Evidence map›Paper›PMID 25587413›Full record

ReviewBiosensors2014

Recent advances in bioprinting and applications for biosensing.

Andrew D Dias, David M Kingsley, David T Corr

Abstract readReview
In one paragraph

Review in Biosensors, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Review
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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.

Andrew D DiasDepartment of Biomedical Engineering, Rensselaer Polytechnic Institute, 110 Eighth St., Troy, NY 12180, USA; E-Mails: diasa@rpi.edu (A.D.D.); kingsd@rpi.edu (D.M.K.).
David M KingsleyDepartment of Biomedical Engineering, Rensselaer Polytechnic Institute, 110 Eighth St., Troy, NY 12180, USA; E-Mails: diasa@rpi.edu (A.D.D.); kingsd@rpi.edu (D.M.K.).
David T CorrDepartment of Biomedical Engineering, Rensselaer Polytechnic Institute, 110 Eighth St., Troy, NY 12180, USA; E-Mails: diasa@rpi.edu (A.D.D.); kingsd@rpi.edu (D.M.K.).

Funding

2016 SETAC Asia/Pacific ConferenceR13ES027302 · NIEHS · SOCIETY/ENVIRONMENTAL TOXICOLOGY/CHEM · PI MENZIE, CHARLES · 2016 to 2016
$6k
NIEHS NIH HHS 27302C0028
6 · The paper itself

Abstract

Future biosensing applications will require high performance, including real-time monitoring of physiological events, incorporation of biosensors into feedback-based devices, detection of toxins, and advanced diagnostics. Such functionality will necessitate biosensors with increased sensitivity, specificity, and throughput, as well as the ability to simultaneously detect multiple analytes. While these demands have yet to be fully realized, recent advances in biofabrication may allow sensors to achieve the high spatial sensitivity required, and bring us closer to achieving devices with these capabilities. To this end, we review recent advances in biofabrication techniques that may enable cutting-edge biosensors. In particular, we focus on bioprinting techniques (e.g., microcontact printing, inkjet printing, and laser direct-write) that may prove pivotal to biosensor fabrication and scaling. Recent biosensors have employed these fabrication techniques with success, and further development may enable higher performance, including multiplexing multiple analytes or cell types within a single biosensor. We also review recent advances in 3D bioprinting, and explore their potential to create biosensors with live cells encapsulated in 3D microenvironments. Such advances in biofabrication will expand biosensor utility and availability, with impact realized in many interdisciplinary fields, as well as in the clinic.

Indexed as

biofabricationbioprintingimmobilizationpatterningthroughput

Identifiers

PMID25587413
PMCPMC4264374

What Socratic 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 Socratic graph.