The DOI matches its Crossref record.
Coefficients of normal blood glucose regulation
Abstract
A previously formulated glucose-insulin feed-back theory was simplified with appropriate assumptions for the purpose of determining which physiological sensitivity coefficients dominate the mathematical characteristics of the normal insulin and glucose tolerance curves. It was found from experimental data that these physiological coefficients approximate the well-known critical damping criteria of servomechanism theory. Correlations between theoretical and experimental results were made with some particular solutions of the necessary differential equations, obtained with the aid of an electronic analogue computer. Using a distribution volume of 17.5 liters for the 70-kg adult in three different methods of approach, it was found that the average coefficients of the insulin and glucose responses of the liver, pancreas, and peripheral tissues are approximately ⍺ = 0.780 unit/hr/unit, β = 0.208 unit/hr/g, γ = 4.34 g/hr/unit, and δ = 2.92 g/hr/g. Submitted on December 27, 1960
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Citations
Cited by
Sorted by citations
Items 101–200 of 345
A review on control-relevant glucose–insulin dynamics models and regulation strategies
Bhonsle, S., & Saxena, S. (2019) · Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering · doi:10.1177/0959651819870328 · Cited by 17
Identifiability of Control-Oriented Glucose-Insulin Linear Models: Review and Analysis
Hoyos, J. D., Villa-Tamayo, M. F., Builes-Montaño, C., Ramírez-Rincón, A., Godoy, J. L., García-Tirado, J., & Rivadeneira, P. (2021) · IEEE Access · doi:10.1109/access.2021.3076405 · Cited by 13
Abbes, I. B., Richard, P., Lefebvre, M.-A., Guilhem, I., & Poirier, J. (2013) · Journal of Diabetes Science and Technology · doi:10.1177/193229681300700315 · Cited by 12
Asadi, S., & Nekoukar, V. (2018) · Mathematical Biosciences · doi:10.1016/j.mbs.2018.09.006 · Cited by 17
Saber, S., & Mirgani, S. M. (2025) · Advances in Complex Systems · doi:10.1142/s1793962325500308 · Cited by 16
Yang, J., Tang, S., & Cheke, R. (2016) · Communications in Nonlinear Science and Numerical Simulation · doi:10.1016/j.cnsns.2016.02.001 · Cited by 16
“Conclusion Since the pioneering work on the dynamics of plasma insulin concentrations that led to the glucose-insulin regulatory system contributing to insulin therapies [28], numerous of research papers have appeared on the topic [1, 2, 9, 12, 14, 15, 29].”
BackgroundLinear Modeling and Prediction in Diabetes Physiology
Cescon, M., & Johansson, R. (2014) · Lecture notes in bioengineering · doi:10.1007/978-3-642-54464-4_9 · Cited by 23
Positive sliding mode control for blood glucose regulation
Menani, K., MohammadRidha, T., Magdelaine, N., et al. (2017) · International Journal of Systems Science · doi:10.1080/00207721.2017.1381893 · Cited by 16
“There are several works that were developed on the dynamics of the insulin since the 1960s, as in Bolie (1961), Bergman model (Bergman, Phillips, & Cobelli, 1981) and Hovorka (Hovorka et al., 2002).”
BackgroundA computational model of the human glucose-insulin regulatory system
Shiang, K., & Kandeel, F. (2010) · Journal of Biomedical Research · doi:10.1016/s1674-8301(10)60048-6 · Cited by 17
“Other than those reviewing journal articles, a pioneering work on modeling the glucose - insulin regulatory sys - tem and its ultradian insulin secretory oscillations can be traced back to Bolie [9] .”
BackgroundMethodResultInfluentialModels, Devices, Properties, and Verification of Artificial Pancreas Systems
Kushner, T., Bequette, B. W., Cameron, F. M., Forlenza, G. P., Maahs, D. M., & Sankaranarayanan, S. (2019) · Computational biology · doi:10.1007/978-3-030-17297-8_4 · Cited by 18
GLUCOSE TOLERANCE TESTS MODELING & PATIENT-SIMULATION FOR DIAGNOSIS
Sarma, D., & Ghista, D. N. (2001) · Journal of Mechanics in Medicine and Biology · doi:10.1142/s0219519401000258 · Cited by 15
Variable setpoint as a relaxing component in physiological control
Risvoll, G. B., Thorsen, K., Ruoff, P., & Drengstig, T. (2017) · Physiological Reports · doi:10.14814/phy2.13408 · Cited by 14
“Examples of other physiological processes modeled in a similar way include blood glucose regulation (Bolie 1961; Cobelli et al. 1987); and calcium oscillations (Sneyd et al. 2004), to mention a few.”
BackgroundThe role of glucagon in the regulation of blood glucose: Model studies
CELESTE, R., Ackerman, E., Gatewood, L. C., REYNOLDS, C., & Molnar, G. D. (1978) · Bulletin of Mathematical Biology · doi:10.1007/bf02463130 · Cited by 14
Models for the insulin response to intravenous glucose
Hagander, P., Tranberg, K. ‐., Thorell, J. I., & DiStefano, J. J. (1978) · Mathematical Biosciences · doi:10.1016/0025-5564(78)90003-2 · Cited by 14
EVALUATION OF THE ORAL GLUCOSE TOLERANCE TEST BY A CONTINUOUS SAMPLING TECHNIQUE.
Burns, T. W., Bregant, R., Hj, V., & Te, H. (1965) · PubMed · Cited by 14
DYNAMIC MODELING OF EXERCISE EFFECTS ON PLASMA GLUCOSE AND INSULIN LEVELS
Roy, A., & Parker, R. S. (2006) · IFAC Proceedings Volumes · doi:10.3182/20060402-4-br-2902.00509 · Cited by 14
Mathematical Model for Detecting Diabetes in the Blood
Kwach, B. O., Ongati, O., & Simwa, R. O. (2012) · Cited by 13
Fereydouneyan, F., Zare, A., & Mehrshad, N. (2011) · Journal of Medical Engineering & Technology · doi:10.3109/03091902.2011.569050 · Cited by 13
“Mathematical models for glucose regulation have been studied since the early 1960s [4].”
BackgroundOptimizing inputs for diagnosis of diabetes. I. Fitting a minimal model to data
Bergman, R. N., Kalaba, R. E., & Spingarn, K. (1976) · Journal of Optimization Theory and Applications · doi:10.1007/bf00933347 · Cited by 13
On the Origins and Rarity of Locally but Not Globally Identifiable Parameters in Biological Modeling
Barreiro, X. R., & Villaverde, A. F. (2023) · IEEE Access · doi:10.1109/access.2023.3288998 · Cited by 12
Glucose-Insulin System Based on Minimal Model: A Realistic Approach
Gonzalez, A. A., Voos, H., & Darouach, M. (2015) · UKSim International Conference on Computer Modelling and Simulation (UKSim) · doi:10.1109/uksim.2015.65 · Cited by 12
A feedback glucose control strategy for type II diabetes mellitus based on fuzzy logic
Ekram, F., Sun, L., Vahidi, O., Kwok, E., & Gopaluni, R. B. (2012) · The Canadian Journal of Chemical Engineering · doi:10.1002/cjce.21667 · Cited by 11
“Many approaches have been taken, starting from the initial glucose modeling work of Bolie [17].”
MethodRobust adaptive observer-based control of blood glucose level for type 1 diabetic patient
Seyedabadi, M., & Kalat, A. A. (2024) · Journal of Applied Biomedicine · doi:10.1016/j.bbe.2024.03.003 · Cited by 11
Blood Glycemia Reconstruction from Discrete Measurements using an Impulsive Observer
Rivadeneira, P. S., Sereno, J. E., Magdelaine, N., et al. (2017) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2017.08.2509 · Cited by 11
Modelling the effects of glucagon during glucose tolerance testing
Kelly, R. A., Fitches, M. J., Webb, S. D., Pop, S. R., & Chidlow, S. J. (2019) · Theoretical Biology and Medical Modelling · doi:10.1186/s12976-019-0115-3 · Cited by 11
Semizer, E., Yüceer, M., Atasoy, İ., & Berber, R. (2011) · Process Safety and Environmental Protection · doi:10.1016/j.cherd.2011.10.017 · Cited by 11
TYPE 1 DIABETIC PATIENT INSULIN DELIVERY USING ASYMMETRIC PI CONTROL
Gantt, J. A., Rochelle, K. A., & Gatzke, E. (2007) · Chemical Engineering Communications · doi:10.1080/00986440600992651 · Cited by 17
“The first attempts to capture the dynamics of glucose and insulin were performed in 1961 by Bolie (1961).”
BackgroundDynamics of a glucose–insulin model
Ma, M.-J., & Li, J. (2022) · Journal of Biological Dynamics · doi:10.1080/17513758.2022.2146769 · Cited by 11
“Bolie [4] is considered as the pioneer to study glucose–insulin dynamics.”
BackgroundMcGrath, T., Murphy, K. G., & Jones, N. S. (2018) · Journal of The Royal Society Interface · doi:10.1098/rsif.2017.0736 · Cited by 10
“…of coupled differential equations expressing insulin levels as a function of insulin secretion and clearance, and glucose levels as a function of glucose arrival and glucose clearance (due to both insulin-dependent and insulin-independent processes) [28,29] (electronic supplementary material, S2.”
Ensemble Glucose Prediction in Insulin-Dependent Diabetes
Ståhl, F. L., Johansson, R., & Renard, É. (2014) · Lecture notes in bioengineering · doi:10.1007/978-3-642-54464-4_2 · Cited by 10
Enhanced IMC for Glucose Control in Type I Diabetics Using a Detailed Physiological Model
Ramprasad, Y., Rangaiah, G. P., & Lakshminarayanan, S. (2006) · Food and Bioproducts Processing · doi:10.1205/fbp.05070 · Cited by 10
“The primitive modelling studies of the diabetic condition (Bolie, 1961; Ackerman et al., 1965) established a precedent for mathematical analysis of insulin-glucose interactions.”
BackgroundModel Reference Adaptive Control on Glucose for the Treatment of Diabetes Mellitus
Wahab, A., Kong, Y. K., & Quek, C. H. (2006) · Proceedings - IEEE Symposium on Computer-Based Medical Systems · doi:10.1109/cbms.2006.117 · Cited by 10
“Puckett Model [5] It uses ordinary Differential Equations (DE), Individual compartment models are obtained by performing mass balances around tissues important to glucose or insulin dynamics.”
MethodInfluentialLiu, S.-W., Huang, H., Lin, C.-H., & Chien, I. (2012) · Industrial & Engineering Chemistry Research · doi:10.1021/ie202308w · Cited by 10
Feedback control indirect response models
Zhang, Y., & D’Argenio, D. Z. (2016) · Journal of Pharmacokinetics and Pharmacodynamics · doi:10.1007/s10928-016-9479-8 · Cited by 10
A mathematical model for glucose-insulin interaction
Millsaps, K. T., & Pohlhausen, K. (1975) · Mathematical Biosciences · doi:10.1016/0025-5564(75)90038-3 · Cited by 10
Cobelli, C. (1984) · Mathematical Biosciences · doi:10.1016/0025-5564(84)90113-5 · Cited by 10
Sato, S., KATAYAMA, K., Kakemi, M., et al. (1988) · Journal of Pharmacobio-Dynamics · doi:10.1248/bpb1978.11.492 · Cited by 10
Optimal inputs for blood glucose regulation parameter estimation, part 3
Kalaba, R. E., & Spingarn, K. (1981) · Journal of Optimization Theory and Applications · doi:10.1007/bf00935551 · Cited by 10
Delay in ATP-dependent calcium inflow may affect insulin secretion from pancreatic beta-cell
Das, P. N., Halder, S., Bairagi, N., & Chatterjee, S. (2020) · Applied Mathematical Modelling · doi:10.1016/j.apm.2020.03.030 · Cited by 9
Theories and Models in Medicine
Thompson, R. P. (2011) · Philosophy of Medicine · doi:10.1016/b978-0-444-51787-6.50004-0 · Cited by 9
Benkerroum, N., ., Y. G., & Ghalfi, H. (2007) · Biotechnology(Faisalabad) · doi:10.3923/biotech.2007.481.488 · Cited by 9
Modeling and Prediction in Diabetes Physiology
Cescon, M. (2013) · Lund University Publications (Lund University) · Cited by 9
Identification, state estimation, and adaptive control of type i diabetic patients
حریری, ع. م. (2011) · Human Biology · Cited by 9
The Identification of Metabolic Systems - A Review
Carson, E. R., Finkelstein, L., & Cobelli, C. (1979) · IFAC Proceedings Volumes · doi:10.1016/s1474-6670(17)65418-1 · Cited by 9
The impact of obesity on predisposed people to type 2 diabetes: Mathematical model
Boutayeb, W., Lamlili, M. E. N., Boutayeb, A., & Derouich, M. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-16483-0_59 · Cited by 8
“Bolie (1961) introduced a simple linear model, using ordinary differential equations in glucose and insulin [5].”
Controllability and accessibility analysis of nonlinear biosystems
Díaz-Seoane, S., Barreiro, A., & Villaverde, A. F. (2023) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2023.107837 · Cited by 8
Rao, F., Zhang, Z., & Li, J. (2023) · Journal of Mathematical Biology · doi:10.1007/s00285-023-02003-6 · Cited by 8
“A footmark for the mathematical modeling approach in the study of diabetic disease can be found in 1961 by Bolie (1961).”
MethodSokol, Y., Solovyova, O., Koval, S. M., Kolisnyk, K., Лапта, С., Гончарова, О. А., Karachentsev, I., & Кравчун, Н. А. (2019) · IEEE International Conference on Electronics and Nanotechnology (ELNANO) · doi:10.1109/elnano.2019.8783806 · Cited by 8
“Bolie [4] (1961), the modifications of which, without eliminating its physiological inadequacy, were ultimately all other models of glucose-insulin interactions.”
BackgroundUllah, N., & Muhammad, A. (2020) · IET Systems Biology · doi:10.1049/iet-syb.2020.0002 · Cited by 8
Gaetano, A. D., Gaz, C., & Panunzi, S. (2019) · PLoS ONE · doi:10.1371/journal.pone.0211331 · Cited by 9
A parsimonious model of blood glucose homeostasis
Ng, E., Kaufman, J. M., VEEN, L. V., & Fossat, Y. (2022) · PLOS Digital Health · doi:10.1371/journal.pdig.0000072 · Cited by 8
“While, in the early 1960s, Bolie [11] built his own analogue computer especially for the purpose of producing numerical predictions with his model, aptly called the “Hormone Computer”, a decade later digital computers were rapidly becoming more accessible and useful, as demonstrated, for instance,…”
BackgroundMethodDevelopment of a physiological model forpatients with type 2 diabetes mellitus
Vahidi, O., Kwok, K. E., Gopaluni, R. B., & Sun, L. (2010) · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · doi:10.1109/acc.2010.5531636 · Cited by 8
Balakrishnan, N. P., Rangaiah, G. P., & Lakshminarayanan, S. (2012) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2012.6346164 · Cited by 8
“Mechanistic and empirical BG models have been developed since early 1960s [1].”
BackgroundFernández-Peruchena, C. M., & Prado-Velasco, M. (2010) · The Open Biomedical Engineering Journal · doi:10.2174/1874120701004010236 · Cited by 7
“Later, several mathematical models were proposed in this area, being a remarkable example the one proposed by Bolie in 1961 about blood glucose regulation [29].”
BackgroundLema-Pérez, L., Aguirre-Zapata, E., & Garcia‐Tirado, J. (2015) · IEEE Colombian Conference on Automatic Control (CCAC) · doi:10.1109/ccac.2015.7345212 · Cited by 9
“Perhaps the first register of such a trend is due to the paper of Bolie in 1961 in which a first physiologic model of the glucose-insulin system was presented [4].”
BackgroundMATHEMATICAL MODELING OF INTRA-VENOUS GLUCOSE TOLERANCE TEST MODEL WITH TWO DISCRETE DELAYS
Pitchaimani, M., Krishnapriya, P., & Monica, C. (2015) · Journal of Biological Systems · doi:10.1142/s021833901550031x · Cited by 8
Mathematical description of the blood sugar system
Antomonov, Y. G., Gnilitskaya, N. K., Kiforenko, S. I., et al. (1968) · Mathematical Biosciences · doi:10.1016/0025-5564(68)90028-x · Cited by 8
A practical approach to prescribe the amount of used insulin of diabetic patients
Mazandarani, M., & Kamyad, A. V. (2011) · Cited by 8
A New Time-Delay Model for Chaotic Glucose-Insulin Regulatory System
Al-Hussein, A.-B. A., Tahir, F. R., Fortuna, L., Bucolo, M. A. R., Frasca, M., & Buscarino, A. (2020) · International Journal of Bifurcation and Chaos · doi:10.1142/s0218127420501783 · Cited by 7
Models for the Study of Whole-Body Glucose Kinetics: A Mathematical Synthesis
McKnight, L. L., López, S., Shoveller, A. K. K., & France, J. (2013) · ISRN Biomathematics · doi:10.1155/2013/120974 · Cited by 7
Recent Trends in Blood Glucose Control Studies
(2015) · Automatic Control of Physiological State and Function · doi:10.4172/2090-5092.1000106 · Cited by 7
Closed Loop Model for Glucose Insulin Regulation System using Labview
Srinivas, P. (2012) · International Journal of Instrumentation and Control Systems · doi:10.5121/ijics.2012.2408 · Cited by 7
Syafiie, S. (2020) · ISA Transactions · doi:10.1016/j.isatra.2020.11.012 · Cited by 7
Regulation of blood glucose level in diabetes mellitus using palatable diet composition
Nilam, V. K. K. (2003) · Australasian Physical & Engineering Sciences in Medicine · doi:10.1007/bf03178783 · Cited by 7
Anin numero study of glucose-insulin interaction
Chorbajian, T., Coull, B. M., & Coull, J. (1971) · Bulletin of Mathematical Biology · doi:10.1007/bf02476786 · Cited by 5
Optimal Inputs For Blood Glucose Regulation Parameter Estimation
Bergman, R. N., & Kalaba, B. E. (2005) · Asilomar Conference on Signals, Systems and Computers (ACSSC) · doi:10.1109/acssc.1977.748954 · Cited by 7
Formalizing the Glucose Homeostasis Mechanism
Singh, N. K., Wang, H., Lawford, M. S., Maibaum, T. S. E., & Wassyng, A. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-07725-3_46 · Cited by 7
“[2] presented the first mathematical model based on differential equations to model the glucose and insulin concentration, illustrating the dynamics of insulin-glucose for diagnostic purpose and evaluating several parameters of the diabetic and pre-diabetic conditions.”
BackgroundMethodIn Vivo Modeling for Glucose Homeostasis
Finkelstein, S. M., Bleicher, M. A., Batthany, S., & Tiefenbrun, J. (1975) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.1975.324539 · Cited by 7
“interaction within the intact closed-loop system can only be obtained if each block is itself described quantitatively [4]-[7].”
BackgroundCarbMetSim: A discrete-event simulator for carbohydrate metabolism in humans
Goyal, M., Aydas, B., Ghazaleh, H., & Rajasekharan, S. (2020) · PLoS ONE · doi:10.1371/journal.pone.0209725 · Cited by 5
Zazueta, C. L., Stavdahl, Ø., & Fougner, A. L. (2021) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2021.3125839 · Cited by 6
Multiple model adaptive postprandial glucose control of type 1 diabetes
Raafat, S. M., Amear, B. K. A.-A., & Al‐Khazraji, A. (2021) · Engineering Science and Technology an International Journal · doi:10.1016/j.jestch.2020.11.007 · Cited by 6
Generalised stochastic model for characterisation of subcutaneous glucose time series
Khovanova, N. A., Zhang, Y., & Holt, T. (2014) · IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI ...) · doi:10.1109/bhi.2014.6864408 · Cited by 6
“where G, I denote the plasma glucose and insulin respectively, J is the glucose input, and a1, a2, a3, a4 are parameters [4].”
BackgroundNuevas Estrategias de Control Glucémico en Pacientes con Diabetes Mellitus Tipo 1
Rivadeneira, P. S., Sereno, J. E., & Caicedo, M. A. (2018) · Revista Iberoamericana de Automática e Informática Industrial RIAI · doi:10.4995/riai.2018.9728 · Cited by 6
“Los modelos tradicionales propuestos para la dinámica de la interacción glucosa-insulina en pacientes DMT1 (Bergman, 2005; Bolie, 1961; De Gaetano y Arino, 2000), se diseñaron con base en el tratamiento intravenoso de tolerancia a la glucosa, debido a esto presentan incongruencias que no son…”
BackgroundWilinska, M. E., & Hovorka, R. (2014) · Lecture notes in bioengineering · doi:10.1007/978-3-642-54464-4_6 · Cited by 6
Simplified Mathematical Model of Glucose-Insulin System
Ntaganda, J. M., Minani, F., Banzi, W., Mpinganzima, L., Niyobuhungiro, J., Gahutu, J. B., Rutaganda, E., Kambutse, I., & Dusabejambo, V. (2018) · American Journal of Computational Mathematics · doi:10.4236/ajcm.2018.83019 · Cited by 6
“Starting from the model proposed by Bolie in 1961 [12] mathematical modeling of glucose-insulin interaction in normal body has been studied.”
MethodLeptin effect’s on glucose and insulin kinetics: A mathematical model
Maamar, M. H., & Belhamiti, O. (2022) · Communications in Nonlinear Science and Numerical Simulation · doi:10.1016/j.cnsns.2022.106591 · Cited by 5
Mathematical models of cystic fibrosis as a systemic disease
Olivença, D. V., Davis, J. D., Kumbale, C. M., Zhao, C., Brown, S. P., McCarty, N. A., & Voit, E. O. (2023) · WIREs Mechanisms of Disease · doi:10.1002/wsbm.1625 · Cited by 6
Giosuè, A., Skantze, V., Hjorth, T., Hjort, A., Brunius, C. F., Giacco, R., Costabile, G., Vitale, M., Wallman, M., Jirstrand, M., et al. (2024) · American Journal of Clinical Nutrition · doi:10.1016/j.ajcnut.2024.11.028 · Cited by 5
Nonlinear turnover models for systems with physiological limits
Peletier, L. A., & Gabrielsson, J. (2008) · European Journal of Pharmaceutical Sciences · doi:10.1016/j.ejps.2008.12.012 · Cited by 5
Mathematical modeling and simulations of the pathophysiology of Type-2 Diabetes Mellitus
Nani, F., & Jin, M. (2015) · International Conference on Biomedical Engineering and Informatics (BMEI) · doi:10.1109/bmei.2015.7401518 · Cited by 5
“Many mathematical models in the literature were devoted mainly to the dynamics of glucose in relation to the hormone, insulin.”
BackgroundArtificial pancreas: glycemic control strategies for avoiding hypoglycemia
Sereno, J. E., Caicedo, M. A., & Rivadeneira, P. S. (2018) · DYNA · doi:10.15446/dyna.v85n207.71535 · Cited by 6
“In the literature, different models have been presented to represent glucose-insulin dynamics [17-19].”
BackgroundSkantze, V., Hjorth, T., Wallman, M., Brunius, C. F., Dicksved, J., Pelve, E. A., Esberg, A., Vitale, M., Giacco, R., Costabile, G., et al. (2023) · Nutrients · doi:10.3390/nu15204369 · Cited by 6
Kiforenko, S. I. (2017) · Kibernetika i vyčislitelʹnaâ tehnika · doi:10.15407/kvt187.01.080 · Cited by 5
A stochastic delay differential model for glucose-insulin interactions
Rihan, F. A., Udhayakumar, K., Nasrin, S. F., & Rajivganthi, C. (2025) · Ain Shams Engineering Journal · doi:10.1016/j.asej.2025.103668 · Cited by 4
Probing the binding affinity of amyloids to reduce toxicity of oligomers in diabetes
Smaoui, M. R., Orland, H., & Waldispühl, J. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv143 · Cited by 4
“We think that by taking into account the observed effect of oligomers on cell death the analytical solution of insulin in Equation (29) introduced by (Bolie, 1961) will be the one presented in Equation (31).”
BackgroundA phenomenological model of plasma FFA, glucose, and insulin concentrations during rest and exercise
Roy, A., & Parker, R. S. (2010) · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · doi:10.1109/acc.2010.5530687 · Cited by 4
“Since the 1960s, mathematical models have been used to describe glucose-insulin dynamics [4], [5], [6], [7].”
MethodKhan, I. U., Ahmad, T., & Maan, N. (2013) · Scientific Research and Essays · doi:10.5897/sre12.066 · Cited by 4
Adams, C., & Lasseigne, D. G. (2018) · Letters in Biomathematics · doi:10.1080/23737867.2018.1429332 · Cited by 12
“Beginning with a model using ordinary differential equations by Bolie (1961), mathematicians and scientists have been developing models for over the past five decades.”
The Negative Feedback Connection in the Homeostatic System of Carbohydrate Exchange Regulation
Sokol, Y., Лапта, С., Chmykhova, O., et al. (2018) · IEEE International Conference on Electronics and Nanotechnology (ELNANO) · doi:10.1109/elnano.2018.8477505 · Cited by 4
“Bolie episodically investigated [5], his model has the following form:”
BackgroundMethodModeling and Control of the Glucose‐Insulin‐Glucagon System in Type I Diabetis Mellitus
Sangeetha, S., Sreepradha, C., Sobana, S., Bidisha, P., & Panda, R. C. (2020) · ChemBioEng Reviews · doi:10.1002/cben.201900015 · Cited by 4
Proportional Insulin Infusion in Closed-Loop Control of Blood Glucose
Grasman, J., Callender, H. L., & Mensink, M. (2017) · PLoS ONE · doi:10.1371/journal.pone.0169135 · Cited by 4
Finite-time control of plasma glucose in insulin therapies for diabetes
Liu, S., Huang, M., Song, X., & Shi, X. (2018) · Advances in Difference Equations · doi:10.1186/s13662-018-1532-z · Cited by 4
The glucose control mechanism viewed as a regulator
Zelin, S., Jun, G. H., & Norwich, K. H. (1975) · Medical & Biological Engineering & Computing · doi:10.1007/bf02477126 · Cited by 4
HIRAYAMA, H., Kasuya, Y., YAGISHITA, A., & Katakura, T. (1985) · Journal of Pharmacobio-Dynamics · doi:10.1248/bpb1978.8.808 · Cited by 4
Gahamanyi, M., Ntaganda, J. M., & Haggar, M. S. D. (2016) · Open Journal of Applied Sciences · doi:10.4236/ojapps.2016.612072 · Cited by 3
“828 the 1960s, researches in the direction of solving mathematical models have been developed to describe glucose-insulin dynamic systems [1] [13].”
BackgroundA biological rhythm in the hypothalamic system links sleep-wake cycles with feeding-fasting cycles
Tamayo-Molina, Y. S., Giraldo, M. A., Rodríguez, B. A., & Machado, G. (2024) · Scientific Reports · doi:10.1038/s41598-024-77915-4 · Cited by 6
Mager, D. E. (2025) · Handbook of experimental pharmacology · doi:10.1007/164_2025_746 · Cited by 3
Robust glucose control via μ-synthesis in type 1 diabetes mellitus
Morales-Contreras, J., Ruiz-Velazquez, E., & García-Rodríguez, J. A. (2017) · IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC) · doi:10.1109/ropec.2017.8261671 · Cited by 3
“Simple linear models have been proposed in [6], [7].”
MethodManrique-Córdoba, J., Romero-Ante, J. D., Albán, Ó. A. V., Vicente-Samper, J. M., & Sabater-Navarro, J. M. (2020) · Revista Iberoamericana de Automática e Informática Industrial RIAI · doi:10.4995/riai.2019.11161 · Cited by 3
“Uno de los pioneros en este campo fue Bolie, quien en 1961 (Bolie, 1961) propuso un modelo usando ecuaciones diferenciales ordinarias que con la ayuda de un computador análogo electrónico realizó correlaciones entre resultados teóricos y experimentales.”
BackgroundSchumock, G., Bandeen‐Roche, K., Chia, C. W., Kalyani, R. R., Ferrucci, L., & Varadhan, R. (2024) · PLoS ONE · doi:10.1371/journal.pone.0302381 · Cited by 3
Metadata
- Authors
- Bolie, V. W.
- Affiliations
- Iowa State University (US)
- Corresponding author
- Bolie, Victor W.
- Venue
- Journal of Applied Physiology
- Publisher
- American Physiological Society
- Published
- 1961-09-01
- Volume
- 16
- Issue
- 5
- Pages
- 783-788
- ISSN
- 0161-7567 (ISSN-L)
- 8750-7587
- 1522-1601
- OpenAlex
- W2337101260
- Cited by
- 349
- References
- 0
- Citations by year
- 2026: 12 · 2025: 25 · 2024: 18 · 2023: 14 · 2022: 10 · 2021: 13 · 2020: 18 · 2019: 13 · 2018: 13 · 2017: 16 · 2016: 8 · 2015: 15 · 2014: 12 · 2013: 12 · 2012: 10
- FWCI
- 2.58
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Applied Physiology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Pancreatic function and diabetes
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Keywords
- blood glucose regulation, glucose tolerance curve, critical damping, volume of distribution, glucose-insulin dynamics
- MeSH terms
- Blood Glucose, Humans, Carbohydrate Metabolism
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review