Real-time computer modeling of weakness following stroke optimizes robotic assistance for movement therapy

This paper describes the development of a novel control system for a robotic arm orthosis for assisting patients in motor training following stroke. The robot allows naturalistic motion of the arm and is as mechanically compliant as a human therapist's arms. This compliance preserves the connection between effort and error that appears essential for motor learning, but presents a challenge: accurately creating desired movements requires that the robot form a model of the patient's weakness, since the robot cannot simply stiffly drive the arm along the desired path. We show here that a standard model-based adaptive controller allows the robot to form such a model of the patient and complete movements accurately. However, we found that the human motor system, when coupled to such an adaptive controller, reduces its own participation, allowing the adaptive controller to take over the performance of the task. This presents a problem for motor training, since active engagement by the patient is important for stimulating neuroplasticity. We show that this problem can be solved by making the controller continuously attempt to reduce its assistance when errors are small. The resulting robot successfully assists stroke patients in moving in desired patterns with very small errors, but also encourages intense participation by the patient. Such robot assistance may optimally provoke neural plasticity, since it intensely engages both descending and ascending motor pathways. © 2007 IEEE

An intuitive Python interface for Bioconductor libraries demonstrates the utility of language translators

<p>Abstract</p> <p>Background</p> <p>Computer languages can be domain-related, and in the case of multidisciplinary projects, knowledge of several languages will be needed in order to quickly implements ideas. Moreover, each computer language has relative strong points, making some languages better suited than others for a given task to be implemented. The Bioconductor project, based on the R language, has become a reference for the numerical processing and statistical analysis of data coming from high-throughput biological assays, providing a rich selection of methods and algorithms to the research community. At the same time, Python has matured as a rich and reliable language for the agile development of prototypes or final implementations, as well as for handling large data sets.</p> <p>Results</p> <p>The data structures and functions from Bioconductor can be exposed to Python as a regular library. This allows a fully transparent and native use of Bioconductor from Python, without one having to know the R language and with only a small community of <it>translators</it> required to know both. To demonstrate this, we have implemented such Python representations for key infrastructure packages in Bioconductor, letting a Python programmer handle annotation data, microarray data, and next-generation sequencing data.</p> <p>Conclusions</p> <p>Bioconductor is now not solely reserved to R users. Building a Python application using Bioconductor functionality can be done just like if Bioconductor was a Python package. Moreover, similar principles can be applied to other languages and libraries. Our Python package is available at: <url>http://pypi.python.org/pypi/rpy2-bioconductor-extensions/</url></p

A Recombinant Secondary Antibody Mimic as a Target-specific Signal Amplifier and an Antibody Immobilizer in Immunoassays

We construct a novel recombinant secondary antibody mimic, GST-ABD, which can bind to the Fc regions of target-bound primary antibodies and acquire multiple HRPs simultaneously. We produce it in tenth of mg quantities with a bacterial overexpression system and simple purification procedures, significantly reducing the manufacturing cost and time without the use of animals. GST-ABD is effectively conjugated with 3 HRPs per molecule on an average and selectively bind to the Fc region of primary antibodies derived from three different species (mouse, rabbit, and rat). HRP-conjugated GST-ABD (HRP-GST-ABD) is successfully used as an alternative to secondary antibodies to amplify target-specific signals in both ELISA and immunohistochemistry regardless of the target molecules and origin of primary antibodies used. GST-ABD also successfully serves as an anchoring adaptor on the surface of GSH-coated plates for immobilizing antigen-capturing antibodies in an orientation-controlled manner for sandwich-type indirect ELISA through simple molecular recognition without any complicated chemical modification.clos

Public Access to Genome-Wide Data: Five Views on Balancing Research with Privacy and Protection

Introductory paragraph: Just over twelve months ago, PLoS Genetics published a paper [1] demonstrating that, given genome-wide genotype data from an individual, it is, in principle, possible to ascertain whether that individual is a member of a larger group defined solely by aggregate genotype frequencies, such as a forensic sample or a cohort of participants in a genome-wide association study (GWAS). As a consequence, the National Institutes of Health (NIH) and Wellcome Trust agreed to shut down public access not just to individual genotype data but even to aggregate genotype frequency data from each study published using their funding. Reactions to this decision span the full breadth of opinion, from ‘‘too little, too late—the public trust has been breached’’ to ‘‘a heavy-handed bureaucratic response to a practically minimal risk that will unnecessarily inhibit scientific research.’’ Scientific concerns have also been raised over the conditions under which individual identity can truly be accurately determined from GWAS data. These concerns are addressed in two papers published in this month’s issue of PLoS Genetics [2,3]. We received several submissions on this topic and decided to assemble these viewpoints as a contribution to the debate and ask readers to contribute their thoughts through the PLoS online commentary features. Five viewpoints are included. The Public Population Project in Genomics (P3G) is calling for a universal researcher ID with an access permit mechanism for bona fide researchers. The contribution by Catherine Heeney, Naomi Hawkins, Jantina de Vries, Paula Boddington, and Jane Kaye of the University of Oxford Ethox Centre outlines some of the concerns over possible misuse of individual identification in conjunction with medical and family history data, and points out that if geneticists mishandle public trust, it will backfire on their ability to conduct further research. George Church posits that actions directed toward restricting data access are likely to exclude researchers who might provide the most novel insights into the data and instead makes the argument that full disclosure and consent to the release of genomic information should be sought from study participants, rather than making difficult-to-guarantee promises of anonymity. Martin Bobrow weighs the risks and benefits and proposes four steps that represent a middle ground: Retain restricted access for now, make malicious de-identification practices illegal, increase public awareness of the issues, and encourage recognition that scientists have a special professional relationship of trust with study participants. Finally, Bruce Weir provides a commentary on the contribution of the two research articles from Braun et al. [2] and Visscher and Hill [3]

Active control for gas turbine combustors

Closed-loop feedback control is implemented in two model combustors as a demonstration of the application of feedback control to gas turbine combustion. The first combustor is an axi-symmetric, swirl-stabilized, spray-fired combustor, while the second combustor incorporates discrete wall injection of primary and dilution air, representative of an actual gas turbine combustor. In both combustors, the emission of carbon monoxide and carbon dioxide, the radiative heat flux to the liner associated with soot and combustor stability are monitored in real time and controlled as a function of combustor load. The control input to the system is the nozzle atomizing air flow rate. The emission of carbon monoxide and carbon dioxide, the radiative flux to the liner, and the combustor stability are obtained through non-intrusive radiometric sensors mounted near the combustor exit plane. This information is conveyed to a control computer which invokes an optimization algorithm to minimize the CO and soot radiative flux, while maximizing the CO2 radiative flux. The index of combustion instability (onset of elevated acoustic emission) is, in the present case, a characteristic frequency in the power spectral density of the CO signal. The identical control methodology is applied to the two combustors with satisfactory and promising results that demonstrate the potential of active control to practical systems. © 1991 Combustion Institute