Evidence map›Paper›PMID 31344297›Full record

ReviewAngewandte Chemie (International ed. in English)2019

Quantitation of Femtomolar-Level Protein Biomarkers Using a Simple Microbubbling Digital Assay and Bright-Field Smartphone Imaging.

Hui Chen, Zhao Li, Lingzhi Zhang, Philippe Sawaya, Jianbo Shi, Ping Wang

Abstract readReview
In one paragraph

Review in Angewandte Chemie (International ed. in English), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
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

22 citing papers in PubMed.

  1. Trial
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  15. Article
  16. DNA Walkers for Biosensing Development.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022
    Review
  17. Article
  18. Article
  19. Article
  20. 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

6 authors.

Hui ChenDepartment of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.ORCID 0000-0002-9422-8959
Zhao LiDepartment of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Lingzhi ZhangDepartment of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Philippe SawayaDepartment of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Jianbo ShiDepartment of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Ping WangDepartment of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.ORCID 0000-0002-8318-4815

Funding

Development of a Point-of-Care Volumetric Bar-Chart Chip for Drug QuantitationR01DA035868 · NIDA · UNIVERSITY OF PENNSYLVANIA · PI QIN, LIDONG, WANG, PING · 2013 to 2020
$4.3M
NIDA NIH HHS R01 DA035868
6 · The paper itself

Abstract

Quantitating ultra-low concentrations of protein biomarkers is critical for early disease diagnosis and treatment. However, most current point-of-care (POC) assays are limited in sensitivity. Herein, we introduce an ultra-sensitive and facile microbubbling assay for the quantification of protein biomarkers with a digital-readout method that requires only a smartphone camera. We used machine learning to develop a smartphone application for automated image analysis to facilitate accurate and robust counting. Using this method, post-prostatectomy surveillance of prostate specific antigen (PSA) can be achieved with a detection limit (LOD) of 2.1 fm (0.060 pg mL

Indexed as

Biological AssayBiomarkersBiosensing TechniquesHumansPoint-of-Care SystemsProteinsSmartphoneBiomarkersProteinsbiosensorsdigital assayplatinum nanoparticlesprotein detectionsmartphone

Identifiers

PMID31344297
PMCPMC7211056

What OpenQuestion holds

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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.