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At least 289 records · Page 16Linked to original sources
PubMed1989

Application of the general linear model for smoothing gas exchange data.

The precision of an interpretation of gas exchange records in progressive exercise is limited by the typical breath-to-breath variation in the data. Recently, two procedures have been proposed for minimizing the "noise" in the estimates of alveolar gas exchange time series data. One approach utilizes an estimate of pulmonary blood flow (Q) for smoothing purposes. The other approach utilizes an estimate of effective lung volume (V'L) for smoothing purposes. In this paper, we formulate the smoothing problem as a general linear model and demonstrate the concurrent estimates of both V'L and Q. Furthermore, we investigate the interaction between V'L and Q. Specifically, when a high value of lung volume is used (such as the subject's resting functional residual capacity) in the alveolar gas exchange algorithm, the estimate of Q is biased low and the result is a less effective smoothing of the data. In addition, we demonstrate how the Q estimate can be improved by utilizing more appropriate estimates of arterial carbon dioxide tension.

Algorithms↗
PubMed1985

Temperature dependence of ethanol depression: linear models in male and female mice.

The relationship between body temperature and ethanol sensitivity was studied in male and female mice. Age-matched drug-naive mice of both sexes were injected with 3.6 g/kg ethanol (20% w/v) and placed into a chamber kept at one of 8 designated temperatures from 13 to 36 degrees C. In both sexes, wake-up rectal temperatures were significantly, positively correlated with chamber temperatures and sleep-times and were significantly, negatively correlated with wake-up brain and blood ethanol concentrations. Linear regression analyses indicated that wake-up temperature accounted for up to 71% of the variability in sleep-times and wake-up ethanol concentrations in these mice. Similar relationships were found when the change in body temperature from baseline (delta T) was substituted for wake-up rectal temperature. Adding body weights and baseline temperatures did not improve the predictive ability of linear models based on wake-up rectal temperature alone. The results support the contention that body temperature represents an important determinant of ethanol sensitivity in both sexes. These findings provide additional evidence that ethanol sensitivity varies with body temperature in accordance with membrane perturbation theories of anesthesia.

Animals↗
PubMed1996

[The prognostic factors in astrocytic tumors: analysis by the Kaplan-Meier method and the Weibull log-linear model].

As the prognosis of astrocytic tumors depends on various factors, identifying prognostic factors should be useful for developing strategies to cope with them. Between 1975 and 1994, more than 200 patients with astrocytic tumors were treated in Kagoshima University. Of these patients, 149 (grade I: 17, grade II: 42, grade III: 41, grade IV: 42, unproven: 7) have been followed up. Records of these patients were retrospectively reviewed for age at the time of initial symptoms, gender, histological grade (WHO), extent of tumor resection, radiation therapy, and administration of anticancer agents. We used the Kaplan-Meier method and the Weibull log-linear model to analyze the relation between survival time and these prognostic factors. Survival time was counted from onset of symptoms, and age of initial treatment was used as a covariant. The mean age of males at the initial diagnosis was 40.8 years (n = 77), and that of females was 39 years (n = 72). Using the Kaplan-Meier method, the mean survival time of the 149 patients was 101 months (males; 72.7 months, females; 134.5 months). Mean survival time of grade II was 144.3 months, that of grade III was 95.2 months, and grade IV (glioblastoma) was 15.9 months. Histological grades and mean ages of the groups showed a positive correlation. Among grades II, III and IV, the Kaplan-Meier survival curves were significantly different (p < 0.0001) according to the log-rank test. By the extent of surgical resection (subtotal or greater resection, partial resection, and less than partial resection), the mean survival time showed a significant difference (p < 0.05) on the log-rank test. However, we could not detect a significant difference in survival time between the group that received chemotherapy and the group which did not. The Weibull log-linear analysis indicated that gender, age, histological grade (WHO), extent of surgery, and dose of radiation therapy were prognostic factors. Covariants of grades II, III, and IV made survival time 0.314, 0.179, and 0.069 times as long as that of grade I. The survival time after "partial resection" became 1.415 times as long as the survival time after "less than partial resection". The covariant of "greater than subtotal resection" showed a prolonged survival time of 2.916 compared with that of "less than partial resection". As for age at treatment, the older the patient was, the shorter the survival time. The rate was 0.986 for each year of age. Irradiation of one Gy increased survival time by 1.015 times. Chemoimmunotherapy (dose of ACNU and interferon beta) could not be confirmed as an effective covariant.

Adult↗
PubMed1982

Non-linear model of the mechanics of breathing applied to the use and design of ventilators.

Respiratory treatment involves clinical problems which are often related to the pulmonary and circulatory condition of the patient. Choice of a proper respirator and its adequate use are very important for overcoming a good deal of the clinical problems which may arise. A good automatic ventilator should, under all circumstances, be capable of assuring a suitable gas exchange at the pulmonary level with as little alteration as possible to the physiological functions of the body. In this paper a non-linear model of the mechanics of breathing is used to examine: (1) the effects of four theoretical inspiratory flow patterns in intermittent positive pressure ventilation (IPPV); (2) the differences obtained with respect to IPPV when we use a positive end-expiratory pressure (PEEP) or a negative pressure in the expiratory phase (IPNPV); (3) the performances of four automatic ventilators at present on the market and commonly used in departments of anaesthesia and intensive care. The results obtained by simulation of the respiratory system indicate that, in practice, an ideal ventilator neither exists nor can be designed. The manner of using the ventilator leads to different results, more so than the theoretical inspiratory flow pattern or the type of ventilator used. The tables and graphs shown in the paper help to utilize the ventilator in such a way as to optimize the parameters which, each time, are considered the most important.

Biomechanical Phenomena↗
PubMedDate not supplied

Linear models for the analysis of variability in factorial designs: an application to anthropometric indicators.

This paper has two aims. One is to evaluate, in a set of 9740 'reference' neonates born in five Italian centres (Trieste, Milan, Parma, Rome, Bari) during 1973-1976 the effects of gestational age and birthplace on the variability of crown-heel length and head circumference at birth; this is a preliminary step in the construction of 'Italian' intrauterine growth standards for such anthropometric measures. The other aim is to put the various techniques for the analysis of variability into a common framework of Linear Models, either Generalized or Classical, to compare their main features and provide some indications about their application.

Analysis of Variance↗
PubMed1992

Generalized linear models with random effects; salamander mating revisited.

In recent years much effort has been devoted to extending regression methodology to non-Gaussian data, where responses are not independent. These methods for dependent responses are suitable for data from longitudinal studies or nested designs. However, use of these methods for crossed designs seems to have serious limitations due to the intensive computations involved because of the intractable nature of the joint distribution. In this paper, we cast the problem in a Bayesian framework and use a Monte Carlo method, the Gibbs sampler, to avoid current computational limitations. The flexibility of this approach is illustrated by analyzing the interesting salamander mating data reported by McCullagh and Nelder (1989, Generalized Linear Models, 2nd edition, London: Chapman and Hall).

Analysis of Variance↗
PubMed1999

Relationship between metallothioneins and metals in a natural population of the clam Ruditapes decussatus from Sfax coast: a non-linear model using Box-Cox transformation.

Cadmium, copper and zinc were determined concomitantly with metallothionein-like proteins (MTLPs) in the subcellular fractions of Ruditapes decussatus digestive gland. This study covered 4 months and aimed to evaluate the effect of metal pollution and other factors such as sex, size and reproductive state on MTLP levels. Copper concentrations did not vary with month, however Cd and Zn concentrations showed high levels during August. Organisms showing low cadmium concentrations presented the highest cadmium percentages in the soluble fraction (SF) containing MTLPs. However for high cadmium concentrations, the insoluble fraction (IF) was implicated in cadmium association. MTLP levels varied according to the month, the sex and the size of the organisms. A non-linear model based on the Box-Cox transformation, was proposed to describe a positive and a significant relationship between MTLPs and the studied metals. A model including sex and size showed that these two factors affected MTLP levels, but were less important than metals. Males of R. decussatus showed higher significant correlations between MTLP levels and cadmium than females. Moreover, the effect of size and reproductive state on MTLP levels was less perceptible in males than in females. As a result, MTLPs in males of R. decussatus could be proposed as suitable biomarker for detecting metal contamination.

Animals↗
PubMed1993

[Non-linear models for real time image processing and their applications in image enhancement, surface area determination and volume visualization].

This paper presents non-linear filter models that are suitable for real-time operations. The requirements imposed on these models by ultrasonic imaging are discussed. In particular, we study the characteristics of temporal filtering in cardiac imaging. Non-linear filter models incorporating these requirements are presented and compared with filtering schemes traditional in ultrasonic imaging. Furthermore, we illustrate how these filter models can be utilized to improve the quality and noise tolerance of automatic, real-time area detection algorithms. Finally, we present results from a 3D ultrasonic study of a foetus. The experiments illustrate how non-linear processing can increase the clinical information content that can be extracted from such investigations.

Body Surface Area↗
PubMed2006

Single subject image analysis using the complex general linear model--an application to functional magnetic resonance imaging with multiple inputs.

A linear time invariant model is applied to functional fMRI blood flow data. Based on traditional time series analysis, this model assumes that the fMRI stochastic output sequence can be determined by a constant plus a linear filter (hemodynamic response function) of several fixed deterministic inputs and an error term assumed stationary with zero mean. The input function consists of multiple exponential distributed (time delay between images) visual stimuli consisting of negative and erotic images. No a priori assumptions are made about the hemodynamic response function that, in essence, is calculated at each spatial position from the data. The sampling rate for the experiment is 400 ms in order to allow for filtering out higher frequencies associated with the cardiac rate. Since the statistical analysis is carried out in the Fourier domain, temporal correlation problems associated with inference in the time domain are avoided. This formal model easily lends itself to further development based on previously developed statistical techniques.

Adult↗
PubMed2003

Linkage disequilibrium assessment via log-linear modeling of SNP haplotype frequencies.

Analyses of high-density single-nucleotide polymorphism (SNP) data, such as genetic mapping and linkage disequilibrium (LD) studies, require phase-known haplotypes to allow for the correlation between tightly linked loci. However, current SNP genotyping technology cannot determine phase, which must be inferred statistically. In this paper, we present a new Bayesian Markov chain Monte Carlo (MCMC) algorithm for population haplotype frequency estimation, particularly in the context of LD assessment. The novel feature of the method is the incorporation of a log-linear prior model for population haplotype frequencies. We present simulations to suggest that 1) the log-linear prior model is more appropriate than the standard coalescent process in the presence of recombination (>0.02 cM between adjacent loci), and 2) there is substantial inflation in measures of LD obtained by a "two-stage" approach to the analysis by treating the "best" haplotype configuration as correct, without regard to uncertainty in the recombination process.

Algorithms↗
PubMed2004

Linear modelling analysis of baroreflex control of arterial pressure variability in rats.

The objective of the present study was to examine whether a simple linear feedback model of arterial pressure (AP) control by the sympathetic nervous system would be able to reproduce the characteristic features of normal AP variability by using AP and renal sympathetic nerve activity (RSNA) data collected in conscious sinoaortic baroreceptor denervated (SAD) rats. As compared with baroreceptor-intact rats (n=8), SAD rats (n=10) had increased spectral power (+ 680%) of AP in the low frequency range (LF, 0.0003-0.14 Hz) and reduced power (-19%) in the mid-frequency range (MF, 0.14-0.8 Hz) containing Mayer waves. In individual SAD rats, RSNA data were translated into 'sympathetic' AP time series by using the RSNA-AP transfer function that had been previously characterized in anaesthetized rats. AP 'perturbation' time series were then calculated by subtracting 'sympathetic' from actual AP time series. Actual RSNA and AP 'perturbation' time series were introduced in a reflex loop that was closed by using the previously identified baroreflex transfer function (from baroreceptor afferent activity to RSNA). By progressively increasing the open-loop static gain, it was possible to compute virtual AP power spectra that increasingly deviated from their progenitor spectra, with spectral power decreasing in the LF range (as a result of baroreflex buffering of haemodynamic perturbations), and increasing in the MF band (as a result of increasing transients at the resonance frequency of the loop). The most accurate reproduction of actual AP and RSNA spectra observed in baroreceptor-intact rats was obtained at 20-30% of the baroreflex critical gain (open-loop static gain resulting in self-sustained oscillations at the resonance frequency). In conclusion, while the gain of the sympathetic component of the arterial baroreceptor reflex largely determines its ability to provide an efficient correction of slow haemodynamic perturbations, this is achieved at the cost of increasing transients at higher frequencies (Mayer waves). However, the system remains fundamentally stable.

Adrenergic Fibers↗
PubMed1994

Linearized models of calcium dynamics: formal equivalence to the cable equation.

The dynamics of calcium and other diffusible second messengers play an important role in intracellular signaling. We show here the conditions under which nonlinear equations governing the diffusion, extrusion, and buffering of calcium can be linearized. Because the resulting partial differential equation is formally identical to the one-dimensional cable equation, quantities analogous to the input resistance, space constant, and time constant--familiar from the study of passive electrical propagation--can be defined. Using simulated calcium dynamics in an infinite cable and in a dendritic spine as examples, we bound the errors due to the linearization, and show that parameter uncertainty is so large that most nonlinearities can usually be ignored: robust phenomena in the nonlinear model are also present in the linear model.

Animals↗
PubMed1988

Sex hormones and human behavior: a critique of the linear model.

Behaviors in which human males and females differ are frequently attributed to fetal gonadal hormone exposures. Much current thinking on this topic relies on a model of explanation the authors call linear-analytic. This model emerges from studies of hormone-behavior relationships in nonhuman animals. Examining three areas of hormone-behavior research in humans, the authors argue that the form of explanation is inappropriate to the behavioral phenomena being explained. They urge the adoption of a more complex neurobiological approach that emphasizes the role of the cerebral cortex and correlatively minimizes the role of fetal hormones.

Brain↗
PubMedDate not supplied

Basic concepts for the linear model of ground water level recession.

Basic concepts are illustrated for the display of ground water level recession as a linear plot on a semilog graph, as first described by Rorabaugh. This exponential decay function can be achieved if there is a definable outflow boundary such as a lake or river and if water levels are expressed relative to the altitude of the boundary. The model can be used to estimate aquifer hydraulic diffusivity. Concepts are illustrated using three finite-difference simulations. One represents the ideal case as described by Rorabaugh, in which the altitude of the outflow boundary is uniform along its length. Another simulation includes a sloping boundary with simple geometry and demonstrates that the model can be used accurately. Based on this simulation, it appears that the ground water level must be expressed relative to the closest point on the outflow boundary. The third simulation includes a sloping boundary and complex boundary shape, and demonstrates departures from the linear model of recession and errors in the estimate of hydraulic diffusivity. Another cause of nonlinearity is the instability of the ground water head profile soon after a recharge event. The nature of these early-time departures will vary depending on the location of the water level observation site relative to the outflow boundary and the hydrologic divide of the ground water flow system.

Fresh Water↗
PubMed1982

HMO enrollment projection process and a proposed linear model.

Estimation of enrollment penetration of target employee' groups, as a percent of total employees, is a critical task in the planning and development process of HMOs. A heuristic process to estimate penetration rates of employee groups is described. Next, a multivariate linear statistical model is proposed and the parameters of the proposed model are estimated on the basis of a data base comprising 83 employee groups for which penetration rates have been estimated using the heuristic process. The linear multivariate model is found to be statistically significant for both the singles and family (marrieds) penetration rates. The proposed model simplifies the method for estimating penetration but has not been tested against actual data.

Forecasting↗
PubMed1999

Variables aggregation in a time discrete linear model.

In this work we extend approximate aggregation methods to deal with a very general linear time discrete model. Approximate aggregation consists in describing some features of the dynamics of a general system in terms of the dynamics of a reduced system governed by a few global variables. We present a time discrete model for a structured population (i.e., the population is subdivided in subpopulations) in which we can distinguish two processes of a general nature and whose corresponding time scales are very different from each other. We transform the general system to make the global variables appear and obtain the reduced system. These global variables are, for each subpopulation, a certain linear combination of the corresponding state variables. We show that, under quite general conditions, the asymptotic behavior of the reduced system can be known in terms of the corresponding behavior for the reduced system. The general method is applied to aggregate a multiregional Leslie model in which the demographic process is supposed to be fast with respect to migration.

Canada↗