Evidence map›Paper›PMID 26586955›Full record

ReviewStem cells and cloning : advances and applications2015

From bench to bedside: use of human adipose-derived stem cells.

Vaughan Feisst, Sarah Meidinger, Michelle B Locke

Abstract readReview
In one paragraph

Review in Stem cells and cloning : advances and applications, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.

0numbers the graph read from it
0cells of the map it votes in
55citing 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

55 citing papers in PubMed.

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  8. Improvement of endometrial thickness andAmerican journal of translational research · 2024
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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

3 authors.

Vaughan FeisstDunbar Laboratory, School of Biological Sciences, The University of Auckland, Auckland, New Zealand.
Sarah MeidingerDunbar Laboratory, School of Biological Sciences, The University of Auckland, Auckland, New Zealand.
Michelle B LockeDepartment of Surgery, Faculty of Medicine and Health Sciences, The University of Auckland, Auckland, New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since the discovery of adipose-derived stem cells (ASC) in human adipose tissue nearly 15 years ago, significant advances have been made in progressing this promising cell therapy tool from the laboratory bench to bedside usage. Standardization of nomenclature around the different cell types used is finally being adopted, which facilitates comparison of results between research groups. In vitro studies have assessed the ability of ASC to undergo mesenchymal differentiation as well as differentiation along alternate lineages (transdifferentiation). Recently, focus has shifted to the immune modulatory and paracrine effects of transplanted ASC, with growing interest in the ASC secretome as a source of clinical effect. Bedside use of ASC is advancing alongside basic research. An increasing number of safety-focused Phase I and Phase IIb trials have been published without identifying any significant risks or adverse events in the short term. Phase III trials to assess efficacy are currently underway. In many countries, regulatory frameworks are being developed to monitor their use and assure their safety. As many trials rely on ASC injected at a distant site from the area of clinical need, strategies to improve the homing and efficacy of transplanted cells are also being explored. This review highlights each of these aspects of the bench-to-bedside use of ASC and summarizes their clinical utility across a variety of medical specialties.

Indexed as

bystander effectmesenchymal stem cellsstandardizationstromal cellsstromal vascular fraction

Identifiers

PMID26586955
PMCPMC4636091

What OpenQuestion holds

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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.