The present studies were designed to establish male rat models of weight gain induced by chronic and acute treatment with antipsychotics.
It was established that a higher proportion of BuA makes the model of weight fraction of polymer Wp in the particle more suitable for simulating the gel effect on the propagation rate coefficient kp.
The objective of this study was to distinguish the role of specific estrogen receptors (ERs), ERα and ERβ, on body weight regulation using a rat model of weight gain subsequent to menopause.
A second limitation here is the model of weight progression.
We constructed a mathematical model of weight loss under total starvation using the established principles of energy balance.
Prepregnancy height was self-reported, and prepregnancy weight was estimated from models of weight gain during pregnancy; however, predicted and self-reported weight were highly correlated.
None of the previous models of weight loss or survival time during starvation have been validated against actual data beyond 30 days of starvation (Hall, 2006; Hall, 2011; Hall, 2012).
Aside from changes indicated above, I have made the following changes to the Discussion: 1) Deleted Figure 9 showing the graphical output of Hall et al. (2011) dynamic model of weight gains in a female and a male.
In the models suggested by Speakman (Speakman, 2007; Speakman, 2008) called the 'drifty gene' hypothesis, it is suggested that early in hominin evolution we probably had a very strictly controlled regulation of body weight and that excessive adiposity was selected against by the risk of predation [see also different models of weight regulation in Speakman et al. (Speakman et al., 2011)].
In the models of weight and tarsus length, this single environmental variable appeared to drive the overall pattern in each case: there was a strong negative relationship between weight and Bio1: mean temperature (linear regression, r = 0.70, p < 0.001, Figure 3a), and a strong positive relationship between tarsus length and percent tree cover (linear regression, r = 0.41, p < 0.001, Figure 3b).
