Microfluidic capture chips are useful for preparing or analyzing a wide range of different chemical, biological, and medical samples. A typical microfluidic capture chip contains features that capture certain targets (i.e. molecules, particles, cells) as they flow through the chip. However, creating optimal capture chip designs is difficult because of the inherent relationship between capture efficiency and flow resistance: as more capture features are added to the chip, the capture efficiency increases, but the additional features slow the flow of fluid through the chip. This paper introduces the use of multi-objective optimization to generate capture chip designs that balance the trade-off between maximizing target capture efficiency and minimizing resistance to fluid flow. Design automation for this important class of microfluidic chips has not been attempted previously. Our approach automatically produces a Pareto front of non-dominated chip designs in a reasonable amount of time, and most of these designs have comparable capture efficiency to hand-designed chips with far lower flow resistance. By choosing from the chip designs on the Pareto front, a user can obtain high capture efficiency without exceeding the flow resistance constraints of their application.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1109/TNB.2022.3212625 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Governance Considerations for Point-of-Care Ultrasound: a HIMSS-SIIM Enterprise Imaging Community Whitepaper in Collaboration with AIUM.
J Imaging Inform Med
January 2025
Independent Consultant, Kirkland, WA, USA.
Point-of-care ultrasound (POCUS) has emerged as a standard of care across a variety of healthcare settings due to its ability to provide critical clinical information and as well as procedural guidance to clinicians directly at the bedside. Implementation of enterprise imaging (EI) strategies is needed such that POCUS images can be appropriately captured, indexed, managed, stored, distributed, viewed, and analyzed. Because of its unique workflow and educational requirements, reliance on traditional order-based workflow solutions may be insufficient.
View Article and Find Full Text PDFDecoupled peak property learning for efficient and interpretable electronic circular dichroism spectrum prediction.
Nat Comput Sci
January 2025
AI for Science (AI4S)-Preferred Program, Peking University Shenzhen Graduate School, Shenzhen, China.
Electronic circular dichroism (ECD) spectra contain key information about molecular chirality by discriminating the absolute configurations of chiral molecules, which is crucial in asymmetric organic synthesis and the drug industry. However, existing predictive approaches lack the consideration of ECD spectra owing to the data scarcity and the limited interpretability to achieve trustworthy prediction. Here we establish a large-scale dataset for chiral molecular ECD spectra and propose ECDFormer for accurate and interpretable ECD spectrum prediction.
View Article and Find Full Text PDFIntegration of paper-based colorimetric microdevice and magnetic nanoparticles affinity for high-throughput capture of antimicrobial resistance-reversing agent from complex natural products.
Biosens Bioelectron
December 2024
Department of Pharmaceutical Analysis, School of Pharmacy, Key Laboratory of Protection, Development and Utilization of Medicinal Resources in Liupanshan Area, Ministry of Education, Ningxia Medical University, Yinchuan, 750004, China. Electronic address:
Efficient analysis of active ingredient in complex natural products is crucial for drug discovery, but developing a simple method for this is challenging. The discovery of drugs against bacterial resistance is urgent because drug-resistant bacteria produce β-lactamases, which inactivate antibiotics and increase infection risks, particularly the AmpC β-lactamase. Here, an integrated analytical model based on colorimetric sensing and magnetic nanoparticles (MNPs) affinity chromatography was developed for screening AmpC β-lactamase inhibitors.
View Article and Find Full Text PDFCombining the Variational and Deep Learning Techniques for Classification of Video Capsule Endoscopic Images.
J Imaging Inform Med
January 2025
Gastroenterology Department of Gandhi Medical College, Bhopal, 462003, India.
Gastrointestinal tract-related cancers pose a significant health burden, with high mortality rates. In order to detect the anomalies of the gastrointestinal tract that may progress to cancer, a video capsule endoscopy procedure is employed. The number of video capsule endoscopic ( ) images produced per examination is enormous, which necessitates hours of analysis by clinicians.
View Article and Find Full Text PDFTopological analysis and predictive modeling of amino acid structures with implications for bioinformatics and structural biology.
Sci Rep
January 2025
Department of Mathematics, College of Natural and Computational Sciences, Wollega University, Nekemte, Ethiopia.
Amino acids, as the fundamental constituents of proteins and enzymes, play a vital role in various biological processes. Amino acids such as histidine, cysteine, and methionine are known to coordinate with metal ions in proteins and enzymes, playing critical roles in their structure and function. In metalloproteins, metal ions are often coordinated by specific amino acid residues, contributing to the protein's stability and catalytic activity.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!