An Exome-Chip Association Analysis in Chinese Subjects Reveals a Functional Missense Variant of GCKR That Regulates FGF21 Levels

Fibroblast growth factor 21 (FGF21) is increasingly recognized as an important metabolic regulator of glucose homeostasis. Here, we conducted an exome-chip association analysis by genotyping 5,169 Chinese individuals from a community-based cohort and two clinic-based cohorts. A custom Asian exome-chip was used to detect genetic determinants influencing circulating FGF21 levels. Single-variant association analysis interrogating 70,444 single nucleotide polymorphisms identified a novel locus, GCKR, significantly associated with circulating FGF21 levels at genome-wide significance. In the combined analysis, the common missense variant of GCKR, rs1260326 (p.Pro446Leu), showed an association with FGF21 levels after adjustment for age and sex (P = 1.61 × 10−12; β [SE] = 0.14 [0.02]), which remained significant on further adjustment for BMI (P = 3.01 × 10−14; β [SE] = 0.15 [0.02]). GCKR Leu446 may influence FGF21 expression via its ability to increase glucokinase (GCK) activity. This can lead to enhanced FGF21 expression via elevated fatty acid synthesis, consequent to the inhibition of carnitine/palmitoyl-transferase by malonyl-CoA, and via increased glucose-6-phosphate–mediated activation of the carbohydrate response element binding protein, known to regulate FGF21 gene expression. Our findings shed new light on the genetic regulation of FGF21 levels. Further investigations to dissect the relationship between GCKR and FGF21, with respect to the risk of metabolic diseases, are warranted.postprin

Photocurrent measurements of supercollision cooling in graphene

The cooling of hot electrons in graphene is the critical process underlying the operation of exciting new graphene-based optoelectronic and plasmonic devices, but the nature of this cooling is controversial. We extract the hot electron cooling rate near the Fermi level by using graphene as novel photothermal thermometer that measures the electron temperature ($T(t)$) as it cools dynamically. We find the photocurrent generated from graphene $p-n$ junctions is well described by the energy dissipation rate $C dT/dt=-A(T^3-T_l^3)$, where the heat capacity is $C=\alpha T$ and $T_l$ is the base lattice temperature. These results are in disagreement with predictions of electron-phonon emission in a disorder-free graphene system, but in excellent quantitative agreement with recent predictions of a disorder-enhanced supercollision (SC) cooling mechanism. We find that the SC model provides a complete and unified picture of energy loss near the Fermi level over the wide range of electronic (15 to $\sim$3000 K) and lattice (10 to 295 K) temperatures investigated.Comment: 7pages, 5 figure

Signatures of arithmetic simplicity in metabolic network architecture

Metabolic networks perform some of the most fundamental functions in living cells, including energy transduction and building block biosynthesis. While these are the best characterized networks in living systems, understanding their evolutionary history and complex wiring constitutes one of the most fascinating open questions in biology, intimately related to the enigma of life's origin itself. Is the evolution of metabolism subject to general principles, beyond the unpredictable accumulation of multiple historical accidents? Here we search for such principles by applying to an artificial chemical universe some of the methodologies developed for the study of genome scale models of cellular metabolism. In particular, we use metabolic flux constraint-based models to exhaustively search for artificial chemistry pathways that can optimally perform an array of elementary metabolic functions. Despite the simplicity of the model employed, we find that the ensuing pathways display a surprisingly rich set of properties, including the existence of autocatalytic cycles and hierarchical modules, the appearance of universally preferable metabolites and reactions, and a logarithmic trend of pathway length as a function of input/output molecule size. Some of these properties can be derived analytically, borrowing methods previously used in cryptography. In addition, by mapping biochemical networks onto a simplified carbon atom reaction backbone, we find that several of the properties predicted by the artificial chemistry model hold for real metabolic networks. These findings suggest that optimality principles and arithmetic simplicity might lie beneath some aspects of biochemical complexity

Reliability and validity of the telephone version of the Cantonese Mini-mental State Examination (T-CMMSE) when used with elderly patients with and without dementia in Hong Kong

Author name used in this publication: Kenneth Nai Kuen Fong2008-2009 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Distributions of epistasis in microbes fit predictions from a fitness landscape model.

How do the fitness effects of several mutations combine? Despite its simplicity, this question is central to the understanding of multilocus evolution. Epistasis (the interaction between alleles at different loci), especially epistasis for fitness traits such as reproduction and survival, influences evolutionary predictions "almost whenever multilocus genetics matters". Yet very few models have sought to predict epistasis, and none has been empirically tested. Here we show that the distribution of epistasis can be predicted from the distribution of single mutation effects, based on a simple fitness landscape model. We show that this prediction closely matches the empirical measures of epistasis that have been obtained for Escherichia coli and the RNA virus vesicular stomatitis virus. Our results suggest that a simple fitness landscape model may be sufficient to quantitatively capture the complex nature of gene interactions. This model may offer a simple and widely applicable alternative to complex metabolic network models, in particular for making evolutionary predictions

Can rhythmical auditory stimulation alter gait pattern in children with asperger syndrome?

2013-2014 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Exome-wide association analysis reveals novel coding sequence variants associated with lipid traits in Chinese

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Context-Specific Metabolic Networks Are Consistent with Experiments

Reconstructions of cellular metabolism are publicly available for a variety of different microorganisms and some mammalian genomes. To date, these reconstructions are “genome-scale” and strive to include all reactions implied by the genome annotation, as well as those with direct experimental evidence. Clearly, many of the reactions in a genome-scale reconstruction will not be active under particular conditions or in a particular cell type. Methods to tailor these comprehensive genome-scale reconstructions into context-specific networks will aid predictive in silico modeling for a particular situation. We present a method called Gene Inactivity Moderated by Metabolism and Expression (GIMME) to achieve this goal. The GIMME algorithm uses quantitative gene expression data and one or more presupposed metabolic objectives to produce the context-specific reconstruction that is most consistent with the available data. Furthermore, the algorithm provides a quantitative inconsistency score indicating how consistent a set of gene expression data is with a particular metabolic objective. We show that this algorithm produces results consistent with biological experiments and intuition for adaptive evolution of bacteria, rational design of metabolic engineering strains, and human skeletal muscle cells. This work represents progress towards producing constraint-based models of metabolism that are specific to the conditions where the expression profiling data is available

The Evolution of Compact Binary Star Systems

We review the formation and evolution of compact binary stars consisting of white dwarfs (WDs), neutron stars (NSs), and black holes (BHs). Binary NSs and BHs are thought to be the primary astrophysical sources of gravitational waves (GWs) within the frequency band of ground-based detectors, while compact binaries of WDs are important sources of GWs at lower frequencies to be covered by space interferometers (LISA). Major uncertainties in the current understanding of properties of NSs and BHs most relevant to the GW studies are discussed, including the treatment of the natal kicks which compact stellar remnants acquire during the core collapse of massive stars and the common envelope phase of binary evolution. We discuss the coalescence rates of binary NSs and BHs and prospects for their detections, the formation and evolution of binary WDs and their observational manifestations. Special attention is given to AM CVn-stars -- compact binaries in which the Roche lobe is filled by another WD or a low-mass partially degenerate helium-star, as these stars are thought to be the best LISA verification binary GW sources.Comment: 105 pages, 18 figure

Numerical simulations for a typical train fire in China

Author name used in this publication: W. K ChowAuthor name used in this publication: N. K. Fong2010-2011 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe