1,305 research outputs found

    Solution structure of human thioredoxin in a mixed disulfide intermediate complex with its target peptide from the transcription factor NFκB

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    AbstractBackground: Human thioredoxin is a 12 kDa cellular redox protein that plays a key role in maintaining the redox environment of the cell. It has recently been shown to be responsible for activating the DNA-binding properties of the cellular transcription factor, NFκB, by reducing a disulfide bond involving Cys62 of the p50 subunit. Using multidimensional heteronuclear-edited and heteronuclear-filtered NMR spectroscopy, we have solved the solution structure of a complex of human thioredoxin and a 13-residue peptide extending from residues 56–68 of p50, representing a kinetically stable mixed disulfide intermediate along the reaction pathway.Results The NFκB peptide is located in a long boot-shaped cleft on the surface of human thioredoxin delineated by the active-site loop, helices α2, α3 and α4, and strands β3 and β4. The peptide adopts a crescent-like conformation with a smooth 110° bend centered around residue 60 which permits it to follow the path of the cleft.Conclusion In addition to the intermolecular disulfide bridge between Cys32 of human thioredoxin and Cys62 of the peptide, the complex is stabilized by numerous hydrogen-bonding, electrostatic and hydrophobic interactions which involve residues 57–65 of the NFκB peptide and confer substrate specificity. These structural features permit one to suggest the specificity requirements for human thioredoxin-catalyzed disulfide bond reduction of proteins

    The social geography of unmarried cohabitation in the USA, 2007-2011

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    US studies of marriage and cohabitation have mainly highlighted the social and racial differentials as they were observed in cross-sections, and have as a result essentially focused on the "pattern of disadvantage". The evolution of such social differentials over time and space reveals that this pattern of disadvantage has clearly persisted, but that it is far from covering the whole story. Historically, there has been a major contribution to the rise of cohabitation by white college students, and later on young white adults with higher education continued to start unions via cohabitation to ever increasing degrees. Only, they seem to move into marriage to a greater extent later on in life than other population segments. Also, the religious affiliation matters greatly: Mormons and evangelical Christians have resisted the current trends. Furthermore this effect is not only operating at the individual but at the contextual level as well. Conversely, even after controls for competing socio-economic explanations, residence in areas (either counties or PUMA-areas) with a Democratic voting pattern is related to higher cohabitation probabilities. And, finally, different legal contexts at the level of States also significantly contributed to the emergence of strong spatial contrasts. Hence, there is a concurrence of several factors shaping the present differentiations, and the rise of secular and liberal attitudes, i.e. the "ethics revolution", is equally a part of the explanation

    Inclusion of genetically identical animals to a numerator relationship matrix and modification of its inverse

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    In the field of animal breeding, estimation of genetic parameters and prediction of breeding values are routinely conducted by analyzing quantitative traits. Using an animal model and including the direct inverse of a numerator relationship matrix (NRM) into a mixed model has made these analyses possible. However, a method including a genetically identical animal (GIA) in NRM if genetic relationships between pairs of GIAs are not perfect, is still lacking. Here, we describe a method to incorporate GIAs into NRM using a K matrix in which diagonal elements are set to 1.0, off-diagonal elements between pairs of GIAs to (1-x) and the other elements to 0, where x is a constant less than 0.05. The inverse of the K matrix is then calculated directly by a simple formula. Thus, the inverse of the NRM is calculated by the products of the lower triangular matrix that identifies the parents of each individual, its transpose matrix, the inverse of the K matrix and the inverse of diagonal matrix D, in which the diagonal elements comprise a number of known parents and their inbreeding coefficients. The computing method is adaptable to the analysis of a data set including pairs of GIAs with imperfect relationships

    A Pilot Phase II Study of Digoxin in Patients with Recurrent Prostate Cancer as Evident by Rising PSA

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    Background: Digoxin was found to inhibit prostate cancer (PCa) growth via the inhibition of HIF-1α synthesis in a mouse model. We hypothesized that a therapeutic dose of digoxin could inhibit human PCa growth and disease progression. Methods: An open label, single arm pilot study was performed. Patients (pts) with non-metastatic, biochemically relapsed PCa with prostate specific antigen doubling time (PSADT) of 3 -24 months and no hormonal therapy within the past 6 months were enrolled. All pts had testosterone 50 ng/dL at baseline. Digoxin was taken daily with dose titration to achieve a target therapeutic level (0.8 – 2 ng/ml); patients had routine follow-up including cardiac monitoring with 12-lead electrocardiograms (ECGs) and digoxin levels. The primary endpoint was the proportion of pts at 6 months post-treatment with a PSADT 200% from the baseline. HIF-1α downstream molecule vascular endothelial growth factor (VEGF) was measured in plasma.Results: Sixteen pts were enrolled and 14 pts finished the planned 6 months of treatment. Twenty percent (3/15) of the pts had PSA decrease 25% from baseline with a medium duration of 14 months. At 6 months, 5 of 13 (38%) pts had PSADT 200% of the baseline PSADT and were continued on study for an additional 24 weeks of treatment. Two patients had durable PSA response for more than 1 year. Digoxin was well tolerated with possible relation of one grade 3 back pain. No patients had evidence of digoxin toxicity. The digoxin dose was lowered in 2 patients for significant ECGs changes (sinus bradycardia and QT prolongation), and there were probable digoxin-related ECG changes in 3 patients. Plasma VEGF was detected in 4 (25%) patients. Conclusions: Digoxin was well tolerated and showed a prolongation of PSDAT in 38% of the patients. However, there was no significant difference comparing that of similar patients on placebo from historical data. Digoxin at the dose used in this study may have limited benefit for patients with biochemically relapsed prostate cancer

    Prognostic value of nuclear morphometry in patients with TNM stage T1 ovarian clear cell adenocarcinoma

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    In 40 patients with TNM stage T1 ovarian clear cell adenocarcinoma, we used nuclear morphometry to study the relations among morphometric variables, clinical prognostic factors and outcome. The presence of one or more giant nuclear cells was positively associated with death (OR = 10.6, P = 0.02) and tended to be associated with disease recurrence (OR = 5.1, P = 0.07). Nuclear irregularity (expressed in terms of the nuclear roundness factor) was positively associated with both death (OR = 8.6, P = 0.02) and disease recurrence (OR = 8.2, P = 0.02). A combination of giant nuclear cell presence or nuclear irregularity proved to be a useful prognostic indicator, with a sensitivity and specificity of 83% and 71% in the prediction of death, and 75% and 71% in the prediction of disease recurrence. Patients' age and substage were of no prognostic value. We conclude that the nuclear morphometric characteristics, especially the presence of giant nuclear cells and nuclear irregularity, may be useful in predicting outcome in patients with early stage ovarian clear cell adenocarcinoma. © 1999 Cancer Research Campaig

    A simple statistical model for prediction of acute coronary syndrome in chest pain patients in the emergency department

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    BACKGROUND: Several models for prediction of acute coronary syndrome (ACS) among chest pain patients in the emergency department (ED) have been presented, but many models predict only the likelihood of acute myocardial infarction, or include a large number of variables, which make them less than optimal for implementation at a busy ED. We report here a simple statistical model for ACS prediction that could be used in routine care at a busy ED. METHODS: Multivariable analysis and logistic regression were used on data from 634 ED visits for chest pain. Only data immediately available at patient presentation were used. To make ACS prediction stable and the model useful for personnel inexperienced in electrocardiogram (ECG) reading, simple ECG data suitable for computerized reading were included. RESULTS: Besides ECG, eight variables were found to be important for ACS prediction, and included in the model: age, chest discomfort at presentation, symptom duration and previous hypertension, angina pectoris, AMI, congestive heart failure or PCI/CABG. At an ACS prevalence of 21% and a set sensitivity of 95%, the negative predictive value of the model was 96%. CONCLUSION: The present prediction model, combined with the clinical judgment of ED personnel, could be useful for the early discharge of chest pain patients in populations with a low prevalence of ACS

    Scalar and vector Slepian functions, spherical signal estimation and spectral analysis

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    It is a well-known fact that mathematical functions that are timelimited (or spacelimited) cannot be simultaneously bandlimited (in frequency). Yet the finite precision of measurement and computation unavoidably bandlimits our observation and modeling scientific data, and we often only have access to, or are only interested in, a study area that is temporally or spatially bounded. In the geosciences we may be interested in spectrally modeling a time series defined only on a certain interval, or we may want to characterize a specific geographical area observed using an effectively bandlimited measurement device. It is clear that analyzing and representing scientific data of this kind will be facilitated if a basis of functions can be found that are "spatiospectrally" concentrated, i.e. "localized" in both domains at the same time. Here, we give a theoretical overview of one particular approach to this "concentration" problem, as originally proposed for time series by Slepian and coworkers, in the 1960s. We show how this framework leads to practical algorithms and statistically performant methods for the analysis of signals and their power spectra in one and two dimensions, and, particularly for applications in the geosciences, for scalar and vectorial signals defined on the surface of a unit sphere.Comment: Submitted to the 2nd Edition of the Handbook of Geomathematics, edited by Willi Freeden, Zuhair M. Nashed and Thomas Sonar, and to be published by Springer Verlag. This is a slightly modified but expanded version of the paper arxiv:0909.5368 that appeared in the 1st Edition of the Handbook, when it was called: Slepian functions and their use in signal estimation and spectral analysi
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