Dataset Information

Digital Microfluidics Chips for the Execution and Real-Time Monitoring of Multiple Ribozymatic Cleavage Reactions.

ABSTRACT: In this paper, we describe the design and performance of two digital microfluidics (DMF) chips capable of executing multiple ribozymatic reactions, with proper controls, in response to short single-stranded DNA inducers. Since the fluorescence output of a reaction is measurable directly from the chip, without the need for gel electrophoresis, a complete experiment involving up to eight reactions (per chip) can be carried out reliably, relatively quickly, and efficiently. The ribozymes can also be used as biosensors of the concentration of oligonucleotide inputs, with high sensitivity, low limits of quantification and of detection, and excellent signal-to-noise ratio. The presented chips are readily usable devices that can be used to automate, speed up, and reduce the costs of ribozymatic reaction experiments.

SUBMITTER: Davis AN

PROVIDER: S-EPMC8427639 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

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Digital Microfluidics Chips for the Execution and Real-Time Monitoring of Multiple Ribozymatic Cleavage Reactions.

Davis Alen N AN Samlali Kenza K Kapadia Jay B JB Perreault Jonathan J Shih Steve C C SCC Kharma Nawwaf N

ACS omega 20210825 35

In this paper, we describe the design and performance of two digital microfluidics (DMF) chips capable of executing multiple ribozymatic reactions, with proper controls, in response to short single-stranded DNA inducers. Since the fluorescence output of a reaction is measurable directly from the chip, without the need for gel electrophoresis, a complete experiment involving up to eight reactions (per chip) can be carried out reliably, relatively quickly, and efficiently. The ribozymes can also b ...[more]

PMID: 34514224

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Project description:Real-time monitoring of the brain is potentially valuable for performance monitoring, communication, training or rehabilitation. In natural situations, the brain performs a complex mix of various sensory, motor or cognitive functions. Thus, real-time brain monitoring would be most valuable if (a) it could decode information from multiple brain systems simultaneously, and (b) this decoding of each brain system were robust to variations in the activity of other (unrelated) brain systems. Previous studies showed that it is possible to decode some information from different brain systems in retrospect and/or in isolation. In our study, we set out to determine whether it is possible to simultaneously decode important information about a user from different brain systems in real time, and to evaluate the impact of concurrent activity in different brain systems on decoding performance.We study these questions using electrocorticographic signals recorded in humans. We first document procedures for generating stable decoding models given little training data, and then report their use for offline and for real-time decoding from 12 subjects (six for offline parameter optimization, six for online experimentation). The subjects engage in tasks that involve movement intention, movement execution and auditory functions, separately, and then simultaneously. Main Results: Our real-time results demonstrate that our system can identify intention and movement periods in single trials with an accuracy of 80.4% and 86.8%, respectively (where 50% would be expected by chance). Simultaneously, the decoding of the power envelope of an auditory stimulus resulted in an average correlation coefficient of 0.37 between the actual and decoded power envelopes. These decoders were trained separately and executed simultaneously in real time.This study yielded the first demonstration that it is possible to decode simultaneously the functional activity of multiple independent brain systems. Our comparison of univariate and multivariate decoding strategies, and our analysis of the influence of their decoding parameters, provides benchmarks and guidelines for future research on this topic.

Dataset Information

Digital Microfluidics Chips for the Execution and Real-Time Monitoring of Multiple Ribozymatic Cleavage Reactions.

Publications

Digital Microfluidics Chips for the Execution and Real-Time Monitoring of Multiple Ribozymatic Cleavage Reactions.

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