Evidence map›Paper›PMID 36188278›Full record

ArticleACS omega2022

Preparation of Hydrothermal Carbon Quantum Dots as a Contrast Amplifying Technique for the diaCEST MRI Contrast Agents.

Shalini Pandey, Rimilmandrita Ghosh, Arindam Ghosh

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In one paragraph

Article in ACS omega, 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. 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

3 authors.

Shalini PandeySchool of Chemical Sciences, National Institute of Science Education and Research Bhubaneswar (NISER), HBNI, AT/PO Jatni, Khordha752050, Odisha, India.ORCID https://orcid.org/0000-0003-0604-2079
Rimilmandrita GhoshSchool of Chemical Sciences, National Institute of Science Education and Research Bhubaneswar (NISER), HBNI, AT/PO Jatni, Khordha752050, Odisha, India.
Arindam GhoshSchool of Chemical Sciences, National Institute of Science Education and Research Bhubaneswar (NISER), HBNI, AT/PO Jatni, Khordha752050, Odisha, India.ORCID https://orcid.org/0000-0002-6963-9879

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The discovery of exogenous contrast agents (CAs) is one of the key factors behind the success and widespread acceptability of MRI as an imaging tool. To the long list of CAs, the newest addition is the chemical exchange saturation transfer (CEST)-based CAs. Among them, the diaCEST CAs are the safer metal-free option constituted by a large pool of organic and macromolecules, but the tradeoff comes in terms of smaller natural offset. Another major challenge for the CEST CAs is that they need to operate in the tens of millimolar concentration range to produce any meaningful contrast. The quest for high efficiency diaCEST agents has led to a number of strategies such as use of hydrogen bonding, use of equivalent protons, and use of diatropic ring current. Here, we present carbon quantum dot formation using hydrothermal treatment as a new strategy to amplify diaCEST contrast efficiency. We show that while the well-known analgesic drug lidocaine hydrochloride when repurposed as a diaCEST CA produces no contrast at the physiological pH and temperature, the carbon dots prepared from it elevate the physiological contrast to a sizable 11%. Also, the maximum efficiency at an acidic pH gets amplified by a factor of 2 to 46%. The study showed that the enhancement in CEST efficiency is reproducible and the pH response of these carbon dots is tunable through variation in synthesis conditions such as temperature, duration, and precursor concentration.

Identifiers

PMID36188278
PMCPMC9520682

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Registered trials

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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.