Terahertz-based biosensors for biomedical applications: A review.

Methods

Department of Electrical and Computer Engineering at Georgia Tech Shenzhen Institute (GTSI), Shenzhen, Guangdong 518052, China; School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA. Electronic address:

Published: December 2024

AI Article Synopsis

  • Biosensors are crucial in life sciences applications, especially in healthcare, for areas like drug development, disease diagnosis, food safety, and environmental monitoring.
  • Terahertz (THz) spectroscopy offers a promising label-free and non-invasive method for detecting biomolecules with high sensitivity and speed, making it ideal for biomedical uses.
  • The review discusses techniques to enhance biosensor performance, compares existing biosensor technologies, and outlines challenges and future directions for THz-based biosensing.

Article Abstract

Biosensors have many life sciences-related applications, particularly in the healthcare sector. They are employed in a wide range of fields, including drug development, food quality management, early diagnosis of diseases, and environmental monitoring. Terahertz-based biosensing has shown great promise as a label-free, non-invasive, and non-contact method of detecting biological substances. THz Spectroscopy has achieved a remarkable advancement in biomolecule recognition providing a rapid, highly sensitive, and non-destructive approach for various biomedical applications. The significance of THz-based biosensors and the broad spectrum of biomolecules that can be detected and analyzed with biosensors are reviewed in this work. Additionally, this work summarizes several techniques that were previously reported to improve the sensitivity and selectivity of these biosensors. Furthermore, an in-depth comparison between previously developed biosensors with an emphasis on their performance is presented and highlighted in the current review. Lastly, the challenges, the potential, and the future prospects of THz-based biosensing technology are critically addressed.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ymeth.2024.12.001DOI Listing

Publication Analysis

Top Keywords

biomedical applications
8
biosensors
5
terahertz-based biosensors
4
biosensors biomedical
4
applications review
4
review biosensors
4
biosensors life
4
life sciences-related
4
sciences-related applications
4
applications healthcare
4

Similar Publications

Quantifying the regulatory potential of genetic variants via a hybrid sequence-oriented model with SVEN.

Nat Commun

December 2024

State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Biomedical Pioneering Innovative Center (BIOPIC) and Beijing Advanced Innovation Center for Genomics (ICG), Center for Bioinformatics (CBI), Peking University, 100871, Beijing, China.

Deciphering how noncoding DNA determines gene expression is critical for decoding the functional genome. Understanding the transcription effects of noncoding genetic variants are still major unsolved problems, which is critical for downstream applications in human genetics and precision medicine. Here, we integrate regulatory-specific neural networks and tissue-specific gradient-boosting trees to build SVEN: a hybrid sequence-oriented architecture that can accurately predict tissue-specific gene expression level and quantify the tissue-specific transcriptomic impacts of structural variants across more than 350 tissues and cell lines.

View Article and Find Full Text PDF

Small-scale continuum robots hold promise for interventional diagnosis and treatment, yet existing models struggle to achieve small size, precise steering, and visualized functional treatment simultaneously, termed an "impossible trinity". This study introduces an optical fiber-based continuum robot integrated imaging, high-precision motion, and multifunctional operation abilities at submillimeter-scale. With a slim profile of 0.

View Article and Find Full Text PDF

Bridged emulsion gels from polymer-nanoparticle enabling large-amount biomedical encapsulation and functionalization.

Nat Commun

December 2024

Key Laboratory of Materials Chemistry for Energy Conversion and Storage of Ministry of Education (HUST), School of Chemistry and Chemical Engineering, Huazhong University of Science and Technology (HUST), Wuhan, 430074, China.

Large-amount encapsulation and subsequent expressing are common characteristics for many biomedical applications, such as cosmetic creams and medical ointments. Emulsion gels can accomplish that, but often undergo exclusive, complex, multiple synthesis steps, showing extremely laborious and non-universal. The method here is simple via precisely interfacial engineering in homogenizing a nanoparticle aqueous dispersion and a polymer oil solution, gaining interfacial 45° three-phase-contact-angle for the nanoparticle that can bridge across oil emulsions' interfaces and ultimately form interconnected macroscopic networks.

View Article and Find Full Text PDF

Critical Role of Nanomaterial Mechanical Properties in Drug Delivery, Nanovaccines and Beyond.

Adv Mater

December 2024

School of Chemical Engineering, The University of Adelaide, North Terrace, South Australia, 5005, Australia.

Nanomaterials have become essential in the daily lives, finding applications in food, skincare, drugs, and vaccines. Traditionally, the surface chemistry of nanoparticles (NPs) is considered the key factor in determining their interactions with biological systems. However, recent studies have shown that the mechanical properties of nanomaterials are equally important in regulating nano-bio interactions, though they have often been overlooked.

View Article and Find Full Text PDF

Deep Learning-Based Ion Channel Kinetics Analysis for Automated Patch Clamp Recording.

Adv Sci (Weinh)

December 2024

Department of Biomedical Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong, Kowloon, Hong Kong SAR, China.

The patch clamp technique is a fundamental tool for investigating ion channel dynamics and electrophysiological properties. This study proposes the first artificial intelligence framework for characterizing multiple ion channel kinetics of whole-cell recordings. The framework integrates machine learning for anomaly detection and deep learning for multi-class classification.

View Article and Find Full Text PDF

Want 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!