Evidence map›Paper›PMID 38203891›Full record

ArticleMaterials (Basel, Switzerland)2023

Highly Reinforced Acrylic Resins for Hard Tissue Engineering and Their Suitability to Be Additively Manufactured through Nozzle-Based Photo-Printing.

Vito Gallicchio, Vincenzo Spinelli, Teresa Russo, Ciro Marino, Gianrico Spagnuolo, Carlo Rengo, Roberto De Santis

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Materials (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Vito GallicchioDepartment of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples Federico II, Via S. Pansini 5, 80131 Naples, Italy.ORCID 0000-0003-4746-7735
Vincenzo SpinelliDepartment of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples Federico II, Via S. Pansini 5, 80131 Naples, Italy.
Teresa RussoInstitute of Polymers, Composites and Biomaterials, National Research Council of Italy, V.le J.F. Kennedy 54, Mostra d'Oltremare Pad. 20, 80125 Naples, Italy.
Ciro MarinoUniversity of Naples Federico II, P.le Tecchio 80, 80125 Naples, Italy.
Gianrico SpagnuoloDepartment of Neurosciences, Reproductive and Odontostomatological Sciences, University of Naples Federico II, Via S. Pansini 5, 80131 Naples, Italy.ORCID 0000-0003-3769-9786
Carlo RengoDepartment of Prosthodontics and Dental Materials, University of Siena, 53100 Siena, Italy.ORCID 0000-0003-1127-0877
Roberto De SantisInstitute of Polymers, Composites and Biomaterials, National Research Council of Italy, V.le J.F. Kennedy 54, Mostra d'Oltremare Pad. 20, 80125 Naples, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mineralized connective tissues represent the hardest materials of human tissues, and polymer based composite materials are widely used to restore damaged tissues. In particular, light activated resins and composites are generally considered as the most popular choice in the restorative dental practice. The first purpose of this study is to investigate novel highly reinforced light activated particulate dental composites. An innovative additive manufacturing technique, based on the extrusion of particle reinforced photo-polymers, has been recently developed for processing composites with a filler fraction (

Indexed as

additive manufacturinglight activated compositesmechanical analysisparticulate composites

Identifiers

PMID38203891
PMCPMC10779947

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.