Evidence map›Paper›PMID 37303174›Full record

ReviewCurrent medicinal chemistry2024

Electrochemical Label-free Methods for Ultrasensitive Multiplex Protein Profiling of Infectious Diseases.

Sasya Madhurantakam, Nathan Kodjo Mintah Churcher, Ruchita Mahesh Kumar, Shalini Prasad

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current medicinal chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 33% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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

4 authors at 1 institution in 1 country.

Sasya MadhurantakamDepartment of Bioengineering, The University of Texas at Dallas, 75080, USA.
Nathan Kodjo Mintah ChurcherDepartment of Bioengineering, The University of Texas at Dallas, 75080, USA.
Ruchita Mahesh KumarDepartment of Bioengineering, The University of Texas at Dallas, 75080, USA.
Shalini PrasadDepartment of Bioengineering, The University of Texas at Dallas, 75080, USA.ORCID 0000-0002-2404-3801
The University of Texas at Dallas · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electrochemical detection methods are the more appropriate detection methods when it comes to the sensitive and specific determination of biomarkers. Biomarkers are the biological targets for disease diagnosis and monitoring. This review focuses on recent advances in label-free detection of biomarkers for infectious disease diagnosis. The current state of the art for rapid detection of infectious diseases and their clinical applications and challenges were discussed. Label-free electroanalytical methods are probably the most promising means to achieve this. We are currently in the early stages of the emerging technology of using label-free electrochemistry of proteins to develop biosensors. To date, antibody-based biosensors have been intensively developed, although many improvements in reproducibility and sensitivity are still needed. Moreover, there is no doubt that a growing number of aptamers and hopefully label-free biosensors based on nanomaterials will soon be used for disease diagnosis and therapy monitoring. And also here in this review article, we have discussed recent developments in the diagnosis of bacterial and viral infections, as well as the current status of the use of label-free electrochemical methods for monitoring inflammatory diseases.

Indexed as

BiomarkersBiosensing TechniquesCommunicable DiseasesElectrochemical TechniquesHumansBiomarkersbiomarkersbiosensorsdiagnosiselectrochemicalInfectious diseaseslabel-free.

Identifiers

PMID37303174
OpenAlexW4380264478

What OpenQuestion holds

Textmetadata
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.