Evidence map›Paper›PMID 24991941›Full record

ReviewSensors (Basel, Switzerland)2014

Cell patterning for liver tissue engineering via dielectrophoretic mechanisms.

Wan Nurlina Wan Yahya, Nahrizul Adib Kadri, Fatimah Ibrahim

Open access · goldAbstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

8 citing papers in PubMed, 21 citations in OpenAlex.

  1. Review
  2. Biophysical control of plasticity and patterning in regeneration and cancer.Cellular and molecular life sciences : CMLS · 2023
    Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Living Cell Microarrays: An Overview of Concepts.Microarrays (Basel, Switzerland) · 2016
    Review
  8. 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.

Wan Nurlina Wan YahyaDepartment of Biomedical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia. wnurlina2@siswa.um.edu.my.
Nahrizul Adib KadriDepartment of Biomedical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia. nahrizuladib@um.edu.my.
Fatimah IbrahimDepartment of Biomedical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia. fatimah@um.edu.my.
University of Malaya · MY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Liver transplantation is the most common treatment for patients with end-stage liver failure. However, liver transplantation is greatly limited by a shortage of donors. Liver tissue engineering may offer an alternative by providing an implantable engineered liver. Currently, diverse types of engineering approaches for in vitro liver cell culture are available, including scaffold-based methods, microfluidic platforms, and micropatterning techniques. Active cell patterning via dielectrophoretic (DEP) force showed some advantages over other methods, including high speed, ease of handling, high precision and being label-free. This article summarizes liver function and regenerative mechanisms for better understanding in developing engineered liver. We then review recent advances in liver tissue engineering techniques and focus on DEP-based cell patterning, including microelectrode design and patterning configuration.

Indexed as

Liver, ArtificialAnimalsCell SeparationElectrophoresisHepatocytesHumansLiverLiver RegenerationMicromanipulationTissue Engineering

Identifiers

PMID24991941
PMCPMC4168452
OpenAlexW2089727560

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.