Evidence map›Paper›PMID 26525998›Full record

ReviewThe Analyst2016

Electrochemistry-based approaches to low cost, high sensitivity, automated, multiplexed protein immunoassays for cancer diagnostics.

Chandra K Dixit, Karteek Kadimisetty, Brunah A Otieno, Chi Tang, Spundana Malla, Colleen E Krause, James F Rusling

Abstract readReview
In one paragraph

Review in The Analyst, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

  1. Review
  2. Review
  3. Promising predictive molecular biomarkers for cervical cancer (Review).International journal of molecular medicine · 2024
    Review
  4. Article
  5. Review
  6. Article
  7. Review
  8. Review
  9. Review
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  11. Article
  12. Review
  13. Review
  14. 3D-Printed Immunosensor Arrays for Cancer Diagnostics.Sensors (Basel, Switzerland) · 2020
    Review
  15. Review
  16. Article
  17. Review
  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

7 authors.

Chandra K DixitDepartment of Chemistry, University of Connecticut, Storrs, CT 06269, USA.
Karteek Kadimisetty
Brunah A Otieno
Chi Tang
Spundana Malla
Colleen E Krause
James F Rusling

Funding

Protein Biomarker Arrays for Personalized Treatment of Prostate CancerR01EB016707 · NIBIB · UNIVERSITY OF CONNECTICUT STORRS · PI RUSLING, JAMES F. · 2014 to 2017
$1.4M
Protein Biosensor Arrays Based on NanomaterialsR01EB014586 · NIBIB · UNIVERSITY OF CONNECTICUT STORRS · PI RUSLING, JAMES F. · 2011 to 2014
$1.4M
NIBIB NIH HHS EB014586NIBIB NIH HHS EB016707NIBIB NIH HHS R01 EB014586NIBIB NIH HHS R01 EB016707
6 · The paper itself

Abstract

Early detection and reliable diagnostics are keys to effectively design cancer therapies with better prognoses. The simultaneous detection of panels of biomarker proteins holds great promise as a general tool for reliable cancer diagnostics. A major challenge in designing such a panel is to decide upon a coherent group of biomarkers which have higher specificity for a given type of cancer. The second big challenge is to develop test devices to measure these biomarkers quantitatively with high sensitivity and specificity, such that there are no interferences from the complex serum or tissue matrices. Lastly, integrating all these tests into a technology that does not require exclusive training to operate, and can be used at point-of-care (POC) is another potential bottleneck in futuristic cancer diagnostics. In this article, we review electrochemistry-based tools and technologies developed and/or used in our laboratories to construct low-cost microfluidic protein arrays for the highly sensitive detection of a panel of cancer-specific biomarkers with high specificity which at the same time has the potential to be translated into POC applications.

Indexed as

Limit of DetectionAutomationElectrochemistryHumansImmunoassayNeoplasmsProteinsProteins

Identifiers

PMID26525998
PMCPMC4701586

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.