Evidence map›Paper›PMID 36551469›Full record

ReviewAntibiotics (Basel, Switzerland)2022

Antibiotic Susceptibility Testing with Raman Biosensing.

Andrei Novikov, Adeliya Sayfutdinova, Ekaterina Botchkova, Dmitry Kopitsyn, Rawil Fakhrullin

Abstract readReview
In one paragraph

Review in Antibiotics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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

5 authors.

Andrei NovikovDepartment of Physical and Colloid Chemistry, Gubkin University, 65/1 Leninsky Prospect, 119991 Moscow, Russia.ORCID 0000-0002-0887-6678
Adeliya SayfutdinovaDepartment of Physical and Colloid Chemistry, Gubkin University, 65/1 Leninsky Prospect, 119991 Moscow, Russia.ORCID 0000-0003-0246-8371
Ekaterina BotchkovaDepartment of Physical and Colloid Chemistry, Gubkin University, 65/1 Leninsky Prospect, 119991 Moscow, Russia.
Dmitry KopitsynDepartment of Physical and Colloid Chemistry, Gubkin University, 65/1 Leninsky Prospect, 119991 Moscow, Russia.ORCID 0000-0002-5791-4917
Rawil FakhrullinDepartment of Physical and Colloid Chemistry, Gubkin University, 65/1 Leninsky Prospect, 119991 Moscow, Russia.ORCID 0000-0003-2015-7649

Funding

Russian Science Foundation 22-73-10224
6 · The paper itself

Abstract

Antibiotics guard us against bacterial infections and are among the most commonly used medicines. The immediate consequence of their large-scale production and prescription is the development of antibiotic resistance. Therefore, rapid detection of antibiotic susceptibility is required for efficient antimicrobial therapy. One of the promising methods for rapid antibiotic susceptibility testing is Raman spectroscopy. Raman spectroscopy combines fast and contactless acquisition of spectra with good selectivity towards bacterial cells. The antibiotic-induced changes in bacterial cell physiology are detected as distinct features in Raman spectra and can be associated with antibiotic susceptibility. Therefore, the Raman-based approach may be beneficial in designing therapy against multidrug-resistant infections. The surface-enhanced Raman spectroscopy (SERS) and resonance Raman spectroscopy (RRS) additionally provide excellent sensitivity. In this review, we present an analysis of the Raman spectroscopy-based optical biosensing approaches aimed at antibiotic susceptibility testing.

Indexed as

antibioticsantibiotic susceptibilitybacteriaminimum inhibitory concentrationmultidrug resistancenanomaterialsnanoparticlessurface-enhanced Raman scattering

Identifiers

PMID36551469
PMCPMC9774239

What OpenQuestion holds

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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.