Evidence map›Paper›PMID 35591151›Full record

ArticleSensors (Basel, Switzerland)2022

A Self-Driven Microfluidic Chip for Ricin and Abrin Detection.

Xuexin Bai, Chenyi Hu, Liang Chen, Jing Wang, Yanwei Li, Wei Wan, Zhiying Jin, Yue Li, Wenwen Xin, Lin Kang and 4 more

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.8field-weighted citation impact, top 32% 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

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
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

14 authors at 3 institutions in 1 country.

Xuexin BaiState Key Laboratory of Pathogen and Biosecurity, Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing 100071, China.
Chenyi HuState Key Laboratory of Pathogen and Biosecurity, Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing 100071, China.
Liang ChenState Key Laboratory of Pathogen and Biosecurity, Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing 100071, China.
Jing WangState Key Laboratory of Pathogen and Biosecurity, Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing 100071, China.
Yanwei LiState Key Laboratory of Pathogen and Biosecurity, Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing 100071, China.
Wei WanState Key Laboratory of Pathogen and Biosecurity, Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing 100071, China.
Zhiying JinState Key Laboratory of Pathogen and Biosecurity, Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing 100071, China.
Yue LiState Key Laboratory of Pathogen and Biosecurity, Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing 100071, China.
Wenwen XinState Key Laboratory of Pathogen and Biosecurity, Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing 100071, China.
Lin KangState Key Laboratory of Pathogen and Biosecurity, Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing 100071, China.
Han JinInstitute of Micro-Nano Science and Technology, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Hao YangState Key Laboratory of Pathogen and Biosecurity, Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing 100071, China.
Jinglin WangState Key Laboratory of Pathogen and Biosecurity, Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing 100071, China.
Shan GaoState Key Laboratory of Pathogen and Biosecurity, Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing 100071, China.
Institute of Microbiology · CNAcademy of Military Medical Sciences · CNShanghai Jiao Tong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ricin and abrin are phytotoxins that can be easily used as biowarfare and bioterrorism agents. Therefore, developing a rapid detection method for both toxins is of great significance in the field of biosecurity. In this study, a novel nanoforest silicon microstructure was prepared by the micro-electro-mechanical systems (MEMS) technique; particularly, a novel microfluidic sensor chip with a capillary self-driven function and large surface area was designed. Through binding with the double antibodies sandwich immunoassay, the proposed sensor chip is confirmed to be a candidate for sensing the aforementioned toxins. Compared with conventional immunochromatographic test strips, the proposed sensor demonstrates significantly enhanced sensitivity (≤10 pg/mL for both toxins) and high specificity against the interference derived from juice or milk, while maintaining good linearity in the range of 10-6250 pg/mL. Owing to the silicon nanoforest microstructure and improved homogeneity of the color signal, short detection time (within 15 min) is evidenced for the sensor chip, which would be helpful for the rapid tracking of ricin and abrin for the field of biosecurity.

Indexed as

AbrinRicinToxins, BiologicalMicrofluidicsSiliconAbrinRicinSiliconToxins, Biologicalabrinbiosecuritymicrofluidic chipnanoforest structurericin

Identifiers

PMID35591151
PMCPMC9101213
OpenAlexW4225301773

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.