratio of albumin (in micrograms) to creatinine (in milligrams) was 17 to 299 or > or = 300, respectively, for men and 25 to 299 or > or = 300, respectively, for women. Measurements of glycosylated hemoglobin (hemoglobin A1) obtained up to four years before the urine testing were used as an index of hyperglycemia. Twelve percent of the patients had overt albuminuria and were excluded from subsequent analyses. RESULTS: The prevalence of microalbuminuria was 18 percent in patients with IDDM. It increased with increasing postpubertal duration of diabetes and, within each six-year interval of disease duration, it increased nonlinearly with the hemoglobin A1 value. For hemoglobin A1 values below 10.1 percent, the slope of the relation was almost flat, whereas for values above 10.1 percent, the prevalence of microalbuminuria rose steeply (P < 0.001). For example, as the hemoglobin A1 value increased from 8.1 to 10.1 percent, the odds of microalbuminuria increased by a factor of 1.3, but as the value increased from 10.1 to 12.1 percent, the odds were increased by a factor of 2.4. CONCLUSIONS: The risk of microalbuminuria in patients with IDDM increases abruptly above a hemoglobin A1 value of 10.1 percent (equivalent to a hemoglobin A1c value of 8.1 percent), suggesting that efforts to reduce the frequency of diabetic nephropathy should be focused on reducing hemoglobin A1 values that are above this threshold.

Adolescent↗

PubMed2006

Quantitative trait associated microarray gene expression data analysis.

Selection on phenotypes may cause genetic change. To understand the relationship between phenotype and gene expression from an evolutionary viewpoint, it is important to study the concordance between gene expression and profiles of phenotypes. In this study, we use a novel method of clustering to identify genes whose expression profiles are related to a quantitative phenotype. Cluster analysis of gene expression data aims at classifying genes into several different groups based on the similarity of their expression profiles across multiple conditions. The hope is that genes that are classified into the same clusters may share underlying regulatory elements or may be a part of the same metabolic pathways. Current methods for examining the association between phenotype and gene expression are limited to linear association measured by the correlation between individual gene expression values and phenotype. Genes may be associated with the phenotype in a nonlinear fashion. In addition, groups of genes that share a particular pattern in their relationship to phenotype may be of evolutionary interest. In this study, we develop a method to group genes based on orthogonal polynomials under a multivariate Gaussian mixture model. The effect of each expressed gene on the phenotype is partitioned into a cluster mean and a random deviation from the mean. Genes can also be clustered based on a time series. Parameters are estimated using the expectation-maximization algorithm and implemented in SAS. The method is verified with simulated data and demonstrated with experimental data from 2 studies, one clusters with respect to severity of disease in Alzheimer's patients and another clusters data for a rat fracture healing study over time. We find significant evidence of nonlinear associations in both studies and successfully describe these patterns with our method. We give detailed instructions and provide a working program that allows others to directly implement this method in their own analyses.

Animals↗

PubMed2000

Improvements to the sensitivity of gravitational clustering for multiple neuron recordings.

We outline two improvements to the technique of gravitational clustering for detection of neuronal synchrony, which are capable of improving the method's detection of weak synchrony with limited data. The advantages of the enhancements are illustrated using data with known levels of synchrony and different interspike interval distributions. The novel simulation method described can easily generate such test data. An important dependence of the sensitivity of gravitational clustering to the interspike interval distribution of the analysed spike trains is described.

Action Potentials↗

PubMed2002

The concurrent accumulation of intra-abdominal and subcutaneous fat explains the association between insulin resistance and plasma leptin concentrations : distinct metabolic effects of two fat compartments.

Obesity is associated with insulin resistance, particularly when body fat has a central distribution. However, insulin resistance also frequently occurs in apparently lean individuals. It has been proposed that these lean insulin-resistant individuals have greater amounts of body fat than lean insulin-sensitive subjects. Alternatively, their body fat distribution may be different. Obesity is associated with elevated plasma leptin levels, but some studies have suggested that insulin sensitivity is an additional determinant of circulating leptin concentrations. To examine how body fat distribution contributes to insulin sensitivity and how these variables are related to leptin levels, we studied 174 individuals (73 men, 101 women), a priori classified as lean insulin-sensitive (LIS, n = 56), lean insulin-resistant (LIR, n = 61), and obese insulin-resistant (OIR, n = 57) based on their BMI and insulin sensitivity index (S(I)). Whereas the BMI of the two lean groups did not differ, the S(I) of the LIR subjects was less than half that of the LIS group. The subcutaneous and intra-abdominal fat areas, determined by computed tomography, were 45 and 70% greater in the LIR subjects (P < 0.001) and 2.5- and 3-fold greater in the OIR group, as compared with the LIS group. Fasting plasma leptin levels were moderately increased in LIR subjects (10.8 +/- 7.1 vs. 8.1 +/- 6.4 ng/ml in LIS subjects; P < 0.001) and doubled in OIR subjects (21.9 +/- 15.5 ng/ml; P < 0.001). Because of the confounding effect of body fat, we examined the relationships between adiposity, insulin sensitivity, and leptin concentrations by multiple regression analysis. Intra-abdominal fat was the best variable predicting insulin sensitivity in both genders and explained 54% of the variance in S(I). This inverse relationship was nonlinear (r = -0.688). On the other hand, in both genders, fasting leptin levels were strongly associated with subcutaneous fat area (r = 0.760) but not with intra-abdominal fat. In line with these analyses, when LIS and LIR subjects were matched for subcutaneous fat area, age, and gender, they had similar leptin levels, whereas their intra-abdominal fat and insulin sensitivity remained different. Thus, accumulation of intra-abdominal fat correlates with insulin resistance, whereas subcutaneous fat deposition correlates with circulating leptin levels. We conclude that the concurrent increase in these two metabolically distinct fat compartments is a major explanation for the association between insulin resistance and elevated circulating leptin concentrations in lean and obese subjects.

Abdomen↗

PubMed1984

Experience with NONMEM: analysis of routine phenytoin clinical pharmacokinetic data.

NONMEM, a program package the produces the extended least squares estimates of population parameters for a nonlinear mixed-effect model, has been applied to two data sets from patients routinely receiving phenytoin. A general model for the data is proposed. The models used in previous, standard-method analyses of each data set are compared to the general model using NONMEM. The comparison involves two questions: The first asks whether the parameters estimated previously agree with NONMEM estimates when the original model is used. We find that for fixed-effect parameters they generally do, while for interindividual random-effect parameters the previous methods' estimates appear upward biased relative to NONMEM. Second, the original model per se is compared to the general model by comparing the best fit to each. The general model is clearly superior. NONMEM's ability to distinguish among models, and to precisely estimate their parameters from sparse individual data, is illustrated and verified.

Computers↗

PubMed1997

Metabolism of the HIV-1 reverse transcriptase inhibitor delavirdine in mice.

Delavirdine mesylate (U-90152T) is a highly specific nonnucleoside HIV-1 reverse transcriptase inhibitor currently under development for the treatment of AIDS. The excretion, disposition, brain penetration, and metabolism of delavirdine were investigated in CD-1 mice after oral administration of [14C]delavirdine mesylate at single doses of 10 and/or 250 mg/kg and multiple doses of 200 mg/kg/day. Studies were conducted with 14C-carboxamide and 2-14C-pyridine labels, as well as 13C3-labeled drug to facilitate metabolite identification. Excretion was dose dependent with 57-70% of the radioactivity eliminated in feces and 25-36% in urine. Pharmacokinetic analyses of delavirdine and its N-desisopropyl metabolite (desalkyl delavirdine) in plasma showed that delavirdine was absorbed and metabolized rapidly, that it constituted a minor component in circulation, that its pharmacokinetics were nonlinear, and that its metabolism to desalkyl delavirdine was capacity limited or inhibitable. Delavirdine did not significantly cross the blood-brain barrier; however, its N-isopropylpyridinepiperazine metabolite arising from amide bond cleavage-was present in brain at levels 2- to 3-fold higher than in plasma. The metabolism of delavirdine in the mouse was extensive and involved amide bond cleavage, N-desalkylation, hydroxylation at the C-6' position of the pyridine ring, and pyridine ring-cleavage as determined by MS and/or 1H and 13C NMR spectroscopies. N-desalkylation and amide bond cleavage were the primary metabolic pathways at low drug doses and, as the biotransformation of delavirdine to desalkyl delavirdine reached saturation or inhibition, amide bond cleavage became the predominant pathway at higher doses and after multiple doses.

Animals↗

PubMed2006

Inside the brain of a neuron.

For many decades, neurons were considered to be the elementary computational units of the brain and were assumed to summate incoming signals and elicit action potentials only in response to suprathreshold stimuli. Although modelling studies predicted that single neurons constitute a much more powerful computational entity, able to perform an array of nonlinear calculations, this possibility was not explored experimentally until the discovery of active mechanisms in the dendrites of most neuron types. Here, we review several modelling studies that have addressed information processing in single neurons, starting with those characterizing the arithmetic of different dendritic components, to those tackling neuronal integration at the cell body and, finally, those analysing the computational abilities of the axon. We present modelling predictions along with supporting experimental data in an effort to highlight the significant contribution of modelling work to enhancing our understanding of single-neuron arithmetic.

Animals↗