The beta subunit of the signal recognition particle receptor is a transmembrane GTPase that anchors the alpha subunit, a peripheral membrane GTPase, to the endoplasmic reticulum membrane.

The signal recognition particle receptor (SR) is required for the cotranslational targeting of both secretory and membrane proteins to the endoplasmic reticulum (ER) membrane. During targeting, the SR interacts with the signal recognition particle (SRP) which is bound to the signal sequence of the nascent protein chain. This interaction catalyzes the GTP-dependent transfer of the nascent chain from SRP to the protein translocation apparatus in the ER membrane. The SR is a heterodimeric protein comprised of a 69-kD subunit (SR alpha) and a 30-kD subunit (SR beta) which are associated with the ER membrane in an unknown manner. SR alpha and the 54-kD subunits of SRP (SRP54) each contain related GTPase domains which are required for SR and SRP function. Molecular cloning and sequencing of a cDNA encoding SR beta revealed that SR beta is a transmembrane protein and, like SR alpha and SRP54, is a member of the GTPase superfamily. Although SR beta defines its own GTPase subfamily, it is distantly related to ARF and Sar1. Using UV cross-linking, we confirm that SR beta binds GTP specifically. Proteolytic digestion experiments show that SR alpha is required for the interaction of SRP with SR. SR alpha appears to be peripherally associated with the ER membrane, and we suggest that SR beta, as an integral membrane protein, mediates the membrane association of SR alpha. The discovery of its guanine nucleotide-binding domain, however, makes it likely that its role is more complex than that of a passive anchor for SR alpha. These findings suggest that a cascade of three directly interacting GTPases functions during protein targeting to the ER membrane

Design and Evaluation of Frequency Weighted LQG Maximum Entropy Controllers on an Experimental Tmss Structure

This paper will discuss the experimental evaluation of a structural control system designed using a combination of Frequency Weighted LQG and Maximum Entropy. The experimental implementation was performed on an experimental truss structure, the Sandia Truss, which is described in the paper. The control design model was obtained via experimental system identification using the eigensystem realization algorithm with data correlation. The control design used frequency weighting to stabilize the unstructured uncertainty of the system due to low signal-to-noise and uncertain system dynamics in various frequency ranges. Maximum entropy is used to provide robustness for structured uncertain system dynamics within the controller bandwidth. The experimental implementation of the controllers designed with this approach show the ability to design controllers with a specified bandwidth, gain .Uabilization of unstructured uncertainty, and robustness to structured uncertainty within the controller bandwidth

The Vibration Virtual Environment for Test Optimization (VETO)

A new test simulation tool is being developed to support vibration test design and to evaluate the overall testability of a component or system. This environment, the Vibration Virtual Environment for Test Optimization (VETO), is utilized to optimally place vibration control and response transducers and to investigate the selection of test parameters needed in the design and performance of a vibration experiment. The engineer can investigate the effects of different control parameters prior to performing an actual vibration test. Additionally, new and existing fixture designs can be evaluated through the development of analytical or experimental models that can be integrated into the simulation environment. This test design environment also provides the engineer with the ability to combine analytically or experimentally derived models of the vibration test hardware, instrumentation and equipment into a simulation model that represents the vibration testing capability. Hardware-in-the-loop simulations can be conducted using this model to examine multiple facets of the test design. This paper presents a new tool that will assist test engineers in maximizing the value of vibration tests through the use of hardware-in-the-loop simulations

Mapping of functionalized regions on carbon nanotubes by scanning tunneling microscopy

Scanning tunneling microscopy (STM) gives us the opportunity to map the surface of functionalized carbon nanotubes in an energy resolved manner and with atomic precision. But this potential is largely untapped, mainly due to sample stability issues which inhibit reliable measurements. Here we present a simple and straightforward solution that makes away with this difficulty, by incorporating the functionalized multiwalled carbon nanotubes (MWCNT) into a few layer graphene - nanotube composite. This enabled us to measure energy resolved tunneling conductance maps on the nanotubes, which shed light on the level of doping, charge transfer between tube and functional groups and the dependence of defect creation or functionalization on crystallographic orientation.Comment: Keywords: functionalization, carbon nanotubes, few layer graphene, STM, CITS, ST

MRI sensing based on the displacement of paramagnetic ions from chelated complexes

We introduce a mechanism for ion sensing by MRI in which analytes compete with paramagnetic ions for binding to polydentate chelating agents. Displacement of the paramagnetic ions results in alteration of solvent interaction parameters and consequent changes in relaxivity and MRI contrast. The MRI changes can be tuned by the choice of chelator. As an example, we show that calcium-dependent displacement of Mn[superscript 2+] ions bound to EGTA and BAPTA results in a T[subscript 1]-weighted MRI signal increase, whereas displacement from calmodulin results in a signal decrease. The changes are ion selective and can be explained using relaxivity theory. The ratio of T[subscript 2] to T[subscript 1] relaxivity is also calcium-dependent, indicating the feasibility of “ratiometric” analyte detection, independent of the probe concentration. Measurement of paramagnetic ion displacement effects could be used to determine analyte ion concentrations with spatial resolution in opaque specimens.National Institutes of Health (U.S.) (grant DP2-OD2441)National Institutes of Health (U.S.) (grant R01-GM65519)McGovern Institute for Brain Research at MIT. Neurotechnology (MINT) Progra

IMPROVE 1.0: Individual Monitoring of Psoriasis Activity by Regular Online App Questionnaires and Outpatient Visits

Smartphone apps gain more and more importance in supporting management of chronic diseases. Psoriasis is a highly prevalent, lifelong chronic inflammatory skin disease with a high impact on patient's quality of life. Disease management includes regular topical and systemic treatment of skin lesions as well as co-treatment of metabolic and psychologic disorders. In this study, we investigated the potential of a new smartphone app (IMPROVE 1.0) for individual monitoring of disease activity and disease influencing factors. Twelve out of 50 psoriasis patients asked for study participation performed self-assessment of psoriasis severity, life quality, and stress scores using the app over a period of 1 year. Every 2 months, study participants were carefully examined by a dermatologist in order to control the quality of app-reported data. We found that psoriasis severity and life quality values as entered in the app closely correlate to physician's examination. Furthermore, we detected strong correlations of disease activity with life quality and psoriasis serum biomarker. Temporal relations between psoriasis aggravation and previous changes of lifestyle factors, such as increased stress levels, were observed in individual patients, indicating a high potential for preventive interventions in future psoriasis apps. The vast majority of study participants evaluated IMPROVE 1.0 app positively and wish to include the app into their daily life. Hence, we demonstrate that smartphone apps are a useful tool to raise self-awareness for the dimensions of complex diseases and fully integrate psoriasis patients into individual disease management. These data are important to develop more advanced digital tools supporting the management of chronic diseases in the future