There is a pressing need for information on the mobility of nanoparticles in the complex aqueous matrices found in realistic environmental conditions. We dispersed three different metal oxide nanoparticles (TiO(2), ZnO and CeO(2)) in samples taken from eight different aqueous media associated with seawater, lagoon, river, and groundwater, and measured their electrophoretic mobility, state of aggregation, and rate of sedimentation. The electrophoretic mobility of the particles in a given aqueous media was dominated by the presence of natural organic matter (NOM) and ionic strength, and independent of pH. NOM adsorbed onto these nanoparticles significantly reduces their aggregation, stabilizing them under many conditions. The transition from reaction to diffusion limited aggregation occurs at an electrophoretic mobility from around -2 to -0.8 microm s(-1) V(-1) cm. These results are key for designing and interpreting nanoparticle ecotoxicity studies in various environmental conditions.

The aim of this study was to obtain information on the axonal diameters of cortico-cortical fibres in the human brain, connecting distant regions of the same hemisphere via the white matter. Samples for electron microscopy were taken from the region of the superior longitudinal fascicle and from the transitional white matter between temporal and frontal lobe where the uncinate and inferior occipitofrontal fascicle merge. We measured the inner diameter of cross sections of myelinated axons. For comparison with data from the literature on the human corpus callosum, we also took samples from that region. For comparison with well-fixed material, we also included samples from corresponding regions of a monkey brain (Macaca mulatta). Fibre diameters in human brains ranged from 0.16 to 9 . Distributions of diameters were similar in the three systems of cortico-cortical fibres investigated, both in humans and the monkey, with most of the average values below 1 m diameter and a small population of much thicker fibres. Within individual human brains, the averages were larger in the superior longitudinal fascicle than in the transitional zone between temporal and frontal lobe. An asymmetry between left and right could be found in one of the human brains, as well as in the monkey brain. A correlation was also found between the thickness of the myelin sheath and the inner axon diameter for axons whose calibre was greater than about 0.6 . The results are compared to white matter data in other mammals and are discussed with respect to conduction velocity, brain size, cognition, as well as diffusion weighted imaging studies.

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Fiber tracts should use space and energy efficiently, because both resources constrain neural computation. We found for a myelinated tract (optic nerve) that astrocytes use nearly 30% of the space and Ͼ70% of the mitochondria, establishing the significance of astrocytes for the brain's space and energy budgets. Axons are mostly thin with a skewed distribution peaking at 0.7 m, near the lower limit set by channel noise. This distribution is matched closely by the distribution of mean firing rates measured under naturalistic conditions, suggesting that firing rate increases proportionally with axon diameter. In axons thicker than 0.7 m, mitochondria occupy a constant fraction of axonal volume-thus, mitochondrial volumes rise as the diameter squared. These results imply a law of diminishing returns: twice the information rate requires more than twice the space and energy capacity. We conclude that the optic nerve conserves space and energy by sending most information at low rates over fine axons with small terminal arbors and sending some information at higher rates over thicker axons with larger terminal arbors but only where more bits per second are needed for a specific purpose. Thicker axons seem to be needed, not for their greater conduction velocity (nor other intrinsic electrophysiological purpose), but instead to support larger terminal arbors and more active zones that transfer information synaptically at higher rates.

This paper discusses conceptual and methodological issues that arise when educational researchers use data from large-scale, survey research to examine the effects of teachers and teaching on student achievement. Using data from Prospects: The Congressionally Mandated Study of Educational Growth and Opportunity 1991–1994, we show that researchers’ use of different statistical models has led to widely varying interpretations about the overall magnitude of teacher effects on student achievement. However, we conclude that in well-specified models of academic growth, teacher effects on elementary school students’ growth in reading and mathematics achievement are substantial (with d-type effect sizes ranging from .72 to .85). We also conclude that various characteristics of teachers and their teaching account for these effects, including variation among teachers in professional preparation and content knowledge, use of teaching routines, and patterns of content coverage, with effect sizes for variables measuring these characteristics of teachers and their teaching showing d-type effect sizes in the range of .10. The paper concludes with an assessment of the current state of the art in large-scale, survey research on teaching. Here, we conclude that survey researchers must simultaneously improve their measures of instruction while paying careful attention to issues of causal inference.

Traps are a versatile and powerful fishing gear. Desired species and sizes can be targeted through trap design and the choice of bait. Size of the catch is affected by trap size, bait quantity and quality, time between setting and hauling, and preventing escape through the entrance. But the largest potential for increasing trap catches is by increasing ease of entry and reducing the effect of gear saturation (animals inside traps preventing those outside from entering). Using catch per trap as an index of abundance is attractive for both fisheries management and ecological studies. However, correlations between catch and abundance have not been well established, probably because of the many factors affecting catchability (e.g. stage of the molt and reproductive cycles, sex, animal size, lunar and diurnal cycles, temperature, and water motion). Methods for conducting trapping surveys, measuring catchability, and comparing fishing strategies are critically reviewed.

Nanoparticulate titanium dioxide (TiO2) is highly photoactive, and its function as a photocatalyst drives much of the application demand for TiO2. Because TiO2 generates reactive oxygen species (ROS) when exposed to ultraviolet radiation (UVR), nanoparticulate TiO2 has been used in antibacterial coatings and wastewater disinfection, and has been investigated as an anti-cancer agent. Oxidative stress mediated by photoactive TiO2 is the likely mechanism of its toxicity, and experiments demonstrating cytotoxicity of TiO2 have used exposure to strong artificial sources of ultraviolet radiation (UVR). In vivo tests of TiO2 toxicity with aquatic organisms have typically shown low toxicity, and results across studies have been variable. No work has demonstrated that photoactivity causes environmental toxicity of TiO2 under natural levels of UVR. Here we show that relatively low levels of ultraviolet light, consistent with those found in nature, can induce toxicity of TiO2 nanoparticles to marine phytoplankton, the most important primary producers on Earth. No effect of TiO2 on phytoplankton was found in treatments where UV light was blocked. Under low intensity UVR, ROS in seawater increased with increasing nano-TiO2 concentration. These increases may lead to increased overall oxidative stress in seawater contaminated by TiO2, and cause decreased resiliency of marine ecosystems. Phototoxicity must be considered when evaluating environmental impacts of nanomaterials, many of which are photoactive.

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