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Abstract. Robust, static disassembly is an important part of achieving high coverage for many binary code analyses, such as reverse engineering, malware analysis, reference monitor in-lining, and software fault isolation. However, one of the major difficulties current disassemblers face is differentiating code from data when they are interleaved. This paper presents a machine learning-based disassembly algorithm that segments an x86 binary into subsequences of bytes and then classifies each subsequence as code or data. The algorithm builds a language model from a set of pre-tagged binaries using a statistical data compression technique. It sequentially scans a new binary executable and sets a breaking point at each potential code-to-code and code-to-data/data-to-code transition. The classification of each segment as code or data is based on the minimum cross-entropy. Experimental results are presented to demonstrate the effectiveness of the algorithm.

16S rRNA methylases confer high-level resistance to most aminoglycosides in Gram-negative bacteria. Seven 16S rRNA methylase genes, armA, rmtA, rmtB, rmtC, rmtD, rmtE and npmA, have been identified since 2003. We studied the distribution of methylase genes in more than 200 aminoglycoside-resistant Gram-negative clinical isolates collected in 2007 at our hospital in Shanghai, China. 16S rRNA methylase genes were amplified by polymerase chain reaction (PCR) among 217 consecutive clinical isolates of Gram-negative bacilli resistant to gentamicin and amikacin by a disk diffusion method. 16S rRNA methylase genes were present in 97.5% (193/198) of clinical isolates highly resistant to amikacin (≥512 μg/ml), with armA and rmtB detected in 67.2 and 30.3% of strains, respectively, while no 16S rRNA methylase genes were detected in 19 strains with amikacin minimum inhibitory concentration (MIC) ≤256 μg/ml. armA or rmtB genes were detected in 100% of 104 strains of Enterobacteriaceae, and these two genes were equally represented (49 vs. 55 strains). Genes for armA or rmtB were detected in 94.7% (89/94) of Acinetobacter baumannii and Pseudomonas aeruginosa strains, and armA was predominant (84 vs. 5 strains with rmtB). No rmtA, rmtC, rmtD or npmA genes were found. Enterobacterial repetitive intergenic consensus sequence (ERIC-PCR) indicated that armA and rmtB genes were spread by both horizontal transfer and clonal dissemination.

The UDP-N-acetylglucosamine (UDP-GlcNAc) is present as one of the glycosyl donors for disaccharide linker (D-N-GlcNAc-L-rhamnose) and the precursor of peptidoglycan in mycobacteria. The bifunctional enzyme GlmU involves in the last two sequential steps of UDP-GlcNAc synthetic pathway. Glucosamine-1-phosphate acetyltransferase catalyzes the formation of N-acetylglucosamine-1-phosphate (GlcNAc-1-P) from glucosamine-1-phosphate (GlcN-1-P) and acetyl coenzyme A (Acetyl CoA), and N-acetylglucosamine-1-phosphate uridyltransferase catalyzes the synthesis of UDP-GlcNAc from GlcNAc-1-P and UTP. The previous studies demonstrating the essentiality of GlmU to mycobacterial survival supported GlmU as a novel and potential target for TB drugs. In this work, two accurate and simple colorimetric assays based on 96-well microtiter plate were developed to measure the kinetic properties of bifunctional GlmU including initial velocity, optimal temperature, optimal pH, the effect of Mg2+, and the kinetic parameters. Both of the colorimetric assays for bifunctional GlmU enzyme activities and the kinetic properties will facilitate high-throughput screening of GlmU inhibitors.

Golgi phosphoprotein 2 (GOLPH2/GP73/GOLM1), a type-II Golgi transmembrane protein of unknown function, is up-regulated in many cancers. Its Golgi luminal domain is potentially the major functional domain. The goal of this study is to identify the proteins interacting with GOLPH2. Using secretory GOLPH2 (sGOLPH2, amino acid residues 55-401) as bait, secretory clusterin (sCLU) was identified as one interacting candidate by yeast two-hybrid screening, and the coiled-coil domain of GOLPH2 was found to be sufficient for interaction with sCLU. The interaction between GOLPH2 and sCLU was confirmed intracellularly and extracellularly. The intracellular co-localization of GOLPH2 and sCLU in Golgi was also shown. These results can help in understanding the biological and pathological significance of GOLPH2.

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