Localized mutations in the gene encoding the cytoskeletal protein filamin A cause diverse malformations in humans

Remodeling of the cytoskeleton is central to the modulation of cell shape and migration. Filamin A, encoded by the gene FLNA, is a widely expressed protein that regulates re-organization of the actin cytoskeleton by interacting with integrins, transmembrane receptor complexes and second messengers. We identified localized mutations in FLNA that conserve the reading frame and lead to a broad range of congenital malformations, affecting craniofacial structures, skeleton, brain, viscera and urogenital tract, in four X-linked human disorders: otopalatodigital syndrome types 1 (OPD1; OMIM 311300) and 2 (OPD2; OMIM 304120), frontometaphyseal dysplasia (FMD; OMIM 305620) and Melnick-Needles syndrome (MNS; OMIM 309350). Several mutations are recurrent, and all are clustered into four regions of the gene: the actin-binding domain and rod domain repeats 3, 10 and 14/15. Our findings contrast with previous observations that loss of function of FLNA is embryonic lethal in males but manifests in females as a localized neuronal migration disorder, called periventricular nodular heterotopia (PVNH; refs. 3-6). The patterns of mutation, X-chromosome inactivation and phenotypic manifestations in the newly described mutations indicate that they have gain-of-function effects, implicating filamin A in signaling pathways that mediate organogenesis in multiple systems during embryonic development.     

A homochiral metal-organic porous material for enantioselective separation and catalysis

Inorganic zeolites are used for many practical applications that exploit the microporosity intrinsic to their crystal structures. Organic analogues, which are assembled from modular organic building blocks linked through non-covalent interactions, are of interest for similar applications. These range from catalysis, separation and sensor technology to optoelectronics, with enantioselective separation and catalysis being especially important for the chemical and pharmaceutical industries. The modular construction of these analogues allows flexible and rational design, as both the architecture and chemical functionality of the micropores can, in principle, be precisely controlled. Porous organic solids with large voids and high framework stability have been produced, and investigations into the range of accessible pore functionalities have been initiated. For example, catalytically active organic zeolite analogues are known, as are chiral metal-organic open-framework materials. However, the latter are only available as racemic mixtures, or lack the degree of framework stability or void space that is required for practical applications. Here we report the synthesis of a homochiral metal-organic porous material that allows the enantioselective inclusion of metal complexes in its pores and catalyses a transesterification reaction in an enantioselective manner. Our synthesis strategy, which uses enantiopure metal-organic clusters as secondary building blocks, should be readily applicable to chemically modified cluster components and thus provide access to a wide range of porous organic materials suitable for enantioselective separation and catalysis.     

Tissue-specific and reversible RNA interference in transgenic mice

Genetically engineered mice provide powerful tools for understanding mammalian gene function. These models traditionally rely on gene overexpression from transgenes or targeted, irreversible gene mutation. By adapting the tetracycline (tet)-responsive system previously used for gene overexpression, we have developed a simple transgenic system to reversibly control endogenous gene expression using RNA interference (RNAi) in mice. Transgenic mice harboring a tet-responsive RNA polymerase II promoter driving a microRNA-based short hairpin RNA targeting the tumor suppressor Trp53 reversibly express short hairpin RNA when crossed with existing mouse strains expressing general or tissue-specific 'tet-on' or 'tet-off' transactivators. Reversible Trp53 knockdown can be achieved in several tissues, and restoring Trp53 expression in lymphomas whose development is promoted by Trp53 knockdown leads to tumor regression. By leaving the target gene unaltered, this approach permits tissue-specific, reversible regulation of endogenous gene expression in vivo, with potential broad application in basic biology and drug target validation.     

Methods for backcasting,nowcasting and forecasting using factor‐MIDAS: With an application to Korean GDP

We utilize mixed‐frequency factor‐MIDAS models for the purpose of carrying out backcasting, nowcasting, and forecasting experiments using real‐time data. We also introduce a new real‐time Korean GDP dataset, which is the focus of our experiments. The methodology that we utilize involves first estimating common latent factors (i.e., diffusion indices) from 190 monthly macroeconomic and financial series using various estimation strategies. These factors are then included, along with standard variables measured at multiple different frequencies, in various factor‐MIDAS prediction models. Our key empirical findings as follows. (i) When using real‐time data, factor‐MIDAS prediction models outperform various linear benchmark models. Interestingly, the “MSFE‐best” MIDAS models contain no autoregressive (AR) lag terms when backcasting and nowcasting. AR terms only begin to play a role in “true” forecasting contexts. (ii) Models that utilize only one or two factors are “MSFE‐best” at all forecasting horizons, but not at any backcasting and nowcasting horizons. In these latter contexts, much more heavily parametrized models with many factors are preferred. (iii) Real‐time data are crucial for forecasting Korean gross domestic product, and the use of “first available” versus “most recent” data “strongly” affects model selection and performance. (iv) Recursively estimated models are almost always “MSFE‐best,” and models estimated using autoregressive interpolation dominate those estimated using other interpolation methods. (v) Factors estimated using recursive principal component estimation methods have more predictive content than those estimated using a variety of other (more sophisticated) approaches. This result is particularly prevalent for our “MSFE‐best” factor‐MIDAS models, across virtually all forecast horizons, estimation schemes, and data vintages that are analyzed.     

Interleukin-33 stimulates formation of functional osteoclasts from human CD14+ monocytes

Interleukin (IL)-33 is a recently described pro-inflammatory cytokine. Here we demonstrate IL-33 as a regulator of functional osteoclasts (OCs) from human CD14⁺ monocytes. IL-33 stimulates formation of tartrate-resistant acid phosphatase (TRAP)⁺ multinuclear OCs from monocytes. This action was suppressed by anti-ST2 antibody, suggesting that IL-33 acts through its receptor ST2, but not by the receptor activator of NF-κB ligand (RANKL) decoy, osteoprotegerin, or anti-RANKL antibody. IL-33 stimulated activating phosphorylations of signaling molecules in monocytes that are critical for OC development. These included Syk, phospholipase Cγ2, Gab2, MAP kinases, TAK-1, and NF-κB. IL-33 also enhanced expression of OC differentiation factors including TNF-α receptor-associated factor 6 (TRAF6), nuclear factor of activated T cells cytoplasmic 1, c-Fos, c-Src, cathepsin K, and calcitonin receptor. IL-33 eventually induced bone resorption. This study suggests that the osteoclastogenic property of IL-33 is mediated through TRAF6 as well as the immunoreceptor tyrosine-based activation motif-dependent Syk/PLCγ pathway in human CD14⁺ monocytes.     

Bias‐corrected bootstrap prediction intervals for autoregressive model: new alternatives with applications to tourism forecasting

This paper proposes the use of the bias‐corrected bootstrap for interval forecasting of an autoregressive time series with an arbitrary number of deterministic components. We use the bias‐corrected bootstrap based on two alternative bias‐correction methods: the bootstrap and an analytic formula based on asymptotic expansion. We also propose a new stationarity‐correction method, based on stable spectral factorization, as an alternative to Kilian's method exclusively used in past studies. A Monte Carlo experiment is conducted to compare small‐sample properties of prediction intervals. The results show that the bias‐corrected bootstrap prediction intervals proposed in this paper exhibit desirable small‐sample properties. It is also found that the bootstrap bias‐corrected prediction intervals based on stable spectral factorization are tighter and more stable than those based on Kilian's stationarity‐correction. The proposed methods are applied to interval forecasting for the number of tourist arrivals in Hong Kong. Copyright © 2010 John Wiley & Sons, Ltd.