Source and Magnitude of Ammonium Generation in Maize Roots1

Studies with 15N indicate that appreciable generation of NH4+ from endogenous sources accompanies the uptake and assimilation of exogenous NH4+ by roots. To identify the source of NH4+ generation, maize (Zea mays L.) seedlings were grown on 14NH4+ and then exposed for 3 d to highly labeled 15NH4+. More of the entering 15NH4+ was incorporated into the protein-N fraction of roots in darkness (approximately 25%) than in the light (approximately 14%). Although the 14NH4+ content of roots declined rapidly to less than 1 μmol per plant, efflux of 14NH4+ continued throughout the 3-d period at an average daily rate of 14 μmol per plant. As a consequence, cumulative 14NH4+ efflux during the 3-d period accounted for 25% of the total 14N initially present in the root. Although soluble organic 14N in roots declined during the 3-d period, insoluble 14N remained relatively constant. In shoots both soluble organic 14N and 14NH4+ declined, but a comparable increase in insoluble 14N was noted. Thus, total 14N in shoots remained constant, reflecting little or no net redistribution of 14N between shoots and roots. Collectively, these observations reveal that catabolism of soluble organic N, not protein N, is the primary source of endogenous NH4+ generation in maize roots.

Hypothesis testing and earthquake prediction.

Requirements for testing include advance specification of the conditional rate density (probability per unit time, area, and magnitude) or, alternatively, probabilities for specified intervals of time, space, and magnitude. Here I consider testing fully specified hypotheses, with no parameter adjustments or arbitrary decisions allowed during the test period. Because it may take decades to validate prediction methods, it is worthwhile to formulate testable hypotheses carefully in advance. Earthquake prediction generally implies that the probability will be temporarily higher than normal. Such a statement requires knowledge of "normal behavior"--that is, it requires a null hypothesis. Hypotheses can be tested in three ways: (i) by comparing the number of actual earth-quakes to the number predicted, (ii) by comparing the likelihood score of actual earthquakes to the predicted distribution, and (iii) by comparing the likelihood ratio to that of a null hypothesis. The first two tests are purely self-consistency tests, while the third is a direct comparison of two hypotheses. Predictions made without a statement of probability are very difficult to test, and any test must be based on the ratio of earthquakes in and out of the forecast regions.

Brain localization for arbitrary stimulus categories: a simple account based on Hebbian learning.

A central theme of cognitive neuroscience is that different parts of the brain perform different functions. Recent evidence from neuropsychology suggests that even the processing of arbitrary stimulus categories that are defined solely by cultural conventions (e.g., letters versus digits) can become spatially segregated in the cerebral cortex. How could the processing of stimulus categories that are not innate and that have no inherent structural differences become segregated? We propose that the temporal clustering of stimuli from a given category interacts with Hebbian learning to lead to functional localization. Neural network simulations bear out this hypothesis.

On the magnitude of the electrostatic contribution to ligand-DNA interactions.

A model based on the nonlinear Poisson-Boltzmann equation is used to study the electrostatic contribution to the binding free energy of a simple intercalating ligand, 3,8-diamino-6-phenylphenanthridine, to DNA. We find that the nonlinear Poisson-Boltzmann model accurately describes both the absolute magnitude of the pKa shift of 3,8-diamino-6-phenylphenanthridine observed upon intercalation and its variation with bulk salt concentration. Since the pKa shift is directly related to the total electrostatic binding free energy of the charged and neutral forms of the ligand, the accuracy of the calculations implies that the electrostatic contributions to binding are accurately predicted as well. Based on our results, we have developed a general physical description of the electrostatic contribution to ligand-DNA binding in which the electrostatic binding free energy is described as a balance between the coulombic attraction of a ligand to DNA and the disruption of solvent upon binding. Long-range coulombic forces associated with highly charged nucleic acids provide a strong driving force for the interaction of cationic ligands with DNA. These favorable electrostatic interactions are, however, largely compensated for by unfavorable changes in the solvation of both the ligand and the DNA upon binding. The formation of a ligand-DNA complex removes both charged and polar groups at the binding interface from pure solvent while it displaces salt from around the nucleic acid. As a result, the total electrostatic binding free energy is quite small. Consequently, nonpolar interactions, such as tight packing and hydrophobic forces, must play a significant role in ligand-DNA stability.