Mechanism for the learning deficits in a mouse model of neurofibromatosis type 1.

Neurofibromatosis type I (NF1) is one of the most common single-gene disorders that causes learning deficits in humans. Mice carrying a heterozygous null mutation of the Nfl gene (Nfl(+/-) show important features of the learning deficits associated with NF1 (ref. 2). Although neurofibromin has several known properties and functions, including Ras GTPase-activating protein activity, adenylyl cyclase modulation and microtubule binding, it is unclear which of these are essential for learning in mice and humans. Here we show that the learning deficits of Nf1(+/-) mice can be rescued by genetic and pharmacological manipulations that decrease Ras function. We also show that the Nf1(+/-) mice have increased GABA (gamma-amino butyric acid)-mediated inhibition and specific deficits in long-term potentiation, both of which can be reversed by decreasing Ras function. Our results indicate that the learning deficits associated with NF1 may be caused by excessive Ras activity, which leads to impairments in long-term potentiation caused by increased GABA-mediated inhibition. Our findings have implications for the development of treatments for learning deficits associated with NF1.     

The detection of superoxide anion from the reaction of oxyhemoglobin and phenylhydrazine using EPR spectroscopy

Summary The low temperature EPR spectrum of a quickly reacted mixture of oxyhemoglobin and phenylhydrazine was studied. With the use of a computer, the spectral contribution of methemoglobin in the region of g=2 was subtracted. The remaining spectrum was that of an axial free radical (g=2.00, g=2.06) having the magnetic parameters of superoxide anion. In the presence of superoxide dismutase, this axial radical was not seen, confirming that superoxide anion is indeed generated by the reaction.The portion of this investigation carried out at the Albert Einstein College of Medicine was supported in part by US Public Health Service Research Grant HL-93399 from the Heart and Lung Institute and by National Institute Contract Nol-CP-55606 to J.P. This is communication No. 378 from the Joan and Lester Avnet Institute of Molecular Biology.Predoctoral fellow in the Medical Scientist Training Program (United States Public Health Service Grant 5-TO-5-GM 01669-12) at the New York University School of Medicine.Recipient of a grant-in-aid from the New York Heart Association.     

Northern Bobwhite habitat selection in relation to brush management in the Rolling Plains of Texas

Many rangelands in the southwestern United States provide quality habitat for Northern Bobwhites ( Colinus virginianus ). These same habitats are frequently managed for livestock production and thus are subjected to various brush management practices that are meant to enhance forage production. Bobwhites rely on woody cover for food, thermal and loafing cover, and protection from avian predators. Implementing brush management practices that reflect bobwhite requirements is important for managing usable space and viable populations. We described the structural vegetative characteristics associated with bobwhite locations and random locations on native rangelands in the upper Rolling Plains of Texas that are dominated by honey mesquite ( Prosopis glandulosa ) and managed with aerial herbicide and prescribed fire. We also used binary logistic regression to model habitat selection; the initial model was built using 67% of the data ( n = 179 used-random paired points) and then validated using the remaining 33% of the data ( n = 88 used-random paired points). Locations used by bobwhites had significantly larger mean values of percent brush canopy cover, visual obstruction, and angle of obstruction than did random locations; random locations had a greater mean value of percent bare ground than locations used by bobwhites. The resulting logistic regression model contained only the angle of obstruction; the model had an 80% probability of correctly classifying used and random locations based on the area under the receiver operating curve (ROC). The model maintained a high classification probability when applied to the smaller validation data set, with an area under the ROC of 0.78.     

The implications of viral reservoirs on the elite control of HIV-1 infection

The mechanisms by which a small percentage of HIV-1 infected individuals known as elite suppressors or controllers are able to control viral replication are not fully understood. Early cases of viremic control were attributed to infection with defective virus, but subsequent work has demonstrated that infection with a defective virus is not the exclusive cause of control. Replication-competent virus has been isolated from patients who control viral replication, and studies have demonstrated that evolution occurs in plasma virus but not in virus isolates from the latent reservoir. Additionally, transmission pair studies have demonstrated that patients infected with similar viruses can have dramatically different outcomes of infection. An increased understanding of the viral factors associated with control is important to understand the interplay between viral replication and host control, and has implications for the design of an effective therapeutic vaccine that can lead to a functional cure of HIV-1 infection.     

Prediction from the One‐Way Error Components Model with AR(1) Disturbances

In this paper we extend the works of Baillie and Baltagi (1999, in Analysis of Panels and Limited Dependent Variables Models, Hsiao C et al. (eds). Cambridge University Press: Cambridge, UK; 255–267) and generalize certain results from the Baltagi and Li (1992, Journal of Forecasting 11 : 561–567) paper accounting for AR(1) errors in the disturbance term. In particular, we derive six predictors for the one‐way error components model, as well as their associated asymptotic mean squared error of multi‐step prediction in the presence of AR(1) errors in the disturbance term. In addition, we also provide both theoretical and simulation evidence as to the relative efficiency of our alternative predictors. The adequacy of the prediction AMSE formula is also investigated by the use of Monte Carlo methods and indicates that the ordinary optimal predictor performs well for various accuracy criteria. Copyright © 2011 John Wiley & Sons, Ltd.     

Glucose sensing by POMC neurons regulates glucose homeostasis and is impaired in obesity

A subset of neurons in the brain, known as 'glucose-excited' neurons, depolarize and increase their firing rate in response to increases in extracellular glucose. Similar to insulin secretion by pancreatic beta-cells, glucose excitation of neurons is driven by ATP-mediated closure of ATP-sensitive potassium (K(ATP)) channels. Although beta-cell-like glucose sensing in neurons is well established, its physiological relevance and contribution to disease states such as type 2 diabetes remain unknown. To address these issues, we disrupted glucose sensing in glucose-excited pro-opiomelanocortin (POMC) neurons via transgenic expression of a mutant Kir6.2 subunit (encoded by the Kcnj11 gene) that prevents ATP-mediated closure of K(ATP) channels. Here we show that this genetic manipulation impaired the whole-body response to a systemic glucose load, demonstrating a role for glucose sensing by POMC neurons in the overall physiological control of blood glucose. We also found that glucose sensing by POMC neurons became defective in obese mice on a high-fat diet, suggesting that loss of glucose sensing by neurons has a role in the development of type 2 diabetes. The mechanism for obesity-induced loss of glucose sensing in POMC neurons involves uncoupling protein 2 (UCP2), a mitochondrial protein that impairs glucose-stimulated ATP production. UCP2 negatively regulates glucose sensing in POMC neurons. We found that genetic deletion of Ucp2 prevents obesity-induced loss of glucose sensing, and that acute pharmacological inhibition of UCP2 reverses loss of glucose sensing. We conclude that obesity-induced, UCP2-mediated loss of glucose sensing in glucose-excited neurons might have a pathogenic role in the development of type 2 diabetes.     

Morphological evolution through multiple cis-regulatory mutations at a single gene

One central, and yet unsolved, question in evolutionary biology is the relationship between the genetic variants segregating within species and the causes of morphological differences between species. The classic neo-darwinian view postulates that species differences result from the accumulation of small-effect changes at multiple loci. However, many examples support the possible role of larger abrupt changes in the expression of developmental genes in morphological evolution. Although this evidence might be considered a challenge to a neo-darwinian micromutationist view of evolution, there are currently few examples of the actual genes causing morphological differences between species. Here we examine the genetic basis of a trichome pattern difference between Drosophila species, previously shown to result from the evolution of a single gene, shavenbaby (svb), probably through cis-regulatory changes. We first identified three distinct svb enhancers from D. melanogaster driving reporter gene expression in partly overlapping patterns that together recapitulate endogenous svb expression. All three homologous enhancers from D. sechellia drive expression in modified patterns, in a direction consistent with the evolved svb expression pattern. To test the influence of these enhancers on the actual phenotypic difference, we conducted interspecific genetic mapping at a resolution sufficient to recover multiple intragenic recombinants. This functional analysis revealed that independent genetic regions upstream of svb that overlap the three identified enhancers are collectively required to generate the D. sechellia trichome pattern. Our results demonstrate that the accumulation of multiple small-effect changes at a single locus underlies the evolution of a morphological difference between species. These data support the view that alleles of large effect that distinguish species may sometimes reflect the accumulation of multiple mutations of small effect at select genes.