Prediction of microRNAs affecting mRNA expression during retinal development.

Background: MicroRNAs (miRNAs) are small RNA molecules (similar to 22 nucleotides) which have been shown to play an important role both in development and in maintenance of adult tissue. Conditional inactivation of miRNAs in the eye causes loss of visual function and progressive retinal degeneration. In addition to inhibiting translation, miRNAs can mediate degradation of targeted mRNAs. We have previously shown that candidate miRNAs affecting transcript levels in a tissue can be deduced from mRNA microarray expression profiles. The purpose of this study was to predict miRNAs which affect mRNA levels in developing and adult retinal tissue and to confirm their expression.

Results: Microarray expression data from ciliary epithelial retinal stem cells (CE-RSCs), developing and adult mouse retina were generated or downloaded from public repositories. Analysis of gene expression profiles detected the effects of multiple miRNAs in CE-RSCs and retina. The expression of 20 selected miRNAs was confirmed by RT-PCR and the cellular distribution of representative candidates analyzed by in situ hybridization. The expression levels of miRNAs correlated with the significance of their predicted effects upon mRNA expression. Highly expressed miRNAs included miR-124, miR-125a, miR-125b, miR-204 and miR-9. Over-expression of three miRNAs with significant predicted effects upon global mRNA levels resulted in a decrease in mRNA expression of five out of six individual predicted target genes assayed.

Conclusions: This study has detected the effect of miRNAs upon mRNA expression in immature and adult retinal tissue and cells. The validity of these observations is supported by the experimental confirmation of candidate miRNA expression and the regulation of predicted target genes following miRNA over-expression. Identified miRNAs are likely to be important in retinal development and function. Misregulation of these miRNAs might contribute to retinal degeneration and disease. Conversely, manipulation of their expression could potentially be used as a therapeutic tool in the future.

Priming of CD8+ and CD4+ T Cells in Experimental Leishmaniasis Is Initiated by Different Dendritic Cell Subtypes

The biological role of Langerin(+) dendritic cells (DCs) such as Langerhans cells and a subset of dermal DCs (dDCs) in adaptive immunity against cutaneous pathogens remains enigmatic. Thus, we analyzed the impact of Langerin(+) DCs in adaptive T cell-mediated immunity toward Leishmania major parasites in a Lang-DTR mouse model that allows conditional diphtheria toxin (DT)-induced ablation of The biological role of Langerin+ dendritic cells (DCs) such as Langerhans cells and a subset of dermal DCs (dDCs) in adaptive immunity against cutaneous pathogens remains enigmatic. Thus, we analyzed the impact of Langerin+ DCs in adaptive T cell-mediated immunity toward Leishmania major parasites in a Lang-DTR mouse model that allows conditional diphtheria toxin (DT)-induced ablation of Langerin+ DCs in vivo. For the first time, infection experiments with DT-treated Lang-DTR mice revealed that proliferation of L. major-specific CD8+ T cells is significantly reduced during the early phase of the immune response following depletion of Langerin+ DCs. Consequently, the total number of activated CD8+ T cells within the draining lymph node and at the site of infection is diminished. Furthermore, we show that the impaired CD8+ T cell response is due to the absence of Langerin+ dDCs and not Langerhans cells. Nevertheless, the CD4+ T cell response is not altered and the infection is cleared as effectively in DT-treated Lang-DTR mice as in control mice. This clearly demonstrates that Langerin+ DCs are, in general, dispensable for an efficient adaptive immune response against L. major parasites. Thus, we propose a novel concept that, in the experimental model of leishmaniasis, priming of CD4+ T cells is mediated by Langerin− dDCs, whereas Langerin+ dDCs are involved in early priming of CD8+ T cells.

A framework for managing uncertain inputs: An axiomization of rewarding

The success postulate in belief revision ensures that new evidence (input) is always trusted. However, admitting uncertain input has been questioned by many researchers. Darwiche and Pearl argued that strengths of evidence should be introduced to determine the outcome of belief change, and provided a preliminary definition towards this thought. In this paper, we start with Darwiche and Pearl’s idea aiming to develop a framework that can capture the influence of the strengths of inputs with some rational assumptions. To achieve this, we first define epistemic states to represent beliefs attached with strength, and then present a set of postulates to describe the change process on epistemic states that is determined by the strengths of input and establish representation theorems to characterize these postulates. As a result, we obtain a unique rewarding operator which is proved to be a merging operator that is in line with many other works. We also investigate existing postulates on belief merging and compare them with our postulates. In addition, we show that from an epistemic state, a corresponding ordinal conditional function by Spohn can be derived and the result of combining two epistemic states is thus reduced to the result of combining two corresponding ordinal conditional functions proposed by Laverny and Lang. Furthermore, when reduced to the belief revision situation, we prove that our results induce all the Darwiche and Pearl’s postulates as well as the Recalcitrance postulate and the Independence postulate.

Modelling the mechanical response of the Reed-mouthpiece-lip system of a clarinet. Part I. A one-dimensional distributed model

The motion of a clarinet reed that is clamped to a mouthpiece and supported by a lip is simulated in the time-domain using finite difference methods. The reed is modelled as a bar with non-uniform cross section, and is described using a one-dimensional, fourth-order partial differential equation. The interactions with the mouthpiece Jay and the player's lip are taken into account by incorporating conditional contact forces in the bar equation. The model is completed by clamped-free boundary conditions for the reed. An implicit finite difference method is used for discretising the system, and values for the physical parameters are chosen both from laboratory measurements and by accurate tuning of the numerical simulations. The accuracy of the numerical system is assessed through analysis of frequency warping effects and of resonance estimation. Finally, the mechanical properties of the system are studied by analysing its response to external driving forces. In particular, the effects of reed curling are investigated.

Maximum likelihood estimation of higher-order integer-valued autoregressive processes

In this article, we extend the earlier work of Freeland and McCabe [Journal of time Series Analysis (2004) Vol. 25, pp. 701–722] and develop a general framework for maximum likelihood (ML) analysis of higher-order integer-valued autoregressive processes. Our exposition includes the case where the innovation sequence has a Poisson distribution and the thinning is binomial. A recursive representation of the transition probability of the model is proposed. Based on this transition probability, we derive expressions for the score function and the Fisher information matrix, which form the basis for ML estimation and inference. Similar to the results in Freeland and McCabe (2004), we show that the score function and the Fisher information matrix can be neatly represented as conditional expectations. Using the INAR(2) speci?cation with binomial thinning and Poisson innovations, we examine both the asymptotic e?ciency and ?nite sample properties of the ML estimator in relation to the widely used conditional least
squares (CLS) and Yule–Walker (YW) estimators. We conclude that, if the Poisson assumption can be justi?ed, there are substantial gains to be had from using ML especially when the thinning parameters are large.

Testosterone levels in dominant sociable males are lower than in solitary roamers: Physiological differences between three male reproductive tactics in a sociably flexible mammal

The relative plasticity hypothesis predicts that alternative tactics are associated with changes in steroid hormone levels. In species with alternative male reproductive tactics, the highest androgen levels have usually been reported in dominant males. However, in sociable species, dominant males show amicable behaviors to gain access to females, which might conflict with high testosterone levels. We compared testosterone, corticosterone, and resting metabolic rate in male striped mice (Rhabdomys pumilio) following a conditional strategy with three different reproductive tactics: (i) philopatric group-living males, (ii) solitary-living roamers, (iii) dominant but sociable group-living territorial breeders. Philopatrics had the lowest testosterone but highest corticosterone levels, suggesting that they make the best of a bad job. Dominant territorial breeders had lower testosterone levels than roamers, which have a lower competitive status. Roamers had the highest testosterone levels, which might promote risky behavior, such as invading territories defended by territorial males. Roamers also had lower resting metabolic rates than either type of group-living males. Our results suggest that dominant males' testosterone levels reflect a trade-off between low testosterone amicable behavior and high testosterone dominance behavior.

Modeling Multivariate Interest Rates Using Time-Varying Copulas and Reducible Nonlinear Stochastic Differential Equations

We propose a new approach for modeling nonlinear multivariate interest rate processes based on time-varying copulas and reducible stochastic differential equations (SDEs). In the modeling of the marginal processes, we consider a class of nonlinear SDEs that are reducible to Ornstein--Uhlenbeck (OU) process or Cox, Ingersoll, and Ross (1985) (CIR) process. The reducibility is achieved via a nonlinear transformation function. The main advantage of this approach is that these SDEs can account for nonlinear features, observed in short-term interest rate series, while at the same time leading to exact discretization and closed-form likelihood functions. Although a rich set of specifications may be entertained, our exposition focuses on a couple of nonlinear constant elasticity volatility (CEV) processes, denoted as OU-CEV and CIR-CEV, respectively. These two processes encompass a number of existing models that have closed-form likelihood functions. The transition density, the conditional distribution function, and the steady-state density function are derived in closed form as well as the conditional and unconditional moments for both processes. In order to obtain a more flexible functional form over time, we allow the transformation function to be time varying. Results from our study of U.S. and UK short-term interest rates suggest that the new models outperform existing parametric models with closed-form likelihood functions. We also find the time-varying effects in the transformation functions statistically significant. To examine the joint behavior of interest rate series, we propose flexible nonlinear multivariate models by joining univariate nonlinear processes via appropriate copulas. We study the conditional dependence structure of the two rates using Patton (2006a) time-varying symmetrized Joe--Clayton copula. We find evidence of asymmetric dependence between the two rates, and that the level of dependence is positively related to the level of the two rates. (JEL: C13, C32, G12) Copyright The Author 2010. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org, Oxford University Press.

Putting a Price on Prisoner Release: The History of Bail and the Future of Parole

In this article, we argue that the history of bail foretells the future of parole. Under a plancalled the Conditional Post-Conviction Release Bond Act (recently passed into law inthree states), US prisoners can secure early release only after posting ‘post-convictionbail’. As with pre-trial bail, the fledgling model would require prisoners to pay a percent-age of the bail amount to secure their release under the contractual responsibility of acommercial bail agency. If release conditions are breached, bounty hunters are legallyempowered to seize and return the parolee to prison. Our inquiry outlines the origins of this post-conviction bond plan and the research upon which it is based. Drawing on the‘new penology’ framework, we identify several underlying factors that make for a ripeadvocacy environment and set the stage for widespread state-level adoption of this planin the near future. Post-conviction bail fits squarely within the growing policy trendstoward privatization, managerialism, and actuarial justice. Most importantly, though,advocates have the benefit of precedent on their side, as most US states have longrelied on a system of commercial bail bonding and private bounty hunting to manageconditional pretrial release.

Pax7-expressing satellite cells are indispensable for adult skeletal muscle regeneration

Distinct cell populations with regenerative capacity have been reported to contribute to myofibres after skeletal muscle injury, including non-satellite cells as well as myogenic satellite cells. However, the relative contribution of these distinct cell types to skeletal muscle repair and homeostasis and the identity of adult muscle stem cells remain unknown. We generated a model for the conditional depletion of satellite cells by expressing a human diphtheria toxin receptor under control of the murine Pax7 locus. Intramuscular injection of diphtheria toxin during muscle homeostasis, or combined with muscle injury caused by myotoxins or exercise, led to a marked loss of muscle tissue and failure to regenerate skeletal muscle. Moreover, the muscle tissue became infiltrated by inflammatory cells and adipocytes. This localised loss of satellite cells was not compensated for endogenously by other cell types, but muscle regeneration was rescued after transplantation of adult Pax7(+) satellite cells alone. These findings indicate that other cell types with regenerative potential depend on the presence of the satellite cell population, and these observations have important implications for myopathic conditions and stem cell-based therapeutic approaches.

Proton pump inhibitors and histamine-2-receptor antagonists and pancreatic cancer risk: a nested case-control study

Background: The relationship between use of proton pump inhibitors (PPIs) and histamine-2-receptor antagonists (H₂RAs) and pancreatic cancer risk has yet to be examined. Data from a range of studies suggest biologically plausible mechanisms, whereby these drugs (or the conditions for which they are prescribed) may affect pancreatic cancer risk. The objective of this study was to investigate the relationship between use of PPIs/H₂RAs and pancreatic cancer risk.

Methods: A nested case – control study was conducted within the UK general practice research database (GPRD). Cases had a diagnosis of exocrine pancreatic cancer and controls were matched to cases on general practice site, sex and year of birth. Exposure to PPIs and to H₂RAs since entry into GPRD until 2 years before the diagnosis date (corresponding date in controls) and in the 5 years before the diagnosis date were separately assessed. Conditional logistic regression analyses were used to generate odds ratios (ORs) and 95% confidence intervals (CIs) associated with PPI or H₂RA use compared with nonuse.

Results: Ever use of PPIs since entry into the GPRD (excluding the 2 years prior to diagnosis) was not associated with risk of pancreatic cancer; OR (95% CI) 1.02 (0.85 – 1.22). Neither the dose nor the duration of PPI or H₂RA use was associated with pancreatic cancer risk. No consistent patterns of association were seen when cumulative exposure (dose and duration) to these drugs was examined separately or together.

Conclusion: PPI/H₂RA use, in a UK population, was not associated with pancreatic cancer risk.

Luminescent Photoinduced Electron Transfer (PET) Molecules for Sensing and Logic Operations

Chemical species can serve as inputs to supramolecular devices so that a luminescence output is created in a conditional manner. Conditionality is built into these devices by employing the classical photochemical process of photoinduced electron transfer (PET) to compete with luminescence emission. The response of these devices in the analogue regime leads to sensors that can operate in nanometric, micrometric, and millimetric spaces. Some of these devices serve in membrane science, cell physiology, and medical diagnostics. The response in the digital regime leads to Boolean logic gates. Some of these find application in improving aspects of medical diagnostics and in identifying small objects in large populations.

How Porosity and Permeability Vary Spatially With Grain Size, Sorting, Cement Volume, and Mineral Dissolution In Fluvial Triassic Sandstones: The Value of Geostatistics and Local Regression

Although it is well known that sandstone porosity and permeability are controlled by a range of parameters such as grain size and sorting, amount, type, and location of diagenetic cements, extent and type of compaction, and the generation of intergranular and intragranular secondary porosity, it is less constrained how these controlling parameters link up in rock volumes (within and between beds) and how they spatially interact to determine porosity and permeability. To address these unknowns, this study examined Triassic fluvial sandstone outcrops from the UK using field logging, probe permeametry of 200 points, and sampling at 100 points on a gridded rock surface. These field observations were supplemented by laser particle-size analysis, thin-section point-count analysis of primary and diagenetic mineralogy, quantitiative XRD mineral analysis, and SEM/EDAX analysis of all 100 samples. These data were analyzed using global regression, variography, kriging, conditional simulation, and geographically weighted regression to examine the spatial relationships between porosity and permeability and their potential controls. The results of bivariate analysis (global regression) of the entire outcrop dataset indicate only a weak correlation between both permeability porosity and their diagenetic and depositional controls and provide very limited information on the role of primary textural structures such as grain size and sorting. Subdividing the dataset further by bedding unit revealed details of more local controls on porosity and permeability. An alternative geostatistical approach combined with a local modelling technique (geographically weighted regression; GWR) subsequently was used to examine the spatial variability of porosity and permeability and their controls. The use of GWR does not require prior knowledge of divisions between bedding units, but the results from GWR broadly concur with results of regression analysis by bedding unit and provide much greater clarity of how porosity and permeability and their controls vary laterally and vertically. The close relationship between depositional lithofacies in each bed, diagenesis, and permeability, porosity demonstrates that each influences the other, and in turn how understanding of reservoir properties is enhanced by integration of paleoenvironmental reconstruction, stratigraphy, mineralogy, and geostatistics.

A model for radiation-induced bystander effects, with allowance for spatial position and the effects of cell turnover

Bystander effects, whereby cells that are not directly exposed to ionizing radiation exhibit adverse biological effects, have been observed in a number of experimental systems. A novel stochastic model of the radiation-induced bystander effect is developed that takes account of spatial location, cell killing and repopulation. The ionizing radiation dose- and time-responses of this model are explored, and it is shown to exhibit pronounced downward curvature in the high dose-rate region, similar to that observed in many experimental systems, reviewed in the paper. It is also shown to predict the augmentation of effect after fractionated delivery of dose that has been observed in certain experimental systems. It is shown that the generally intractable solution of the full stochastic system can be considerably simplified by assumption of pairwise conditional dependence that varies exponentially over time. (C) 2004 Elsevier Ltd. All rights reserved.

Speculative Return Address Stack Management Revisited

Branch prediction feeds a speculative execution processor core with instructions. Branch mispredictions are inevitable and have negative effects on performance and energy consumption. With the advent of highly accurate conditional branch predictors, nonconditional branch instructions are gaining importance.

Behavior-Based branch prediction by dynamically clustering branch instructions

Conditional branches frequently exhibit similar behavior (bias, time-varying behavior,...), a property that can be used to improve branch prediction accuracy. Branch clustering constructs groups or clusters of branches with similar behavior and applies different branch prediction techniques to each branch cluster. We revisit the topic of branch clustering with the aim of generalizing branch clustering. We investigate several methods to measure cluster information, with the most effective the storage of information in the branch target buffer. Also, we investigate alternative methods of using the branch cluster identification in the branch predictor. By these improvements we arrive at a branch clustering technique that obtains higher accuracy than previous approaches presented in the literature for the gshare predictor. Furthermore, we evaluate our branch clustering technique in a wide range of predictors to show the general applicability of the method. Branch clustering improves the accuracy of the local history (PAg) predictor, the path-based perceptron and the PPM-like predictor, one of the 2004 CBP finalists.