Sustained glucagon-like peptide 1 expression from encapsulated transduced cells to treat obese diabetic rats

Obesity and type 2 diabetes (T2D) are two prevalent chronic diseases that have become a major public health concern in industrialized countries. T2D is characterized by hyperglycemia and islet beta cell dysfunction. Glucagon-like peptide 1 (GLP-1) promotes β cell proliferation and neogenesis and has a potent insulinotropic effect. Leptin receptor deficient male rats are obese and diabetic and provide a model of T2D. We hypothesized that their treatment by sustained expression of GLP-1 using encapsulated cells may prevent or delay diabetes onset. Vascular smooth muscle cells (VSMC) retrovirally transduced to secrete GLP-1 were seeded into TheraCyte(TM) encapsulation devices, implanted subcutaneously and rats were monitored for diabetes. Rats that received cell implants showed mean plasma GLP-1 level of 119.3 ± 10.2pM that was significantly elevated over control values of 32.4 ± 2.9pM (P<0.001). GLP-1 treated rats had mean insulin levels of 45.9 ± 2.3ng/ml that were significantly increased over control levels of 7.3±1.5ng/ml (P<0.001). In rats treated before diabetes onset elevations in blood glucose were delayed and rats treated after onset became normoglycemic and showed improved glucose tolerance tests. Untreated diabetic rats possess abnormal islet structures characterized by enlarged islets with α-cell infiltration and multifocal vacuolization. GLP-1 treatment induced normalization of islet structures including a mantle of α-cells and increased islet mass. These data suggest that encapsulated transduced cells may offer a potential long term treatment of patients.     

A Model-Theoretic Approach for Recovering Consistent Data from Inconsistent Knowledge Bases

One of the most significant drawbacks of classical logic is its being useless in the presence of an inconsistency. Nevertheless, the classical calculus is a very convenient framework to work with. In this work we propose means for drawing conclusions from systems that are based on classical logic, although the information might be inconsistent. The idea is to detect those parts of the knowledge base that cause the inconsistency, and isolate the parts that are recoverable. We do this by temporarily switching into Ginsberg/Fitting multivalued framework of bilattices (which is a common framework for logic programming and nonmonotonic reasoning). Our method is conservative in the sense that it considers the contradictory data as useless and regards all the remaining information unaffected. The resulting logic is nonmonotonic, paraconsistent, and a plausibility logic in the sense of Lehmann.     

Multiparameter method for analysis and selection of motion estimation algorithms for video compression

This paper proposes a new multiparameter method for analysis and selection of motion estimation algorithms for video compression. We present motion estimation algorithms, results of computer simulations and illustrate the analysis with tables, PSNR and performance plots. Numerous algorithms and tests for analysis of algorithm performance for video compression have recently been suggested, which has resulted in a need for effective evaluation methods. A highly qualified expert is also needed to evaluate the test results. The more input parameters used the more complex and subjective the evaluation will be. Our multiparameter method for algorithm analysis and selection eliminates subjectivity and provides a qualitative and quantitative evaluation of the tested algorithms for any number of algorithms and parameters. We propose two new methods of evaluation: (1) a quality method—a graphic method using the Pareto approach, and (2) a quantity method which obtains an integrated parameter composed of numerous evaluation parameters. In addition, we evaluate various motion estimation algorithms accordingly to two different implementation strategies: (a) using a software video encoder that depends on available processing resources using a computational complexity–rate–distortion (C–R–D) evaluation framework and (b) using a power-limited video encoder implemented on mobile or handheld computing platform by using energy–rate–distortion (E–R–D) behavior.

Accelerating Bounded Model Checking of Safety Properties

Bounded Model Checking based on SAT methods has recently been introduced as a complementary technique to BDD-based Symbolic Model Checking. The basic idea is to search for a counterexample in executions whose length is bounded by some integer k. The BMC problem can be efficiently reduced to a propositional satisfiability problem, and can therefore be solved by SAT methods rather than BDDs. SAT procedures are based on general-purpose heuristics that are designed for any propositional formula. We show how the unique characteristics of BMC invariant formulas (G p) can be exploited for a variety of optimizations in the SAT checking procedure. Experiments with these optimizations on real designs prove their efficiency in many of the hard test cases, in comparison to both the standard SAT procedure and a BDD-based model checker.     

Reasoning with logical bilattices

The notion of bilattice was introduced by Ginsberg, and further examined by Fitting, as a general framework for many applications. In the present paper we develop proof systems, which correspond to bilattices in an essential way. For this goal we introduce the notion of logical bilattices. We also show how they can be used for efficient inferences from possibly inconsistent data. For this we incorporate certain ideas of Kifer and Lozinskii, which happen to suit well the context of our work. The outcome are paraconsistent logics with a lot of desirable properties. A preliminary version of this paper appears in Arieli and Avron (1994).      

Protein microarray platforms for clinical proteomics

Proteomics for clinical applications is presently in a state of transition. It has become clear that the classical approaches based on 2-DE and/or MS need to be complemented by different kinds of technologies. The well-known problems include sample complexity, sensitivity, quantitation, reproducibility, and analysis time. We suggest that the new technologies for clinical proteomics can be supported by antibody-centric protein microarray platforms. These platforms presently include antibody microarrays and lysate, or reverse capture/reverse phase protein microarrays. Other forms of these arrays are in less mature developmental stages, including ORF and self assembling protein microarrays. Bioinformatic support for interpreting these arrays is becoming more available as the whole field of systems biology begins to mature. The present set of applications for these platforms is profoundly focused on certain common cancers, immunology, and cystic fibrosis. However, we predict that many more disease entities will become studied as knowledge of the power and availability of these platforms becomes more widely established. We anticipate that these platforms will eventually evolve to accommodate label-free detection technologies, human genome-scale numbers of analytes, and increases in analytic and bioinformatic speeds.     

Beyond vacuity: towards the strongest passing formula

Given an LTL formula φ in negation normal form, it can be strengthened by replacing some of its literals with false. Given such a formula and a model M that satisfies it, vacuity and mutual vacuity attempt to find one or a maximal set of literals, respectively, with which φ can be strengthened while still being satisfied by M. We study the problem of finding the strongest LTL formula that satisfies M and is in the Boolean closure of strengthened versions of φ as defined above. This formula is stronger or equally strong to any formula that can be obtained by vacuity and mutual vacuity. We present our algorithms in the framework of lattice automata.     

Enabling Rapid Charging Lithium Metal Batteries via Surface Acoustic Wave-Driven Electrolyte Flow

Both powerful and unstable, practical lithium metal batteries have remained a difficult challenge for over 50 years. With severe ion depletion gradients in the electrolyte during charging, they rapidly develop porosity, dendrites, and dead Li that cause poor performance and, all too often, spectacular failure. Remarkably, incorporating a small, 100 MHz surface acoustic wave device (SAW) solves this problem. Providing acoustic streaming electrolyte flow during charging, the device enables dense Li plating and avoids porosity and dendrites. SAW-integrated Li cells can operate up to 6 mA cm⁻² in a commercial carbonate-based electrolyte; omitting the SAW leads to short circuiting at 2 mA cm⁻². The Li deposition is morphologically dendrite-free and close to theoretical density when cycling with the SAW. With a 245 µm thick Li anode in a full Li||LFP (LiFePO₄) cell, introducing the SAW increases the uncycled Li from 145 to 225 µm, decreasing Li consumption from 41% to only 8%. A closed-form model is provided to explain the phenomena and serve as a design tool for integrating this chemistry-agnostic approach into batteries whatever the chemistry within.     

Inference rules for proving the equivalence of recursive procedures

Inspired by Hoare’s rule for recursive procedures, we present three proof rules for the equivalence between recursive programs. The first rule can be used for proving partial equivalence of programs; the second can be used for proving their mutual termination; the third rule can be used for proving the equivalence of reactive programs. There are various applications to such rules, such as proving equivalence of programs after refactoring and proving backward compatibility.