Dataset Information

Electrochemiluminescence in paired signal electrode (ECLipse) enables modular and scalable biosensing.

ABSTRACT: Electrochemiluminescence (ECL) has an inherently low background and enables precise chemical reactions through electrical control. Here, we report an advanced ECL system, termed ECLipse (ECL in paired signal electrode). We physically separated ECL generation from target detection: These two processes were carried out in isolated chambers and coupled through an electrode. The strategy allowed us to minimize cross-chemical reactions, design electrodes for high ECL signals, and integrate multiple sensors in a chip. As a proof of concept, we implemented an eight-plex ECLipse and applied it to detect host factors in human plasma. ECLipse achieved higher signal-to-noise ratio than conventional ECL assays and was >7000-fold more sensitive than enzyme-linked immunosorbent assay. In a pilot clinical study, we could detect septic conditions by measuring host factors [i.e., interleukin-3 (IL-3), IL-6, and procalcitonin (PCT)]. ECLipse assay further revealed distinct IL-3 and IL-6 patterns in patients with severe acute respiratory syndrome coronavirus 2 infection.

SUBMITTER: Cho YK

PROVIDER: S-EPMC9491722 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Electrochemiluminescence in paired signal electrode (ECLipse) enables modular and scalable biosensing.

Cho Young Kwan YK Kim Hyunho H Bénard Alan A Woo Hyun-Kyung HK Czubayko Franziska F David Paul P Hansen Frederik J FJ Lee Jong Ik JI Park Jay Hoon JH Schneck Emmanuel E Weber Georg F GF Shin Ik-Soo IS Lee Hakho H

Science advances 20220921 38

Electrochemiluminescence (ECL) has an inherently low background and enables precise chemical reactions through electrical control. Here, we report an advanced ECL system, termed ECLipse (ECL in paired signal electrode). We physically separated ECL generation from target detection: These two processes were carried out in isolated chambers and coupled through an electrode. The strategy allowed us to minimize cross-chemical reactions, design electrodes for high ECL signals, and integrate multiple s ...[more]

PMID: 36129990

Similar Datasets

Project description:As phenomics data volume and dimensionality increase due to advancements in sensor technology, there is an urgent need to develop and implement scalable data processing pipelines. Current phenomics data processing pipelines lack modularity, extensibility, and processing distribution across sensor modalities and phenotyping platforms. To address these challenges, we developed PhytoOracle (PO), a suite of modular, scalable pipelines for processing large volumes of field phenomics RGB, thermal, PSII chlorophyll fluorescence 2D images, and 3D point clouds. PhytoOracle aims to (i) improve data processing efficiency; (ii) provide an extensible, reproducible computing framework; and (iii) enable data fusion of multi-modal phenomics data. PhytoOracle integrates open-source distributed computing frameworks for parallel processing on high-performance computing, cloud, and local computing environments. Each pipeline component is available as a standalone container, providing transferability, extensibility, and reproducibility. The PO pipeline extracts and associates individual plant traits across sensor modalities and collection time points, representing a unique multi-system approach to addressing the genotype-phenotype gap. To date, PO supports lettuce and sorghum phenotypic trait extraction, with a goal of widening the range of supported species in the future. At the maximum number of cores tested in this study (1,024 cores), PO processing times were: 235 minutes for 9,270 RGB images (140.7 GB), 235 minutes for 9,270 thermal images (5.4 GB), and 13 minutes for 39,678 PSII images (86.2 GB). These processing times represent end-to-end processing, from raw data to fully processed numerical phenotypic trait data. Repeatability values of 0.39-0.95 (bounding area), 0.81-0.95 (axis-aligned bounding volume), 0.79-0.94 (oriented bounding volume), 0.83-0.95 (plant height), and 0.81-0.95 (number of points) were observed in Field Scanalyzer data. We also show the ability of PO to process drone data with a repeatability of 0.55-0.95 (bounding area).

Dataset Information

Electrochemiluminescence in paired signal electrode (ECLipse) enables modular and scalable biosensing.

Publications

Electrochemiluminescence in paired signal electrode (ECLipse) enables modular and scalable biosensing.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets