Evidence map›Paper›PMID 38647880›Full record

ArticleBioresources and bioprocessing2022

A modular 3D printed microfluidic system: a potential solution for continuous cell harvesting in large-scale bioprocessing.

Lin Ding, Sajad Razavi Bazaz, Mahsa Asadniaye Fardjahromi, Flyn McKinnirey, Brian Saputro, Balarka Banerjee, Graham Vesey, Majid Ebrahimi Warkiani

Abstract read
In one paragraph

Article in Bioresources and bioprocessing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Biomicrofluidics · 2024
    Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Review
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

8 authors.

Lin Ding *School of Biomedical Engineering, University of Technology Sydney, Sydney, NSW, 2007, Australia.
Sajad Razavi Bazaz *School of Biomedical Engineering, University of Technology Sydney, Sydney, NSW, 2007, Australia.
Mahsa Asadniaye Fardjahromi *School of Biomedical Engineering, University of Technology Sydney, Sydney, NSW, 2007, Australia.
Flyn McKinnireyRegeneus Ltd, Paddington, Sydney, NSW, 2021, Australia.
Brian SaputroRegeneus Ltd, Paddington, Sydney, NSW, 2021, Australia.
Balarka BanerjeeRegeneus Ltd, Paddington, Sydney, NSW, 2021, Australia.
Graham VeseyRegeneus Ltd, Paddington, Sydney, NSW, 2021, Australia.
Majid Ebrahimi WarkianiSchool of Biomedical Engineering, University of Technology Sydney, Sydney, NSW, 2007, Australia. majid.warkiani@uts.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microfluidic devices have shown promising applications in the bioprocessing industry. However, the lack of modularity and high cost of testing and error limit their implementation in the industry. Advances in 3D printing technologies have facilitated the conversion of microfluidic devices from research output to applicable industrial systems. Here, for the first time, we presented a 3D printed modular microfluidic system consisting of two micromixers, one spiral microfluidic separator, and one microfluidic concentrator. We showed that this system can detach and separate mesenchymal stem cells (MSCs) from microcarriers (MCs) in a short time while maintaining the cell's viability and functionality. The system can be multiplexed and scaled up to process large volumes of the industry. Importantly, this system is a closed system with no human intervention and is promising for current good manufacturing practices.

Indexed as

3D printingBioprocessingMesenchymal stem cellsMicrofluidicsModular microfluidic system

Identifiers

PMID38647880
PMCPMC10991575

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.