Evidence map›Paper›PMID 25665851›Full record

ArticleJournal of materials science. Materials in medicine2015

Hierarchical polymeric scaffolds support the growth of MC3T3-E1 cells.

Rosa Akbarzadeh, Joshua A Minton, Cara S Janney, Tyler A Smith, Paul F James, Azizeh-Mitra Yousefi

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of materials science. Materials in medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
3.1field-weighted citation impact, top 9% 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

9 citing papers in PubMed, 34 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. 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

6 authors at 1 institution in 1 country.

Rosa AkbarzadehDepartment of Chemical, Paper and Biomedical Engineering, Miami University, 650 E High Street, Oxford, OH, 45056, USA.
Joshua A Minton
Cara S Janney
Tyler A Smith
Paul F James
Azizeh-Mitra Yousefi
Miami University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tissue engineering makes use of the principles of biology and engineering to sustain 3D cell growth and promote tissue repair and/or regeneration. In this study, macro/microporous scaffold architectures have been developed using a hybrid solid freeform fabrication/thermally induced phase separation (TIPS) technique. Poly(lactic-co-glycolic acid) (PLGA) dissolved in 1,4-dioxane was used to generate a microporous matrix by the TIPS method. The 3D-bioplotting technique was used to fabricate 3D macroporous constructs made of polyethylene glycol (PEG). Embedding the PEG constructs inside the PLGA solution prior to the TIPS process and subsequent extraction of PEG following solvent removal (1,4-dioaxane) resulted in a macro/microporous structure. These hierarchical scaffolds with a bimodal pore size distribution (<50 and >300 μm) contained orthogonally interconnected macro-channels generated by the extracted PEG. The diameter of the macro-channels was varied by tuning the dispensing parameters of the 3D bioplotter. The in vitro cell culture using murine MC3T3-E1 cell line for 21 days demonstrated that these scaffolds could provide a favorable environment to support cell adhesion and growth.

Indexed as

Tissue Scaffolds3T3 CellsAnimalsCell AdhesionCell ProliferationCells, CulturedCell SurvivalLactic AcidMaterials TestingMicePolyglycolic AcidPolylactic Acid-Polyglycolic Acid CopolymerPorosityTissue EngineeringLactic AcidPolyglycolic AcidPolylactic Acid-Polyglycolic Acid Copolymer

Identifiers

PMID25665851
OpenAlexW2023712178

What OpenQuestion holds

Textmetadata
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.