Kyungpook National University

About: Kyungpook National University is a education organization based out in Daegu, South Korea. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 20497 authors who have published 42107 publications receiving 834608 citations.

Obesity and Its Metabolic Complications: The Role of Adipokines and the Relationship between Obesity, Inflammation, Insulin Resistance, Dyslipidemia and Nonalcoholic Fatty Liver Disease

Abstract: Accumulating evidence indicates that obesity is closely associated with an increased risk of metabolic diseases such as insulin resistance, type 2 diabetes, dyslipidemia and nonalcoholic fatty liver disease. Obesity results from an imbalance between food intake and energy expenditure, which leads to an excessive accumulation of adipose tissue. Adipose tissue is now recognized not only as a main site of storage of excess energy derived from food intake but also as an endocrine organ. The expansion of adipose tissue produces a number of bioactive substances, known as adipocytokines or adipokines, which trigger chronic low-grade inflammation and interact with a range of processes in many different organs. Although the precise mechanisms are still unclear, dysregulated production or secretion of these adipokines caused by excess adipose tissue and adipose tissue dysfunction can contribute to the development of obesity-related metabolic diseases. In this review, we focus on the role of several adipokines associated with obesity and the potential impact on obesity-related metabolic diseases. Multiple lines evidence provides valuable insights into the roles of adipokines in the development of obesity and its metabolic complications. Further research is still required to fully understand the mechanisms underlying the metabolic actions of a few newly identified adipokines.

Observation of a Narrow Charmoniumlike State in Exclusive B±→K±π+π-J/ψ Decays

Abstract: We report the observation of a narrow charmoniumlike state produced in the exclusive decay process B+/--->K+/-pi(+)pi(-)J/psi. This state, which decays into pi(+)pi(-)J/psi, has a mass of 3872.0+/-0.6(stat)+/-0.5(syst) MeV, a value that is very near the M(D0)+M(D(*0)) mass threshold. The results are based on an analysis of 152M B-Bmacr; events collected at the Upsilon(4S) resonance in the Belle detector at the KEKB collider. The signal has a statistical significance that is in excess of 10sigma.

The major cell populations of the mouse retina.

Abstract: We report a quantitative analysis of the major populations of cells present in the retina of the C57 mouse. Rod and cone photoreceptors were counted using differential interference contrast microscopy in retinal whole mounts. Horizontal, bipolar, amacrine, and Muller cells were identified in serial section electron micrographs assembled into serial montages. Ganglion cells and displaced amacrine cells were counted by subtracting the number of axons in the optic nerve, learned from electron microscopy, from the total neurons of the ganglion cell layer. The results provide a base of reference for future work on genetically altered animals and put into perspective certain recent studies. Comparable data are now available for the retinas of the rabbit and the monkey. With the exception of the monkey fovea, the inner nuclear layers of the three species contain populations of cells that are, overall, quite similar. This contradicts the previous belief that the retinas of lower mammals are “amacrine-dominated”, and therefore more complex, than those of higher mammals.

Protein Analysis by Shotgun/Bottom-up Proteomics

Abstract: According to Genome Sequencing Project statistics (http://www.ncbi.nlm.nih.gov/genomes/static/gpstat.html), as of Feb 16, 2012, complete gene sequences have become available for 2816 viruses, 1117 prokaryotes, and 36 eukaryotes.1–2 The availability of full genome sequences has greatly facilitated biological research in many fields, and has greatly contributed to the growth of proteomics. Proteins are important because they are the direct bio-functional molecules in the living organisms. The term “proteomics” was coined from merging “protein” and “genomics” in the 1990s.3–4 As a post-genomic discipline, proteomics encompasses efforts to identify and quantify all the proteins of a proteome, including expression, cellular localization, interactions, post-translational modifications (PTMs), and turnover as a function of time, space and cell type, thus making the full investigation of a proteome more challenging than sequencing a genome. There are possibly 100,000 protein forms encoded by the approximate 20,235 genes of the human genome,5 and determining the explicit function of each form will be a challenge. The progress of proteomics has been driven by the development of new technologies for peptide/protein separation, mass spectrometry analysis, isotope labeling for quantification, and bioinformatics data analysis. Mass spectrometry has emerged as a core tool for large-scale protein analysis. In the past decade, there has been a rapid advance in the resolution, mass accuracy, sensitivity and scan rate of mass spectrometers used to analyze proteins. In addition, hybrid mass analyzers have been introduced recently (e.g. Linear Ion Trap-Orbitrap series6–7) which have significantly improved proteomic analysis. “Bottom-up” protein analysis refers to the characterization of proteins by analysis of peptides released from the protein through proteolysis. When bottom-up is performed on a mixture of proteins it is called shotgun proteomics,8–10 a name coined by the Yates lab because of its analogy to shotgun genomic sequencing.11 Shotgun proteomics provides an indirect measurement of proteins through peptides derived from proteolytic digestion of intact proteins. In a typical shotgun proteomics experiment, the peptide mixture is fractionated and subjected to LC-MS/MS analysis. Peptide identification is achieved by comparing the tandem mass spectra derived from peptide fragmentation with theoretical tandem mass spectra generated from in silico digestion of a protein database. Protein inference is accomplished by assigning peptide sequences to proteins. Because peptides can be either uniquely assigned to a single protein or shared by more than one protein, the identified proteins may be further scored and grouped based on their peptides. In contrast, another strategy, termed ‘top-down’ proteomics, is used to characterize intact proteins (Figure 1). The top-down approach has some potential advantages for PTM and protein isoform determination and has achieved notable success. Intact proteins have been measured up to 200 kDa,12 and a large scale study has identified more than 1,000 proteins by multi-dimensional separations from complex samples.13 However, the top-down method has significant limitations compared with shotgun proteomics due to difficulties with protein fractionation, protein ionization and fragmentation in the gas phase. By relying on the analysis of peptides, which are more easily fractionated, ionized and fragmented, shotgun proteomics can be more universally adopted for protein analysis. In fact, a hybrid of bottom-up and top-down methodologies and instrumentation has been introduced as middle-down proteomics.14 Essentially, middle-down proteomics analyzes larger peptide fragments than bottom-up proteomics, minimizing peptide redundancy between proteins. Additionally the large peptide fragments yield similar advantages as top-down proteomics, such as gaining further insight into post-translational modifications, without the analytical challenges of analyzing intact proteins. Shotgun proteomics has become a workhorse for the analysis of proteins and their modifications and will be increasingly combined with top-down methods in the future. Figure 1 Proteomic strategies: bottom-up vs. top-down vs. middle-down. The bottom-up approach analyzes proteolytic peptides. The top-down method measures the intact proteins. The middle-down strategy analyzes larger peptides resulted from limited digestion or ... In the past decade shotgun proteomics has been widely used by biologists for many different research experiments, advancing biological discoveries. Some applications include, but are not limited to, proteome profiling, protein quantification, protein modification, and protein-protein interaction. There have been several reviews nicely summarizing mass spectrometry history,15 protein quantification with mass spectrometry,16 its biological applications,5,17–26 and many recent advances in methodology.27–32 In this review, we try to provide a full and updated survey of shotgun proteomics, including the fundamental techniques and applications that laid the foundation along with those developed and greatly improved in the past several years.