Evidence map›Paper›PMID 24256302›Full record

ArticleTissue engineering. Part C, Methods2014

Rapid assessment of migration and proliferation: a novel 3D high-throughput platform for rational and combinatorial screening of tissue-specific biomaterials.

Courtney M Dumont, Pankaj Karande, Deanna M Thompson

Open access · greenAbstract read
In one paragraph

Article in Tissue engineering. Part C, Methods, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 39% 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

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
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 at 1 institution in 1 country.

Courtney M Dumont1 Department of Biomedical Engineering, Rensselaer Polytechnic Institute , Troy, New York.
Pankaj Karande
Deanna M Thompson
Rensselaer Polytechnic Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Designing an ideal biomaterial supportive of multicellular tissue repair is challenging, especially with a poor understanding of the synergy between constituent proteins and growth factors. A brute-force approach, based on screening all possible combinations of proteins and growth factors, is inadequate due to the prohibitively large experimental space coupled with current low-throughput screening techniques. A high-throughput screening platform based on rational and combinatorial strategies for design and testing of proteins and growth factors can significantly impact the discovery of novel tissue-specific biomaterials. Here, we report the development of a flexible high-throughput screening platform, Rapid Assessment of Migration and Proliferation (RAMP), to rapidly investigate cell viability, proliferation, and migration in response to highly miniaturized three-dimensional biomaterial cultures (4-20 μL) with sparingly low cell densities (63-1000 cells per μL for cell arrays; 1 μL of 1000-10,000 cells per μL for migration arrays). The predictions made by RAMP on the efficacy and potency of the biomaterials are in agreement with the predictions made by conventional assays but at a throughput that is at least 100-1000-fold higher. The RAMP assay is therefore a novel approach for the rapid discovery of tissue-specific biomaterials for tissue engineering and regenerative medicine.

Indexed as

Cell MovementCell ProliferationAnimalsBiocompatible MaterialsCell SurvivalMaterials TestingRatsRats, Sprague-DawleySchwann CellsBiocompatible Materials

Identifiers

PMID24256302
PMCPMC4115783
OpenAlexW2233998637

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.