Is Peri-Operative Isolated Systolic Hypertension (ISH) a Cardiac Risk Factor?

We are presenting a review of Isolated Systolic Hypertension (ISH) as a cardiovascular risk factor with emphasis on the perioperative period

Derivation of a tasselled cap transformation based on Landsat 7 at-satellite reflectance

A new tasselled cap transformation based on Landsat 7 at-satellite reflectance was developed. This transformation is most appropriate for regional applications where atmospheric correction is not feasible. The brightness, greenness and wetness of the derived transformation collectively explained over 97% of the spectral variance of the individual scenes used in this study

Derivation of a tasselled cap transformation based on Landsat 7 at-satellite reflectance

A new tasselled cap transformation based on Landsat 7 at-satellite reflectance was developed. This transformation is most appropriate for regional applications where atmospheric correction is not feasible. The brightness, greenness and wetness of the derived transformation collectively explained over 97% of the spectral variance of the individual scenes used in this study

Don't Start From Scratch: Leveraging Prior Data to Automate Robotic Reinforcement Learning

Reinforcement learning (RL) algorithms hold the promise of enabling autonomous skill acquisition for robotic systems. However, in practice, real-world robotic RL typically requires time consuming data collection and frequent human intervention to reset the environment. Moreover, robotic policies learned with RL often fail when deployed beyond the carefully controlled setting in which they were learned. In this work, we study how these challenges can all be tackled by effective utilization of diverse offline datasets collected from previously seen tasks. When faced with a new task, our system adapts previously learned skills to quickly learn to both perform the new task and return the environment to an initial state, effectively performing its own environment reset. Our empirical results demonstrate that incorporating prior data into robotic reinforcement learning enables autonomous learning, substantially improves sample-efficiency of learning, and enables better generalization. Project website: https://sites.google.com/view/ariel-berkeley/Comment: 17 pages, project website at https://sites.google.com/view/ariel-berkeley

Inhibition of Allergic Inflammation in a Murine Model of Asthma by Expression of a Dominant-Negative Mutant of GATA-3

AbstractThe cytokines IL-4, IL-5, and IL-13, secreted by Th2 cells, have distinct functions in the pathogenesis of asthma. We have previously shown that the transcription factor GATA-3 is expressed in Th2 but not Th1 cells. However, it was unclear whether GATA-3 controls the expression of all Th2 cytokines. Expression of a dominant-negative mutant of GATA-3 in mice in a T cell–specific fashion led to a reduction in the levels of all the Th2 cytokines IL-4, IL-5, and IL-13. Airway eosinophilia, mucus production, and IgE synthesis, all key features of asthma, were severely attenuated in the transgenic mice. Thus, targeting GATA-3 activity alone is sufficient to blunt Th2 responses in vivo, thereby establishing GATA-3 as a potential therapeutic target in the treatment of asthma and allergic diseases

The p63 Protein Isoform ΔNp63α Modulates Y-box Binding Protein 1 in Its Subcellular Distribution and Regulation of Cell Survival and Motility Genes

The Y-box binding protein 1 (YB-1) belongs to the cold-shock domain protein superfamily, one of the most evolutionarily conserved nucleic acid-binding proteins currently known. YB-1 performs a wide variety of cellular functions, including transcriptional and translational regulation, DNA repair, drug resistance, and stress responses to extracellular signals. Inasmuch as the level of YB-1 drastically increases in tumor cells, this protein is considered to be one of the most indicative markers of malignant tumors. Here, we present evidence that ΔNp63α, the predominant p63 protein isoform in squamous epithelia and YB-1, can physically interact. Into the nucleus, ΔNp63α and YB-1 cooperate in PI3KCA gene promoter activation. Moreover, ΔNp63α promotes YB-1 nuclear accumulation thereby reducing the amount of YB-1 bound to its target transcripts such as that encoding the SNAIL1 protein. Accordingly, ΔNp63α enforced expression was associated with a reduction of the level of SNAIL1, a potent inducer of epithelial to mesenchymal transition. Furthermore, ΔNp63α depletion causes morphological change and enhanced formation of actin stress fibers in squamous cancer cells. Mechanistic studies indicate that ΔNp63α affects cell movement and can reverse the increase of cell motility induced by YB-1 overexpression. These data thus suggest that ΔNp63α provides inhibitory signals for cell motility. Deficiency of ΔNp63α gene expression promotes cell mobilization, at least partially, through a YB-1-dependent mechanism

Work functions, ionization potentials, and in-between: Scaling relations based on the image charge model

We revisit a model in which the ionization energy of a metal particle is associated with the work done by the image charge force in moving the electron from infinity to a small cut-off distance just outside the surface. We show that this model can be compactly, and productively, employed to study the size dependence of electron removal energies over the range encompassing bulk surfaces, finite clusters, and individual atoms. It accounts in a straightforward manner for the empirically known correlation between the atomic ionization potential (IP) and the metal work function (WF), IP/WF$\sim$2. We formulate simple expressions for the model parameters, requiring only a single property (the atomic polarizability or the nearest neighbor distance) as input. Without any additional adjustable parameters, the model yields both the IP and the WF within $\sim$10% for all metallic elements, as well as matches the size evolution of the ionization potentials of finite metal clusters for a large fraction of the experimental data. The parametrization takes advantage of a remarkably constant numerical correlation between the nearest-neighbor distance in a crystal, the cube root of the atomic polarizability, and the image force cutoff length. The paper also includes an analytical derivation of the relation of the outer radius of a cluster of close-packed spheres to its geometric structure.Comment: Original submission: 8 pages with 7 figures incorporated in the text. Revised submission (added one more paragraph about alloy work functions): 18 double spaced pages + 8 separate figures. Accepted for publication in PR

Evaluating The National Land Cover Database Tree Canopy and Impervious Cover Estimates Across the Conterminous United States: A Comparison with Photo-Interpreted Estimates

The 2001 National Land Cover Database (NLCD) provides 30-m resolution estimates of percentage tree canopy and percentage impervious cover for the conterminous United States. Previous estimates that compared NLCD tree canopy and impervious cover estimates with photo-interpreted cover estimates within selected counties and places revealed that NLCD underestimates tree and impervious cover. Based on these previous results, a wall-to-wall comprehensive national analysis was conducted to determine if and how NLCD derived estimates of tree and impervious cover varies from photo-interpreted values across the conterminous United States. Results of this analysis reveal that NLCD significantly underestimates tree cover in 64 of the 65 zones used to create the NCLD cover maps, with a national average underestimation of 9.7% (standard error (SE) = 1.0%) and a maximum underestimation of 28.4% in mapping zone 3. Impervious cover was also underestimated in 44 zones with an average underestimation of 1.4% (SE = 0.4%) and a maximum underestimation of 5.7% in mapping zone 56. Understanding the degree of underestimation by mapping zone can lead to better estimates of tree and impervious cover and a better understanding of the potential limitations associated with NLCD cover estimates