Retinal development and ommin pigment in the cranchiid squid Teuthowenia pellucida (Cephalopoda: Oegopsida)

The cranchiid Teuthowenia pellucida, like many deep-sea squid species, possesses large eyes that maximise light sensitivity in a nearly aphotic environment. To assess ontogenetic changes in the visual system, we conducted morphometric and histological analyses of the eyes using specimens from New Zealand collections. While the ratio between eye diameter and mantle length maintained a linear relationship throughout development, histological sections of the retina revealed that the outer photoreceptor layer became proportionally longer as the animal aged, coincident with a habitat shift into deeper, darker ocean strata. Other retinal layers maintained the same absolute thickness as was observed in paralarvae. Granules of the pigment ommin, normally located in the screening layer positioned at the base of the photoreceptors, were also observed at the outer end of the photoreceptor segments throughout the retina in young and mid-sized specimens. Early developmental stages of this species, dwelling in shallow waters, may therefore rely on migratory ommin to help shield photoreceptors from excess light and prevent over-stimulation. The oldest, deeper-dwelling specimens of T. pellucida examined had longer photoreceptors, and little or no migrated ommin was observed; we suggest therefore that short-term adaptive mechanisms for bright light conditions may be used primarily during epipelagic, early life stages in this species

Blockade of lymphotoxin-beta receptor signaling reduces aspects of Sjögren's syndrome in salivary glands of non-obese diabetic mice

Introduction The lymphotoxin-beta receptor (LTβR) pathway is important in the development and maintenance of lymphoid structures. Blocking this pathway has proven beneficial in murine models of autoimmune diseases such as diabetes and rheumatoid arthritis. The aim of this study was to determine the effects of LTβR pathway blockade on Sjögren syndrome (SS)-like salivary gland disease in non-obese diabetic (NOD) mice. Methods The course of SS-like disease was followed in NOD mice that were given lymphotoxin-beta receptor-immunoglobulin fusion protein (LTβR-Ig) starting at 9 weeks of age. Treatment was given as a single weekly dose for 3, 7, or 10 weeks. Age-matched NOD mice treated with mouse monoclonal IgG1, or not treated at all, were used as controls. The severity of inflammation, cellular composition, and lymphoid neogenesis in the submandibular glands were determined by immunohistochemistry. Mandibular lymph nodes were also studied. Saliva flow rates were measured, and saliva was analyzed by a multiplex cytokine assay. The salivary glands were analyzed for CXCL13, CCL19, and CCL21 gene expression by quantitative polymerase chain reaction. Results Treatment with LTβR-Ig prevented the increase in size and number of focal infiltrates normally observed in this SS-like disease. Compared with the controls, the submandibular glands of LTβR-Ig-treated mice had fewer and smaller T- and B-cell zones and fewer high endothelial venules per given salivary gland area. Follicular dendritic cell networks were lost in LTβR-Ig-treated mice. CCL19 expression was also dramatically inhibited in the salivary gland infiltrates. Draining lymph nodes showed more gradual changes after LTβR-Ig treatment. Saliva flow was partially restored in mice treated with 10 LTβR-Ig weekly injections, and the saliva cytokine profile of these mice resembled that of mice in the pre-disease state. Conclusions Our findings show that blocking the LTβR pathway results in ablation of the lymphoid organization in the NOD salivary glands and thus an improvement in salivary gland function

Coincidence between transcriptome analyses on different microarray platforms using a parametric framework

A parametric framework for the analysis of transcriptome data is demonstrated to yield coincident results when applied to data acquired using two different microarray platforms. Discrepancies among transcriptome studies are frequently reported, casting doubt on the reliability of collected data. The inconsistency among observations can be largely attributed to differences among the analytical frameworks employed for data analysis. The existing frameworks normalizes data against a standard determined from the data to be analyzed. In the present study, a parametric framework based on a strict model for normalization is applied to data acquired using an in-house printed chip and GeneChip. The framework is based on a common statistical characteristic of microarray data, and each data is normalized on the basis of a linear relationship with this model. In the proposed framework, the expressional changes observed and genes selected are coincident between platforms, achieving superior universality of data compared to other methods

Canopy nitrogen, carbon assimilation, and albedo in temperate and boreal forests: Functional relations and potential climate feedbacks

The availability of nitrogen represents a key constraint on carbon cycling in terrestrial ecosystems, and it is largely in this capacity that the role of N in the Earth\u27s climate system has been considered. Despite this, few studies have included continuous variation in plant N status as a driver of broad-scale carbon cycle analyses. This is partly because of uncertainties in how leaf-level physiological relationships scale to whole ecosystems and because methods for regional to continental detection of plant N concentrations have yet to be developed. Here, we show that ecosystem CO2 uptake capacity in temperate and boreal forests scales directly with whole-canopy N concentrations, mirroring a leaf-level trend that has been observed for woody plants worldwide. We further show that both CO2 uptake capacity and canopy N concentration are strongly and positively correlated with shortwave surface albedo. These results suggest that N plays an additional, and overlooked, role in the climate system via its influence on vegetation reflectivity and shortwave surface energy exchange. We also demonstrate that much of the spatial variation in canopy N can be detected by using broad-band satellite sensors, offering a means through which these findings can be applied toward improved application of coupled carbon cycle–climate models

Modelling the spatial distribution of DEM Error

Assessment of a DEM’s quality is usually undertaken by deriving a measure of DEM accuracy – how close the DEM’s elevation values are to the true elevation. Measures such as Root Mean Squared Error and standard deviation of the error are frequently used. These measures summarise elevation errors in a DEM as a single value. A more detailed description of DEM accuracy would allow better understanding of DEM quality and the consequent uncertainty associated with using DEMs in analytical applications. The research presented addresses the limitations of using a single root mean squared error (RMSE) value to represent the uncertainty associated with a DEM by developing a new technique for creating a spatially distributed model of DEM quality – an accuracy surface. The technique is based on the hypothesis that the distribution and scale of elevation error within a DEM are at least partly related to morphometric characteristics of the terrain. The technique involves generating a set of terrain parameters to characterise terrain morphometry and developing regression models to define the relationship between DEM error and morphometric character. The regression models form the basis for creating standard deviation surfaces to represent DEM accuracy. The hypothesis is shown to be true and reliable accuracy surfaces are successfully created. These accuracy surfaces provide more detailed information about DEM accuracy than a single global estimate of RMSE