Study on the Changes in Enzyme and Insulin-like Growth Factor-1 Concentrations in Blood Serum and Growth Characteristics of Velvet Antler during the Antler Growth Period in Sika Deer (&lt;i&gt;Cervus nippon&lt;/i&gt;)

Park, Jaehyun; Jeon, Byong-Tae; Kang, S. K.; Oh, Mirae; Kim, Myonghwa; Jang, Se-Young; Park, Pyojam; Kim, Sangwoo

doi:10.5713/ajas.14.0535

Cited by 5 publications

(4 citation statements)

References 22 publications

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“…Estimates of regression coefficients of age ( and 4.36) and field-dressed weight ( and 0.75) in Eq 1 showed that there were positive linear relationships between the effects of age and field-dressed weight and the traits of antler beam diameter and length. This result is consistent with previous reports [6, 7, 43]. Our results also showed that age is related to antler characteristics and body size in WTD.…”

Section: Resultssupporting

confidence: 94%

“…The relationships among antler characteristics, age and field-dressed weight and predictions of these traits in deer populations have been studied by using linear models [6, 7]. Significant literature exists related to the use of body measurement, such as antler size, to predict age, as well as correlation between antler size and body weight.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of linear model and artificial neural network using antler beam diameter and length of white-tailed deer (Odocoileus virginianus) dataset

et al. 2019

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Evaluation of harvest data remains one of the most important sources of information in the development of strategies to manage regional populations of white-tailed deer. While descriptive statistics and simple linear models are utilized extensively, the use of artificial neural networks for this type of data analyses is unexplored. Linear model was compared to Artificial Neural Networks (ANN) models with Levenberg–Marquardt (L-M), Bayesian Regularization (BR) and Scaled Conjugate Gradient (SCG) learning algorithms, to evaluate the relative accuracy in predicting antler beam diameter and length using age and dressed body weight in white-tailed deer. Data utilized for this study were obtained from male animals harvested by hunters between 1977–2009 at the Berry College Wildlife Management Area. Metrics for evaluating model performance indicated that linear and ANN models resulted in close match and good agreement between predicted and observed values and thus good performance for all models. However, metrics values of Mean Absolute Error and Root Mean Squared Error for linear model and the ANN-BR model indicated smaller error and lower deviation relative to the mean values of antler beam diameter and length in comparison to other ANN models, demonstrating better agreement of the predicted and observed values of antler beam diameter and length. ANN-SCG model resulted in the highest error within the models. Overall, metrics for evaluating model performance from the ANN model with BR learning algorithm and linear model indicated better agreement of the predicted and observed values of antler beam diameter and length. Results of this study suggest the use of ANN generated results that are comparable to Linear Models of harvest data to aid in the development of strategies to manage white-tailed deer.

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Section: Resultssupporting

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Comparison of linear model and artificial neural network using antler beam diameter and length of white-tailed deer (Odocoileus virginianus) dataset

et al. 2019

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“…During velvet regeneration and development, plasma levels of IGF1 are significantly elevated during the velvet antler growth phase, relative to the other phases of pedicle, as well as first antler development, and a strong positive correlation exists between antler growth rate and circulating concentrations of IGF1 [ 8 ]. The effects of IGF1 on the growth of the fibroblast and cartilage zones were investigated; IGF1 was found to be mitogenic for cells originating from the perichondrium, mesenchyme, and cartilage zone of antler [ 9 , 10 ]. The localization of IGF1 in chondrocytes and osteoblasts also suggests that IGF1 may play an important role in cartilage and bone formation [ 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

The Regulatory Mechanism of MLT/MT1 Signaling on the Growth of Antler Mesenchymal Cells

Yang

Sun

et al. 2017

Molecules

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Melatonin (MLT) plays an important role in regulating the physiological cycle of seasonal breeding animals. Melatonin receptor I (MT1) is effectively expressed in the cambium layer of deer antler. However, the function and metabolic mechanism of MLT/MT1 signaling in the mesenchymal cells of sika deer remain to be further elucidated. In this work, we detected the effects of MLT/MT1 signaling on mesenchymal cells proliferation and the interaction between MLT/MT1 and IGF1/IGF1-R signaling. The results show that (1) deer antler mesenchymal cells actually express MT1; (2) exogenous melatonin significantly promotes mesenchymal cells proliferation, while MT1 knock-down significantly impairs the positive effects of melatonin; and (3) melatonin significantly enhanced IGF1/IGF1-R signaling, as both the expression of IGF1 and IGF-1R increased, while MT1 knock-down significantly decreased IGF1-R expression and IGF1 synthesis. In summary, these data verified that MLT/MT1 signaling plays a crucial role in antler mesenchymal proliferation, which may be mediated by IGF1/IGF1-R.

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“…In addition to this fundamental pursuit, antler measurement is of considerable importance to other scientific investigations focused on determining the effects of systemic hormones and local growth factors (specifically insulin‐like growth factor) on antler growth (Park et al., ), determining the relationship between temperature and antler growth (Bowers et al., ), quantifying the variation of body mass and antler size with animal age and sex (Melnycky et al., ), and identifying the correlation between live weight and first antler development (Ward et al., ). Antler measurement also has several very practical applications with significant economic impact including the identification of sires for breeding (Ward et al., ) and the determination of optimal velvet harvest time (Bowers et al., ).…”

Section: Introductionmentioning

confidence: 99%

The Practical Application Of 3D Vision in the Field: Measuring Reindeer (Rangifer Tarandus) Antler Growth Velocities

Lichti

Steward

Chow

et al. 2016

The Photogrammetric Record

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Advances in three-dimensional (3D) optical imaging have made possible precise and accurate measurements of many scenes, ranging from engineering to architecture to art. However, measurements of some 3D objects are more difficult to obtain than others, particularly if the edges do not feature regular geometry, the colour is dark and variable, and if the object moves haphazardly. Such objects occur regularly in biology, and the present study illustrates some of the challenges of evaluating such objects. The growing antlers of three live reindeer (Rangifer tarandus) is presented as an example of how 3D imaging, specifically time-of-flight range imaging, can be used to solve to a reasonable extent a problem that is very difficult to approximate using traditional techniques. Mean antler growth velocities of the order of 7 to 9 mm/day were estimated, using the proposed methodology, from data of these three animals collected over a seven-week period. ZusammenfassungFortschritte in der 3D-Kameratechnik erlauben pr€ azise Vermessungen vieler Szenen: von Ingenieurwesen € uber Architektur bis zur Kunst. Dennoch sind die Messung einiger 3D Objekte viel schwieriger zu erhalten als andere, insbesondere wenn die Kanten keine regul€ are Geometrie besitzen, die Farbe dunkel ist und variiert oder wenn das Objekt sich willk€ urlich bewegt. Solche Objekte treten oft in biologischen Anwendungen auf und die vorgestellte Studie pr€ asentiert einige der Herausforderungen, um solche Objekte zu evaluieren. DasThe Photogrammetric Record

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Study on the Changes in Enzyme and Insulin-like Growth Factor-1 Concentrations in Blood Serum and Growth Characteristics of Velvet Antler during the Antler Growth Period in Sika Deer (<i>Cervus nippon</i>)

Cited by 5 publications

References 22 publications

Comparison of linear model and artificial neural network using antler beam diameter and length of white-tailed deer (Odocoileus virginianus) dataset

Comparison of linear model and artificial neural network using antler beam diameter and length of white-tailed deer (Odocoileus virginianus) dataset

The Regulatory Mechanism of MLT/MT1 Signaling on the Growth of Antler Mesenchymal Cells

The Practical Application Of 3D Vision in the Field: Measuring Reindeer (Rangifer Tarandus) Antler Growth Velocities

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