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Recent Trends and Advances in Lab-on-a-Chip for Biosensing Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biosensors".

Deadline for manuscript submissions: closed (25 December 2023) | Viewed by 1273

Special Issue Editor

State Key Laboratory Breeding Base-Shenzhen Key Laboratory of Chemical Biology, Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China
Interests: microfluidics-based cell analysis; microdroplet reaction; MALDI imaging; LC-MS based metabolomics; proteomics

Special Issue Information

Dear Colleagues,

Cancer is one of the leading causes of death around the world. Tumor markers such as proteins, miRNAs, circulating tumor cells, or tumor-derived extracellular vesicles play an important role in early diagnosis and disease progression monitoring. Various methods have been reported for detecting single or multiplex tumor biomarkers. Microfluidics technology has shown a promising and powerful tool for biological detection due to its outstanding advantages, including its miniaturization, automation, portability, parallel analytical ability, minimal handling of hazardous materials, small reagent consumption, and point-of care diagnosis. Most importantly, all operation steps, including sample pre-treatment, reaction, and detection, can be integrated into one microfluidic platform for on-site test applications. To date, a large number of microfluidic platforms have been reported to combine with different kinds of technologies for tumor biomarker detection. We encourage the submission of original research articles and reviews that focus on the topic “Recent Trends and Advances in Lab-on-a-Chip for Biosensing Applications” related to tumor markers.

Dr. Dan Gao
Guest Editor

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.

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Published Papers (1 paper)

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Review

76 pages, 4474 KiB  
Review
Biosensor-Enhanced Organ-on-a-Chip Models for Investigating Glioblastoma Tumor Microenvironment Dynamics
by Gayathree Thenuwara, Bilal Javed, Baljit Singh and Furong Tian
Sensors 2024, 24(9), 2865; https://doi.org/10.3390/s24092865 - 30 Apr 2024
Viewed by 957
Abstract
Glioblastoma, an aggressive primary brain tumor, poses a significant challenge owing to its dynamic and intricate tumor microenvironment. This review investigates the innovative integration of biosensor-enhanced organ-on-a-chip (OOC) models as a novel strategy for an in-depth exploration of glioblastoma tumor microenvironment dynamics. In [...] Read more.
Glioblastoma, an aggressive primary brain tumor, poses a significant challenge owing to its dynamic and intricate tumor microenvironment. This review investigates the innovative integration of biosensor-enhanced organ-on-a-chip (OOC) models as a novel strategy for an in-depth exploration of glioblastoma tumor microenvironment dynamics. In recent years, the transformative approach of incorporating biosensors into OOC platforms has enabled real-time monitoring and analysis of cellular behaviors within a controlled microenvironment. Conventional in vitro and in vivo models exhibit inherent limitations in accurately replicating the complex nature of glioblastoma progression. This review addresses the existing research gap by pioneering the integration of biosensor-enhanced OOC models, providing a comprehensive platform for investigating glioblastoma tumor microenvironment dynamics. The applications of this combined approach in studying glioblastoma dynamics are critically scrutinized, emphasizing its potential to bridge the gap between simplistic models and the intricate in vivo conditions. Furthermore, the article discusses the implications of biosensor-enhanced OOC models in elucidating the dynamic features of the tumor microenvironment, encompassing cell migration, proliferation, and interactions. By furnishing real-time insights, these models significantly contribute to unraveling the complex biology of glioblastoma, thereby influencing the development of more accurate diagnostic and therapeutic strategies. Full article
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