Transcriptional slippage in bacteria: distribution in sequenced genomes and utilization in IS element gene expression

BACKGROUND: Transcription slippage occurs on certain patterns of repeat mononucleotides, resulting in synthesis of a heterogeneous population of mRNAs. Individual mRNA molecules within this population differ in the number of nucleotides they contain that are not specified by the template. When transcriptional slippage occurs in a coding sequence, translation of the resulting mRNAs yields more than one protein product. Except where the products of the resulting mRNAs have distinct functions, transcription slippage occurring in a coding region is expected to be disadvantageous. This probably leads to selection against most slippage-prone sequences in coding regions. RESULTS: To find a length at which such selection is evident, we analyzed the distribution of repetitive runs of A and T of different lengths in 108 bacterial genomes. This length varies significantly among different bacteria, but in a large proportion of available genomes corresponds to nine nucleotides. Comparative sequence analysis of these genomes was used to identify occurrences of 9A and 9T transcriptional slippage-prone sequences used for gene expression. CONCLUSIONS: IS element genes are the largest group found to exploit this phenomenon. A number of genes with disrupted open reading frames (ORFs) have slippage-prone sequences at which transcriptional slippage would result in uninterrupted ORF restoration at the mRNA level. The ability of such genes to encode functional full-length protein products brings into question their annotation as pseudogenes and in these cases is pertinent to the significance of the term 'authentic frameshift' frequently assigned to such genes

Beyond deficit-based models of learners' cognition: Interpreting engineering students' difficulties with sense-making in terms of fine-grained epistemological and conceptual dynamics

Researchers have argued against deficit-based explanations of students' troubles with mathematical sense-making, pointing instead to factors such as epistemology: students' beliefs about knowledge and learning can hinder them from activating and integrating productive knowledge they have. In this case study of an engineering major solving problems (about content from his introductory physics course) during a clinical interview, we show that "Jim" has all the mathematical and conceptual knowledge he would need to solve a hydrostatic pressure problem that we posed to him. But he reaches and sticks with an incorrect answer that violates common sense. We argue that his lack of mathematical sense-making-specifically, translating and reconciling between mathematical and everyday/common-sense reasoning-stems in part from his epistemological views, i.e., his views about the nature of knowledge and learning. He regards mathematical equations as much more trustworthy than everyday reasoning, and he does not view mathematical equations as expressing meaning that tractably connects to common sense. For these reasons, he does not view reconciling between common sense and mathematical formalism as either necessary or plausible to accomplish. We, however, avoid a potential "deficit trap"-substituting an epistemological deficit for a concepts/skills deficit-by incorporating multiple, context-dependent epistemological stances into Jim's cognitive dynamics. We argue that Jim's epistemological stance contains productive seeds that instructors could build upon to support Jim's mathematical sense-making: He does see common-sense as connected to formalism (though not always tractably so) and in some circumstances this connection is both salient and valued.Comment: Submitted to the Journal of Engineering Educatio

Early Gadolinium Enhancement for Area at Risk Determination: A Preclinical Validation Study

Objectives—The aim of this study was to determine if early gadolinium enhancement (EGE) by cardiovascular magnetic resonance (CMR) imaging in a canine model of reperfused myocardial infarction depicts the area at risk (AAR) as determined by microsphere blood flow analysis. Background—It remains controversial whether only the irreversibly injured myocardium enhances when performing CMR imaging in the setting of acute myocardial infarction. Recently, EGE has been proposed as a measure of the AAR in acute myocardial infarction as it correlates well with T2-weighted imaging of the AAR, but still requires pathological validation. Methods—Eleven dogs underwent 2 hours of coronary artery occlusion and 48 hours of reperfusion prior to imaging at 1.5T. EGE imaging was performed 3 minutes after contrast administration with coverage of the entire left ventricle. Late gadolinium enhancement (LGE) imaging was performed between 10 and 15 minutes after contrast injection. AAR was defined as myocardium with blood flow (mL/min/g) \u3c 2SD from remote myocardium determined by microspheres during occlusion. The size of infarction was determined using triphenyltetrazolium chloride (TTC). Results—There was no significant difference in the size of enhancement by EGE compared to the size of AAR by microspheres (44.1± 15.8% vs. 42.7± 9.2%, p=0.61) with good correlation (r=0.88, p \u3c 0.001) and good agreement by Bland-Altman analysis (mean bias 1.4± 17.4%). There was no difference in the size of enhancement by EGE compared to enhancement on native T1 and T2 maps. The size of EGE was significantly greater than the infarct by TTC, (44.1± 15.8% vs. 20.7± 14.4%, p \u3c 0.001) and LGE (44.1± 15.8% vs. 23.5± 12.7%, p \u3c 0.001). Conclusion—At three minutes post-contrast, EGE correlated well with the AAR by microspheres and CMR, and was greater than infarct size. Thus, EGE enhances both reversibly and irreversibly injured myocardium

First-principles extrapolation method for accurate CO adsorption energies on metal surfaces

We show that a simple first-principles correction based on the difference between the singlet-triplet CO excitation energy values obtained by DFT and high-level quantum chemistry methods yields accurate CO adsorption properties on a variety of metal surfaces. We demonstrate a linear relationship between the CO adsorption energy and the CO singlet-triplet splitting, similar to the linear dependence of CO adsorption energy on the energy of the CO 2$\pi$* orbital found recently {[Kresse {\em et al.}, Physical Review B {\bf 68}, 073401 (2003)]}. Converged DFT calculations underestimate the CO singlet-triplet excitation energy $\Delta E_{\rm S-T}$, whereas coupled-cluster and CI calculations reproduce the experimental $\Delta E_{\rm S-T}$. The dependence of $E_{\rm chem}$ on $\Delta E_{\rm S-T}$ is used to extrapolate $E_{\rm chem}$ for the top, bridge and hollow sites for the (100) and (111) surfaces of Pt, Rh, Pd and Cu to the values that correspond to the coupled-cluster and CI $\Delta E_{\rm S-T}$ value. The correction reproduces experimental adsorption site preference for all cases and obtains $E_{\rm chem}$ in excellent agreement with experimental results.Comment: Table sent as table1.eps. 3 figure

Bailing Out the Milky Way: Variation in the Properties of Massive Dwarfs Among Galaxy-Sized Systems

Recent kinematical constraints on the internal densities of the Milky Way's dwarf satellites have revealed a discrepancy with the subhalo populations of simulated Galaxy-scale halos in the standard CDM model of hierarchical structure formation. This has been dubbed the "too big to fail" problem, with reference to the improbability of large and invisible companions existing in the Galactic environment. In this paper, we argue that both the Milky Way observations and simulated subhalos are consistent with the predictions of the standard model for structure formation. Specifically, we show that there is significant variation in the properties of subhalos among distinct host halos of fixed mass and suggest that this can reasonably account for the deficit of dense satellites in the Milky Way. We exploit well-tested analytic techniques to predict the properties in a large sample of distinct host halos with a variety of masses spanning the range expected of the Galactic halo. The analytic model produces subhalo populations consistent with both Via Lactea II and Aquarius, and our results suggest that natural variation in subhalo properties suffices to explain the discrepancy between Milky Way satellite kinematics and these numerical simulations. At least ~10% of Milky Way-sized halos host subhalo populations for which there is no "too big to fail" problem, even when the host halo mass is as large as M_host = 10^12.2 h^-1 M_sun. Follow-up studies consisting of high-resolution simulations of a large number of Milky Way-sized hosts are necessary to confirm our predictions. In the absence of such efforts, the "too big to fail" problem does not appear to be a significant challenge to the standard model of hierarchical formation. [abridged]Comment: 12 pages, 3 figures; accepted by JCAP. Replaced with published versio

The impact of dark matter cusps and cores on the satellite galaxy population around spiral galaxies

(Abridged) We use N-body simulations to study the effects that a divergent (i.e. "cuspy") dark matter (DM) profile introduces on the tidal evolution of dwarf spheroidal galaxies (dSphs). Our models assume cosmologically-motivated initial conditions where dSphs are DM-dominated systems on eccentric orbits about a host galaxy composed of a dark halo and a baryonic disc. We find that the resilience of dSphs to tidal stripping is extremely sensitive to the halo cuspiness; whereas dwarfs with a cored profile can be easily destroyed by the host disc, those with cusps always retain a bound remnant. For a given halo profile the evolution of the structural parameters as driven by tides is controlled solely by the total amount of mass lost. This information is used to construct a semi-analytic code that simulates the hierarchical build-up of spiral galaxies assuming different halo profiles and disc masses. We find that tidal encounters with discs tend to decrease the average mass of satellites at all galactocentric radii. Interestingly, satellites accreted before re-ionization (z>6), which may be singled out by anomalous metallicity patterns, survive only if haloes are cuspy. We show that the size-mass relation established from Milky Way (MW) dwarfs strongly supports the presence of cusps in the majority of these systems, as cored models systematically underestimate the masses of the known Ultra-Faint dSphs. Our models also indicate that a massive M31 disc may explain why many of its dSphs fall below the size-mass relationship derived from MW dSphs. We use our models to constrain the mass threshold below which star formation is suppressed in DM haloes, finding that luminous satellites must be accreted with masses above 10^8--10^9 M_sol in order to explain the size-mass relation observed in MW dwarfs.Comment: 17 pages, 14 figures, MNRAS accepted after minor revisio

The Cost of Universal Health Care in India: A Model Based Estimate

Introduction: As high out-of-pocket healthcare expenses pose heavy financial burden on the families, Government of India is considering a variety of financing and delivery options to universalize health care services. Hence, an estimate of the cost of delivering universal health care services is needed. Methods: We developed a model to estimate recurrent and annual costs for providing health services through a mix of public and private providers in Chandigarh located in northern India. Necessary health services required to deliver goo

MultiRTA: A simple yet reliable method for predicting peptide binding affinities for multiple class II MHC allotypes

abstract: Background The binding of peptide fragments of antigens to class II MHC is a crucial step in initiating a helper T cell immune response. The identification of such peptide epitopes has potential applications in vaccine design and in better understanding autoimmune diseases and allergies. However, comprehensive experimental determination of peptide-MHC binding affinities is infeasible due to MHC diversity and the large number of possible peptide sequences. Computational methods trained on the limited experimental binding data can address this challenge. We present the MultiRTA method, an extension of our previous single-type RTA prediction method, which allows the prediction of peptide binding affinities for multiple MHC allotypes not used to train the model. Thus predictions can be made for many MHC allotypes for which experimental binding data is unavailable. Results We fit MultiRTA models for both HLA-DR and HLA-DP using large experimental binding data sets. The performance in predicting binding affinities for novel MHC allotypes, not in the training set, was tested in two different ways. First, we performed leave-one-allele-out cross-validation, in which predictions are made for one allotype using a model fit to binding data for the remaining MHC allotypes. Comparison of the HLA-DR results with those of two other prediction methods applied to the same data sets showed that MultiRTA achieved performance comparable to NetMHCIIpan and better than the earlier TEPITOPE method. We also directly tested model transferability by making leave-one-allele-out predictions for additional experimentally characterized sets of overlapping peptide epitopes binding to multiple MHC allotypes. In addition, we determined the applicability of prediction methods like MultiRTA to other MHC allotypes by examining the degree of MHC variation accounted for in the training set. An examination of predictions for the promiscuous binding CLIP peptide revealed variations in binding affinity among alleles as well as potentially distinct binding registers for HLA-DR and HLA-DP. Finally, we analyzed the optimal MultiRTA parameters to discover the most important peptide residues for promiscuous and allele-specific binding to HLA-DR and HLA-DP allotypes. Conclusions The MultiRTA method yields competitive performance but with a significantly simpler and physically interpretable model compared with previous prediction methods. A MultiRTA prediction webserver is available at http://bordnerlab.org/MultiRTA.The electronic version of this article is the complete one and can be found online at: http://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-48

Insulin-like growth factor 2 mRNA binding protein 3 (IGF2BP3) overexpression in pancreatic ductal adenocarcinoma correlates with poor survival

<p>Abstract</p> <p>Background</p> <p>Pancreatic ductal adenocarcinoma is a lethal disease with a 5-year survival rate of 4% and typically presents in an advanced stage. In this setting, prognostic markers identifying the more agrressive tumors could aid in managment decisions. Insulin-like growth factor 2 mRNA binding protein 3 (IGF2BP3, also known as IMP3 or KOC) is an oncofetal RNA-binding protein that regulates targets such as insulin-like growth factor-2 (IGF-2) and ACTB (beta-actin).</p> <p>Methods</p> <p>We evaluated the expression of IGF2BP3 by immunohistochemistry using a tissue microarray of 127 pancreatic ductal adenocarcinomas with tumor grade 1, 2 and 3 according to WHO criteria, and the prognostic value of IGF2BP3 expression.</p> <p>Results</p> <p>IGF2BP3 was found to be selectively overexpressed in pancreatic ductal adenocarcinoma tissues but not in benign pancreatic tissues. Nine (38%) patient samples of tumor grade 1 (n = 24) and 27 (44%) of tumor grade 2 (n = 61) showed expression of IGF2BP3. The highest rate of expression was seen in poorly differentiated specimen (grade 3, n = 42) with 26 (62%) positive samples. Overall survival was found to be significantly shorter in patients with IGF2BP3 expressing tumors (P = 0.024; RR 2.3, 95% CI 1.2-4.8).</p> <p>Conclusions</p> <p>Our data suggest that IGF2BP3 overexpression identifies a subset of pancreatic ductal adenocarcinomas with an extremely poor outcome and supports the rationale for developing therapies to target the IGF pathway in this cancer.</p