Near infrared fluorescence (NIRF) spectroscopy is capable of sensitive and selective detection of semiconductive, single-walled carbon nanotubes (SWNT) using the unique electronic bandgap properties of these carbon allotropes. We reported here the first detection and quantitation of SWNT in sediment and biota at environmentally relevant concentrations using NIRF spectroscopy. In addition, we utilized this technique to qualitatively characterize SWNT samples before and after ecotoxicity, bioavailability and fate studies in the aquatic environment. Sample preparation prior to NIRF analysis consisted of surfactant-assisted high power ultrasonication. The bile salt sodium deoxycholate (SDC) enabled efficient extraction and disaggregation of SWNT prior to NIRF analysis. The method was validated using standard-addition experiments in two types of estuarine sediments, yielding recoveries between 66 ± 7% and 103 ± 10% depending on SWNT type and coating used, demonstrating the ability to isolate SWNT from complex sediment matrices. Instrument detection limits were determined to be 15 ng mL(-1) SWNT in 2% SDC solution and method detection limits (including a concentration step) were 62 ng g(-1) for estuarine sediment, and 1.0 μg L(-1) for water. Our work has shown that NIRF spectroscopy is highly sensitive and selective for SWNT and that this technique can be applied to track the environmental and biological fate of this important class of carbon nanomaterial in the aquatic environment.

Detection of SWCNTs in complex matrices presents a unique challenge as common techniques lack spatial resolution and specificity. Near infrared fluorescence (NIRF) has emerged as a valuable tool for detecting and quantifying SWCNTs in environmental samples by exploiting their innate fluorescent properties. The objective of this study was to optimize NIRF-based imaging and quantitation methods for tracking and quantifying SWCNTs in an aquatic vertebrate model in conjunction with assessing toxicological end points. Fathead minnows (Pimephales promelas) were exposed by single gavage to SWCNTs and their distribution was tracked using a custom NIRF imaging system for 7 days. No overt toxicity was observed in any of the SWCNT treated fish; however, histopathology observations from gastrointestinal (GI) tissue revealed edema within the submucosa and altered mucous cell morphology. NIRF images showed strong SWCNT-derived fluorescence signals in whole fish and excised intestinal tissues. Fluorescence was not detected in other tissues examined, indicating that no appreciable intestinal absorption occurred. SWCNTs were quantified in intestinal tissues using a NIRF spectroscopic method revealing values that were consistent with the pattern of fluorescence observed with NIRF imaging. Results of this work demonstrate the utility of NIRF imaging as a valuable tool for examining uptake and distribution of SWCNTs in aquatic vertebrates.

This Critcal Review evaluates passive sampler uptake of hydrophobic organic contaminants (HOCs) in water column and interstitial water exposures as a surrogate for organism bioaccumulation. Fifty-seven studies were found where both passive sampler uptake and organism bioaccumulation were measured and 19 of these investigations provided direct comparisons relating passive sampler uptake and organism bioaccumulation. Polymers compared included low-density polyethylene (LDPE), polyoxymethylene (POM), and polydimethylsiloxane (PDMS), and organisms ranged from polychaetes and oligochaetes to bivalves, aquatic insects, and gastropods. Regression equations correlating bioaccumulation (C) and passive sampler uptake (C) were used to assess the strength of observed relationships. Passive sampling based concentrations resulted in log-log predictive relationships, most of which were within one to 2 orders of magnitude of measured bioaccumulation. Mean coefficients of determination (r) for LDPE, PDMS, and POM were 0.68, 0.76, and 0.58, respectively. For the available raw, untransformed data, the mean ratio of C and C was 10.8 ± 18.4 (n = 609). Using passive sampling as a surrogate for organism bioaccumulation is viable when biomonitoring organisms are not available. Passive sampling based estimates of bioaccumulation provide useful information for making informed decisions about the bioavailability of HOCs.

One of the enduring questions that has driven neuroscientific enquiry in the last century has been the nature of differences in the prefrontal cortex of humans versus other animals [1]. The prefrontal cortex has drawn particular interest due to its role in a range of evolutionarily specialized cognitive capacities such as language [2], imagination [3], and complex decision making [4]. Both cytoarchitectonic [5] and comparative neuroimaging [6] studies have converged on the conclusion that the proportion of prefrontal cortex in the human brain is greatly increased relative to that of other primates. However, considering the tremendous overall expansion of the neocortex in human evolution, it has proven difficult to ascertain whether this extent of prefrontal enlargement follows general allometric growth patterns, or whether it is exceptional [1]. Species' adherence to a common allometric relationship suggests conservation through phenotypic integration, while species' deviations point toward the occurrence of shifts in genetic and/or developmental mechanisms. Here we investigate prefrontal cortex scaling across anthropoid primates and find that great ape and human prefrontal cortex expansion are non-allometrically derived features of cortical organization. This result aligns with evidence for a developmental heterochronic shift in human prefrontal growth [7, 8], suggesting an association between neurodevelopmental changes and cortical organization on a macroevolutionary scale. The evolutionary origin of non-allometric prefrontal enlargement is estimated to lie at the root of great apes (∼19-15 mya), indicating that selection for changes in executive cognitive functions characterized both great ape and human cortical organization.

In this article, we unintentionally omitted to expand on a citation of previously published results. In the caption of Figure 2, we stated that ''F and p values indicate the significance of a phylogenetic ANCOVA testing for intercept differences between humans and other primates (see also Smaers and Rohlf [9], Supplemental Information..., and Table S2 for more detailed results)'' (p. 716). We would like to clarify that in this statement, ''see also Smaers and Rohlf'' refers, specifically and exclusively, to the phylogenetic ANCOVA of primate prefrontal cortex to primary visual cortex and frontal motor areas using the Smaers dataset in [9]. These results were depicted in a subsection of our Figure 2 (the two top left regression plots) and were numerically presented in a subsection of our Table S2. Smaers and Rohlf presented these results as an empirical example when describing the least-squares solution of phylogenetic ANCOVA and did not discuss the wider biological implications of these results for primate brain evolution. The presentation of the previous results was discussed openly during the review process of this manuscript. The authors apologize for any confusion this oversight may have caused.