| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
RESEARCH |
Division of Veterinary Medicine, Tulane National Primate Research Center, 18703 Three Rivers Road, Covington, Louisiana 70433, USA and 1 Department of Mathematics, Tulane University, 6823 St Charles Avenue, New Orleans, Louisiana 70118, USA
Correspondence should be addressed to H M Kubisch; Email: mkubisch{at}tulane.edu
 |
Abstract |
|---|
 Top Abstract IntroductionMaterials and MethodsResultsDiscussionAcknowledgementsReferences |
|---|
|
Introduction |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionAcknowledgementsReferences |
|---|
The age at which reproductive senescence occurs in nonhuman primates is not well defined, although studies on the subject are emerging because of the interest in developing nonhuman models for studies of human menopause. Pavleka & Fedigan (1999) reported an age range for reproductive senescence of 14.5–32.7 years in Japanese macaques. Pigtail macaques experience a gradual fertility decline beginning at about 9 years, eventually reaching cessation at 19 years (Ha et al. 2000). Rhesus macaques, the most frequently used species for reproductive studies, reach reproductive senescence sometime between 10 and 24 years of age (Johnson & Kapsalis 1995).
Several reports have described the anatomical and physiological changes associated with age in rhesus macaques. Histological evidence has shown follicle depletion patterns in rhesus ovaries similar to those observed in the human ovary (Nichols et al. 2005). An increase in gonadotropin releasing hormone concentrations, associated with a reduction of estrogen at menopause, has also been reported in aged rhesus monkeys (Gore et al. 2004). Aging rhesus monkeys experience irregular menstrual cycles and long follicular phases due to delayed ovulation (Gilardi et al. 1997). Moreover, Schramm et al.(2002) found that as monkeys age, serum follicle stimulating hormone (FSH) levels increase, peak estradiol levels during hyperstimulation decrease and oocyte retrieval numbers are lower when compared with younger animals, which is consistent with what is commonly seen in older women.
Nevertheless, while rhesus monkeys experience similar reproductive changes as women, there is a significant difference in the timing of these events (Bellino & Wise 2002), which might, in part, stem from the seasonal breeding pattern of rhesus monkeys. Indeed, Shideler et al.(2001) monitored rhesus monkeys for a complete year and found that menstrual cycling in older females frequently ceased during the nonbreeding season. They also reported that the monkeys in their study did not exhibit a rise in baseline FSHß during the transition to menopause, although that has been reported in perimenopausal women (Santoro et al. 1996).
While population studies of both captive (van Wagenen 1972, Pavleka & Fedigan 1999, Ha et al. 2000) and free ranging (Johnson & Kapsalis 1995) rhesus monkey colonies, as well as clinical observations (Nichols et al. 2005, Schramm et al. 2002), have confirmed age-related changes in reproductive patterns, there is still considerable ambiguity about the exact time at which reproduction stops entirely, as an event that is separate from mortality.
This study was, therefore, designed to determine the effects of various parameters on fertility with particular consideration of the effects of age on reproductive efficiency.
|
Materials and Methods |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionAcknowledgementsReferences |
|---|
As the objective of this study was to assess possible changes in reproductive patterns during a female’s lifetime, only those animals with a minimum of five pregnancies were included in these analyses. It was assumed that females with fewer pregnancies had most likely not lived long enough to develop age-related changes in fertility.
All rhesus monkeys were housed in large outside corrals in social groups with access to food and water ad libitum. Supplemental fruits and forage were provided weekly. Initially, each of the 22 half-acre corrals contained on average 45 adult females and 5 adult males. Animals were monitored daily by trained animal care staff. Sick or injured animals were removed and brought to a designated clinic for evaluation by the attending veterinarian. All animals received semi-annual health examinations, which included tuberculin skin testing and anthelmintic treatment. Pregnancy loss was determined only by physical evidence, i.e. after finding a late stage fetus and/or a placenta and when these could be unequivocally assigned to a specific female.
Statistical analysis
General approach
Much of this study is focused on the relation of birth outcomes to various covariates. Three separate analyses were performed to identify factors associated with different pregnancy outcomes: a) factors related to a pregnancy resulting in an aborted fetus, b) factors related to an early death (within the first 30 days) given a live birth, and c) factors related to a late infant death (infants dying between 1 and 12 months of age) given survival past 1 month. Additional analyses were performed to identify factors associated with the length of the interbirth intervals (IBI), the occurrence of extended IBI, the length of the menopausal period, and the occurrence of extended menopausal periods. For binary response models, logistic regression or logistic regression with random intercepts was used. For models with continuous responses, linear regression or linear mixed models were used.
Models for birth outcomes
Most of this study centers on covariates associated with various binary birth outcomes. In general, these observations are likely to be correlated. Pregnancy outcomes from a single dam probably have an inherent correlation because of dam-specific attributes, and in addition, past outcomes for a given dam may influence current outcomes. Consequently, suitable models can be complex and difficult to implement computationally.
Random effects models
For the analysis of the effects of ordinary covariates on binary birth outcome variables, logistic regression models with random intercepts for each dam were used. As is standard, it was assumed that the population of dam-specific intercepts is normally distributed with zero mean and unknown variance. These models were implemented through PROC GENMOD of SAS, using adaptive Gaussian quadrature with 63 quadrature points for each dam.
Extended random effects models
For two binary birth outcome variables, aborted fetus and early infant death, covariates included the immediate previous values of these birth outcome variables. For the analysis, the Markov assumption was made that the distribution of each of these two outcome variables for a given pregnancy, conditional on the entire past history of the dam, can be written as a logistic linear function of the ordinary covariates, the values of these two birth outcome variables for the immediate previous pregnancy, and a dam-specific random intercept. A primiparous indicator variable was included to accommodate the first pregnancy for each dam. It was further assumed that the two dam-specific random intercept variables in these two birth outcome models are uncorrelated. To implement a full maximum likelihood analysis, the likelihood functions for these two binary birth outcome variables could then be maximized separately, using the same SAS procedures as for the random effects models above. While there may have been a nominal loss of efficiency of estimation in choosing to maximize the two likelihoods separately, the dataset is quite large. It is unlikely that the estimation of the main effects was affected in any important way, and there has been a considerable gain in computational facility. Nonetheless, to confirm the validity of the effects obtained from these models, the data were analyzed second time with partly conditional mean models, which use generalized estimating equations to relate population proportions to covariates but allow dependence on selected past outcomes and history (Pepe & Couper 1997). The results obtained by this latter method agreed qualitatively with what was obtained from the random effects models, although they were not numerically identical, as the models are not intended to be entirely equivalent.
The factors that were entered into these models are, Abort (=1 if stillbirth, 0 otherwise), EarlyDth (=1 if live birth and death within first 30 days), LateDth (=1 if survives 30 days but dies before 1 year), Weaned (=1 if survives 1 year), DamAge (=dam age in years), Female (=1 if baby is female), Male (=1 if baby male), PrimDam (=1 if primiparous dam), PreIBI (=dam age at current birth minus dam age at previous birth), PostIBI (=dam age at next birth minus dam age at current birth), PreLongBI (=1 if PreIBI exceeds 1.5 years), PostLongBI (=1 if PostIBI exceeds 1.5 years), PAbort (=1 if previous fetus aborted), PEarlyDth (=1 if previous birth resulted in an early death) and LaIBI (=ln[0.5(PreIBI+PostIBI)]).
To understand the reasons for having indicator variables PreLongBI and PostLongBI, it is helpful to review the histogram of birth intervals IBI (Fig. 1
), which shows a primary peak at about 1 year, and secondary and tertiary peaks at 2 and 3 years, and so on. This is caused by the seasonal breeding cycles of these animals; consequently the indicator variables PreLongBI and PostLongBI, suggest a missed previous or subsequent breeding season. The limit of 1.5 years serves to divide the group of IBIs peaking around 1 year from those peaking around later years.
|
To determine the existence and nature of menopause, the variable time to death (TTD; =time from birth of last infant to death of dam) was analyzed by least squares regression for dependence on DamAgeLB (=age of dam at last birth). To avoid censoring bias and yet restrict the dams to animals that had died by the end of the time during which these records had been generated, only the 878 dams born before March 31, 1984 were included in this particular analysis. In addition, logistic regression was used to analyze the probability of TTD>4.5 years for dependence on appropriate covariates. The routines lm and glm were used from the MASS library of the statistical package R.
|
Results |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionAcknowledgementsReferences |
|---|
.
|
).
|
Survival to day 30
Of the infants that did not survive to 1 year of age, 27.1% died within the first 30 days. An extended random effects model with binary response variable EarlyDth was implemented for all live births. Interestingly, essentially the same factors associated with a pregnancy loss proved to be factors associated with an infant’s death during this period. Thus, the likelihood of dying within this period was significantly increased by greater dam age (P<0.001), but not quite by having the preceding birth interval exceed 1.5 years (P=0.06). Similarly, having a PrimDam as a mother (P<0.001) and having an aborted pregnancy (P<0.001) or early death (P=0.005) in the dam’s preceding pregnancy were significant factors in elevating the probability an infant died during this period (see also Fig. 4). Finally, the inverse age effect prevailed for PrimDams, with young PrimDams being less likely to have an infant survive to 30 days (P=0.001).
|
Interbirth intervals
Both the effects of covariates on the length of IBI and the effects of covariates on the occurrences of PreLongBI and PostLongBI were considered. To analyze the effect of DamAge on the length of IBI and avoid spurious correlations with DamAge, the IBI response was based on the average of PreIBI and PostIBI. The distribution of average IBI across dam ages is shown in Fig. 5. A linear mixed effects model with response variable LaIBI (=natural log of the average IBI) was implemented for the data in which first and last pregnancies were omitted. This analysis showed DamAge to be a significant factor in increasing LaIBI (P<0.001). The effects of the outcome of the preceding pregnancy on PostIBI and PostLongBI are illustrated in Table 1. The table illustrates that late death (LateDth) has the lowest proportion of extended PostIBIs. Note that IBIs are rounded off for each birth outcome category.
|
|
Post-reproduction period
The least squares linear regression analysis of the relationship between the age at last birth of a dam and her subsequent TTD indicated that as dams become older at time of their last birth, the time to their death increased (P<0.001). Table 2 classifies dams according to their age at last birth and their subsequent TTD.
|
. The trend of Table 3 was formally analyzed with a logistic regression which further indicated that the probability of an extended menopausal period (TTD>4.5 years) increases with dam age at last birth (P<0.001). Note that both tables show an increase in the time between last birth and death at around 13 years of age.
|
|
Discussion |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionAcknowledgementsReferences |
|---|
Females in the present analyses began producing infants at about 4 years of age and the proportion of infants produced by females within an age group increased steadily up to 10 years, after which it gradually declined until reproduction ceased altogether. This reproductive pattern is similar to what has been reported in captive pigtail macaques at the Washington National Primate Research Center (Ha et al. 2000), and for Japanese macaques in Texas (Pavleka & Fedigan 1999). Female macaques can continue to produce infants well into their twenties, after which they cease to be reproductively active (Johnson & Kapsalis 1995, Pavleka & Fedigan 1999, Ha et al. 2000). This decline and ultimate cessation of reproductive capabilities of female macaques resembles that is seen in most other mammals (Cohen 2004) and is recognized to be a separate event from somatic senescence and more attributable to a change in reproductive status than a decline in overall body condition.
The factors that determine longevity among rhesus macaques are likely to be as varied as they are among other primate species. However, one important consideration is that rhesus macaque groups have stable linear dominance hierarchies in which females of one matriline outrank females of lower matrilines. It is likely that this social structure has some bearing on the fate of at least some of the females in a group. Indeed, in many captive primates, especially macaques, social stress has been found to influence the incidence or progression of diseases such as atherosclerosis (Williams et al. 1991, Shively & Clarkson 1994, Shively et al. 2000, Kaplan et al. 1996, 2002, Skantze et al. 1998), respiratory infections (Cohen et al. 1997, Cohen 1999) and depression (Shively et al. 1997a, 1997b, 2005). Moreover, the relationship between social status and social stress is particularly consistent among females, with an inverse relationship between status and stress (Kaplan et al. 1984, Saltzman et al. 1991, Shively et al. 1997a, 1997b).
One of the notable effects of aging in females in the present study was a concomitant increase in pregnancy losses. This might, at least in part, be due to a decline in oocyte and embryo quality or changes in the uterine environment. Indeed, work on oocytes and embryos of humans, mice and other animal species has shown that the aging of the female is associated with a number of characteristic abnormalities including chromosomal aneuploidies (Volarcik et al. 1998), increased DNA fragmentation (Fujino et al. 1996, Wu et al. 2000), a decreased ability to mature and extrude a polar body in vitro (Peluso et al. 1980, Hewitt & England 1998), increased oxidative damage (Tarin et al. 1996, 2002), and an increase in the incidence and degree of mitochondrial damage (Keefe et al. 1995). Evidence of age-related changes in the uterine environment has been more difficult to ascertain and attempts have largely relied on reciprocal embryo transfer experiments in mice, hamsters, and rabbits. Transfers of embryos obtained from young animals into older recipients have shown a marked decline in pregnancy rates in these species (Blaha 1964, Talbert & Krohn 1966, Adams 1979).
The present study also revealed that the interval between births increased with the age of the mother, as did the late loss of an infant, while the length of preceding birth interval or infant sex did not seem to have any effect. Similar conclusions were reached by Wilson et al.(1983). In contrast, Maestripieri (2001) observed longer birth interval after daughters, possibly due to increased maternal investment in female offspring, while shorter birth intervals have been found to be associated with male offspring (Simpson & Simpson 1982).
A study of Japanese macaques (Fedigan et al. 1986) reported a nonsignificant trend towards a lengthening of birth intervals in aging females, while an age-dependent linear increase in birth intervals has also been described in pigtail macaques (Ha et al. 2000).
The fact that birth intervals tend to increase with advancing age may be a reflection of irregular ovulation patterns in older monkeys (Nozaki et al. 1995, Gilardi et al. 1997), as well as the increased strain on older mothers raising infants. In a study of the population on Cayo Santiago, older females were much less likely to produce an infant if they had given birth the previous season (Campell & Gerald 2004).
While the present study did not reveal any effects of infant sex on subsequent birth intervals for either sex, the results did indicate a higher mortality rate for male infants when compared with females, a trend also found in other colonies (Drickamer 1974, Mastripieri 2001). It was surprising that the present study revealed that the age of the mother appears to be a determinant of infant survival only during the first 30 days, while it does not seem to affect survival during the subsequent 11 months. It is not clear whether this reflects pre- or postnatal developmental problems among infants of older dams or a reduced mothering ability or a combination of both.
In the present study, the time between last birth and death increased significantly for older mothers. Up to age 19, females that died generally did so within the time of an average birth interval, indicating that their deaths were not preceded by extended periods of infertility. Monkeys surviving past age 22, however, showed much greater gaps between the time of birth of their last infant and death, which ranged from 3 to 8 years. The lengths of these intervals, which are much longer than the length of rhesus infant dependence, suggest that this may be the point at which menopausal transition has occurred.
There are two primary hypotheses that have been developed to explain the origin of menopause (Austad 1994). The adaptive theory, or grandmother hypothesis, proposes that menopause evolved as the risks of reproduction by older females were outweighed by the benefits of contributions made by these females to the survival of children and grandchildren (Williams 1957, Peccei 1995, Shanley & Kirkwood 2001, Lahdenpara et al. 2004). The alternative theory suggests that menopause is the result of nonadaptive evolution, in which menopause is a mere artifact of increases in lifespan, which are brought on by environmental factors such as better nutrition. In this view, a long post-reproductive lifespan does not enhance overall survival of offspring. Support for the latter view comes from species such as the olive baboon, in which family structures do include prominent grandmother involvement. However, it has been pointed out that offspring do not seem to derive any particular advantage from this arrangement (Packer et al. 1998).
Evidence reported to date supports the idea that macaques go through physical changes associated with reproductive senescence, reminiscent of changes observed during human menopause. Studies involving ovarian, hormonal, and pituitary function of aging rhesus macaques (Hodgen et al. 1977, Gilardi et al. 1997, Gore et al. 2004, Nichols et al. 2005, Schramm et al. 2002) have consistently shown biological changes mirroring those known to occur in women and support the macaque as an adequate model of human menopause. In Japanese macaques, a decrease in ovarian control of gonadotropin levels has been reported in monkeys approximately at age 18 (Nozaki et al. 1995).
Overall, our study, as well as those by others, shows that fertility declines as females age, due, at least in part, to changing aspects of the reproductive system. Moreover, cessation of fertility can precede death by several years. Nevertheless, given the often conflicting results of reports on rhesus macaque reproduction, in general, further studies are clearly needed.
|
Acknowledgements |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionAcknowledgementsReferences |
|---|
|
References |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionAcknowledgementsReferences |
|---|
Adams CE 1979 Aging and reproduction in the female mammal with particular reference to the rabbit. Journal of Reproduction and Fertility. Supplement 12 1–16.
Anderson MA & Simpson MJA 1979 Breeding performance of a captive colony of rhesus macaques (Macaca mulatta). Laboratory Animals 13 275–281.
Austad SN 1994 Menopause: and evolutionary perspective. Experimental Gerontology 4 255–263.
Bellino FL & Wise PM 2002 Nonhuman primate models of menopause workshop. Biology of Reproduction 68 10–18.[CrossRef][Web of Science]
Blaha GC 1964 Effect of age of the donor and recipient on the development of transferred golden hamster ova. Anatomical Record 150 413–416.[CrossRef][Medline]
Campell BC & Gerald MS 2004 Body composition, age and fertility among free-ranging female rhesus macaques (Macaca mulatta). Journal of Medical Primatology 33 70–77.[CrossRef][Web of Science][Medline]
Cohen S 1999 Social status and susceptibility to respiratory infections. Annals of the New York Academy of Sciences 896 246–253.[CrossRef][Web of Science][Medline]
Cohen AA 2004 Female post-reproductive lifespan: a general mammalian trait. Biological Reviews of the Cambridge Philosophical Society 79 733–750.[Medline]
Cohen S, Line S, Manuck SB, Rabin BS, Heise ER & Kaplan JR 1997 Chronic social stress, social status, and susceptibility to upper respiratory infection in nonhuman primates. Psychosomatic Medicine 59 213–221.
Drickamer LC 1974 A ten-year summary of reproductive data for free-ranging Macaca mulatta. Folia Primatologica 21 61–80.[Web of Science][Medline]
Fedigan LM, Fedigan L, Gouzoules S, Gouzoules H & Koyama N 1986 Lifetime reproductive success in female Japanese macaques. Folia Primatologica 47 143–157.[Web of Science][Medline]
Fujino Y, Ozaki K, Yamamasu S, Ito F, Matsuoko I, Hayashi E, Nakamura H, Ogita S, Sato E & Inoue M 1996 DNA fragmentation off oocytes in aged mice. Human Reproduction 11 1480–1483.
Gilardi KV, Shideler SE, Valverde CR, Roberts JA & Lasley BL 1997 Characterization of the onset of menopause in the rhesus macaque. Biology of Reproduction 57 335–340.[Abstract]
Gore AC, Windsor-Engnell BM & Terasawz E 2004 Menopausal increases in pulsatile gonadotropin-releasing hormone release in a nonhuman primate (Macaca mulatta). Endocrinology 145 4633–4659.
Ha JC, Robinette RL & Sackett GP 2000 Demographic analysis of the Washington Regional Primate Research Center pigtailed macaque colony, 1967–1996. American Journal of Primatology 52 187–198.[CrossRef][Web of Science][Medline]
Hewitt DA & England GCW 1998 The effect of oocyte size and bitch age upon nuclear maturation in vitro. Theriogenology 49 957–966.[CrossRef][Web of Science][Medline]
Hodgen GD, Goodman AL, O’Connor A & Johnson DK 1977 Menopause in rhesus monkeys: model for study of disorders in the human climacteric. American Journal of Obstetrics and Gynecology 12 581–584.
Johnson RL & Kapsalis E 1995 Ageing, infecundity and reproductive senescence in free-ranging female rhesus monkeys. Journal of Reproduction and Fertility 105 271–278.
Kaplan JR, Adams MR, Clarkson TB & Koritnik DR 1984 Psychosocial influences on female ‘protection’ among cynomolgus macaques. Atherosclerosis 53 283–295.[CrossRef][Web of Science][Medline]
Kaplan JR, Adams MR, Clarkson TB, Manuck SB, Shively CA & Williams JK 1996 Psychosocial factors, sex differences, and atherosclerosis: lessons from animal models. Psychosomatic Medicine 58 598–611.
Kaplan JR, Manuck SB, Anthony MS & Clarkson TB 2002 Premenopausal social status and hormone exposure predict postmenopausal atherosclerosis in female monkeys. Obstetrics & Gynecology 99 381–388.[CrossRef][Web of Science][Medline]
Keefe DL, Niven-Fairchild T, Powell S & Buragadunta S 1995 Mitochondrial deoxyribonucleic acid deletions in oocytes and reproductive ageing in women. Fertility and Sterility 64 577–583.[Web of Science][Medline]
Lahdenpara M, Lummaa V, Helle S, Tremblay M & Russell AF 2004 Fitness benefits of prolonged post-reproductive lifespan in women. Nature 428 178–181.[CrossRef][Medline]
Maestripieri D 2001 Female-biased maternal investment in rhesus macaques. Folia Primatologica 72 44–47.[CrossRef][Web of Science][Medline]
Nichols SM, Bavister BD, Brenner CA, Didier PJ, Harrison RM & Kubisch HM 2005 Ovarian senescence in the rhesus monkey (Macaca mulatta). Human Reproduction 20 79–83.
Nozaki M, Mitsunaga F & Shimizu K 1995 Reproductive senescence in female Japanese monkeys (Macaca fuscata): age- and season-related changes in hypothalamic–pituitary–ovarian functions and fecundity rates. Biology of Reproduction 52 1250–1257.[Abstract]
Packer C, Tatar M & Collins A 1998 Reproductive cessation in female mammals. Nature 392 807–811.[CrossRef][Medline]
Pavleka MSM & Fedigan LM 1999 Reproductive termination in female Japanese monkeys: a comparative life history perspective. American Journal of Physical Anthropology 109 455–464.[CrossRef][Web of Science][Medline]
Peccei JS 1995 A hypothesis for the origin and evolution of menopause. Maturitas 21 83–89.[CrossRef][Web of Science][Medline]
Peluso JJ, England-Charlesworth C & Hutz R 1980 Effect of age and of follicular aging on the preovulatory oocyte. Biology of Reproduction 22 999–1005.[Abstract]
Pepe MS & Couper D 1997 Modelling partly conditional means with longitudinal data. Journal of the American Statistical Association 92 991–998.[CrossRef][Web of Science]
Saltzman W, Mendoza SP & Mason WA 1991 Sociophysiology of relationships in squirrel monkeys: I. Formation of female dyads. Physiology & Behavior 50 271–280.[CrossRef][Medline]
Santoro N, Brown JR, Adel T & Skurnick JH 1996 Characterization of hormonal dynamics in the perimenopause. Journal of Clinical Endocrinology and Metabolism 81 1495–1501.[Abstract]
Schramm RD, Paprocki AM & Bavister BD 2002 Features associated with reproductive ageing in female rhesus monkeys. Human Reproduction 17 1597–1603.
Shanley DP & Kirkwood TBL 2001 Evolution of the human menopause. Bioessays 23 282–287.[CrossRef][Web of Science][Medline]
Shideler SE, Gee NA, Chen J & Lasley BL 2001 Estrogen and progesterone metabolites and follicle stimulating hormone in the aged macaque female. Biology of Reproduction 65 1718–1725.
Shively CA & Clarkson TB 1994 Social status and coronary artery atherosclerosis in female monkeys. Arteriosclerosis Thrombosis 14 721–726.
Shively CA, Grant KA, Ehrenkaufer RL, Mach RH & Nader MA 1997a Social stress, depression, and brain dopamine in female cynomolgus monkeys. Annals of the New York Academy of Sciences 807 574–577.[CrossRef][Web of Science][Medline]
Shively CA, Laber-Laird K & Anton RF 1997b Behavior and physiology of social stress and depression in female cynomolgus monkeys. Biological Psychiatry 41 871–882.[CrossRef][Web of Science][Medline]
Shively CA, Adams MR, Kapan JR & Williams JK 2000 Social stress, gender, and coronary heart disease risk in monkeys. In Stress, Coping, and Cardiovascular Disease, pp 71–84. Ed. AR Wellens. Mahwah, NJ: Erlbaum Association.
Shively CA, Register TC, Friedman DP, Morgan TM, Thompson J & Lanier T 2005 Social stress-associated depression in adult female cynomolgus monkeys (Macaca fascicularis). Biological Psychology 69 67–84.[CrossRef][Web of Science][Medline]
Simpson MJA & Simpson AE 1982 Birth sex ratios and social rank in rhesus monkey mothers. Nature 300 440–441.[CrossRef][Medline]
Skantze HB, Kaplan J, Pettersson K, Manuck S, Blomqvist N, Kyes R, Williams K & Bondjers G 1998 Psychosocial stress causes endothelial injury in cynomolgus monkeys via beta1-adrenoceptor activation. Atherosclerosis 136 153–161.[CrossRef][Web of Science][Medline]
Talbert GB & Krohn PL 1966 Effect of maternal age on viability of ova and uterine support of pregnancy in mice. Journal of Reproduction and Fertility 11 399–406.
Tarin JJ, Vendrell FJ, Ten J, Blanes R, van Blerkom J & Cano A 1996 The oxidizing agent tertiary butyl hydroperoxide induces disturbances in spindle organization, c-meiosis, and aneuploidy in mouse oocytes. Molecular Human Reproduction 2 895–901.
Tarin JJ, Perez-Albala S & Cano A 2002 Oral antioxidants counteract the negative effects of female aging on oocyte quantity and quality in the mouse. Molecular Reproduction and Development 61 385–397.[CrossRef][Web of Science][Medline]
Van Wagenen G 1972 Vital statistics from a breeding colony. Reproduction and pregnancy outcome in Macaca mulatta. Journal of Medical Primatology 1 2–28.[Medline]
Volarcik K, Sheean L, Goldfarb J, Woods L, Abdul-Karim FW & Hunt P 1998 The meiotic competence of in vitro matured human oocytes is influenced by donor age: evidence that folliculogenesis is compromised in the reproductively aged ovary. Human Reproduction 13 154–160.
Williams GC 1957 Pleiotropy, natural selection, and the evolution of senescence. Evolution 11 398–411.[CrossRef][Web of Science]
Williams JK, Vita JA, Manuck SB, Selwyn AP & Kaplan JR 1991 Psychosocial factors impair vascular responses of coronary arteries. Circulation 84 2146–2153.
Wilson ME, Walker ML & Gordon TP 1983 Consequences of first pregnancy in rhesus monkeys. American Journal of Physical Anthropology 61 103–110.[CrossRef][Web of Science][Medline]
Wu J, Zhang L & Wang X 2000 Maturation and apoptosis of human oocytes in vitro are age-related. Fertility and Sterility 74 1137–1141.[CrossRef][Web of Science][Medline]
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
