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Mechanisms of the Age-Associated Deterioration in Glucose Tolerance
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Glucose tolerance decreases with age. For determining the cause of this decrease, 67 elderly and 21 young (70.1 ± 0.7 vs. 23.7 ± 0.8 years) participants ingested a mixed meal and received an intravenous injection of glucose. Fasting glucose and the glycemic response above basal were higher in the elderly than in the young participants after either meal ingestion (P < 0.001) or glucose injection (P < 0.01). Insulin action (Si), measured with the meal and intravenous glucose tolerance test models, was highly correlated (r = 0.72; P < 0.001) and lower (P ≤ 0.002) in the elderly than in the young participants. However, when adjusted for differences in percentage body fat and visceral fat, Si no longer differed between groups. When considered in light of the degree of insulin resistance, all indexes of insulin secretion were lower (P < 0.01) in the elderly participants, indicating impaired β-cell function. Hepatic insulin clearance was increased (P < 0.002), whereas total insulin clearance was decreased (P < 0.002) in the elderly subjects. Multivariate analysis (r = 0.70; P < 0.001) indicated that indexes of insulin action (Si) and secretion (Phitotal) but not age, peak oxygen uptake, fasting glucose, degree of fatness, or hepatic insulin clearance predicted the postprandial glycemic response. We conclude that the deterioration in glucose tolerance that occurs in healthy elderly subjects is due to a decrease in both insulin secretion and action with the severity of the defect in insulin action being explained by the degree of fatness rather than age per se.
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“Furthermore, use of the meal minimal model in conjunction with the triple tracer method permits robust model assessments of indices of insulin action on the periphery (SI) and on the liver (SIL), glucose effectiveness (SG), insulin secretion, and β-cell function (disposition index).[49][50][51][52][53][54][55][56][57][58][59][60][61]”
From Developing the UVA/Padova Type 1 Diabetes Simulator: Modeling, Validation, Refinements, and Utility (2023) · cites this paper as [49]
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“our results are consistent with a growing body of evidence that indicates that age-related changes in adiposity and physical inactivity are the primary determinants of the age-related declines in insulin sensitivity rather than chronological age (6,7,31–33).”
From Age, Obesity, and Sex Effects on Insulin Sensitivity and Skeletal Muscle Mitochondrial Function (2010) · cites this paper as [7]
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“These sophisticated models became possible because of unique phenotypic data of carbohydrate metabolism obtained from studies conducted in >200 adults and children applying the triple tracer technique to derive key metabolic indices and parameters.[48][49][50][51][52][53][54]”
From Developing the UVA/Padova Type 1 Diabetes Simulator: Modeling, Validation, Refinements, and Utility (2023) · cites this paper as [49]
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“Lower fasting glucose levels and greater postprandial glucose disappearance rates in elderly women than in men were also observed in another study (7).”
From Age, Obesity, and Sex Effects on Insulin Sensitivity and Skeletal Muscle Mitochondrial Function (2010) · cites this paper as [7]
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“which is consistent with a recent report in a large number of people (7) that demonstrated that after adjusting for body composition and cardiorespiratory fitness, the age-related differences in insulin action were eliminated.”
From Age, Obesity, and Sex Effects on Insulin Sensitivity and Skeletal Muscle Mitochondrial Function (2010) · cites this paper as [7]
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“Other studies have also demonstrated that diabetes can be prevented (or delayed) by lifestyle change (23,24) and medication (25,26), but the DPP provides unique information about prevention in older adults.”
From ]. The Influence of Age on the Effects of Lifestyle Modification and Metformin in Prevention of Diabetes (2006) · cites this paper as [23]
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Cites
Longitudinal Effects of Aging on Serum Total and Free Testosterone Levels in Healthy Men
Harman, S. M., Metter, E. J., Tobin, J. D., Pearson, J., & Blackman, M. R. (2001) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jcem.86.2.7219 · Cited by 2,760
Quantitative estimation of insulin sensitivity.
Bergman, R. N., Ider, Y. Z., Bowden, C. R., & Cobelli, C. (1979) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.1979.236.6.e667 · Cited by 1,874 · cited 1×
“Indexes of insulin action (SiIVGTT) and glucose effectiveness (SgIVGTT) were calculated after intravenous glucose injection as previously described (39).”
MethodSelf-citationBergman, R. N., Phillips, L. S., & Cobelli, C. (1981) · Journal of Clinical Investigation · doi:10.1172/jci110398 · Cited by 1,640
Self-citationKahn, S. E., Prigeon, R. L., McCulloch, D. K., Boyko, E. J., Bergman, R. N., Schwartz, M. W., Neifing, J. L., Ward, W. K., Beard, J. C., & Palmer, J. P. (1993) · Diabetes · doi:10.2337/diab.42.11.1663 · Cited by 1,405
Zander, M., Madsbad, S., Madsen, J. L., & Holst, J. J. (2002) · The Lancet · doi:10.1016/s0140-6736(02)07952-7 · Cited by 1,297
Toward Physiological Understanding of Glucose Tolerance: Minimal-Model Approach
Bergman, R. N. (1989) · Diabetes · doi:10.2337/diab.38.12.1512 · Cited by 1,001
Cauter, E. V., Mestrez, F., Sturis, J., & Polonsky, K. S. (1992) · Diabetes · doi:10.2337/diab.41.3.368 · Cited by 887
RIZZA, R. A., MANDARINO, L. J., & GERICH, J. E. (1982) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jcem-54-1-131 · Cited by 696 · cited 1×
“tide and glucagon-like peptide-1-(7-36) amide infused at near-physiological”
BackgroundSelf-citationCauter, E. V., Mestrez, F., Sturis, J., et al. (1992) · Diabetes · doi:10.2337/diabetes.41.3.368 · Cited by 643
Glucose Intolerance and Aging: Evidence for Tissue Insensitivity to Insulin
DeFronzo, R. A. (1979) · Diabetes · doi:10.2337/diab.28.12.1095 · Cited by 595
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Tatsumi, Y., Ohno, Y., Morimoto, A., Nishigaki, Y., Maejima, F., Mizuno, S., & Watanabe, S. (2012) · Diabetology International · doi:10.1007/s13340-012-0067-x · Cited by 24
Bush, N. C., Basu, R., Rizza, R. A., Nair, K. S., Khosla, S., & Jensen, M. D. (2012) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2012-2285 · Cited by 22
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Denti, P., Bertoldo, A., Vicini, P., & Cobelli, C. (2010) · American Journal of Physiology. Endocrinology and Metabolism · doi:10.1152/ajpendo.00656.2009 · Cited by 23
Self-citationXie, X., Wu, C., Dao, F., Deng, K., Yan, D., Huang, J., Lyu, H., & Lin, H. (2025) · iMeta · doi:10.1002/imt2.70060 · Cited by 22
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Seiron, P., Stenwall, A., Hedin, A., Granlund, L., Esguerra, J. L. S., Volkov, P., Renström, E., Korsgren, O., Lundberg, M., & Skog, O. (2021) · PLoS ONE · doi:10.1371/journal.pone.0247888 · Cited by 17
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Shahid, R. K., Chu, L. M., Arnason, T., & Pahwa, P. (2023) · Canadian Journal of Diabetes · doi:10.1016/j.jcjd.2023.03.006 · Cited by 21
Semnani‐Azad, Z., Johnston, L., Lee, C., Retnakaran, R. R., Connelly, P. W., Harris, S. B., Zinman, B., & Hanley, A. J. (2019) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2019-000825 · Cited by 20
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He, X., Zhao, X., Gu, Q., Shen, J., Hu, Y., & Hu, R. (2012) · The Tohoku Journal of Experimental Medicine · doi:10.1620/tjem.227.245 · Cited by 21
Liu, J., Yy, W., Huang, X.-M., Yang, M. L., Bb, Z., WANG, F., Zha, Y., Sheng, L., Zp, C., & Gu, Y. (2014) · PubMed · Cited by 20
Zhang, Y., Liu, X., Wang, M., Song, Y., Zhang, L., You, Y., Su, Y., Liu, Y., & Kou, C. (2018) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph15061125 · Cited by 20
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Varayil, J. E., Yadav, S., Miles, J. M., Okano, A., Kelly, D. G., Hurt, R. T., & Mundi, M. S. (2015) · Journal of Parenteral and Enteral Nutrition · doi:10.1177/0148607115606116 · Cited by 21
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Kim, H., Chijiki, H., Nanba, T., Ozaki, M., Sasaki, H., Takahashi, M., & Shibata, S. (2020) · Nutrients · doi:10.3390/nu12103035 · Cited by 19
Ma, X., Becker, D. J., Arena, V. C., Vicini, P., & Greenbaum, C. J. (2009) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2008-2687 · Cited by 18
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Sunehag, A. L., Man, C. D., TOFFOLO, G. M., Haymond, M. W., Bier, D. M., & Cobelli, C. (2008) · Obesity · doi:10.1038/oby.2008.496 · Cited by 19
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Wilkin, T. J. (2013) · Current Diabetes Reports · doi:10.1007/s11892-013-0407-7 · Cited by 20
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Yue, F., Zhang, G., Tang, R., Zhang, Z., Teng, L., & Zhang, Z. (2016) · Lipids in Health and Disease · doi:10.1186/s12944-016-0280-x · Cited by 22
Ning, F., Qiao, Q., Tuomilehto, J. O., Hammar, N., Ho, S. Y., Söderberg, S., Zimmet, P., Shaw, J. E., Nakagami, T., Mohan, V., et al. (2010) · Diabetes/Metabolism Research and Reviews · doi:10.1002/dmrr.1078 · Cited by 19
Katakura, M., Komatsu, M., Sato, Y., Hashizume, K., & Aizawa, T. (2004) · Metabolism · doi:10.1016/j.metabol.2004.02.024 · Cited by 19
Holistic and Personalized Strategies for Managing in Elderly Type 2 Diabetes Patients
Yun, J., Kim, K., Ahn, Y., Han, K., & Ko, S. (2024) · Diabetes & Metabolism Journal · doi:10.4093/dmj.2024.0310 · Cited by 26
Duijsens, D., Verkempinck, S. H. E., Somers, E., Hendrickx, M., & Grauwet, T. (2023) · Food & Function · doi:10.1039/d3fo04241c · Cited by 18
Morimoto, S., Sosa, T. C., Calzada, L., Reyes‐Castro, L. A., Díaz‐Díaz, E., Morales, A., Nathanielsz, P. W., & Zambrano, E. (2012) · Journal of Developmental Origins of Health and Disease · doi:10.1017/s2040174412000463 · Cited by 18
Chen, J., KASTROLL, J., Bello, F. M., Pangburn, M. M., Murali, A., Smith, P. M., Rychcik, K., Loughridge, K. E., Vandevender, A. M., Dedousis, N. L., et al. (2025) · Scientific Reports · doi:10.1038/s41598-025-92572-x · Cited by 17
An update on pancreatic regeneration mechanisms: Searching for paths to a cure for type 2 diabetes
Soldovieri, L., Giuseppe, G. D., Ciccarelli, G., Quero, G., Cinti, F., Brunetti, M., Nista, E. C., Gasbarrini, A., Alfieri, S., Pontecorvi, A., et al. (2023) · Molecular Metabolism · doi:10.1016/j.molmet.2023.101754 · Cited by 19
Liu, Z., Yokoyama, N. N., Blair, C. A., Li, X., Avizonis, D. Z., Wu, X., Uchio, E., Youssef, R. F., McClelland, M., Pollak, M., et al. (2016) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.mct-15-0714-t · Cited by 17
Denti, P., Bertoldo, A., Vicini, P., & Cobelli, C. (2009) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2009.2020171 · Cited by 18
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Gandhi, G. Y., & Mooradian, A. D. (2021) · Drugs & Aging · doi:10.1007/s40266-021-00910-1 · Cited by 18
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Janssens, G. E., Grevendonk, L., Schomakers, B. V., Perez, R. Z., van Weeghel, M., Schrauwen, P., Hoeks, J., & Houtkooper, R. H. (2023) · GeroScience · doi:10.1007/s11357-023-00827-0 · Cited by 15
Responsiveness of the innate immune system and glucose concentrations in the oldest old
Wijsman, C. A., Mooijaart, S. P., Westendorp, R. G. J., & Maier, A. B. (2011) · AGE · doi:10.1007/s11357-011-9292-7 · Cited by 16
Ross, M., Lithgow, H., Hayes, L. D., & Florida-James, G. D. (2019) · Sub-cellular biochemistry/Subcellular biochemistry · doi:10.1007/978-981-13-3681-2_12 · Cited by 16
Kashima, S., Inoue, K., & Matsumoto, M. (2021) · Scientific Reports · doi:10.1038/s41598-021-94441-9 · Cited by 18
Insulin Minimal Model Indexes and Secretion: Proper Handling of Uncertainty by a Bayesian Approach
Magni, P., Sparacino, G., Bellazzi, R., TOFFOLO, G. M., & Cobelli, C. (2004) · Annals of Biomedical Engineering · doi:10.1023/b:abme.0000032465.75888.91 · Cited by 16
Self-citationTresguerres, J. A. F., Cuesta‐Sancho, S., Kireev, R. A., Garcı́a, C., Acuña-Castroviejo, D., & Vara, E. (2013) · Hormone Molecular Biology and Clinical Investigation · doi:10.1515/hmbci-2013-0041 · Cited by 16
Schelp, A. O., Mendes-Chiloff, C. L., Paduan, V. C., Corrente, J. E., Vieira, A., Marchette, J. C. N., de Souza, J. T., Luvizutto, G. J., Nogueira, C. R., & Bazán, R. (2017) · Clinical Nutrition ESPEN · doi:10.1016/j.clnesp.2017.03.006 · Cited by 16
Park, H. B., Gwark, J.-Y., Jung, J., & Jeong, S. (2022) · Journal of Shoulder and Elbow Surgery · doi:10.1016/j.jse.2022.03.003 · Cited by 15
Singh, J., Jackson, K. L., Tang, F. S., Fu, T., Nowell, C. J., Salimova, E., Kiriazis, H., Ritchie, R. H., Head, G. A., Woodman, O. L., et al. (2024) · The FASEB Journal · doi:10.1096/fj.202301802r · Cited by 17
Clinical and Epidemiological Characteristics of Diabetic Ketoacidosis in Older Adults
Schwarzfuchs, D., Rabaev, E., Sagy, I., Zimhony‐Nissim, N., Lipnitzki, I., Musa, H., Jotkowitz, A., Brandstaetter, E., & Barski, L. (2020) · Journal of the American Geriatrics Society · doi:10.1111/jgs.16376 · Cited by 15
Choi, Y. S., Cho, B. W., Kim, H. J., Lee, Y. S., Park, K. K., & Lee, B. (2022) · Journal of the American Academy of Orthopaedic Surgeons · doi:10.5435/jaaos-d-21-00656 · Cited by 15
Age and Its Association with Low Insulin and High Amyloid-β Peptides in Blood
Li, H., Zhu, H., Wallack, M., Mwamburi, M., Abdul‐Hay, S. O., Leissring, M. A., & Qiu, W. Q. (2015) · Journal of Alzheimer s Disease · doi:10.3233/jad-150428 · Cited by 14
Komada, H., Sakaguchi, K., Takeda, K., Hirota, Y., Hashimoto, N., Okuno, Y., Seino, S., & Ogawa, W. (2011) · Journal of Diabetes Investigation · doi:10.1111/j.2040-1124.2010.00099.x · Cited by 14
Espinoza, S. E., Wang, C.-P., Tripathy, D., Clement, S. C., Schwenke, D. C., Banerji, M. A., Bray, G. A., Buchanan, T. A., Henry, R. R., Kitabchi, A. E., et al. (2016) · AGE · doi:10.1007/s11357-016-9946-6 · Cited by 14
Liu, Y., Guo, H., Wang, Q., Chen, J., Xuan, Y., Xu, J., Liu, Y., Sun, K., Gao, Q., Sun, Z., et al. (2021) · Primary care diabetes · doi:10.1016/j.pcd.2021.12.009 · Cited by 15
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Drigo, R. A. E., Erikson, G. A., Tyagi, S., Capitanio, J. S., Lyon, J. G., Spigelman, A. F., Bautista, A., Fox, J. E. M., Shokhirev, M., MacDonald, P. E., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/729541 · Cited by 14
Leblond, F., Nguyen, A. Q., Bolduc, V., Lambert, J., Yu, C., Duquette, N., & Thorin, É. (2013) · Pflügers Archiv - European Journal of Physiology · doi:10.1007/s00424-012-1206-8 · Cited by 13
Kashiwagi-Takayama, R., Iwahashi, H., Yamada, Y., Sakaue, T., Okita, T., Kawachi, Y., Iwamoto, R., Saisho, K., Tamba, S., Yamamoto, K., et al. (2017) · Endocrine Journal · doi:10.1507/endocrj.ej17-0113 · Cited by 13
Elzinga, S. E., Koubek, E. J., Hayes, J. M., Carter, A., Mendelson, F. E., Webber‐Davis, I. F., Lentz, S. I., & Feldman, E. L. (2023) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2023.1167688 · Cited by 12
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Jin, X., Lai, C. T., Perrella, S. L., McEachran, J. L., Gridneva, Z., & Geddes, D. T. (2024) · Nutrients · doi:10.3390/nu16172854 · Cited by 12
Lajara, R., Aguilar, R. B., Hehnke, U., Woerle, H., & von Eynatten, M. (2014) · Clinical Therapeutics · doi:10.1016/j.clinthera.2014.07.020 · Cited by 12
Metabolic profile of first and second generation antipsychotics among Chinese patients
Lee, E. H. M., Chow, L.-Y., & Leung, C. M. (2010) · Psychiatry Research · doi:10.1016/j.psychres.2010.04.050 · Cited by 12
Shi, M., Ellingsen, Ø., Bathen, T. F., Høydal, M. A., Koch, L. G., Britton, S. L., Wisløff, U., Stølen, T., & Esmaeili, M. (2018) · PLoS ONE · doi:10.1371/journal.pone.0208703 · Cited by 13
Comparison of inducible nitric oxide synthase activity in pancreatic islets of young and aged rats.
Farrokhfall, K., Hashtroudi, M. S., Ghasemi, A., & Mehrani, H. A. (2015) · Europe PMC (PubMed Central) · Cited by 12
Meynial‐Denis, D., Miri, A., Biélicki, G., Mignon, M., Renou, J. P., & Grizard, J. (2005) · The Journal of Nutritional Biochemistry · doi:10.1016/j.jnutbio.2004.12.001 · Cited by 12
Toth, M. J., Cooper, B. C., Pratley, R. E., Mari, A., Matthews, D. E., & Casson, P. R. (2008) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.00789.2007 · Cited by 12
Age-associated changes in pancreatic exocrine secretion of the isolated perfused rat pancreas
Jiang, Z.-E., Jiang, C.-Z., Chen, B., Koh, C. S., Yong, J., Park, D.-H., Won, M., & Lee, Y.-L. (2013) · Laboratory Animal Research · doi:10.5625/lar.2013.29.1.19 · Cited by 12
Shin, D., Eom, Y. S., Chon, S., Kim, B.-J., Yu, K., & Lee, D. H. (2019) · Diabetes Metabolic Syndrome and Obesity · doi:10.2147/dmso.s195350 · Cited by 11
Takino, K., Kameshima, M., Asai, C., Kawamura, I., Tomita, S., Sato, H., Hirakawa, A., & Yamada, S. (2022) · Annals of Physical and Rehabilitation Medicine · doi:10.1016/j.rehab.2022.101659 · Cited by 11
The Association between the Serum C-Peptide Level and Bone Mineral Density
Li, Y., Liu, H., & Sato, Y. (2013) · PLoS ONE · doi:10.1371/journal.pone.0083107 · Cited by 11
Tatsumi, Y., Ohno, Y., Morimoto, A., Nishigaki, Y., Mizuno, S., & Watanabe, S. (2012) · Obesity Research & Clinical Practice · doi:10.1016/j.orcp.2012.05.001 · Cited by 13
Impact of the PPAR gamma-2 gene polymorphisms on the metabolic state of postmenopausal women
Grygiel‐Górniak, B., Mosor, M., Marcinkowska, J., Przysławski, J., & Nowak, J. (2016) · Journal of Biosciences · doi:10.1007/s12038-016-9633-x · Cited by 11
Stephens, F. B., & Tsintzas, K. (2018) · Biochemical Society Transactions · doi:10.1042/bst20170198 · Cited by 11
Vedantham, S., Kluever, A.-K., & Deindl, E. (2018) · Cells · doi:10.3390/cells7100181 · Cited by 11
Cooper, B. C., Sites, C. K., Casson, P. R., & Toth, M. J. (2007) · Fertility and Sterility · doi:10.1016/j.fertnstert.2006.11.045 · Cited by 11
Kobza, V. M., Fleet, J. C., Zhou, J., Conley, T. B., Peacock, M., IglayReger, H. B., DePalma, G., & Campbell, W. W. (2013) · Nutrition Research · doi:10.1016/j.nutres.2013.03.005 · Cited by 11
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Umegaki, H., Haimoto, H., Ishikawa, J., & Kario, K. (2008) · Journal of the American Geriatrics Society · doi:10.1111/j.1532-5415.2008.01730.x · Cited by 11
Idrees, T., Zabala, Z. E., Moreno, E. M., Gerges, A., Urrutia, M. A., Ruíz, J. G., Vaughan, C. P., Vellanki, P., Pasquel, F. J., Peng, L., et al. (2023) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2023.110603 · Cited by 9
Wang, Y., Cheng, T., Zhang, T., Guo, R., Ma, H., & Zhao, W. G. (2025) · Frontiers in Endocrinology · doi:10.3389/fendo.2025.1598171 · Cited by 12
Age-related differences in water and sodium handling after commercial hydration beverage ingestion
Wolf, S. T., Stanhewicz, A. E., Clarke, M. M., Cheuvront, S. N., Kenefick, R. W., & Kenney, W. L. (2019) · Journal of Applied Physiology · doi:10.1152/japplphysiol.01094.2018 · Cited by 10
Wu, W., Diao, J., Yang, J., Sun, D., Wang, Y., Ni, Z., Yang, F., Tan, X., Li, L., & Li, L. (2021) · International Journal of Hypertension · doi:10.1155/2021/4514871 · Cited by 10
Liu, T., Wang, Y., Zhao, M., Jiang, J., Li, T., & Zhang, M. (2022) · Frontiers in Endocrinology · doi:10.3389/fendo.2022.992827 · Cited by 10
Solís, A. J. D., Fernández‐Agulló, T., Frutos, M. G.-S., Perez‐Pardo, P., Bogónez, E., Andrés, A., Ros, M., & Carrascosa, J. M. (2012) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2012.03.006 · Cited by 12
Ikee, R., Honda, K., Ishioka, K., Oka, M., Maesato, K., Moriya, H., Hidaka, S., Ohtake, T., & Kobayashi, S. (2010) · Hypertension Research · doi:10.1038/hr.2010.22 · Cited by 10
Naito, H., Kaga, H., Someya, Y., Tabata, H., Kakehi, S., Tajima, T., Ito, N., Yamasaki, N., Sato, M., Kadowaki, S., et al. (2023) · Journal of the Endocrine Society · doi:10.1210/jendso/bvad164 · Cited by 10
Nielsen, B. U., Mathiesen, I. H. M., Krogh‐Madsen, R., Katzenstein, T. L., Pressler, T., Shaw, J., Rickels, M. R., Almdal, T., Faurholt‐Jepsen, D., & Stefanovski, D. (2024) · Diabetologia · doi:10.1007/s00125-024-06220-6 · Cited by 10
Burattini, R., Morettini, M., Nardo, F. D., & Boemi, M. (2011) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-011-0760-0 · Cited by 9
Önal, A. (2019) · IntechOpen eBooks · doi:10.5772/intechopen.73958 · Cited by 9
Bonadonna, R. C., Mauricio, D., Müller‐Wieland, D., Freemantle, N., Bigot, G., Mauquoi, C., Ciocca, A., Bonnemaire, M., & Gourdy, P. (2021) · Diabetes Therapy · doi:10.1007/s13300-021-01030-0 · Cited by 9
Sejooti, S. S., Naher, S., Hoque, M. M., Zaman, M. S., & Rashid, H.-M. (2018) · Diabetes & Metabolic Syndrome Clinical Research & Reviews · doi:10.1016/j.dsx.2018.08.022 · Cited by 9
Viskochil, R. H., Blankenship, J. M., Makari‐Judson, G., STAUDENMAYER, J. W., Freedson, P. S., Hankinson, S. E., & Braun, B. (2019) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgz213 · Cited by 10
Khalafi, M., Symonds, M. E., Ghasemi, F., Rosenkranz, S. K., Rohani, H., & Sakhaei, M. H. (2023) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2023.110741 · Cited by 10
Jin, X., Lai, C. T., Perrella, S. L., Gridneva, Z., McEachran, J. L., Hassan, G. M., Taylor, N. L., & Geddes, D. T. (2025) · Nutrients · doi:10.3390/nu17223524 · Cited by 9
Garg, P. K., Biggs, M. L., Kizer, J. R., Shah, S. J., Psaty, B. M., Carnethon, M. R., Gottdiener, J. S., Siscovick, D. S., & Mukamal, K. J. (2022) · Cardiovascular Diabetology · doi:10.1186/s12933-022-01547-z · Cited by 8
Effect of Vietnamese Common Diet on Postprandial Blood Glucose Level in Adult Females
Pei-Ying, L. I. N., Nhung, B. T., Khẩn, N. C., Sarukura, N., Kunii, D., Sakai, T., Kassu, A., & Yamamoto, S. (2007) · Journal of Nutritional Science and Vitaminology · doi:10.3177/jnsv.53.247 · Cited by 8
Ghachem, A., Brochu, M., & Dionne, I. J. (2019) · Therapeutic Advances in Chronic Disease · doi:10.1177/2040622319854239 · Cited by 8
Tomimaru, Y., Kobayashi, S., Ito, T., Iwagami, Y., Yamada, D., Akita, H., Noda, T., Gotoh, K., Kenmochi, T., Doki, Y., et al. (2021) · Pancreatology · doi:10.1016/j.pan.2021.01.002 · Cited by 8
Oesterle, A., Bůžková, P., Pellegrini, C. N., Hirsch, C. H., Tracy, R. P., Siscovick, D. S., Djoussé, L., Mukamal, K. J., & Kizer, J. R. (2022) · The Journals of Gerontology Series A · doi:10.1093/gerona/glac229 · Cited by 8
Halter, J. B. (2010) · Elsevier eBooks · doi:10.1016/b978-0-12-378638-8.00017-8 · Cited by 8
Insulin resistance in hypertension quantified by oral glucose tolerance test: comparison of methods
Nardo, F. D., Casagrande, F., Boemi, M., Fumelli, P., Morosini, P., & Burattini, R. (2006) · Metabolism · doi:10.1016/j.metabol.2005.08.006 · Cited by 8
Stedman, M., Heald, A. H., Holland, D., Halsall, I., Green, L., Wu, P., Patel, K. A., Scargill, J., Gibson, M., Hanna, F., et al. (2024) · Diabetes Therapy · doi:10.1007/s13300-024-01680-w · Cited by 7
Milk Composition Is Predictive of Low Milk Supply Using Machine Learning Approaches
Jin, X., Lai, C. T., Perrella, S. L., Zhou, X., Hassan, G. M., McEachran, J. L., Gridneva, Z., Taylor, N. L., Wlodek, M. E., & Geddes, D. T. (2025) · Diagnostics · doi:10.3390/diagnostics15020191 · Cited by 7
Methods to Assess In Vivo Insulin Sensitivity and Insulin Secretion
Bonadonna, R. C., Boselli, L., Dei, A., & Trombetta, M. (2018) · Endocrinology · doi:10.1007/978-3-319-27317-4_11-1 · Cited by 8
Errors in measuring plasma free fatty acid concentrations with a popular enzymatic colorimetric kit
Song, Y., Zhou, L., & Jensen, M. D. (2019) · Clinical Biochemistry · doi:10.1016/j.clinbiochem.2019.01.008 · Cited by 7
Self-citationMcFadden, S., Sime, L. N., Cox, M. F., Findley, C. A., Peck, M. R., Quinn, K., Fang, Y., Bartke, A., Hascup, E. R., & Hascup, K. N. (2022) · The Journals of Gerontology Series A · doi:10.1093/gerona/glac223 · Cited by 7
Wang, C., Wu, C., Chen, F.-Y., Pei, D., & Huang, L.-Y. (2023) · Journal of the Chinese Medical Association · doi:10.1097/jcma.0000000000000976 · Cited by 7
Eizadi, M., Bagheri, G., Kasparast, J. M., Zahedmanesh, F., & Afsharmand, Z. (2012) · Science & Sports · doi:10.1016/j.scispo.2012.01.001 · Cited by 7
Someya, Y., Tamura, Y., Kohmura, Y., Aoki, K., Kawai, S., & Daida, H. (2017) · The Journal of Physical Fitness and Sports Medicine · doi:10.7600/jpfsm.6.167 · Cited by 7
Probing β-Cell Biology in Space and Time
Drigo, R. A. E. (2021) · Diabetes · doi:10.2337/dbi21-0008 · Cited by 6
Herpich, C., Kochlik, B., Weber, D., Ott, C., Grune, T., Norman, K., & Raupbach, J. (2021) · The Journals of Gerontology Series A · doi:10.1093/gerona/glab331 · Cited by 7
Metadata
- Authors
- Basu, R., Breda, E., Oberg, A. L., Powell, C. C., Dalla Man, C., Basu, A., Vittone, J. L., Klee, G. G., Arora, P., Jensen, M. D., Toffolo, G., Cobelli, C., & Rizza, R. A.
- Affiliations
- Mayo Clinic (US)
- University of Padua (IT)
- Department of Information Engineering, University of Padua, Padua, Italy
- ORCID
- Venue
- Diabetes
- Publisher
- American Diabetes Association
- Published
- 2003-07-01
- Volume
- 52
- Issue
- 7
- Pages
- 1738-1748
- ISSN
- 0012-1797 (ISSN-L)
- 1939-327X
- OpenAlex
- W2139834641
- Semantic Scholar
- d8e228956833647e46e0380931e47b93ca54183f
- Cited by
- 440
- References
- 58
- Citations by year
- 2026: 8 · 2025: 23 · 2024: 22 · 2023: 17 · 2022: 23 · 2021: 27 · 2020: 19 · 2019: 22 · 2018: 17 · 2017: 14 · 2016: 24 · 2015: 18 · 2014: 16 · 2013: 26 · 2012: 22
- FWCI
- 15.38
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Diabetes (publishedVersion)
- PubMed (publishedVersion)
- Padua Research Archive (University of Padova) (submittedVersion)
- Funders
- American Diabetes Association
- Mayo Foundation for Medical Education and Research
- Novo Nordisk
- U.S. Public Health Service (RR-00585)
- National Institute on Aging (AG14383, P01AG014383)
- National Institute of Biomedical Imaging and Bioengineering (P41EB001975)
- National Center for Research Resources (RR-00585, M01RR000585)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Pancreatic function and diabetes
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
- Keywords
- insulin resistance, insulin secretion, beta-cell function, postprandial glycemic response, hepatic insulin clearance, fat mass, visceral fat, older adults, glucose tolerance test
- MeSH terms
- Insulin Secretion, Adult, Aged, Aging, Blood Glucose, C-Peptide, Eating, Fatty Acids, Nonesterified, Glucagon, Glucose, Glucose Tolerance Test, Humans, Hydrocortisone, Insulin, Body Mass Index, Palmitic Acid, Dehydroepiandrosterone Sulfate, Human Growth Hormone
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