Allocation of 14C assimilated in late spring to tissue and biochemical stem components of cork oak (Quercus suber L.) over the seasons

Carbon distribution in the stem of 2-year-old cork oak plants was studied by 14CO2 pulse labeling in late spring in order to trace the allocation of photoassimilates to tissue and biochemical stem components of cork oak. The fate of 14C photoassimilated carbon was followed during two periods: the first 72 h (short-term study) and the first 52 weeks (long-term study) after the 14CO2 photosynthetic assimilation. The results showed that 14C allocation to stem tissues was dependent on the time passed since photoassimilation and on the season of the year. In the first 3 h all 14C was found in the polar extractives. After 3 h, it started to be allocated to other stem fractions. In 1 day, 14C was allocated mostly to vascular cambium and, to a lesser extent, to primary phloem; no presence of 14C was recorded for the periderm. However, translocation of 14C to phellem was observed from 1 week after 14CO2 pulse labeling. The phellogen was not completely active in its entire circumference at labeling, unlike the vascular cambium; this was the tissue that accumulated most photoassimilated 14C at the earliest sampling. The fraction of leaf-assimilated 14C that was used by the stem peaked at 57% 1 week after 14CO2 plant exposure. The time lag between C photoassimilation and suberin accumulation was ∼8 h, but the most active period for suberin accumulation was between 3 and 7 days. Suberin, which represented only 1.77% of the stem weight, acted as a highly effective sink for the carbon photoassimilated in late spring since suberin specific radioactivity was much higher than for any other stem component as early as only 1 week after 14C plant labeling. This trend was maintained throughout the whole experiment. The examination of microautoradiographs taken over 1 year provided a new method for quantifying xylem growth. Using this approach it was found that there was more secondary xylem growth in late spring than in other times of the year, because the calculated average cell division time was much shorter.

Three-dimensional distribution of cortical synapses: a replicated point pattern-based analysis

The biggest problem when analyzing the brain is that its synaptic connections are extremely complex. Generally, the billions of neurons making up the brain exchange information through two types of highly specialized structures: chemical synapses (the vast majority) and so-called gap junctions (a substrate of one class of electrical synapse). Here we are interested in exploring the three-dimensional spatial distribution of chemical synapses in the cerebral cortex. Recent research has showed that the three-dimensional spatial distribution of synapses in layer III of the neocortex can be modeled by a random sequential adsorption (RSA) point process, i.e., synapses are distributed in space almost randomly, with the only constraint that they cannot overlap. In this study we hypothesize that RSA processes can also explain the distribution of synapses in all cortical layers. We also investigate whether there are differences in both the synaptic density and spatial distribution of synapses between layers. Using combined focused ion beam milling and scanning electron microscopy (FIB/SEM), we obtained three-dimensional samples from the six layers of the rat somatosensory cortex and identified and reconstructed the synaptic junctions. A total volume of tissue of approximately 4500μm3 and around 4000 synapses from three different animals were analyzed. Different samples, layers and/or animals were aggregated and compared using RSA replicated spatial point processes. The results showed no significant differences in the synaptic distribution across the different rats used in the study. We found that RSA processes described the spatial distribution of synapses in all samples of each layer. We also found that the synaptic distribution in layers II to VI conforms to a common underlying RSA process with different densities per layer. Interestingly, the results showed that synapses in layer I had a slightly different spatial distribution from the other layers.