The change of plasma C-reactive protein and metabolite concentrations, and MPS sick degree score in Landrase selected for resistance to MPS, Large Yorkshire selected for immune performances and the crossbreed

Swine Mycoplasma Hyopneumoniea, hp, is known as a major factor to affect for the specific pneumonia (MPS). This damages is very serious because carrier rate of hp in piglets from 3 to 4 months of age is very high, the rate of piglets that the response of antibody to hp shows positive is 80 % over, and the rate that has very terrible tissue from MPS is 51% in Japanese pig farm. We bred a resistant strain to MPS by selection to decrease MPS pathogenic condition over 5 generations using Landrase (MPS strain), and a high immune performance strain by selection for peripheral phagocytosis, complement activity and antibody production against erysipelatous vaccine using Large Yorkshire (HI strain)

Glia-Pinealocyte Network: The Paracrine Modulation of Melatonin Synthesis by Tumor Necrosis Factor (TNF)

The pineal gland, a circumventricular organ, plays an integrative role in defense responses. The injury-induced suppression of the pineal gland hormone, melatonin, which is triggered by darkness, allows the mounting of innate immune responses. We have previously shown that cultured pineal glands, which express toll-like receptor 4 (TLR4) and tumor necrosis factor receptor 1 (TNFR1), produce TNF when challenged with lipopolysaccharide (LPS). Here our aim was to evaluate which cells present in the pineal gland, astrocytes, microglia or pinealocytes produced TNF, in order to understand the interaction between pineal activity, melatonin production and immune function. Cultured pineal glands or pinealocytes were stimulated with LPS. TNF content was measured using an enzyme-linked immunosorbent assay. TLR4 and TNFR1 expression were analyzed by confocal microscopy. Microglial morphology was analyzed by immunohistochemistry. In the present study, we show that although the main cell types of the pineal gland (pinealocytes, astrocytes and microglia) express TLR4, the production of TNF induced by LPS is mediated by microglia. This effect is due to activation of the nuclear factor kappa B (NF-kB) pathway. In addition, we observed that LPS activates microglia and modulates the expression of TNFR1 in pinealocytes. As TNF has been shown to amplify and prolong inflammatory responses, its production by pineal microglia suggests a glia-pinealocyte network that regulates melatonin output. The current study demonstrates the molecular and cellular basis for understanding how melatonin synthesis is regulated during an innate immune response, thus our results reinforce the role of the pineal gland as sensor of immune status

Developments in cell biology for quantitative immunoelectron microscopy based on thin sections: a review

Quantitative immunoelectron microscopy uses ultrathin sections and gold particle labelling to determine distributions of molecules across cell compartments. Here, we review a portfolio of new methods for comparing labelling distributions between different compartments in one study group (method 1) and between the same compartments in two or more groups (method 2). Specimen samples are selected unbiasedly and then observed and expected distributions of gold particles are estimated and compared by appropriate statistical procedures. The methods can be used to analyse gold label distributed between volume-occupying (organelle) and surface-occupying (membrane) compartments, but in method 1, membranes must be treated as organelles. With method 1, gold counts are combined with stereological estimators of compartment size to determine labelling density (LD). For volume-occupiers, LD can be expressed simply as golds per test point and, for surface-occupiers, as golds per test line intersection. Expected distributions are generated by randomly assigning gold particles to compartments and expressing observed/expected counts as a relative labelling index (RLI). Preferentially-labelled compartments are identified from their RLI values and by Chi-squared analysis of observed and expected distributions. For method 2, the raw gold particle counts distributed between compartments are simply compared across groups by contingency table and Chi-squared analysis. This identifies the main compartments responsible for the differences between group distributions. Finally, we discuss labelling efficiency (the number of gold particles per target molecule) and describe how it can be estimated for volume- or surface-occupiers by combining stereological data with biochemical determinations

Contribution of Microbe-Mediated Processes in Nitrogen Cycle to Attain Environmental Equilibrium

Nitrogen (N), the most important element, is required by all living organisms for the synthesis of complex organic molecules like amino acids, proteins, lipids etc. Nitrogen cycle is considered to be the most complex yet arguably important cycle next to carbon cycle. Nitrogen cycle includes oxic and anoxic reactions like organic N mineralization, ammonia assimilation, nitrification denitrification, anaerobic ammonium oxidation (anammox), dissimilatory nitrate reduction to ammonium (DNRA), comammox, codenitrification etc. Nitrogen cycling is one of the most crucial processes required for the recycling of essential chemical requirements on the planet. Soil microorganisms not only improve N-cycle balance but also pave the way for sustainable agricultural practices, leading to improved soil properties and crop productivity as most plants are opportunistic in the uptake of soluble or available forms of N from soil. Microbial N transformations are influenced by plants to improve their nutrition and vice versa. Diverse microorganisms, versatile metabolic activities, and varied biotic and abiotic conditions may result in the shift in the equilibrium state of different N-cycling processes. This chapter is an overview of the mechanisms and genes involved in the diverse microorganisms associated in the operation of nitrogen cycle and the roles of such microorganisms in different agroecosystems

Posttranscriptional regulation of pineal melatonin synthesis in Octodon degus

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74175/1/j.1600-079X.2009.00690.x.pd

The change of plasma C-reactive protein and metabolite concentrations, and MPS sick degree score in Landrase selected for resistance to MPS, Large Yorkshire selected for immune performances and the crossbreed

Swine Mycoplasma Hyopneumoniea, hp, is known as a major factor to affect for the specific pneumonia (MPS). This damages is very serious because carrier rate of hp in piglets from 3 to 4 months of age is very high, the rate of piglets that the response of antibody to hp shows positive is 80 % over, and the rate that has very terrible tissue from MPS is 51% in Japanese pig farm. We bred a resistant strain to MPS by selection to decrease MPS pathogenic condition over 5 generations using Landrase (MPS strain), and a high immune performance strain by selection for peripheral phagocytosis, complement activity and antibody production against erysipelatous vaccine using Large Yorkshire (HI strain).</p

Association Analysis of Genetic Variants with Type 2 Diabetes in a Mongolian Population in China

The large scale genome wide association studies (GWAS) have identified approximately 80 single nucleotide polymorphisms (SNPs) conferring susceptibility to type 2 diabetes (T2D). However, most of these loci have not been replicated in diverse populations and much genetic heterogeneity has been observed across ethnic groups. We tested 28 SNPs previously found to be associated with T2D by GWAS in a Mongolian sample of Northern China (497 diagnosed with T2D and 469 controls) for association with T2D and diabetes related quantitative traits. We replicated T2D association of 11 SNPs, namely, rs7578326 (IRS1), rs1531343 (HMGA2), rs8042680 (PRC1), rs7578597 (THADA), rs1333051 (CDKN2), rs6723108 (TMEM163), rs163182 and rs2237897 (KCNQ1), rs1387153 (MTNR1B), rs243021 (BCL11A), and rs10229583 (PAX4) in our sample. Further, we showed that risk allele of the strongest T2D associated SNP in our sample, rs757832 (IRS1), is associated with increased level of TG. We observed substantial difference of T2D risk allele frequency between the Mongolian sample and the 1000G Caucasian sample for a few SNPs, including rs6723108 (TMEM163) whose risk allele reaches near fixation in the Mongolian sample. Further study of genetic architecture of these variants in susceptibility of T2D is needed to understand the role of these variants in heterogeneous populations