1,055 research outputs found

    Bilinear modulation models for seasonal tables of counts

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    We propose generalized linear models for time or age-time tables of seasonal counts, with the goal of better understanding seasonal patterns in the data. The linear predictor contains a smooth component for the trend and the product of a smooth component (the modulation) and a periodic time series of arbitrary shape (the carrier wave). To model rates, a population offset is added. Two-dimensional trends and modulation are estimated using a tensor product B-spline basis of moderate dimension. Further smoothness is ensured using difference penalties on the rows and columns of the tensor product coefficients. The optimal penalty tuning parameters are chosen based on minimization of a quasi-information criterion. Computationally efficient estimation is achieved using array regression techniques, avoiding excessively large matrices. The model is applied to female death rate in the US due to cerebrovascular diseases and respiratory diseases

    Localized inhibition of protein phosphatase 1 by NUAK1 promotes spliceosome activity and reveals a MYC-sensitive feedback control of transcription.

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    Deregulated expression of MYC induces a dependence on the NUAK1 kinase, but the molecular mechanisms underlying this dependence have not been fully clarified. Here, we show that NUAK1 is a predominantly nuclear protein that associates with a network of nuclear protein phosphatase 1 (PP1) interactors and that PNUTS, a nuclear regulatory subunit of PP1, is phosphorylated by NUAK1. Both NUAK1 and PNUTS associate with the splicing machinery. Inhibition of NUAK1 abolishes chromatin association of PNUTS, reduces spliceosome activity, and suppresses nascent RNA synthesis. Activation of MYC does not bypass the requirement for NUAK1 for spliceosome activity but significantly attenuates transcription inhibition. Consequently, NUAK1 inhibition in MYC-transformed cells induces global accumulation of RNAPII both at the pause site and at the first exon-intron boundary but does not increase mRNA synthesis. We suggest that NUAK1 inhibition in the presence of deregulated MYC traps non-productive RNAPII because of the absence of correctly assembled spliceosomes

    Visualization of Genomic Changes by Segmented Smoothing Using an L0 Penalty

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    Copy number variations (CNV) and allelic imbalance in tumor tissue can show strong segmentation. Their graphical presentation can be enhanced by appropriate smoothing. Existing signal and scatterplot smoothers do not respect segmentation well. We present novel algorithms that use a penalty on the norm of differences of neighboring values. Visualization is our main goal, but we compare classification performance to that of VEGA

    Electrochemical investigation of the kinetics of chloride substitution upon reduction of [Ru(porphyrin)(NO)Cl] complexes in THF.

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    The electrochemistry of several ruthenium porphyrin nitrosyl chloride complexes [Ru(por)(NO)Cl] have been examined in tetrahydrofuran. The complexes undergo 1-electron irreversible reductions which result in the diffusion-limited substitutions of the chloride ligands for THF. This chloride metathesis is reversible in the presence of added NBu4Cl, and equilibrium constants and rate constants for chloride loss have been estimated. These parameters correlate with the NO stretching frequencies of the parent complexes, with more electron-donating porphyrin ligands favouring chloride loss from the reduced complexes. The [Ru(por)(NO)(THF)] products of the reductions can be detected by IR, EPR and visible spectroscopies. These species undergo three further reductions, with good reversibility at scan rates \u3e0.40 V s-1. The [Ru(por)(NO)(THF)]+/0 couples have also been determined, and the rate constants and equilibrium constants for recombination with chloride have been estimated. One-electron reductions of the [Ru(por)(NO)Cl] complexes result in ~1018 enhancement of the rates of chloride loss

    Restriction of memory B cell differentiation at the germinal center B cell positive selection stage

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    Memory B cells (MBCs) are key for protection from reinfection. However, it is mechanistically unclear how germinal center (GC) B cells differentiate into MBCs. MYC is transiently induced in cells fated for GC expansion and plasma cell (PC) formation, so-called positively selected GC B cells. We found that these cells coexpressed MYC and MIZ1 (MYC-interacting zinc-finger protein 1 [ZBTB17]). MYC and MIZ1 are transcriptional activators; however, they form a transcriptional repressor complex that represses MIZ1 target genes. Mice lacking MYC-MIZ1 complexes displayed impaired cell cycle entry of positively selected GC B cells and reduced GC B cell expansion and PC formation. Notably, absence of MYC-MIZ1 complexes in positively selected GC B cells led to a gene expression profile alike that of MBCs and increased MBC differentiation. Thus, at the GC positive selection stage, MYC-MIZ1 complexes are required for effective GC expansion and PC formation and to restrict MBC differentiation. We propose that MYC and MIZ1 form a module that regulates GC B cell fate

    Biogenesis of mitochondrial porin

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    We review here the present knowledge about the pathway of import and assembly of porin into mitochondria and compare it to those of other mitochondrial proteins. Porin, like all outer mitochondrial membrane proteins studied so far is made as a precursor without a cleavble lsquosignalrsquo sequence; thus targeting information must reside in the mature sequence. At least part of this information appears to be located at the amino-terminal end of the molecule. Transport into mitochondria can occur post-translationally. In a first step, the porin precursor is specifically recognized on the mitochondrial surface by a protease sensitive receptor. In a second step, porin precursor inserts partially into the outer membrane. This step is mediated by a component of the import machinery common to the import pathways of precursor proteins destined for other mitochondrial subcompartments. Finally, porin is assembled to produce the functional oligomeric form of an integral membrane protein wich is characterized by its extreme protease resistance

    Biogenesis of the mitochondrial phosphate carrier

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    The mitochondrial phosphate carrier (PiC) is a member of the family of inner-membrane carrier proteins which are generally synthesized without a cleavable presequence. Surprisingly, the cDNA sequences of bovine and rat PiC suggested the existence of an amino-terminal extension sequence in the precursor of PiC. By expressing PiC in vitro, we found that PiC is indeed synthesized as a larger precursor. This precursor was imported and proteolytically processed by mitochondria, whereby the correct amino-terminus of the mature protein was generated. Import of PiC showed the characteristics of mitochondrial protein uptake, such as dependence on ATP and a membrane potential and involvement of contact sites between mitochondrial outer and inner membranes. The precursor imported in vitro was correctly assembled into the functional form, demonstrating that the authentic import and assembly pathway of PiC was reconstituted when starting with the presequence-carrying precursor. These results are discussed in connection with the recently postulated role of PiC as an import receptor located in the outer membrane

    Selection of tuning parameters in bridge regression models via Bayesian information criterion

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    We consider the bridge linear regression modeling, which can produce a sparse or non-sparse model. A crucial point in the model building process is the selection of adjusted parameters including a regularization parameter and a tuning parameter in bridge regression models. The choice of the adjusted parameters can be viewed as a model selection and evaluation problem. We propose a model selection criterion for evaluating bridge regression models in terms of Bayesian approach. This selection criterion enables us to select the adjusted parameters objectively. We investigate the effectiveness of our proposed modeling strategy through some numerical examples.Comment: 20 pages, 5 figure
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