Evidence map›Paper›PMID 32756393›Full record

ReviewBiosensors2020

The Current Trends of Biosensors in Tissue Engineering.

Yi-Chen Ethan Li, I-Chi Lee

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Biosensors, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

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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

2 authors.

Yi-Chen Ethan LiDepartment of Chemical Engineering, Feng Chia University, Taichung 40724, Taiwan.
I-Chi LeeDepartment of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu 300044, Taiwan.

Funding

Ministry of Science and Technology, Taiwan MOST 107-2314-B-035-001-MY2, MOST 109-2221-E-035 -007 -MY3, MOST 109-2221-E-035 -036 -MY3, and MOST 107-2314-B-182-017-MY
6 · The paper itself

Abstract

Biosensors constitute selective, sensitive, and rapid tools for disease diagnosis in tissue engineering applications. Compared to standard enzyme-linked immunosorbent assay (ELISA) analytical technology, biosensors provide a strategy to real-time and on-site monitor micro biophysiological signals via a combination of biological, chemical, and physical technologies. This review summarizes the recent and significant advances made in various biosensor technologies for different applications of biological and biomedical interest, especially on tissue engineering applications. Different fabrication techniques utilized for tissue engineering purposes, such as computer numeric control (CNC), photolithographic, casting, and 3D printing technologies are also discussed. Key developments in the cell/tissue-based biosensors, biomolecular sensing strategies, and the expansion of several biochip approaches such as organs-on-chips, paper based-biochips, and flexible biosensors are available. Cell polarity and cell behaviors such as proliferation, differentiation, stimulation response, and metabolism detection are included. Biosensors for diagnosing tissue disease modes such as brain, heart, lung, and liver systems and for bioimaging are discussed. Finally, we discuss the challenges faced by current biosensing techniques and highlight future prospects of biosensors for tissue engineering applications.

Indexed as

Biosensing TechniquesHumansMicrofluidic Analytical TechniquesTissue Engineeringbiosensorscell-based biosensorslabel-free biosensorsorgans-on-chipstissue engineeringtissue/organ-based biosensors

Identifiers

PMID32756393
PMCPMC7459738

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.