Evidence map›Paper›PMID 34026742›Full record

ArticleFrontiers in bioengineering and biotechnology2021

Mussel Inspired Chemistry and Bacteria Derived Polymers for Oral Mucosal Adhesion and Drug Delivery.

Nazanin Owji, Nandin Mandakhbayar, David A Gregory, Elena Marcello, Hae-Won Kim, Ipsita Roy, Jonathan C Knowles

Open access · goldAbstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.0field-weighted citation impact, top 28% 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

10 citing papers in PubMed, 16 citations in OpenAlex.

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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

7 authors at 4 institutions in 2 countries.

Nazanin OwjiDivision of Biomaterials and Tissue Engineering, Royal Free Hospital, Eastman Dental Institute, University College London, London, United Kingdom.
Nandin MandakhbayarInstitute of Tissue Regeneration Engineering (ITREN), Dankook University, Cheonan, South Korea.
David A GregoryDepartment of Materials Science and Engineering, University of Sheffield, Sheffield, United Kingdom.
Elena MarcelloFaculty of Science and Technology, University of Westminster, London, United Kingdom.
Hae-Won KimInstitute of Tissue Regeneration Engineering (ITREN), Dankook University, Cheonan, South Korea.
Ipsita RoyDepartment of Materials Science and Engineering, University of Sheffield, Sheffield, United Kingdom.
Jonathan C KnowlesDivision of Biomaterials and Tissue Engineering, Royal Free Hospital, Eastman Dental Institute, University College London, London, United Kingdom.
University College London · GBUniversity of Sheffield · GBDankook University · KRUniversity of Westminster · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ulceration of the oral mucosa is common, can arise at any age and as a consequence of the pain lessens enjoyment and quality of life. Current treatment options often involve the use of topical corticosteroids with poor drug delivery systems and inadequate contact time. In order to achieve local controlled delivery to the lesion with optimal adhesion, we utilized a simple polydopamine chemistry technique inspired by mussels to replicate their adhesive functionality. This was coupled with production of a group of naturally produced polymers, known as polyhydroxyalkanoates (PHA) as the delivery system. Initial work focused on the synthesis of PHA using

Indexed as

biomimeticdrug deliveryoral mucosapolydopamine chemistrypolyhydroxyalkanoatessurface functionalization

Identifiers

PMID34026742
PMCPMC8133231
OpenAlexW3165519525

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.