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Artículos de revistas sobre el tema "Models of Ageing"

Autor: Grafiati

Publicado: 4 de junio de 2021

Última modificación: 15 de febrero de 2022

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1

Howlett, Susan E., and Kenneth Rockwood. "Ageing: Develop models of frailty." Nature 512, no. 7514 (2014): 253. http://dx.doi.org/10.1038/512253d.

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2

Hoylaerts, Marc F. "Animal Models of Aging Research." Blood 126, no. 23 (2015): SCI—4—SCI—4. http://dx.doi.org/10.1182/blood.v126.23.sci-4.sci-4.

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Ageing is associated with increased hypercoagulability, due to a slow rise of several coagulation factors, factor VIII, fibrinogen and thrombin-antithrombin complexes, markers of fibrinolysis and progressively defective Protein C activation, yet compatible with life at very high age. Mice, naturally aged up to 24 months, likewise show a progressive elevation of coagulation factors, triggering enhanced thrombogenicity during acute injury-induced thrombus formation. To overcome the still gradual natural ageing in mice, several mouse models of premature ageing were characterized, in an effort to

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3

Toescu, Emil C. "Normal brain ageing: models and mechanisms." Philosophical Transactions of the Royal Society B: Biological Sciences 360, no. 1464 (2005): 2347–54. http://dx.doi.org/10.1098/rstb.2005.1771.

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Normal ageing is associated with a degree of decline in a number of cognitive functions. Apart from the issues raised by the current attempts to expand the lifespan, understanding the mechanisms and the detailed metabolic interactions involved in the process of normal neuronal ageing continues to be a challenge. One model, supported by a significant amount of experimental evidence, views the cellular ageing as a metabolic state characterized by an altered function of the metabolic triad: mitochondria–reactive oxygen species (ROS)–intracellular Ca 2+ . The perturbation in the relationship betwe

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4

Gray, Rosaire P. "Cardiology in the ageing heart: Models." Drug Discovery Today: Disease Models 2, no. 3 (2005): 233–37. http://dx.doi.org/10.1016/j.ddmod.2005.08.003.

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5

Gjerde, A. C. "Multifactor ageing models - origin and similarities." IEEE Electrical Insulation Magazine 13, no. 1 (1997): 6–13. http://dx.doi.org/10.1109/57.567392.

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6

Vermeij, W. P., Monique C. de Waard, R. Brandt, et al. "Neurodegeneration in accelerated ageing mouse models." Experimental Gerontology 48, no. 7 (2013): 686. http://dx.doi.org/10.1016/j.exger.2013.05.017.

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7

MOCEIKIS, Rimvydas, Asta KIČAITĖ, Gintautas SKRIPKIŪNAS, and Aleksandrs KORJAKINS. "AGEING MODELS AND ACCELERATED AGEING TESTS OF GLASS FIBER REINFORCED CONCRETE." Engineering Structures and Technologies 10, no. 1 (2018): 10–17. http://dx.doi.org/10.3846/est.2018.1467.

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Glass fiber reinforced concrete (GRC) is used for 40 years to create world’s most stunning and complex architectural elements due to its high mechanical properties, particularly flexural strength. Yet it is very important to note that any type of glass fibers in the concrete matrix are undergoing complex ageing processes, resulting to significant decrease of initial mechanical characteristics of this composite material under natural weathering conditions. Aspects of GRC durability are mainly dependent from the properties of fibers and interaction between them and concrete matrix. In this artic

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8

Emery Thompson, Melissa, Alexandra G. Rosati, and Noah Snyder-Mackler. "Insights from evolutionarily relevant models for human ageing." Philosophical Transactions of the Royal Society B: Biological Sciences 375, no. 1811 (2020): 20190605. http://dx.doi.org/10.1098/rstb.2019.0605.

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As the world confronts the health challenges of an ageing population, there has been dramatically increased interest in the science of ageing. This research has overwhelmingly focused on age-related disease, particularly in industrialized human populations and short-lived laboratory animal models. However, it has become clear that humans and long-lived primates age differently than many typical model organisms, and that many of the diseases causing death and disability in the developed world are greatly exacerbated by modern lifestyles. As such, research on how the human ageing process evolved

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9

Rychtaříková, Jitka. "Perception of population ageing and age discrimination across EU countries." Population and Economics 3, no. 4 (2019): 1–29. http://dx.doi.org/10.3897/popecon.3.e49760.

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Population ageing is the most dominant demographic challenge that the European Union is experiencing in the 21st century. This may create negative attitudes and lead to discrimination against persons of advanced age. Age-related stereotypes and prejudice can result in age discrimination, termed ageism. This research concerns the question of perceived ageism towards older people in 25 EU countries, surveyed in 2015 using the Special Eurobarometer 437. The analytical section includes descriptive findings and the results of three multi-level regression models addressing three domains (explained v

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10

Durang, Xavier, and Malte Henkel. "Exactly solvable models of growing interfaces and lattice gases: the Arcetri models, ageing and logarithmic sub-ageing." Journal of Statistical Mechanics: Theory and Experiment 2017, no. 12 (2017): 123206. http://dx.doi.org/10.1088/1742-5468/aa9a53.

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11

Duran, Adele L., Paul Potter, Sara Wells, et al. "Shared Ageing Research Models (ShARM): a new facility to support ageing research." Biogerontology 14, no. 6 (2013): 789–94. http://dx.doi.org/10.1007/s10522-013-9457-0.

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12

Dekkers, Gijs, and Richard Cumpston. "On weights in dynamic-ageing microsimulation models." International Journal of Microsimulation 5, no. 2 (2011): 59–65. http://dx.doi.org/10.34196/ijm.00072.

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13

Lees, Hayley, Hannah Walters, and Lynne S. Cox. "Animal and human models to understand ageing." Maturitas 93 (November 2016): 18–27. http://dx.doi.org/10.1016/j.maturitas.2016.06.008.

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14

Rabbitt, Patrick, Christine Lowe, and Val Shilling. "Frontal tests and models for cognitive ageing." European Journal of Cognitive Psychology 13, no. 1 (2001): 5–28. http://dx.doi.org/10.1080/09541440042000197.

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15

Rabbitt, Patrick, Christine Lowe, and Val Shilling. "Frontal tests and models for cognitive ageing." European Journal of Cognitive Psychology 13, no. 1-2 (2001): 5–28. http://dx.doi.org/10.1080/09541440125722.

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16

Sunoj, S. M., N. Unnikrishnan Nair, Asok K. Nanda, and R. S. Rasin. "Ageing Intensity Function for Conditionally Specified Models." American Journal of Mathematical and Management Sciences 39, no. 4 (2020): 329–44. http://dx.doi.org/10.1080/01966324.2020.1762143.

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17

Nakamura, Motoki, Thomas Haarmann-Stemmann, Jean Krutmann, and Akimichi Morita. "Alternative test models for skin ageing research." Experimental Dermatology 27, no. 5 (2018): 495–500. http://dx.doi.org/10.1111/exd.13519.

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18

Heng, Yang, Bart J. L. Eggen, Erik W. G. M. Boddeke, and Susanne M. Kooistra. "Mouse models of central nervous system ageing." Drug Discovery Today: Disease Models 25-26 (2017): 21–34. http://dx.doi.org/10.1016/j.ddmod.2018.10.002.

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19

Misra, Neeraj, and Jisha Francis. "Relative ageing in frailty and resilience models." Metrika 83, no. 2 (2019): 171–96. http://dx.doi.org/10.1007/s00184-019-00726-5.

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20

Selman, Colin, and Dominic J. Withers. "Mammalian models of extended healthy lifespan." Philosophical Transactions of the Royal Society B: Biological Sciences 366, no. 1561 (2011): 99–107. http://dx.doi.org/10.1098/rstb.2010.0243.

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Over the last two centuries, there has been a significant increase in average lifespan expectancy in the developed world. One unambiguous clinical implication of getting older is the risk of experiencing age-related diseases including various cancers, dementia, type-2 diabetes, cataracts and osteoporosis. Historically, the ageing process and its consequences were thought to be intractable. However, over the last two decades or so, a wealth of empirical data has been generated which demonstrates that longevity in model organisms can be extended through the manipulation of individual genes. In p

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21

Richards, Laura J., Jon T. Schnute, A. R. Kronlund, and Richard J. Beamish. "Statistical Models for the Analysis of Ageing Error." Canadian Journal of Fisheries and Aquatic Sciences 49, no. 9 (1992): 1801–15. http://dx.doi.org/10.1139/f92-200.

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We present statistical models for estimating the true age distribution of a population, based on multiple readings from individual fish. There are two steps to this process. The first involves estimating a classification matrix that defines the probability of assigning an age a to a fish when its true age is b. Since true age is unknown, we require an assumption related to ageing error bias; we assume that the true age is the most probable value for the observed age. True age proportions, or alternatively, true ages of fish in the sample are then estimated in the second step. Our methods allow

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22

McAllan, B. M. "Dasyurid marsupials as models for the physiology of ageing in humans." Australian Journal of Zoology 54, no. 3 (2006): 159. http://dx.doi.org/10.1071/zo05073.

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Marsupials of the order Dasyuromorphia have features that make them useful as models for ageing processes in humans. First, they are long-lived for their size, with most small species living for at least 1 year, often several years, contrasting with the mouse, a conventional model for ageing studies, where most populations turn over within 4–6 months. Longevity in some dasyurids allows biological comparisons with other long-lived mammals. Second, the predictable reproduction and life histories of the genera Antechinus and Sminthopsis allow analysis of the role of sex hormones in physiological

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23

Jones, D. Leanne, and Thomas A. Rando. "Emerging models and paradigms for stem cell ageing." Nature Cell Biology 13, no. 5 (2011): 506–12. http://dx.doi.org/10.1038/ncb0511-506.

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24

Lavery, W. Lindsay. "How relevant are animal models to human ageing?" Journal of the Royal Society of Medicine 93, no. 6 (2000): 296–98. http://dx.doi.org/10.1177/014107680009300605.

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25

Han, Xingbo, Yongxu Xia, Fei Ye, and Yongdong Wang. "Ageing models and maintenance strategy for road tunnels." Structure and Infrastructure Engineering 16, no. 5 (2019): 831–46. http://dx.doi.org/10.1080/15732479.2019.1670680.

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26

Lagacé, Martine, Isaac Nahon-Serfaty, and Joelle Laplante. "Canadian government’s framing of ageing at work and older workers: Echoing positive ageing models." Work 52, no. 3 (2015): 597–604. http://dx.doi.org/10.3233/wor-152114.

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27

Nappo, Giovanna, and Fabio Spizzichino. "Relations between ageing and dependence for exchangeable lifetimes with an extension for the IFRA/DFRA property." Dependence Modeling 8, no. 1 (2020): 1–33. http://dx.doi.org/10.1515/demo-2020-0001.

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AbstractWe first review an approach that had been developed in the past years to introduce concepts of “bivariate ageing” for exchangeable lifetimes and to analyze mutual relations among stochastic dependence, univariate ageing, and bivariate ageing.A specific feature of such an approach dwells on the concept of semi-copula and in the extension, from copulas to semi-copulas, of properties of stochastic dependence. In this perspective, we aim to discuss some intricate aspects of conceptual character and to provide the readers with pertinent remarks from a Bayesian Statistics standpoint. In part

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28

Kõks, Sulev, Soner Dogan, Bilge Guvenc Tuna, Herminia González-Navarro, Paul Potter, and Roosmarijn E. Vandenbroucke. "Mouse models of ageing and their relevance to disease." Mechanisms of Ageing and Development 160 (December 2016): 41–53. http://dx.doi.org/10.1016/j.mad.2016.10.001.

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29

Bilkei-Gorzo, Andras. "Genetic mouse models of brain ageing and Alzheimer's disease." Pharmacology & Therapeutics 142, no. 2 (2014): 244–57. http://dx.doi.org/10.1016/j.pharmthera.2013.12.009.

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30

Yeoman, Mark, Greg Scutt, and Richard Faragher. "Insights into CNS ageing from animal models of senescence." Nature Reviews Neuroscience 13, no. 6 (2012): 435–45. http://dx.doi.org/10.1038/nrn3230.

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31

Purnell, P. "Interpretation of climatic temperature variations for accelerated ageing models." Journal of Materials Science 39, no. 1 (2004): 113–18. http://dx.doi.org/10.1023/b:jmsc.0000007734.71945.93.

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32

BERNARDES, AMERICO T., and DIETRICH STAUFFER. "MONTE CARLO SIMULATION OF AGEING: BEYOND BIT-STRING MODELS." International Journal of Modern Physics C 06, no. 06 (1996): 789–806. http://dx.doi.org/10.1142/s0129183195000654.

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Penna's bit-string model of biological ageing due to the accumulation of deleterious mutations is generalized to allow for more than one disease per year. The results remain qualitatively unchanged except for a more complicated non-monotonic approach to equilibrium. We also look at "mutational meltdown", the extinction of the whole population if all mutations are deleterious and heritable, and why the Penna model can escape this extinction. No dependence on population size is found for mutational meltdown, with up to 108 individuals.

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33

Newby, Martin. "Failure Models and Data Analysis Based on Ageing Properties." International Journal of Quality & Reliability Management 4, no. 3 (1987): 36–46. http://dx.doi.org/10.1108/eb002883.

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34

Das, M., I. Gabriely, and N. Barzilai. "Caloric restriction, body fat and ageing in experimental models." Obesity Reviews 5, no. 1 (2004): 13–19. http://dx.doi.org/10.1111/j.1467-789x.2004.00115.x.

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35

Crisanti, A., and F. Ritort. "Equilibrium and ageing dynamics of simple models for glasses." Journal of Physics: Condensed Matter 12, no. 29 (2000): 6413–22. http://dx.doi.org/10.1088/0953-8984/12/29/313.

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36

McKillop, Laura E., and Vladyslav V. Vyazovskiy. "Sleep and ageing: from human studies to rodent models." Current Opinion in Physiology 15 (June 2020): 210–16. http://dx.doi.org/10.1016/j.cophys.2020.03.004.

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37

Osorio, Fernando G., Álvaro J. Obaya, Carlos López-Otín, and José M. P. Freije. "Accelerated ageing: from mechanism to therapy through animal models." Transgenic Research 18, no. 1 (2008): 7–15. http://dx.doi.org/10.1007/s11248-008-9226-z.

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38

García-García, Verónica A., Josefa P. Alameda, Angustias Page та María Llanos Casanova. "Role of NF-κB in Ageing and Age-Related Diseases: Lessons from Genetically Modified Mouse Models". Cells 10, № 8 (2021): 1906. http://dx.doi.org/10.3390/cells10081906.

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Ageing is a complex process, induced by multifaceted interaction of genetic, epigenetic, and environmental factors. It is manifested by a decline in the physiological functions of organisms and associated to the development of age-related chronic diseases and cancer development. It is considered that ageing follows a strictly-regulated program, in which some signaling pathways critically contribute to the establishment and maintenance of the aged state. Chronic inflammation is a major mechanism that promotes the biological ageing process and comorbidity, with the transcription factor NF-κB (nu

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39

Reid, J. M., D. Dai, C. Christian, et al. "Developing predictive models of excellent and devastating outcome after stroke." Age and Ageing 41, no. 4 (2012): 560–64. http://dx.doi.org/10.1093/ageing/afs034.

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40

Hays, R., P. Clarkson, S. Tucker, and D. Challis. "113 * EXAMINING MODELS OF SPECIALIST HEALTHCARE SUPPORT TO CARE HOMES." Age and Ageing 43, suppl 1 (2014): i31. http://dx.doi.org/10.1093/ageing/afu044.8.

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41

Naughton, Corina, Ciara O'Reilly, Ide O’Shaughnessy, et al. "92Frailty Team Models in Ireland: Core Principles and Active Ingredients." Age and Ageing 47, suppl_5 (2018): v13—v60. http://dx.doi.org/10.1093/ageing/afy140.69.

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42

Gallagher, Michela. "Animal models of memory impairment." Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 352, no. 1362 (1997): 1711–17. http://dx.doi.org/10.1098/rstb.1997.0153.

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Memory impairment in the elderly resembles a mild temporal lobe dysfunction. Alterations in the hippocampal formation are also a probable basis for cognitive deficits in some animal models of ageing. For example, aged rats are impaired in hippocampal-dependent tests of spatial memory. Recent studies have revealed considerable structural integrity in the aged hippocampus, even in aged rats with the most impaired spatial memory. In contrast, atrophy/loss of cholinergic neurons in the basal forebrain and deficiency in cholinergic transduction in hippocampus correlate with the severity of spatial

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43

Hatch, Joshua, and Yan Jiao. "A comparison between traditional and measurement-error growth models for weakfishCynoscion regalis." PeerJ 4 (September 21, 2016): e2431. http://dx.doi.org/10.7717/peerj.2431.

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Inferring growth for aquatic species is dependent upon accurate descriptions of age-length relationships, which may be degraded by measurement error in observed ages. Ageing error arises from biased and/or imprecise age determinations as a consequence of misinterpretation by readers or inability of ageing structures to accurately reflect true age. A Bayesian errors-in-variables (EIV) approach (i.e., measurement-error modeling) can account for ageing uncertainty during nonlinear growth curve estimation by allowing observed ages to be parametrically modeled as random deviates. Information on the

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44

Rose, Michael R., and Laurence D. Mueller. "Ageing and immortality." Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences 355, no. 1403 (2000): 1657–62. http://dx.doi.org/10.1098/rstb.2000.0728.

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The concept of the force of natural selection was developed to explain the evolution of ageing. After ageing, however, comes a period in which mortality rates plateau and some individual organisms could, in theory, live forever. This late–life immortality has no presently agreed upon explanation. Two main theories have been offered. The first is heterogeneity within ageing cohorts, such that only extremely robust individuals survive ageing. This theory can be tested by comparisons of more and less robust cohorts. It can also be tested by fitting survival data to its models. The second theory i

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45

Azzu, Vian, and Teresa G. Valencak. "Energy Metabolism and Ageing in the Mouse: A Mini-Review." Gerontology 63, no. 4 (2017): 327–36. http://dx.doi.org/10.1159/000454924.

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The mouse has rapidly become the mammalian model organism of choice in ageing research due to its relatively short lifespan, the proximity of its genome and physiology to humans, and most importantly due to its genetic pliability and the availability of mutant strains. Mouse models have provided great insights into the ageing process, which in its broadest sense is the progressive decline of body functions over time. In this mini-review, we briefly cover the historical views on the link between ageing and metabolic rate, highlight genetically modified transgenic mouse models of extended lifesp

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46

Hui, W., D. A. Young, A. D. Rowan, T. E. Cawston, and C. J. Proctor. "Investigating molecular mechanisms of ageing cartilage using computer simulation models." Osteoarthritis and Cartilage 22 (April 2014): S57—S58. http://dx.doi.org/10.1016/j.joca.2014.02.120.

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47

Čepin, M., and A. Volkanovski. "Consideration of ageing within probabilistic safety assessment models and results." Kerntechnik 74, no. 3 (2009): 140–49. http://dx.doi.org/10.3139/124.110021.

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48

Tomlins, P. E., and B. E. Read. "Creep and physical ageing of polypropylene: a comparison of models." Polymer 39, no. 2 (1998): 355–67. http://dx.doi.org/10.1016/s0032-3861(97)00258-9.

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49

Jeevaratnam, K., K. R. Chadda, S. Ahmad, et al. "P801Arrhythmogenic mechanisms in ageing: insights from murine models of arrhythmia." EP Europace 20, suppl_1 (2018): i143. http://dx.doi.org/10.1093/europace/euy015.405.

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50

Beckingham, Ann C., and Andrea Baumann. "The ageing family in crisis: assessment and decision-making models." Journal of Advanced Nursing 15, no. 7 (1990): 782–87. http://dx.doi.org/10.1111/j.1365-2648.1990.tb01907.x.

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