Measurement of Methionine-Enkephalin [Arg6,Phe7] in Rat Brain by Specific Radioimmunoassay Directed at Methionine Sulphoxide Enkephalin[Arg6,Phe7]

Abstract: A specific and sensitive radioimmunoassay procedure for Metenkephalin[Arg⁶,Phe⁷] which allows its measurement in regions of the rat brain is described. The antiserum was raised against the methionine sulphoxide derivative of the peptide, and all samples and standards were oxidized with hydrogen peroxide prior to use in the assay with chloramine T-oxidized ¹²⁵I-labelled Met(O)-enkephalin[Arg⁶,Phe⁷]. The only significant cross-reactivity was 30% with the reduced heptapeptide Met-enkephalin[Arg⁶,Phe⁷]. The assay showed less than 0.15% cross-reactivity with fragments of the heptapeptide and with leucine-enkephalin-containing peptides. Acid acetone extraction of rat striatum followed by Sephadex G-50 chromatography and reverse-phase high pressure liquid chromatography showed that essentially all immunoreactivity co-chromatographed with Met-enkephalin[Arg⁶,Phe⁷]. This confirmed the specificity of the assay and showed that the striatum does not contain a high concentration of larger molecular weight forms with the heptapeptide at the COOH terminus. Distribution of the heptapeptide followed that of methionine enkephalin, with highest concentrations in the globus pallidus, intermediate levels in caudate-putamen and hypothalamus, and low levels in cortex and cerebellum.     

Transfer RNA and protein synthesis

The three-dimensional structure of yeast phenylalanine transfert RNA has been determined in orthorhombic crystals. The current status of this work is reviewed together with the relationship of the transfer RNA structure in the crystal to its biologically active form. In addition some speculations are put forward regarding the mode of interaction of tRNA molecules in the ribosome and the manner in which tRNA interacts with aminoacyl synthetase.     

Diet crude protein reduction on follicular fluid and cumulus-oocyte complexes of mid-lactating Girolando cows

This study evaluated the effect of crude protein (CP) reduction in four diets (156, 139, 132, and 127 g Kg^-1 DM) maintaining constant metabolizable protein (188 g/day) on the follicular fluid and cumulus-oocyte complexes of mid-lactating Girolando cows. Twenty-two Girolando cows with average of 21.55 ±3.19 L daily milk yield, 105.30 ±22.62 days in lactation and 3.22 ±0.03 body condition score were selected. To reduce CP in diets and maintain constant metabolizable protein, urea and soybean meal were gradually replaced by lignosulfonate-treated soybean meal (SoyPass^®, Cargill), resulting in an increase in rumen-undegradable protein and a reduction in rumen degradable protein. A linear and quadratic reduction was observed in the plasma and follicular fluid urea nitrogen concentration following CP reduction, with the most intense reduction occurring in the 127 g Kg^-1 DM group (p<0.001). As CP reduced, there was a tendency for a linear increase in the follicular growth rate (P=0.0696), on the number and proportion of viable oocytes (P<0.09), and also a linear increase for the number (P=0.0397) and proportion (P<0.09) of grade I viable oocytes. Plus, there was a linear effect for the number of cumulus oophorus cells. Cows fed with the lowest amount of CP had cumulus-oocyte complexes with higher numbers of cumulus oophorus cells (P=0.0238). Also, the reduction of diet crude protein was followed by a decrease in the probability of oocytes’ DNA degradation. In conclusion, the reduction of CP in the diet of mid-lactating Girolando cows, reduces urea nitrogen concentration in both blood plasma and follicular fluid, and, as a consequence, increases the viability of oocytes and the number of cumulus oophorus cells while reducing oocytes’ DNA degradation of follicular included cumulus-oocyte complex. The reduction on dietary CP may improve in vivo oocytes’ embryo development impacting fertility of lactating dairy cows.     

Co‐benefits,trade‐offs,barriers and policies for greenhouse gas mitigation in the agriculture,forestry and other land use (AFOLU) sector

The agriculture, forestry and other land use (AFOLU) sector is responsible for approximately 25% of anthropogenic GHG emissions mainly from deforestation and agricultural emissions from livestock, soil and nutrient management. Mitigation from the sector is thus extremely important in meeting emission reduction targets. The sector offers a variety of cost‐competitive mitigation options with most analyses indicating a decline in emissions largely due to decreasing deforestation rates. Sustainability criteria are needed to guide development and implementation of AFOLU mitigation measures with particular focus on multifunctional systems that allow the delivery of multiple services from land. It is striking that almost all of the positive and negative impacts, opportunities and barriers are context specific, precluding generic statements about which AFOLU mitigation measures have the greatest promise at a global scale. This finding underlines the importance of considering each mitigation strategy on a case‐by‐case basis, systemic effects when implementing mitigation options on the national scale, and suggests that policies need to be flexible enough to allow such assessments. National and international agricultural and forest (climate) policies have the potential to alter the opportunity costs of specific land uses in ways that increase opportunities or barriers for attaining climate change mitigation goals. Policies governing practices in agriculture and in forest conservation and management need to account for both effective mitigation and adaptation and can help to orient practices in agriculture and in forestry towards global sharing of innovative technologies for the efficient use of land resources. Different policy instruments, especially economic incentives and regulatory approaches, are currently being applied however, for its successful implementation it is critical to understand how land‐use decisions are made and how new social, political and economic forces in the future will influence this process.     

Cell recruitment and cytokines in skin mice sensitized with the vaccine adjuvants: saponin, incomplete Freund's adjuvant, and monophosphoryl lipid A

Vaccine adjuvants are substances associated with antigens that are fundamental to the formation of an intense, durable, and fast immune response. In this context, the use of vaccine adjuvants to generate an effective cellular immune response is crucial for the design and development of vaccines against visceral leishmaniasis. The objective of this study was to evaluate innate inflammatory response induced by the vaccine adjuvants saponin (SAP), incomplete Freund's adjuvant (IFA), and monophosphoryl lipid A (MPL). After a single dose of adjuvant was injected into the skin of mice, we analyzed inflammatory reaction, selective cell migration, and cytokine production at the injection site, and inflammatory cell influx in the peripheral blood. We found that all vaccine adjuvants were able to promote cell recruitment to the site without tissue damage. In addition, they induced selective migration of neutrophils, macrophages, and lymphocytes. The influx of neutrophils was notable at 12 h in all groups, but at other time points it was most evident after inoculation with SAP. With regard to cytokines, the SAP led to production of interleukin (IL)-2, IL-6, and IL-4. IFA promoted production of tumor necrosis factor (TNF)-α, interferon (IFN)-γ, IL-6, IL-17, IL-4, and IL-10. We also observed that MPL induced high production of IL-2, TNF-α, and IFN-γ, in addition to IL-6, IL-17, and IL-10. In peripheral blood, values of certain cell populations in the local response changed after stimulation. Our data demonstrate that the three vaccine adjuvants stimulate the early events of innate immune response at the injection site, suggesting their ability to increase the immunogenicity of co-administered antigens. Moreover, this work provides relevant information about elements of innate and acquired immune response induced by vaccine adjuvants administered alone.     

Methods to account for spatial autocorrelation in the analysis of species distributional data: a review

Species distributional or trait data based on range map (extent‐of‐occurrence) or atlas survey data often display spatial autocorrelation, i.e. locations close to each other exhibit more similar values than those further apart. If this pattern remains present in the residuals of a statistical model based on such data, one of the key assumptions of standard statistical analyses, that residuals are independent and identically distributed (i.i.d), is violated. The violation of the assumption of i.i.d. residuals may bias parameter estimates and can increase type I error rates (falsely rejecting the null hypothesis of no effect). While this is increasingly recognised by researchers analysing species distribution data, there is, to our knowledge, no comprehensive overview of the many available spatial statistical methods to take spatial autocorrelation into account in tests of statistical significance. Here, we describe six different statistical approaches to infer correlates of species’ distributions, for both presence/absence (binary response) and species abundance data (poisson or normally distributed response), while accounting for spatial autocorrelation in model residuals: autocovariate regression; spatial eigenvector mapping; generalised least squares; (conditional and simultaneous) autoregressive models and generalised estimating equations. A comprehensive comparison of the relative merits of these methods is beyond the scope of this paper. To demonstrate each method's implementation, however, we undertook preliminary tests based on simulated data. These preliminary tests verified that most of the spatial modeling techniques we examined showed good type I error control and precise parameter estimates, at least when confronted with simplistic simulated data containing spatial autocorrelation in the errors. However, we found that for presence/absence data the results and conclusions were very variable between the different methods. This is likely due to the low information content of binary maps. Also, in contrast with previous studies, we found that autocovariate methods consistently underestimated the effects of environmental controls of species distributions. Given their widespread use, in particular for the modelling of species presence/absence data (e.g. climate envelope models), we argue that this warrants further study and caution in their use. To aid other ecologists in making use of the methods described, code to implement them in freely available software is provided in an electronic appendix.