scholarly journals Maternal effects on offspring growth indicate post-weaning juvenile dependence in chimpanzees (Pan troglodytes verus)

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Liran Samuni ◽  
Patrick Tkaczynski ◽  
Tobias Deschner ◽  
Therese Löhrrich ◽  
Roman M. Wittig ◽  
...  
Keyword(s):  
Specific Gravity ◽  
Muscle Mass ◽  
Maternal Effects ◽  
Early Adulthood ◽  
Growth Curves ◽  
Maternal Investment ◽  
Individual Characteristics ◽  
Growth Patterns ◽  
Urinary Creatinine ◽  
Maternal Presence

Abstract Background In animals with altricial offspring, most growth occurs after birth and may be optimized by post-natal maternal care. Maternal effects on growth may be influenced by individual characteristics of the mothers, such as social status, individual investment strategies and the length of association with offspring. The prolonged juvenile dependence seen in humans is a distinctive life history adaptation, which may have evolved to facilitate sustained somatic and brain growth. In chimpanzees, offspring are typically weaned at approximately 4 years old, yet immature individuals continue to associate with their mothers for up to 10 years beyond weaning. Whether this lengthy association or the individual characteristics of mothers influences growth patterns in this species is not clear. The relationship between urinary creatinine and specific gravity is an established non-invasive measure of muscle mass in humans and chimpanzees. We analysed the urinary creatinine and specific gravity of 1318 urine samples from 70 wild chimpanzees from the Taï Forest, Ivory Coast aged 4 to 15 years. Results We showed a clear increase in urinary creatinine levels with age in both males and females, replicating established growth curves in this species and reaffirming this measure as a reliable proxy for lean body mass. Comparing those who experience maternal loss (orphans) with non-orphan chimpanzees, maternal presence beyond weaning age and into late juvenility positively influenced offspring muscle mass throughout ontogeny such that orphans had significantly less muscle mass than age-matched non-orphans. In age-matched offspring with mothers, those with high-ranking mothers had greater muscle mass. Accounting for variation in muscle mass attributable to maternal presence, we found no effect of maternal investment (length of inter birth interval, from own birth to birth of following sibling) on offspring muscle mass. Conclusion Chimpanzee mothers have an extended and multi-faceted influence on offspring phenotypes. Our results suggest that maternal investment extends beyond lactation and into early adulthood and has clear benefits to offspring physical development. Therefore, prolonged juvenile dependence, although unique in its form in human societies, may be a trait with deeper evolutionary origins.

PATTERNS OF GROWTH IN HEIGHT AND WEIGHT FROM BIRTH TO EIGHTEEN YEARS OF AGE

PEDIATRICS ◽  
1959 ◽  
Vol 24 (5) ◽  
pp. 904-921
Author(s):  
Robert B. Reed ◽  
Harold C. Stuart
Keyword(s):  
Growth Curves ◽  
Growth Patterns ◽  
Individual Growth ◽  
Growth Spurt ◽  
Adolescent Growth Spurt ◽  
Wide Range ◽  
Basic Facts ◽  
The Individual ◽  
Rates Of Growth ◽  
Mature Size

In this report is displayed the range of variation observed in the growth curves of height and weight in a series of 134 children observed from birth to 18 years. For purposes of simplification the individuals have been classified on the basis of their rates of growth during three successive 6-year intervals. Even in terms of this crude classification several basic facts about individual growth patterns of height and weight are apparent. The wide range of differences between individuals applies not only to facts about size at specific ages but also to the pattern of change followed from age period to age period. The rate of growth during early childhood, i.e. before 6 years of age, is associated with, but not specifically predictive of, size at maturity and timing of the adolescent growth spurt. Individuals with rapid growth before 6 years of age tend to have large mature size and early adolescent growth spurt. It will be the objective of future reports from this research project to determine the manner in which the individual differences in growth demonstrated and classified here are related to aspects of physical development, to environmental influences such as dietary intake and to the level of health of the child.

Creatinine Excretion

PEDIATRICS ◽  
1983 ◽  
Vol 71 (1) ◽  
pp. 140-140
Author(s):  
JAMES L. SUTPHEN
Keyword(s):  
Muscle Mass ◽  
Initial Presentation ◽  
Creatinine Excretion ◽  
Urinary Creatinine ◽  
Weight Measurement ◽  
Body Muscle ◽  
Creatinine Measurement ◽  
Urinary Creatinine Excretion

In Reply.— The questions posed by Harkavy allow me to expand on the initial presentation of the data in my previous report.1 As documented by numerous previous reports, urinary creatinine excretion does, in fact, reflect body muscle mass.2 Furthermore, it has been documented in older infants that creatinine excretion per kilogram increases with the age, weight, and length of the infant.3 The regression data in my report are not expressed in terms of creatinine per kilogram as the dependent variable as this multiplies the error of creatinine measurement by including the error in weight measurement (hydration states etc).

scholarly journals Growth Curve of Selectively Bred Tambaqui (Colossoma macropomum) Reared in Different Environments

2020 ◽  
Vol 8 (3) ◽  
pp. 585
Author(s):  
Rebeca Marcos ◽  
Ruy Alberto Caetano Corrêa Filho ◽  
Janessa Sampaio de Abreu ◽  
Guilherme Do Nascimento Seraphim ◽  
Ana Carla Carvalho Silva ◽  
...  
Keyword(s):  
Growth Curve ◽  
Growth Curves ◽  
Growth Patterns ◽  
Production Performance ◽  
Environment Interaction ◽  
Morphometric Traits ◽  
Mato Grosso ◽  
Colossoma Macropomum ◽  
Genotype Environment Interaction ◽  
The Family

The objective of this study was to obtain the growth curve of selectively bred tambaqui (Colossoma macropomum) reared in different environments. The experiment was carried out in the municipalities of Santo Antônio de Leverger (Mato Grosso – MT) and Campo Grande (Mato Grosso do Sul – MS), Brazil, over 431 days. Weight and morphometric traits of two families (A and B) from the second generation of selective breeding (G2) were measured every 30-45 days. The Gompertz regression model was used to obtain the growth curves. The production performance of both families and the interaction between families and locations (genotype × environment) were evaluated by analysis of variance considering the family (A and B), location (MT and MS), family × location interaction and error as variation factors. The asymptotic value (parameter A) obtained for weight and morphometric traits (except head length) was higher (P<0.05) in MT (weight of families A and B: 2279.6 g) than in MS (weight of family A: 1400.0 g; weight of family B: 1600.0 g). Family B showed better production performance in MS. There was a genotype × environment interaction effect on weight, body length and standard length. The two families have distinct growth patterns in different production environments. Family B has better growth performance in the environment with lower temperatures (MS).

A Parsimonious Number of Growth Curves

1993 ◽  
Vol 10 (3) ◽  
pp. 132-136 ◽  
Author(s):  
Boris Zeide
Keyword(s):  
Growth Pattern ◽  
Ecological Factors ◽  
Growth Curves ◽  
Site Index ◽  
Growth Conditions ◽  
Growth Patterns ◽  
Construction Methods ◽  
Complex Interactions ◽  
Site Index Curve ◽  
Index Curve

Abstract Construction of new site index curves is often justified by a lack of growth information for a given species and site. This justification presumes that there is a one-to-one correspondence between growth pattern and stand conditions which are determined by numerous genetic and ecological factors together with their complex interactions. Because these factors are combined in an infinite number of ways, each stand is unique and needs its own site index curve. The effort required for collecting growth information would be prohibitive. This effort is also unnecessary because many existing curves coincide with each other and are, therefore, redundant. Differences in species, site, and construction methods do not prevent the appearance of the same growth patterns. These facts indicate that unique growth conditions do not mean that each stand has a unique growth pattern. Therefore, a more productive approach to growth modeling consists of distilling these patterns from existing curves and yield tables rather than piling up more new site index curves. Earlier investigations showed that the diversity in growth curves can be reduced to a small number (15-30) of growth types. The present study demonstrates that the number of types can be further reduced to 3-5 without sacrificing accuracy of growth predictions. North. J. Appl. For. 10(3):132-136.

Age and growth of blue grenadier, Macruronus novaezelandiae (Hector), in south-eastern Australian waters

1987 ◽  
Vol 38 (5) ◽  
pp. 625 ◽  
Author(s):  
TJ Kenchington ◽  
O Augustine
Keyword(s):  
Growth Parameters ◽  
Growth Curves ◽  
Growth Patterns ◽  
Age And Growth ◽  
Double Blind ◽  
Blind Test ◽  
Thin Sections ◽  
South Eastern ◽  
Weight Data ◽  
Immature Fish

Blue grenadier, Macruronus novaezelandiae, from south-eastern Australian waters were aged, using their otoliths (whole and in transverse thin sections). The greatest recorded age was 25 years. A double blind test showed that the recorded ages were sufficiently reproducible to use in fitting growth curves (Index of Average Percent Error: 8%), but not sufficiently so to assign individuals to particular year-classes. Von Bertalanffy growth curves were fitted to both length and weight data. For males, Lt = 90.7 (1 - exp[-0.256(t + 1.21)]} and Wt = 2.62 (1 - exp[-0.277(t + 1.39)]}3. For females, Lt = 99.3 {l - exp[-0.203(t + 1.48)]} and Wt = 4.16{1 - exp[-0.157(t + 2.93)]}3. L is the length in centimetres, W is the weight in kilograms and t is the age in years. A comparison with length-frequency modes validated the growth curves for immature fish, but no validation was possible for the adults. The $exes have qignificantly different growth patterns. Their growth parameters are typical of those of commercially exploited, temperate gadoid fishes and show no modification for the deep-water zone inhabited by blue grenadier.

Height Growth and Site Index Curves for Douglas-Fir in the Siuslaw National Forest, Oregon

1989 ◽  
Vol 4 (4) ◽  
pp. 136-142 ◽  
Author(s):  
Joseph E. Means ◽  
Thomas E. Sabin
Keyword(s):  
Growth Curves ◽  
Site Index ◽  
Height Growth ◽  
Growth Patterns ◽  
National Forest ◽  
Coast Range ◽  
Oregon Coast Range ◽  
Plant Associations ◽  
Stand Yield ◽  
Combined Data

Abstract On the Siuslaw National Forest in the central Oregon Coast Range we performed stem analysis of 55 trees selected with the criteria used by the forest. Height growth patterns of these trees were significantly different (α = 0.05) from commonly used regional height growth curves. Height growth patterns also differed significantly among groups of floristically similar plant associations in the Siuslaw National Forest. We constructed height growth and site index curves for two classes of plant associations having different height growth curve forms and for the combined data. Forest managers should consider building local height-growth and site-index curves if these are important in estimating stand yield or site productivity. West. J. Appl. For. 4(4):136-142, October 1989

Influence of body mass index status on urinary creatinine and specific gravity for epidemiological study of children

2015 ◽  
Vol 174 (11) ◽  
pp. 1481-1489 ◽  
Author(s):  
Bin Wang ◽  
Chuanxi Tang ◽  
Hexing Wang ◽  
Wei Zhou ◽  
Yue Chen ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Specific Gravity ◽  
Epidemiological Study ◽  
Body Mass ◽  
Urinary Creatinine ◽  
Body Mass Index Status

scholarly journals Comparison of growth curves of two genotypes of dairy goats using nonlinear mixed models

2013 ◽  
Vol 152 (5) ◽  
pp. 829-842 ◽  
Author(s):  
J. G. L. REGADAS FILHO ◽  
L. O. TEDESCHI ◽  
M. T. RODRIGUES ◽  
L. F. BRITO ◽  
T. S. OLIVEIRA
Keyword(s):  
Random Effects ◽  
Growth Curve ◽  
Mixed Model ◽  
Growth Curves ◽  
Growth Patterns ◽  
Dairy Goat ◽  
Residual Variance ◽  
Nonlinear Mixed Model ◽  
Error Structure ◽  
Mixed Model Methodology

SUMMARYThe objective of the current study was to assess the use of nonlinear mixed model methodology to fit the growth curves (weightv.time) of two dairy goat genotypes (Alpine, +A and Saanen, +S). The nonlinear functions evaluated included Brody, Von Bertalanffy, Richards, Logistic and Gompertz. The growth curve adjustment was performed using two steps. First, random effectsu1,u2andu3were linked to the asymptotic body weight (β1), constant of integration (β2) and rate constant of growth (β3) parameters, respectively. In addition to a traditional fixed-effects model, four combinations of models were evaluated using random variables: all parameters associated with random effects (u1,u2andu3), onlyβ1andβ2(u1andu2), onlyβ1andβ3(u1andu3) and onlyβ1(u1). Second, the fit of the best adjusted model was refined by using the power variance and modelling the error structure. Residual variance ($\sigma _e^2 $) and the Akaike information criterion were used to evaluate the models. After the best fitting model was chosen, the genotype curve parameters were compared. The residual variance was reduced in all scenarios for which random effects were considered. The Richards (u1andu3) function had the best fit to the data. This model was reparameterized using two isotropic error structures for unequally spaced data, and the structure known in the literature as SP(MATERN) proved to be a better fit. The growth curve parameters differed between the two genotypes, with the exception of the constant that determines the proportion of the final size at which the inflection point occurs (β4). The nonlinear mixed model methodology is an efficient tool for evaluating growth curve features, and it is advisable to assign biologically significant parameters with random effects. Moreover, evaluating error structure modelling is recommended to account for possible correlated errors that may be present even when using random effects. Different Richard growth curve parameters should be used for the predominantly Alpine and Saanen genotypes because there are differences in their growth patterns.

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