Evidence map›Paper›PMID 34841078›Full record

ArticleClinical mass spectrometry (Del Mar, Calif.)2019

Unified representation of high- and low-resolution spectra to facilitate application of mass spectrometric techniques in clinical practice.

E S Zhvansky, A A Sorokin, S I Pekov, M I Indeykina, D G Ivanov, V A Shurkhay, V A Eliferov, D S Zavorotnyuk, N G Levin, K V Bocharov and 5 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Clinical mass spectrometry (Del Mar, Calif.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.3field-weighted citation impact, top 20% 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

3 citing papers in PubMed, 18 citations in OpenAlex.

  1. Early Prediction of Septic Shock in Emergency Department Using Serum Metabolites.Journal of the American Society for Mass Spectrometry · 2025
    Article
  2. Article
  3. Article
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

15 authors at 3 institutions in 1 country.

E S ZhvanskyMoscow Institute of Physics and Technology, Dolgoprudnyy, Moscow Region, Russian Federation.
A A SorokinMoscow Institute of Physics and Technology, Dolgoprudnyy, Moscow Region, Russian Federation.
S I PekovMoscow Institute of Physics and Technology, Dolgoprudnyy, Moscow Region, Russian Federation.
M I IndeykinaMoscow Institute of Physics and Technology, Dolgoprudnyy, Moscow Region, Russian Federation.
D G IvanovMoscow Institute of Physics and Technology, Dolgoprudnyy, Moscow Region, Russian Federation.
V A ShurkhayFederal State Autonomous Institution N.N. Burdenko National Scientific and Practical Center for Neurosurgery of the Ministry of Healthcare of the Russian Federation, Moscow, Russian Federation.
V A EliferovMoscow Institute of Physics and Technology, Dolgoprudnyy, Moscow Region, Russian Federation.
D S ZavorotnyukMoscow Institute of Physics and Technology, Dolgoprudnyy, Moscow Region, Russian Federation.
N G LevinMoscow Institute of Physics and Technology, Dolgoprudnyy, Moscow Region, Russian Federation.
K V BocharovMoscow Institute of Physics and Technology, Dolgoprudnyy, Moscow Region, Russian Federation.
S I TkachenkoMoscow Institute of Physics and Technology, Dolgoprudnyy, Moscow Region, Russian Federation.
M S BelenikinMoscow Institute of Physics and Technology, Dolgoprudnyy, Moscow Region, Russian Federation.
A A PotapovFederal State Autonomous Institution N.N. Burdenko National Scientific and Practical Center for Neurosurgery of the Ministry of Healthcare of the Russian Federation, Moscow, Russian Federation.
E N NikolaevSkolkovo Institute of Science and Technology, Moscow, Russian Federation.
I A PopovMoscow Institute of Physics and Technology, Dolgoprudnyy, Moscow Region, Russian Federation.
Moscow Institute of Physics and Technology · RUMinistry of Health of the Russian Federation · RUSkolkovo Institute of Science and Technology · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The majority of research in the biomedical sciences is carried out with the highest resolution accessible to the scientist, but, in the clinic, cost constraints necessitate the use of low-resolution devices. Here, we compare high- and low-resolution direct mass spectrometry profiling data and propose a simple pre-processing technique that makes high-resolution data suitable for the development of classification and regression techniques applicable to low-resolution data, while retaining high accuracy of analysis. This work demonstrates an approach to de-noising spectra to make the same representation for both high- and low-resolution spectra. This approach uses noise threshold detection based on the Tversky index, which compares spectra with different resolutions, and minimizes the percentage of resolution-specific peaks. The presented method provides an avenue for the development of analytical algorithms using high-resolution mass spectrometry data, while applying these algorithms in the clinic using low-resolution mass spectrometers.

Indexed as

Ambient ionization mass-spectrometryData transformationDESI, desorption electrospray ionizationFWHM, full width at half maximumICR, ion cyclotron resonanceLow- and high-resolution comparisonMALDI, matrix assisted laser desorption ionizationNESI, needle electrospray ionizationREIMS, rapid evaporative ionization mass spectrometrySNR, signal to noise ratio

Identifiers

PMID34841078
PMCPMC8620137
OpenAlexW2923378847

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.