Evidence map›Paper›PMID 36559812›Full record

ReviewPolymers2022

Advances in Polymeric Colloids for Cancer Treatment.

Imran Ali, Sara H Althakfi, Mohammad Suhail, Marcello Locatelli, Ming-Fa Hsieh, Mosa Alsehli, Ahmed M Hameed

Abstract readReview
In one paragraph

Review in Polymers, 2022. 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
–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

3 citing papers in PubMed.

  1. Article
  2. Review
  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

7 authors.

Imran AliDepartment of Chemistry, Jamia Millia Islamia (Central University), Jamia Nagar, New Delhi 110025, India.ORCID 0000-0001-6511-8374
Sara H AlthakfiDepartment of Chemistry, Faculty of Applied Sciences, Umm Al-Qura University, Makkah 21955, Saudi Arabia.
Mohammad SuhailDepartment of Chemistry, Siddhartha Degree College, Aakhlaur Kheri (Saharanpur), Uttar Pradesh 251311, India.
Marcello LocatelliAnalytical and Bioanalytical Chemistry, Department of Pharmacy, University "G. d'Annunzio" of Chieti-Pescara, Build B, Level 2, Via dei Vestini, 31, 66100 Chieti, Italy.ORCID 0000-0002-0840-825X
Ming-Fa HsiehDepartment of Biomedical Engineering, Chung Yuan Christian University, 200, Chung Pei Rd., Chung Li 320314, Taiwan.ORCID 0000-0001-5254-1341
Mosa AlsehliDepartment of Chemistry, College of Science, Taibah University, Medina 46423, Saudi Arabia.
Ahmed M HameedDepartment of Chemistry, Faculty of Applied Sciences, Umm Al-Qura University, Makkah 21955, Saudi Arabia.ORCID 0000-0003-0437-4918

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Polymer colloids have remarkable features and are gaining importance in many areas of research including medicinal science. Presently, the innovation of cancer drugs is at the top in the world. Polymer colloids have been used as drug delivery and diagnosis agents in cancer treatment. The polymer colloids may be of different types such as micelles, liposomes, emulsions, cationic carriers, and hydrogels. The current article describes the state-of-the-art polymer colloids for the treatment of cancer. The contents of this article are about the role of polymeric nanomaterials with special emphasis on the different types of colloidal materials and their applications in targeted cancer therapy including cancer diagnoses. In addition, attempts are made to discuss future perspectives. This article will be useful for academics, researchers, and regulatory authorities.

Indexed as

cancer diagnosis and treatmentcolloidal polymeric nanomaterialsfuture perspectivespolymer colloids

Identifiers

PMID36559812
PMCPMC9788371

What OpenQuestion holds

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LicenceCC BY
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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.