Evidence map›Paper›PMID 34378906›Full record

ArticleAnalytical chemistry2021

Sample-to-Answer Robotic ELISA.

Chuqing Zhou, Zecong Fang, Cunyi Zhao, Xiyan Mai, Shiva Emami, Ameer Y Taha, Gang Sun, Tingrui Pan

Open access · greenAbstract read
In one paragraph

Article in Analytical chemistry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.1field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 39 citations in OpenAlex.

  1. Article
  2. Naked-Eye and On-Site Detection ofFoods (Basel, Switzerland) · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 2 countries.

Chuqing ZhouMicro-Nano Innovations (MiNI) Laboratory, Department of Biomedical Engineering, University of California, Davis, California 95616, United States.
Zecong FangMicro-Nano Innovations (MiNI) Laboratory, Department of Biomedical Engineering, University of California, Davis, California 95616, United States.
Cunyi ZhaoDepartment of Biological and Agricultural Engineering, University of California, Davis, California 95616, United States.ORCID 0000-0003-0360-2050
Xiyan MaiMicro-Nano Innovations (MiNI) Laboratory, Department of Biomedical Engineering, University of California, Davis, California 95616, United States.
Shiva EmamiDepartment of Food Science and Technology, University of California, Davis, California 95616, United States.
Ameer Y TahaDepartment of Food Science and Technology, University of California, Davis, California 95616, United States.ORCID 0000-0003-4611-7450
Gang SunDepartment of Biological and Agricultural Engineering, University of California, Davis, California 95616, United States.ORCID 0000-0002-6608-9971
Tingrui PanMicro-Nano Innovations (MiNI) Laboratory, Department of Biomedical Engineering, University of California, Davis, California 95616, United States.ORCID 0000-0002-8851-0667
University of California, Davis · USMolecular Innovations (United States) · USChinese Academy of Sciences · CNUniversity of Science and Technology of China · CN

Funding

Workshop on Environmental Technology Transfer and EntrepreneurshipP42ES004699 · NIEHS · UNIVERSITY OF CALIFORNIA DAVIS · PI YOUNG, THOMAS MICHAEL · 1987 to 2021
$50.1M
NIEHS NIH HHS P42 ES004699
6 · The paper itself

Abstract

Enzyme-linked immunosorbent assays (ELISA), as one of the most used immunoassays, have been conducted ubiquitously in hospitals, research laboratories, etc. However, the conventional ELISA procedure is usually laborious, occupies bulky instruments, consumes lengthy operation time, and relies considerably on the skills of technicians, and such limitations call for innovations to develop a fully automated ELISA platform. In this paper, we have presented a system incorporating a robotic-microfluidic interface (RoMI) and a modular hybrid microfluidic chip that embeds a highly sensitive nanofibrous membrane, referred to as the Robotic ELISA, to achieve human-free sample-to-answer ELISA tests in a fully programmable and automated manner. It carries out multiple bioanalytical procedures to replace the manual steps involved in classic ELISA operations, including the pneumatically driven high-precision pipetting, efficient mixing and enrichment enabled by back-and-forth flows, washing, and integrated machine vision for colorimetric readout. The Robotic ELISA platform has achieved a low limit of detection of 0.1 ng/mL in the detection of a low sample volume (15 μL) of chloramphenicol within 20 min without human intervention, which is significantly faster than that of the conventional ELISA procedure. Benefiting from its modular design and automated operations, the Robotic ELISA platform has great potential to be deployed for a broad range of detections in various resource-limited settings or high-risk environments, where human involvement needs to be minimized while the testing timeliness, consistency, and sensitivity are all desired.

Indexed as

Microfluidic Analytical TechniquesRobotic Surgical ProceduresColorimetryEnzyme-Linked Immunosorbent AssayHumansImmunoassayMicrofluidics

Identifiers

PMID34378906
PMCPMC8422985
OpenAlexW3191866662

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.