1000 resultados para I IODOTHYRONINE DEIODINASE


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Iodothyronine deiodinases are selenoenzymes which regulate the thyroid hormone homeostasis by catalyzing the regioselective deiodination of thyroxine (T4). Synthetic deiodinase mimetics are important not only to understand the mechanism of enzyme catalysis, but also to develop therapeutic agents as abnormal thyroid hormone levels have implications in different diseases, such as hypoxia, myocardial infarction, critical illness, neuronal ischemia, tissue injury, and cancer. Described herein is that the replacement of sulfur/selenium atoms in a series of deiodinase mimetics by tellurium remarkably alters the reactivity as well as regioselectivity toward T4. The tellurium compounds reported in this paper represent the first examples of deiodinase mimetics which mediate sequential deiodination of T4 to produce all the hormone derivatives including T0 under physiologically relevant conditions.

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We perform numerical experiments to study the shear dynamo problem where we look for the growth of a large-scale magnetic field due to non-helical stirring at small scales in a background linear shear flow in previously unexplored parameter regimes. We demonstrate the large-scale dynamo action in the limit where the fluid Reynolds number (Re) is below unity while the magnetic Reynolds number (Rm) is above unity; the exponential growth rate scales linearly with shear, which is consistent with earlier numerical works. The limit of low Re is particularly interesting, as seeing the dynamo action in this limit would provide enough motivation for further theoretical investigations, which may focus attention on this analytically more tractable limit of Re < 1 compared to the more formidable limit of Re > 1. We also perform simulations in the regimes where (i) both (Re, Rm) < 1, and (ii) Re > 1 and Rm < 1, and compute all of the components of the turbulent transport coefficients (alpha(ij) and alpha(ij)) using the test-field method. A reasonably good agreement is observed between our results and the results of earlier analytical works in similar parameter regimes.

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The steady-state negative supercoiling of eubacterial genomes is maintained by the action of DNA topoisomerases. Topoisomerase distribution varies in different species of mycobacteria. While Mycobacterium tuberculosis (Mtb) contains a single type I (Topol) and a single type II (Gyrase) enzyme, Mycobacterium smegmatis (Msm) and other members harbour additional relaxases. Topol is essential for Mtb survival. However, the necessity of Topol or other relaxases in Msm has not been investigated. To recognize the importance of Topol for growth, physiology and gene expression of Msm, we have developed a conditional knock-down strain of Topol in Msm. The Topol-depleted strain exhibited extremely slow growth and drastic changes in phenotypic characteristics. The cessation of growth indicates the essential requirement of the enzyme for the organism in spite of having additional DNA relaxation enzymes in the cell. Notably, the imbalance in Topol level led to the altered expression of topology modulatory proteins, resulting in a diffused nucleoid architecture. Proteomic and transcript analysis of the mutant indicated reduced expression of the genes involved in central metabolic pathways and core DNA transaction processes. RNA polymerase (RNAP) distribution on the transcription units was affected in the Topol-depleted cells, suggesting global alteration in transcription. The study thus highlights the essential requirement of Topol in the maintenance of cellular phenotype, growth characteristics and gene expression in mycobacteria. A decrease in Topol level led to altered RNAP occupancy and impaired transcription elongation, causing severe downstream effects.

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T-cell responses in humans are initiated by the binding of a peptide antigen to a human leukocyte antigen (HLA) molecule. The peptide-HLA complex then recruits an appropriate T cell, leading to cell-mediated immunity. More than 2000 HLA class-I alleles are known in humans, and they vary only in their peptide-binding grooves. The polymorphism they exhibit enables them to bind a wide range of peptide antigens from diverse sources. HLA molecules and peptides present a complex molecular recognition pattern, as many peptides bind to a given allele and a given peptide can be recognized by many alleles. A powerful grouping scheme that not only provides an insightful classification, but is also capable of dissecting the physicochemical basis of recognition specificity is necessary to address this complexity. We present a hierarchical classification of 2010 class-I alleles by using a systematic divisive clustering method. All-pair distances of alleles were obtained by comparing binding pockets in the structural models. By varying the similarity thresholds, a multilevel classification was obtained, with 7 supergroups, each further subclassifying to yield 72 groups. An independent clustering performed based only on similarities in their epitope pools correlated highly with pocket-based clustering. Physicochemical feature combinations that best explain the basis of clustering are identified. Mutual information calculated for the set of peptide ligands enables identification of binding site residues contributing to peptide specificity. The grouping of HLA molecules achieved here will be useful for rational vaccine design, understanding disease susceptibilities and predicting risk of organ transplants.

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Minimization problems with respect to a one-parameter family of generalized relative entropies are studied. These relative entropies, which we term relative alpha-entropies (denoted I-alpha), arise as redundancies under mismatched compression when cumulants of compressed lengths are considered instead of expected compressed lengths. These parametric relative entropies are a generalization of the usual relative entropy (Kullback-Leibler divergence). Just like relative entropy, these relative alpha-entropies behave like squared Euclidean distance and satisfy the Pythagorean property. Minimizers of these relative alpha-entropies on closed and convex sets are shown to exist. Such minimizations generalize the maximum Renyi or Tsallis entropy principle. The minimizing probability distribution (termed forward I-alpha-projection) for a linear family is shown to obey a power-law. Other results in connection with statistical inference, namely subspace transitivity and iterated projections, are also established. In a companion paper, a related minimization problem of interest in robust statistics that leads to a reverse I-alpha-projection is studied.

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We report molecular dynamics (MD) simulations to explore the influence of a counterion on the structure and dynamics of cationic and anionic solvation shells for various ions in methanol at 298 K. We show that the variation in ionic size of either the cation or the anion in an ion pair influences the solvation structure of the other ion as well as the diffusivity in an electrolyte solution of methanol. The extent of ionic association between the cation and its counteranion of different ionic sizes has been investigated by analyzing the radial distribution functions (RDFs) and the orientation of methanol molecules in the first solvation shell (FSS) of ions. It is shown that the methanol in the FSS of the anion as well the cation exhibit quite different radial and orientational structures as compared to methanol which lie in the FSS of either the anion or the cation but not both. We find that the coordination number (CN) of F-, Cr-, and I- ions decreases with increasing size of the anion which is contrary to the trend reported for the anions in H2O. The mean residence time (MRT) of methanol molecules in the FSS of ions has been calculated using the stable states picture (SSP) approach. It is seen that the ion-counterion interaction has a considerable influence on the MRT of methanol molecules in the FSS of ions. We also discuss the stability order of the ion-counterion using the potentials of mean force (PMFs) for ion pairs with ions of different sizes. The PMF plots reveal that the Li+-F- pair (small-small) is highly stable and the Li+-I- pair is least stable (small-large) in electrolyte solutions.

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In this paper, for the first time, the key design parameters of a shallow trench isolation-based drain-extended MOS transistor are discussed for RF power applications in advanced CMOS technologies. The tradeoff between various dc and RF figures of merit (FoMs) is carefully studied using well-calibrated TCAD simulations. This detailed physical insight is used to optimize the dc and RF behavior, and our work also provides a design window for the improvement of dc as well as RF FoMs, without affecting the breakdown voltage. An improvement of 50% in R-ON and 45% in RF gain is achieved at 1 GHz. Large-signal time-domain analysis is done to explore the output power capability of the device.

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Two new Cu(I) compounds, namely Cu-2(bds)(bpy)(2)]center dot 2H(2)O (1) and Cu-4(bds)(2)(azpy)(4)]center dot 6H(2)O (3) (where bds = benzene-1,3-disulfonate, bpy = 4,4'-bipyridine and azpy = 4,4'-azopyridine), and four Ag(I) compounds, namely Ag-2(bds)(bpy)(2)]center dot 2H(2)O (2), Ag-2(bds)(azpy)(2)]center dot 4H(2)O (4), Ag(bds)(1/2)(bpe)]center dot 3H(2)O (5), and Ag-4(bds)(2)(tmdp)(4)]center dot 9H(2)O (6) (where bpe = 1,2-di(4-pyridyl) ethylene and tmdp = 4,4'trimethylenedipyridine), have been synthesized, and their structures were determined and characterized by elemental analysis, IR, UV-vis and thermal studies. The structure of the compounds changed from 1D (1 and 2) to 2D (3-5) and interpenetrated 3D (6). In the case of 5, a solid-state 2 + 2] photochemical cycloaddition reaction has been performed. Compound 2 exhibits a reversible anion exchange for perchlorate and permanganate, whereas the other compounds (1, 3-6) exhibit an irreversible anion exchange behaviour for perchlorate. Catalytic studies on 2 indicate Lewis acidity.

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The cybernetic modeling framework for the growth of microorganisms provides for an elegant methodology to account for the unknown regulatory phenomena through the use of cybernetic variables for enzyme induction and activity. In this paper, we revisit the assumption of limited resources for enzyme induction (Sigma u(i) = 1) used in the cybernetic modeling framework by presenting a methodology for inferring the individual cybernetic variables u(i) from experimental data. We use this methodology to infer u(i) during the simultaneous consumption of glycerol and lactose by Escherichia coli and then model the fitness trade-offs involved in the recently discovered predictive regulation strategy of microorganisms.