The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Sex‐ and tissue‐specific changes in mTOR signaling with age in C57 BL /6J mice
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Higher mTORC1/S6K activity in muscle of older mice, rats and humans is associated with sarcopenia.
“Higher mTORC1/S6K activity in muscle of older mice, rats and humans is associated with sarcopenia 97–101, and in brain is associated with Alzheimer’s disease 101–105.”
From Targeting the biology of aging with mTOR inhibitors (2023) · cites this paper as [97]
The Results (page unavailable) report increased muscle S6 phosphorylation in older male mice and older rats, supporting an age-related increase in a readout of mTORC1 signaling. The increase was absent in female mice, and the paper does not link these measurements to sarcopenia or report corresponding human muscle findings. Its Discussion also cautions that muscle S6 and S6K1 readouts diverged after refeeding. (LLM, conf=0.88)
Experimental — accuracy not yet measuredAltered mTORC1 signaling with age has been reported in other tissues of mice, with most studies reporting increased mTORC1 activity with age.
“Altered mTORC1 signaling with age has also been reported in other tissues of mice, with most studies reporting increased mTORC1 activity with age 39,97,106–108.”
From Targeting the biology of aging with mTOR inhibitors (2023) · cites this paper as [97]
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Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
Mootha, V. K., Lindgren, C. M., Eriksson, K.-F., Subramanian, A., Sihag, S., Lehar, J., Puigserver, P., Carlsson, E., Ridderstråle, M., Laurila, E., et al. (2003) · Nature Genetics · doi:10.1038/ng1180 · Cited by 10,197
Ribosomal Protein S6 Kinase 1 Signaling Regulates Mammalian Life Span
Selman, C., Tullet, J. M. A., Wieser, D., Irvine, E., Lingard, S. J., Choudhury, A. I., Claret, M., Al-Qassab, H., Carmignac, D., Ramadani, F., et al. (2009) · Science · doi:10.1126/science.1177221 · Cited by 1,120 · cited 2×
“Mice lacking S6K1 or with decreased mTORC1 activity have extended lifespan, demonstrating that decreased mTORC1 signaling is sufficient to promote longevity, at least in females (Selman et al., 2009; Lamming et al., 2012).”
BackgroundBar-Peled, L., Chantranupong, L., Cherniack, A. D., Chen, W. W., Ottina, K. A., Grabiner, B. C., Spear, E. D., Carter, S. L., Meyerson, M., & Sabatini, D. M. (2013) · Science · doi:10.1126/science.1232044 · Cited by 1,080
Solon-Biet, S. M., McMahon, A. C., Ballard, J. W. O., Ruohonen, K., Wu, L. E., Cogger, V. C., Warren, A., Huang, X., Pichaud, N., Melvin, R. G., et al. (2014) · Cell Metabolism · doi:10.1016/j.cmet.2014.02.009 · Cited by 904
TOR Signaling and Rapamycin Influence Longevity by Regulating SKN-1/Nrf and DAF-16/FoxO
Robida-Stubbs, S., Glover-Cutter, K., Lamming, D. W., Mizunuma, M., Narasimhan, S. D., Neumann-Haefelin, E., Sabatini, D. M., & Blackwell, T. K. (2012) · Cell Metabolism · doi:10.1016/j.cmet.2012.04.007 · Cited by 648
Self-citationmTORC1 activation in podocytes is a critical step in the development of diabetic nephropathy in mice
Inoki, K., Mori, H., Wang, J., Suzuki, T., Hong, S., Yoshida, S., Blattner, S. M., Ikenoue, T., Rüegg, M. A., Hall, M. N., et al. (2011) · Journal of Clinical Investigation · doi:10.1172/jci44771 · Cited by 538
The metabolic footprint of aging in mice
Houtkooper, R. H., Argmann, C., Houten, S. M., Cantó, C., Jeninga, E. H., Andreux, P. A., Thomas, C., Doenlen, R., Schoonjans, K., & Auwerx, J. (2011) · Scientific Reports · doi:10.1038/srep00134 · Cited by 528
AGEMAP: A Gene Expression Database for Aging in Mice
Zahn, J. M., Poosala, S., Owen, A. B., Ingram, D. K., Lustig, A., Carter, A., Weeraratna, A. T., Taub, D. D., Gorospe, M., Mazan-Mamczarz, K., et al. (2007) · PLoS Genetics · doi:10.1371/journal.pgen.0030201 · Cited by 431
Ramos, F. J., Chen, S. C., Garelick, M. G., Dai, D.-F., Liao, C.-Y., Schreiber, K. H., MacKay, V. L., An, E. H., Strong, R., Ladiges, W. C., et al. (2012) · Science Translational Medicine · doi:10.1126/scitranslmed.3003802 · Cited by 349
TOR-Driven Aging: Speeding Car Without Brakes
Blagosklonny, M. V. (2009) · Cell Cycle · doi:10.4161/cc.8.24.10310 · Cited by 95 · cited 1×
“Alternatively, mTORC1 signaling may be optimal during development, but inappropriately high for the maintenance of health later in life, and rapamycin acts to repress this overactive mTORC1 signaling (Blagosklonny, 2009).”
BackgroundLamming, D. W., Cummings, N. E., Rastelli, A. L., Gao, F., Cava, E., Bertozzi, B., Spelta, F., Pili, R., & Fontana, L. (2015) · Oncotarget · doi:10.18632/oncotarget.5180 · Cited by 69
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Research works printed but not linked: 33
- 10.1016/S0002-9440(10)63687-5 · DOI · Paper page
- 10.1016/j.cmet.2009.11.010 · DOI · Paper page
- Calhoun C, 2015, Senescent Cells Contribute to the Physiological Remodeling of Aged Lungs, J. Gerontol. A Biol. Sci. Med. Sci.
- 10.1126/scitranslmed.3002346 · DOI · Paper page
- 10.1126/scisignal.2000559 · DOI · Paper page
- 10.1111/acel.12203 · DOI
- 10.1016/B978-012369454-6/50074-1 · DOI · Paper page
- 10.1371/journal.pone.0083988 · DOI
- 10.1158/2159-8290.CD-13-0929 · DOI
- 10.1016/j.mad.2012.07.003 · DOI
- 10.1186/2193-1801-3-735 · DOI · Paper page
- 10.1002/9780470015902.a0021316.pub2 · DOI
- 10.1126/science.1215135 · DOI · Paper page
- 10.1111/acel.12097 · DOI
- 10.1096/fj.13-237743 · DOI
- 10.1111/acel.12256 · DOI · Paper page
- 10.1016/j.cell.2012.03.017 · DOI · Paper page
- 10.4161/15384101.2014.949150 · DOI · Paper page
- 10.1111/j.1474-9726.2007.00319.x · DOI
- 10.1111/acel.12088 · DOI · Paper page
- 10.1093/gerona/glq178 · DOI · Paper page
- 10.1111/acel.12194 · DOI
- 10.1371/journal.pone.0069178 · DOI
- 10.1016/j.cmet.2008.06.011 · DOI · Paper page
- 10.1101/gad.1381406 · DOI · Paper page
- 10.1016/j.mad.2005.07.001 · DOI
- 10.1007/s00726-010-0615-2 · DOI
- 10.1016/j.molcel.2006.03.029 · DOI · Paper page
- 10.1111/acel.12313 · DOI
- 10.1038/nature09584 · DOI · Paper page
- 10.1093/gerona/54.11.B492 · DOI
- 10.1002/emmm.201303183 · DOI
- 10.1016/j.neuron.2012.03.043 · DOI · Paper page
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Autophagy as a promoter of longevity: insights from model organisms
Hansen, M., Rubinsztein, D. C., & Walker, D. W. (2018) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-018-0033-y · Cited by 754
The mechanistic target of rapamycin: the grand conducTOR of metabolism and aging
Kennedy, B. K., & Lamming, D. W. (2016) · Cell Metabolism · doi:10.1016/j.cmet.2016.05.009 · Cited by 544
Self-citationTargeting the biology of aging with mTOR inhibitors
Mannick, J. B., & Lamming, D. W. (2023) · Nature Aging · doi:10.1038/s43587-023-00416-y · Cited by 372
Self-citationNecroptosis contributes to chronic inflammation and fibrosis in aging liver
Mohammed, S., Thadathil, N., Selvarani, R., Nicklas, E. H., Wang, D., Miller, B. F., Richardson, A., & Deepa, S. S. (2021) · Aging Cell · doi:10.1111/acel.13512 · Cited by 192
Protein synthesis and quality control in aging
Anisimova, A. S., Alexandrov, A. I., Makarova, N. E., Gladyshev, V. N., & Dmitriev, S. E. (2018) · Aging · doi:10.18632/aging.101721 · Cited by 172
Metadata
- Authors
- Baar, E. L., Carbajal, K. A., Ong, I. M., & Lamming, D. W.
- Affiliations
- Department of Medicine University of Wisconsin‐Madison Madison WI USA
- Department of Biostatistics and Medical Informatics University of Wisconsin‐Madison Madison WI USA
- ORCID
- Lamming, Dudley W.
- Venue
- Aging Cell
- Publisher
- Wiley
- Published
- 2015-11-24
- Volume
- 15
- Issue
- 1
- Pages
- 155-166
- ISSN
- 1474-9718
- 1474-9726
- PMC
- PMC4717274
- Cited by
- 177
- References
- 12
- Language
- en
- Funders
- University of Wisconsin Carbone Cancer Center (P30 CA014520)
- National Center for Advancing Translational Sciences (UL1TR000427)
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