The authors describe a hybrid computer neurone model intended for the investigation of stochastic transformations effected by neurones in correlation to some of their physiological parameters. The model is designed so as to give the best possible characterization of the internal dynamics of a neurone with minimum limiting conditions. It allows the generation of suitable input stochastic processes or operates with input processes obtained experimentally in the living neurone and it carries out basic statistical tests of the output stochastic process.

Computers, Hybrid↗

PubMed1982

Model analysis of the frequency of neuronal action potentials in the case of Gaussian input stochastic processes.

The authors describe the effects of changes in excitatory and inhibitory synapse weight on the number of spikes generated in the presence of constant absolute refractory phase and threshold level values. Input stochastic processes with Gaussian distributions were presumed. The problem was resolved in a hybrid computer model of stochastic neuronal activity. The results are given in the form of "e-curves", "i-curves" and gradient fields. It was shown that, in a set of paired values of the two weights, zones could be found in which the number of generated spikes depended mainly on just one of them. It was also shown that, in a given neurone with a fixed synapse morphology, the effect of the individual synapses on the number of generated spikes altered with changes in input stochastic processes to the synapses.

Action Potentials↗

PubMed1981

[Modern trends in modeling stochastic processes in neurons].

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Models, Neurological↗

PubMed1973

[Open bite and disorders of pronunication].

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Adolescent↗

PubMedDate not supplied

Computer models of albumin and haemoglobin glycation.

UNLABELLED: Two first-order mathematical models were developed to mimic the glycation of haemoglobin (H) and albumin (A). The total concentrations of A and H were assumed to be constant. The responses of the two models to varying blood glucose level were compared. The parameters of the haemoglobin model were not numerically estimated, only an informal fit was performed using clinical and published data. Nonlinear regression analysis was used to estimate the parameters of the albumin model. The level of glycated A (GA) was derived from the measured fructosamine level. Three diabetics were monitored daily for the level of fructosamine and blood glucose profile over a period of 10, 16 and 21 days, respectively. CONCLUSIONS: (1) The difference between GA and glycated H (GH) resulting from different elimination rates is decreased by the stratification of erythrocyte population. (2) Both GA and GH seem to have higher elimination rates than their nonglycated equivalents.

Blood Glucose↗

PubMedDate not supplied

A consultation system for insulin therapy.

This paper describes a computer system to advice on insulin therapy for diabetic in-patients. A mathematical model was developed to describe the effect of insulin on blood glucose (BG) level. The system uses an adaptive approach to analyse the response to an applied insulin dosage. It learns the patient's individual parameters. All conventional injection and insulin pump regimens are supported. The individualised model is used to predict BG level of the proposed insulin dosage. The system uses a generate-reject strategy to output optimum insulin therapy in terms of optimum BG. The predictive capability of the system was tested and it is able to predict BG with a precision of 2.5 mmol/l after 3 days and 6 days of insulin pump treatment and conventional injection therapy, respectively.

Blood Glucose Self-Monitoring↗

PubMedDate not supplied

The influence of short-term fasting on serum leptin levels, and selected hormonal and metabolic parameters in morbidly obese and lean females.

The aim of our study was to compare the changes of serum leptin levels after 24-h fasting in morbidly obese and lean females and to search for hormonal and metabolic factors responsible for the changes in serum leptin levels. Fourteen morbidly obese and twelve lean females were included in the study. The blood for leptin, insulin, cortisol, blood glucose (BG), beta-OH-butyrate (beta-OH), dehydroepiandrosterone (DHEA) and DHEA-sulphate (DHEA-S) measurements was withdrawn before and after a 24-h fast. Basal body mass index (BMI), serum leptin, insulin and beta-OH levels were significantly higher in the obese compared to the lean group. The 24-h fasting decreased significantly BMI, serum leptin (by 20% in obese vs. 62% in lean subjects), insulin (by 23.3% in obese vs. 23.1% in lean subjects) and increased beta-OH (by 36% in obese vs. 1300% in lean subjects). Basal serum leptin levels correlated positively with BMI in both groups and with insulin levels in the obese group. The multiple regression analysis using delta leptin as dependent and the basal values of the rest of studied parameters as independent variables revealed that in lean subjects serum cortisol together with DHEA-S and BMI accounted for 71% of variations of the change of serum leptin levels (delta leptin = 0.31- 0.0101 cortisol + 0.0012 DHEA-S + 0.37 BMI). In obese subjects the 43.9% of variations of the change of serum leptin levels was explained by BMI together with age and DHEA-S levels (delta leptin = 36.09 + 0.35 BMI - 0.717 age- 0.008 DHEA-S). The drop of serum leptin levels after 24-h starvation is significantly blunted in obese compared to lean subjects. The reason for the difference is probably the insulin resistance possibly further modified by different DHEA-S levels.

3-Hydroxybutyric Acid↗