Evidence map›Paper›PMID 33674934›Full record

ArticleAnalytical and bioanalytical chemistry2022

Signal amplification strategies for clinical biomarker quantification using elemental mass spectrometry.

Andrea L Larraga-Urdaz, Maria L Fernandez Sanchez, Jorge Ruiz Encinar, Jose M Costa-Fernandez

Abstract read
PubMed Publisher
In one paragraph

Article in Analytical and bioanalytical chemistry, 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
–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

4 citing papers in PubMed.

  1. Review
  2. Review
  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

4 authors.

Andrea L Larraga-UrdazDepartment of Physical and Analytical Chemistry, University of Oviedo, Avda. Julian Claveria, 8, 33006, Oviedo, Spain.
Maria L Fernandez SanchezDepartment of Physical and Analytical Chemistry, University of Oviedo, Avda. Julian Claveria, 8, 33006, Oviedo, Spain.
Jorge Ruiz EncinarDepartment of Physical and Analytical Chemistry, University of Oviedo, Avda. Julian Claveria, 8, 33006, Oviedo, Spain. ruizjorge@uniovi.es.
Jose M Costa-FernandezDepartment of Physical and Analytical Chemistry, University of Oviedo, Avda. Julian Claveria, 8, 33006, Oviedo, Spain. jcostafe@uniovi.es.ORCID http://orcid.org/0000-0002-8671-5300

Funding

Government of Principado de Asturias FC-GRUPIN-IDI/2018/000166Spanish Ministry of Economy and Competitiveness PID2019- 109698GB-I00
6 · The paper itself

Abstract

The current trends in modern medicine towards early diagnosis, or even prognosis, of different diseases have brought about the need for the corresponding biomarker detection at ever lower levels in really complex matrices. To do so, it is necessary to use proper extremely sensitive detection techniques such as elemental mass spectrometry. However, target labelling with metals for subsequent sensitive ICP-MS detection falls short nowadays even if resorting to inorganic nanoparticles containing a high number of detectable elements. Thus, new amplification strategies are being proposed to face this analytical challenge that will be critically discussed in this paper. Fundamentals of different novel strategies developed to achieve signal amplification and sensitive elemental mass spectrometry detection are here discussed. Some representative examples of relevant clinical applications are highlighted, along with future prospects and challenges.

Indexed as

BiomarkersHep G2 CellsHumansMass SpectrometryMetal NanoparticlesSensitivity and SpecificityBiomarkersBiomarker quantificationClinical biomarkersElemental mass spectrometryElemental tagsICP-MSSignal amplification

Identifiers

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.