DSIbin:Identifying dynamic data structures in C/C++ binaries

Reverse engineering binary code is notoriously difficult and, especially, understanding a binary's dynamic data structures. Existing data structure analyzers are limited wrt. program comprehension: they do not detect complex structures such as skip lists, or lists running through nodes of different types such as in the Linux kernel's cyclic doubly-linked list. They also do not reveal complex parent-child relationships between structures. The tool DSI remedies these shortcomings but requires source code, where type information on heap nodes is available. We present DSIbin, a combination of DSI and the type excavator Howard for the inspection of C/C++ binaries. While a naive combination already improves upon related work, its precision is limited because Howard's inferred types are often too coarse. To address this we auto-generate candidates of refined types based on speculative nested-struct detection and type merging; the plausibility of these hypotheses is then validated by DSI. We demonstrate via benchmarking that DSIbin detects data structures with high precision

The lytB Gene of Escherichia coli Is Essential and Specifies a Product Needed for Isoprenoid Biosynthesis

LytB and GcpE, because they are codistributed with other pathway enzymes, have been predicted to catalyze unknown steps in the nonmevalonate pathway for isoprenoid biosynthesis. We constructed a conditional Escherichia coli lytB mutant and found that LytB is essential for survival and that depletion of LytB results in cell lysis, which is consistent with a role for this protein in isoprenoid biosynthesis. Alcohols which can be converted to pathway intermediates beyond the hypothesized LytB step(s) support limited growth of E. coli lytB mutants. An informatic analysis of protein structure suggested that GcpE is a globular protein of the TIM barrel class and that LytB is also a globular protein. Possible biochemical roles for LytB and GcpE are suggested

Structure of a Mycobacterium tuberculosis NusA–RNA complex

NusA is a key regulator of bacterial transcriptional elongation, pausing, termination and antitermination, yet relatively little is known about the molecular basis of its activity in these fundamental processes. In Mycobacterium tuberculosis, NusA has been shown to bind with high affinity and specificity to BoxB–BoxA–BoxC antitermination sequences within the leader region of the single ribosomal RNA (rRNA) operon. We have determined high-resolution X-ray structures of a complex of NusA with two short oligo-ribonucleotides derived from the BoxC stem–loop motif and have characterised the interaction of NusA with a variety of RNAs derived from the antitermination region. These structures reveal the RNA bound in an extended conformation to a large interacting surface on both KH domains. Combining structural data with observed spectral and calorimetric changes, we now show that NusA binding destabilises secondary structure within rRNA antitermination sequences and propose a model where NusA functions as a chaperone for nascently forming RNA structures

The Robot that Learns from the Therapist How to Assist Stroke Patients

Results from clinical studies suggest that assisted training is beneficial for the recovery of functioning in patients with stroke and other central nervous system injuries. The training consists of the repetition of movements, which change the excitability of the brain, and due to cortical plasticity have carry-over effects. We are developing a 3D arm assistant that interfaces the patient at the hand/wrist. The development addresses three major issues: (1) the selection of the tasks that are appropriate for the training based on the level of motor abilities (2) the design of the visual feedback that enhances the motivation to train, and (3) the assessment of the performance. Therefore, our design integrates the new 3D robot assistant, various gaming based visual feedback, and software that acquires data on-line from sensors (position of the hand and force between the robot and the hand). The major novelties that the 3D arm assistant brings are the following: an automatic method of capturing movements presented by the therapist (expert), the use of the probabilistic movement representation for control of the robot, the incorporation of simple gaming with adjustable levels of difficulty, and finally, the assessment of differences between the achieved and target movements (kinematics) and interface force measured by a special handle with multiple sensors. The components of the new arm assistant in 2D have been tested and proved to work effectively in the clinical trials with stroke patients