How and why to measure the germination process?

In the last two centuries, papers have been published including measurements of the germination process. High diversity of mathematical expressions has made comparisons between papers and some times the interpretation of results difficult. Thus, in this paper is included a review about measurements of the germination process, with an analysis of the several mathematical expressions included in the specific literature, recovering the history, sense, and limitations of some germination measurements. Among the measurements included in this paper are the germinability, germination time, coefficient of uniformity of germination (CUG), coefficient of variation of the germination time (CVt), germination rate (mean rate, weighted mean rate, coefficient of velocity, germination rate of George, Timson’s index, GV or Czabator’s index; Throneberry and Smith’s method and its adaptations, including Maguire’s rate; ERI or emergence rate index, germination index, and its modifications), uncertainty associated to the distribution of the relative frequency of germination (U), and synchronization index (Z). The limits of the germination measurements were included to make the interpretation and decisions during comparisons easier. Time, rate, homogeneity, and synchrony are aspects that can be measured, informing the dynamics of the germination process. These characteristics are important not only for physiologists and seed technologists, but also for ecologists because it is possible to predict the degree of successful of a species based on the capacity of their harvest seed to spread the germination through time, permitting the recruitment in the environment of some part of the seedlings formed.

One hundred million years of interhemispheric communication: the history of the corpus callosum

Analysis of regional corpus callosum fiber composition reveals that callosal regions connecting primary and secondary sensory areas tend to have higher proportions of coarse-diameter, highly myelinated fibers than callosal regions connecting so-called higher-order areas. This suggests that in primary/secondary sensory areas there are strong timing constraints for interhemispheric communication, which may be related to the process of midline fusion of the two sensory hemifields across the hemispheres. We postulate that the evolutionary origin of the corpus callosum in placental mammals is related to the mechanism of midline fusion in the sensory cortices, which only in mammals receive a topographically organized representation of the sensory surfaces. The early corpus callosum may have also served as a substrate for growth of fibers connecting higher-order areas, which possibly participated in the propagation of neuronal ensembles of synchronized activity between the hemispheres. However, as brains became much larger, the increasingly longer interhemispheric distance may have worked as a constraint for efficient callosal transmission. Callosal fiber composition tends to be quite uniform across species with different brain sizes, suggesting that the delay in callosal transmission is longer in bigger brains. There is only a small subset of large-diameter callosal fibers whose size increases with increasing interhemispheric distance. These limitations in interhemispheric connectivity may have favored the development of brain lateralization in some species like humans. "...if the currently received statements are correct, the appearance of the corpus callosum in the placental mammals is the greatest and most sudden modification exhibited by the brain in the whole series of vertebrated animals..." T.H. Huxley (1).

A simple model for circadian timing by mammals

Circadian timing is structured in such a way as to receive information from the external and internal environments, and its function is the timing organization of the physiological and behavioral processes in a circadian pattern. In mammals, the circadian timing system consists of a group of structures, which includes the suprachiasmatic nucleus (SCN), the intergeniculate leaflet and the pineal gland. Neuron groups working as a biological pacemaker are found in the SCN, forming a biological master clock. We present here a simple model for the circadian timing system of mammals, which is able to reproduce two fundamental characteristics of biological rhythms: the endogenous generation of pulses and synchronization with the light-dark cycle. In this model, the biological pacemaker of the SCN was modeled as a set of 1000 homogeneously distributed coupled oscillators with long-range coupling forming a spherical lattice. The characteristics of the oscillator set were defined taking into account the Kuramoto's oscillator dynamics, but we used a new method for estimating the equilibrium order parameter. Simultaneous activities of the excitatory and inhibitory synapses on the elements of the circadian timing circuit at each instant were modeled by specific equations for synaptic events. All simulation programs were written in Fortran 77, compiled and run on PC DOS computers. Our model exhibited responses in agreement with physiological patterns. The values of output frequency of the oscillator system (maximal value of 3.9 Hz) were of the order of magnitude of the firing frequencies recorded in suprachiasmatic neurons of rodents in vivo and in vitro (from 1.8 to 5.4 Hz).