Evidence map›Paper›PMID 18006108›Full record

ReviewAdvanced drug delivery reviews2008

Controlled differentiation of stem cells.

Nathaniel S Hwang, Shyni Varghese, Jennifer Elisseeff

Abstract readReview
In one paragraph

Review in Advanced drug delivery reviews, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 102 papers.

0numbers the graph read from it
0cells of the map it votes in
102citing 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

102 citing papers in PubMed.

  1. Review
  2. Noninvasive andThe Analyst · 2025
    Article
  3. Review
  4. Review
  5. Review
  6. Review
  7. Article
  8. Review
  9. Stem Cell Therapy for the Management of Type 1 Diabetes: Advances and Perspectives.Endocrine, metabolic & immune disorders drug targets · 2024
    Review
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Review
  18. Review
  19. Article
  20. Review

42 more citing papers are in PubMed but not listed here.

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

3 authors.

Nathaniel S HwangDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
Shyni Varghese
Jennifer Elisseeff

Funding

Tissue Engineering in Congenital Craniofacial DefectsR01DE016887 · NIDCR · JOHNS HOPKINS UNIVERSITY · PI ELISSEEFF, JENNIFER H · 2006 to 2009
$1.4M
Engineering and Integration of Osteochondral TissueR01EB005517 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI ELISSEEFF, JENNIFER H · 2005 to 2008
$1.1M
NIBIB NIH HHS R01 EB005517NIDCR NIH HHS R01 DE016887
6 · The paper itself

Abstract

The extracellular microenvironment plays a significant role in controlling cellular behavior. Identification of appropriate biomaterials that support cellular attachment, proliferation and, most importantly in the case of human embryonic stem cells, lineage-specific differentiation is critical for tissue engineering and cellular therapy. In addition to growth factors and morphogenetic factors known to induce lineage commitment of stem cells, a number of scaffolding materials, including synthetic and naturally-derived biomaterials, have been utilized in tissue engineering approaches to direct differentiation. This review focuses on recent emerging findings and well-characterized differentiation models of human embryonic stem cells. Additionally, we also discuss about various strategies that have been used in stem cell expansion.

Indexed as

Biocompatible MaterialsCell Culture TechniquesCell DifferentiationEmbryonic Stem CellsHumansIntercellular Signaling Peptides and ProteinsTissue EngineeringTissue ScaffoldsBiocompatible MaterialsIntercellular Signaling Peptides and Proteins

Identifiers

PMID18006108
PMCPMC2712932

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.