Evidence map›Paper›PMID 25268706›Full record

ArticleThe Analyst2014

Online SERS detection of the 20 proteinogenic L-amino acids separated by capillary zone electrophoresis.

Pierre Negri, Zachary D Schultz

Abstract read
In one paragraph

Article in The Analyst, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
3.6field-weighted citation impact, top 7% 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

18 citing papers in PubMed, 68 citations in OpenAlex.

  1. Article
  2. Review
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  4. Article
  5. Determination of lentiviral titer by surface enhanced Raman scattering.Analytical methods : advancing methods and applications · 2022
    Article
  6. 3-D printed injection system for capillary electrophoresis.Analytical methods : advancing methods and applications · 2022
    Article
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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

2 authors at 1 institution in 1 country.

Pierre NegriDepartment of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA. Schultz.41@nd.edu.
Zachary D Schultz
University of Notre Dame · US

Funding

Ultrasensitive Label-Free Flow Detector via Surface Enhanced Raman ScatteringR21GM107893 · NIGMS · UNIVERSITY OF NOTRE DAME · PI SCHULTZ, ZACHARY · 2013 to 2015
$570k
NIGMS NIH HHS R21 GM107893
6 · The paper itself

Abstract

A sheath-flow surface-enhanced Raman scattering (SERS) detector is demonstrated to provide chemical information enabling identification of the 20 proteinogenic L-amino acids separated by capillary zone electrophoresis (CZE). Amino acids were used to illustrate the chemical specificity of SERS detection from structurally related molecules. Analysis of the SERS electropherograms obtained from the separation and sequential online detection of six groups of structurally related amino acids shows that our sheath-flow SERS detector is able to resolve the characteristic Raman bands attributed to the amine, carboxyl, and side chain constituents. The results demonstrate the chemical information available from our detector and also provide insight into the nature of the analyte interaction with the silver SERS substrate. The spectra extracted from the SERS electropherogram of a mixture containing the 20 proteinogenic L-amino acids show unique signatures characteristic to each amino acid, thus enabling identification. The results presented here demonstrate the potential of this sheath-flow SERS detector as a general purpose method for high throughput characterization and identification following separations of complex biomolecular mixtures.

Indexed as

Amino AcidsElectrophoresis, CapillarySpectrum Analysis, RamanAmino Acids

Identifiers

PMID25268706
PMCPMC4249764
OpenAlexW2152569355

What OpenQuestion holds

Textmetadata
LicenceTDM
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.