| Records |
| Author |
Lee, R.D. |
| Title |
Rethinking the evolutionary theory of aging: transfers, not births, shape senescence in social species |
Type |
Journal Article |
| Year |
2003 |
Publication |
Proceedings of the National Academy of Sciences of the United States of America |
Abbreviated Journal |
Proc Natl Acad Sci U S A |
| Volume |
100 |
Issue |
16 |
Pages  |
9637-9642 |
| Keywords |
Adaptation, Physiological; *Aging; Animals; *Biological Evolution; Demography; Economics; Environment; Fertility; Humans; Life Expectancy; Longevity; Models, Theoretical; Parturition; Population Dynamics; Population Growth; Reproduction |
| Abstract |
The classic evolutionary theory of aging explains why mortality rises with age: as individuals grow older, less lifetime fertility remains, so continued survival contributes less to reproductive fitness. However, successful reproduction often involves intergenerational transfers as well as fertility. In the formal theory offered here, age-specific selective pressure on mortality depends on a weighted average of remaining fertility (the classic effect) and remaining intergenerational transfers to be made to others. For species at the optimal quantity-investment tradeoff for offspring, only the transfer effect shapes mortality, explaining postreproductive survival and why juvenile mortality declines with age. It also explains the evolution of lower fertility, longer life, and increased investments in offspring. |
| Address |
Department of Demography, University of California, 2232 Piedmont Avenue, Berkeley, CA 94720-2120, USA. rlee@demog.berkeley.edu |
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English |
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| ISSN |
0027-8424 |
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| Notes |
PMID:12878733 |
Approved |
no |
| Call Number |
Equine Behaviour @ team @ |
Serial |
5465 |
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| Author |
Newman, M.E.J. |
| Title |
Mixing patterns in networks |
Type |
Journal Article |
| Year |
2003 |
Publication |
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics |
Abbreviated Journal |
Phys Rev E Stat Nonlin Soft Matter Phys |
| Volume |
67 |
Issue |
2 Pt 2 |
Pages |
026126 |
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| Abstract |
We study assortative mixing in networks, the tendency for vertices in networks to be connected to other vertices that are like (or unlike) them in some way. We consider mixing according to discrete characteristics such as language or race in social networks and scalar characteristics such as age. As a special example of the latter we consider mixing according to vertex degree, i.e., according to the number of connections vertices have to other vertices: do gregarious people tend to associate with other gregarious people? We propose a number of measures of assortative mixing appropriate to the various mixing types, and apply them to a variety of real-world networks, showing that assortative mixing is a pervasive phenomenon found in many networks. We also propose several models of assortatively mixed networks, both analytic ones based on generating function methods, and numerical ones based on Monte Carlo graph generation techniques. We use these models to probe the properties of networks as their level of assortativity is varied. In the particular case of mixing by degree, we find strong variation with assortativity in the connectivity of the network and in the resilience of the network to the removal of vertices. |
| Address |
Department of Physics, University of Michigan, Ann Arbor, MI 48109-1120, USA |
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English |
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Edition |
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| ISSN |
1539-3755 |
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| Notes |
PMID:12636767 |
Approved |
no |
| Call Number |
Equine Behaviour @ team @ |
Serial |
5215 |
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| Author |
Gavrilova, O.; Haluzik, M.; Matsusue, K.; Cutson, J.J.; Johnson, L.; Dietz, K.R.; Nicol, C.J.; Vinson, C.; Gonzalez, F.J.; Reitman, M.L. |
| Title |
Liver peroxisome proliferator-activated receptor gamma contributes to hepatic steatosis, triglyceride clearance, and regulation of body fat mass |
Type |
Journal Article |
| Year |
2003 |
Publication |
The Journal of biological chemistry |
Abbreviated Journal |
J Biol Chem |
| Volume |
278 |
Issue |
36 |
Pages |
34268-34276 |
| Keywords |
Adipose Tissue/*metabolism; Animals; Blotting, Southern; Blotting, Western; Female; Hypoglycemia/genetics; Insulin Resistance/genetics; Lipid Metabolism; Liver/*metabolism; Liver Diseases/genetics/*metabolism; Male; Mice; Mice, Inbred C57BL; Mice, Knockout; Mice, Transgenic; RNA/metabolism; Receptors, Cytoplasmic and Nuclear/*genetics/*physiology; Recombination, Genetic; Thiazoles/pharmacology; *Thiazolidinediones; Time Factors; Transcription Factors/*genetics/*physiology; Triglycerides/*metabolism |
| Abstract |
Peroxisome proliferator-activated receptor gamma (PPAR gamma) is a nuclear receptor that mediates the antidiabetic effects of thiazolidinediones. PPAR gamma is present in adipose tissue and becomes elevated in fatty livers, but the roles of specific tissues in thiazolidinedione actions are unclear. We studied the function of liver PPAR gamma in both lipoatrophic A-ZIP/F-1 (AZIP) and wild type mice. In AZIP mice, ablation of liver PPAR gamma reduced the hepatic steatosis but worsened the hyperlipidemia, triglyceride clearance, and muscle insulin resistance. Inactivation of AZIP liver PPAR gamma also abolished the hypoglycemic and hypolipidemic effects of rosiglitazone, demonstrating that, in the absence of adipose tissue, the liver is a primary and major site of thiazolidinedione action. In contrast, rosiglitazone remained effective in non-lipoatrophic mice lacking liver PPAR gamma, suggesting that adipose tissue is the major site of thiazolidinedione action in typical mice with adipose tissue. Interestingly, mice without liver PPAR gamma, but with adipose tissue, developed relative fat intolerance, increased adiposity, hyperlipidemia, and insulin resistance. Thus, liver PPAR gamma regulates triglyceride homeostasis, contributing to hepatic steatosis, but protecting other tissues from triglyceride accumulation and insulin resistance. |
| Address |
Diabetes Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892, USA. oksanag@bdg10.niddk.nih.gov |
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English |
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| ISSN |
0021-9258 |
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| Notes |
PMID:12805374 |
Approved |
no |
| Call Number |
refbase @ user @ |
Serial |
81 |
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