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Mathematical models of renal fluid and electrolyte transport: acknowledging our uncertainty.

Mathematical models of renal tubular function, with detail at the cellular level, have been developed for most nephron segments, and these have generally been successful at capturing the overall bookkeeping of solute and water transport. Nevertheless, considerable uncertainty remains about important transport events along the nephron. The examples presented include the role of proximal tubule tight junctions in water transport and in regulation of Na(+) transport, the mechanism by which axial flow in proximal tubule modulates solute reabsorption, the effect of formate on proximal Cl(-) transport, the assessment of potassium transport along collecting duct segments inaccessible to micropuncture, the assignment of pathways for peritubular Cl(-) exit in outer medullary collecting duct, and the interaction of carbonic anhydrase-sensitive and -insensitive pathways for base exit from inner medullary collecting duct. Some of these uncertainties have had intense experimental interest well before they were cast as modeling problems. Indeed, many of the renal tubular models have been developed based on data acquired over two or three decades. Nevertheless, some uncertainties have been delineated as the result of model exploration and represent communications from the modelers back to the experimental community that certain issues should not be considered closed. With respect to model refinement, incorporating more biophysical detail about individual transporters will certainly enhance model reliability, but ultimate confidence in tubular models will still be contingent on experimental development of critical information at the tubular level.

Absorption↗

Mathematical models of diffusion-limited gas bubble dynamics in tissue.

Mathematical models of bubble evolution in tissue have recently been incorporated into risk functions for predicting the incidence of decompression sickness (DCS) in human subjects after diving and/or flying exposures. Bubble dynamics models suitable for these applications assume the bubble to be either contained in an unstirred tissue (two-region model) or surrounded by a boundary layer within a well-stirred tissue (three-region model). The contrasting premises regarding the bubble-tissue system lead to different expressions for bubble dynamics described in terms of ordinary differential equations. However, the expressions are shown to be structurally similar with differences only in the definitions of certain parameters that can be transformed to make the models equivalent at large tissue volumes. It is also shown that the two-region model is applicable only to bubble evolution in tissues of infinite extent and cannot be readily applied to bubble evolution in finite tissue volumes to simulate how such evolution is influenced by interactions among multiple bubbles in a given tissue. Two-region models that are incorrectly applied in such cases yield results that may be reinterpreted in terms of their three-region model equivalents but only if the parameters in the two-region model transform into consistent values in the three-region model. When such transforms yield inconsistent parameter values for the three-region model, results may be qualitatively correct but are in substantial quantitative error. Obviation of these errors through appropriate use of the different models may improve performance of probabilistic models of DCS occurrence that express DCS risk in terms of simulated in vivo gas and bubble dynamics.

Air Pressure↗

A mathematical model of ventilation response to inhaled carbon monoxide.

A comprehensive mathematical model, describing the respiration, circulation, oxygen metabolism, and ventilatory control, is assembled for the purpose of predicting acute ventilation changes from exposure to carbon monoxide in both humans and animals. This Dynamic Physiological Model is based on previously published work, reformulated, extended, and combined into a single model. Model parameters are determined from literature values, fitted to experimental data, or allometrically scaled between species. The model predictions are compared with ventilation-time history data collected in goats exposed to carbon monoxide, with quantitatively good agreement. The model reaffirms the role of brain hypoxia on hyperventilation during carbon monoxide exposures. Improvement in the estimation of total ventilation, through a more complete knowledge of ventilation control mechanisms and validated by animal data, will increase the accuracy of inhalation toxicology estimates.

Administration, Inhalation↗

Mathematical modeling of mitochondrial adenine nucleotide translocase.

We have developed a mathematical model of adenine nucleotide translocase (ANT) function on the basis of the structural and kinetic properties of the transporter. The model takes into account the effect of membrane potential, pH, and magnesium concentration on ATP and ADP exchange velocity. The parameters of the model have been estimated from experimental data. A satisfactory model should take into account the influence of the electric potential difference on both ternary complex formation and translocation processes. To describe the dependence of translocation constants on electric potential we have supposed that ANT molecules carry charged groups. These groups are shifted during the translocation. Using the model we have evaluated the translocator efficiency and predicted the behavior of ANT under physiological conditions.

Adenosine Diphosphate↗

Mathematical model for assimilation and contrast in perception of extent.

A mathematical model for assimilation and contrast in the perception of extent is presented, and predictions generated from the model are empirically tested. Implications of the model for the Müller-Lyer illusion are dealt with explicitly, and implications of the model for the Delboeuf, Ebbinghaus, and other illusions of extent are discussed in general terms.

Discrimination, Psychological↗

A mathematical model for peripheral nerve conduction velocity.

OBJECTIVE: To derive a mathematical model for peripheral axon geometry, and apply it to the prediction of latencies along a nerve. DESIGN: Retrospective review of data from individuals with bilaterally normal EMG/NCS, those with a diagnosis of carpal tunnel syndrome alone, and data from previous researchers. SETTING: Electrodiagnostic laboratory at a teaching hospital. SUBJECTS: Twenty-two (22) individuals with bilaterally normal EMG/NCS, and 61 hands from 40 individuals with carpal tunnel syndrome. Data from previous researchers was also utilized. RESULTS: Applying an exponentially tapering axon model to normal data yielded a formula for latency (L = kd 0.775) where k is a constant, and d is the distance from the distal end of the nerve. This formula produced a correlation of 0.777 for predicting median distal motor latencies using the proximal latency, and 0.676 for the ulnar nerve. The largest difference between predicted and actual distal latency was 0.48 msecs for the median nerve and 0.60 msecs for the ulnar nerve. This formula correctly classified as abnormal 3 (37.5%) out of 8 carpal tunnel syndrome cases with completely normal motor studies by standard criteria. This formula also agreed well with the data of other researchers, predicting normal distal latencies, F wave latencies, and identifying abnormal data. CONCLUSIONS: A single model for axon geometry based on uniform exponential tapering accurately predicts latencies for many nerves, and can detect subtle neuropathology.

Adult↗

[Mathematical modeling of oxygen diffusion and consumption in malignant tumor].

A mathematical model of oxygen diffusion and consumption in a malignant spherical tumor was developed. The model takes into account the dependence of the rate of oxygen consumption by cells on oxygen concentration. The expressions for the description of the dependence of oxygen concentration on the coordinate in the tumor are presented. Some model parameters were estimated from known experimental data. The hypoxic cells fraction (index related to tumour radioresistance) at critical and limiting tumor sizes were calculated.

Animals↗

Mathematical model of granulocytopoiesis and chronic myelogenous leukemia.

We present a mathematical model of granulocytopoiesis that depends on certain physiologically meaningful parameters. By choosing different values of these parameters, the model describes both the normal process and that in chronic myelogenous leukemia (CML). The model fits all the available experimental data tested. Furthermore, it shows how the CML cells can ultimately outnumber the normal cells and how this process can be very slow. The model provides a quantitative approach to the relationship between proliferation and maturation and resolves the apparent contradiction between decreased proliferation and increased production, by assuming that a greater fraction of CML cells is produced by division rather than by maturation. The model should be helpful in designing experiments to better define the abnormalities of proliferation and maturation in CML and in seeking to define the specific alterations in the cell regulatory networks resulting from the production of the chimeric p210bcr-abl protein characteristic of CML.

Granulocytes↗

Renal excretory function after renal denervation and administration of diuretics to unanaesthetized dogs evaluated by a mathematical model for describing the dynamics of the excretory process.

A mathematical model has been employed for describing the cumulative curve of excretion after diuretic administration. The program, developed in accordance with the model and the criteria of evaluation, allows an easy and rapid comparison of the effects of different kinds of diuretics in different doses. The experiments were carried out prior to and after left kidney denervation in unanaesthetized dogs with exteriorized ureters. Acetazolamide 3.0 mg/kg b.w., Furosemide 0.2 mg/kg b.w. or Amiloride 1.0 mg/kg b.w. were injected intravenously. The amount of excreted urine as well as of sodium, chloride and potassium was studied. No statistically significant differences in the dynamics of renal excretory function between the denervated and innervated kidneys were observed after the administration of Acetazolamide and Amichloride. After Furosemide, the flow-rate during maximum diuresis and the maximum chloride excretion rate were greater in the denervated kidney. No statistically significant differences were noted in sodium excretion. It appears that the greater part of compensatory reabsorption in the distal tubules of the denervated kidney takes place in the zone up to macula densa.

Acetazolamide↗

[Monitoring of occupational activities under the risk of heat stress: use of mathematical models in the prediction of physiological parameters].

Some authors proposed mathematical models that, starting from standardized conditions of environmental microclimate parameters, thermal impedance of the clothing, and energetic expenditure allowed the forecast of the body temperature and heart rate variations in respect to the basal values in subjects standing in the same environment. In the present work we verify the usefulness of these models applied to the working tasks characterized by standardized job made under unfavourable thermal conditions. In subject working in an electric power station the values of the body temperature and heart rate are registered and compared with the values obtained by the application of the studied models. The results are discussed in view of the practical use.

Body Temperature↗

[Use of mathematical models for quantitative environmental health risk assessment].

Two groups of mathematical models used in the quantitative assessment of cancer risk resulting from exposure to chemical substances for identifying a dose-response relationship are presented. They are as follows: statistical and stochastic models or those biologically motivated. Among statistical models, the logit, probit and Weibull models were considered. Among those biologically motivated, a one-hit model was analysed with special reference to they way from assumptions of the carcinogenesis theory to obtaining a dose-response curve. The two remaining models--multi-hit and multi-stage are discussed very briefly. An example of the fitting dose-response curves to experimental data is presented.

Animals↗

[Mathematical model of the cyclic variability of the influenza virus].

A mathematical model has been constructed on the basis of the hypothesis of cyclic variability of influenza A agent. This model simulates shift changes as a sequence of pulses of antigenic activity of five subtypes, these pulses being shifted in respect of each other and repeating in cycles.

Antigenic Variation↗

[Mathematical model of development of long-term synaptic plasticity].

Proposed mathematical model is described the long-term synaptic plasticity creation as the postsynaptic process based on the number of membrane receptor increase. The transmitter as the "marker" of the receptor type synthesis and the protein kinase as the activator of this protein synthesis are proposed.

Models, Theoretical↗

[Mathematical model of epidermal growth factor receptor-mediated lipid phosphatidylinositol(4,5)-bisphosphate hydrolyzation by phospholipase C-gamma1 activity].

OBJECTIVE: To investigate the dynamic characteristics of lipid phosphatidylinositol (4,5)-bisphosphate (PIP(2)) in plasma membrane hydrolyzed by phospholipase C-gamma1 in epidermal growth factor receptor(EGFR)-mediated signal pathway. METHODS: A mathematical model based on the law of mass action was established with differential equations to simulate metabolizable pathway of PIP(2). RESULTS: Differential equations of the key product concentration during hydrolysis of PIP(2) were formulated, and the effects of the parameters on these hydrolyzed products analyzed. CONCLUSION: This mathematical model provides foundation for further investigation of the dynamic changes of biological characteristics and the relations between the key product concentrations in PIP2 hydrolysis.

ErbB Receptors↗

Integrating multiscale mathematical modeling and multidimensional data reveals the effects of epigenetic instability on acquired drug resistance in cancer.

Biological and dynamic mechanisms by which Drug-tolerant persister (DTP) cells contribute to the development of acquired drug resistance have not been fully elucidated. Here, by integrating multidimensional data from drug-treated PC9 cells, we developed a novel multiscale mathematical model from an evolutionary perspective that encompasses epigenetic and cellular population dynamics. By coupling stochastic simulation with quantitative analysis, we identified epigenetic instability as the most prominent kinetic feature related to the emergence of DTP cell subpopulations and the effectiveness of intermittent treatment. Moreover, we revealed the optimal schedule for intermittent treatment, including the optimal area for therapeutic time and drug holidays. By leveraging single-cell RNA-seq data characterizing the drug tolerance of lung cancer, we validated the predictions made by our model and further revealed previously unrecognized biological features of DTP cells, such as cell autophagy and migration, as well as new biomarker genes of therapeutic tolerance. Our work not only provides a paradigm for the integration of multiscale mathematical models with newly emerging genomics data but also improves our understanding of the crucial roles of DTP cells and offers guidance for developing new intermittent treatment strategies against acquired drug resistance in cancer.

Drug Resistance, Neoplasm↗

Short-term autonomic control of cardiovascular function: a mini-review with the help of mathematical models.

In this work the main aspects of the short-term regulation of the cardiovascular system are reviewed and critically discussed, laying special emphasis on the role of the autonomic neural mechanisms involved, on their mutual interrelationships and complex integration. All these aspects are summarized with the help of mathematical models developed by the authors in past years. The main characteristics of the uncontrolled system (i.e., the heart and vessels) and of the efferent neural branches (sympathetic and vagal) working on it are first described. Then, the afferent pathways which participate in feedback mechanisms (baroreceptors, chemoreceptors, lung-stretch receptors, direct CNS response), and the feedforward mechanisms anticipating cardiovascular requirements are introduced, and their role discussed with reference to various cardiovascular perturbations (hemorrhage or posture changes, hypoxia, asphyxia, dynamic exercise). Analysis of physiological data via mathematical equations, and results of computer simulations, emphasize the great complexity, richness and variability of the autonomic cardiovascular control, including redundant mechanisms and antagonistic requirements. The use of mathematical models is essential to capture this richness, and to summarize apparent contradictory data into a coherent and comprehensive theoretical setting.

Animals↗

A mathematical model of combination therapy using the EGFR signaling network.

An increasing awareness of the significance of abnormal signal transduction in tumors and the concomitant development of target-based drugs to selectively modulate aberrantly-activated signaling pathways has given rise to a variety of promising new strategies in cancer treatment. This paper uses mathematical modeling to investigate a novel type of combination therapy in which multiple nodes in a signaling cascade are targeted simultaneously with selective inhibitors, pursuing the hypothesis that such an approach may induce the desired signal attenuation with lower doses of the necessary agents than when one node is targeted in isolation. A mathematical model is presented which builds upon previous theoretical work on EGFR signaling, simulating the effect of administering multiple kinase inhibitors in various combinations. The model demonstrates that attenuation of biochemical signals is significantly enhanced when multiple upstream processes are inhibited, in comparison with the inhibition of a single upstream process. Moreover, this enhanced attenuation is most pronounced in signals downstream of serially-connected target points. In addition, the inhibition of serially-connected processes appears to have a supra-additive (synergistic) effect on the attenuation of downstream signals, owing to the highly non-linear relationships between network parameters and signals.

Animals↗

Mathematical model of the filtration in the vascular network of the ophidian glomerulus.

The present work is a mathematical model of the fluid filtration in the glomerular network occurring in snakes. The model is based on the differential form of Starling's hypothesis and takes into account the angioarchitecture of the network and the behaviour on the microrheology of blood with nucleated red cells. The model predicts the hemodynamics and the transvascular fluxes in each vascular segment within the network. The model is applied to a vascular network of the glomerulus of the garter snake. A value of 0.593 microns/(s.mmHg) was determined for the hydraulic conductivity of the glomerular capillaries using the geometrical data of the network together with experimental data for the pressures and the blood flow rate reported in the literature. The analysis shows that the local filtration rates cover a wide range. In some of the vascular segments, the filtration leads to such a high increase in colloid-osmotic pressure that the level of the transvascular hydrostatic pressure difference is reached. Mathematical simulations of the variation of the glomerular blood flow rate due to vasoactivity of preglomerular arterioles show the effect on the filtration rate and the hemorheologic parameters.

Animals↗