Hostname: page-component-84b7d79bbc-fnpn6 Total loading time: 0 Render date: 2024-07-31T22:43:45.317Z Has data issue: false hasContentIssue false
  • English
  • Français

Total body glucose metabolism in the conscious, unrestrained piglet and its relation to body- and organ weight

Published online by Cambridge University Press:  09 March 2007

P. A. Flecknell ,
R. Wootton  and
Muriel John
P. A. Flecknell
Affiliation:
Division of Comparative Medicine andClinical Research Centre, Watford Road, Harrow, HAI 3UJ
R. Wootton
Affiliation:
Division of Radioisotopes, Clinical Research Centre, Watford Road, Harrow, HAI 3UJ
Muriel John
Affiliation:
Division of Comparative Medicine andClinical Research Centre, Watford Road, Harrow, HAI 3UJ
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

1. Neonatal hypoglycaemia is a relatively common clinical problem in children but ethical constraints limit the investigations that may be made in the newborn.

2. As a preliminary step to assess the suitability of the piglet as a model for glucose metabolism in man, whole-body glucose turnover and glucose pool size were measured using [2-3H]glucose in forty piglets from ten litters.

3. Glucose pool size was linearly related to brain weight. However, multiple regression showed that the most useful predictors of pool size were body-weight and resting plasma glucose concentration.

4. Glucose turnover was related to both brain weight and body-weight alone, but multiple regression showed that better predictors of turnover were liver weight, spleen weight and pancreas weight.

5. Similarities between our own results in piglets and those obtained in human neonates by Bier et al. (1977) extend not only to glucose turnover, but also to its relationship with body-and brain weight. These findings suggest that the piglet may be a useful model for the study of glucose metabolism in babies.

Type
Papers on General Nutrition
Information
British Journal of Nutrition , Volume 44 , Issue 2 , September 1980 , pp. 193 - 203
Copyright
Copyright © The Nutrition Society 1980

References

REFERENCES

Bier, D. M., Leake, R. D., Haymond, M. W., Arnold, K. J., Gruenke, L. D., Sperling, M. A. & Kipnis, D. M. (1977). Diabetes 26, 1016.CrossRefGoogle Scholar
Cowett, R. M., Susa, J. B., Oh, W. & Schwartz, R. (1976). Pediat. Res. 10, 407.Google Scholar
Davies, O. L. & Goldsmith, P. L. (Eds.) (1977). Statisticol methods in research and producrion. London: Longman.Google Scholar
Draper, N. R. & Smith, H. (1966). Applied regression analysis. London: Wiley.Google Scholar
Dunn, A., Chenoweth, M. & Schaeffer, L. D. (1967). Biochemistry 6, 6.CrossRefGoogle Scholar
Dunn, A., Katz, J., Golden, S. & Chenoweth, M. (1976). Am. J. Physiol. 230, 1159.CrossRefGoogle Scholar
Flecknell, P. A. (1979). J. Physiol., Lond. 29, 19.Google Scholar
Freeman, C. P., Noakes, D. E. & Annison, E. F. (1970). Br. J. Nutr. 24, 705.CrossRefGoogle Scholar
Goodwin, R. F. W. (1957). J. Physiol., Lond. 136, 208.CrossRefGoogle Scholar
Hetenyi, G., Varma, S. & Cowan, J. S. (1972). Br. med. J. ii, 625.CrossRefGoogle Scholar
Issekutz, B., Allen, M. & Borkov, I. (1972). Am. J. Physiol. 222, 710.CrossRefGoogle Scholar
Judson, G. J. & Leng, R. A. (1972). Aust. J. biol. Sci. 25, 1313.CrossRefGoogle Scholar
Katz, J. & Dunn, A. (1967). Biochemistry, 6, I.Google Scholar
Katz, J., Dunn, A., Chenoweth, M. & Golden, S. (1974). Biochem. J. 142, 171.CrossRefGoogle Scholar
Kornhauser, D., Adam, P. A. J. & Schwartz, R. (1970). Pediat. Res 4, 120.CrossRefGoogle Scholar
Meyer, J. A., Briskey, E. J., Hoekstra, W. G. & Bray, R. W. (1962). J. Anim. Sci. 21, 543.CrossRefGoogle Scholar
Mount, L. E. (1959). J. Physiol., Lond. 147, 333.CrossRefGoogle Scholar
Nelder, J. A. & Mead, R. (1965). Computer J. 7, 308.CrossRefGoogle Scholar
Oh, W. (1977). Clin. Obstet. Gynec. 20, 991.CrossRefGoogle Scholar
Royal Statistical Society (1978). The GLIM System, release 3: Numerical Algorithms Group, Oxford: Royal Statistical Society.Google Scholar
Segal, S., Berman, M. & Blair, A. (1961). J. clin. Invest. 40, 1263.CrossRefGoogle Scholar
Sherwood, W. G., Hill, D. E. & Chance, G. W. (1976). Pediat. Res. 10, 414.Google Scholar
Somogyi, M. J. (1945). J. biol. Chem. 160, 69.CrossRefGoogle Scholar