Evidence map›Paper›PMID 35293092›Full record

ArticleAngewandte Chemie (International ed. in English)2022

Ultrafast Electrothermal Flow-Enhanced Magneto Biosensor for Highly Sensitive Protein Detection in Whole Blood.

Jiran Li, Peter B Lillehoj

Open access · greenAbstract read
In one paragraph

Article in Angewandte Chemie (International ed. in English), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.4field-weighted citation impact, top 22% 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

4 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
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

2 authors at 1 institution in 1 country.

Jiran LiDepartment of Mechanical Engineering, Rice University, Houston, TX 77005, USA.
Peter B LillehojDepartment of Mechanical Engineering, Rice University, Houston, TX 77005, USA.ORCID 0000-0002-0289-2634
Rice University · US

Funding

Rapid in-field malaria diagnosis, prognosis and monitoring using a mobile phoneR01AI113257 · NIAID · RICE UNIVERSITY · PI LILLEHOJ, PETER B · 2015 to 2018
$1.8M
Unbiased electrothermal flow-enhanced identification of antigen-specific T cells in lung cancerR21CA283852 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LILLEHOJ, PETER B, REUBEN, ALEXANDRE · 2023 to 2023
$413k
NCI NIH HHS R21 CA283852NIAID NIH HHS R01 AI113257
6 · The paper itself

Abstract

Current diagnostic tests for sensitive protein detection rely on immunological techniques, such as ELISA, which require sample purification, multiple washing steps and lengthy incubation, hindering their use for rapid testing. Here, we report a simple electrothermal flow-enhanced biosensor for ultrafast, high sensitivity measurements of protein biomarkers in whole blood. Magnetic nanobeads dually-labeled with a detection antibody and enzyme reporter are used to form immunocomplexes with the target protein, which are readily transported to the sensor via magnetic concentration. The incorporation of electrothermal flows enhances immunocomplex formation, allowing for rapid and sensitive detection without requiring blood purification or lengthy incubation. Proof of concept was carried out using Plasmodium falciparum histidine-rich protein 2 (PfHRP2), a malaria parasite biomarker, which could be detected at concentrations as low as 5.7 pg mL

Indexed as

Biosensing TechniquesMalaria, FalciparumAntibodiesEnzyme-Linked Immunosorbent AssayHumansPlasmodium falciparumProtozoan ProteinsAntibodiesProtozoan ProteinsBloodElectrochemicalElectrothermal FlowImmunosensorsMagneto

Identifiers

PMID35293092
PMCPMC9117500
OpenAlexW4220738850

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.