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      Determining insulin sensitivity from glucose tolerance tests in Iberian and landrace pigs

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          Abstract

          As insulin sensitivity may help to explain divergences in growth and body composition between native and modern breeds, metabolic responses to glucose infusion were measured using an intra-arterial glucose tolerance test (IAGTT). Iberian ( n = 4) and Landrace ( n = 5) barrows (47.0 ± 1.2 kg body weight (BW)), fitted with a permanent carotid artery catheter were injected with glucose (500 mg/kg BW) and blood samples collected at -10, 0, 5, 10, 15, 20, 25, 30, 45, 60, 90, 120 and 180 min following glucose infusion. Plasma samples were analysed for insulin, glucose, lactate, triglycerides, cholesterol, creatinine, albumin and urea. Insulin sensitivity indices were calculated and analysed. Mean plasma glucose, creatinine and cholesterol concentrations were lower ( P < 0.01) in Iberian (14, 68 and 22%, respectively) than in Landrace pigs during the IAGTT. However, mean plasma insulin, lactate, triglycerides and urea concentrations were greater ( P < 0.001) in Iberian (50, 35, 18 and 23%, respectively) than in Landrace pigs. Iberian pigs had larger area under the curve (AUC) of insulin ( P < 0.05) or tended to a greater AUC of lactate ( P < 0.10), and a smaller ( P < 0.05) AUC for glucose 0-60 min compared with Landrace pigs. Indices for estimating insulin sensitivity in fasting conditions indicated improved β-cell function in Iberian compared with Landrace pigs, but no difference ( P > 0.10) in calculated insulin sensitivity index was found after IAGTT between breeds. A time response ( P < 0.05) was obtained for insulin, glucose and lactate so that maximum concentration was achieved at 10 and 15 min post-infusion for insulin (Iberian and Landrace pigs, respectively), immediately post-infusion for glucose, and 20 min post-infusion for lactate, decreasing thereafter until basal levels. There was no time effect for the rest of metabolites evaluated. In conclusion, growing Iberian pigs challenged with an IAGTT showed changes in biochemical parameters and insulin response that may indicate an early stage of insulin resistance.

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          G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences

          G*Power (Erdfelder, Faul, & Buchner, 1996) was designed as a general stand-alone power analysis program for statistical tests commonly used in social and behavioral research. G*Power 3 is a major extension of, and improvement over, the previous versions. It runs on widely used computer platforms (i.e., Windows XP, Windows Vista, and Mac OS X 10.4) and covers many different statistical tests of the t, F, and chi2 test families. In addition, it includes power analyses for z tests and some exact tests. G*Power 3 provides improved effect size calculators and graphic options, supports both distribution-based and design-based input modes, and offers all types of power analyses in which users might be interested. Like its predecessors, G*Power 3 is free.
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            Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man.

            The steady-state basal plasma glucose and insulin concentrations are determined by their interaction in a feedback loop. A computer-solved model has been used to predict the homeostatic concentrations which arise from varying degrees beta-cell deficiency and insulin resistance. Comparison of a patient's fasting values with the model's predictions allows a quantitative assessment of the contributions of insulin resistance and deficient beta-cell function to the fasting hyperglycaemia (homeostasis model assessment, HOMA). The accuracy and precision of the estimate have been determined by comparison with independent measures of insulin resistance and beta-cell function using hyperglycaemic and euglycaemic clamps and an intravenous glucose tolerance test. The estimate of insulin resistance obtained by homeostasis model assessment correlated with estimates obtained by use of the euglycaemic clamp (Rs = 0.88, p less than 0.0001), the fasting insulin concentration (Rs = 0.81, p less than 0.0001), and the hyperglycaemic clamp, (Rs = 0.69, p less than 0.01). There was no correlation with any aspect of insulin-receptor binding. The estimate of deficient beta-cell function obtained by homeostasis model assessment correlated with that derived using the hyperglycaemic clamp (Rs = 0.61, p less than 0.01) and with the estimate from the intravenous glucose tolerance test (Rs = 0.64, p less than 0.05). The low precision of the estimates from the model (coefficients of variation: 31% for insulin resistance and 32% for beta-cell deficit) limits its use, but the correlation of the model's estimates with patient data accords with the hypothesis that basal glucose and insulin interactions are largely determined by a simple feed back loop.
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              Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans.

              Insulin resistance plays an important role in the pathophysiology of diabetes and is associated with obesity and other cardiovascular risk factors. The "gold standard" glucose clamp and minimal model analysis are two established methods for determining insulin sensitivity in vivo, but neither is easily implemented in large studies. Thus, it is of interest to develop a simple, accurate method for assessing insulin sensitivity that is useful for clinical investigations. We performed both hyperinsulinemic isoglycemic glucose clamp and insulin-modified frequently sampled iv glucose tolerance tests on 28 nonobese, 13 obese, and 15 type 2 diabetic subjects. We obtained correlations between indexes of insulin sensitivity from glucose clamp studies (SI(Clamp)) and minimal model analysis (SI(MM)) that were comparable to previous reports (r = 0.57). We performed a sensitivity analysis on our data and discovered that physiological steady state values [i.e. fasting insulin (I(0)) and glucose (G(0))] contain critical information about insulin sensitivity. We defined a quantitative insulin sensitivity check index (QUICKI = 1/[log(I(0)) + log(G(0))]) that has substantially better correlation with SI(Clamp) (r = 0.78) than the correlation we observed between SI(MM) and SI(Clamp). Moreover, we observed a comparable overall correlation between QUICKI and SI(Clamp) in a totally independent group of 21 obese and 14 nonobese subjects from another institution. We conclude that QUICKI is an index of insulin sensitivity obtained from a fasting blood sample that may be useful for clinical research.
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                peerj
                peerj
                PeerJ
                PeerJ Inc. (San Diego, USA )
                2167-8359
                10 March 2021
                2021
                : 9
                : e11014
                Affiliations
                [1 ]Départment Sciences Agronomiques et Animales, Institut Polytechnique LaSalle Beauvais , Beauvais, France
                [2 ]Department of Physiology and Biochemistry of Animal Nutrition, Estación Experimental del Zaidín, Consejo Superior de Investigaciones Científicas , Granada, Spain
                Article
                11014
                10.7717/peerj.11014
                7955676
                33854837
                e9571bb5-a63b-4bc6-97d4-df826ee8a0ca
                ©2021 Rodríguez-López et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 13 November 2020
                : 5 February 2021
                Funding
                Funded by: Ministerio de Educación y Ciencia (Spain) and RECUPERA 2020, FEDER
                Award ID: AGL 2006-05937/GAN
                Award ID: AGL 2009-08916
                This research was supported by grants no. AGL 2006-05937/GAN and AGL 2009-08916 from Ministerio de Educación y Ciencia (Spain) and RECUPERA 2020, FEDER funding). There was no additional external funding received for this study. The publication fee was supported by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Agricultural Science
                Biochemistry
                Zoology

                insulin resistance,metabolism,obesity,fatty pig,lean pig
                insulin resistance, metabolism, obesity, fatty pig, lean pig

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