Evidence map›Paper›PMID 38002041›Full record

ArticleBiomedicines2023

Metalloproteinases in Restorative Dentistry: An In Silico Study toward an Ideal Animal Model.

Simone Gomes de Oliveira, Nelson Kotowski, Helio Rodrigues Sampaio-Filho, Flávio Henrique Baggio Aguiar, Alberto Martín Rivera Dávila, Rodrigo Jardim

Open access · goldAbstract read
In one paragraph

Article in Biomedicines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 82% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

6 authors at 3 institutions in 1 country.

Simone Gomes de OliveiraPiracicaba School of Dentistry, Campinas State University, Piracicaba 13414-903, SP, Brazil.
Nelson KotowskiComputational and Systems Biology Laboratory, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro 21040-900, RJ, Brazil.
Helio Rodrigues Sampaio-FilhoSchool of Dentistry, State University of Rio de Janeiro, Rio de Janeiro 20551-030, RJ, Brazil.
Flávio Henrique Baggio AguiarPiracicaba School of Dentistry, Campinas State University, Piracicaba 13414-903, SP, Brazil.
Alberto Martín Rivera DávilaComputational and Systems Biology Laboratory, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro 21040-900, RJ, Brazil.
Rodrigo JardimComputational and Systems Biology Laboratory, Oswaldo Cruz Institute, Oswaldo Cruz Foundation, Rio de Janeiro 21040-900, RJ, Brazil.ORCID 0000-0002-0943-5356
Fundação Oswaldo Cruz · BRUniversidade Estadual de Campinas (UNICAMP) · BRUniversidade do Estado do Rio de Janeiro · BR

Funding

São Paulo Research Foundation 2019/20576-0
6 · The paper itself

Abstract

In dentistry, various animal models are used to evaluate adhesive systems, dental caries and periodontal diseases. Metalloproteinases (MMPs) are enzymes that degrade collagen in the dentin matrix and are categorized in over 20 different classes. Collagenases and gelatinases are intrinsic constituents of the human dentin organic matrix fibrillar network and are the most abundant MMPs in this tissue. Understanding such enzymes' action on dentin is important in the development of approaches that could reduce dentin degradation and provide restorative procedures with extended longevity. This in silico study is based on dentistry's most used animal models and intends to search for the most suitable, evolutionarily close to

Indexed as

animal modelphylogenyrestorative dentistry

Identifiers

PMID38002041
PMCPMC10669239
OpenAlexW4388659817

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.