scholarly journals Fluorescence detection of GDP in real time with the reagentless biosensor rhodamine–ParM

2011 ◽  
Vol 440 (1) ◽  
pp. 43-49 ◽  
Author(s):  
Simone Kunzelmann ◽  
Martin R. Webb
Keyword(s):  
Drug Discovery ◽  
Response Time ◽  
Real Time ◽  
Fluorescence Detection ◽  
Basic Research ◽  
Nucleotide Exchange ◽  
Gtp Hydrolysis ◽  
Fluorescence Response ◽  
Reagentless Biosensor ◽  
Fluorescence Methods

The development of novel fluorescence methods for the detection of key biomolecules is of great interest, both in basic research and in drug discovery. Particularly relevant and widespread molecules in cells are ADP and GDP, which are the products of a large number of cellular reactions, including reactions catalysed by nucleoside triphosphatases and kinases. Previously, biosensors for ADP were developed in this laboratory, based on fluorophore adducts with the bacterial actin homologue ParM. It is shown in the present study that one of these biosensors, tetramethylrhodamine–ParM, can also monitor GDP. The biosensor can be used to measure micromolar concentrations of GDP on the background of millimolar concentrations of GTP. The fluorescence response of the biosensor is fast, the response time being <0.2 s. Thus the biosensor allows real-time measurements of GTPase and GTP-dependent kinase reactions. Applications of the GDP biosensor are exemplified with two different GTPases, measuring the rates of GTP hydrolysis and nucleotide exchange.

scholarly journals Academic collaborative models fostering the translation of physiological in vitro systems from basic research into drug discovery

2021 ◽  
Author(s):  
Alessandra Silvestri ◽  
Francisca Vicente ◽  
María J. Vicent ◽  
Bahne Stechmann ◽  
Wolfgang Fecke
Keyword(s):  
Drug Discovery ◽  
Basic Research ◽  
Collaborative Models ◽  
In Vitro Systems

scholarly journals Engineering a reagentless biosensor for single-stranded DNA to measure real-time helicase activity in Bacillus

2014 ◽  
Vol 61 ◽  
pp. 579-586 ◽  
Author(s):  
Matthew Green ◽  
Neville S. Gilhooly ◽  
Shahriar Abedeen ◽  
David J. Scott ◽  
Mark S. Dillingham ◽  
...  
Keyword(s):  
Real Time ◽  
Helicase Activity ◽  
Single Stranded Dna ◽  
Reagentless Biosensor

scholarly journals Real Time Neutron Radiography Applications in Gas Turbine and Internal Combustion Engine Technology

1988 ◽  
Author(s):  
John T. Lindsay ◽  
C. W. Kauffman
Keyword(s):  
Real Time ◽  
Gas Turbine ◽  
Internal Combustion Engines ◽  
Combustion Engine ◽  
Neutron Radiography ◽  
Three Dimensional ◽  
Basic Research ◽  
Internal Combustion ◽  
Turbine Engines ◽  
Gas Turbine Engines

Real Time Neutron Radiography (RTNR) is rapidly becoming a valuable tool for nondestructive testing and basic research with a wide variety of applications in the field of engine technology. The Phoenix Memorial Laboratory (PML) at the University of Michigan has developed a RTNR facility and has been using this facility to study several phenomena that have direct application to internal combustion and gas turbine engines. These phenomena include; 1) the study of coking and debris deposition in several gas turbine nozzles (including the JT8D), 2) the study of lubrication problems in operating standard internal combustion engines and in operating automatic transmissions (1, 2, 3), 3) the location of lubrication blockage and subsequent imaging of the improvement obtained from design changes, 4) the imaging of sprays inside metallic structures in both a two-dimensional, standard radiographic manner (4, 5) and in a computer reconstructed, three-dimensional, tomographic manner (2, 3), and 5) the imaging of the fuel spray from an injector in a single cylinder diesel engine while the engine is operating. This paper will show via slides and real time video, the above applications of RTNR as well as other applications not directly related to gas turbine engines.

scholarly journals Dynamic approach to minimize overhead and response time in scheduling periodic real-time tasks

2021 ◽  
Vol 8 (4) ◽  
pp. 75-81
Author(s):  
Ahmed A. Alsheikhy ◽  
Keyword(s):  
Response Time ◽  
Real Time ◽  
Periodic Tasks ◽  
Dynamic Priority ◽  
New Novel ◽  
Context Switching ◽  
Novel Approach ◽  
Efficiency And Effectiveness ◽  
Time Systems ◽  
The Given

In real-time systems, a task or a set of tasks needs to be executed and completed successfully within a predefined time. Those systems require a scheduling technique or a set of scheduling methods to distribute the given task or the set of tasks among different processors or on a processor. In this paper, a new novel scheduling approach to minimize the overhead from context switching between several periodic tasks is presented. This method speeds up a required response time while ensuring that all tasks meet their deadline times and there is no deadline miss occurred. It is a dynamic-priority technique that works either on a uniprocessor or several processors. In particular, it is proposed to be applied on multiprocessor environments since many applications run on several processors. Various examples are presented within this paper to demonstrate its optimality and efficiency. In addition, several comparison experiments with an earlier version of this approach were performed to demonstrate its efficiency and effectiveness too. Those experiments showed that this novel approach sped up the execution time from 15% to nearly around 46%. In addition, it proved that it reduced the number of a context switch between tasks from 12% to around 50% as shown from simulation tests. Furthermore, this approach delivered all tasks/jobs successfully and ensured there was no deadline miss happened.

scholarly journals On the Usage of GPUs for Efficient Motion Estimation in Medical Image Sequences

2011 ◽  
Vol 2011 ◽  
pp. 1-15 ◽  
Author(s):  
Jeyarajan Thiyagalingam ◽  
Daniel Goodman ◽  
Julia A. Schnabel ◽  
Anne Trefethen ◽  
Vicente Grau
Keyword(s):  
Motion Estimation ◽  
Real Time ◽  
Three Dimensional ◽  
Basic Research ◽  
Estimation Algorithm ◽  
Image Sequences ◽  
Multicore Architectures ◽  
Gpu Architectures ◽  
Access Patterns ◽  
Performance Gains

Images are ubiquitous in biomedical applications from basic research to clinical practice. With the rapid increase in resolution, dimensionality of the images and the need for real-time performance in many applications, computational requirements demand proper exploitation of multicore architectures. Towards this, GPU-specific implementations of image analysis algorithms are particularly promising. In this paper, we investigate the mapping of an enhanced motion estimation algorithm to novel GPU-specific architectures, the resulting challenges and benefits therein. Using a database of three-dimensional image sequences, we show that the mapping leads to substantial performance gains, up to a factor of 60, and can provide near-real-time experience. We also show how architectural peculiarities of these devices can be best exploited in the benefit of algorithms, most specifically for addressing the challenges related to their access patterns and different memory configurations. Finally, we evaluate the performance of the algorithm on three different GPU architectures and perform a comprehensive analysis of the results.

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