Evidence map›Paper›PMID 30228291›Full record

ArticleScientific reports2018

Nanoparticle-based Chemiluminescence for Chiral Discrimination of Thiol-Containing Amino Acids.

Maryam Shahrajabian, Forough Ghasemi, M Reza Hormozi-Nezhad

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.3field-weighted citation impact, top 13% 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

8 citing papers in PubMed, 34 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. 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

3 authors at 1 institution in 1 country.

Maryam ShahrajabianDepartment of Chemistry, Sharif University of Technology, Tehran, 11155-9516, Iran.
Forough GhasemiDepartment of Chemistry, Sharif University of Technology, Tehran, 11155-9516, Iran.
M Reza Hormozi-NezhadDepartment of Chemistry, Sharif University of Technology, Tehran, 11155-9516, Iran. hormozi@sharif.edu.
Sharif University of Technology · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ability to recognize the molecular chirality of enantiomers is extremely important owing to their critical role in drug development and biochemistry. Convenient discrimination of enantiomers has remained a challenge due to lack of unsophisticated methods. In this work, we have reported a simple strategy for chiral recognition of thiol-containing amino acids including penicillamine (PA), and cysteine (Cys). We have successfully designed a nanoparticle-based chemiluminescence (CL) system based on the reaction between cadmium telluride quantum dots (CdTe QDs) and the enantiomers. The different interactions of CdTe QDs with PA enantiomers or Cys enantiomers led to different CL intensities, resulting in the chiral recognition of these enantiomers. The developed method showed the ability for determination of enantiomeric excess of PA and Cys. It has also obtained an enantioselective concentration range from 1.15 to 9.2 mM for PA. To demonstrate the potential application of this method, the designed platform was applied for the quantification of PA in urine and tablet samples. For the first time, we presented a novel practical application of nanoparticle-based CL system for chiral discrimination.

Indexed as

LuminescenceQuantum DotsCadmium CompoundsCysteineHumansLuminescent MeasurementsNanoparticlesPenicillamineTabletsTelluriumUrinalysisCadmium Compoundscadmium tellurideCysteinePenicillamineTabletsTellurium

Identifiers

PMID30228291
PMCPMC6143635
OpenAlexW2892002408

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.