Video-rate molecular imaging in vivo with stimulated Raman scattering

Optical imaging in vivo with molecular specificity is important in biomedicine because of its high spatial resolution and sensitivity compared with magnetic resonance imaging. Stimulated Raman scattering (SRS) microscopy allows highly sensitive optical imaging based on vibrational spectroscopy without adding toxic or perturbative labels. However, SRS imaging in living animals and humans has not been feasible because light cannot be collected through thick tissues, and motion-blur arises from slow imaging based on backscattered light. In this work, we enable in vivo SRS imaging by substantially enhancing the collection of the backscattered signal and increasing the imaging speed by three orders of magnitude to video rate. This approach allows label-free in vivo imaging of water, lipid, and protein in skin and mapping of penetration pathways of topically applied drugs in mice and humans.     

Clonal stability in <Emphasis Type="Italic">Pinus radiata</Emphasis> across New Zealand and Australia. I. Growth and form traits

To investigate genotype by environment interaction (G×E) for clones of radiata pine (Pinus radiata), clonal stability was evaluated for growth and form traits from three trials in New Zealand and three trials in Australia. There were 215–245 clones in common between pairs of New Zealand trials, 17–26 clones in common among Australian trials, while 32–52 clones were in common between New Zealand and Australian sites. Clonal repeatability ( [^(H)]² ) \left( {\hat{H}^{2} } \right) and type-B genetic correlations were estimated. The general trend across the six trials for clonal repeatability was that [^(H)]² \hat{H}^{2} was greatest for height (HGT) followed by diameter at breast height (DBH), stem straightness (STR), and branch quality score (BRQ). Within New Zealand trials, there was little evidence of G×E for growth traits, but more for form traits. For DBH the average type-B genetic correlation within New Zealand was 0.82; and for HGT, the average type-B genetic correlation within New Zealand was 0.76. Within Australia, there was only one statistically significant type-B genetic correlation for DBH and this estimate was high indicating that clonal ranks were similar on these two trials. Additionally, within Australia and between regions type-B genetic correlations were generally high for form traits, at least for STR. One Australian trial (Trial 5) showed relatively high clonal stability with the three trials in New Zealand indicating that the ranks of these clones were relatively stable in both regions. From a clonal testing standpoint, these results suggest that stable clones can be identified that perform well in both New Zealand and Australia. Improvements in both growth and form traits can be expected when radiata pine clones are transferred between Australia and New Zealand within regions similar to those sampled in this trial series.     

Impact of different isolation procedures on the functionality of zein and kafirin

Commercial corn prolamin (zein) aggregates in water at elevated temperatures into an extensible, viscoelastic gluten-like substance. This specific functionality of zein can be used in the production of gluten-free bread from true dough systems and not from batters. The present study examined laboratory-scale isolation of such functional zein from dry milled corn. RP-HPLC indicated that successful isolation procedures resulted in relatively pure α-zeins, with a maximum ratio of (β + γ)/α-zeins of about 10%. In the present study, such functional zeins were obtained by using 70% ethanol as the extractant, without added alkali or reducing agent in the main extraction step. In contrast, films could be cast from a wider range of zein isolates, also with higher ratios of (β + γ)/α-zeins. Isolation of the analogous prolamin (kafirin) from dry milled sorghum required a more hydrophobic extractant such as 83% isopropanol to achieve partial functionality. Such kafirin was able to aggregate in warm water, preferably when a reducing agent was added; however, it quickly became firm and lost its extensibility. The present study suggests that hydrophobic interactions rather than disulfide bonds are the key to gluten-like functionality of zein and kafirin.     

Multivariate correlations between imagery and field measurements across scales: comparing pixel aggregation and image segmentation

To successfully use remotely-sensed data in landscape-level management, questions as to the relevance of image data to landscape patterns and optimal scales of analysis must be addressed. Object-based image analysis, segmenting images into homogeneous regions called objects, has been suggested for increasing accuracy of remotely-sensed products, but little research has gone into determining image object size with regard to scaling of ecosystem properties. We looked at how segmentation of high-resolution Ikonos and medium-resolution Landsat images into successively coarser objects affected multivariate correlations between image data and eight percent-cover measurements of a sagebrush ecosystem. We also looked at changes in correlation as imagery was aggregated into larger square pixels. We found similar canonical correlations between field and image data at the finest scales, but higher for image segmentation than pixel aggregation for both images when scale increased. For image segmentation, correlations between the canonical variables and original field variables were invariant with respect to size of the image objects, suggesting linear scaling of vegetation cover in our study system. We detected a scaling threshold with the Ikonos segmentation and confirmed with a semi-variogram of the sample data. Below the threshold interpretation of the canonical variables was consistent: scale levels differed primarily in the amount of detail portrayed. Above the threshold, meaning of the canonical variables changed. This approach proved useful for evaluating overall utility of images to address an objective, and identified scaling limits for analysis. Selection of appropriate scale for analysis will ultimately depend on the objective being considered.     

Productivity benefits of selectively breeding Black Tiger shrimp (Penaeus monodon) in Australia

Advances in the domestication and selective breeding of Australian Black Tiger shrimp, Penaeus monodon, opens the opportunity for world producers to reconsider the benefits of farming this species. Just over a decade ago this species was the world's most farmed shrimp species, however, difficulty in its domestication, in part, led to the widespread establishment of Penaeus vannamei (Pacific White shrimp) as the most farmed shrimp species in the world. This study empirically evaluates the productivity benefits of commercially domesticating P. monodon against production from wild broodstock of the same species. The evaluation compared the relative production from commercial ponds stocked with the progeny of wild P. monodon broodstock and ponds stocked with the progeny of domesticated stocks. The production data were from 164 ponds of domesticated stocks and 30 ponds of wild stocks, collected over 4 years (2009–2013) from two separate farm sites of the same Australian shrimp farming company. The wild stocks were sourced from the east coast of Australia. The results suggested that the productivity of the selectively bred stocks was 39% greater compared with production from wild stocks given equivalent amounts of feed and other inputs. Furthermore, productivity was additionally enhanced depending on the choice of feeds and whether stocking took place in September rather than later in the year (i.e. in early spring rather than late spring/early summer in the Southern hemisphere). This suggests that there is significant potential to further enhance the productivity of P. monodon farms via integrating advances in domestication, feeds and management practices.     

Ecosystem models for fisheries management: finding the sweet spot

The advent of an ecosystem‐based approach dramatically expanded the scope of fisheries management, creating a critical need for new kinds of data and quantitative approaches that could be integrated into the management system. Ecosystem models are needed to codify the relationships among drivers, pressures and resulting states, and to quantify the trade‐offs between conflicting objectives. Incorporating ecosystem considerations requires moving from the single‐species models used in stock assessments, to more complex models that include species interactions, environmental drivers and human consequences. With this increasing model complexity, model fit can improve, but parameter uncertainty increases. At intermediate levels of complexity, there is a ‘sweet spot’ at which the uncertainty in policy indicators is at a minimum. Finding the sweet spot in models requires compromises: for example, to include additional component species, the models of each species have in some cases been simplified from age‐structured to logistic or bioenergetic models. In this paper, we illuminate the characteristics, capabilities and short‐comings of the various modelling approaches being proposed for ecosystem‐based fisheries management. We identify key ecosystem needs in fisheries management and indicate which types of models can meet these needs. Ecosystem models have been playing strategic roles by providing an ecosystem context for single‐species management decisions. However, conventional stock assessments are being increasingly challenged by changing natural mortality rates and environmentally driven changes in productivity that are observed in many fish stocks. Thus, there is a need for more tactical ecosystem models that can respond dynamically to changing ecological and environmental conditions.