Broad Anatomical Variation within a Narrow Wood Density Range—A Study of Twig Wood across 69 Australian Angiosperms

ObjectivesJust as people with the same weight can have different body builds, woods with the same wood density can have different anatomies. Here, our aim was to assess the magnitude of anatomical variation within a restricted range of wood density and explore its potential ecological implications.MethodsTwig wood of 69 angiosperm tree and shrub species was analyzed. Species were selected so that wood density varied within a relatively narrow range (0.38–0.62 g cm^-3). Anatomical traits quantified included wood tissue fractions (fibres, axial parenchyma, ray parenchyma, vessels, and conduits with maximum lumen diameter below 15 μm), vessel properties, and pith area. To search for potential ecological correlates of anatomical variation the species were sampled across rainfall and temperature contrasts, and several other ecologically-relevant traits were measured (plant height, leaf area to sapwood area ratio, and modulus of elasticity).ResultsDespite the limited range in wood density, substantial anatomical variation was observed. Total parenchyma fraction varied from 0.12 to 0.66 and fibre fraction from 0.20 to 0.74, and these two traits were strongly inversely correlated (r = -0.86, P < 0.001). Parenchyma was weakly (0.24 ≤|r|≤ 0.35, P < 0.05) or not associated with vessel properties nor with height, leaf area to sapwood area ratio, and modulus of elasticity (0.24 ≤|r|≤ 0.41, P < 0.05). However, vessel traits were fairly well correlated with height and leaf area to sapwood area ratio (0.47 ≤|r|≤ 0.65, all P < 0.001). Modulus of elasticity was mainly driven by fibre wall plus vessel wall fraction rather than by the parenchyma component.ConclusionsOverall, there seem to be at least three axes of variation in xylem, substantially independent of each other: a wood density spectrum, a fibre-parenchyma spectrum, and a vessel area spectrum. The fibre-parenchyma spectrum does not yet have any clear or convincing ecological interpretation.     

Data-Driven Method to Estimate Nonlinear Chemical Equivalence

There is great need to express the impacts of chemicals found in the environment in terms of effects from alternative chemicals of interest. Methods currently employed in fields such as life-cycle assessment, risk assessment, mixtures toxicology, and pharmacology rely mostly on heuristic arguments to justify the use of linear relationships in the construction of “equivalency factors,” which aim to model these concentration-concentration correlations. However, the use of linear models, even at low concentrations, oversimplifies the nonlinear nature of the concentration-response curve, therefore introducing error into calculations involving these factors. We address this problem by reporting a method to determine a concentration-concentration relationship between two chemicals based on the full extent of experimentally derived concentration-response curves. Although this method can be easily generalized, we develop and illustrate it from the perspective of toxicology, in which we provide equations relating the sigmoid and non-monotone, or “biphasic,” responses typical of the field. The resulting concentration-concentration relationships are manifestly nonlinear for nearly any chemical level, even at the very low concentrations common to environmental measurements. We demonstrate the method using real-world examples of toxicological data which may exhibit sigmoid and biphasic mortality curves. Finally, we use our models to calculate equivalency factors, and show that traditional results are recovered only when the concentration-response curves are “parallel,” which has been noted before, but we make formal here by providing mathematical conditions on the validity of this approach.     

Structure-function analysis of the rat prolactin promoter: phasing requirements of proximal cell-specific elements

Expression of PRL, a member of the GH family of genes, is restricted to the lactotroph cells of the anterior pituitary. The proximal promoter of the rat PRL (rPRL) gene contains four factor-binding sites. Three nonadjacent elements, footprints (FP) I, III, and IV, are separated by an integral number of helical turns and bind a pituitary-specific factor, LSF-1. FP II binds another factor present in pituitary and nonpituitary cells. The mechanisms by which DNA-bound proteins influence RNA polymerase-II activity over large distances are not fully understood, but protein-protein interactions, with looping of intervening DNA, may bring distant sites into close proximity. Here, we demonstrate, using protein titration studies, that LSF-1 binds to the most proximal FP I element with the highest affinity, whereas it binds the more distal elements, FP III and FP IV, with progressively lower affinities. Time-course and salt-sensitivity studies reveal that binding of LSF-1 to all three pituitary-specific rPRL promoter sites occurs rapidly (less than or equal to 1 min) and requires fairly high salt concentrations (greater than or equal to 300 mM KCl) to destabilize protein-DNA interactions. Moreover, once bound, the pituitary nuclear factor(s) induces a conformational change in rPRL DNA structure with greatly delayed kinetics (greater than 15 min) and at a different salt concentration than are required for simply factor binding. Taken together, these data suggest a model in which LSF-1 initially binds fairly rapidly to multiple nonadjacent elements and then interacts with itself or other DNA-bound proteins much more slowly, possibly looping or bending the rPRL promoter.(ABSTRACT TRUNCATED AT 250 WORDS)