Supplementary MaterialsAdditional file 1 ROI data and corresponding Patlak plots from FDG-PET scans in each one of the 11 tumor models A to K discussed in the written text (see Desk ?Table11). rate continuous NVP-AUY922 small molecule kinase inhibitor is noticed (sampled) in a glucose range between 60 and 140. We remember that when em K /em i can be observed in a restricted range around some glucose midpoint [ em m.glc /em ], em K /em we ( em V /em max/( em K /em m + [ em m.glc /em ])+([ em m.glc /em ] em V /em max)/( em K /em m + [ em m.glc /em ])2)- em V /em max/( em K /em m + [ em m.glc /em ])2[ em glc /em ] + em /em , we.electronic., em K /em i is around linear in [ em glc /em ]. The remaining panel in Shape ?Figure99 shows 400 simulated observations drawn from a MM model with em Rabbit Polyclonal to DRD1 V /em max = 40, em K /em m = 100, = .025, where glucose was randomly sampled from a Gaussian distribution with a mean of 100 and a typical deviation of 15. As is seen, in the sampled range, em K /em i can be around linear in [ em glc /em ]. The proper panel displays a scatter plot of [ em glc /em ] versus. em MRgluc /em . In keeping with our derivations, the sample correlations in both plots are -.48 and .53, respectively. For the selected parameter NVP-AUY922 small molecule kinase inhibitor options NVP-AUY922 small molecule kinase inhibitor and glucose distribution, predicated on the above arguments, the sample correlation between [ em glc /em ] and em MRgluc /em ought to be close to its theoretically predicted worth of .51. (Because of this data, the sample correlation between [ em glc /em ] and em MRglucMAX /em = em K /em i( em K /em m + [ em glc /em ]) can be .01.) Open up in another window Figure 9 Scatter plots of [ em glc /em ] versus. em K /em i (remaining) and [ em glc /em ] versus. em MRgluc /em (correct). The remaining panel also displays the underlying MM procedure (dashed black range) that the info was sampled, along with theoretical (reddish colored solid) and installed (dark solid) regression lines. Competing passions The authors declare they have no competing interests. Authors’ contributions S-PW designed the studies and wrote the manuscript, JEF-M programmed the data analyses and prepared the figures, REP guided the discussion, and TB guided the data analysis and statistics. All authors read and approved the final manuscript. Supplementary Material Additional file 1:ROI data and corresponding Patlak plots from FDG-PET scans in NVP-AUY922 small molecule kinase inhibitor each of the 11 tumor models A to K discussed in the text (see Table ?Table11). In each plot, the data from one cohort ( em n /em = 14 to 36) of essentially identical mice are superimposed. Left, in red: the liver-derived input function; center, in blue: the tumor; right, in gray: the Patlak plot. Click here for file(458K, PDF) Additional file 2:Confidence intervals for correlations between PET metrics and blood glucose. To obtain the 95% confidence limits for Pearson’s correlation coefficient ( em r /em ), the Fisher transformation was applied to the sample correlation coefficients. Click here for file(128K, PDF) Acknowledgements The authors gratefully acknowledge the contributions of Annie Ogasawara, Alex Vanderbilt, Jeff Tinianow, Herman Gill, Leanne McFarland, and Karissa Peth who helped execute the imaging studies analyzed here..