Airway diseases affect over 7% of the U.S. population and millions of patients worldwide. Asthmatic patients have wide variation in clinical severity with different clinical and physiologic manifestations of disease that may be driven by distinct biologic mechanisms. Further, the immunologic underpinnings of this complex trait disease are heterogeneous and treatment success depends on defining subgroups of asthmatics. Due to the limited availability and number of cells from the lung, the active site, in-depth investigation has been challenging. Recent advances in technology support transcriptional analysis of cells from induced sputum. Flow cytometry studies have described cells present in the sputum but a detailed analysis of these subsets is lacking. Mass cytometry or CyTOF (Cytometry by Time-Of-Flight) offers tremendous opportunities for multiparameter single cell analysis. Experiments can now allow detection of up to ~40 markers to facilitate unprecedented multidimensional cellular analyses. Here we demonstrate the use of CyTOF on primary airway samples obtained from well-characterized patients with asthma and cystic fibrosis. Using this technology, we quantify cellular frequency and functional status of defined cell subsets. Our studies provide a blueprint to define the heterogeneity among subjects and underscore the power of this single cell method to characterize airway immune status.

A systematic investigation is presented about the robustness of logic synthesis tools to equivalence-preserving transformations of the input Verilog file. We have developed a framework that: 1) parses Verilog behavioral models into an abstract syntax tree; 2) generates random equivalence-preserving transformations on the syntax tree, and; 3) writes the transformed design back in Verilog format. The original and the transformed Verilog descriptions are then checked for equivalence and synthesized. Results show that average (peak) improvements in area of 2.5%(11%) and length of the critical path of 4%(13%) are achievable. Indeed these figures are comparable to recent advancements in logic synthesis ([17] [8] achieve 4.9%(23%) 5%(24%) improvements area-wise, respectively), signaling a relevant lack of robustness in synthesis tools. This lack of robustness suggests that new synthesis algorithms should be evaluated by measuring the average improvement on several transformed files to assess their real contributions to the quality of the results.

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We present a novel, sound, and complete algorithm for deciding safety properties in programs with static memory allocation. The new algorithm extends the program verification paradigm using loop invariants presented in [1] with a counterexample guided abstraction refinement (CEGAR) loop [2] where the refinement is achieved by strengthening loop invariants using the QF BV generalization of Property Directed Reachability (PDR) discussed in [3,4]. We compare the algorithm with other approaches to program verification and report experimental results.