A flexible sigmoid function of determinate growth

A new empirical equation for the sigmoid pattern of determinate growth, 'the beta growth function', is presented. It calculates weight (w) in dependence of time, using the following three parameters: t(m), the time at which the maximum growth rate is obtained; t(e), the time at the end of growth; and w(max), the maximal value for w, which is achieved at t(e). The beta growth function was compared with four classical (logistic, Richards, Gompertz and Weibull) growth equations, and two expolinear equations. All equations described successfully the sigmoid dynamics of seed filling, plant growth and crop biomass production. However, differences were found in estimating w(max). Features of the beta function are: (1) like the Richards equation it is flexible in describing various asymmetrical sigmoid patterns (its symmetrical form is a cubic polynomial); (2) like the logistic and the Gompertz equations its parameters are numerically stable in statistical estimation; (3) like the Weibull function it predicts zero mass at time zero, but its extension to deal with various initial conditions can be easily obtained; (4) relative to the truncated expolinear equation it provides more reasonable estimates of final quantity and duration of a growth process. In addition, the new function predicts a zero growth rate at both the start and end of a precisely defined growth period. Therefore, it is unique for dealing with determinate growth, and is more suitable than other functions for embedding in process-based crop simulation models to describe the dynamics of organs as sinks to absorb assimilates. Because its parameters correspond to growth traits of interest to crop scientists, the beta growth function is suitable for characterization of environmental and genotypic influences on growth processes. However, it is not suitable for estimating maximum relative growth rate to characterize early growth that is expected to be close to exponential.     

Comparative study of four sigmoid models of pressure-volume curve in acute lung injury

Background  

The pressure-volume curve of the respiratory system is a tool to monitor and set mechanical ventilation in acute lung injury. Mathematical models of the static pressure-volume curve of the respiratory system have been proposed to overcome the inter- and intra-observer variability derived from eye-fitting. However, different models have not been compared.     

Effect of hyperoxia on the oxyhemoglobin dissociation curve in various periods of aging

Gas composition of the arterial and venous blood and the oxyhemoglobin dissociation curve were determined before and after 20 minutes of oxygen inhalation in 9 apparently healthy subjects aged 60 to 74 years and in 9 young subjects aged 19 to 32 years. In hyperoxia of younger subjects, there was a shift to the left of both the oxyhemoglobin dissociation curve of the native blood and standard dissociation curve (pH 7.4). In old age, the shift to the left of the standard dissociation curve due to hypoxia was quite negligible and statistically insignificant, whereas in the native blood it was entirely absent because of the increased blood PCO2 and associated Bohr effect.     

Protein aggregation as a paradigm of aging

The process of physiological decline leading to death of the individual is driven by the deteriorating capacity to withstand extrinsic and intrinsic hazards, resulting in damage accumulation with age. The dynamic changes with time of the network governing the outcome of misfolded proteins, exemplifying as intrinsic hazards, is considered here as a paradigm of aging. The main features of the network, namely, the non-linear increase of damage and the presence of amplifying feedback loops within the system are presented through a survey of the different components of the network and related cellular processes in aging and disease.