Evidence map›Paper›PMID 39744316›Full record

Article3D printing and additive manufacturing2024

Design Optimization of a 3D Microfluidic Channel System for Biomedical Applications.

Radita Tyas Atsani Susanto, Brijesh Patel, Yu-Sheng Hsiao, Hsiu-Yang Tseng, Po Ting Lin

Abstract read
In one paragraph

Article in 3D printing and additive manufacturing, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Radita Tyas Atsani SusantoDepartment of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan.
Brijesh PatelDepartment of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan.
Yu-Sheng HsiaoDepartment of Materials Science and Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan.
Hsiu-Yang TsengDepartment of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan.
Po Ting LinDepartment of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan.ORCID https://orcid.org/0000-0001-5907-7828

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microfluidic channel systems can be used for various biomedical applications, including drug administration, wound healing, cell culture research, and many others. A 3D microfluidic channel system has enormous potential over conventional microfluidic channel systems, including the capacity to simulate biological events in a laboratory setting. This system has the ability to recreate biological phenomena such as concentration gradient generators (CGGs). Microfluidic CGGs have complex fabrication when built into a 3D channel system. These complex systems can be built with complicated processes such as plasma bonding, which requires expensive setup and fine equipment. Therefore, in this study, a smart additive manufacturing technique is applied for an enormous review of the design and fabrication process, which is optimized for different operating conditions. This study employs a 3D printed removable channel mold to avoid the complex fabrication technique of microfluidic channels, allowing the direct casting of polydimethylsiloxane without extra bonding stages. The proposed design comprises dual mixing stages, incorporating a 3D mixer configuration and a converging output to attain the desired gradient outcome. Optimization is performed to achieve the best operating conditions by using response surface methodology, with channel dimension

Indexed as

concentration gradient generationmicrofluidic channel systemoptimizationresponse surface methodology

Identifiers

PMID39744316
PMCPMC11685786

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.