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Micromachines
Special Issues
Recent Advances in Lab-on-a-Chip and Their Biomedical Applications
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Recent Advances in Lab-on-a-Chip and Their Biomedical Applications

A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "B：Biology and Biomedicine".

Deadline for manuscript submissions: 30 October 2024 | Viewed by 2329

Special Issue Editors

Prof. Dr. Guoqing Hu

E-Mail Website
Guest Editor
Department of Engineering Mechanics, Zhejiang University, Hangzhou 310027, China
Interests: microfluidics/manofluidics; lab on a chip; nanotoxicology; numercial simulations
Dr. Xiaoyan Liu

E-Mail Website
Guest Editor
Institute for Health Innovation & Technology (iHealthtech), National University of Singapore, Singapore 117599, Singapore
Interests: organ on a chip; drug screening; cell mechanobiology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleague,

This Special Issue, "Recent Advances in Lab-on-a-Chip and Their Biomedical Applications", serves as a platform to showcase the latest breakthroughs and innovations in the field of lab-on-a-chip (LOC) technology and its diverse applications in biomedicine. Lab-on-a-chip platforms have revolutionized medical diagnostics, drug discovery, and biomedical research by providing miniaturized, integrated systems that offer high precision and efficiency.

This Special Issue seeks to gather research papers and review articles focusing on the current state of LOC technology, from the development of microfluidic devices to their biomedical applications. It welcomes contributions from researchers and experts across various disciplines who are exploring the integration of LOC systems into medical diagnostics, point-of-care testing, and drug development. It also encompasses a wide range of topics, including microfabrication techniques, bioanalytical methods, biomarker detection, single-cell analysis, and the miniaturization of laboratory processes, and highlights the translation of LOC technologies into clinical practice and their role in improving patient care and outcomes.

By fostering collaboration and knowledge exchange among scientists, engineers, and healthcare professionals, this Special Issue aims to accelerate the adoption of lab-on-a-chip platforms in biomedicine. We invite submissions that reflect the latest advancements and innovative applications contributing to the ongoing transformation of healthcare and the advancement of biomedical research.

We look forward to receiving your submissions.

Prof. Dr. Guoqing Hu
Dr. Xiaoyan Liu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Micromachines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • lab on a chip
  • organ on a chip
  • microfluidics
  • biomedical applications
  • drug screening
  • high-throughput analysis
  • point-of-care diagnostics
  • lab-on-a-chip devices
  • microfluidic separation
  • disease diagnosis
  • biochips
  • micrototal analysis systems (μTASs)

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Published Papers (2 papers)

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27 pages, 21312 KiB  
Article
YOLO-PBESW: A Lightweight Deep Learning Model for the Efficient Identification of Indomethacin Crystal Morphologies in Microfluidic Droplets
by Jiehan Wei, Jianye Liang, Jun Song and Peipei Zhou
Micromachines 2024, 15(9), 1136; https://doi.org/10.3390/mi15091136 - 6 Sep 2024
Viewed by 618
Abstract
Crystallization is important to the pharmaceutical, the chemical, and the materials fields, where the morphology of crystals is one of the key factors affecting the quality of crystallization. High-throughput screening based on microfluidic droplets is a potent technique to accelerate the discovery and [...] Read more.
Crystallization is important to the pharmaceutical, the chemical, and the materials fields, where the morphology of crystals is one of the key factors affecting the quality of crystallization. High-throughput screening based on microfluidic droplets is a potent technique to accelerate the discovery and development of new crystal morphologies with active pharmaceutical ingredients. However, massive crystal morphologies’ datum needs to be identified completely and accurately, which is time-consuming and labor-intensive. Therefore, effective morphologies’ detection and small-target tracking are essential for high-efficiency experiments. In this paper, a new improved algorithm YOLOv8 (YOLO-PBESW) for detecting indomethacin crystals with different morphologies is proposed. We enhanced its capability in detecting small targets through the integration of a high-resolution feature layer P2, and the adoption of a BiFPN structure. Additionally, in this paper, adding the EMA mechanism before the P2 detection head was implemented to improve network attention towards global features. Furthermore, we utilized SimSPPF to replace SPPF to mitigate computational costs and reduce inference time. Lastly, the CIoU loss function was substituted with WIoUv3 to improve detection performance. The experimental findings indicate that the enhanced YOLOv8 model attained advancements, achieving AP metrics of 93.3%, 77.6%, 80.2%, and 99.5% for crystal wire, crystal rod, crystal sheet, and jelly-like phases, respectively. The model also achieved a precision of 85.2%, a recall of 83.8%, and an F1 score of 84.5%, with a mAP of 87.6%. In terms of computational efficiency, the model’s dimensions and operational efficiency are reported as 5.46 MB, and it took 12.89 ms to process each image with a speed of 77.52 FPS. Compared with state-of-the-art lightweight small object detection models such as the FFCA-YOLO series, our proposed YOLO-PBESW model achieved improvements in detecting indomethacin crystal morphologies, particularly for crystal sheets and crystal rods. The model demonstrated AP values that exceeded L-FFCA-YOLO by 7.4% for crystal sheets and 3.9% for crystal rods, while also delivering a superior F1-score. Furthermore, YOLO-PBESW maintained a lower computational complexity, with parameters of only 11.8 GFLOPs and 2.65 M, and achieved a higher FPS. These outcomes collectively demonstrate that our method achieved a balance between precision and computational speed. Full article
(This article belongs to the Special Issue Recent Advances in Lab-on-a-Chip and Their Biomedical Applications)
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12 pages, 10693 KiB  
Article
Capillary Force-Driven Quantitative Plasma Separation Method for Application of Whole Blood Detection Microfluidic Chip
by Xiaohua Fang, Cuimin Sun, Peng Dai, Zhaokun Xian, Wenyun Su, Chaowen Zheng, Dong Xing, Xiaotian Xu and Hui You
Micromachines 2024, 15(5), 619; https://doi.org/10.3390/mi15050619 - 1 May 2024
Viewed by 1272
Abstract
Separating plasma or serum from blood is essential for precise testing. However, extracting precise plasma quantities outside the laboratory poses challenges. A recent study has introduced a capillary force-driven membrane filtration technique to accurately separate small plasma volumes. This method efficiently isolates 100–200 [...] Read more.
Separating plasma or serum from blood is essential for precise testing. However, extracting precise plasma quantities outside the laboratory poses challenges. A recent study has introduced a capillary force-driven membrane filtration technique to accurately separate small plasma volumes. This method efficiently isolates 100–200 μL of pure human whole blood with a 48% hematocrit, resulting in 5–30 μL of plasma with less than a 10% margin of error. The entire process is completed within 20 min, offering a simple and cost-effective approach to blood separation. This study has successfully addressed the bottleneck in self-service POCT, ensuring testing accuracy. This innovative method shows promise for clinical diagnostics and point-of-care testing. Full article
(This article belongs to the Special Issue Recent Advances in Lab-on-a-Chip and Their Biomedical Applications)
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